The topic concerns the so far unknown mechanism of bubble effect in a large mass of moistured cellulose heated with mineral oil. The so far well-known phenomenon of bubble effect occurs in the Hot Spot area, i.e., in the place where the hot metal of the windings is in contact with the winding paper. As a result of presented in the article model tests, it was shown that cyclical heating of the transformer windings causes significant drying of the winding paper what reduces the possibility of bubble effect in the Hot Spot area, while there is a possibility of bubble effect appearing in large volume of pressboard heated with mineral oil. It has been shown that the pressure in the air cushion over oil surface, after the bubble effect starts in the pressboard, depends on the ratio of the mass of cellulose to the mass of oil: the greater the ratio, the greater the pressure in the air cushion. The ar-ticle presents the dependence of bubble effect initiation temperature in pressboard heated with oil on pressboard moisture.

Fungi can remarkably sense and adapt to various extracellular stimuli and stress conditions. Oxidative stress, which results from an imbalance between reactive oxygen species production and antioxidant defenses, leads to cellular damage and death. In Trichophyton rubrum, oxidative stress is managed by a complex antioxidant system including thioredoxins, glutathione, catalases, peroxidases, and superoxide dismutase, with glutathione playing a crucial role. The fungus also responds to oxidative stress through critical pathways such as the glycerol high osmolarity pathway, activator protein 1 transcription factor, and responsive regulator SKN7. To better understand the role of the transcription factor StuA in regulating oxidative stress-related genes within these pathways, we conducted gene expression studies in ΔstuA mutant and wild-type strains of T. rubrum cultivated in keratin and under oxidative stress induced by hydrogen peroxide. Our results revealed significant downregulation of essential antioxidant genes, including glutathione transferases and catalases, in the ΔstuA mutant. Moreover, catalase and glutathione S-transferase activities were impaired in the mutants under stress conditions, highlighting the impact of this mutation. These findings underscore the critical role of StuA in the oxidative stress response and fungal pathogenesis and provide new insights into T. rubrum's adaptive mechanisms.

Microplastics (MPs) are plastic particles ranging from 1,000 to 5,000 µm in diameter, posing a growing environmental and health risk. Composting is an excellent way to add nutrient-rich humus to the soil to boost plant development, but it also pollutes agricultural soil with MPs. Previous research has shown that MPs can threaten plant development, production, and quality, hence they must be studied. This study examined how a mixture of three MP types—polyethylene (PE), polystyrene (PS), and polypropylene (PP)—affected greenhouse tomato plant development. MP types were spiked at 1% w/w (MPs/soil) in tomato pots, whereas non-spiked growth medium was the control. Statistical analysis was conducted using an analysis of variance (ANOVA) and Tukey test (95% confidence) to compare treatments and controls. Soil spiked with MPs increased chlorophyll content (SPAD), transpiration rate, photosynthetic rate, and stomata conductance by 5.16%, 16.71%, 25.81%, and 20.75%, respectively, compared to the control but decreased sub-stomata CO2 concentration by 3.23%. However, MPs did not significantly affect tomato plant morpho-physiological features (p > 0.05). Biochemical analysis of tomato fruits showed significant (p < 0.05) reduction effects of MPs on carotenoid, total flavonoid, and sugar but increased protein, ascorbate, and peroxidase activity. However, there was no significant difference (p > 0.05) in the effects of the combined MPs on total phenolic content. These data imply that whereas MPs did not influence tomato plant physiological and morphological properties, tomato fruit biochemistry was reduced. This raise concerns that an increase in MPs in soils may reduce antioxidant content and negatively affect human health contributing to a decrease in food security.

The cultivated passion fruit (Passiflora edulis) is a diploid plant (2n=2x=18) and is an important fruit tree in southern China. However, the occurrence and spread of stem rot in passion fruit severely impact its yield and quality. This study aims to construct a high-density genetic linkage map and identify the quantitative trait locus (QTL) and candidate genes associated with stem rot resistance in passion fruit. In this study, we used an HG and ZG7 hybrid to develop a BC1F1 population consisting of 158 individuals. Take a previously published passion fruit genome as reference, a high-density genetic linkage map was constructed with 1,180,406 single nucleotide polymorphisms (SNPs). The map contains 9 linkage groups, covering a total genetic distance of 1559.03 cM, with an average genetic distance of 311.81 cM. The average genetic distance between 4206 bins was 0.404 cM, and the average gap length was 10.565 cM. The collinearity correlation coefficient between the genetic map and the passion fruit genome was 0.9994. Fusarium solani was used to infect the BC1F1 population, and the resistance to stem rot showed a continuous distribution. A QTL, qPSR5, was identified in the 145.878-152.951 cM region on the 5th linkage group. We performed RNA-seq and RT-qPCR to analyze the expression levels of predicted genes in the candidate region and identified ZX.05G0020740 and ZX.05G0020810 as ideal candidate genes for stem rot resistance in passion fruit. The findings in this study not only lay the foundation for cloning the qPSR5 responsible for stem rot resistance but also provide genetic resources for the genetic improvement of passion fruit.

