We show that the longest length N of a string, composed according to the principles of assembly theory of b different basic symbols, which has the assembly index of N-1 is given by b²+b+1 and this odd-length string is nearly balanced.

Biomass fuel pellets exhibit variations in quality due to differences in feedstock sources. Moni-toring processing parameters is crucial for converting biomass into high-quality energetic pellets. This study examined the effects of selected parameters on the properties of cocoa pod husk pellets produced using a modified pelleting machine. The pellets were produced by varying the com-pression ratio (0.8, 1.0, 1.2), moisture content (10, 15, 20%) and binder quantity (0, 2.5, 5 wt%). A Box-Behnken design was employed to structure the experiment. The pellets were analyzed for density, proximate composition (moisture, volatile matter, fixed carbon, and ash contents), and higher heating value to assess their quality. The results were subjected to ANOVA at a 95% con-fidence level. The cocoa pod husk pellets had a bulk density of 0.28-0.41 g/cm³, moisture content of 13.22-19.30% (db), volatile matter of 48.61-57.83%, fixed carbon of 21.25-23.10%, ash content of 3.49-12.99%, and higher heating values of 18.28-19.30 MJ/kg. Significant differences were observed at the 95% confidence level (p≤0.05). Compression ratio, binder quantity and moisture content were found to affect the physicochemical properties of the pellets.

The primary therapeutic method for correcting hyperglycemia today is diet therapy. Lipids are not only a source of nutrients but can also act as initiators of adipocyte differentiation in the fetus, which explains the development of fetal macrosomia and future metabolic disorders in children born to mothers with gestational diabetes mellitus (GDM). Changes in the profile of circulating lipids in the maternal bloodstream, depending on adherence to a rational diet among mothers with GDM and the development of fetal macrosomia, is a complex and not fully understood process. The aim of the study was to examine the characteristics of the lipid profile in the blood plasma of pregnant women with GDM in all trimesters of pregnancy based on adherence to diet therapy. The design of the clinical part of the work was carried out within the framework of a 'case-control' study.The study included 110 women, 80 of whom were in the control group, 20 in the group with GDM adhering to the diet, and 10 in the group with GDM not adhering to the diet. The laboratory part was conducted as part of a longitudinal dynamic study with venous blood samples taken at three points: 11-13, 24-26, and 30-32 weeks of pregnancy.A significant impact of diet therapy on the blood lipid composition throughout pregnancy was demonstrated, starting as early as the first trimester. ROC analysis showed high effectiveness of the developed models with an AUC of 0.98 for the "30-32 weeks" model, with sensitivity and specificity of 1 and 0.9, respectively. An association was found between diet, maternal blood lipid composition at 32 weeks of pregnancy, and newborn weight. The direction of changes in the lipid spectrum during the development of macrosomia and diet therapy is diametrically opposed. This confirms at the molecular level that diet therapy can normalize not only carbohydrate but also lipid metabolism in the mother and fetus. Based on the obtained data, it can be suggested that after validation, the developed models could be used to refine the prognosis of macrosomia development based on the lipid profile of blood plasma at different stages of pregnancy.

Against the background of the sky, imaging and perception of aircraft are cru- cial. Among these, the location of aircrafts is not a very difficult problem in general, because that deep learning algorithms and object detection models based on convolutional neural network(CNN) are ever-evolving. In order to have a better identification of various aircrafts, or to accurately locate different types of flying targets in the sky, it becomes significant to distinguish and recognize different types of aircrafts. One question is that, distinguishing and recognizing between sub-categories of aircrafts pose great challenges. Although fine-grained recognition focuses on exploring and studying such problems, aircrafts under different sub-categories and granularities lead us to rethink the application of features. We noticed that features in swin-transformer demonstrates the under- standing and processing of images, fully showcasing the encoding and indexing of information. Through this research and proposed approach, we discovered a better understanding of features encoding and use, which are inspired by the feature encoding and computation in swin-transformer. In our paper, our ap- proach has achieved effects on features encoded graphically, manifested from the architecture design and convolutional neural network computation, and outper- forms other famous fine-graiend classification models on this issue. Not only approach we proposed has demonstrated superior performance in fine-grained aicraft classification, but also the mechanisms of the feature encoding under different sample space partitions is revealed for this issue, which provides a re- search for the representation of aircraft fineness characteristics. The relationship between representation orientation of aircraft feature information under various grained divisions, shows that the recognition of different categories according to man-made, such as aircraft, can be achieved by means of the feature represen- tations studied in this paper, for more specific defined classification tasks and various man-made targets partition criteria, which may influences the princi- ple of design for calculation and feature extraction in fine-grained classification models.

This study investigates the influence of internal factors on growth dynamics in four Cyprinus carpio varieties: three Romanian strains (Frăsinet, Ineu, and Podu Iloaiei) and the ornamental Koi variety. The research aims to elucidate variety-specific growth patterns and their implications for aquaculture and ecological management. Fish were measured for total length, maximum height, and weight at four ontogenic stages: 7 days post-hatch, summer fingerlings (0⁺), one year and summer old (1⁺), and two years and summer old (2⁺). Weight Gain (WG), Specific Growth Rate (SGR), Relative Growth Rate (RGR), Fulton's condition factor, and profile index were calculated and analyzed. Results revealed significant intervariety differences in growth performance, body shape development, and physiological condition across life stages. The Romanian varieties showed superior growth performance at later stages, while Koi exhibited unique growth patterns. Fulton's condition factor and profile index varied markedly among varieties and life stages, indicating differential energy allocation and morphological adaptations. These findings highlight the complex interplay between genetic factors and developmental processes in carp varieties, providing valuable insights for selective breeding programs, aquaculture practices, and ecological management strategies. The study underscores the importance of variety-specific approaches in carp cultivation and conservation efforts.

This study aims to explore methods for automating the replication of correlated portfolios across shares using various algorithms. The goal is to select one algorithm for implementation in a visualization tool that will facilitate portfolio building. The dynamics of the stock market provide a comprehensive view of the global economy, acting as a catalyst for stakeholders to participate and benefit various sectors financially, primarily through investments in companies that yield returns and contribute to the economy. The evaluation and comparison of these algorithms are crucial for making well-informed decisions regarding the core objectives of the study. Ultimately, a determination will be made as to whether the program can effectively analyse data from Yahoo finance to provide a quick overview of the financial market state of companies in the S&P 500 US stock prices.

In the fast-evolving landscape of web services, success relies on optimizing efficiency, reliability, and user satisfaction. Decision-making in real-world applications demands a blend of quantitative (numerical values of quality of Service factors) and qualitative data of experts’ ratings of the quality of service factors. This paper proposes an optimization technique that integrates Hesitant and Intuitionistic Fuzzy Linguistic Terms with TOPSIS, leveraging Entropy Objective weights. There is limited research on Hesitant Intuitionistic Fuzzy Linguistic terms and the need to model fuzziness, haste and intuition in data precisely from experts rating. Thus, this article introduces an Entropy-based model tailored for web service optimization. Using the WS-DREAM dataset, quantitative data was extracted and objective weights were determined through the Entropy algorithm and qualitative evaluations from five experts, employing Hesitant Intuitionistic Fuzzy Linguistic Terms, were integrated. The process involved computing criteria weights and experts' assessment of Quality of Service factors for four services (S1, S2, S3, and S4) to form the Fuzzy Decision Matrix using modified Online output software. Applying the proposed technique to a web service optimization problem validated its effectiveness. The results indicated optimal selection of S1 as the best web service, supported by Coefficient Index values (0.785). This study introduces a novel approach, Entrop – Hesitationistic - Fuzz-TOPSIS, for web service optimization, integrating quantitative and qualitative data through an Entropy-based model. The effectiveness of the proposed technique, validated through application on the WS-DREAM dataset, underscores its potential in addressing real-world decision-making challenges. The optimal selection of S1 as the best web service suggests practical utility. The study encourages further exploration of this technique's applicability to diverse Multiple Criteria Decision Making (MCDM) problems, opening avenues for future research and application.

Delayed Gastric Conduit Emptying (DGCE) occurs in 15-39% of patients who underwent esophagectomy. Intra-Pyloric Injection of Botulinum Toxin (IPBT), Pneumatic Balloon Dilation (PBD), and the same session combination (BTPD), represent the main endoscopic procedures, but comparative data are currently unavailable. We retrospectively analyzed prospectively collected data on all consecutive patients with DGCE treated endoscopically with IPBT, PBD, or BTPD. ISDE Diagnostic Criteria were used for DGCE diagnosis and classification. Gastric Outlet Obstruction Score was used for clinical staging. All patients undergoing IPBT received 100 UI of toxin, while those undergoing PBD were dilated up to 20mm. Clinical success (CS) was defined as the resolution of symptoms/resumption of feeding at discharge or expanding dietary intake at any rate. Recurrence was defined as symptom relapse after more than 15 days of well-being requiring endoscopic/surgical intervention. 64 patients (81.2% male, 90.6% Ivor-Lewis esophagectomy, 77.4% adenocarcinoma), median age 62 years (IQR 55-70), were enrolled: 18 (28.1%) in the IPBT group, 24 (37.5%) in the PBD group and 22 (34.4%) in the BTPD group. No statistically significant differences were found in the baseline characteristics, surgical techniques, and median follow-up among the three groups. BTPD showed a higher CS rate (100%) compared to the PD and BTPD groups (p=0.02) and Kaplan-Meier analysis with log-rank test revealed that the BTPD group was associated both with a significatively shorter mean time to refeed of 1.16 days (95% CI 0.8-1.5; p=0.001) and a shorter median time to discharge of 1 day (95% CI 1-3; p=0.0001). Endoscopic management of DGCE remains challenging. Waiting for further strong evidence, BTPD can offer patients a higher clinical efficacy rate and a shorter time to refeed and be discharged.

With all the sophisticated threats to network security, intrusion detection is a section of the security technology industry that is becoming increasingly significant. In this research paper, we have discussed in detail the detection, effects, and prevention protocols of security issues. Security issues are a wide range of elements. Hence, we narrowed our research to two main sectors which are malware attacks and distributed denial of service (DDOS). To make the research more informative, we looked at three selected real-life cases of security intrusion that occurred around the world in recent years. Malware attacks and DDOS are constantly being developed creatively to challenge all the current security systems. In addition, we have analysed and highlighted the potential threats of the security issue and included proposed countermeasure ideas to avoid the security issues. The research findings also show us that malware is evolving simultaneously with our security technology growth. This gives us an understanding that prevention is significantly a continual improvement process.

Ash dieback (ADB), caused by the invasive fungal pathogen Hymenoscyphus fraxineus, poses a significant ecological and economic challenge across Europe. Fraxinus excelsior (European ash), a key component of forest ecosystems, has experienced mortality rates reaching up to 85% in affected regions, severely threatening its ecological role and economic value. This study examines the relationship between the phenological traits of ash clones, particularly the timing of spring bud burst, and their susceptibility to H. fraxineus infection. The study was conducted in a clonal seed orchard located in northeastern Poland, encompassing 31 ash clones from different bioclimatic regions. Phenological observations of bud burst were carried out from early April to late May during the years 2018-2020, and crown damage and de-foliation levels were assessed multiple times throughout the growing season. The results confirm that clones with earlier bud burst exhibit significantly higher survival rates and reduced crown damage. It was found that the timing of bud burst is strongly correlated with susceptibility to ash dieback, suggesting that phenological timing is a crucial factor in the selection of genotypes resistant to ash dieback. Statistical analyses, including ANOVA and mixed models, revealed significant differences in susceptibility to infection among clones from different bioclimatic regions. Furthermore, the study high-lights the potential of breeding strategies focused on these traits to enhance the resilience of ash popula-tions. These findings are critical for the development of effective forest management practices aimed at conserving ash resources and maintaining biodiversity in the face of climate change and the ongoing spread of the pathogen.

Groundwater pollution in intensive horticultural areas is becoming an increasingly important problem. Therefore, this study evaluates nitrogen (N) fertilization in open field processing pepper crop in Extremadura, Spain. Previous research on the effect of N on sweet peppers grown in greenhouses is abundant, but data on outdoor cultivation, especially considering variety and site influences, are lacking. Field trials were conducted in 2020, 2021 and 2022 to determine the opti-mum N fertilizer rate for processing peppers, with the aim of reducing environmental impacts such as nitrate leaching while maintaining crop yields. Different N rates were applied in the trials, ranging from no N fertilizer to 300 kg N/ha. Meas-urements included crop yield, biomass, intercepted photosynthetically active radiation (PAR), and canopy cover. The study also developed a critical nitrogen curve (CNC) to determine the minimum N concentration required for optimal growth. The results showed that applying more than 200 kg N/ha did not significantly increase yield. Nitrogen-free treatments resulted in earlier fruit maturity, concentrating the harvest and reducing waste. In addition, excessive N application led to envi-ronmental problems such as groundwater contamination due to nitrate leaching. The study concludes that outdoor pepper crops in this region can achieve optimal yields with lower N rates (around 120 kg N/ha) compared to current practices, thereby reducing environmental risks and fertilizer costs. It also established relationships between biomass, canopy cover, and N uptake to improve fertilization strategies. These data support future crop modelling and sustainable fertili-zation practices.

Numerous studies on evaporative cooling systems have been conducted globally, but there is a scarcity of investigations in eastern Africa. The few studies undertaken in this region have primarily focused on their application in food storage and preservation, rather than for building purpose. The goal of this study is to review the most recent advancements in evaporative cooling technology, which would be relevant in eastern Ethiopia and could provide adequate cooling, give adequate thermal comfort, use less energy, and minimize environmental effect in hot and dry areas. There aren't many studies on evaporative cooling systems for building applications in Eastern Africa as a whole, thus this review has taken into account studies conducted in regions with climates similar to eastern Ethiopia. This study covers the classification, operation, and performance of evaporative cooling systems in hot and dry climate. Evaporative cooling systems work well in hot and dry climates, as revealed by this review study.

