In recent decades, large-scale forest disturbances such as windthrow and bark beetle infestations have significantly impacted the carbon balance of Earth and forest ecosystems, mainly by altering soil respiration (SR) in addition to decreased gross primary productivity. SR is considered the second highest flux on Earth, emitting 78-98 Gt C yr-1 to the atmosphere, thus contributing to global warming. Post-disturbance development is marked by changes in the size of SR. To investigate the impact of bark beetle (Ips typographus) infestations in mountain spruce forests on SR, we measured SR at infested sites by bark beetles and adjacent undisturbed stands in the High Tatra Mountains (Slovakia). The measurements were conducted during the vegetation period (May-September) in 2016 and 2017, five to six years after the initial attack by bark beetles, at an altitudinal gradient (1100-1400 m a.s.l.). SR varied throughout different months and altitudes, and we observed that SR at infested sites reached higher values (in most cases) than at uninfested stands. Average monthly and altitude SR rates during both vegetation periods showed higher values at infested sites, but not all of them were statistically significant. We observed an insignificant change in SR rate between 2016 and 2017 at both infested and uninfested sites. The highest rates of SR were observed in 2016 from July to August at both infested and undisturbed sites. On the other hand, in 2017 the highest SR rates were observed in June and July at undisturbed sites and from June to August at infested sites. However, yearly SR from May-September at infested sites showed significantly higher rates than uninfested ones in both years. SR showed a decreasing pattern with elevation gain in 2016 at infested sites. However, this pattern was not observed in 2017. Based on our observation and results we postulate that SR rates at infested sites are boosted by needle fall and debris from dead and dying trees, which increases heterotrophic SR and compensates the decrease of autotrophic SR from tree roots. This study provides important insights into the impact of bark beetle infestations on SR and highlights the need for further research on the long-term effects of forest disturbances on carbon cycling.

Background: Traumatic events adversely affect the clinical course of obsessive-compulsive disorder (OCD). Our investigation explores the correlation between prolonged interpersonal trauma and the severity of symptoms related to obsessive-compulsive and anxiety disorders. Methods: The study follows a cross-sectional and observational design, employing the International Trauma Questionnaire (ITQ) to examine areas linked to interpersonal trauma, the Hamilton Anxiety Rating Scale (HAM-A), and the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) to assess anxious and obsessive-compulsive symptoms, respectively. Descriptive analysis, analysis of variance (ANOVA), and logistic regression analyses were conducted. Results: We recruited 107 OCD-diagnosed patients, categorizing them into subgroups based on the presence or absence of complex post-traumatic stress disorder (cPTSD). The ANOVA revealed statistically significant differences between the two groups in the onset age of OCD (p=0.083), psychiatric familial history (p=0.023), HAM-A, and Y-BOCS (p=0.000). Logistic regression indicated a statistically significant association between the presence of cPTSD and Y-BOCS scores (p=0.000). Conclusion: The coexistence of cPTSD in OCD exacerbates obsessive-compulsive symptoms and increases the burden of anxiety. Further advancements in this field are crucial for mitigating the impact of early trauma on the trajectory of OCD and associated anxious symptoms.

In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

OBJECTIVE: Analyzing the effects of different physical exercise programs on the anthropometric, cardiovascular, metabolic, and strength variables of the elderly participating in health care programs. METHODS: Controlled clinical trial, with 60 elderly participants from health care groups, allocated into four groups: Group of resistance exercises in open-air gyms – GT1 (n = 17); Group of aerobic and localized exercises - GT2 (n = 11); Group of resistance exercises at GT3 gym (n = 17); Control group: non-exercise practitioners - CG (n = 15). Anthropometric (BMI, % body fat, and waist circumference), cardiovascular (SBP, DBP, HR, and DP), metabolic (total cholesterol, triglycerides, and glycemia), and strength variables were evaluated before and after 16 weeks of intervention. Descriptive statistics, Shapiro-Wilk and Kolmogorov-Smirnov normality test, equal variance test, T-Student test, non-parametric Mann-Witney test, ANOVA One Way, multivariate data analysis using data mining and machine learning techniques, Pearson and Spearman correlation tests, Classical Clustering (Agglomerative Hierarchical Method); Principal Component Analysis (PCA), Z score, Fruchterman-Reingold algorithm, Euclidian Similarity Index and, Cohen’s equations were applied. RESULTS: To observe effect size, morphofunctional variables for the GT1 group show a small effect for fat percentage, WHR, and ULS and a medium effect for LLS. For the GT2 group, there was a small effect for fat percentage, WHR, and ULS and a large effect for LLS. For the GT3 group, there was a small effect for the percentage of fat and HC, a medium effect for ULS, and a large effect for LLS. A small effect for glycemia in GT1, a medium effect for glycemia and triglycerides for GT2, a small effect for total cholesterol for GT3, and a large effect for glycemia in CG, with this effect being an increase in this analyte. For the cardiovascular variables, there is a small effect for SBP and HR in GT1, a small effect for DBP, HR, and DP, and a large effect for SBP in GT2, a small effect for SBP, DBP, and HR in GT3 and small effects for SBP and HR in CG. The correlation between BMI (P = 0.0007) and Body Fat% (P = 0.007) with ULS. The variables TG, LLS, and ULS were the ones that differed most in each type of stimulus chosen as an intervention in the present study. CONCLUSIONS: The results of this study indicate that GT2 caused more significant percentage reductions in body mass and BMI. However, GT3 caused greater fat percentage reduction. The GT2 caused the greatest decrease in waist circumference, while the GT3 caused the largest decline in hip circumference. The three groups induced an increase in strength (ULS and LLS). However, in ascending order, GT1 caused the smallest increase, GT2 an intermediate increase, and GT3 the greatest increase in strength, with considerable effects in GT2 and GT3. Finally, GT2 caused a greater percentage reduction in systolic blood pressure (large effect) and double product (small effect) than the other groups. The three methods proved to be efficient, but with particularities that may reflect the choice of one over another due to health conditions, objectives to be achieved, or characteristics of the patient at the time of their choice by the prescriber.

This research examines how rainfall and mining affect the slope damage resulting from the transition from open-pit mining to underground mining. Using unmanned aerial vehicle (UAV), the Huangniu slope of Dexing Copper Mine was fully characterized, and experiments were conducted on rock samples from appropriate sites. First, the mechanical properties of the samples were measured. Then, the parameters of the similarity simulation experiments were derived based on the similarity theory. Subsequently, the rainfall, rock slope, data acquisition and monitoring systems were designed. Finally, the rock mass failure with different slope angles was analyzed, and the deformation and damage patterns under the coupling effect were obtained. The results show that rainfall increases pore water pressure and moisture content. Rainfall and slope-slip water have more impact on the open-pit platform. The pore water pressure values on the upper rock mass rise faster than inside. In the open-pit mining stage, the rock mass shifts slightly to the upper left. In the room mining stage, vertical fractures and goaf sinking occur. The fractures above the mine room form a semi-ellipse. In the pillar mining stage, the overlying rock displacement is evident, and fractures persist. In the continuous pillar mining stage, the overlying rock collapses massively. The 65° slope model is the most damaged, while the 55° slope model is the least damaged. The results also suggest that the UAV guides sample selection.

One of the main challenges of the globalization became the increased destabilization and frequent economic crises. In general, managing an economic crisis is a particularly difficult task for any economy (developed or developing, and regardless the size). In the context of globalization, the process faces additional challenges. On the one hand, the world economy witnessed a shift from traditional purely economic instruments to more financial mechanisms of economic development. Indeed, the liberalization of the economy since the 1990s complicated the traditional trends of the world market development, resulting in significant fluctuation of the growth rates between different countries and regions. To respond to this evolution, governments and international organizations changed well-established strategies. For example, financial sector found itself given expanded role in economic development, with, different financial mechanisms used as key variables to evaluate an economic growth. On the other hand, the increased role of financial sector in a globilised world, increased financial relations among individual states and thus, interdependences. This “financial globalization” causes important fluctuations in the system and, as a result, causes instability in socio-economic development. Thus, an economic crisis of any important economy soon becomes a global issue (financial crisis of 2008, economic crisis of 2020).The recent global economic crisis due to the Covid-19 world pandemic, appeared to be unique for several reasons. First, it highlighted the transnational and origin-specific nature of the crisis. Second, it appeared to be the first case when non-economic factors caused a major economic crisis. As a result, this crisis turned out to be particularly difficult to predict and to manage. In this case, the main strategy of the global post-crisis rehabilitation became the restoration of the economy's predictability and ensuring its ability to obey the classical principles. According to the Organic Law on "Economic Freedom" of the European Union (2011), any factor which increases the equilibrium amount of output is reflected in the economic rehabilitation plan. Such exogenous factors are primarily fiscal mechanisms, i.e. - Reduction of taxes and increase of state expenditures. This crisis caused important structural problems with their effects on public expenditures (especially health expenditures, to the public expenditures, economic growth, price stability and budget balance) in both, developed and developing countries. Nearly every state declared an increase in public debt, inflation, and unemployment rates, while an important decrease was shown in growth rates and capital outflows. As the crisis due to the world pandemic was radically different from previous economic crises, it was difficult to manage it efficiently at the initial stage. It was complicated to forecast the scenarios of the unknown crisis with non-standard nature which was more linked to epidemiologic factors than objective economic law. The dynamics of crisis resolution depended on correct forecasting and effective implementation of global, but especially country-based reforms. More importantly, this crisis showed the important role of individual states to manage the global crisis. The traditional function of a government to ensure country’s socio-economic growth and security, increases in an extraordinary environment, such as sharp economic fluctuations and crises. In such contexts, the centralized management functions are sharply activated. The global pandemic processes have updated the economic essence of the state. The large scale of the latest economic crisis due to the world pandemic has determined the need for mutually coordinated development of anti-crisis plans of different countries. In today's dynamic landscape, modern global systems are redefining the standards and priorities of national economic policies. The economic status of countries is changing significantly as a result of their participation in these systems. As a result of these changes, today's global economy is marked by the proliferation of regionalism and the emergence of spatial economic frameworks. Thus, classical economic concepts are evolving, giving rise to a new model known as economic nationalism. This paradigm shift is generating new risks, which are increasing in severity and scope. The overriding objective of economic policy is now to ensure and predict stable development. Reflections are underway to meet the challenges of economic equilibrium and its social and institutional sustainability.In addition to the decentralization of the unified governance system, the global economy is characterized by the activation of centralized governance elements within individual countries. This requires the development of new norms for global cooperation and the careful balancing of national integration and development factors. The question of government's influence on the economy and the delegation of its powers becomes relevant once again. Effective coordination of public administration is based on the principle of decentralized government, which is a key element of a democratic model of society and facilitates the transfer of management tools to the public. The key objectives of this research are focused on the optimal distribution of state functions and the study of hierarchical principles of territorial organization within the country, fiscal mechanisms for the distribution of powers, as well as the particularities of the structuring of the spatial economy and its budgetary provisioning mechanisms.The example of the last two economic crisis showed that contemporary anti-crisis strategies should reflect several considerations. First, it becomes impossible to develop a single unified model of crisis management. Even in the context of important economic and financial globalization, the current decentralization and new spatial economic processes make it necessary to find a balance between the local priorities and global interests. Second, the role of non-economic crisis-causing factors increases compared to economic determinants. That is why international and country-based reforms should aim at not only economic rehabilitation, but also on the social, cultural and environmental restorations. Third, it becomes difficult to correctly predict the consequences of the crisis and thus, the effects of the anti-crisis strategy. Consequently, the success of the post-crisis rehabilitation of the countries' economies depends significantly not only on the effective realization of their own plan, but also, in general, on the specificities of the global economy and on the ability of the world markets to overcome the negative consequences of a crisis. In this context, the development of complex post-crisis platforms and state post-crisis strategies is the priority. The most effective component in the anti-crisis strategy is the monetary instruments of economic management. As for the determinant of successful functioning of economy, the priority should be given to the regulation of exchange rate, interest rate and inflationary processes. A state anti-crisis programs should reflect the crisis prevention strategy, which, on its turn, should differentiate the economic functions of the state and crisis management mechanisms according to the specific trends of given processes. It should aim at gaining stable development of the economy. Additionally, an anti-crisis plan should reflect the role of the society in the development process and its mental changes under crisis conditions. The state should be responsible for establishing and monitoring anti-crisis management mechanisms, financial recovery of the country and formation of correct relations. It is especially important to ensure economic security, to stabilize the development process and standard of living, to support the private sector and small entrepreneurship, to increase economic freedom, to ensure effective distribution of labor and capital, and others. All strategies of the anti-crisis platform should be focused on social results, as it should contribute to a fair distribution of income and to poverty reduction.

Abstract: (1) Background: Post-COVID syndrome is defined as symptoms that occur simultane-ously with or after COVID-19 infection, last for 12 weeks, and are not due to another diagnosis. Limited data are available on people’s long-term quality of life (QoL) following COVID-19 infection. The aim of this cross-sectional study was to investigate long-term QoL after COVID-19 among employees of the St. Josef Hospital in Paderborn, Germany, and to identify risk factors. (2) Methods: A monocentric, cross-sectional study was conducted using the validated and digitized WHOQOL-BREF questionnaire via Netigate® between 10/2022 and 02/2023. Data on QoL and global health status were collected in the following four domains: physical health, mental health, social relationships, and environment. (3) Results: The response rate was 73.84% (923/1250). Furthermore, 63.45% of hospital staff respondents reported at least one persistent symptom after COVID-19 infection, leading to significant differences in QoL. Pre-existing conditions, persistent symptoms, and disability after COVID-19 infection, as well as high BMI, no partnership, and low educational level were found to significantly contribute to long-term low QoL. (4) Conclusions: Obesity, lack of partnership, and a low level of education were independent risk factors for lower QoL post-COVID-19 infection in this cohort of hospital staff. Further multicenter studies are re-quired to validate the incidence and their suitability as independent risk factors for post-COVID syndrome.

Background and aims: For many surgical procedures, spinal anesthesia is a reliable and efficient anesthetic approach. Numerous drugs have been reported to be administered to intrathecal local anesthetics as adjuvants to increase the efficacy of spinal anesthesia. There is little evidence of the effect of intrathecal dexmedetomidine on pain scores and the consumption of analgesia postoperatively. Methods: After obtaining ethical approval, demographical and clinical data of patients who underwent surgical procedures under spinal anesthesia with intrathecal dexmedetomidine or fentanyl was collected and analyzed. Results: In this study with 96 patients, intrathecal dexmedetomidine (group D) resulted in significantly lower post-operative pain scores compared to intrathecal fentanyl (group F) (p=0.000). Across various surgical types, including Orthopedic, General, Urology, and Obs/Gyne procedures, group D consistently displayed reduced pain scores (p<0.001). The number of patients who needed post-operative analgesia was significantly higher in group (F) than in group (D) (40 vs 23, p=0.002). Conclusion: Compared to fentanyl, intrathecal dexmedetomidine as an adjuvant to local anesthesia was found to lower post-operative pain scores and decrease the need for post-operative analgesia.