Breast cancer is among the most prevalent cancers in Indonesia. One of the methods for early detection of breast cancer is utilizing ultrasound images to classify breast conditions into normal, benign tumors, or cancer. The advent of deep learning technology facilitates the image analysis process, such as the use of Transfer Learning Convolutional Neural Networks (CNNs). Generally, CNN models require large and balanced datasets to perform well in classification tasks. However, medical datasets like breast ultrasound images tend to be limited and imbalanced. The Wasserstein GAN (WGAN) is a generative data augmentation method capable of producing synthetic images by learning the pattern of the distribution of real image data. The implementation of the Wasserstein distance results in the training process of WGAN demonstrating stability from epochs 3000, 2500, and 3000 out of a total of 5000 epochs. The quality of the synthetic images improves with an increasing number of training iterations. By using WGAN, all of the evaluation metrics of each classifier are increasing, with the best accuracy score is achieved by VGG16 model with 83.33% accuracy

The origin of life has previously been subject to numerous studies and hypotheses. Typically, related models focus on the emergence of chemical networks such as the RNA world or the Krebs energy cycle. Here, the onset of life is described as a symmetry-breaking kinetic phase transition of the II. kind. The novel symmetry of life is the arbitrariness of code that is fundamental to symbolic information processing, coining all forms of life from the very beginning. Symbols evolved from non-symbolic, structural information of the inanimate physical world. The responsible transition process had been discovered a century ago in behavioural biology, regarded as 'ritualisation'. Physical properties of this transition include neutral Lyapunov stability and critical fluctuations of the associated Goldstone modes. As a conceptual model, a hypothetical simple molecular ritualisation process is suggested, along with the emergent semiotics of symbolic information processing.

Chronic Obstructive Pulmonary Disease (COPD) is a progressive respiratory disorder that poses significant challenges in treatment adherence. This systematic review aims to evaluate the effectiveness of mobile health (mHealth) interventions compared to conventional therapy in improving treatment adherence among COPD patients. A total of 13 randomized controlled trials and comparative cohort studies were included, all investigating the impact of mHealth interventions, such as medication reminders and remote monitoring, in adult COPD patients. Studies with participants under 18 years of age or those with severe comorbidities were excluded. The review identified 4,688 records through comprehensive searches in databases including MEDLINE, WEB OF SCIENCE, and SCOPUS. Of these, 13 studies met the inclusion criteria. Results showed that mHealth interventions improved treatment adherence in some studies, particularly in exercise and symptom monitoring . However, the evidence was inconsistent, and variations in outcomes were reported across different studies. The review concludes that while mHealth interventions show potential in enhancing treatment adherence in COPD patients, further high-quality research with larger sample sizes is required to confirm these findings and support the integration of mHealth into clinical practice. The need for more robust study designs is also emphasized to address current limitations in evidence.

Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnostics due to its ability to produce high-contrast images across a variety of sequences, each highlighting distinct tissue characteristics. This study focuses on enabling multimodal MRI sequences to advance the automatic segmentation of low-grade astrocytomas, a challenging task due to their diffuse and irregular growth patterns. A novel mutual-attention deep learning framework is proposed, which integrates complementary information from multiple MRI sequences, including T2-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, to enhance the segmentation accuracy. Unlike conventional segmentation models, which treat each modality independently or simply concatenate them, our model introduces mutual attention mechanisms. This allows the network to dynamically focus on salient features across modalities by jointly learning interdependencies between imaging sequences, leading to more precise boundary delineations even in regions with subtle tumor signals. The proposed method is validated using the UCSF-PDGM dataset, which consists of 35 astrocytoma cases, presenting a realistic and clinically challenging dataset. The results demonstrate that T2w/FLAIR modalities contribute most significantly to the segmentation performance. The mutual-attention model achieves an average Dice coefficient of 0.87, outperforming traditional approaches. This study provides an innovative pathway toward improving segmentation of low-grade tumors by enabling context-aware fusion across imaging sequences. Furthermore, the study showcases the clinical relevance of integrating AI with multimodal MRI, potentially improving non-invasive tumor characterization and guiding future research in radiological diagnostics.