Recent advancements in Intelligent Tutoring Systems (ITS), driven by Artificial Intelligence (AI), have attracted substantial research interest, particularly in the domain of computer programming education. Given the diversity in learners' backgrounds, cognitive abilities, and learning paces, the development of personalized tutoring strategies to support effective attainment of learning objectives has become a critical challenge. This paper introduces PerFuSIT (Personalized Fuzzy Logic Strategies for Intelligent Tutoring of Programming), an innovative fuzzy logic-based module designed to select the most appropriate tutoring strategy from five available options, based on individual learner characteristics. The available strategies include revisiting previous content, progressing to the next topic, providing supplementary materials, assigning additional exercises, or advising the learner to take a break. PerFuSIT's decision-making process incorporates a range of learner-specific parameters, such as performance metrics, error types, indicators of carelessness, frequency of help requests, and the time required to complete tasks. Embedded within the traditional ITS framework, PerFuSIT introduces a sophisticated reasoning mechanism for dynamically determining the optimal instructional approach. Experimental evaluations demonstrate that PerFuSIT significantly enhances learner performance and improves the overall efficacy of interactions with the ITS. The findings highlight the potential of fuzzy logic to optimize adaptive tutoring strategies by customizing instruction to individual learners' strengths and weaknesses, thereby providing more effective and personalized educational support in programming instruction.

A polyphasic taxonomic study was carried out on the rod-shaped, orange pigmented strain C11T, isolated from gold mine tailings. Sequencing of the 16S rRNA gene showed relatedness to Brevundimonas, with 98.4 % and 98.2 % similarity to Brevundimonas bacteroides and Brevundimonas variabilis, respectively. Average nucleotide identity and digital DNA–DNA hybridization with the closest phylogenetic neighbor of C11T indicates distinction at the species level, further confirmed by differences in physiology. C18:1 ω7c is the dominant cellular fatty acid. DNA G + C content is 68.3 mol %. The predominant ubiquinone is Q-10; 1,2-Di-O-acyl-3-O-α-D-glucopyranuronosyl glycerol, phosphatidylglycerol, 1,2-di-O-acyl-3-O-α-D-glucopyranosyl glycerol and 1,2-di-O-acyl-3-O-[D-glucopyranosyl-(1->4)-α-D-glucopyranuronosyl] glycerol are the major polar lipid constituents. This bacterium produces bacteriochlorophyll a and tolerates high concentrations of (μg/mL): tellurium (>1500), selenium (1000 to >5000), and vanadium (>5000) oxyanions. Data supports the inclusion of C11T into the genus Brevundimonas as a new species with the proposed name Brevundimonas aurifodinae sp. nov., (C11T = NRRL B-61758T; = DSM 118059T).

In this paper I dig deep down along the slope of what touches me deeply – a democratic decline in climate politics. I follow the course of critical researchers in management and organisation studies, striving to move away from traditional, horizontal norms of academic writing that focus on counting rather than content and elision the author from the text, towards a more vertical writing acknowledging the value of incorporating the voice of the author. Embodying and resonating with my own emotional experiences of hate and threat campaigns, not locking my own vulnerabilities in, I analyse qualitatively the use, reasons, contents, senders and targets of such nasty rhetoric in Swedish climate politics, and the implications thereof for democracy. At the moment, a far-right populist nativist party holds tangible powers dictating the content and process of Swedish climate politics. In less than two years, Swedish climate politics have turned into an antidemocratic divisive politics portraying climate science as “a point of view”, female journalists writing about climate change and climate policy as “crypto environmentalists”, “motherfuckers” and “moron hags” that should be “fired” and “raped”, and the climate justice movement as “terrorists” and “a threat to Swedish democracy” that should be “sent to prison” and “executed”. Such nasty rhetoric is used not only by anonymous trolls in social media, but by the prime minister, cabinet ministers and parliamentarians, even in debates in the Swedish parliament. It has inspired the far-right extremist movement to use physical violence. Use of nasty politics aims to silence the opponents to the government’s climate policy, the political opposition, climate scientists, the climate justice movement and journalists, breaching liberal and deliberative democratic norms such as legitimacy, accountability and justice. It is a powerful tactic that leaves its targets with an anxious fear of losing control and often a need for disappearance. Many targets resign or stay silent. I chose to break the silence and write differently about the issue.

Catalog and key for identifying common marine invertebrates in the Little Sippewissett Marsh, Woods Hole, MA. Species identifications from August to September 2024 focused on arthropoda phylum and interacting ecosystems.

Power consumption prediction is a crucial component in enhancing the efficiency and sustainability of building operations. This study investigates the impact of data collection frequency and model selection on the predictive accuracy of power consumption in two distinct building types: an Academic one with 15-minute interval data and an Industrial one with hourly data. Various machine learning models, including Support Vector Machine (SVM) with Radial and Sigmoid kernels, Random Forest (RF), and Deep Neural Networks (DNN), across different data splits and feature sets. Our analysis reveals that higher data collection frequency generally improves model performance, as indicated by lower RMSE, MAPE, and CV values, alongside higher R² scores. The inclusion of more historical power consumption features has also been found to have a more significant impact on the accuracy of predictions than including climate condition features. Moreover, the SVM-Radial model consistently outperformed others, particularly in capturing complex, non-linear patterns in the data. However, the DNN model, while competent in some metrics, showed elevated MAPE values, suggesting potential overfitting issues. These findings suggest that careful consideration of data frequency, features and model selection is essential for optimizing power prediction, contributing to more efficient power management strategies in building operations.

Patient symptoms play a critical role in disease progression and diagnosis, yet they are most often captured in unstructured clinical notes. This study explores use of large language models (LLMs) for extracting patient symptoms from clinical notes, comparing their performance against rule-based information extraction (IE) systems, like BioMedICUS. By fine-tuning an LLM on diverse corpora from multiple healthcare institutions, we aimed to improve symptom extraction accuracy and efficiency with symptoms related to acute and post-acute sequelae of SARS-CoV-2. We also conducted prevalence analysis to highlight significant differences in symptom prevalence across corpora and performed fairness analysis to assess the model's equity across race and gender. Our findings indicate that while LLMs can match the effectiveness of rule-based IE methods, they face significant challenges related to demographic bias and generalizability due to variability in training corpora. This evaluation revealed overfitting and insufficient generalization, especially when models were trained predominantly on limited datasets with single annotator bias. This study also revealed that LLMs offer substantial advantages in efficiency, adaptability, and scalability for biomedical IE, marking a transformative shift in clinical data extraction processes. These results provide real-world evidence of the necessity for diverse, high-quality training datasets and robust annotation processes to enhance LLM’s performance and reliability in clinical applications.

Valles Marineris (VM), the most prominent example of a Martian Valley Network, has been extensively studied for over 50 years, yet no detailed examination of the principal azimuths of the system exists. To address this, two methods are presented to precisely calculate the principal azimuths, a Bezier Spline analysis, and a GIS technique. The medial axis of the main canyon of VM was determined analytically from cubic polynomial splines fitted to 93 coordinate points along both north and south edges of the canyon. These splines were optimized, and medial axis points were calculated through numerical techniques that ensured orthogonality between the tangents of each spline and their connecting normal lines. 1,000 Medial Axis points were extracted, and various regression models constructed, including fitting to sinusoidal and cubic polynomial curves, achieving accuracies with R² values of 0.98 and 0.99, respectively. Principal azimuths were obtained using the sinusoidal equation with the slope of the tangent at any point x simply determined by the derivative of the curve’s equation. This analytic approach was cross-validated by a GIS method (using QGIS software), where a vector medial axis was obtained which produced principal azimuths that agreed with values from the analytic study with a correlation coefficient of 1.00, and a p value of 6.43e-65. The findings suggest that a deterministic process plays a significant role in the structural geometry of VM, highlighting its potential importance in the canyon’s formation.

Crisis management is essential for businesses to effectively respond to, recover from, and mitigate the effects of unexpected disruptions. This study investigates factors influencing organizational resilience in Himachal Pradesh's pharmaceutical sector (India), focusing on crisis management techniques. The primary goal is to identify key components that support resilience in this industry. Data were collected using structured online and offline questionnaires, yielding 483 valid responses from a sample size of 500 across six pharmaceutical companies. Factor analysis with SPSS software identified three crucial components: "Innovations and Employee Engagement," "Organizational Resources," and "Organizational Culture and Values." Innovations and Employee Engagement" highlight the importance of fostering a creative environment where employees feel empowered to take initiative during crises. "Organizational Resources" underscore the critical role of adequate infrastructure, financial resources, and technological advancements in building resilience. "Organizational Culture and Values" emphasize the importance of shared standards, values, and beliefs in promoting cohesion and unity during adversity. By prioritizing these elements, pharmaceutical companies in Himachal Pradesh can enhance their crisis response capabilities and foster a resilient organizational culture. Implementing these insights through targeted strategies can ensure long-term viability and improve preparedness for future crises.

Children account for a significant proportion of the world's population and are a particularly vulnerable subpopulation regarding environmental factors. In a scoping review of a total of 3130 articles compiled from relevant medical literature, including 107 publications, we provide an empirical overview of the literature on masks in connection with children, particularly with regard to its' expected effects on viruses during the pandemic 2020-2023 versus scientific reality and evidence, including the side effects. While masks lack ecological validity from a strictly empirical point of view (transferability of experimental results from laboratories and modelling to the real world, e.g. to situations or environments typical of everyday life) and high-quality studies are showing little evidence of their effectiveness in real-world scenarios, whereas the side effects appear to be clear. An individual risk-benefit analysis is necessary and also a consideration of the situations, in which the use of masks in children could be justified. This review including the literature found and analysed will be able to help when making decisions in this regard.

Quadruped robots possess significant mobility in complex and uneven terrains due to their outstanding stability and flexibility, making them highly suitable in rescue missions, environmental monitoring, and smart agriculture. With the increasing use of quadruped robots in more demanding scenarios, ensuring accurate and stable state estimation in complex environments has become particularly important. Existing state estimation algorithms relying on multi-sensor fusion, such as those using IMU, LiDAR, and visual data, often face challenges on non-stationary terrains due to issues like foot-end slippage or unstable contact, leading to significant state drift. To tackle this problem, this paper introduces a state estimation algorithm that integrates an Invariant Extended Kalman Filter (InEKF) with a disturbance observer, aiming at estimating the motion state of quadruped robots on non-stationary terrains. Firstly, foot-end slippage is modeled as a deviation in body velocity and explicitly included in the state equations, allowing for a more precise representation of how slippage affects the state. Secondly, the state update process integrates both foot-end velocity and position observations to improve the overall accuracy and comprehensiveness of the estimation. Lastly, a foot-end contact probability model, coupled with an adaptive covariance adjustment strategy, is employed to dynamically modulate the influence of the observations. These enhancements significantly improve the filter's robustness and the accuracy of state estimation in non-stationary terrain scenarios. Experiments conducted with the Jueying Mini quadruped robot on various non-stationary terrains show that the enhanced InEKF method offers notable advantages over traditional filters in compensating for foot-end slippage and adapting to different terrains.

This article explores the intricate functioning of the human brain, highlighting how it operates near a critical state to optimize memory storage, adaptability, and the generation of thoughts. Through complex, fractal-like neural networks and brain waves, the brain largely governs our actions via subconscious processes, allowing for rapid, automated responses while reserving conscious thought for novel or complex tasks. Reasoning and planning emerge from the interplay of episodic memory and various neural networks such as Default Mode Network (DMN), Salience Network (SN), and Executive Network (EN), guiding decisions and actions. The "self" and “consciousness” are portrayed as functional illusions, which is being continuously constructed by dynamic neural activity, while free will is examined as a deterministic illusion shaped by prior neural states. We have argued that the brain's response to the physical world is a blend of subconscious automation and conscious sensory processing, thus, reality navigating through an evolving neural plasticity that promotes creativity and the illusion of a coherent, freely acting self. We discuss how does the mind select what to think about, how does it begin? Online and offline state of mind. We address what is an intelligence, understanding, creativity. We propose individual neuronal cells might store information beyond synaptic changes, the pathways through which neuronal thoughts propagate and Darwinian-like evolution of thoughts in minimizing surprises. We have drawn some parallels between the human brain and Large Language Model (LLM) like ChatGPT in terms of their functional roles.

Prediabetes is a significant risk factor for the development of Type 2 diabetes, cardiovascular diseases, chronic kidney disease, and other complications. Early diagnosis of prediabetes, coupled with education on lifestyle changes that support blood glucose management, are crucial for the prevention or delay of type 2 diabetes and related complications. This study aimed to examine the effects of individualized nutrition therapy (INT) combined with continuous glucose monitoring (CGM) on blood glucose control in individuals with prediabetes who are overweight or obesese. Participants (mean age ± SD: 55 ± 6 years; BMI: 31.1 ± 4.1 kg/m²) were randomly assigned to either the treatment group (n = 15) or the control group (n = 15). Both groups received INT and CGM, but the control group was blinded to the CGM data until the end of the study. Participants were followed for 30 days and visited the lab every 10 days for CGM replacement, study measurements, and dietary consultations. The treatment group showed a significant increase in the percent of time in the target blood glucose range (p=0.02) and a significant decrease in mean blood glucose concentration (p<0.05), glucose management indicator (p=0.02), percent coefficient of variation for blood glucose (p=0.01), and the percent time spent in the high or very high blood glucose ranges (p= 0.04). These changes were not statistically significant for the control group. We conclude that adding CGM feedback to INT resulted in better management of blood glucose levels in overweight or obese individuals with prediabetes.