Clothing consumers mostly purchase, use, and dispose of clothing products in a linear business model. This approach pollutes the environment and causes economic and social crises in the ecosystems. This study evaluates the amount of generated postconsumer clothing waste (PCCW) and proposes recycling as a sustainable waste management approach. Data were collected to understand disposal behavior of consumers with 474 respondents selected from households in Bahir Dar city. The findings show that all the determinant factors on the PCCW generation level except religion were significant. The most frequently disposed type of clothing waste is jeans-trouser (51%). The CEBM was used to develop alternative products from a jeans-based clothing waste. The jean's fiber and fabric-reinforced composite materials were developed using unsaturated polyester resin as a sustainable way of PCCW management strategy. The shredded form fiber-reinforced composite was found to have a smoother surface than that of the chopped or cut fabric-reinforced composite. The product was characterized by physical and mechanical properties. The study can be further extended to the scope of the entire consumers in Ethiopia and alternative recyclable products can be studied.

Obesity entails metabolic alterations across multiple organs, highlighting the role of inter-organ communication in its pathogenesis. Extracellular vesicles (EVs) are communication agents in physiological and pathological conditions and although they have been associated with obesi-ty-comorbidities, their protein cargo in this context remain largely unknown. To decipher the messages encapsulated in EVs, we isolated plasma derived EVs from diet induced obese murine models. Obese plasma EVs exhibited a decline in protein diversity while control EVs revealed significant enrichment in protein folding functions, highlighting the importance of proper folder in maintaining metabolic homeostasis. Previously, we revealed that gut derived EVs proteome holds particular significance in obesity. Here, we compared plasma and gut EVs and identified four proteins exclusively present in the control state of both EVs, revealing the potential for a non-invasive assessment of gut health by analyzing blood derived EVs. Given the relevance of post-translational modifications (PTMs), we observed a shift in chromatin-related proteins from glycation to acetylation in obese gut EVs, suggesting a regulatory mechanism targeting DNA transcription during obesity. This study provides valuable insights into novel roles of EVs and protein post-translational modifications in the intricate mechanisms underlying obesity, shed-ding light on potential biomarkers and pathways for future research.

During deep-sea mining, the heavy metals pollutants can cause contamination in the marine environment. In this paper, the multiphasic coupling model is established to describe the heavy metal migration process during deep-sea mining, which takes the effects of convection-diffusion, adsorption-desorption and sedimentation-resuspension of heavy metals in the aquatic environment into full consideration. Due to the advantages of Lattice Boltzmann method, it is adopted to numerically solve the multiphasic coupling model and achieve the simulation for heavy metal migration process during deep-sea mining. In addition, taking Cadmium as an example, the concentration variations are discussed and analyzed in detail. Based on the established model and Lattice Boltzmann method, the concentration distribution of heavy metals can be accurately described to provide the reasonable bases for the evaluation of marine environmental protection.

The COVID-19 pandemic has led to a substantial revolution in the incorporation of digital solutions in healthcare. This systematic review investigates the enduring physical and psychological consequences individuals experience up to two years post-recovery. Additionally, it focuses on examining the influence of mHealth interventions on these effects. Significantly, 41.7% of survivors experience lingering symptoms that have not been addressed, while 14.1% encounter difficulties in returning to work. The presence of anxiety, compromised respiratory functioning, and persistent symptoms highlight the immediate requirement for specific therapies. Telehealth, particularly telerehabilitation, presents itself as a possible way to address these difficulties. The study thoroughly examines 10 studies encompassing 749 COVID-19 patients, investigating the efficacy of telerehabilitation therapies in addressing various health markers. Telerehabilitation-based breathing exercises yield substantial enhancements in functional performance, dyspnea, and overall well-being. The results emphasize the potential of telerehabilitation to have a favorable effect on patient outcomes, however more research is needed to strengthen the existing evidence basis as one of the most important limitation is the limited number of trials and the evaluation of varied therapies. The analysis highlights the significance of digital solutions in post-COVID care and calls for ongoing research to improve comprehension and implementation of telehealth interventions in a swiftly changing healthcare environment.

Kiribati is a Pacific Island nation with a widely dispersed population and one of the highest rates of leprosy worldwide. Single dose rifampicin post exposure prophylaxis (SDR-PEP) of leprosy contacts has reduced new case detection rates in controlled trials. In 2018, a SDR-PEP programme was introduced in Kiribati that included screening and chemoprophylaxis of household contacts of leprosy cases both retrospectively (2010-2017) and prospectively (2018 onwards). We conducted a retrospective audit to determine comprehensiveness, timeliness and feasibility of the SDR-PEP programme. Overall, 13,643 household contacts were identified (9,791 in the retrospective and 3,850 in the prospective cohort). In the retrospective cohort, 1,044 (11%) contacts were absent, 403 (4%) were ineligible for SDR and 42 new cases were detected (0.4%) Overall SDR coverage was 84.7%. In the prospective cohort, 164 (4%) contacts were absent, 251 (7%) were ineligible for SDR and 23 new cases were diagnosed (0.6%). Overall, SDR coverage was 88.1%. Across both cohorts, there were a total of 23 SDR refusals. The median time to SDR ad-ministration was 220 days (IQR 162-468) and 120 days (IQR 36-283) for the retrospective and prospective cohorts respectively. SDR was readily accepted in both cohorts. The new case detec-tion rate (0.5%) is consistent with that seen in other studies. Overall SDR coverage in both the retrospective and prospective phases met programmatic expectations.

The paper proposes a traceability framework based on methodological approach for the deployment of IOTA-Based Distributed Ledger in the mining industry, as a first step of certification and labelling of the sustainable material production. The methodology is evaluated in real-world implementation in scope of the DIG_IT project. The implementation provides significant amount of heterogeneous data originating from different processes and sources during the operation in mines, such as vehicles operations, mining and raw material extraction, workers physical parameters, environmental parameters, sensors (field, biometric, assets), market (supply chains, commodity prices), weather data, etc. Most of these datasets, especially the data about the emission, needs integrity and the ability to be audited by the public community, government and the stakeholders. The methodology for establishing the transparency for the mining operations, the requirements, technical architecture, General Data Protection Regulation (GDPR) assessment, Distributed Ledger Technology (DLT) infrastructure, as well as end-to-end traceability, are proposed and evaluated with the actual deployment. The approach advocates end to end security for the increased traceability and data integrity based on Distributed Ledger Technology. Namely, W3C Decentralised Identities and Public Key Infrastructure (PKI) should be deployed from the data source to the cloud and anchored onto the Blockchain. The approach showed promising results with the regulations compliance made possible, making the data available and advertised publicly for the emission compliance.

The meticulously engineered powertrain mounting system of hybrid-electric vehicles plays a critical role in minimizing vehicle vibrations and noise, thereby enhancing the longevity of vital powertrain components. However, developing and designing such a system demands substantial time and financial investments due to intricate analysis and modeling requirements. To tackle this challenge, this study integrates data-mining technology into the design and optimization processes of the powertrain mount system. The research focuses on the powertrain mounting system of a transverse four-cylinder hybrid-electric vehicle, employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to establish a data-mining prediction model for mounting stiffness. This model utilizes three data mining algorithms—Multi-SVR, MRTs, and MLPR—assessing their predictive accuracy concerning mounting system stiffness estimation. A comparative analysis reveals that the MRTs algorithm outperforms others as the most effective prediction model. The proposed predictive model elucidates the quantifiable correlation between vibration isolation performance and installation stiffness, overcoming complexities associated with traditional modeling approaches. Applying this model in powertrain mounting system design showcases the efficacy of the CRISP-DM-based approach, significantly enhancing design efficiency without compromising prediction accuracy.

Post-earthquake fire is considered as a catastrophic secondary disaster to personal and property safety. In this article, an evacuation assessment of a complex rail transit station under the post-earthquake fire for sustainable buildings was conducted from the internal environment and external rescue based on Building Information Modeling (BIM) and Fire Dynamic Simulation (FDS). The internal environment evacuation assessment simulation experiments were conducted in six hypothetical high-risk scenarios. Besides, the external rescue assessment was based on investigation of the route and the rescue time required during different periods of holidays and workdays. The results show that: (1) The influence caused by different size of fire area in the power distribution room is smaller than those in the train at the platform floor. (2) In the case of fire scenarios with the same fire area but different fire locations, the impact on temperature is greater than that on CO concentration in power distribution room. (3) It shows slight differences between single-floor fire and double-floor fire on evacuation of small area fire in power distribu-tion room. Meanwhile, optimized design recommendations are proposed to reduce the risk of emergency evacuation in both internal and external environments of rail transit stations for sustainable future buildings.

Mechanical properties of three-dimensional (3D) printed resin can be improved by decreasing oxygen concentrations during post-curing, and nitrogen saturated post-curing has been applied for the purpose. This study aimed to evaluate and compare the color stability of 3D printed resin crowns post-cured in normal air and nitrogen saturated conditions. Crowns were fabricated with 3D printer and post-cured in normal air (control group; air) or nitrogen saturated condition (experimental group; nitrogen). The specimens in each group were subdivided into four subgroups, each exposed to different discoloration agents: distilled water, coffee, wine, and curry. Post-immersion color changes were measured using a digital spectrophotometer and analyzed through repeated measures ANOVA. Fourier Transform Infrared (FT-IR) spectroscopy evaluated the degree of conversion of resin over immersion times for both post-curing conditions. Comparing the effects of post-curing conditions, significant difference was found between control and experimental groups over immersion time in wine and curry subgroups. In FT-IR analysis, there was significant difference in degree of conversion between the air and nitrogen groups from 10 to 300 seconds. The findings suggest that nitrogen saturated post-curing can potentially enhances the conversion rate of 3D printed resin crowns, thereby improving their color stability.

The success of Toxoplasma gondii (intracellular parasite) host cell invasion relies on the apical complex, a specialized microtubule cytoskeleton structure associated with secretory organelles. The genome encodes three isoforms of both α- and β-tubulin which are altered by specific post-translational modifications (PTMs), changing the biochemical/biophysical proprieties of microtubules, and modulating their interaction with associated proteins. Tubulin PTMs are a powerful and evolutionarily conserved mechanism to generate tubulin diversity, forming a biochemical ‘tubulin code’ that can be ‘read’ by microtubule-interacting factors. The T. gondii tubulin PTMs are: α-tubulin acetylation, α-tubulin detyrosination, Δ5α-tubulin, Δ2α-tubulin, α- and β-tubulin polyglutamylation, and α- and α-tubulin methylation. Tubulin glutamylation is a key candidate to assist microtubule remodeling in Toxoplasma, being involved in the regulation of microtubule stability, dynamics, interaction with motor proteins, and severing enzymes. The correct balance of tubulin glutamylation is achieved by the coordinated action of polyglutamylases and deglutamylating enzymes. In this work we will review and discuss the current knowledge on T. gondii tubulin glutamylation. By in silico identification of mammalian protein orthologs we explored and updated the identification of putative proteins related to glutamylation, contributing to a better understanding of the role of tubulin glutamylation in T. gondii.

Knowledge of post-larval swordfish (Xiphias gladius) ecology in the world’s oceans is incomplete as they are rarely found in ichthyoplankton samplings or commercial catches and individuals are difficult to observe in the marine ecosystem. Analyses of stomach contents of apex predators can provide otherwise unobtainable ecological insights. Two well-preserved bills of post-larval swordfish were identified among the partially digested stomach contents of an adult male dolphinfish (Coryphaena hippurus) caught in the northern Tyrrhenian Sea. The lower jaw to fork lengths of the two predated swordfish were estimated at respectively, 18 and 22 cm, corresponding to 81- and 99-day-old swordfish hatched in the 2022 spawning season. This analysis and recent information on the reproductive dynamics of swordfish in the same area reported in the literature shed light not only on the early stages of swordfish growth but also on dolphinfish ecology in the Tyrrhenian Sea. The two species share the same habitat and are both caught with commercial pelagic surface longlines. Environmental shifts associated with climate change could unpredictably modify the reproduction dynamics, growth, recruitment and distribution of both species. This knowledge is important for the sustainable management of regional fisheries.

The Hollow fiber membrane contactor (HFMC) is an intensification process that combines membrane and absorption technologies, being a technology in expansion, so the dynamics of this process is crucial for an increase in industrial scale-up. In this manuscript a rigorous dynamic model of an HFMC is developed and simulated in Python software for the absorption of post-combustion CO2 using a monoethanolamine (MEA) solution, which was validated using available data in literature in steady state. Dynamic simulations were performed to analyze the model's capability to predict the effect of disturbances on the responses of CO2 capture ratio and loading. Four distinct experiments were conducted by step changes and pulse disturbances at the following variables: gas and liquid volumetric flow rates, CO2 composition in flue gases, and CO2 lean load. The gas phase showed a faster response compared to the liquid. The CO2 capture ratio and rich loading presented opposite responses when disturbing both liquid flows, and for the composition and lean loading variations, the capture ratio presented an inverse response characteristic, while the loading showed a delayed response. As the model proved to be capable of returning to the reference state, it can potentially be used for control studies purposes.

This article presents a narrative review of neonatal and paediatric complications in post-dated pregnancy and covers scientific views on the aetiology, pathology, risk factors, symptoms and complications of post-dated pregnancy. A pregnancy extending beyond 42 weeks of gestation is termed as a post term pregnancy. There are multiple complications that can occur in the perinatal period, some of the most common ones are stillbirth, asphyxia, meconium aspiration syndrome, fetal distress syndrome, etc which are found to be greater in post-dated pregnancy and hence ultimately leads to increased mortality and morbidity of the new born. Studies have shown that post-term pregnancy also causes increased risk of developing behavioural and emotional problems in children of paediatric age group. It is surprising not much importance has been given to the maternal and neonatal consequences of post- term pregnancies. It is not well understood why some women experience post-dated pregnancies. It is found that factors such as hormones and genetic build up, are responsible for causing post-term pregnancy in an obese female. The treatment and management of a post-term pregnancy still poses a challenge to clinicians in determining the right choice and right time for a particular intervention so that both mother and fetus can be prevented from having complications.