Background: Hypopituitarism is a potentially serious but often underdiagnosed condition that can occur following non-traumatic subarachnoid hemorrhage (SAH). The condition is characterized by the partial or complete deficiency of one or more pituitary hormones, leading to a range of clinical manifestations that may complicate the recovery process. This narrative review aims to synthesize the current literature on the prevalence, pathophysiology, and clinical implications of hypopituitarism associated with non-traumatic SAH. Methods: A comprehensive review of the literature was conducting by authors using databases such as PubMed, MEDLINE, and Scopus, focusing on studies published in the last two decades. Studies were selected based on their relevance to the topic, with an emphasis on those that reported on the prevalence, diagnostic approaches, pathophysiological mechanisms, and clinical outcomes of hypopituitarism post-SAH. Results: The review revealed a wide variability in the reported prevalence of hypopituitarism following non-traumatic SAH, ranging from 14% to 92.3%, depending on the diagnostic criteria, timing of assessment, and hormonal axes evaluated. Commonly affected hormones include growth hormone, gonadotropins, and cortisol. The pathophysiology of hypopituitarism in this context is multifactorial, involving ischemic damage, inflammation, and direct mechanical injury to the hypothalamic-pituitary axis. While some studies suggest a link between hypopituitarism and adverse clinical outcomes, the evidence remain inconclusive, highlighting the need for standardized diagnostic protocols and longitudinal studies. Conclusion: Hypopituitarism is a prevalent but often overlooked complication of non-traumatic SAH, with significant potential implications for long-term health outcomes. Routine endocrine evaluation and management of pituitary deficiencies are recommended to improve patient care. Future research should focus on refining diagnostic criteria, elucidating the underlying mechanisms, and evaluating the long-term impact of hormone replacement therapy in this patient population.

Bioavailability, release and stability of pharmaceuticals under physicochemical conditions is the major cause of drug candidates failing during their clinical trials. Therefore, extensive efforts have been invested in the development of novel drug delivery systems able to transport drugs to a desired site and to improve the bioavailability. Hydrogels, and peptide hydrogels in particular, have been extensively investigated due to their excellent biocompatibility and biodegradability properties. However, peptide hydrogels often have weak mechanical strength, which limits their therapeutic efficacy. Therefore, a number of methods in improving their rheological properties have been established. This review will cover the broad area of drug delivery focusing on the recent developments in this research field. We will discuss the variety of different types of nanocarrier drug delivery systems, and then, more specifically, the significance and perspectives of peptide-based hydrogels. In particular, the interplay of intermolecular forces that govern the self-assembly of peptide hydrogels, progress made in understanding the distinct morphologies of hydrogels, and applications of non-canonical amino acids in hydrogel design will be discussed in more detail.

Neonatal brain injury remains a significant issue with limited treatment options. The endogenous neurosteroids dehydroxyepiandrosterone (DHEA) and its sulfate ester (DHEAS) have demonstrated promising therapeutic potential in adult brain injury models due to their neuroprotective mechanisms. This study aimed to analyze the neuroprotective potential of DHEA and DHEAS with a particular interest in anti-oxidative properties in a mouse model of neonatal hypoxic-ischemic brain injury. Using the modified Rice-Vanucci model, brain injury was induced in 7-day-old mouse pups, followed by treatment with various concentrations of DHEA and DHEAS (0.1, 1, and 10 µg/g body weight) via intraperitoneal injection after a 2-hour recovery period. Mice were sacrificed after 24 hours for analysis of somatometry, brain injury, apoptosis, microglial activation, and oxidative stress markers (NOX2, 4-HNE, 8-OHdG), along with the anti-oxidant marker SOD1. No statistically significant effects of the treatments were observed at the tested doses and time points. Although this study did not conclusively demonstrate the anti-oxidative neuroprotective potential of DHEA or DHEAS, neither substance exhibited toxic or harmful effects. Several factors may have contributed to the lack of observable effects, underscoring the need for further refinement in future studies of DHEA(S) and other treatments of neonatal hypoxic-ischemic brain injury.

Mzuzu city is Malawi’s fastest growing city but this has brought with it degradation of its urban green infrastructure (UGI) which has contributed to the city’s increased vulnerability to climate change-related hazards such as flooding. Mzuzu’s major UGI, the Lunyangwa River basin (LR) and the Mzuzu Botanic Gardens (MBG), are particularly affected. Nature-based solutions (NBS), interventions that improve the flow of ecosystem services (ES) to enhance and strengthen urban resilience and sustainability at multiple scales, contribute to the restoration, protection and management of ecosystems to address ecological degradation. This study maps land use land cover changes (LULC) to explore the role of NBS interventions in addressing the city’s climate change adaptation and mitigation challenges. The study used remote sensing data obtained from satellite imagery to map spatio-temporal changes in LULC in Mzuzu city in general and the LR basin and MBG ecosystems in particular, over a period of 34 years from 1986 to 2020. The study found that the LR basin and MBG have undergone both formal and informal urban encroachment in some sections and that in these areas urban communities are more affected by flood-related disasters than in those where there has been little or no encroachment. The study concludes that mapping and quantifying urbanisation-driven LULC provides a spatial framework for identifying and targeting NBS interventions which involve urban green infrastructure restoration and protection to address the city’s vulnerability to climate change impacts such as flooding and mudslides.