In this work, we explore Conjecture 1 proposed in the newly released pioneering paper “Volatility transformers: an optimal transport-inspired approach to arbitrage-free shaping of implied volatility surfaces” by Zetocha Valer, which posits that the “One-X” property is both a necessary and sufficient condition for convex order between non-negative continuous strictly increasing distributions with the same mean. We provide a counterexample demonstrating that the conjecture, as originally stated, does not hold. By examining stochastic orders, particularly the increasing convex order, and the “One-X” property, we propose an enhanced version of the conjecture which is shown to be valid. Furthermore, we discuss the implications of these findings in the context of equity implied volatility fitting and the construction of implied volatility surfaces, highlighting the challenges posed by real-market conditions. In the end, we propose several applications in implied volatility surface construction or simulation.

Keratin extraction from chicken feathers provides a sustainable way to valorise poultry by-products. This study aimed to optimize keratin yield and antioxidant properties by compar-ing two pre-treatment methods: the typical (T-method), involving washing, drying, cutting, grinding, and defatting, and the simplified (S-method), involving only washing, drying, and cut-ting, under various alkaline hydrolysis conditions. These included different feather mass to NaOH ratios (1:3, 1:6, or 1:9), hydrolysis times (16, 24, or 32 h), and shaking speeds (150, 175, or 200 rpm). Under the most intensive hydrolysis conditions (1:9 ratio, 32 hours, 200 rpm), the T-method achieved the highest keratin yield (72%), DH of 2 mmol NH2/g protein, and an average molecular weight of 5.0-5.9 kDa. The S-method had a lower yield (57%) and a higher molecular weight (7.4 kDa). The highest antioxidant activity was observed under 1:3 feather mass to NaOH ratio, 32 h of hydrolysis time, and 175 rpm of shaking speeds. The T-method is optimal for maximum yield, while the S-method is suitable for large-scale applications due to its simplicity and high antioxidant activity.

Education for sustainable development seeks transformative learning in order to empower learners to change the ways they understand the world. In order to achieve its goals, teaching materials are needed, that reflect its principles and goals in their content and pedagogy they promote. The study of the epistemological background on which the teaching material is structured is a research proposal, which is addressed to researchers, authors and practitioners for sustainable development, pointing out that the structuring and development of the materials should be based on a theoretical framework that effectively link the teaching activity with all 17 Sustainable Development Goals with a focus on Quality Education. This scoping review attempts to map the existing literature that assesses the effectiveness of formal and non-formal educational materials that seek to promote education for sustainability. In addition, research is presented that evaluates the effectiveness of teaching materials from the perspective of sociocultural learning theory, considering that education for sustainable development (an ideal to be achieved) is in a dynamic relationship with constructivism (a learning theory) on the basis of knowledge construction, learning and sustainability's sociocultural aspects. It was found that the international literature investigating the contradictions presented by educational materials in relation to the objectives they set and achieve and the way in which the activities they propose are implemented in practice, is limited.

The potato is the most important non-cereal food crop, and thus improving potato growth and yield is in the focus of agricultural researchers and practitioners worldwide. Several studies reported beneficial effects of silicon (Si) fertilization on potato performance, although plant species from the family Solanaceae are generally considered as non-Si-accumulating. We used results from two field experiments in the temperate zone to gain insight into silica accumulation in potato plants as well as corresponding long-term potato yield performance. We found relatively low Si contents in potato leaves and roots (up to 0.08% and 0.3% in the dry mass, respectively) and negligible Si contents in potato tuber skin and tuber flesh for plants grown in soils with different concentrations of plant available Si (field experiment 1). Moreover, potato yield was not correlated to plant available Si concentrations in soils in the long-term (1965-2015, field experiment 2). Based on our results we ascribe the beneficial effects of Si fertilization on potato growth and yield performance reported in previous studies mainly to antifungal/osmotic effects of foliar-applied Si fertilizers and to changes in physicochemical soil properties (e.g., enhanced phosphorus availability and water holding capacity) caused by soil-applied Si fertilizers.

Di(2-ethhylhexyl) phthalate (DEHP) is a common plastic rubberizer. DEHP leaches from plastic matrices and is under increasing scrutiny as numerous studies have linked it to negative human health manifestations. Coxsackievirus B3 (CVB) is a human pathogen that typically causes subclinical infections but can sometimes cause severe diseases such as pancreatitis, myocarditis, and meningoencephalitis. Though CVB infections are common, severe illness is relatively rare, and it is unclear what factors mediate severity of disease. Here we show that DEHP drastically increases CVB infection in a variety of human cell types. While not entirely clear what cellular processes underly DEHP’s proviral properties, we observe that DEHP may subvert CVB-induced interferon signaling and elevate levels of interferon-induced transmembrane proteins which appear to bolster CVB infection. We hypothesize that DEHP may represent a major environmental factor associated with the severity of CVB infection. Further understanding how DEHP exacerbates infection may better elucidate its potential role as a proviral environmental factor.

This study introduces a novel predictive model for atomization droplet size, developed through comprehensive data collected under elevated temperature and pressure conditions using a twin swirl airblast nozzle. The model, grounded in flow instability theory, has been meticulously parameterized using the Particle Swarm Optimization (PSO) algorithm. Through rigorous analysis, including analysis of variance (ANOVA), the model has demonstrated robust reliability and precision, with a maximum relative error of 19.3% and an average relative error of 6.8%. Compared to the classical atomization model by Rizkalla and Lefebvre, this model leverages theoretical insights and incorporates a range of interacting variables, enhancing its applicability and accuracy. Spearman correlation analysis reveals that air pressure and the air pressure drop ratio significantly negatively impact droplet size, whereas the fuel-air ratio (FAR) shows a positive correlation. Experimental validation at ambient conditions shows that the model is applicable with a reliability threshold of ≥0.13 and highlight the predominance of the pressure swirl mechanism over aerodynamic atomization at higher fuel flow rates (q > 1.25 kg/h). This research effectively bridges theoretical and practical perspectives, offering critical insights for the optimization of airblast nozzle design.

AbstractBackground: In Ethiopia, 8.6% of maternal deaths are attributed to abortion. Despite the legalization of abortion and improved accessibility of safe abortion services, almost six in 10 abortions in Ethiopia are performed outside of the health facility. Abortion considered as an indicator for various aspects of reproductive health and healthcare access within a particular region or country. Despite the significance of the problem, there is a limited understanding of the magnitude of abortion and the contributing factors in the study area. Therefore, this study aimed to assess the prevalence of abortion and determinant factors among reproductive-age women in the Sidama regional state of Ethiopia.Methods: A community-based cross-sectional study was conducted from October to November 11, 2022, among 1,130 women of reproductive age. We utilized a multi-stage sampling method to select eligible women. A structured and pretested questionnaire was utilized to collect the data using Open Data Kit (ODK) mobile application. Due to the hierarchical nature of the data, a multilevel logistic regression model was applied. Variables with p-values < 0.25 on bi-variable analysis were included in a multivariable regression model. In the multivariable regression model, variables with a p-value < 0.05 were declared as statistically significant factors of abortion. Results: Nearly one-fifth (19.5%) of the women had a history of abortion. From the individual level determinates; women with formal education (AOR=0.44; 95% CI: 0.24-0.79), and planned pregnancy (AOR=0.41; 95% CI: 0.28-0.61) had lower odds of abortion. While from the community related factors; urban residence increased the odds of abortion (AOR=2.25; 95% CI: 1.20-4.20) as compared to the rural residence.Conclusion: the prevalence of abortion among reproductive age women of Northern Zone of Sidama Region was high. Education and a planned pregnancy serve as protective factors for abortion, while the risk of abortion increased among women reside in urban area. Therefore, to lower the abortion rate, it is better to implement a comprehensive approach, focusing on education, family planning, and urban-specific intervention.

Common prosperity is the core goal of rural revitalization, and sustainable growth of farmers' income is an inevitable requirement. This study uses CLDS2016-2020 village and family level questionnaire data to reveal how the degree of village organization affects the sustainable growth of farmers' income, thus providing reference and decision-making for the local government to promote the increase of farmers' income and narrow the gap from the village level. The results show that the degree of village organization can significantly affect farmers' income, and the analysis results of the degree of formal organization are consistent with them. Specifically, for every 1% increase in the degree of village organization, the per capita household income will increase by 32.4%, among which the wage income will increase by 22.6%, the operational income will increase by 5%, the property income will increase by 0.8%, and the transfer income will increase by 4.2%. The estimation results through instrumental variables are consistent, and the results are robust. At the same time, improving the degree of village organization can also significantly increase the proportion of farmers' non-agricultural income and narrow the income gap among farmers. On the impact of heterogeneity, it is found that the geographical distance between villages and county and township governments, as well as the political identity and education level of farmers will affect the role of the degree of organization. The results of mechanism analysis show that improving the degree of village organization is mainly through promoting the circulation of agricultural land, socialized service of agricultural machinery and industrial and commercial capital to the countryside to increase farmers' income. The research revealed that the modernization of rural governance should be accelerated, and the degree of village organization should be improved, especially the degree of formal organization, so as to build a benign trust and cooperation relationship between the two village committees and the villagers, and implement policies and measures to improve the income of farmers according to local conditions. At the same time, strengthen the publicity and education in party member to improve the proportion of rural party member and the education level of farmers.

To promote of the rural revitalization strategy in China, this study attempts to summarize the gains and losses by the review of the design practice of rural buildings of the People's Commune in the late 1950s. Firstly, from the macro perspective, this paper gleans the relevant commune housing design cases in the Architectural Journal from 1958 to 1960 and summarizes the overall common design policies. Secondly, from the micro perspective, the paper analyzes the process of the investigation and creation through a concrete case. The paper concludes that the actual production and living needs of farmers must be taken into consideration in the process of the implementation of rural modernization, instead of simply putting the focus on standardized construction. Finally, the article points out the two characteristics of "rural modernity" reflected in the process of promoting rural modernization during the early stage of modern China: 1) collective wisdom and efforts; 2) combining local and foreign cultures. This article aims to provide a historical reference for current architects to carry out effective design practices in combination with rural development.

Objective: To evaluate the value of otolith‑associated protein otoconin‑90 (OC90) and otolin-1 in the pathogenesis research and clinical treatment of benign paroxysmal positional vertigo (BPPV). Material and Method: The study included 50 patients with BPPV admitted to neurology and otorhinolaryngology departments and 30 healthy subjects with no history of dizziness as control group. Results: BPPV and controls were similar in terms of gender and age. Otolin-1 level was significantly greater in the BPPV group than controls (710.44 [584.35-837.39] vs 280.45 [212.7-419.61] ; p

Polypharmacy, the use of multiple medications, is a prevalent issue globally that contributes to increased healthcare costs and places additional burdens on patients' organs. This study aims to reduce the incidence of polypharmacy in the emergency department. We conducted a retrospective review of randomly selected medical records from the Internal Medicine Department of Taipei MacKay Emergency Department, spanning from August 1, 2023, to October 31, 2023. For cases identified as involving polypharmacy, pharmacists provided medication education using the TRM Polypharmacy Interview Guide, while social workers contacted patients via phone to recommend follow-up visits for deprescribing. Patients experiencing polypharmacy were significantly older than those on appropriate medication regimens (79.8 vs. 67.3 years, p=0.002). After deprescribing interventions, the average number of medications for polypharmacy patients was 5.9 higher than for those receiving appropriate prescriptions (9.2 vs. 3.3, p=0.001). The most common conditions associated with polypharmacy were diabetes mellitus, hypertension, and arrhythmia. Polypharmacy poses a significant medication management challenge, with affected patients taking an average of 6.9 more medications than those on appropriate treatment regimens. Our team’s resource management module successfully reduced the incidence of polypharmacy by 8.4% in the emergency department.

The increasing urbanization of cities worldwide has driven a parallel rise in resource consumption, waste generation, and environmental degradation. The transition to a circular economy (CE) offers a sustainable alternative, shifting from traditional linear systems of resource use and disposal to regenerative systems that prioritize material reuse, resource efficiency, and ecological restoration. Urban design and planning play an essential role in facilitating this shift by creating the physical and regulatory infrastructure necessary to implement CE principles in cities. This paper explores the role of urban design in promoting circular economy strategies, with a focus on adaptive reuse of buildings, green architecture, and the integration of nature-based solutions (NBS) into urban environments. Through detailed analysis of these strategies and case studies from cities around the world, this paper demonstrates that regenerative design is essential for closing material and resource loops and creating more sustainable, resilient cities.

The use of digital twin and shadow concepts for industrial material processes have promoted new notions to bridge the gap between physical and cyber manufacturing processes. Hence, many multi-disciplinary areas like advanced sensor technologies, material science, data analytics, and machine learning algorithms are employed to create such hybrid systems. On the other hand, new additive manufacturing (AM) processes for metals and polymers based on novel emerging technologies have already shown a promising horizon for manufacturing of sophisticated parts with complex geometries. These processes are going through a major transformation with the emergence of digital technology, hybrid physical-data driven modelling and fast reduced models. This paper presents a fresh look at the hybrid physical-data driven and reduced order modelling (ROM) techniques for digitalization of AM processes within a digital-twin concept. The main contribution is to show the benefits of ROM and machine learning (ML) technology for process data handling, optimization\controlling and their integration into the real-time assessment of AM processes. Hence, a novel combination of efficient data solver technology and architecturally designed neural network (NN) module has been developed for the transient manufacturing processes with high heating\cooling rates. Furthermore, a real-world case study has been presented where the combination of hybrid modelling along with ROM and ML schemes are used for an industrial wire arc AM (WAAM) process.