With the development of electricity spot markets, accurate electricity load forecasting enables power generation companies to supply the right amount of electricity, Significantly avoid power waste. As a result, time series forecasting in the field of power can bring significant benefits. Previously, the Informer model successfully introduced the Transformer into long time series forecasting(LTSF) by proposing the ProbSparse self-attention mechanism, which solved the inherent problem of high memory complexity in self-attention. Recent research has further demonstrated the potential of the self-attention for mining complex dependencies. However, the limited amount of historical data has become one of the main challenges in applying deep learning techniques to power LSTF tasks. Previous reserches often add a large number of time covariates to provide more information. In this paper, to address this issue, (i) we design a simple but effective Season-aware Block to enhance the model’s ability to mine artificial prior information in temporal covariates; (ii) we conduct experiments using the provincial power data of Zhejiang Province, China, from 2019 to 2022, and our model outperforms other models, achieving a 19 percent MSE relative improvement; (iii) we conduct ablation experiments to assess the efficacy of the Season-aware Block in extracting temporal periodic features. Furthermore, we elucidate the underlying reasons for the effectiveness of both the self-attention mechanism and the Season-aware Block through visualization experiments.

(1) Background: Non-surgical endodontic treatment has been repeatedly shown to be clinically successful, however, clinical data are scarce. This practice-based retrospective clinical study aimed to investigate endodontic outcome over 40 years and to identify relevant factors from clinical protocols. (2) Methods: Two experienced dental practitioners in two different private dental practices treated 174 patients with 243 teeth from 1969 to 1993. After obturation, either a new restoration (amalgam, resin composite, glass-ionomer cement), or re-cementation of pre-existing prosthetic restorations or its renewal followed. Metal posts (operator A) or screws (operator B) were inserted when indicated. The primary outcome (tooth survival) was achieved when the endodontically treated tooth was in situ, painless and in full function. Secondary outcome was to investigate the impact of potential prognostic factors on survival rates. (3) Results: Overall mean 40-years survival was 56.1% of all treated teeth after 40 years of clinical service resulting in an annual failure rate of 1.1%. Most investigated clinical factors (Jaw, tooth position, number of intracanal dressings, post/screw placement, sex) had no significant influence on survival. Among postendodontic restorations, resin composite was advantageous. (4) Conclusions: Even with materials and techniques from the 1970’s and 1980’s, successful root canal treatment was achievable. Except postendodontic restorations, most of the evaluated factors had no significant influence on clinical long-term survival of root-canal treated teeth.

Long Covid or post-acute sequelae of SARS-CoV-2 infection (PASC) can manifest as long-term symptoms in multiple organ systems, including respiratory, cardiovascular, neurological, and metabolic systems. In patients with severe COVID-19, immune dysregulation is significant, and the relationship between metabolic regulation and immune response is of great interest in determining the pathophysiological mechanisms. We aimed to characterize the metabolomic footprint for recovering severe COVID-19 patients in three consecutive time points and compare metabolite levels to controls. Our findings add proof of dysregulated amino acid metabolism in the acute phase, and dyslipidemia, glycoprotein level alterations, and energy metabolism disturbances in severe COVID-19 patients 3-4 months post hospitalization.

Non-coding RNAs, specifically microRNAs (miRNAs), exhibit altered expression and contribute significantly to the pathological processes observed in numerous diseases, encompassing various types of human cancers. Recent discoveries regarding miRNAs underscore their crucial roles in tumor pathogenesis and their responses to diverse therapeutic interventions. miRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in the miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive target genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many types of cancers functioning as either oncomiRs or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling deregulated miRNAs in many cancer types has been shown to correlate with disease diagnosis, indicate optimal treatment options, and predict response to a specific therapy. Specific miRNA signatures can track all stages of disease including many cancer types and hold potential as biomarkers and therapeutic targets as well as therapeutics as miRNA mimics and inhibitors (antagomirs). As such, identifying specific miRNAs and mRNAs they regulate in many types of cancer along with downstream pathways can be used as potential therapeutic targets. Because a single miRNA can regulate a pool of targets involved in similar cellular processes and pathways, thereby amplifying the cellular response, this potentially makes miRNAs powerful therapeutics to restore cell functions that are altered as part of a disease phenotype. However, because a single miRNA regulates multiple gene expressions their cellular effects are numerous leading to potential off-target effects. Besides their intended targeting issues, there is a need to reduce the immunogenic reactions and determine the minimal dosing to achieve the desired effect while minimizing side effects. As such, a careful risk evaluation of miRNA therapeutics is needed to minimize off-target effects and to avoid overdosing of miRNA drugs. Furthermore, a limited understanding and validation of the specific roles of miRNAs limits their clinical application. In addition, there are many challenges concerning the delivery, sensitivity, specificity, toxicity, and applicability of the potential utility of miRNAs as therapeutic targets or therapeutics. Thus, future work will warrant if miRNAs can be used as cancer biomarkers as well as therapeutics for clinical application.

The COVID-19 pandemic necessitated a profound shift to online education, impacting students across various educational levels. This research, drawing from a comprehensive survey of 1,000,000 students, delves into the surge in demand for online education during the pandemic and its potential enduring implications. The study scrutinizes factors steering this transition, the perceived effectiveness of online education, challenges encountered by students, and their anticipated preferences for the future. Results unveil nuanced perspectives among K-12, undergraduate, and postgraduate students, with safety, flexibility, and accessibility emerging as pivotal influencers. The findings offer valuable insights into challenges faced and future preferences, enlightening educational stakeholders about the dynamic needs of students and contributing to the ongoing evolution of the post-pandemic educational landscape.

background: The Islamic Republic of Iran has been under sanctions since 1979. These sanctions were further reinforced between the years 2005 and 2012. This study utilizes available data from Iran post-sanctions to review the impact of economic sanctions on both the mental health and the quality of life of Iranian citizens.Methods: A comprehensive scoping review was conducted to identify studies examining the impact of sanctions on health in Iran. Searches were initiated in 2012 using PubMed/Medline, Embase, Web of Science, Scopus, and the Scientific Information Database (Iranian Database) with keywords such as sanctions, implications, mental health, quality of life, civilian mental health, and Iran. Subsequent to the screening process, secondary reports and letters to the editor were excluded. Only original studies—those collecting data via observation, interviews, surveys, experiments, or literature reviews—were retained for analysis. In addition to these search strategies, reference scanning was undertaken to identify additional articles pertinent to the scope of the current study. This thorough approach facilitated the discovery of relevant and significant articles exploring the effects of sanctions against Iran on the mental health and overall well-being of its civilian population. Following the search, duplicate articles were meticulously identified and removed by the authors. Data were subsequently extracted and summarized, focusing on study characteristics and the observed effects of sanctions on civilian mental health and quality of life in Iran.Result: Out of 165 items identified in the preliminary search, ten articles met the inclusion criteria. These selected articles highlighted the pronounced effects of sanctions on various health-related domains.Conclusion: Since 2012, Iran has been subject to intensified sanctions. There is evidence to suggest that the economic sanctions, imposed by Western nations, and have exerted a negative and detrimental impact on the health of individual Iranians.

Process mining offers significant services in the development of digital threads and digital twin applications for healthcare. One of the sub-emerging case studies is the use of patients’ location data in process mining analyses. While the streamlining of published works is focused on introducing process discovery algorithms, there is a necessity to address challenges beyond that. Literature analysis indicates that explainability, reasoning, and characterizing the root causes of process drifts in healthcare processes is an important but overlooked challenge. In addition, incorporating domain-specific knowledge into process discovery could be a significant contribution to process mining literature. To address this, we present the DIAG approach that consists of a meta-model and an algorithm that enables diagnosing in process mining through an ontology-driven approach. With DIAG, we modeled the healthcare semantics in a process mining application and diagnosed the causes of drifts in patients’ pathways. We performed an experiment in a hospital living lab to examine the effectiveness of the DIAG approach.

In today’s competitive landscape, achieving customer-centricity is paramount for the sustainable growth and success of organisations. This research is dedicated to understanding customer preferences in the context of the Internet of Things (IoT) and employs a two-part modeling ap-proach tailored in this digital era. In the first phase, we leverage the power of the Self-Organizing Map (SOM) algorithm to segment IoT customers based on their connected device usage patterns. This segmentation approach reveals three distinct customer clusters, with the second cluster demonstrating the highest propensity for IoT device adoption and usage. In the second phase, we introduce a robust Decision Tree methodology designed to prioritize various factors influencing customer satisfaction in the IoT ecosystem. We employ the Classification and Regression Tree (CART) technique to analyze 17 key questions that assess the significance of factors impacting IoT device purchase decisions. By aligning these factors with the identified IoT customer clusters, we gain profound insights into customer behaviour and preferences in the rapidly evolving world of connected devices. This comprehensive analysis delves into the factors contributing to customer retention in the IoT space, with a strong emphasis on crafting logical marketing strategies, en-hancing customer satisfaction, and fostering customer loyalty in the digital realm. Our research methodology involves surveys and questionnaires distributed to 207 IoT users, categorizing them into three distinct IoT customer groups. Leveraging analytical statistical methods, regression analysis, and IoT-specific tools and software, this study rigorously evaluate the factors influencing IoT device purchases. Importantly, this approach not only effectively clusters the IoT Customer Relationship Management (IoT-CRM) dataset but also provides valuable visualizations that are essential for understanding the complex dynamics of the IoT customer landscape. Our findings underscore the critical role of logical marketing strategies, customer satisfaction, and customer loyalty in enhancing customer retention in the IoT era. This research makes a significant contri-bution to businesses seeking to optimize their IoT -CRM strategies and capitalize on the oppor-tunities presented by the IoT ecosystem.

Intelligent Tutoring Systems (ITS) are increasingly popular for online learning. These systems use adaptive algorithms to recommend relevant content based on students' profiles. However, instructors need to periodically assess students' performance to ensure learning outcomes and adjust strategies accordingly. Our objective is to predict students' progress in advance, enabling teachers to make quicker decisions and facilitating the iterative process of adaptive algorithms. For this study, we collected a dataset from ALIN, an online learning platform, consisting of over 5,000 students' learning records and test results. Using this dataset, we conducted experiments employing various machine learning algorithms. The results indicate that learning behavior contributes to improving forecast performance, while students' progress strongly correlates with their previous test results. Additionally, we discovered that students' progress can be indirectly predicted by forecasting their scores. Furthermore, by breaking down overall scores into several distinct components and predicting individual scores for each component, the accuracy of the forecasts can be improved.

The establishment of an isolation layer in submarine mining has long presented an enduring challenge. In the context of this research, we conducted a similarity simulation test to preliminarily ascertain the interplay between the thickness and extent of the isolation layer. Subsequently, we introduce an innovative approach that integrates fractal theory and the bonded block model (BBM) to simulate undersea isolation layer mining. The validation of this method hinges on on-site borehole scanning and displacement monitoring, which serve to depict the intricate fractal evolution of fractures and predict the optimal thickness of the isolation layer. Our findings affirm the robustness and validity of this method. Evaluation of the fractal dimensions of fractures reveals that a critical threshold of 1.7 exists to prevent structural failure of the isolation layer, while a limit of 1.5 is necessary to avert significant water ingress. Remarkably, the correlation dimension of the settlement time series closely aligns with the fractal dimension of the fractures, underscoring the feasibility of ensuring the safety of isolation layer mining through real-time settlement monitoring.

One of the hallmarks of Alzheimer’s disease (AD) is the accumulation of beta-amyloid peptide (Aβ) leading to formation of soluble neurotoxic Aβ oligomers and insoluble amyloid plaques in various parts of the brain. Aβ undergoes post-translational modifications that alter its pathogenic properties. Aβ is produced not only in brain, but also in the peripheral tissues. Such Aβ, including its post-translationally modified forms, can enter the brain from circulation by binding to RAGE and contribute to the pathology of AD. However, the transport of modified forms of Aβ across the blood–brain barrier (BBB) has not been investigated. Here, we used a transwell BBB model as a controlled environment for permeability studies. We found that Aβ42 containing isomerized Asp7 residue (iso-Aβ42) and Aβ42 containing phosphorylated Ser8 residue crossed the BBB better than unmodified Aβ42, which correlated with different contribution of endocytosis mechanisms to the transport of these isoforms. Using microscale thermophoresis, we observed that RAGE binds to iso-Aβ42 an order of magnitude weaker than to Aβ42. Thus, post-translational modifications of Aβ increase the rate of its transport across the BBB and modify the mechanisms of the transport, which may be important for AD pathology and treatment.

This academic article examines the effectiveness of international humanitarian intervention in conflict zones. Humanitarian intervention refers to the use of military, diplomatic, or economic measures by external actors to protect civilians, promote human rights, and alleviate suffering in areas affected by armed conflict. The research employs a comprehensive approach, incorporating content analysis, case study, and historical analysis in its methodology. It explores the key challenges faced by international actors in implementing humanitarian interventions and evaluates their impact on conflict resolution and post-conflict reconstruction. Through this thorough analysis of case studies and scholarly literature, this article contributes to the ongoing debate surrounding the efficacy of international humanitarian intervention.

ICT and digital technology adoption, sustainable development, community empowerment and local wisdom and destinations uniqueness are keywords that will be further explored in the de-velopment of tourism villages in Kenderan as the most importance of tourism destinations de-velopment from the village level. Therefor this research is aimed at developing suitable model for post smart or wise tourism village through proposing Culture and Tradition Festival and the application of a circular economy. Circular economy development in tourism villages focuses on the application of sustainable production principles in the tourism value chain, namely in creating tourism experiences together with tourists (co-creation of experience) and integrated in a tourism system that supports environmental sustainability. This research is applied research conducted with a sequential mixed method research by conducting qualitative research through expert judgment and quantitative research by circulating questionnaire to tourists visiting Kenderan village, while the collected data is analyzed by Structural Equation Modelling to see the rela-tionship between variables. The results of this research show that creative event as the locality aspects of tourist village, digital competence, and sustainability practice are the building blocks of post smart tourism village, while digital competence and sustainable practice have significant mediating effect of locality on post smart tourism village. To make tourism village possesses sustainable competitive advantages, the village must explore and promote its locality aspects to differentiate its tourist village by identifying the valuable, rare, inimitable and non-substitutable tourism resources. The implication of this research is that to develop smart tourism destination wiser and distinctive, tourist village should explore their local values and resources, embed them into its tourism basic components and core resources, and co create, distribute, deliver and promote it to global market through technology adoption and global sustainability value.

The official recommendations to manage COVID-19 in the outpatient setting focus on high-cost drugs (remdesivir, nirmatrelvir-ritonavir, molnupiravir), suffering from many problems. Therefore, one may consider also other treatments meeting these criteria: • promising effectiveness, based on favorable randomized controlled trials (RCTs) of sufficient validity. Even without definitive evidence, physicians and informed patients can consider them if they are also: • safe, to the state of knowledge • with a very favorable opportunity cost • biologically plausible/not implausible • accessible • without major commercial sponsors in the trials promoting them, and with researchers without major conflicts of interests. The main focus is on a limited group of functional foods and some their active ingredients, with further mention of other substances of different origin, yet fully meeting all the aforementioned criteria. The functional foods and substances described and discussed certainly do not cover all the known effective therapies for COVID-19 (in one case also for Long-COVID), but the only therapies proposed in this paper currently satisfy all the above criteria. The supporting scientific evidence will favor meta-analyses of RCTs that include the most definitive outcome: all-cause mortality, i.e. the outcome that most fully informed people tend to prioritize. Furthermore, the reported evidence favors clinical studies of the most valid design, i.e. RCTs.