Gliomas are malignant tumours arising from glial cells in the central nervous system (CNS), presenting significant clinical challenges. High-grade gliomas (HGGs) are particularly concerning as they are the primary cause of CNS cancer-related deaths. Low-grade gliomas (LGGs), which include diffuse types, represent only 15% of all glioma cases. this review aims to identify the critical hub genes associated with HGG and LGG, understand their proliferation, apoptosis, and mutation role in glioma, and their therapeutic potential as well. First, we identified the gene interaction networks by employing bioinformatics techniques, such as differential expression analysis, Venn enrichment, Cytoscape, and CytoHubba analyses. Next, we summarized the role of hub genes, addressing recent advancements and emerging evidence related to the identified hub genes to provide a comprehensive understanding. The analysis revealed ten hub genes: CCNB1, TOP2A, CENPF, NEK2, ASPM, TPX2, PBK, RRM2, KIF15, and ATAD2. Most hub genes showed elevated expression in HGG compared to LGG, and a strong positive correlation with glioma pathology. Also, might hold significant therapeutic potential, particularly CCNB1, CENPF, NEK2, and TPX2, due to their crucial biological functions and the results of gene mania analysis. This review offers an overview and comprehensive knowledge of the hub genes in glioma pathology, which may inform future research and clinical trials aimed at developing targeted therapeutic strategies.

Lysine succinylation, and its reversal by sirtuin-5 (SIRT5), is known to modulate mitochondrial fatty acid β-oxidation (FAO). We recently showed that feeding mice dodecanedioic acid, a 12-carbon dicarboxylic acid (DC12) that can be chain-shortened four rounds to succinyl-CoA, drives high-level protein hypersuccinylation in the peroxisome, particularly on peroxisomal FAO enzymes. But the ability of SIRT5 to reverse DC12-induced peroxisomal succinylation, or to regulate peroxisomal FAO in this context, remained unexplored. Here, we showed that feeding DC12 strongly recruits SIRT5 into hepatic peroxisomes. Knocking out SIRT5 impaired peroxisomal FAO as evidenced by reduced 14C-DC12 flux in liver homogenates and elevated levels of partially shortened DC12 catabolites in urine. Further, mass spectrometry revealed a trend toward less peroxisomal protein succinylation in SIRT5 knockout liver. This is consistent with reduced flux of DC12 through the peroxisomal FAO pathway, thereby reducing production of the succinyl-CoA that chemically reacts with lysine residues to produce protein succinylation. Mass spectrometry comparisons of site-level succinylation in wildtype and SIRT5 knockout liver did not reveal any clear pattern of SIRT5 target sites in the peroxisome after DC12 feeding. However, SIRT5 co-immunoprecipitated with 15 peroxisomal proteins including the key peroxisomal FAO enzymes acyl-CoA oxidase-1 and enoyl-CoA/3-hydroxyacyl-CoA dehydrogenase (EHHADH). In vitro, recombinant SIRT5 partially desuccinylated chemically modified recombinant ACOX1a, ACOX1b, and EHHADH. Desuccinylation by SIRT5 had no effect on enzyme activity for ACOX1a and EHHADH. For ACOX1b, SIRT5-mediated desuccinylation decreased activity by ~15%. Possible interpretations of this data are discussed.

In the midst of the push for dual-carbon goals, urban centers are faced with the imperative of reducing emissions and conserving energy, while rural regions are harnessing their abundant new energy resources to promote balanced urban-rural development. Photovoltaic (PV) power generation, known for its cleanliness, safety, and emission-free nature, is playing a crucial role in the evolution of Henan Province's power supply industry. This paper delves into the current state of Henan's power supply infrastructure, the trajectory of its low-carbon development, and the policies shaping the PV sector. It also examines the establishment of an urban-rural mutual aid model through the lens of alternative energy technologies. By utilizing a combination of case studies and systematic theoretical research, this paper uncovers the untapped economic potential of new energy sources in rural areas and presents strategies for synergistic development in alignment with dual-carbon goals within the power supply industry. The research underscores the significance of an urban-rural mutual assistance model in achieving carbon neutrality, addressing urban-rural development gaps, fostering shared prosperity, and contributing Chinese insights to global climate governance frameworks.