This article introduces a novel three-phase angular perturbation technique for solv- 1 ing the School Bus Problem (SBP), an NP-hard combinatorial optimization challenge. The three 2 phases—initial solution, global and local search, and solution exploration—focus on optimizing 3 school bus routes by minimizing sharp turns and reducing travel distances. The performance of 4 three metaheuristic algorithms (GAACOSA-AP, BFSPSO-AP, RL-AP) is evaluated, and significant 5 improvements in routing efficiency are observed. we evaluated the performance of our hybrid algo- 6 rithm against the industry-leading optimization software, CPLEX, and other optimization techniques 7 across multiple school scenarios. The results show that the GAACOSA-AP algorithm consistently 8 outperforms its counterparts, achieving substantial reductions in travel distances, particularly for 9 complex routes with numerous stops. The integration of Angular Perturbation was key to improving 10 route geometry by, reducing sharp turns, and enhancing overall path optimization by an average 11 reduction of 27.12% compared to 22.37% without Angular Perturbation.12

This study aims to understand the role of BPJS Kesehatan as a variable that mediates or mediates the relationship between emergency services and patient satisfaction. This can include how administrative processes, access to services, or costs incurred by BPJS affect the relationship between service and satisfaction. Quantitative studies of a correlational nature are a part of this investigation. In order to forecast endogenous variables (Y) Purchase decisions, researchers conduct correlational studies, which examine the link between one or more variables and other factors. Here, X represents emergency services, Y stands for patient satisfaction, and M for BPJS are the exogenous variables. The purpose of this research is to examine the role of BPJS as a moderator between the impact of emergency services on patients' levels of satisfaction. There were 120 people that filled out the survey, and the margin of error was 10% (based on a 90% truth rate and a 10% error rate). Purposive sampling was used to select participants for the aforementioned studies. Warppls 8.0 and the Warp Partial Least Square program were utilized for data analysis in this investigation. The study found that PKD significantly and positively affected 71% of participants' happiness with the impact they received. With a 63% influence, PKD has a favorable and statistically significant effect on BPJS. Patient satisfaction is significantly impacted by BPJS, which has a favorable association. When looking at the connection between community satisfaction and emergency services, BPJS is a key mediator. Community satisfaction can be enhanced through the provision of fast and excellent emergency services, and BPJS plays a vital role in mediating this relationship. The beneficial effect of emergency services on community satisfaction can be amplified if BPJS is able to offer sufficient coverage while simultaneously reducing costs and expediting administrative processes

Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 811 papers initially identified, 26 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations.

In the past ten years, the generative artificial intelligence trend has evolved from simply enhancing the creation of audiovisuals using generative adversarial networks to becoming an entirely disruptive force, transforming operations in various industries and markets, including education and business. The introduction and subsequent widespread popularity of Open AI’s ChatGPT in 2022 raised concerns about the use of Generative AI in professional spaces and its impact on authenticity, innovation, data privacy, and integrity. This study seeks to assess the current applications of this disruptive technology in corporate America and build on that knowledge to provide insight into the current innovative practices and the factors driving its use. The research will further outline some risks associated with generative AI technology in business functions and industries and how this technology is being misused in industries worldwide. Following these revelations, recommendations will be made on the need for regulations surrounding the use of generative AI and the future of this technology for researchers and corporations alike. This study aims to equip corporate strategists and leaders with the knowledge needed to embrace AI, be aware of its possible challenges, and find the best ways to use Generative AI to gain competitive advantage. In addition, it seeks to further equip technology experts and professionals with key information about Generative AI to help them make informed choices when working. The study also aims at research management experts and personnel as it contains vital information that will set the foundation for future research.

(1) Background: The development of generative artificial intelligence (GAI) is transforming higher education. This systematic literature review synthesizes recent empirical studies on the use of GAI, focusing on its impact on teaching, learning, and institutional practices. (2) Methods: Following PRISMA guidelines, a comprehensive search strategy was employed to locate scientific articles on GAI in higher education, published by Scopus and Web of Science between January 2023 and January 2024. (3) Results: The search identified 102 articles, with 37 meeting the inclusion criteria. These studies were grouped into three themes: the application of GAI technologies, stakeholder acceptance and perceptions, and specific use situations. (4) Discussion: Key findings include GAI’s versatility and potential use, student acceptance, and educational enhancement. However, chal-lenges such as assessment practices, institutional strategies, and risks to academic integrity were also noted. (5) Conclusions: The findings help identify potential directions for future research, including assessment integrity and pedagogical strategies, ethical considerations and policy development, the impact on teaching and learning processes, perceptions of students and instructors, technological advancements, and the preparation of future skills and workforce readiness. The study has certain limitations, particularly due to the short time frame and the search criteria, which might have varied if conducted by different researchers

According to EuroStat data recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. Gradual decline slowed after the entering into force of the reform of the European Common Fisheries Policy (CFP) end 2013, but was followed by a steeper decline after 2018 (1). This casts some doubt on claims that the resources are nowadays better managed, even if a warming ocean provokes measurable poleward migration of species. Within this general picture, the broad-brush landscape is influenced by policy applications more in favour of industrial exploitations and regulatory and market environments making it very hard for many small-scale fishers (SSF) to remain in business, let alone attract younger successors for generational transition. In crowded marine spaces it is a challenge to allocate access rights fairly between fisheries, exclusion zones for resource and habitat protection and much needed ecosystem recovery (2), platforms for fossil exploitation, wind farms, underwater cables and recreational uses. Two examples of local initiatives with recovery potential in the Mediterranean are briefly presented. They are spearheaded by artisanal fishers, who seek to restore spawning grounds and other coastal habitats as a way to procure enough fish and other complementary activities to secure their livelihoods in the future and supported by local scientists and nature conservation organisations. While promising, this is still rather the exception. Here it is argued that trust-building between artisanal fishers, conservationists and scientists, and greater systemic support to SSF by governments increase chances for the urgently needed structural shifts that can reverse the on-going decline in biodiversity and ocean productivity which all aspire to.

Introduction: Urinary tract infections (UTIs) are a significant global health issue, especially among women, with growing concerns related to antibiotic resistance and adverse effects. The Uromune® vaccine, a sublingual bacterial lysate, represents a promising therapeutic alternative by enhancing immune responses against uropathogens. Methods: This retrospective study, conducted at Hospital Universitari de Sant Joan de Reus from January 2017 to August 2022, evaluated the effectiveness of Uromune® in treating recurrent UTIs (rUTIs). Patients received personalized autovaccines administered as two sublingual puffs daily for three months. Clinical, microbiological, and demographic data were analyzed to assess treatment outcomes and identify recurrence-associated factors. Results: Forty-nine patients (mean age, 61 years, and 59.2% women) were included in the study. Uromune® treatment decreased UTI episodes, from 3.73 ± 0.97 the year before to 0.98 ± 1.36 (P &lt; 0.001) the year after its administration. The number of patients who suffered three or more episodes per year dropped from 43 (87.7%) before the intervention to 7 (14.3%) afterward. The maximum effectiveness of the autovaccine was observed three months post-administration, with 44 patients not experiencing any UTI episodes. Regression analysis identified having had a urostomy, chronic kidney disease, and being immunosuppressed as predictors of recurrence. Conclusion: The Uromune® autovaccine effectively reduced the frequency of rUTIs and associated hospitalizations, offering substantial relief to patients. These findings support the integration of Uromune® into routine clinical practice as a viable alternative to conventional antibiotic treatments.

As the carbon storage capacity of timber is recognized, there is growing interest in timber and wooden structures as a solution to various environmental problems. The use of Korean timber with substantial carbon storage capacity is required to reduce Korean carbon emissions and circulate timber resources. In this study, fire tests were conducted to investigate the charring properties of glued laminated timber columns made of Korean larch. The fire tests were conducted under both load-bearing and non-load-bearing conditions. The fire test results showed that the charring depth was affected by the corners of the section, and that the load ratio had an insignificant influence on the charring depth when the load ratio was 0.9 or less. This study provides data that can be used to compare the charring properties of laminated wood produced using South Korean larch with the charring properties of foreign standards. This provides reference data for developing fire-resistant design standards for timber structures made from South Korean timber.

Abstract: Individualized nursing care allows a systematic assessment and intervention, considers the patient's preferences, values, and context, and contributes to a positive care trajectory. However, its operationalization has proven to be challenging. This research aims to determine which items of nursing care individualization are most integrated into nurses' clinical practice, and those that are less included. A cross-sectional study was conducted on 122 eligible and registered nurses at a Hospital Center, in Ophthalmology (operating room and inpatient ward), Cardiology Service, Internal Medicine, and Medical Emergency Unit, in Portugal. The Indi-vidualized Care Scale nursing version (ICS-Nurse) was used for the assessment, including three sub-dimensions: clinical situation, personal life situation, and decisional control over care-related decisions. Analyses were performed using Cronbach's Alpha and Principal Component Analysis to confirm the relationships between the variables, suggested by the literature and previous studies. In the results, no statistically significant differences were identified between the sociodemographic profile and the sub-dimensions of individualization. Nurses overall have a good perception of the importance of individualized care (4.06 ± 0.46 ICS-A-NURSE), but face difficulties in its implementation during the last shift worked (3.97 ± 0.49 ICS-B-NURSE). The sub-dimensions more integrated into the care environment were clinical situations and decisional control, and the less integrated were the personal lives of patients. This study identifies key aspects of the individualization of nursing care in acute and perioperative settings, as its omission represents a failure to address the multidimensional health needs of patients, families, and caregivers. We suggest the development of training programs that promote a holistic approach, as well as future studies that consider patient outcomes related to the individualization of nursing care.

The Huaniushan lead-zinc-silver deposit is a hydrothermal sedimentary exhalative deposit (SEDEX). The mining area has complex geological conditions. The main tectonic structure in the area is the Huaheitan-Shuangfengshan Fault (F3), which controls the distribution of strata and magmatic rocks. Since the discovery of the Huaniushan Lead-zinc-silver polymetallic deposit, there are diverse understandings of the deposit's genesis and mineralization law, making it challenging to meet the geological interpretation requirements of the Huaniushan Lead-zinc-silver polymetallic deposit. Moreover, a single geophysical exploration method utilizes limited rock physical parameters, making it difficult to effectively characterize underground structures. The integrated exploration of multiple geophysical methods can effectively integrate the geophysical characteristics of different rock physical parameters, reducing the multiplicity and uncertainty of geophysical data inverse interpretation. The comprehensive interpretation of three-dimensional inversion based on various geophysical data, the construction of geological-geophysical models based on geological grounds, the establishment of hidden ore exploration and positioning, and the rapid evaluation of geophysical technology systems are the current development trends in mineral exploration. In light of this, this paper conducts research on the three-dimensional inversion interpretation of the heavy magnetoelectric exploration data of the Huaniushan sedimentary exhalative deposit lead-zinc-silver polymetallic deposit in the mining area and constructs a three-dimensional geological-geophysical model of the study area based on the obtained three-dimensional physical structure of the underground three-dimensional density, magnetization intensity, resistivity, and polarizability structure of the study area, in combination with the information of related geology and drilling holes. It comprehensively interprets the favorable mineralization parts in the study area.

This comprehensive review examines the role of fenoldopam, a selective dopamine-1 receptor agonist, in preventing and treating acute kidney injury (AKI) during cardiac surgery. AKI remains a significant complication in cardiac surgery, associated with increased morbidity, mortality, and healthcare costs. The review explores fenoldopam's pharmacological properties, mechanism of action, and clinical applications, synthesizing evidence from randomized controlled trials, meta-analyses, and observational studies. While some studies have shown promising results in improving renal function and reducing AKI incidence, others have failed to demonstrate significant benefits. The review discusses these conflicting findings, explores potential reasons for discrepancies, and identifies areas requiring further research. It also compares fenoldopam to other renoprotective strategies, including dopamine, diuretics, and N-acetylcysteine. The safety profile of fenoldopam, including common side effects and contraindications, is addressed. Current guidelines and recommendations for fenoldopam use in cardiac surgery are presented, along with a cost-effectiveness analysis. The review concludes by outlining future research directions and potential new applications of fenoldopam in cardiac surgery. By providing a thorough overview of the current state of knowledge, this review aims to facilitate informed decision-making for clinicians and researchers while highlighting areas for future investigation.

Diabetes markedly increases susceptibility to adverse cardiovascular events, including heart failure (HF), leading to heightened morbidity and mortality rates. Elevated levels of natriuretic peptides (NPs), notably B-type natriuretic peptide (BNP) and N-terminal-proBNP (NT-proBNP), correlate with cardiac structural and functional abnormalities, aiding in risk stratification and treatment strategies in individuals with diabetes. This article reviews the intricate relationship between diabetes and HF, emphasizing the role of NPs in risk assessment and guiding therapeutic strategies, particularly in individuals with type 2 diabetes mellitus (T2DM). It also explores the challenges and prospects of natriuretic peptide-guided therapy in managing cardiovascular risk in patients with diabetes.

Linear programming models have been used in forest management planning since the 1960s. These models have been formulated in three basic ways: Models I, II, and III, which are defined by the sequences of management unit states represented by the variables. In Model I, variables represent sequences of states from the beginning of the planning horizon to the end. In Model II, variables represent sequences of states from one intervention to the next. Finally, in Model III, variables represent a single arc in a management unit’s decision tree, i.e., two states. The objectives of this paper are to clarify the definitions of these model variations and evaluate the advantages and disadvantages of each model. This second objective was achieved by formulating a case study problem using each model type. The case study includes three increasingly complex scenarios, each incorporating additional ecosystem services. Results show that despite having more variables and constraints, Model III requires the least time to formulate due to its less dense parameter matrix. Model II has the shortest solution times, followed closely by Model III, while Model I requires the longest times for both formulation and solution. These results are increasingly apparent in more complex scenarios.

This research has its focus on the African Igbo people of Southeast Nigeria. In all the manifestations of culture across the globe, there exist practices which celebrate life circle transitions especially from birth until the termination of human life. One of such practices is the rite of passage. 'Ibe-ugwu' (circumcision) is a rite of passage observed among the Ukawu people of Ebonyi State, Southeast Nigeria. The rites and rituals have their main focus on preparing and equipping the female adolescents of Ukawu (Igbo) community to assume the roles of wives, mothers, and women in the society, ready to make their own contributions towards the development of the community, family and by extension the global community. It is the contention of this work, that the continued neglect of such cultural heritage is one of the major reasons for seeming African Igbo loss of identity, moral decadence and social vices amongst her youths today. The work advocates for a revival of such African Igbo cultural heritage. This research makes use of documented, observation and interview methods of data gathering while deploying the sociological (structural functionalist) approach in its data analysis.