The pandemic was an enormous experience all over the world. The type of living, working and study were changed irreversibly. Facing the opportunity to establish old frames of education in universities is impossible. The adoption of new ways of teaching and assessments reveal their convenience and in the same way their weak points. In response to that stage, on 14 December 2022, the EU parliament accepted the "Digital Decade Policy Programme 2030", for the establishment of a digital transformation community (EU 2022). Trakia University had an online assessment system, quizzes for self-training, and final exams, developed in 2008 on Moodle virtual learning environment. During the pandemic, online exams and lectures were conducted using platforms like BigBlueButton in Moodle or Google Meets. The article gives the results of online exams before, during, and after the pandemic. The outcome, without doubt, displays the lowering knowledge level or performance during the social isolation due to COVID-19, and after, and the reasons are discussed. During the second year of the pandemic was mentioned also a high dropout of students. Now the situation is returning to the previous levels, before the pandemic, but the quality of education is not yet reached. The article values the grades results of session exams and has the intention to clarify the influence of the pandemic period on the excellence of high institution education.

Breast Angiosarcoma is a rare malignancy, accounting less than 1% of all soft tissue. It comprises primitive and secondary subtypes, such as radiogenic breast angiosarcoma (RAS). Despite the multimodal treatment, angiosarcomas represent an incurable disease for many patients and represent a cause of substantial deterioration of their quality of life. Surgery represents the cornerstone in the management, but high recurrence rates are reported. Electrochemotherapy (ECT) is practicable locoregional treatment in patients with advanced angiosarcoma, in a multimodal therapeutic strategy. ECT palliative benefit includes optimal patient compliance, good local hemostasis control, and local responses. Considering that only 22 cases are described in literature, we reported a rare case of RAS treated with ECT, after a multidisciplinary approach including Next Generation Sequencing (NGS). A literature review about the feasibility of ECT in RAS management was also performed.

Depression and cognitive impairment are recognized complications of COVID-19. This study aimed to assess cognitive performance in clinically diagnosed post-COVID depression (PCD) patients using neuropsychological testing. The study involved 71 post-COVID patients, with matched control groups: recovered COVID-19 individuals without complications (n=18) and individuals without prior COVID-19 history (n=19). A post-COVID depression group (PCD, n=25) was identified based on psychiatric diagnosis, a comparison group (noPCD, n=46) included participants with neurological COVID-19 complications, excluding clinical depression. The PCD patients showed significantly less scores in the MoCA test, decreased immediate memory recall in the Word Memory Test, decreased processing speed and higher accuracy in the Trail Making Test, and near to significant worse executive control and processing speed in the Stroop task compared to controls and the noPCD patients. The number of post-COVID symptoms negatively correlated with immediate word memory recall and processing speed among all post-COVID patients. In PCD patients, negative correlations between number of post-COVID symptoms and delayed recall, between time after recovery and immediate recall, and positive correlation between the number of acute symptoms and processing speed in the incongruent condition of the Stroop task were found. No differences between groups in Sniffin’s stick olfactory test was found. Overall, our study revealed cognitive impairment in PCD patients similar to those in major depressive disorder.

The two-stage direct thermal contact (2sDTC) process is a rapid dewatering approach for fluid fine tailings (FFT) that is integrated into an oil sands bitumen extraction plant to reduce tailings pond storage and freshwater usage. In the first stage, combustion gas directly contacts atomized FFT, vaporizing water and yielding dry solids and steam-rich hot gas. The second stage involves pond effluent water directly contacting the steam-rich hot gas, recovering heat and condensing moisture. Case studies confirm the technical feasibility of the integration. Benefits include producing a dry discharge, reducing tailings water discharge and conserving an equivalent to 0.2 barrels of freshwater per barrel of oil produced. Most importantly, these benefits incur no additional energy cost to the plant as the integration eliminates the energy penalty and CO2 emissions associated with FFT dewatering. Further capacity enhancement can be achieved by using centrifuge-concentrated FFT. The study reveals that FFT concentrated to ~50 wt% solids could still maintain its pump-ability and be accommodated by the 2sDTC process, leading to an integration which could dewater more FFT annually and conserve more freshwater ( 0.58 barrels per barrel of oil produced), with the sole energy requirement being the power to drive the centrifuge machinery.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a frequent, debilitating and still enigmatic disease. There is a broad overlap in the symptomatology of ME/CFS and the Post-COVID Syndrome (PCS). A fraction of the PCS patients develops the full clinical picture of ME/CFS. New observations in microvessels and blood from patients suffering from PCS have appeared and include microclots and malformed pathological blood cells. Capillary blood flow is impaired not only by pathological blood components but also by prothrombotic changes in the vascular wall, endothelial dysfunction, and expression of adhesion molecules in the capillaries. These disturbances can finally cause a low capillary flow and even capillary stasis. A low cardiac stroke volume due to hypovolemia and the inability of the capacitance vessels to adequately constrict to deliver the necessary cardiac preload generate an unfavorable low precapillary perfusion pressure. Furthermore, a predominance of vasoconstrictor over vasodilator influences exists, in which sympathetic hyperactivity and endothelial dysfunction play a strong role, causing constriction of resistance vessels and of precapillary sphincters which leads to a fall in capillary pressure behind the sphincters. The interaction of these two precapillary cardiovascular mechanisms causing a low capillary perfusion pressure is hemodynamically highly unfavorable in the presence of a primary capillary stasis already caused by the pathological blood components and their interaction with the capillary wall, to severely impair organ perfusion. The detrimental coincidence of the microcirculatory with the precapillary cardiovascular disturbances may constitute the key disturbance of the Post-COVID-19 syndrome and finally lead to ME/CFS in pre-disposed patients because the interaction causes a particular kind of perfusion disturbance - capillary ischemia-reperfusion - which has a high potential of causing mitochondrial dysfunction by inducing sodium- and calcium-overload in skeletal muscles. The latter in turns worsens the vascular situation by the generation of reactive oxygen species to close a vicious cycle from which the patient can hardly escape.

Mineral extraction is one of the most important for the economies of different countries, and Brazil is one of the world's primary iron ore producers. Unfortunately, the dams are still the main problem, mainly in Minas Gerais, especially after the Fundão Dam rupture happened in 2015. Additionally, there is still a massive presence of buildings produced on earth throughout the Minas Gerais mining region, built from the 18th century to today. Investigating the potential of IOT to be incorporated into traditional earthen construction techniques in regions affected by dam ruptures presents a relevant and innovative research approach. In addition, the local reuse of these sediments should be the priority. Thus, the main objective of this work was to collect, characterize, and analyze the possibilities of application of these tailings to produce RE. XRD, XRF, granulometry, porosity, specific density, toxicity, and MEV/EDS were performed on the samples collected at three points. To analyze the soil-IOT compatibility, representative mixtures of RE were produced, and the specific mass, compaction, and compressive strength were performed. It was observed that the IoT samples have a high silica content and that the mixtures of IOT-soil, even without cement, reached compressive strength values above the current international standards.

Premortem clinical diagnoses and postmortem autopsy findings do not match throughout history. These clinicopathological discrepancies are expected to be raised during the coronavirus disease 2019 (COVID-19) pandemic due to increased pressure on healthcare. At the same time, autopsies and clinicopathological discrepancies accurately display the quality of the healthcare system. To assess that, we examined the relevant works of literature according to the PRISMA-based protocol. As discrepancy rate changes in the correlation to the length of stay in the hospital, we also checked whether studies with patients from the intensive care unit (ICU) differed in discrepancies significantly. We found overall risk differences pretty much alike in "pre-COVID" and "during the pandemic" groups of studies. Based on that, we concluded that healthcare quality did not drop significantly during the pandemic. Be it as it may, the pandemic exposed some shortcomings in mortem healthcare regarding consensus to the autopsy, organ retention, burial, and the postponed burial or the digitalization of post mortem healthcare. All of these issues should be addressed in the future.

Post-training quantization is pivotal in deploying convolutional neural networks for mobile applications. Block-wise reconstruction with adaptive rounding, as employed in prior works like BrecQ and Qdrop, facilitates acceptable 4-bit quantization accuracy. However, adaptive rounding is time-intensive, and its constraint on weight optimization space curtails the potential for quantization performance. The optimality of block-wise reconstruction hinges on the quantization status of subsequent network blocks. In this investigation, we delve into the theoretical underpinnings of the limitations inherent in adaptive rounding and block-wise reconstruction. Our exploration leads to the development of a post-training quantization methodology, designated as AE-Qdrop. This algorithm operates in two distinct phases: block-wise reconstruction and global fine-tuning. The block-wise reconstruction phase introduces a progressive optimization strategy, superseding adaptive rounding, which not only augments quantization precision but also significantly improves quantization efficiency. To mitigate the risk of overfitting, we introduce a random weighted quantized activation mechanism. During the global fine-tuning phase, we account for interdependencies among quantized network blocks. The weight of each network block will be corrected with logit matching and feature matching. Extensive experiments validate that AE-Qdrop achieves high-precision and efficient quantization. For instance, in the case of 2-bit MobileNetV2, AE-Qdrop outperforms Qdrop by achieving a 6.26% enhancement in quantization accuracy and quintupling the quantization efficiency.

Depression is one of the most severe sequelae of COVID-19, with major depressive disorder often characterized by disruption in white matter (WM) connectivity , stemming from changes in brain myelination. This study aimed to quantitatively assess brain myelination in clinically diagnosed post-COVID depression using recently proposed MRI method, macromolecular proton fraction (MPF) mapping. The study involved 63 recovered COVID-19 patients (52 mild, 11 moderate, 2 severe) at 13.5±10.0 months post-recovery, with matched controls without prior COVID-19 history (n=19). A post-COVID depression group (PCD, n=25) was identified based on psychiatric diagnosis, while a comparison group (noPCD, n=38) included participants with neurological COVID-19 complications, excluding clinical depression. Fast MPF mapping revealed extensive demyelination in PCD patients, particularly in juxtacortical WM (predominantly occipital lobe and medial surface), WM tracts (inferior fronto-occipital fasciculus (IFOF), posterior thalamic radiation, external capsule, sagittal stratum, tapetum), and grey matter (GM) structures (hippocampus, putamen, globus pallidus, and amygdala). The noPCD group also displayed notable demyelination but with less magnitude and propagation. Multiple regression analysis highlighted IFOF demyelination as the primary predictor of PCD presence and severity according to Hamilton scores. The number of post-COVID symptoms was a significant predictor of PCD presence while the number acute of symptoms was a significant predictor of PCD severity. This study, for the first time, reveals extensive demyelination in numerous WM and GM structures in PCD, outlining IFOF demyelination as a key biomarker.

The influences of doped hole transporting layer (HTL) on the performances of perovskite solar cells were studied. The influences of electrostatic and surface roughness effect by solvent additive doping were compared. The electrostatic effect of solvent additive doping was compared by addition of 1,8-diiodooctane and 1,8-dichlorooctane to the HTL layer. The surface roughness effect of solvent additive doping was examined using atomic force microscopy. The perovskite crystallinity by doping HTL was studied by X-ray diffraction. The conductivity of HTL was measured using four probe methods and was higher for doped devices. Enhanced conductivity of PEDOT:PSS film was also proved using fluorescence emission quenching. Long-term stability of the device was enhanced by doping HTL. The device with solvent additive exhibited much enhanced stability, retained over 80% of the initial PCE for 400 hours, while PCE of the device without solvent additive decreased to less than 80% after 200 hours. A very weak power microwave treatment was used for post-annealing of the fully fabricated devices. Post-annealing enhanced the lifetime of the device. Comparing different size of cells, the device lifetime was decreased as the cell area increased and as the size of the cell increased, the extent of lifetime enhancement by doping was increased.

Objective: To assess the recovery of voice in patients with unilateral vocal cord paralysis after thyroid surgery following treatment with nursing intervention combined with voice training. Methods: Thirty patients with unilateral vocal cord paralysis and hoarseness for 6-12 months post-thyroid surgery were selected. They first underwent two weeks of psychological and cognitive intervention, followed by a psychological resilience assessment, and then proceeded with 12 weeks of voice training. This training primarily included muscle relaxation exercises, breathing training, and phonation exercises. A comparative analysis was conducted on the patients' voice parameters before and after the training, including jitter, shimmer, maximum phonation time (MPT), noise to harmonic ratio (NHR), and the Voice Handicap Index (VHI) scores. Results: After psychological and cognitive intervention, scores for optimism, resilience, and self-strength among the 30 patients increased. Post-voice training, reductions were observed in jitter, shimmer, NHR, and VHI scores, the Maximum Phonation Time (MPT) increased compared to pre-training, with the difference being statistically significant (P<0.05). Conclusion: Nursing intervention combined with voice training can effectively improve voice quality in patients with unilateral vocal cord paralysis after thyroid surgery.

Experimental quantification of retention factors related to post-fire strength as well as post-fire ductility of intentionally selected stainless steel grades applied in construction is the objective of research presented here. These steel grades are characterized by a two-phase austenitic-ferritic microstructure of the duplex type. In this context two mutually corresponding chromium-nickel-molybdenum steel grades have been subjected to analysis, namely X2CrNiMoN22-5-3 steel belonging to the standard duplex group (DSS 22% Cr) and X2CrMnNiN21-5-1 steel belonging to the lean duplex group (LDSS). The similarities and differences in the mechanical properties exhibited by these steel grades after effective cooling, following more or less prolonged simulated fire action conforming to several development scenarios, have been identified and indicated. The resistance of given steel grade to permanent structural changes induced by the heating program proved to be the critical factor determining these properties and resulting in many cases in increased susceptibility to brittle fracture.