Pastırma is an ethnic meat product defined as dry-curing, drying, pressing the whole muscles of cattle and buffalo, and coating them with a special paste containing fenugreek seed flour, garlic, milled red capia pepper, and water. In this narrative literature review, historical aspects of pastırma, its definition and classification, detailed production steps, composition and yield, chemical and microbiological properties, pastırma fraud and customer concerns are mentioned. In the shape of the narrative review, relevant studies were identified by searching Scopus, Science Direct, Web of Science, Trdizin, and Google Scholar Search included English- or Turkish-based articles, online reports, books, and electronic books. The keywords "pastırma, pastirma, çemen, cemen, cemening, cemen paste, Fenugreek" were used. The results of this review indicate that future studies on pastırma may focus on related cultural aspects, elimination of unpleasant odour from fenugreek, histological and chemical effects of pressing meat parts, kinetics of drying, osmotic dehydration, and developing new starter combinations.

Background/Objectives: Chronic Musculoskeletal Pain (CMP) is a rather widespread and heterogeneous health problem whose evaluated framework can be of fundamental importance to intervene effectively and rapidly on the causes and consequences of the pathology, as well as on the dominant symptom of pain. One of the evaluation parameters that is increasingly gaining consensus in the assessment of the health status is the Phase Angle (PA), obtained through bioelectrical monitoring with body Bioimpedance Analysis (BIA); Methods: To evaluate the reliability of the PA as a tool for assessing CMP, data from 53 patients, with an average age of 60 years, were observed. They underwent assessment of perceived pain using the Numeric Pain Rating Scale (NPRS) and of the body's bioelectrical status using the BIA, before the beginning (T0) and after the end (T1) of a cycle of 10 treatment sessions with Ion Cyclotron Resonance - Bioresonance Therapy (ICR-BT); Results: At the end of the observation we detected a significant reduction in the NPRS value and a positive but not statistically significant increase in the PA value. Furthermore, given the misalignment in the significance of the positive trend of the two observed variables, it was not possible to define a clear correlation between pain and the bioimpedenziometric values ​​of patients. Conclusions: The study confirms the efficacy of ICR-BT as a therapeutic tool in the presence of CMP. However, it was not possible to define a clear reliability of PA as a diagnostic tool for CMP. Although PA has shown a promising trend during the study, its non-significant correlation to the pain trend would suggest investigating the topic more deeply, through larger and better structured experimental studies.

Blockchain technology presents significant advancements in demand-side management (DSM) by facilitating decentralized, transparent, and secure transactions within energy systems. This study investigates a novel blockchain-based approach aimed at enhancing electricity efficiency through optimized DSM strategies. We propose an innovative framework that integrates blockchain technology with real-time data analytics to optimize energy consumption, encourage consumer participation, and promote efficient energy utilization. Our experimental analysis reveals that the integration of blockchain enhances DSM by achieving a 25% reduction in electricity costs for consumers, a 30% increase in demand response participation rate, and a 15% improvement in overall grid stability compared to traditional DSM approaches. These findings underscore the effectiveness of our proposed method, showcasing its originality and potential for future energy management solutions.

Aim: This study sought to evaluate the effectiveness of lactate/albumin ratio for ICU mortality prediction in a large cohort of patients with severe Coronavirus Disease-2019 (COVID-19) admitted to the intensive care unit (ICU). Methods: This is a single-center retrospective cohort study of prospectively collected data derived from the COVID-19 dataset for all critically ill patients admitted to an academic ICU. Data were used to determine the relation between lactate/albumin ratio and other laboratory parameters measured on the first day of ICU stay and to evaluate the prognostic performance for ICU mortality prediction. Results: A total of 805 ICU patients were included, the median age (IQR) was 67 (57-76) years, with 68% being male. ICU mortality was 48% and the median lactate/albumin ratio was 0.53 (0.39-0.59). Survival analysis showed that patients with higher lactate/albumin ratio values had significantly lower survival rates (Log Rank p

Epicauta gorhami is a hypermetamorphic insect that mainly forage soybeans during the adult stage. However, the lack of appropriate references hinders our studying of the gene function in E. gorhami. In this study, refer to five computational tools (Ct value, geNorm, NormFinder, BestKeeper and RefFinder), the stability of 10 housekeeping genes (GAPDH, ACT, RPL4, RPL27, α-TUB, RPS18, EF1α, RPS28, RPL13 and SOD) was assessed by RT-qPCR under three different conditions (adult ages, tissues/organs and temperatures). The findings suggested that SOD and RPS18 were the most ideal references for examine gene transcripts among diverse adult ages and at various temperatures; A pair of RPS18 and RPS28 was the most reliable genes to assess gene expressions in diverse adult tissues. Finally, The relative expression levels of EgUAP were computed after normalization RPS18 and RPS28 with across diverse adult tissues. As expected, EgUAP expression was abundant in the foregut, trachea and antenna, and low in the midgut, hindgut and epidermis. These findings will lay a solid foundation for analysing the gene expression of E. gorhami.