The purpose of this study is to evaluate the amounts of apically extruded 3% sodium hypochlorite using two modes of Er:YAG laser-activated irrigation (LAI), super short pulse (SSP) and shock wave enhanced emission photoacoustic streaming (SWEEPS®), combining three types of laser tips (FT) and conventional syringe needle irrigation (SNI). Methods: Twenty extracted human maxillary central incisors prepared using Reciproc® instruments (size 40, taper 0.06). Irrigant volumetric flow (IVF) was accurately standardized using a precision syringe pump with constant irrigant delivery through the 27G needle. The tested irrigation protocols (60 s) were groups 1: 27-G SNI with 0.05 ml/s constant IVF; group 2: SSP (10 mJ, 15 Hz, pulse duration 50 μs) + Radial SWEEPS FT; group 3: SSP + photon-induced photoacoustic streaming (PIPS) FT; group 4: SSP+SWEEPS FT; group 5: AutoSWEEPS (20 mJ, 15 Hz, pulse duration 25 µs) + Radial SWEEPS FT; group 6: AutoSWEEPS+PIPS FT; group 7: AutoSWEEPS+SWEEPS FT. Each protocol was evaluated in 10 repetitions each. Apically extruded irrigant was collected, and the net weighted. Results: There were significantly lower amounts of extruded irrigant with SNI and SSP using radial SWEEPS and PIPS FTs compared to the other tested laser protocols (p&lt;0.05). In the AutoSWEEPS groups, all three FTs had similar amounts of extruded irrigant (p&gt;0.05). Conclusion: In straight root canals, the use of various fiber FTs in the AutoSWEEPS mode exhibited a higher potential for irrigant extrusion.

Objective: Scaphoid fractures, particularly occult and non-displaced fractures, are difficult to detect using traditional X-ray methods due to their subtle appearance and variability in bone density. The study proposes a two-stage CNN approach to detect and classify scaphoid fractures using anterior-posterior (AP) and lateral (LA) X-ray views for more accurate diagnosis. Methods: The study emphasizes the use of multi-view X-ray images (AP and LA views) to improve fracture detection and classification. The multi-view fusion module helps integrate information from both views to enhance detection accuracy, particularly for occult fractures that may not be visible in a single view. The proposed method includes two stages that are stage 1: Detect the scaphoid bone using Faster R-CNN and Feature Pyramid Network (FPN) for region proposal and small object detection. The detection accuracy for scaphoid localization is 100% with Intersection over Union (IoU) scores of 0.8662 for AP views and 0.8478 for LA views. And stage 2: Perform fracture classification using a ResNet backbone and FPN combined with a multi-view fusion module to combine features from both AP and LA views. This stage achieves a classification accuracy of 89.94%, recall of 87.33%, and precision of 90.36%. Results: The proposed model performs well in both scaphoid bone detection and fracture classification. The multi-view fusion approach significantly improves recall and accuracy in detecting fractures compared to single-view approaches. In scaphoid detection, both AP and LA views achieved 100% detection accuracy. In fracture detection, using multi-view fusion, the accuracy for AP views reached 87.16%, and for LA views, it reached 83.83%. Conclusion: The multi-view fusion model effectively improves the detection of scaphoid fractures, particularly in cases of occult and non-displaced fractures. The model provides a reliable, automated approach to assist clinicians in detecting and diagnosing scaphoid fractures more efficiently.

In the context of constructing new power systems, distribution networks are increasingly incorporating distributed resources such as distributed photovoltaic (PV) systems, decentralized wind turbines (WT), and new types of energy storage system (ESS), which may lead to prominent issues such as voltage overruns and reverse heavy overloads in the distribution network. While distributed resources are valuable for voltage regulation, their regulation characteristics vary with their operation means, and the randomness and volatility of renewable power generation will also influence the optimization and regulation of voltage in the distribution network. This paper proposes a multi-time scale reactive power optimization and regulation method for distribution networks in a multi-source interactive environment. Firstly, the voltage regulation characteristics of distributed PV systems, decentralized ES, and distributed WT are analyzed. Based on this analysis, then a multi-time scale voltage optimization scheme for distribution networks using MPC method is proposed, which optimizes the voltage regulation strategies for each distributed resource in a rolling manner. Furthermore, an event-triggered real-time voltage zoning control strategy based on voltage sensitivity is proposed to address the real-time sudden voltage overlimit problems. The modified IEEE 33-node system is used to verify the performance of proposed method, simulation results indicate that the issue of voltage overruns at distribution network nodes has been improved, and the intraday rolling optimization yields results that are more realistic compared to the day-ahead optimization method.

Driven by global sustainability trends, Building Information Modelling (BIM) technology is in-creasingly becoming a key tool in the construction industry to improve efficiency and sustaina-bility.This study aims to identify the key factors affecting BIM implementation in the context of Environmental, Social and Governance (ESG) and Sustainable Development Goals (SDGs) and to construct a theoretical framework for BIM implementation based on these factors.To achieve this objective, this study used a systematic literature review (SLR) method to systematically review the relevant literature between 2009 and 2024, and identified 16 key factors from the selected 406 studies through keyword co-occurrence analysis (using VOSviewer) and data coding.These key factors include:Top Management Support for ESG and SDGs,Alignment of SDGs,ESG Integra-tion,Technical Support,BIM Software,BIM Hardware,Structural Adjustment & Collabora-tion,Capacity Building,Change Management,Skill and Attitude,Educational Training and Devel-opment,Incentive Mechanism,Roles & Responsibilities,Sustainable Construction Practic-es,Policies and Regulations,Resource Efficiency.This study categorises these factors under the STOPE framework (Strategy, Technology, Organisation, People, Environment) and proposes a theoretical implementation framework for BIM accordingly. The findings not only provide a practical guiding framework for the sustainable development of construction companies in the context of ESG and SDG integration, but also lay a solid theoretical foundation for future empiri-cal research.

Dengue fever is a persistent public health issue in tropical regions, including Vietnam, where climate variability plays a crucial role in disease transmission dynamics. This study focuses on developing climate-based machine learning models to forecast dengue outbreaks in Ba Ria Vung Tau (BRVT) province, Vietnam, using meteorological data from 2003 to 2022. We utilized four predictive models—Negative Binomial Regression (NBR), Seasonal AutoRegressive Integrated Moving Average with Exogenous Regressors (SARIMAX), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM)—to predict weekly dengue incidence. Key climate variables, including temperature, humidity, precipitation, and wind speed, were integrated into these models, with lagged variables included to capture delayed climatic effects on dengue transmission. The NBR model demonstrated the best performance in terms of predictive accuracy, achieving the lowest Mean Absolute Error (MAE) compared to other models. The inclusion of lagged climate variables significantly enhanced the model’s ability to predict dengue cases. SARIMAX and LSTM models, although effective in capturing seasonal trends, struggled with overfitting and failed to accurately predict short-term outbreaks. XGBoost exhibited moderate predictive power but was sensitive to overfitting, particularly without fine-tuning. Our findings confirm that climate-based machine learning models, particularly the NBR model, offer valuable tools for forecasting dengue outbreaks in BRVT. However, improving the models’ ability to predict short-term peaks remains a challenge. The integration of meteorological data into early warning systems is crucial for public health authorities to plan timely and effective interventions. This research contributes to the growing body of literature on climate-based disease forecasting and underscores the need for further model refinement to address the complexities of dengue transmission in highly endemic regions.

Introduction: Obstructive sleep apnea syndrome (OSAS) is characterized by recurrent episodes of upper airway obstruction and involves intermittent hypoxia and sleep fragmentation, with potentially serious consequences for affected patients. (1–3). Although nocturnal polysomnography is the gold standard, it is an exam that is not readily available and is very expensive. (4). Hence, the need to find new diagnostic methods. Considering that the causes of OSAS can be divided into anatomical-structural ones, related to craniofacial anomalies, it has been hypothesized that anthropometric measurements taken by new 3D stereophotogrammetric systems could be useful as a diagnostic tool in pediatric patients with OSAS (5) (6). The primary objective of the study is, therefore, to evaluate the correlation between mandibular length measured between menton and gonion, obtained through 3D stereophotogrammetry using the "Face Scanner maxi 6", and the severity of OSAS (AHI classification), defined by the score of the Sleep Clinical Record (SCR) questionnaire in a group of pediatric patients with suspected obstructive sleep disorders. The secondary objective concerns the identification of possible correlations between other mandibular parameters estimated by 3D stereophotogrammetry and the severity of OSAS, defined by the McGill Oximetry Score (MOS), and the association between MOS and SCR to determine the AHI level. Materials and methods: The study considered patients who were prescribed a pulseoximetry exam due to suspected obstructive sleep disorders. All participating patients underwent a specialized orthodontic examination, which included completing the SCR questionnaire and taking facial photographs using a 3D stereophotogrammetric system. The SCR questionnaire considers 11 dental, nasal, oropharyngeal, and facial phenotype parameters to determine a final score from 0 to 18, indicating the risk of obstructive sleep apnea syndrome. The acquired stereophotogrammetric images were processed using dedicated software to obtain a three-dimensional model representing the patient's facial phenotype. Subsequently, anatomical landmarks and relevant anthropometric measurements were identified on the model, and it was assessed whether one or more of these showed concordance criteria with the parameters derived from SCR and MOS. The anthropometric evaluation was performed by expert operators, taking into account mandibular variables. Results: Fifteen patients were analyzed, with 2 excluded due to alterations in the stereophotogrammetric images caused by poor patient cooperation during the acquisition of the photographs. Spearman's correlation analysis was performed to investigate the relationship between anthropometric measurements, obtained by 3D stereophotogrammetry, and OSAS severity, by means of SCR, MOS, and SCR+MOS. A significant and negative correlation was observed between right mandibular length (gonion-menton) and MOS (ρ=−0.586, p=0.036). Conclusions: The result obtained has important implications for the field of study and suggests that future attention should focus more on the mandibular length variable as a determining factor for OSAS. However, the sample examined was relatively small, which might obscure the correlation with contralateral mandibular length and potential correlations with other mandibular/facial parameters. Additionally, the small sample size prevented stratification by sex and age. The study thus provides an important contribution to understanding the relationships between 3D stereophotogrammetry and pediatric OSAS but also highlights the need for further research that could potentially influence future developments in diagnosing OSAS in children.

This paper aims to investigate appropriate mathematical models devoted to optimization of some cleaning processes related to pharmaceutical contaminants removal. In our previous recent works has been reported that a possibility for removal from water sources of this type of micropollutants is to rehabilitate the existing cleaning plants by introducing efficient techniques such as adsorption on granulated active carbon filters, micro-, nano- or ultrafiltration. To have such processes under a better control and to pass from small to large scale treatment stations, specific mathematical models are necessary. Starting from Navier-Stokes equations and imposing proper boundary conditions, some mathematical physics problems are obtained for which adequate solving methods via variational methods and surjectivity results are proposed. The importance of these solution characterizations consists in their continuation in a numerical method and the possibility to visualize the result by using CFD program.

Objectives: Although the prevalence of metabolic syndrome (MetS) has increased among Koreans, the specific health benefits of the Korean Healthy Diet (KHD) score remain unexplored. This study aimed to evaluate the association between the KHD score and MetS, and to identify the optimal cutoff of the KHD score for reducing MetS prevalence. Methods: This cross-sectional study used data from 11,403 participants of the 7th and 8th Korea National Health and Nutrition Examination Survey. The KHD score was calculated based on adherence to 13 dietary components. Logistic regression analysis was used to determine the association between the KHD score and MetS, and to identify the optimal cutoff values for the KHD score. Results: The average KHD score was significantly lower in participants with MetS than in those without MetS (5.03 vs. 5.14, p=0.016). A one- and two-point increase in the KHD score was associated with reduction in MetS prevalence (one-point, odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.91–0.98; two-point, OR: 0.90, 95% CI: 0.84–0.97). The optimal cutoff for the KHD score was identified as &gt;7 points, which was related to lower odds of MetS (OR: 0.78, 95% CI: 0.65–0.93) compared to 1–4 points, particularly with hypertriglyceridemia (OR: 0.80, 95% CI: 0.69–0.94) and low high-density lipoprotein cholesterol (OR: 0.85, 95% CI: 0.74–0.98). Conclusions: The KHD score was inversely associated with MetS prevalence, and the identified optimal cutoff values can serve as a practical tool for public health interventions aimed at reducing the risk of MetS.

Excess associated gas from unconventional wells is typically flared while excess produced water is injected underground. In this work, flare gas recovery is integrated with produced water desalination and a solar pre-heater. The solar module with a beam splitter preheats the produced water. Aspen Plus was used to perform process modeling as well as to estimate capital and operating costs. The Solar-Flare Gas RDcovery- desalination (Solar-FGRD) process can conserve water resources and reduce the brine injection by 77%. The accompanying solar farm results in excess solar electricity for exporting to the grid. The process burner combustion efficiency (CE) is 99.8% with the destruction and removal efficiency (DRE) of 99.99% for methane as opposed to the flare CE of 80-98% (and a methane DRE of 91-98%). The greenhouse gas (GHG) emissions for CO2 and methane in terms of CO2 equivalent (CO2e) can be reduced by 45 % for US North Dakota & Texas flaring and 13% for North Sea flaring by employing the Solar- FGRD process. The comprehensive financial analysis demonstrates the financial-economic feasibility of the investment project with or without tax credits. Best-case and worst-case scenarios provide a realistic range that investors can consider before making investment decisions.