: Kentucky is one of the largest coal producing states and surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas and vegetation change and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age, mining percentage, reclaimed forest percentage, and reclaimed woods percentage) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n=9), summer (n=14), and fall (n=58) 2017 to study changes in water quality variables (SO42-, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+,Fe3+) in response to changes in land cover. Pearson correlation analyses indicated conductivity has strong to very strong relationships with other variables of water quality variables related to coal mining (except Al3+, Fe2+,Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate multivariate regression analyses were performed with conductivity values based on samples collected in the fall. First, conductivity response to mining percentage, reclamation age and topographic variables were examined (adjusted R2=0.818, p &lt; 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p &lt; 0.01). Finally, reclamation age and mining percentage were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p &lt; 0.01) with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal Mine Related Stream Chemistry in areas where agriculture and urban development are limited. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining as well as refining land reclamation practices.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex disease characterized by profound fatigue, post-exertional malaise (PEM), and neurocognitive dysfunction. Immune dysregulation and gastrointestinal symptoms are commonly observed in ME/CFS patients. Despite affecting approximately 0.89% of the general population, the underlying pathophysiological mechanisms remain poorly understood. This study aimed to elucidate the relationship between immunological characteristics and intestinal barrier function in ME/CFS patients. ME/CFS patients were stratified into two groups based on their immune competence. After documentation of detailed medical records, serum and plasma samples were collected for assessment of inflammatory immune mediators and biomarkers for intestinal barrier integrity by ELISA. We found reduced complement protein C4a levels in immunodeficient ME/CFS patients suggesting a sub-group specific innate immune dysregulation. ME/CFS patients without immunodeficiencies exhibit a mucosal barrier leakage, as indicated by elevated levels of Lipopolysaccharide-binding protein (LBP). Stratifying ME/CFS patients based on immune competence enabled the distinction of two subgroups with different pathophysiological patterns. The study highlights the importance of emphasizing precise patient stratification in ME/CFS, particularly in the context of defining suitable treatment strategies. Given the substantial health and socioeconomic burden associated with ME/CFS, urgent attention and research efforts are needed to define causative treatment approaches.

In this inclusive review article, the focus is on navigating the dynamic landscape of literature education, particularly the profound pedagogical shifts observed in the aftermath of the pandemic. The article synthesizes global insights, delving into how educators have adapted to hybrid models and embraced digital tools, fundamentally transforming the reading, analysis, and engagement with literary works. Exploring the integration of digital tools in literature education, the review uncovers the transformative impact of technology on traditional pedagogies. It analyzes the challenges and opportunities inherent in adapting literature education to the digital era, emphasizing the need for inclusive practices and adaptability. The article concludes by suggesting future research directions, encompassing AI integration, inclusive practices, cultural variations, long-term effects of hybrid models, and effective pedagogical strategies for technology integration. With a comprehensive approach, this review not only summarizes the current state of literature education but also discusses its implications, offering a holistic understanding of the contemporary educational landscape and setting the stage for future research endeavors.

Background: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. Methods: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network : Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals. Results: Currently operational within eleven French cancer centres, Consore employs natural language processing to structure the therapeutic management data of approximately 1.3 million cancer patients. This data originates from their electronic medical records, encompassing about 65 millions of medical records. Thanks to the structured data, which is harmonized within a common data model, and its federated search tool, Consore can create patient cohorts based on patient or tumor characteristics, and treatment modalities. This ability to derive larger cohorts is particularly attractive when studying rare cancers. Conclusions: Consore serves as a tremendous data mining instrument that propels French cancer centres into the big data era. With its federated technical architecture and unique shared data model, Consore facilitates compliance to regulations and acceleration of cancer research projects.

Background: Alongside their long-term effects - post-concussion syndrome (PCS) - mild traumatic brain injuries (mTBI) are significant public health concerns. Currently, there is a lack of reliable biomarkers for diagnosing and monitoring mTBI and PCS. Exosomes are small extracellular vesicles secreted by cells that have recently emerged as a potential source of biomarkers for mTBI and PCS due to their ability to cross the blood-brain barrier and reflect the pathophysiology of brain injury. This study aimed to investigate the role of salivary exosomal biomarkers in mTBI and PCS. Methods: A systematic review using the PRISMA guidelines was conducted, and studies were selected based on their relevance to the topic. Results: Studies have shown that exosomal tau, phosphorylated tau (p-tau), amyloid beta (Aβ), and microRNAs (miRNAs) are potential biomarkers for mTBI and PCS. Specifically, elevated levels of exosomal tau and p-tau have been associated with mTBI and PCS, as well as with repetitive mTBI. Dysregulated exosomal miRNAs have also been observed in individuals with mTBI and PCS. Additionally, exosomal Prion cellular protein (PRPc), coagulation factor XIII (XIIIa), synaptogyrin-3, IL-6, and aquaporins have been identified as promising biomarkers for mTBI and PCS. Conclusion: Salivary exosomal biomarkers have the potential to serve as non-invasive and easily accessible diagnostic and prognostic tools for mTBI and PCS. Further studies are needed to validate these biomarkers and to develop standardized protocols for their use in clinical settings. Salivary exosomal biomarkers can improve the diagnosis, monitoring, and treatment of mTBI and PCS, leading to improved patient outcomes.

Post-viral fatigue syndrome (PVFS) encompasses a wide range of complex neuroimmune disorders of unknown cause characterized by disabling post-exertional fatigue, myalgia and joint pain, cognitive impairments, unrefreshing sleep, autonomic dysfunction, and neuropsychiatric symptoms. It includes myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and more recently post-COVID-19 condition (Long COVID). To date, there are no definitive clinical case criteria and no FDA-approved pharmacological therapies for PVFS. Given the current lack of effective treatments, there is a need to develop novel therapeutic strategies for these disorders. Mitochondria, the cellular organelles responsible for tissue energy production, have recently garnered attention in research into PVFS due to their crucial role in cellular bioenergetic metabolism in these conditions. Accumulating literature has identified a link between mitochondrial dysfunction and low-grade systemic inflammation in ME/CFS, FM, and Long COVID. To address this issue, this article aimed to critically review the evidence relating to mitochondrial dysfunction in the pathogenesis of these disorders; in particular, to evaluate the effectiveness of coenzyme Q10 supplementation on chronic fatigue and pain symptoms as a novel therapeutic strategy for the treatment of PVFS.

The study aimed to evaluate the after-effects of the COVID-19 pandemic on the sleep quality and patterns of women across different cultural settings within Iraq, spanning the period of 2022. A cross-sectional survey was administered to a diverse cohort of women from multiple provinces in Iraq. The survey measured various parameters, including sleep duration, onset latency, and disturbances. The post-pandemic period has seen a notable decline in sleep quality among the female population. Contributing factors include psychological stress, lifestyle changes due to the pandemic, and ongoing socio-economic challenges. The impact on sleep quality exhibited variation across different cultural groups, indicating a significant cultural influence on the pandemic's psychological aftermath. The study concludes that the post-pandemic phase has adversely affected the sleep health of women in Iraq, with cultural factors playing a critical role in these changes. There is a pressing need for culturally sensitive public health strategies to address sleep disturbances and mitigate their long-term effects on women's health. Public health initiatives should be tailored to address the specific cultural contexts within Iraq to improve sleep health among women. Further research is warranted to explore the long-term consequences of disturbed sleep patterns and the effectiveness of different intervention strategies.

Background: Chronic post-surgical pain is a condition persisting at least three months after surgery. It is estimated that 25-60% of patients who underwent breast cancer removal surgery suffer from post-mastectomy pain syndrome and occurred anxiety, depression, sleep disturbance and catastrophizing. Physical activity can reduce the risk of chronic diseases and has a good impact on mood and cognitive function. Aim of this study was to evaluate the effects of physical activity on the intensity of pain, depression and anxiety in women underwent mastectomy for breast cancer removal. Methods: A prospective observational unicentric cohort study was performed. Patients were female underwent unilateral or bilateral mastectomy. Numerical Rating Scale (NRS), was used to assess pain intensity, Beck’s Depression Inventory (BDI) for depression and Generalized Anxiety Disorders-7 (GAD-7), for anxiety evaluation. Physical activity was assessed by International Physical activity questionnaire (IPAQ). Interleukin (IL)-17, IL-1β, cortisol, adrenocorticotropic hormone (ACTH) and brain-derived neurotrophic factor (BDNF) were also evaluated in the blood of patients. All the evaluation was assessed 3 and 6 months after the surgery. Results: Adequate physical activity reduced intensity of pain, depression and anxiety symptoms in women affected by post-mastectomy pain syndrome. Moreover, adequate active women, showed a reduction of biomarkers of inflammation, cortisol, ACTH and an increase of BDNF. Conclusions: Our results suggest that physical activity can improve quality of life, reducing intensity of pain, inflammatory markers and it can be useful in the reduction of associated anxiety and depression.

The purpose of the present study was to investigate the effect of post-activation performance enhancement (PAPE) induced by eccentric half-squat exercise on vertical jump performance in male jumpers. The jumping height, peak power, and work were measured and evaluated in twenty male jumpers. Participants performed five eccentric half-squats at 85% of their one-repetition maximum (1 RM), with a knee angle below 90°, followed by immediate and 2min delayed jump assessments using Squat Jump (SJ) and Countermovement Jump (CMJ) tests. Results showed that this specific PAPE protocol did not significantly improve jump performance for both SJ and CMJ tests. Factors such as stimulus specificity, rest intervals, muscle length, and the balance between potentiation and fatigue may explain these results. The study highlights the complexity of PAPE responses and suggests that a single set of eccentric squats with a short rest may not improve jump performance in male jumpers. Further research is required to optimize the interplay between conditioning stimulus and rest periods to maximize PAPE effects in athletic performance enhancement.

The coronavirus disease 2019 (COVID-19), instigated by the zoonotic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), rapidly transformed from an outbreak in Wuhan, China, into a widespread global pandemic. A significant post-infection condition, known as ‘long- COVID’, emerges in a substantial subset of patients, manifesting with a constellation of over 200 reported symptoms that span multiple organ systems. This condition, also known as 'post-acute sequelae of SARS-CoV-2 infection' (PASC), presents a perplexing clinical picture with far-reaching implications, often persisting long after the acute phase. While initial research focused on the immediate pulmonary impact of the virus, the recognition of COVID-19 as a multiorgan disruptor has unveiled a gamut of protracted and severe health issues. This review provides a summary of the primary effects of long COVID on the cardiovascular, nervous, and respiratory systems. It also delves into the mechanisms underlying these impacts and underscores the critical need for a comprehensive understanding of long COVID's pathogenesis.

Coal mining has caused a significant loss of nitrogen content of soil in mining areas. This article studies the effects of organic fertilizer, inorganic fertilizer, and combined application of Pseudomonas fluorescens with the ability of nitrogen fixation on soil nitrogen accumulation and composition in the reclamation area of Tunlan Coal Mine from 2016 to 2022 under the condition of equal nitrogen application, providing scientific basis for microbial fertilization and rapid increase of nitrogen content in the reclaimed soil of mining areas. The results showed that as the reclamation time increased, the nitrogen content and its composition structure of the soil treated with fertilization rapidly evolved towards normal farmland soil. The soil nitrogen content increased the fastest in the treatment of Pseudomonas fluorescens + organic fertilizer (MB), compared with inorganic fertilizer (CF), organic fertilizer (M), and Pseudomonas fluorescens + inorganic fertilizer (CFB) treatments, the treatment of Pseudomonas fluorescens + organic fertilizer (MB) can bring the total nitrogen (TN) content of the soil to normal farmland soil levels 1-3 years earlier. The comprehensive scores of Pseudomonas fluorescens + organic fertilizer (MB) and Pseudomonas fluorescens + inorganic fertilizer (CFB) on the two principal components were increased 1.58 and 0.79 than those of organic fertilizer (M) and inorganic fertilizer (CF) treatments, respectively. This further indicates that the combination of Pseudomonas fluorescens and organic fertilizer has a better effect on improving soil nitrogen accumulation than the combination of Pseudomonas fluorescens and inorganic fertilizer. At the same time, the application of Pseudomonas fluorescens will increase the content of unknown nitrogen (UN) in acid-hydrolysable nitrogen (AHN), and decrease the content of amino acid nitrogen (AAN) and ammonia nitrogen (AN), relatively. However, there was no significant effect on the content of ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) in soil inorganic nitrogen (SMN). When combined with inorganic fertilizer, the contribution of soil mineralized nitrogen (SMN) to total nitrogen (TN) increased by 14.78%, while when combined with organic fertilizer, the contribution of acid-hydrolysable nitrogen (AHN) to total nitrogen (TN) increased by 44.77%. In summary, the use of Pseudomonas fluorescens is beneficial for nitrogen recovery in the reclaimed soil of coal mining areas. The optimal fertilization method under the experimental conditions is the combination of Pseudomonas fluorescens and organic fertilizer.

Background. There are few studies about post myocardial infarction follow-up using telemedicine. We organized a post-discharge telemedicine service with a dedicated team. To do this, it was necessary that all stakeholders involved in the organization and use of the telemedicine service were properly educated and informed. Methods. We designed a theoretical-practical mini-course, to train healthcare personnel and increase skills, with excellent learning outcomes and satisfaction. Thereafter, we enrolled patients affected by acute myocardial infarction with ST elevation (STEMI), MINOCA (myocardial infarction with no obstructive coronary atherosclerosis), Takotsubo syndrome or spontaneous coronary dissection, and high-risk acute myocardial infarction without ST elevation (NSTEMI). At discharge, the cardiology technician performed counselling for the patient; using regional platforms, televisit at 1 and 4 months monitored major adverse cardiac events (MACE), heart failure, arrhythmias, unstable angina and non-cardiovascular events, therapy adherence, target therapy and customer satisfaction. Results. Between November 2021 and February 2023, we enrolled 110 patients: 72% affected by STEMI, 22% by NSTEMI. At the 1-month follow up, 12 patients did not reach pressure target and 23 patients did not reach LDL target. We observed three in hospital readmission, three in hospital visits for further investigation and one death. To date, a four months follow up was performed for 54 patients. No readmissions or deaths occurred. We detect a rate of 96% of customer satisfaction. Conclusion. A health coordination center with a dedicated team makes televisit safe as a follow-up for post myocardial infarction patients. Before, it is fundamental for healthcare professionals the acquisition of theoretical knowledge and updates and the acquisition of manual, technical and practical skills.

This text mining study delves into the multifaceted contributions of the energy sector to the Sus-tainable Development Goals (SDGs). By analyzing a wide range of academic literature, we un-cover key themes, trends, and challenges shaping the intersection of energy and sustainability. The findings reveal that the energy sector plays a pivotal role in achieving SDGs such as affordable and clean energy (SDG 7) and climate action (SDG 13). Critical issues encompass governance, policy frameworks, and technological innovations. This research underscores the need for inter-disciplinary collaboration and holistic approaches in addressing complex energy-related sus-tainability challenges. The insights derived here provide guidance to policymakers, researchers, and stakeholders seeking to harness the energy sector's potential for a more sustainable and eq-uitable future.