The volatility of global energy markets, particularly electricity prices, plays a crucial role in influencing international economic activities. With the ongoing global energy transition and the push for low-carbon development, predicting electricity prices has become increasingly important for policymakers and market participants. This paper explores the forecasting capabilities of the ARIMA and LSTM models in analyzing electricity prices in the United States, drawing from data spanning 2001 to 2024.ARIMA, a traditional time series model, is valued for its simplicity and effectiveness in capturing linear trends, while LSTM, a deep learning-based model, excels at handling long-term dependencies in complex datasets. This study reveals that while both models offer valuable insights, each exhibits limitations. ARIMA struggles with non-linear patterns and volatility, whereas LSTM tends to underestimate extreme price values. The findings highlight the potential of hybrid models that combine traditional and machine learning approaches to enhance forecasting accuracy in the increasingly dynamic energy market. This research provides essential guidance for improving decision-making processes in the context of the global shift towards clean energy.

An urgent issue that mankind faces is energy transition, the shift away from fossil-based systems of energy production and consumption required for both biological survival and economic production. Energy is a conserved quantity, so we’ll never run out of energy that the mission of the energy transition is the search for a sustainable supply of free energy, the conceptual centerpiece of thermodynamics. The orthodox version of thermodynamics is referred to as energy physics, which is undergirded by the dual foundations of free energy, the concept, and the conversion doctrine of free energy. While free energy dissipates continuously and spontaneously, it is the conversion doctrine that infers the tenet of “a continuous and irrevocable qualitative degradation of free into bound energy.” Free energy consumption is the cause of our energy problem, but the “irrevocable degradation of free energy” has led us astray in framing the energy problem as well as searching for its solution. Two previous papers proposed a new theoretical system, Unified Classical Thermodynamics (UCT), defined by rejecting the conversion doctrine of energy physics. This paper, the third of the trilogy, focuses on the real rationale behind rejecting the conversion doctrine: with the doctrine as the core of the conceptual foundation of energy physics, the conceptual foundation precludes energy physics from carrying out its theory-development based on its methodological foundation, conceptual differentiation. UCT is thus identified to be a theoretical system erected on a new cornerstone with dual foundations, both conceptual (entropic) and methodological (differentiation)—on which we can investigate the sustainability of a WHOLE system keeping the WHOLE planetary system, as well as individual organisms and economic units, far from equilibrium.

Mono-crop plantation widely found in the world and dominated by few species such as Eucalyptus, Pinus and Tectona. While they lack diversified product, negative to environmental service and limited forest product for local use. The experiment was designed to evaluate the impact of mixed plantings on the early growth performance of the E. globulus tree species. The treatments included one monoculture of E. globulus and a combination of the plant with three other native and one foreign tree species. In four consecutive years after plantation, height, root collar diameter, DBH and leaf/branch count were measured. Following two years of out planting, the survival rates of seedlings were determined. Destructive sampling was applied to measure biomass of E. globulus. The growth performance of E. globulus in mixed plantations was compared to that of trees produced in pure plantations. The findings showed that there were no significant variations in growth parameters across the treatments. Following two years of out planting, the survival rates of seedlings were determined. The growth performance of E. globulus in mixed plantations was compared to that of trees produced in pure plantations. The findings showed that there were no significant variations in growth parameters across the treatments. The survival rate of E. globulus was good, ranging from 75 to 96.8%. Similarly, the growth performance of E. globulus's root collar diameter was larger even if the trial did not reveal a significant difference between the treatments for height. In comparison to other treatments, the one that included junipers and E. globulus had a higher mean height throughout the course of three years (1.28, 2.53, and 6.12 meters, respectively), as well as a lower RCD in the first and third years (1.3 and 5.34 cm). At year four, E. globulus attain higher in Height and DBH with high growth rate in mixed plantations compared to pure stands. The relative yield of E. globulus in pure stands compare to mixed stands greater than 1. Above and below ground biomass and carbon density of E, globulus is comparable in all treatment. Overall, the study's findings confirm that planting E. globulus improves its mingling with the examined tree species. Such studies ought to be conducted again over a longer time frame in order to examine the effects at a later stage and recommend technologies for broader implementation.