Background: Exclusive enteral nutrition (EEN) is the recommended first-line induction therapy for pediatric patients with active luminal Crohn’s disease (CD). The primary aim of this retrospective study was to ascertain the efficacy of EEN used as induction therapy for children with newly di-agnosed CD resident in the South Island of NZ over a ten-year period (2010 – 2021). Secondary aims were to assess the clinical impact of EEN therapy on anthropometry, biochemistry, the pro-gression to medical therapies over three time periods, and to identify positive predictors of re-sponse to EEN therapy. Methods: This retrospective clinical case review collected data from children diagnosed with CD at Christchurch Hospital, Christchurch, New Zealand, and prescribed EEN as induction therapy between the years January 1st, 2010 – December 31st, 2021. Descriptive statistics, Spearman’s correlation coefficient, multivariate logistic regression test and standard t-tests were used for analyses. Results: Data were collected for total of 161 children, 128 (80%) children were offered EEN as induction therapy and were included in this analysis. One hundred and twenty-one (94.5%) children successfully completed an eight-week course of EEN, and a de-crease in PCDAI scores ≥ 15 points from baseline to the end of week 8 of EEN treatment was seen in 119 (98.3%). L1 and L4 disease location were positive predictors of response (p

This paper presents a novel approach to financial network analysis by leveraging PolyModel theory. Traditional financial networks often rely on correlation matrices to represent relationships between assets, but these fail to capture the complex, non-linear interactions prevalent in financial markets. In response, we propose a method that quantifies the relationship between financial time series by comparing their reactions to a broad set of environmental risk factors. This method constructs a network based on the inherent similarities in how assets respond to external risks, offering a more robust representation of financial markets. We introduce several network topological properties, such as eigenvalues, degree, and clustering coefficients, to measure market stability and detect financial instabilities. These metrics are applied to a real-world dataset, including the DOW 30, to predict market drawdowns. Our results indicate that this PolyModel-based network framework is effective in capturing downside risks and can predict significant market drawdowns with high accuracy. Furthermore, we enhance sensitivity to smaller market changes by introducing new time-series indicators, which further improve the predictive power of the model.

This study aimed to determine the incidence of post-chikungunya chronic rheumatism (pCHIK-CR) its impact on quality of life (QoL) and chronic fatigue in adult seven years after the 2014-2015 CHIKV outbreak in Piedecuesta, Colombia. We evaluated 78 adults (median age: 30 years, IQR: 21.0; women 60.3%) with confirmed CHIKV infection. In 2022, participants underwent a GALS examination and completed surveys on disability, stiffness, health status, and fatigue. A rheumatologist evaluated patients who reported arthralgia, morning stiffness, and abnormal GALS examination. Chronic fatigue was defined as fatigue persisting for over six months. Seven years after infection, 14.1% of participants were classified as pCHIK-CR cases, 41.0% as having non-inflammatory pain likely degenerative (NIP-LD), and 44.9% without rheumatic disease (Wo-RM). Patients with pCHIK-CR and NIP-LD exhibited significantly worse QoL compared to Wo-RM cases. Chronic fatigue prevalence increased from 8.6% in Wo-RM patients to 25.0% in NIP-LD and 54.6% in pCHIK-CR cases. This study implemented a comprehensive clinical as-sessment to objectively estimate and characterize the incidence of chronic rheumatological disease attributed to CHIKV infection. One in seven cases with CHIKV infection develops pCHIK-CR, which impacts both QoL and chronic fatigue. This study contributes to understanding the burden of these arboviruses in the medium term.

Background: Colorectal cancer is a major global health burden, with surgical resection being the standard treatment aimed at curative tumor removal. Oxidative stress plays a crucial role in colorectal cancer progression and prognosis. This study hypothesized that physical removal of colorectal cancer, a primary source of oxidative stress, would reduce blood levels of reactive oxygen metabolite derivatives (d-ROMs), a marker of oxidative stress, and biologic antioxidant potential (BAP) levels, a marker of antioxidant potential. Methods: The study included 123 patients who underwent radical resection for colorectal cancer. d-ROM and BAP levels were measured before and one month after surgery. Results: The clinicopathological analysis showed a correlation between preoperative d-ROM levels and tumor size (p&lt;0.001). The study confirmed a significant reduction in d-ROM levels following tumor resection, indicating reduced systemic oxidative stress. The reduction was significant in stages II and III but not in stage I. The d-ROM ratio before and after tumor resection was significantly higher in cases with positive lymph node metastasis and larger tumor size. BAP levels showed no significant changes post-surgery. Conclusion: These results suggest that d-ROMs could serve as a valuable biomarker for monitoring tumor burden and surgical efficacy in patients with colorectal cancer.

We present how the Bekenstein-Hawking entropy of a growing black hole variant of Rh = ct cosmology model can be rewritten as a function of the Cosmic Microwave Background (CMB) radiation temperature or Hubble parameter, rather than the Hubble radius, as first pointed out by Tatum and Seshavatharam [1]. We then show how our CMB temperature formulae lead to much higher precision in the estimated entropy of the Hubble radius universe, since the CMB temperature can be measured with great precision. We also briefly discuss how the Schwarzschild metric can be rewritten as a function of the Bekenstein-Hawking entropy, and how the entropy of the universe can be directly linked to recent estimates of the number of quantum operations in the universe since its beginning.

This research explores the role of transparency and traceability in the agricultural food supply chain. By utilizing blockchain's decentralized and secure features, stakeholders can improve information sharing from farm to consumer, transparency and traceability issues. Real-world examples illustrate blockchain's successful application in agriculture, boosting transparency, efficiency, and trust and create immutable records, enhance visibility, and provide reliable data, while combating fraud and promoting sustainability. It also examines blockchain's impact on food safety through IoT and smart contracts, highlighting successful implementations in supply chain management, the research underscores blockchain's potential to build consumer trust in food safety, quality, and origin.

Process parameters influencing mechanical properties have always been a critical area of research for quite some time. We investigated the effect of laser power and laser scan velocity on the impact strength and maximum stress of 3D-printed metallic specimens of steel 1.2709 and 1.4542. Laser power significantly affected the impact strength and maximum stress of both the steels. With the increase in laser power, the impact strength increased for 1.2709 steel. However, there was a little increase in the impact strength with increasing laser power in the case of 1.4542 steel. Laser power had a decreasing impact on the maximum stress for 1.2709 steel. For 1.4542, maximum stress increased with increasing laser power, but then gradually declined. We observed that using laser power beyond 350W led to printing defect in the specimens, as maximum stress for some specimens reached close to zero in the case of 1.4542 steel. Laser scan velocity had a strong declining effect on the impact strength of 1.2709 steel.

Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality worldwide, including in Croatia. Since most patients have multiple disorders and diseases caused largely by the same risk factors, and as it is essential to approach each patient as a person with all disorders, today we are talking about a new paradigm - cardio-renal-metabolic (CKM) syndrome and cardio-renal-metabolic health, which necessarily includes brain health. Elevated systolic blood pressure, LDL cholesterol, smoking, obesity, diabetes, impaired renal function or chronic kidney disease, which all stem from insufficient physical activity, unhealthy diet with excessive intake of table salt, and air pollution, are the leading causes of overall morbidity and mortality from CKM diseases, especially mortality from CVD. Experts from various fields key to CKM health have written this document with the aim of integrating it as part of the national plan for the prevention of chronic non-communicable diseases with a focus on CVD, which should become mandatory and be based on the existing guidelines of professional societies.

Osteoarthritis (OA) is a degenerative joint disease characterized by cartilage degradation and inflammation. This study investigates the therapeutic potential of secretome derived from adipose tissue mesenchymal stem cells (ASCs) in mitigating inflammation and promoting cartilage repair in an in vitro model of OA. Our in vitro model comprised chondrocytes inflamed with TNF. To assess the therapeutic potential of secretome, inflamed chondrocytes were treated with it and concentrations of pro-inflammatory cytokines, metalloproteinases (MMPs) and extracellular matrix markers were measured. In addition, secretome-treated chondrocytes were subject to a microarray analysis to determine which genes were upregulated and which were downregulated. Treating TNF-inflamed chondrocytes with secretome in vitro inhibits the NF-κB pathway, thereby mediating anti-inflammatory and anti-catabolic effects. Additional protective effects of secretome on cartilage are revealed in the inhibition of hypertrophy markers such as RUNX2, COLX and increases in Col2a1 and ACAN production as well as the upregulation of Sox-9. These findings suggest that ASC-derived secretome can effectively reduce inflammation, promote cartilage repair, and maintain chondrocyte phenotype. This study highlights the potential of ASC-derived secretome as a novel, non-cell-based therapeutic approach for OA, offering a promising alternative to current treatments by targeting inflammation and cartilage repair mechanisms.

The aerospace industry has made extensive use of titanium alloy material due to its exceptional qualities, which include high strength, low weight, and resistance to corrosion. However, these qualities also pose challenges for the material's processing. This paper examines the Ti6Al4V milling endmills coating. First, an analysis is done on the solubility of Ti and Si elements. It is discovered that W and Co elements are far more soluble in Ti than Si and Zr elements, which can effectively stop element diffusion. Next, the base's composition was planned. It was discovered that when the amount of Al increased, the base's surface roughness increased while its hardness and elastic modulus decreased. The binding force between the substrate and the base was greater at 50: 50 Ti:Al ratio. TiSiN and TiSiN/ZrN functional layer properties are examined. When Zr is added to TiSiN/ZrN coating, it improves the coating's hardness and elastic modulus, increases density, and decreases surface roughness and friction coefficient when compared to TiSiN coating. Lastly, an analysis of the initial and intermediate tool wear was done using the Ti6Al4V milling experiment. It was discovered that adding Zr element could successfully extend the tool's cutting life by preventing adhesive wear.

Ramsey approach to the vectors fields is introduced. Set of vectors defined on R^3, taken as the generators of the bi-colored complete graph, is introduced. Vectors are considered as the vertices of the graph. Following coloring procedure is suggested: vertices numbered i and j are linked with the red edge if their scalar product is non-negative; and they are linked with the green edge if their scalar product is negative. This procedure gives rise to the complete, bi-color graph. Graph generated by six vectors inevitably contains the monochromatic triangle: the Ramsey number Ring-like systems of generating vectors are addressed. Applications of the graphs emerging from the vector fields are discussed.

Physics is imagined in the human brain which was formed in Darwin's Evolution by responding to certain threats for the survival of our evolutionary ancestors. The struggle to survive prevented us from wasting resources by paying attention to parts of reality that had no survival impact. These parts are of unknown scope and dimension. Can we negotiate this Darwin's barrier? As to reality within our reach, we suffer from imbalance between information absorption capacity and information analysis capacity which resulted in ignoring the overflow of information to match human capacity to make sense of it. Also James Clerk Maxwell suggested that reality has small scale phenomena beyond our human reach. Since we have no brain other than what Darwin equipped us with, this barrier looked unsurmountable. But lo and behold: much as we have built vehicles to carry us further than our biological legs, so we now build artificial intelligence machines that carry us beyond our Darwinist barrier. Physics may transform to building AI capability to ride on. This capability may require a more universal geometry and material representation to fit AI inference engines. Suggesting Depth Unbound Reality Architecture (DURA). AI connects raw data to its conclusion potential, by-passing a storied theory of nature. The objective of physics ahead may be to build theory-replacement AI machines.

Launched on 2 February 2018, CSES is the first constellation in China to advance our understanding of seismo-ionospheric influence and lithosphere-atmosphere-ionosphere coupling process in electromagnetic environment during earthquake prediction practice. For this purpose, a software platform developed for automatically searching ionospheric perturbations from the CSES plasma data had been put into service immediately after the Wushi MS 7.1 earthquake occurred on 23 January 2024 to weekly detect possible precursory information before impending aftershocks. Effective ionospheric variations were successfully detected two times during more than four weeks. An ionospheric perturbation with an enhanced magnitude 38.3% was primarily detected on electron density but none on ion density on 24 January 2024 at night orbit 33175 and the corresponding variations in different parameters recorded at the same orbit presented a complex features. There irregularities possibly combined with influence both from three following strong aftershocks with magnitudes over 5.0 during 25–30, January and magnetic storm disturbance due to Kp value once up to 3.7 on 24 January. An electron perturbation with an amplitude 24.6%, as well as an ion one with 27.3%, was successfully searched automatically at the same revisiting orbit 33251 occurred on the revisiting date of 3 February 2024 in a magnetic quiet period. These two plasma variations, as well as ones on other ionospheric parameters, were characterized by highly similar properties, which increases the availability as seismic precursors. However, no obvious variations had been observed at other revisiting orbits or other orbits near the aftershock areas during this period till the occurrence of a magnitude 5.3 earthquake on 24 February and the strongest one 5.8 on 25 February, respectively, 20 days after and 1000 km away.

Commercial Brazilian wheat flour was subjected to extrusion, oven, and microwave treatments. The solubility, monomeric and polymeric proteins, and glutenin and gliadin profiles of gluten were analyzed. In addition, in vitro digestibility and response against potential celiac disease immune-stimulatory epitopes were investigated. All treatments resulted in low solubility of the polymeric and monomeric proteins. The amounts of insoluble proteins increased from 5.6 % in control flour to approximately 10 % for all treatments, whereas soluble proteins decreased from 6.5 % to less than 0.5 % post treatment. In addition, treatments affected glutenin and gliadin pro-files. The amount of α/β- gliadin extracted decreased after all treatments, while that of γ-gliadin was unaffected. Finally, alteration of the gluten structure and complexity was not sufficient to render a product safe for consumption for individuals with celiac disease; the number of poten-tial celiac disease immune-stimulatory epitopes remained high.

The primary purpose of this prospective cohort study was to determine if treating endometriosis with optimal excision surgery leads to lower rates of repeat surgery as compared to historical rates of repeat surgery by ablation. A secondary outcome was to examine whether the use of hormonal suppression differed before surgery, depending on the stage of endometriosis found at surgery. Optimal excision was defined as completely excising all areas of abnormal peritoneum, wherever found in the pelvis, having looked systematically with near contact laparoscopy. All surgeries were performed by a single surgeon specializing in optimal excision at a tertiary referral center. The rate of repeat surgery after optimal excision surgery for endometriosis was remarkably low (2.5%, 15/620) as compared to historical rates of repeat surgery by ablation. Additionally, the lack of significant evidence between hormonal suppression use and progression of stage of endometriosis provides implicit evidence that hormonal suppression does not prevent progression of the disease. Further controlled studies are needed to verify these findings.