Background There is a considerable overlap between clinical presentation of post-COVID-19 condition (PCC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) . Many of their common symptoms can be linked to dysregulation of the autonomic nervous system (dysautonomia). This study aimed to objectively assess autonomic function in patients with PCC and in patients with ME/CFS whose disease was not related to COVID-19. Methods Synchronous recordings of an electrocardiogram, continuous dynamics of blood pressure in the digital artery using the Penaz method and ultrasound pneumotachography with the spirography function were obtained with spiroarteriocardiorhythmography method in 34 patients diagnosed with ME/CFS, in whom the onset of the disease was not associated with COVID-19, 29 patients meeting PCC definition and 32 healthy controls. Heart rate variability (HRV), systolic and diastolic blood pressure variability (RV), respiration variability were assessed at rest and in tests with fixed respiratory rates. At rest, indicators of baroreflex regulation were additionally determined (baroreflex effectiveness index and baroreflex sensitivity). Results The total power, power of very low frequency, low-frequency and high-frequency of RR interval variability at rest as well as baroreflex effectiveness index in up-ramps of arterial blood pressure and baroreflex sensitivity were significantly lower both in PCC and ME/CFS patients compared to HC. Several diagnostic prediction models for ME/CFS were developed based on HRV parameters. During slow breathing HRV parameters return to normal in PCC, but not in ME/CFS. Correlation analysis revealed a close relationship of HRV, RV parameters and baroreflex sensitivity with fatigue, but not with HADS depressive/anxiety symptoms in ME/CFS and PCC. Conclusion A similar pattern of HRV and baroreflex failure with signs of a pathological acceleration of age-dependant dysautonomia was identified in ME/CFS and PCC. The clinical, diagnostic and therapeutic implications of these findings are discussed, in light of previously described relationship between inflammation, vascular pathology, atherosclerotic cardiovascular disease and autonomic dysfunction.

The JCR 2022, for the first time, included the ESCI journals, increasing the number of publication titles by approximately 60%. In this paper, the subcategory Mining and Mineral Processing (as part of the Engineering and Geosciences category), where 12 of the ESCI journals were merged with the 20 SCIEx ones, is presented and analysed. Only three of the ESCI journals, that JCR 2022 included in the database, would be ranked in the Q1/Q2. The inclusion of the entire ESCI added new content for readers and authors relying on the JCR sources, and will help the journals in the database to attract more papers and citations in the future. Consequently, part of the journals (probably more than 25% marked in this analysis) will have a bigger chance to reach the Q1/Q2 ranking in the forthcoming years. This paper gives the authors, researchers, and publishers in the Mining and Mineral Processing field practical insights into the potential benefits and challenges associated with the changing landscape of indexed journals, as well as the in-depth, systematic analyses for potential future authors to have the opportunity to select the most suitable journal for submitting their papers.

Text annotation is an essential element of the natural language processing approaches. The manual annotation process performed by humans has several drawbacks, such as subjectivity, slowness, fatigue, and possibly carelessness. In addition, annotators may annotate ambiguous data. So, we developed the concept of automated annotation to get the best annotations using several machine-learning approaches. The proposed approach is based on an ensemble algorithm of meta-learners and meta-vectorizer techniques. The approach employs a semi-supervised learning technique for automated annotation, aimed at detecting hate speech. This involves leveraging various machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbors (KNN), and Naive Bayes (NB), in conjunction with Word2Vec and TF-IDF text extraction methods. The annotation process is performed using 13,169 Indonesian YouTube comments data. The proposed model used a Stemming approach using data from Sastrawi and also new data of 2,245 words. Semi-supervised learning uses 5%, 10%, and 20% of labeled data as compared to performing labeling based on 80% of the datasets. In semi-supervised learning, the model learns from the labeled data, which provides explicit information, and the unlabeled data, which offers implicit insights. This hybrid approach enables the model to generalize and make informed predictions even when limited labeled data is available, ultimately enhancing its ability to handle real-world scenarios with scarce annotated information. In addition, the proposed method uses a variety of thresholds for matching words labeled with hate speech ranging from 0.6, 0.7, 0.8, and 0.9. The experiment showed that the KNN-Word2ec model has the best accuracy value of 96.9% with a scenario of 5%:80%:0.9. However, several other methods have also accuracy above 90%, such as SVM and DT based on both text extraction methods in several test scenarios.

Most of the research in data mining concentrated on finding the positive associations that exist in frequent patterns. Frequent patterns have no bearing on the time duration and, therefore, lose interestingness. The Regularity of an itemset is related to the time at which the transaction occurred and the time distance between the transactions. Frequent Regular item sets can be generated considering the Frequency and the Regularity of the occurrence of the Item Sets. The frequent and regular Item sets will be so huge that they cannot be handled in real time. The count of Frequent and regular item sets gets reduced drastically when the properties “closed” and “Maximality” are applied. Finding negative associations among such patterns are important in the field of medicine. Many drugs administered to cure some diseases have counter reactions leading to many other diseases. Negative associations among the mined patterns are important as they reveal significant contradictions frequently among medical drugs administered by medical practitioners to cure some diseases. This paper proposes a method that mines medical databases to find regular, frequent patterns applied with closed and maximal properties and find negative associations among those patterns. The proposed algorithm is accurate to 98% and performs 9% more efficiently than the other algorithms presented in the literature.

The expansion of mankind in Space will eventually lead to the need for resource extraction on places different from Earth. For the few who would succeed, the monetary gains from space mining are promising but inevitably, such activities will bring about substantial consequences to the celestial bodies they are conducted on and to the political-economical scene of the parties involved. Thus, a new set of moral interrogatives needs to be dealt with. This paper reflects, from a utilitarian perspective, on whether it is ethical or not to exploit extra-terrestrial resources and tries to produce moral norms on the matter. The main research question is analyzed with respect to three crucial aspects: environmental consequences, interaction with possible forms of life and the political-economical setting around resource extraction in space. Reflections, argumentations, and claims are backed up or confronted with already existing theories and positions of other authors. Altogether, we concluded that the extraction and usage of the resources of another celestial body is ethical only when: 1) it is regulated enough to avoid the destruction of naturalistic, aesthetically or culturally valuable environments; 2) it does not interfere (or at least, it tries to deal) with existing or possible future forms of life, which ought to be protected with ad-hoc legislation; 3) it is regulated to prevent tensions that would likely arise between countries that want to access specific resources-rich sites, issuing laws able to avoid conflicts and a possible economic collapse. To summarize, we identified the concept of responsible innovation as the key director for future policies that will need to be established when space resource extraction becomes a reality.

Post-stroke depressive disorders (PSD) and post-stroke cognitive impairments (PCI) are frequent consequences of ischemic stroke (IS). The study was focused on exploring possible associations between relative volumes of cortical and limbic brain structures during the acute period of IS, and changes in biochemical indices of hypothalamic-pituitary-adrenal, sympathoadrenal medullary and inflammatory systems, with the development of PSD or PCI after mild or moderate IS. Patients developing PSD later on had significantly smaller relative volumes of the hippocampus, entorhinal cortex, and temporal pole versus patients without depressive symptoms. PCI development was associated with significantly smaller volumes of temporal pole and supramarginal gyrus versus patients without cognitive changes. Multiple logistic regression analysis showed higher likelihood of developing PSD in patients with smaller temporal pole volume (β0=10.9; β=-4.27; p=0.04) and increased salivary α-amylase activity (β0=-3.55; β=2.68e-05; p=0.02,). PCI likelihood was higher in patients with smaller supramarginal gyrus volume (β0=3.41; β=-0.99; p=0.047), smaller temporal pole volume (β0=3.41; β=-3.12; p=0. 06), and increased hair cortisol concentration at admission (index of accumulated stress load within a month before IS; β0=3.41; β=-0.05; p=0.08). The data support the hypothesis suggesting predisposition to PSD and PCI and multi hit scenarios of their pathogenesis with IS providing a final hit.

Introduction: Outcome measures using telerehabilitation (TR) in the context of post-stroke rehabilitation is an area of emerging research. The current review assesses the literature related to TR for patients requiring post-stroke rehabilitation. The purpose of this study additionally is to survey the outcome measures used in TR studies and to define which parts of the International Organization of Functioning are measured in trials. Methods: TR studies were searched in Cochrane Central Register of Controlled Trials, PubMed, Embase, Scopus, Google Scholar, and Web of Science from 2016 to June 2023. Two reviewers individually assessed the full text. Disagreements about inclusion or exclusion were determined by consensus or by checking with a third reviewer. Results: A total of 24 studies were included in the current review. The results were synthesized and reported considering the implications of the results within clinical practice, areas of investigation, and strategic implementation. Conclusions: The current scoping review recognized a wide range of outcome measures used in TR studies and helped elucidate gaps in the current use of outcome measures in the literature. The scoping review also informs researchers and end users (i.e. clinicians and policymakers) regarding the most suitable outcome measures for TR.

The fusion of surface-modified steel with tungsten carbide (WC) and NiCrBSi powder through laser metal deposition has emerged as a formidable strategy for fortifying components against wear and corrosion in extreme operating environments. Meticulous selection of WC content, innovative pre-alloying techniques, and precise control of laser metal deposition profoundly influence the mechanical properties and microstructural evolution of WC-NiCrBSi coatings applied to surface-enriched commercial alloy steel (805M2, 832M13, and 827M40). These tailored coatings exhibit exceptional resilience, ideal for harsh industrial settings in Oil and gas drilling, petrochemical, and Mining sectors. Advanced materials testing techniques, including scanning electron microscopy, light optical microscopies, and microhardness testing, unveil the innate hardness attributes, with findings highlighting the unassailable fortitude of the Mixed matrix layer's side face. The amalgamation of these testing methodologies with laser metal deposition promises an unparalleled path to extend the operational lifespan of critical components in challenging working conditions. The research horizon for WC-NiCrBSi coatings remains broad, with the potential to enhance durability, operational efficiency, and cost-effectiveness across diverse applications.

This paper delves into the essential role of local communities in mitigating climate change in the post-pandemic landscape, with a specific focus on Barangay Acmac, Iligan City, Philippines. Employing a qualitative research approach, the study integrates in-depth literature reviews, informal interviews with participants (B-Part 1 to B-Part 20), meticulous observations, and thematic analysis. The research has uncovered crucial insights, including variations in community climate change awareness that emphasize the necessity of comprehensive education and awareness campaigns. It highlights the significance of community-driven initiatives, adaptation, and resilience as key elements in addressing climate change. Collaborative efforts between local government officials and the community are showcased as effective instruments of climate change mitigation, yet challenges persist, including addressing the perceived powerlessness of some community members. The methodology, participants, and theoretical framework offer a robust foundation for exploring community responses to climate change. Drawing from a diverse theoretical framework, this study presents a comprehensive understanding of the climate change and pandemic intersection. The findings firmly establish that local communities are pivotal players in the global endeavor to mitigate climate change, underscoring the need for collective action, extensive education, and shared responsibility. The post-pandemic era presents a unique opportunity for local communities, policymakers, barangay officials, and residents to champion climate education, foster community-driven initiatives, and empower individuals to enact change at the grassroots level. The collaborative spirit observed in Barangay Acmac in 2022 serves as a model for communities worldwide, offering a blueprint for addressing similar challenges. Overall, this paper concludes with a resounding call to action, advocating for the recognition of local communities as the driving force in climate change mitigation, stressing that the power to combat climate change resides within these communities. The time for action is now, and local communities are the catalysts of this essential mission.

In the ever-evolving landscape of higher education, the shift to hybrid teaching approaches has introduced novel challenges and opportunities for both educators and students. This qualitative study, grounded in a robust theoretical framework, combines in-depth literature reviews, informal interviews, observations, and thematic analysis to explore the multifaceted dynamics of hybrid language learning within a College of Arts and Sciences. By investigating the experiences of twenty students (referred to as 'S-Part 1' to 'S-Part 20'), the research delves into the core theme of 'Teacher-Student Interaction in Higher Education Institutions' and unpacks nine additional themes: 'Adaptability and Resilience,' 'Flexibility and Autonomy,' 'Connectivity Challenges,' 'Feelings of Isolation,' 'Technology Competence,' 'Personalized Learning,' 'Resource Accessibility,' 'Support Mechanisms,' and 'Positive Learning Experiences.' In this study, these themes encapsulate the diverse experiences and challenges encountered by teachers and college students as they navigate the evolving educational landscape. The insights derived from the study are underpinned by a robust theoretical framework and complemented by existing scholarly literature. As we delve into these themes, it becomes evident that they shed light on not only the intricacies of hybrid language learning but also the broader educational context, offering valuable guidance for educators, institutions, students, and researchers. Based on the ample results, recommendations are presented for school administrators, teachers, students, and future researchers to enhance the quality of hybrid teaching and learning, aligning it with the demands of the post-academic era. Overall, this study contributes to the ongoing dialogue on innovative pedagogical strategies and responsive educational environments, underlining the significance of teacher-student interaction in the new normal of higher education.

Post-operative pain is the unpleasant sensory and emotional experience after surgery, its origin being both the inflammatory reaction induced by the surgical trauma on the abdominal wall, and the splanchnic pain, induced by the activation of nociceptors of the viscera, which are highly sensi-tive to distension, ischemia and inflammation. Nowadays, it is well recognized that there is a close relationship between the gut microbiome and pain perception, and that microbiome is highly af-fected by both anaesthesia and surgical manipulation. Thus, efforts to restore the disturbed micro-biome by supplementation with beneficial bacteria, namely probiotics, seems to be effective. In this article the knowledge gained mainly from experimental research on this topic is analyzed, the con-cluding message being that each probiotic strain works in its own way towards pain relief.

Regional anesthesia in postoperative pain management have developed in recent years, especially with the advent of fascial plane blocks. This study aims to compare the ultrasound-guided bilateral erector spinae plane block (ESPB) versus bilateral transversus abdominis plane block (TAPB) on postoperative analgesia after laparoscopic or robotic urologic surgery. This was a retrospective observational study; 97 patients (ESPB-group) received bilateral ultrasound-guided ESPB with 20 mL of ropivacaine 0.375% plus 0.5 mcg/kg of dexmedetomidine in each side at the level of T7-T9, and 93 patients (TAPB-group) received bilateral ultrasound-guided TAPB with ropivacaine 0.375% or 0.25%. The primary outcome was post-operative numeric rating scale (NRS) pain score, which was significantly lower in the ESPB-group on postoperative days 0, 2, and 3 (p=0.012, p=0.016 and p=0.004). Concerning the secondary outcomes, consumption of ropivacaine was significantly lower in ESPB-group (p<0.001) and the total amount of analgesic rescue doses was significantly lower in the ESPB-group than TAPB-group in postoperative days from 2 to 4 (1 vs 3, p>0.001). Incidence of postoperative nausea and vomiting was higher in the TAPB-group and no block related complications were observed. We conclude that ESPB provide better postoperative pain control with less consumption of local anesthetic and less total rescue analgesic therapies.