Coastal ecosystems are crucial in mitigating the impact of coastal hazards on society. However, the paucity of infor-mation about the purpose of these ecosystems in reducing floods in Rivers State, Nigeria. This study aims to assess the contribution of mangrove ecosystems in protecting coastal communities from flooding using the InVEST coastal vulnera-bility model (version 3.10.2). The model analyzes various data inputs and assigns relative numbers, ranging from 1 to 5, indicating different levels of exposure. Data on population, bathymetry, shoreline type, land use land cover, and conti-nental shelf were obtained from relevant websites and the InVEST model package. The findings indicate that the mangrove ecosystems in River State offer minimal protection against coastal flooding due to their degraded state caused by oil spills and over-exploitation. Additionally, sandy beaches provide little to no protection, and the socio-economic conditions in the communities contribute to increased vulnerability to flooding. The study recommends awareness programs to educate the public about the importance of mangroves for coastal protection in addition to their conservation and restoration.

The actual types of activities which foster social contact between the tourist-resident and their impact on tourists' or residents' perceptions have received less attention. This study addresses this critical topic by assessing tourists’ impression on the locals through examination of a tourist-resident social contact axis proposed by the authors from a selection of frequent tourist activities. The goal is to evaluate the nature and frequency of tourists’ activities and their impact on their 'image' through five contact scenarios as constructs of social contact. An empirical survey-based study in Kashan, and data from the questionnaire and semi-structured interviews from 165 travelers, we assumed that travelers' experience is heavily influenced by sociocultural practices of wayfinding, eating, shopping, and contact with locals. The results indicate a strong tendency among travelers to communicate directly with the locals on all constructs of their travel behavior. There is also a mutual reflection on behavior and manner.

As virtual reality (VR) games appeal to increasingly large audiences, many newcomers need convenient and flexible onboarding sessions. Traditional methods of creating tutorial levels can be time-consuming and require additional effort from the development team. In this paper, we present a toolkit for computer-assisted tutorial generation in VR. We conducted an interview with developers and a between-subjects user study to evaluate our toolkit compared to a manually designed onboarding experience by measuring user performance in actual gameplay. The results indicate that our toolkit performs equivalently to manual tutorials in terms of user success. Most users subjectively prefer a manually designed tutorial primarily for its aesthetic value. These results are encouraging, as they prove the feasibility of semi-automated onboarding.

Placebo effects are acknowledged and no longer considered inert, as they can trigger neural and organic responses working through circuits involving the rostral anterior cingulate cortex, pontine nucleus, and cerebellum. Recent findings of quantum tunneling have expanded the possible functions of placebo interventions that may explain the rigidity of belief systems and functionality of homeopathy, opening a new chapter of the future of medicine, drawn from the prefrontal cortex, amygdala, anterior cingulate cortex, and striatum. The choice of current interventions, such as psychedelic substances, SSRIs, TMS, and DBS, can be expanded as our knowledge about the placebo intervention improves. At the same time, we need to understand the pros and cons of placebo-controlled clinical trials to ensure that stereotyped clinical trial designs do not hamper new drug development.

Solar driven hydrogen generation is one of the promising technologies to a address the world’s growing energy demand in an sustainable way. While, for hydrogen generation (otherwise water splitting), photocatalytic, photoelectrochemical and PV-integrated water splitting systems employing conventional semiconductor oxides materials and their electrodes are under investigation over a decade, lead (Pb)- halide perovskites (HPs) made their debut in 2016. Since then, the exceptional characteristics of these materials, such as their tunable optoelectronic properties, ease of processing, high absorption coefficients, and long diffusion lengths, have positioned them as a highly promising material for solar-driven water splitting. Like in solar photovoltaics, in solar driven water splitting field is also dominated by Pb-HPs with on-going efforts to improve the material stability and improving the hydrogen evolution/generation rate (HER). Despite this, with the unveiling potential of various Pb-free HP compositions in the photovoltaics and optoelectronics inspired researchers to explore the potential of these materials in water splitting. In this current review, we outlined the fundamentals of the water splitting, summary of Pb HPs in this field and the associated issues are presented. Subsequently, Pb-free HPs compositions and strategies employed for improving the photocatalytic and/or electrochemical activity of the material are discussed in detail. Finally, this review presents existing issues and future potential of lead-free HPs, which show potential for enhancing productivity of solar-to-hydrogen conversion technologies.

Cryptococcus neoformans is an opportunistic fungal pathogen that is a continuous global health concern especially for immunocompromised populations. The World Health Organization recognized C. neoformans as one of four critical fungal pathogens, thus emphasizing the need for increased research efforts and clinical resource expansion. Currently there are no fungal vaccines available for clinical use. Exciting new findings in cryptococcal vaccine development have identified whole cell-based and protein subunit-based vaccinations to help mitigate health risks and make commercialization attainable. Importantly, recent work has focused on how different cryptococcal cell wall antigens modified in these vaccine candidates allow us to manipulate their immunogenicity to produce a desired long term protective anti-fungal immune response. In this review we discuss the different cryptococcal cell immunogens, namely the polysaccharide capsule, glucans, chitin/chitosan, mannoproteins, and extracellular vesicles and their role in novel cryptococcal vaccination approaches. Additionally, we examine the immunological mechanisms responsible for protection in these vaccine candidates and the similar host response stimulation pathways induced through different immunogen exposure.