Background: The inflammation associated with overweight and obesity seems to alter iron metabolism, but there are few studies evaluating those conditions in children. Thus, we aimed to evaluate leukometric, immunological and hematimetric parameters of overweight and obese schoolchildren. Methods: This is a cross-sectional study, in which 39 children living in Chonim de Cima (Brazil), underwent anthropometric, hematological and immunological assessments. The evaluated parameters were compared between the study group (overweight/obesity, n=15) and the control group (n=24). Unpaired t-test, Mann-Whitney test and linear regression were used for statistical tests and the panoramic profile was used to illustrate differences between groups. Results: The study group had lower mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) and higher TNF levels compared to the control group. Positive correlations were observed between BMI-for-age percentile and total leukocytes (r=0.1493; p=0.0151) or neutrophils (r=0.1395; p=0.0192). Negative correlations between the BMI-for-age percentile and MCV (r=0.1464; p=0.0162) and MCH (r=0.1460; p=0.0164) were found. Furthermore, through the panoramic profile it was noted that the study group had a higher frequency of individuals with high levels of TNF and lower frequencies of individuals with increased hemoglobin and serum iron. Conclusions: Our data suggests that overweight and obesity contribute to a pro-inflammatory context (leukocytes, neutrophils and TNF) and MCV and MCH reduction in schoolchildren.

This paper explores a novel approach to modeling the positional dynamics of stars using discrete dynamical systems. We define star evolution through discrete-time update rules based on right ascension, declination, and distance, incorporating chaotic behavior via nonlinear functions and external perturbations. By applying Ricci flow and Riemannian metrics, we provide new insights into the positional dynamics of stars. Theoretical computations of Perelman entropy are used to assess system complexity, with high-precision Runge-Kutta methods ensuring accurate solutions for our chaotic model. We quantify chaos using Lyapunov exponents and perform bifurcation analysis to study how parameter variations affect the dynamics. Comparing our model to the Lorenz attractor reveals both similarities and unique characteristics in stellar dynamics. Our results show that entropy increases exponentially, indicating that predicting star positions with precision becomes increasingly challenging over time. This study advances the understanding of chaos in celestial systems and contributes to dynamical systems theory by integrating chaos theory with astronomical modeling.

The experimental investigation of plant growth under space conditions is a necessary prerequisite of long-term space missions. Besides experiments in space, many studies are performed under simulated microgravity, using a clinostat. However, the Earth magnetic field is usually not taken into account in such investigations. Here, a self-designed and constructed system of coupled devices – a clinostat and a Helmholtz cage – is presented. The clinostat can, on the average, cancel the effective gravity field by using two independent rotations, enabling simulated zero-valued gravity experiments. Additionally, appropriately symmetrically mounted Helmholtz cage can be used to cancel the natural Earth magnetic field in the volume where the clinostat is located. The combination of these two devices offers the opportunity, e.g. for bio-inspired experiments in which plant cultivation can be carried out in conditions that imitate space environment. We provide information about the experimental setup and show first experimental results of growth tests.

Human osteosarcoma (OS) is a rare tumor predominantly affecting long bones and characterized by a poor prognosis. Currently, the first line of intervention consists of surgical resection of primary tumors combined with radiotherapy and chemotherapy, with a profound impact on patient’s life. Since surgical removal of OS frequently results in large resection of bones the use of biomaterials to sustain the stability of remaining tissue and to stimulate bone regeneration is challenging. Moreover, residual neoplastic cells might be responsible for tumor recurrence. Here we explored the potential of doped-bioactive glass as novel therapeutic intervention to both eradicate residual malignant cells and promote bone regeneration. Bioactive glass (BAG) has been extensively studied and employed in the field of regenerative medicine, due to its osseointegration properties and ability to improve bone tissue regeneration. We found that the incorporation of tellurium in BAG selectively kills OS cells through ferroptosis while preserving the viability of hBMSCs, and stimulating their osteodifferentiation. Although the mechanism of Te toxicity is still unclear: i) Te-BAG generates lipid-ROS through LOXs activity but not iron overload; ii) Te-dependent ferroptosis is mediated by GPX4 down-regulation, and iv) abrogates the anti-ferroptotic activity of FSP1, which expression confers resistance of OS to canonical induction of ferroptosis.

Gastric cancer has become one of the most common cancers in the world.Immunotherapy, especially immune point inhibitors targeting programmed cell death 1 or its ligand PD-L1, has been successfully applied in the clinical treatment of GC. However, only a small number of cancer patients experience persistent clinical responses during immunotherapy. In this review, we discussed the current status of immunotherapy for colorectal cancer, elucidated the mechanisms mediating immunotherapy resistance, predicted biomarkers for immunotherapy resistance, and strategies for improving immunotherapy efficacy.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, liver damage can be found and the imperative of employing natural antioxidants becomes apparent. In this study, we first showed that 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed group compared to controls (p&lt;0.05). Interestingly, P.lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces P.lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Furthermore, our investigations unveil P.lentiscus’s anti-proliferative efficacy against different human breast cancer cell lines. Thus, our findings underscore P.lentiscus‘s robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene induced mammary cancer initiation. We posit that P.lentiscus may serve as a prophylactic agent against breast cancer and liver oxidative damage instigated by this carcinogen.

Since the identification of acquired immunodeficiency syndrome (AIDS) in 1981, approximately 85.6 million people have been infected with HIV, resulting in 40.4 million deaths. As of 2022, 53% of the 39 million people living with HIV are women and girls. Despite the advent of antiretroviral therapy (ART) improving survival rates, cervical cancer remains prevalent among HIV-infected individuals. By 2030, cervical cancer is projected to cause 727,500 new cases and 432,000 deaths globally. Human papillomavirus (HPV) is a well-known cause of cervical cancer, with HIV infection exacerbating the prevalence of high-risk HPV (HR-HPV) and cervical intraepithelial neoplasia (CIN). HIV and HPV share transmission routes, and HIV worsens cervical carcinogenesis by inhibiting tumour suppressor genes and altering cell cycle regulation. Chronic inflammation and cytokine imbalances, notably increased IL-10 levels, are linked to cervical cancer progression. Despite ART improving overall health, cervical cancer remains a significant issue, highlighting the need for better screening and prevention measures. A cross-sectional study in Brazil evaluated cytokine levels in cervicovaginal lavage among HIV-positive women, revealing a high prevalence of specific HPV types. ART has been shown to reduce the likelihood of developing squamous intraepithelial lesions (SILs) and HR-HPV prevalence, although its impact on invasive cervical cancer remains inconclusive. In a study in Accra, 250 sexually active HIV-positive women exhibited a high HPV prevalence, emphasising the need for regular screening. HPV testing, visual inspection with acetic acid (VIA), and cytology-based tests are primary screening methods, each with specific advantages and limitations. A systematic review and meta-analysis indicated that ART is associated with a lower prevalence of HR-HPV and high-grade cervical lesions, suggesting that early ART initiation may reduce cervical lesion incidence and progression. HPV is a significant cause of sexually transmitted diseases, with high prevalence in sub-Saharan Africa. Studies show a substantial burden of HPV among men in the region, underscoring the potential benefits of HPV vaccination programs. A study in Tanzania highlighted a high prevalence of HR-HPV among HIV-positive men, suggesting the efficacy of HPV vaccines irrespective of HIV status. Cervical cancer rates in sub-Saharan Africa are alarmingly high, necessitating targeted vaccination and prevention strategies.

The learning system is primarily based on teaching, and teaching through digital resources is referred to as e-learning. As the world progresses towards success day by day, the use of technology, digital devices, and modern techniques is becoming increasingly prevalent. The global shift from traditional paperwork to digital learning is one of the most significant changes in the education sector. However, many factors have created numerous hurdles during the online setup. The Covid-19 pandemic has led to serious problems all over the world, with the education sector being one of the most affected. One of the greatest challenges students face during online education is the lack of digital infrastructure, especially in remote areas of Pakistan. The biggest challenge is connecting students with teachers due to limited internet access. Without proper internet connectivity, both students and teachers cannot access educational materials. In this context, the government plays a crucial role in providing adequate facilities to students, particularly in primary schools. If proper infrastructure is not made available during this pandemic, students will be deprived of a good quality education. Therefore, good infrastructure is essential for effective online education. With the proper resources in place, students will be able to receive a quality education.

The mining industry, critical for global resource supply, has historically been linked to significant environmental degradation and social challenges including habitat disruption, water and soil contamination as well as fatalities. But recently the industry has been undergoing a transformative change to meet evolving environmental and societal expectations. Operations Research (OR) provides essential tools and techniques to optimize decision-making processes in this context. This paper presents a comprehensive review of different OR methods and their applications in balancing economic, social and environmental objectives in surface mine planning. By evaluating the strengths and limitations of these techniques, this review offers valuable insights for researchers and practitioners aiming to improve production efficiency and sustainability through advanced planning strategies.

The utilization of biowaste fillers in the development of high-density polyurethane (PU) foams has gained significant attention due to environmental and economic benefits. This study investigates the mechanical properties of PU foams reinforced with biowaste fillers extracted from fish scales (FS) and fish scale derived collagen (FSC). The fish scales and collagen were characterized for their composition and integrated into PU foams at various loadings. Mechanical properties such as tensile strength, hardness, and density were evaluated. ANOVA was used to analyze the mean values. Bonferroni tests were used to identify differences between the filler materials (α=.05). The tensile strength increases with increase in filler content for both FS (59.48 Kpa) and FSC (65.43Kpa). No differences were observed between FS and FSC in tensile strength. Significance differences were observed between the FS and FSC in both hardness and density (p&lt;0.001). The results demonstrated that both fillers enhanced the mechanical properties of PU foams, with collagen-reinforced foams showing superior performance. This suggests that collagen and fish scales can be effective biowaste fillers for developing environmentally friendly PU foams with enhanced mechanical properties.

Ghana spends over $4000 (US dollars) annually managing municipal solid waste (MSW) with little improvement in regional sanitation. Energy demand in the country is also on the rise. Therefore, addressing waste problems via the waste-to-energy valorization approach is necessary for dual benefits. This paper thus seeks to comprehensively review Ghana's MSW's proximate and ultimate compositions for biological and thermochemical conversions. Studies between 2011 and 2024 were analyzed. The findings revealed that the organic fraction of Ghana’s MSW is currently about 10.47Kt per day. The proximate analysis reveals a moisture content from 13.55 – 61.9 %, volatile matter ranges from 6.24 - 80.25%, and the calorific value ranges from 14.96-21.46MJ/Kg. The ultimate analysis revealed that the carbon-to-nitrogen ratios range from 24.3-32.2, and the hydrogen content ranges from 5.53-22.8%. The sulphur and nitrogen contents were below 0.6 and 1.7% respectively. Approximately 2,534.65 GWh of electricity is estimated from the organic fraction. Ghana’s MSW is more suited for biochemical conversions.

As with all new fields of discovery, work on the biological role of G-quadruplexes (GQ) has produced a number of results that at first glance are quite baffling, sometimes because they do not fit well together, but mostly because they are different from commonly held expectations. Like other classes of flipons, those that form G-quadruplexes have a repeat sequence motif that enables the fold. The canonical DNA motif (G3N1-7)3G3, where N is any nucleotide and G is guanine, a feature that is under active selection in avian and mammalian genomes. The involvement of G-flipons in genome maintenance traces back to the invertebrate Caenorhabditis elegans and to ancient DNA repair pathways. A role for GQ in transcription is supported by the observation that yeast Rap1 protein binds both B-DNA, in a sequence-specific manner, and GQ, in a structure-specific manner, through the same helix. Other sequence-specific transcription factors (TF) also engage both conformations to actuate cellular transactions. Noncoding RNAs can also modulate GQ formation in a sequence-specific manner and engage the same cellular machinery as localized by TF, linking the ancient RNA world with the modern protein world. The coevolution of noncoding RNAs and sequence-specific proteins is supported by studies of early embryonic development, where the transient formation of G-quadruplexes coordinates the epigenetic specification of cell fate.

This paper explores the dynamics of political competition, resource availability, and conflict through a simulation-based approach. Utilizing agent-based models (ABMs) within an evolutionary game theoretical framework, we investigate how individual behaviors and motivations influence collective outcomes in civil conflicts. Our study builds on the theoretical model developed by Basuchoudhary et al. (2023), which integrates factors such as resource availability, state capacity, and political entrepreneurship to explain the evolution of civil conflict. By simulating boundedly rational agents, we demonstrate how changes in resource availability and state capacity can alter the nature of civil conflict, leading to different equilibrium outcomes. The findings highlight the importance of understanding individual motivations and adaptive behaviors in predicting the stability and resolution of conflicts. This research contributes to the growing body of literature on the use of agent-based models in evolutionary game theory and provides valuable insights into the complex interactions that drive civil violence.

Objective: To explore the effect of time exposure to flat screen electronic devices with LED lighting and the Mediterranean diet on macular pigment optical density (MPOD). Methods MPOD was measured by heterochromatic flicker photometry in 164 eyes (47 of young women 20-31 years and 35 adult women 42-70 years). Exclusion criteria: evidence of macular degeneration and eyes with cataracts. Data on the use of electronic devices and Mediterranean diet adherence were collected through a survey. Nonparametric analysis of variance and independent sample t-tests were used to compare subjects. Results Significant differences (p

Dengue fever remains one of the most significant public health challenges globally, particularly in tropical and subtropical regions. Traditional early warning systems (EWS) for dengue outbreaks, based on retrospective epidemiological data, suffer from delays and limited predictive accuracy. Modern systems, leveraging real-time data, artificial intelligence (AI), and machine learning (ML), improve accuracy but can be costly and difficult to implement in resource-constrained settings. This paper proposes a novel hybrid model that integrates the strengths of both traditional and modern EWS, with real-world examples from Brazil, and Malaysia. The hybrid model balances accuracy, scalability, and cost-effectiveness, making it a feasible option for low- and middle-income countries.