Data mining techniques have garnered significant attention within the realm of education. However, the procurement of ample student data poses a formidable challenge. In response to this challenge, we present a student dataset characterized by its size and distinctive attributes. This dataset encompasses various task-related topics interconnected through a learning pathway, thereby enabling researchers to delve into the data from novel perspectives. Moreover, it encompasses extensive longitudinal student behavioral data, a rarity that adds substantial value. Spanning the years from 2010 to 2021, our dataset comprises a cohort of 7,933 students, 64,344 test scores, and 183,390 behavior records, solidifying its status as a valuable resource for educational research. In our experiments, we achieved successful predictions of students' test outcomes based on behavioral learning data. The strengths of our dataset render it apt for analyzing the nexus between student conduct and academic performance, crafting personalized learning recommendations, and pursuing various other research pursuits.

During virus outbreaks in the recent past web behavior mining, modeling, and analysis have served as means to examine, explore, interpret, assess, and forecast the worldwide perception, readiness, reactions, and response linked to these virus outbreaks. The recent outbreak of the Marburg Virus disease (MVD), the high fatality rate of MVD, and the conspiracy theory linking the FEMA alert signal in the United States on October 4, 2023, with MVD and a zombie outbreak, resulted in a diverse range of reactions in the general public which has transpired in a surge in web behavior in this context. This resulted in “Marburg Virus” featuring in the list of the top trending topics on Twitter on October 3, 2023, and “Emergency Alert System” and “Zombie” featuring in the list of top trending topics on Twitter on October 4, 2023. No prior work in this field has mined and analyzed the emerging trends in web behavior in this context. The work presented in this paper aims to address this research gap and makes multiple scientific contributions to this field. First, it presents the results of performing time series forecasting of the search interests related to MVD emerging from 216 different regions on a global scale using ARIMA, LSTM, and Autocorrelation. The results of this analysis present the optimal model for forecasting web behavior related to MVD in each of these regions. Second, the correlation between search interests related to MVD and search interests related to zombies (in the context of this conspiracy theory) was investigated. The findings show that there were several regions where there was a statistically significant correlation between MVD-related searches and zombie-related searches (in the context of this conspiracy theory) on Google on October 4, 2023. Finally, the correlation between zombie-related searches (in the context of this conspiracy theory) in the United States and other regions was investigated. This analysis helped to identify those regions where this correlation was statistically significant.

Arginine shows Jekyll and Hyde behavior in several respects. It participates in protein folding via ionic and H-bonds and cation-pi interactions; the charge and hydrophobicity of its side chain makes it a disorder-promoting amino acid. Its methylation in histones; RNA binding proteins; chaperones regulates several cellular processes. The arginine-centric modifications are important in oncogenesis and as biomarkers in several cardiovascular diseases. The cross-links involving arginine in collagen and cornea are involved in pathogenesis of tissues but have also been useful in tissue engineering and wound-dressing materials. Arginine is a part of active site of several enzymes such as GTPases, peroxidases, and sulfotransferases. Its metabolic importance is obvious as it is involved in production of urea, NO, ornithine and citrulline. It can form unusual functional structures such as molecular tweezers in vitro and sprockets which engage DNA chains as part of histones in vivo. It has been used in design of cell-penetrating peptides as drugs. Arginine has been used as an excipient in both solid and injectable drug formulations; its role in suppressing opalescence due to liquid-liquid phase separation is particularly very promising. It has been known as a suppressor of protein aggregation during protein refolding. It has proved its usefulness in protein bioseparation processes like ion-exchange, hydrophobic and affinity chromatographies. Arginine is an amino acid, whose importance in biological sciences and biotechnology continues to grow in diverse ways.

Keywords: Post-Stroke; Hyperbaric oxygen therapy; Sequelae; Feasibility; Out-patient.

Background: Post-Covid condition can reduce activity and quality of life, resulting in a significant socioeconomic and health burden. Understanding its impact on patients' health is important for the development of personalized rehabilitation interventions. An independent association between obesity and post-covid condition was found because of complications and comorbidities. Methods: Sixteen patients with obesity and post-COVID symptoms (i.e., dyspnea, pain, poor sleep quality, muscle fatigue) admitted to the Istituto Auxologico Italiano, Piancavallo (VB), Italy, were recruited for a four-week rehabilitation program including conventional exercise therapy, nutritional intervention, psychological support and whole-body cryostimulation (WBC). Results: All participants attended all sessions of the program. Anthropometric data showed statistically significant changes in weight, waist circumference and body mass index. Biochemical analyses showed significant reductions in lipid and inflammatory profiles. There was a significant improvement in physical performance, reduction in pain and improvement in psychological well-being. Conclusion: A multidisciplinary rehabilitation protocol including WBC designed for patients with obesity and post-covid condition is safe and feasible. The overall improvements demonstrate that multidisciplinary rehabilitation was effective on post COVID patients and suggest that the use of WBC is safe and could play a role as a booster in rehabilitation programs.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate the tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) the tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving the tour routes, the transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

With the rapid growth of large language models (LLMs), there is increasing demand for memory and computation for LLMs. Recent efforts on post-training pruning of LLMs aim to reduce the model size and computation, yet the performance is still sub-optimal. In this paper, we present a plug-and-play solution for post-training pruning of LLMs. The proposed solution has two innovative components: 1) **Relative Importance and Activations** (RIA), a new pruning metric that jointly considers the weight and activations efficiently on LLMs; and 2) **Channel Permutation**, a new approach to maximally preserve important weights under N:M sparsity. The proposed two components can be readily combined to further enhance the N:M structuredly pruned LLMs. Our empirical experiments show that RIA alone can already surpass all existing post-training pruning methods on prevalent LLMs, e.g., LLaMA ranging from 7B to 65B. Furthermore, N:M structured pruning with channel permutation can even outperform the original LLaMA2 70B on zero-shot tasks, together with practical speed-up on specific hardware.

At the beginning of 2019, the petroleum crisis impacted many economies dependent on this industry. The Mexican government started programs to identify points and government officials involved in the gasoline stealing from PEMEX (Petróleos Mexicanos), the country’s leading government petroleum company. The programs consisted of supervising and monitoring the Mexican country network of gasoline ducts to detect points where gasoline was being stolen. Consequently, large urban regions faced a lack and shortage of gasoline. This situation generated several reactions in social media and many open data in news media. Although the government provided open data about stealing gasoline locations related to crimes, it did not analyze the collected data to identify patterns, insights, and the spatio-temporal characterization of this phenomenon. This paper presents a study to deal with the regional semantics described in the social media locations of gasoline stealing. Thus, a framework to discover the trends that emerge from social media and how it is correlated with the government’s open data is also presented—the proposed methodology used machine learning techniques based on linguistic and semantic technologies. The analysis was applied to a dataset of 24,317 geo-referenced tweets. The obtained results reflected the Mexican thinking opinion regarding discovered social topics, polarization maps, and regional insights. According to discovered trends, there were long fuel lines between 1.5 and 5 kilometers (on average) at fuel stations in different Mexican states.

The recognition of coal-rock interface is very crucial for the research in the intelligent production of coal mine. This study investigates the application of terahertz time-domain spectroscopy in the recognition of coal-rock interface, including the identification of coal-rock and coal-rock mixtures, as well as the accurate characterization of coal seam thickness. Terahertz detection was used to obtain the optical parameter information of the pressed pellets prepared by mixing two different kinds of coal and two kinds of rock. Based on the experiment results, the database was established for the identification of coal-rock interfaces in coal mining machines. The terahertz detection was performed on 10 different kinds of sheet anthracite with different thickness, and the terahertz spectra of coal seams with different thickness were simulated and calculated by using simulation software, which can accurately obtain the thickness of coal seams and provide effective mining thickness parameters for coal seam mining. Through the experiment and simulation, the terahertz time-domain spectroscopy technology has a promising application prospect in the identification of coal-rock interface.

As the oil industry increasingly turns to unconventional low-permeability and low-porosity reservoirs, precise post-fracture production prediction is a pivotal instrument in investment de-cision-making, formulation of energy policies, and promotion of environmental assessments. Nevertheless, despite extensive research spanning decades, the precise post-fracture production prediction based on logging parameters remains an intricate task. In this study, we gathered ex-tensive logging data and segmented the post-frac gas production during well testing on the first day to enrich the dataset. Nine pipelines were then architected using various techniques of data preprocessing, feature extraction, and advanced machine learning models. Hyperparameter op-timization was executed via the GridsearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), and root mean square error (RMSE) were invoked. Among the several pipelines explored, the PS-NN exhibited excellent predictive capability in specific reservoir contexts (an R2 value of 0.94 and an RMSE of 48.15). In essence, integrating machine learning with logging parameters effectively assesses reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties en-demic to reservoir exploration but also equips petroleum engineers with monitoring on reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides res-ervoir engineers with an efficient way of reservoir performance oversight.

Post-harvest handling and ripening techniques have an impact on peach quality and shelf life, which has a big impact on consumer satisfaction and market competitiveness. This review paper examines recent advancements in ripening techniques and post-harvest technologies with the goal of improving peach fruit quality and sustainability. The factors impacting fruit quality after harvest and the physiological changes that occur throughout peach ripening are fully explained. For maintaining peach freshness and reducing losses, novel handling methods like modified atmosphere packaging (MAP) and controlled atmosphere storage (CAS) have been investigated. The study explores the possibilities of nanotechnology applications and low-temperature storage for prolonging shelf life while maintaining texture, flavor, and aroma. Examining the effectiveness and waste reduction potential of automation and mechanization in post-harvest activities. The paper also discusses ethylene-based and non-ethylene-based ripening agents, as well as innovative techniques including gene editing and RNAi technology for controlled and delayed ripening. Analyses are done on how these technologies affect the sensory qualities and nutrient profiles of peaches. The study emphasizes the significance of sustainable practices in the peach industry by focusing on waste reduction, resource efficiency, and circular economy integration. Post-harvest technologies' potential environmental consequences have been taken into consideration and the paper encourages more study and cooperation to increase sustainability.

The measures related to climate change and international technology transfer have been closely intervened as most international environmental instruments, including the United Nations Framework Convention on Climate Change and Kyoto Protocol as well as Paris Agreement which contain the provisions concerning environmentally friendly technology transfer. However, technologies have not been transferred adequately owing to the flaws in the relevant provisions and due to the fact that most technologies are possessed by transnational corporations and other private sectors. In order to undertake the commitment by the governments of developed countries and at the same time, to conform the commercial activities of their respective private sectors to the level of promised international obligation, an uniform international technology transfer agreement needs to be established separately, particularly under the World Trade Organization regime in Post Pairs-Agreement era. This paper first explores the defects and challenges found in provisions related to technology transfer in existing environmental agreements, and examines the possibilities of concluding an international technology transfer agreement both from theoretical and practical perspectives. climate change;environmentally sound technology;international technology transfer;Post Paris-Agreement Era

The crisis of mining-industrial activities in Western Europe since the middle of the 20th century caused the cessation of mining, triggering a structural crisis. It is necessary to look for alternatives, among which tourist activities based on mining heritage stand out. However, there are unattractive peripheral spaces in which new activities encounter obstacles to their development, facing the post-industrial and rural crises. The Riotinto Mining Basin (Huelva, Andalusia) represents an example of such spaces with an enormous cultural heritage. A central agent, the Río Tinto Foundation, has opted to enhance tourism value, while the mine has recently been reactivated. The objective of this research is to analyze the contribution of mining tourism to sustainable rural development. The methodology applied has been mixed based on conducting interviews and analyzing secondary data. The results are (a) achievement of the tourism value of the mining heritage; (b) difficulties for tourism to overcome its peripheral condition; (c) relative contribution of tourism to the improvement of the territorial image; (d) lack of coordination among stakeholders; (e) limited contribution of tourism to sustainable rural development, moving to a secondary economic role after the reopening of the mine.

The purpose of this study was to analyze the influence of Chitosan 0.2% in various final cleaning methods on the bond strength of fiberglass post (FP) to intrarradicular dentin. Ninety bovine incisors were sectioned to obtain root remnants measuring 18 mm in length. The roots were divided: G1: EDTA 17%; G2: EDTA 17% + PUI; G3: EDTA 17% + EA; G4: EDTA 17% + XPF; G5: Chitosan 2%; G6: Chitosan 2% + PUI; G7: Chitosan 2% + EA; G8: Chitosan 2% +XPF. After carrying out the cleaning methods, the posts were installed, and the root cleaved to to generate two disks from each root third. Bond strength values (MPa) obtained from the micro push-out test data were assessed by Kruskal-Wallis and Dwass-Steel-Critchlow-Fligner tests for multiple comparisons (α = 5%). Differences were observed in the cervical third between G1 and G8 (p=0.038), G4 and G8 (p=0.003), G6 and G8 (p=0.049), and Control and G8 (p=0.019). The final cleaning method influenced the adhesion strength of cemented FP to intrarradicular dentin. Chitosan 0.2% + XPF positively influenced adhesion strength, with the highest values in the cervical third.

Considering the importance of assessing the impacts resulting from a sport career, this study aimed at developing and validating a semi-structure interview guide suitable for quantifying the socio-demographic and epidemiological profile of former professional football players. Based on the theoretical frameworks and several methodological procedures, an interview guide was de-veloped, consisting of 3 areas of conceptual organization (A1. Biographical data; A2. Career data; and A3. Post-Career Transition data) and 8 data collection categories (C1. Personal data; C2. Pro-fessional data; C3. Socio-demographic pathway in the post-career; epidemiological pathway; C4. Epidemiological pathway; C5. Moment of leaving the career; C6. Socio-demographic pathway in post-career; C7. Epidemiological pathway in the post-career; and C8. Perceptions on post-career planning). The construction and validation of the interview guide following 4 steps: Ad hoc con-struction of the interview guide (step 1); Review of the interview guide by a panel of experts (step 2); Definition of procedures and protocol for the application of the interview (step 3); Application of the pilot study for face validation of the interview guide (step 4). Thus, in procedural terms, four stages were considered for the construction and validation of the interview guide, namely the Ad hoc construction of the interview guide (i), the review of the in-terview guide by a panel of experts (ii), definition of procedures and protocol for the application of the interview (iii), and the application of the pilot study for the face validation of the interview guide (iv). The results showed that the interview guide for the study of the impacts of the sports careers on the quality of life of Portuguese former football players shows reliability for the collec-tion of qualitative and quantitative information from the respective content analysis. The use of the interview guide characterizes the path of former player, providing information and knowledge on the socio-demographic and epidemiological impact factors resulting from their post-career (sports retirement).

Actively combating post-harvest food spoilage and waste can dramatically increase the efficiency of food utilization worldwide. In climacteric fruits, chemical treatments such as 1-MCP are an effective way of reducing post-harvest spoilage and waste by inhibiting the fruit’s ability to perceive ethylene. 1-MCP treatment is increasingly being used to explore the complex nature of ripening physiology at a fundamental level, however, differences in application and quantitation methods create difficulties in comparing conclusions across studies. Here we report an effective and reproducible method for 1-MCP application and quantitation for small-medium sized research applications. By use of surrogate alkene standards 1-butene and cis-2-butene, the highly volatile and elusive 1-MCP molecule can be identified and quantified by gas chromatography and subsequent standard curves may be developed. It is hoped that the methodology outlined here can help standardize consistent 1-MCP application for post-harvest research without excessive investment in specialized equipment.