Several degraded ecosystems worldwide need to attain a stable vegetal cover after mandatory active restoration; thus, plants soil, and soil biodiverse microbes can be taken into consideration for a successful mission. Among environmental and biological variables, interactions with soil and its microorganisms are critical for permanent plant establishment. Thus, advances in the use of microbial management such as inoculation of mycorrhizas and bacteria become a modern aspect of active restoration programs. New strengths have increased worldwide since most plant species, including grasses, associate to mycorrhizae, Thus, a high percent of restored areas, which were degraded due to the increasing mining or conventional agriculture, rest to be monitored. This study shows current reports on active restoration of degraded landscapes as well as the methodology required for a successful ecosystem restoration. Active restoration has been recognized as the best method to restore tropical forests; however, the higher cost of active restoration, which requires planting seedlings, direct seeding, root inoculation of microorganisms or mitigation of disturbances, which aid the recovery process despite monitoring. On the other hand, the spontaneous recovery of trees that colonize and establish in abandoned fields or natural disturbances, named natural regeneration, is less targeted and can require more time to achieve results. We conducted a web of science search of recent published articles on restoration and analyzed them. We confirmed the important role of AMF on root colonization and soil AMF spores as drivers of restoration of main ecosystems according to previous results from restored sites in Brazil. In the restored sites AMF (more than 8 species) was generally found, while in preserved sites dominated Gigaspora, Scutellospora and Acaulospora, restored sites presented relevant AMF richness as well as the preserved sites. Root colonization by AMF in experimental mined sites was high. Vesicles were frequent in restored sites.; however, colonization intensity was generally the same despite treatments. In general, in the control treatments, values of root colonization remain high.

Gold is a significant revenue source for custom copper smelters facing profitability challenges due to low treatment and refining charges, stricter regulations, and rising costs. Gold is also often blended with copper concentrates, but precise recovery rates from smelting processes are poorly documented despite gold critical economic importance. This paper aims to provide the first comprehensive estimates of gold first-pass recovery across various operational units within the copper sulfide concentrate processing flowsheet. It evaluates the effectiveness of different copper smelting and converting technologies in recovering gold. Optimizing gold first-pass recovery is especially important to enhance immediate financial returns and responsiveness to market dynamics, allowing companies to capitalize on favorable gold prices without delays. Given the absence of direct measurements for gold recovery rates, this research develops an estimation method based on understanding gold loss mechanisms during smelting. The study identifies and analyzes key input and output parameters by examining data from various copper producers. By correlating these parameters with gold loss, the research estimates gold first-pass recovery rates within the copper smelting process. Among integrated smelting-converting routes, the flash smelting to Peirce-Smith converting route achieves the highest gold first-pass recovery (98.8–99.5%), followed by the Mitsubishi continuous smelting and converting process (94.3–99.8%), bottom-blowing smelting to bottom-blowing converting (95.8%), flash smelting to flash converting (95.5%), Teniente smelting to Peirce-Smith converting (95.2%), and the Noranda continuous smelting and converting process (94.8%). The final recovery rates are expected to be higher considering the by-products internal recirculation and post-processing within the copper flowsheet. Additionally, superior gold recoveries are attributed to advanced metallurgical practices and control systems, which vary even among companies with similar technologies. The research demonstrates that copper smelting can effectively recover over 99% of gold from sulfide concentrates. Gold accumulates up to 1000 times its original concentration in anode slime during electrolytic refining, generating 5-10 kilograms of slime per ton of copper, which is further processed to recover gold and other by-products. Major smelters operate precious metal plants where recovering gold from highly concentrated anode slime is both cost-effective and efficient.

Fucoidans, known for their diverse biological properties such as anti-inflammatory, antiviral, antitumor, and immune-stimulatory effects, have recently gained attention for their potential benefits in exercise endurance, muscle mass, and anti-fatigue. However, the mechanisms by which fucoidans enhance exercise performance are still unclear. To investigate these effects, we administered 400 mg/kg/day of fucoidan extract derived from Undaria pinnatifida to sixty-four C57BL/6J mice over ten weeks. We evaluated changes in running activity, mitochondrial-related gene expression in skeletal muscle, and alterations in the intestinal microbiome. Our results showed that fucoidan supplementation significantly increased daily running distance and muscle mass by 25.5% and 10.4%, respectively, in mice on a standard chow diet, and with more modest effects observed in those on a high-fat diet (HFD). Additionally, fucoidan supplementation led to a significant increase in beneficial gut bacteria, including Bacteroides/Prevotella, Akkermansia muciniphila, and Lactobacillus, along with a notable reduction in the Firmicutes/Bacteroidetes ratio, indicating improved gut microbiome health. Mechanistically, fucoidan supplementation upregulated the mRNA expression of key genes related to mitochondrial biogenesis and oxidative capacity, such as COX4, MYH1, PGC-1α, PPAR-γ, and IGF1, in both standard chow and HFD-fed mice. Our findings suggest that fucoidan supplementation enhances exercise performance, improves muscle function, and positively modulates the gut microbiome in mice, regardless of diet. These effects may be attributed to fucoidans' potential prebiotic role, promoting the abundance of beneficial gut bacteria and contributing to enhanced exercise performance, increased muscle strength, and improved recovery.

Vascular endothelial growth factor (VEGF) and its receptors (VEGFRs) serve an essential role in tumor angiogenesis and have emerged as potential therapeutic targets in lung cancer. This review explores the significance of serum VEGF levels as a predictive biomarker in non-small cell lung cancer (NSCLC). The VEGF family, consisting of VEGFA, VEGFB, VEGFC, VEGFD, and placenta growth factor (PlGF), engages with specific receptors, including tyrosine kinase receptors (VEGFR-1, VEGFR-2, and VEGFR-3) and neuropilin receptors (NRP-1 and NRP-2), to promote angiogenesis and lymphangiogenesis. VEGF-A, the primary component of the VEGF family, binds to VEGFR-2 to stimulate endothelial cell proliferation and migration, while VEGF-B, VEGF-C, and VEGF-D interact with VEGFR-1 and VEGFR-3 to regulate tumor angiogenesis, lymphangiogenesis, and metastasis. The VEGF/VEGFR signaling pathway activates various downstream effectors, including phospholipase Cγ1, MAPK, and PI3K/Akt, which are essential for maintaining vascular homeostasis and promoting angiogenesis. In NSCLC, elevated serum VEGF levels have been observed, and the VEGF/VEGFR axis is frequently impaired, leading to irregular blood vessel formation and metastatic spread. Despite the development of anti-VEGF therapies, their impact on lung cancer outcomes has been limited. Further research is needed to optimize the effectiveness of these treatments and elucidate the potential of serum VEGF as a predictive biomarker in NSCLC.

Vaccination against HPV significantly reduced the incidence of HPV-related le-sions worldwide. Considering the increasingly younger age of patients in the gynaecological office and the resulting earlier sexual initiation and potentially contact with the HPV virus, doctors need to have tools to verify the diagnosis. Nowadays, women plan motherhood later, so it is necessary to consider whether sexual treatment in the form of, among others, LEEP-conization may increase the risk of premature birth or difficulty dilating the cervix during labour.For this reason, to avoid overtreatment of LSIL changes, methylation testing may be considered. In patients with histopathologically confirmed HSIL during biopsy and ultimately a lower diagnosis - i.e., LSIL or no signs of atypia - methylation turned out to be a useful tool. We performed Pap-smear, HPV genotyping, punch biopsy, LEEP-conization (if needed) and methylation test in 108 women admitted to the District Public Hospital in Poland. Women with a negative methylation test result were significantly more likely to be ultimately diagnosed with LSIL (p=0.013). This means that in 85.7% of patients with HSIL, major cervical surgery could have been avoided if methylation was negative. Methylation testing, as well as dual-staining and diagnostics detecting mRNA transcripts of highly oncogenic types of HPV, might be used in future in the diagnosis of pre-cancerous conditions, mainly of the cervix, and in HPV-dependent cervical cancer screening. The methylation test may also be used in the diagnosis and identification of lesions within the cervical canal, including those located deep within the frontal crypts, not visible even during a professional colposcopic evaluation of the cervix, as well as within the crypts of the palatine tonsils - in diagnostics of head and neck diseases.

Software quantum simulators are the most accessible tools for designing and testing quantum algorithms. This paper presents a comprehensive approach to building a software-based quantum simulator based on classical computing architectures. We explore fundamental quantum computing concepts, including state vector representations, quantum gates, and memory management techniques. The simulator prototype implements various memory optimization strategies, such as full-state representation, dynamic state pruning, and shared memory parallelization with OpenMP and distributed memory models using MPI. Additionally, data compression techniques, like ZFP, are explored to enhance simulation performance by reducing memory footprint. The results are validated through performance comparisons with leading open-source quantum simulators, such as Intel-QS, QuEST, and qsim. Our findings highlight the trade-offs between computational overhead and memory efficiency. This demonstrates that a hybrid approach using distributed memory and compression offers the best scalability for simulating large quantum systems. This work provides a foundation for developing efficient quantum simulators supporting more complex quantum algorithms on classical hardware.

The Surface Water and Ocean Topography (SWOT) mission was launched on December 16, 2022 to measure water levels over both open ocean and inland waters. To achieve these objectives, the SWOT Payload contains an innovative Ka-band radar interferometer, called KaRIn, completed with a conventional nadir altimeter called POSEIDON-3C that has been switched on a month after launch and a few days before KaRIn. POSEIDON-3C measurements provide a link between large scale phenomena and high resolution. POSEIDON-3C design is based on POSEIDON-3B, its predecessor on-board JASON-3. It is also a dual frequency radar altimeter operating in C and Ku bands, but with some improvements to enhance its performance. Even though it is a Low Resolution Mode altimeter, its performances over open ocean, inland waters and coastal zones are indeed excellent.This paper first describes the POSEIDON-3C design, and its modes with a focus on its new features and its Digital Elevation Model that drives its open-loop tracking mode. Then we assess the in-flight performances of the altimeter from an instrumental point of view. For that purpose, special and routine calibrations have been realized. They show the good performances and stability of the radar. In-flight assessments give thus confidence to ensure excellent altimeter measurement stability throughout the mission duration.

Regenerative medicine is an interdisciplinary field that combines stem cell technology and tissue engineering to replace or regenerate human cells, tissues, or organs and restore normal functions. The term 'regenerative medicine' was coined by William Haseltine at a 1999 conference on Lake Como. Since its inception in 1968, the field has offered clinical benefits for the regeneration, repair, and restoration of bones, skin, cartilage, neural tissue, and heart, as well as scaffold fabrication. Inorganic biomaterials play a crucial role in regenerative medicine, often surpassing traditional synthetic materials due to their adjustable intrinsic properties, such as size, topography, charge, and chemical stability. These properties enable a flexible cellular response within intracellular matrix environments and provide structural support for cell adhesion and tissue regeneration. Given the wide gamut of near-future potential applications of inorganic biomaterials, this article gives an overview of their emerging roles in stem cell regenerative research, tissue engineering, artificial skin and cartilage regeneration, neural nerve injuries, 3D bioprinting, and development of new inorganic bio-scaffolds. The review also addresses the challenges related to the clinical application and tissue compatibility of inorganic biomaterials, utilizing current state-of-the-art techniques.

In Eucalyptus plantations, coppice rotations often yield less than initial rotations. The TECHS project (Tolerance of Eucalyptus Clones to Hydric, Thermal and Biotic Stresses) studied short rotation coppicing across a 3,000 km gradient. The main objective of this work was to compare the survival, sprouting and initial growth of Eucalyptus clones managed, and to examine factors that might influence the productivity of the coppice rotation: climate, genotypes and stocking. Eight of the TECHS sites spread from latitudes 6o S to 30o S were included in the coppice study, with 17 genotypes at each site. The initial rotation had been planted at a 3 x 3 m spacing, and also in a spacing trial at densities from 450 to 14,000 trees ha-1. Six months after harvesting the initial Eucalyptus rotation, average survival was 88%, with tropical clones showing over twice the sprouting biomass (6.7 vs 2.9 Mg ha-1) and four times the woody biomass compared to subtropical clones (4.7 vs 1.1 Mg ha-1). Greater initial water deficits had stronger sprouting and growth. Clones with higher belowground carbon allocation in the initial rotation performed better in coppicing, and precipitation became more influential after 12 months. Drought and spacing trial significantly affected growth.

Antimicrobial-resistant bacteria represent a serious threat to public health. Among these bacteria, Salmonella is of high priority because of its morbidity levels and its ability to induce different types of cancer. Aim: This study aimed to identify Salmonella strains encoding genes linked to the promotion of precancerous lesions and to isolate a bacteriophage to evaluating its preclinical potential against these bacteria. Methodology: An epidemiological approach based on wastewater analysis was employed to isolate Salmonella strains and detect genes associated with the induction of precancerous lesions. Antimicrobial susceptibility was assessed by disk diffusion method. A bacteriophage was isolated via the double agar technique, and its morphological characteristics, stability, host range, replication dynamics and ability to control Salmonella under different conditions were evaluated. The bacteriophage genome was sequenced and analyzed using bioinformatics tools. Results: Thirty-seven Salmonella strains were isolated, 17 of which contained the five genes associated with precancerous lesions induction. These strains exhibited resistance to multiple antimicrobials, including fluoroquinolones. A bacteriophage from the Au-tographiviridae family with lytic activity against 21 bacterial strains was isolated. This phage ex-hibited a 20 min replication cycle, releasing 52 ± 3 virions per infected cell. It demonstrated sta-bility and efficacy in reducing Salmonella concentration in simulated gastrointestinal conditions, and its genome lacked genes that represent a biosafety risk. Conclusion: This bacteriophage shows promising preclinical potential as a biotherapeutic agent against Salmonella.