The embryonic epicardium originates from the proepicardium, an extracardiac primordium constituted by a cluster of mesothelial cells. In early embryos, the embryonic epicardium is characterized by a squamous cell epithelium resting on the myocardium surface. Subsequently, it invades the subepicardial space and thereafter the embryonic myocardium by means of epithelial-mesenchymal transition. Within the myocardium, epicardial-derived cells present multilineage potential, later differentiating into smooth muscle cells and contributing both to coronary vasculature and cardiac fibroblasts in the mature heart. Over the last decades, we have progressively increased our understanding of those cellular and molecular mechanisms driving proepicardial/embryonic epicardium formation. This study provides a state-of-the-art review of the transcriptional and emerging post-transcriptional mechanisms involved in the formation and differentiation of the embryonic epicardium.

The paper investigates into the intricacies of semiconductor manufacturing, a highly complex process entailing a wide array of subprocesses and diverse equipment. Semiconductors are miniaturized integrated circuits comprising numerous components. The semiconductor manufacturing process begins with the thin disc-shaped silicon wafers. On each wafer, up to thousands of identical chips can be prepared depending upon the diameter of the wafer to build up the circuits layer by layer in a wafer fab. The size of the semiconductors requires a high number of units to be produced, thus necessitating a large amount of data to control for improving the semiconductor manufacturing process. Therefore, the collection and analysis of the equipment data, process data, and machine history data throughout the manufacturing process are required to diagnose faults, monitor the process, and manage the manufacturing process effectively. This research is focused on improving the semiconductor manufacturing process through a rigorous analysis of collected manufacturing process data, employing statistical process control (SPC), data mining techniques, and data-driven decision models. The project's primary objective is to increase the manufacturing process stability and productivity by utilizing the latest data-driven technologies in the scientific community. A structured review was undertaken, exploring contemporary data-driven methodologies in semiconductor manufacturing process improvement, specifically pertaining to process capability, product yield rate, and process stability. This review accentuates a comprehensive evaluation of data-driven methodologies applicable to conventional semiconductor manufacturing facilities, aiming to drive substantial process improvements. It features a detailed demonstration facilitating the selection of optimal semiconductor manufacturing processes to enhance overall operational performance. This study of process improvement in the semiconductor manufacturing steps through the application of data-driven methodologies will be effective in delivering advanced, real-time, and proactive control decisions throughout the manufacturing facilities. This endeavor is expected to promptly provide critical insights for enterprise manufacturing decision-makers to reduce manufacturing cycle time, improve the product yield rate, and increase the overall efficiency of the manufacturing process.

Carbon nanomaterial is widely used in structural health monitoring due to the advantage of sensitivity and good mechanical properties. This study presents a novel approach employing carbon nanocomposite materials (CNM) to characterize deformation and damage evolution in physical modelling. As the primary measurement method, the CNM is used to investigate the deformation characteristics of a 200-400 m thick sandstone bed at a 1 km deep longwall mine. The sandstone unit is identified as an ultra-thick key stratum (UTKS), with its thicknesses varying across different mining panels of the UTKS. The results of CNM monitoring show that the UTKS remains stable even after a consecutive excavation of 900 m in width. This stability impedes the upward propagation of overlying strata failure, leading to minimal surface subsidence. The study demonstrates the huge potential of CNM in the mining area, which can be useful for investigating material damage in physical modelling studies. The findings suggest that the cumulative extraction width in individual mining areas of the mine should be controlled to avoid a sudden collapse of the UTKS, and that special attention should be paid to where the UTKS's thickness changes substantially. The substantial variation in UTKS thickness significantly impacts the pattern of overburden subsidence.

This study intricately explores the evolving tapestry of Christmas celebrations in a post-pandemic era, where tradition delicately intertwines with technology. The literature review presents a global panorama of Christmas observances, delving into varied religious perspectives. Within this exploration, a Southeast Asian country discreetly initiates its festivities as early as September—a nuanced response to the profound significance of Christmas. Navigating the digital age, the paper dissects the impact of virtual gatherings, the surge in e-commerce, and digital church services on festive traditions. Employing diverse research methods, including thematic analysis, nuanced insights are synthesized from extensive literature reviews, interviews, and observations. Scrutinizing challenges posed by the digital divide, the erosion of personal connections in virtual gatherings, and sustainability concerns in online celebrations, the qualitative research methodology reveals the interplay between tradition and technology. The paper contemplates the future of Christmas in this transformative era, offering implications for future celebrations, technology developers, policymakers, and beyond. This endeavor invites contemplation on the dynamic interplay shaping the festive landscape and prompting reflection on future celebrations.

Wide-scale commercialization of cultured meat, produced from in vitro-grown animal stem cells, is still a long way off because of technical, regulatory and, above all, social acceptability constraints. As a result, despite the advancement of knowledge, it is difficult to predict whether this innovation will be commonly accepted. The concept of media framing is key to better understanding individuals’ decision-making and mental interpretative patterns in relation to cultured meat adoption. This research therefore analyzes the role of media framing (namely the social media platform Twitter) on the components of consumer attitudes (cognitive, affective, and conative) in relation to cultured meat. A total of 23 020 publications and 38 531 comments were analyzed qualitatively (content analysis) and quantitatively (MANOVA). This study showed that media-framed posts influenced consumer attitudes more than did non-media-framed posts. Although the results indicate that the different types of media framing (ethical, intrinsic, informational, and belief) do not exert the same influence on each attitude component, they suggest that posts combining the ethical, intrinsic, and informational media frames have a greater impact on the acceptability of cultured meat and that the belief frame is equally important, particularly for the behavioral component. Relevant implications can be drawn for authorities and businesses on the use of differentiated education and marketing strategies

Qualitative comparative analysis (QCA) was developed by Charles Ragin in 1987 for the comparative analysis of small data sets. The method has become widespread in sociological and economic research. There are examples of successful use of QCA in the field of medicine and epidemiology. The purpose of this review is to describe the key stages of QCA with a discussion the application of this method to the analysis of medical and epidemiological data.

Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME/CFS) is an acquired disease with significant morbidity that affects both children and adults. Effective tools to assess functional capacity (FC) are severely lacking which has significant consequences for timely diagnosis, assessments for patient disability benefits and assessing the impact and effectiveness of interventions. In interventional research the inability to assess FC can result in an incomplete assessment of the potential effect of the intervention. Specifically of concern is that if an intervention is effective in reducing symptom load, patients may increase their activity level to reach a pre-intervention symptom load. Thus, if FC is not accurately assessed, beneficial treatment outcomes may be missed. To address this issue, using extensive, repeated patient feedback we have developed a new questionnaire, FUNCAP, to achieve optimal FC assessment in ME/CFS patients. The questionnaire covers eight domains and activity types: A. Personal hygiene / basic functions, B. Walking / movement, C. Being upright, D. Activities in the home, E. Communication, F. Activities outside the home, G. Reactions to light and sound, and H. Concentration. Through five rounds of anonymous web-based surveys and a further test - retest validation round, two versions of the questionnaire were developed; a longer version comprising 55 questions (FUNCAP55) to improve diagnostic and disability benefit/ insurance FC assessments and a shorter version (FUNCAP27) for interventional research and less extensive FC assessments. FUNCAP may also be useful in other conditions where fatigue and PEM is present, such as Long Covid.

In conclusion, this qualitative exploration has unveiled the profound and essential impact of music on psychological well-being, especially in the post-pandemic world. Through in-depth literature reviews, informal interviews, and observations with thirty CAS participants from SMC, the researcher uncovered ten salient themes that collectively illustrate music's multifaceted role as a potent remedy. These findings showcase how music serves as an emotional outlet, a cognitive enhancer, and a source of inspiration. The emotional depth and spiritual resonance participants associate with music underscore its capacity to address diverse human needs, making it an indispensable tool in navigating the complexities of our post-pandemic reality. Moreover, the cognitive benefits observed, such as improved concentration and focus, are particularly pertinent in the context of remote work and education, highlighting music's necessity in our daily lives. Additionally, this study emphasizes the vital role of virtual music communities in fostering social connections, even amidst physical isolation, further underscoring the enduring relevance of music in these challenging times. This research contributes to the expanding knowledge of music's impact on well-being, offering a holistic perspective encompassing spiritual, emotional, social, and cognitive dimensions. It enriches existing music psychology theories and invites further exploration into the mechanisms underpinning music's diverse effects. These insights have practical implications for fields such as mental health, education, and remote work, where music can be utilized as an essential tool for stress reduction and emotional regulation. This is highlighted further in the Suggested songs that can help sought the mind, body, spirit and soul. Looking ahead, future research could delve deeper into the long-term impact of music engagement on well-being and explore the universality of music's benefits through cross-cultural studies. Overall, music, as illuminated by this study, stands as a timeless and indispensable companion, offering solace, inspiration, vitality, and connection in the face of any contemporary challenges.

Sensor fusion algorithms and models have been widely used in recent times. Although research evidence has informed the use of sensor fusion models in diverse applications, there is room for improvement, especially in home-based health monitoring applications which require less supervision and technical knowledge of users. The present work compares data mining-based fusion software packages such as RapidMiner Studio, Anaconda, Weka, and Orange, and proposes a data fusion framework suitable for in-home applications. 574 privacy-friendly (binary) images and 1,722 datasets gleaned from thermal and Radar sensing solutions respectively, were fused using the software packages on instances of homogeneous and heterogeneous data aggregation. Experimental results indicated that the proposed fusion framework achieved an average Classification Accuracy of 84.7% and 95.7% on homogeneous and heterogeneous datasets respectively, with the help of data mining and machine learning models such as Naïve Bayes, Decision Tree, Neural Network, Random Forest, Stochastic Gradient Descent, Support Vector Machine, K-Nearest Neighbours and CN2 induction. Further evaluation of the sensor data fusion framework based on cross validation of features indicated average values of 94.4% for Classification Accuracy, 95.7% Precision and 96.4% for Recall.

Background: As the world tends to recover from the crisis created by the COVID-19 pandemic, vaccines have served as one of the most valuable tools of combat and large-scale immunization has helped to tide over the catastrophe. However, several reports of post -vaccination neurological complications around the globe have surfaced up in recent literature. This study was conducted with an aim to describe the spectrum of neurological ailments requiring hospitalization following COVID-19 vaccination.Methods: An ambispective observational study was carried out from March 2021 to February 2022 at a tertiary care institute with 25 patients who satisfied the inclusion criteria of a new onset neurological illness requiring hospitalization within 4 days to 42 days of vaccination. The patients were duly followed upto months after discharge.Results: The median age of the sample was 36 years and the median latency of onset of neurological events was 14 days. Guillain-Barré syndrome was documented in 11 patients; majority were acute motor axonal neuropathy (45.45%) followed by acute inflammatory demyelinating polyradiculoneuropathy (36.36%) and acute motor sensory axonal neuropathy (18.18%). Central nervous system demyelination was reported in 9 patients; two patients had acute disseminated encephalomyelitis, 2 patients were diagnosed with myelin oligodendrocyte glycoprotein antibody-associated disease, one patient with aquaporin-4 positive neuromyelitis optica spectrum disorder , and the rest were labelled as seronegative central nervous system demyelination. Vascular events were noted in 5 patients comprising of 2 cases each of cerebral venous sinus thrombosis and intracerebral hemorrhage and a case of Moyamoya angiopathy. All patients were conservatively managed and had a complete to partial recovery suggestive of a favorable outcome after 3 months. Conclusion: The pathomechanisms of post -vaccination neurological complications is yet to be elucidatedand any causal association attributable to vaccination warrants further research. Compared to the enormity of the vaccinated population, the adverse effects are miniscule to hinder and discourage vaccination.

Background Posttraumatic stress disorder (PTSD) is a complex condition that represents a significant burden in terms of individual disability and societal costs. Despite decades of research investigating treatment options, PTSD remains a major cause of quality-of-life impairment. We hypothesized that patients with PTSD might benefit from peripheral somatosensory stimulation (PSS) therapy. Methods Six adult patients with clinically diagnosed PTSD were enrolled to undergo daily PSS therapy over a 4-week period. Patients completed two surveys evaluating satisfaction with treatment and overall well-being (Survey 1) and severity of PTSD symptoms (Survey 2). Survey 1 was completed weekly during the course of the study. Survey 2 was based on the 9-question National Stressful Events Survey PTSD Short Scale (NSESSS) and was completed as a baseline prior to initiation of therapy and then at the conclusion of the trial. All data were analyzed by an independent statistician. Results Six male patients were enrolled in the study; all completed the trial. All patients demonstrated a decrease in symptoms within one week of initiation of therapy. This benefit was sustained and appeared to further improve over the course of the trial. For Survey 1, the overall median scores demonstrated a significant time-dependent improvement across measurement times (p < 0.001). For Survey 2, patients had statistically significant improvements from baseline regarding feelings of being emotionally upset and being overly alert. Results from a cumulative link mixed model demonstrated that treatment yielded a 38.2-fold higher likelihood of transitioning from a higher PTSD score at baseline to a lower (improved) score at week 4. No adverse events were described by the patients. Conclusions PSS stimulation appeared to improve symptoms in all six patients with PTSD symptoms in this trial. Patients had unanimous and clinically meaningful improvement in overall PTSD symptoms with treatment. By week 4, all patients responded that they enjoyed the treatment and would like to keep their device. We suggest that further investigation into the potential usefulness of PSS therapy in patients with PTSD is warranted.

Mining activities often generate important amounts of extractive waste, and as a consequence, environmental impacts that affects all factors to a greater or lesser extent. Depending on a variety of variables, the impact can be permanent or temporary, reversible or irreversible, negative or positive. This study conducted research on the status of closure and remediation processes of mining areas in Romania, specifically in the counties of Maramureș, Suceava, Harghita, Alba, Hunedoara, and Caraș-Severin. Furthermore, based on the type and level of pollution, the degree of application of remediation techniques for water and soil pollution in the investigated mining areas was studied. From the analysed information, it is evident that although the closure and remediation process started in Romania over 20 years ago, unfortunately, to this day, the technical projects, technical assistance, and execution of closure and remediation works have not yet completely solved the complex environmental issues in the mining sector. Most of the tailing ponds and waste piles of former mines continue to pose permanent specific risk to the environment and the population. This study concludes that the mining sector in Romania, although it has the necessary techniques and technologies for the ecological rehabilitation of degraded lands related to the Extractive Waste Facilities and the elimination of negative impacts on the environment and public health, has not yet been able to fully concretize its remediation efforts.