Background/Objectives: Clinical decision support systems (CDSS) consisting of computerized physician order entry (CPOE) and oncology pathways serve as the foundation of high-quality cancer care. However, the resources needed to develop and maintain these systems have not been characterized for oncology enterprises. Methods: Missing CPOEs for oncology treatments were identified by comparing current CPOEs to those in the Elsevier ClinicalPath treatment pathways. New FDA oncology drug approvals were used to estimate ongoing CPOE build needs. The impacts of missing orders on clinicians and pharmacists were surveyed. Benchmarking from two other large oncology enterprises supported new resource needs to build and maintain CPOE in our EPIC Beacon system. A program to manage oncology pathways and CPOE for an enterprise using EPIC was developed and implemented. Results: Resources and impacts of CDSS for oncology enterprises are described. Program management is described. Conclusions: Updating and maintaining CDSS for an oncology enterprise requires program management and resources for which a framework has not been previously reported. We present this work as a framework for others to understand the components and resources for budgeting and management of CDSS. We report on the work of the City of Hope enterprise using the EPIC electronic health record.

Background: Food properties can directly influence individual dietary intake. Therefore, computer vision-based food recognition could be used to estimate meal contents for patients with metabolic diseases. Food recognition based on deep learning can create opportunities for breakthroughs in dietary interventions for personal health management and have rapidly emerged as dietary assessment strategies. Methods: This study proposed a methodology for automatic food recognition based on fine-grained visual classification, the High-temperaturE Refinement and Background Suppression network (HERBS). A technical investigation was conducted involved in the HERBS model on CNFOOD241 benchmark to verify the model effectiveness. The visualization analysis of HERBS was compared with the VGG16 and RepViT on CNFOOD241. Results: The system achieved classification accuracy of 82.72 % and 97.19 % in Top-1 accuracy and Top-5 accuracy respectively. Data showed that HERBS structure widened the attention area and outperformed VGG16 and RepViT on feature maps. Conclusions: Our findings elucidated that the proposed methodology using HERBS model establishes a new benchmark for SOTA performance in food recognition on CNFOOD 241 dataset. This study proved the feasibility of the proposed approach in a challenging food dataset. We further described a vision-language model structure consisting of a multi-modal vision model, language encoder and a multilayer perceptron classifier for food composition recognition.

Acute cardiovascular disorders are incriminated in up to 33% of maternal death and the presence of sickle cell anaemia (SCA) aggravates the risk of peripartum complications. Herein, we present a 24-year Caribbean old woman with known SCA who developed vaso-occlusive crisis at 36-week gestation that justified emergency caesarean section in Pointe à Pitre (Guadeloupe). In the early postpartum period, she experienced acute res-piratory distress in the context of COVID-19 infection that required tracheal intubation with mechanical ventilation. Cardiogenic shock with severe biventricular dysfunction developed that was initially treated with inotropes and vasopressors. As the hemody-namic condition worsened, the cardiac surgical and intensive care team at the Universi-ty Hospital of Martinique (UHM) was requested to apply veno-arterial extracorporeal membrane oxygenation (ECMO) support and, a few hours later, the patient was trans-ferred by helicopter to the UHM. Administration of cardiovascular drugs was rapidly tapered off, there were no signs of ongoing hemolysis and progressive recovery of ven-tricular function allowed weaning of ECMO support, three days after implantation. The patient was extubated one day later, chest-X-Rays showing partial resolution of lung edema and she was transported back to Guadeloupe under medical treatment.

In order to improve the energy, operational and ecological efficiency of District Heating Systems (DHS) powered by a Combined Heat and Power (CHP) plant or a Heating Plant, Thermal Energy Storages (TES) should be used. Improvement of energy efficiency is primarily associated with greater operational efficiency of energy generation, improvement of operational efficiency and fewer start-ups and number of operating hours of peak boilers. Improving ecological efficiency is associated with lower emissions of pollutants into the atmosphere. The presented paper examines the impact of the use and operation of a TES built in a CHP plant supplying a large DHS on the amount of particulates emission to the atmosphere. Detailed research was carried out for Siekierki-Warsaw and Białystok CHP plants in Poland. The analysis allowed to determine the factors affecting the reduction of pollutant emissions and the volume of the energy effect of using a TES in the CHP plant. In order to objectify the results of the comparative analysis of the impact of TES in CHP plant on the emission of particulates, the so-called Comparative Index (CI) was in-troduced, which takes into account the volume of electricity and heat production and climatic conditions in the analyzed time periods. The CI for the analyzed years, should have a similar value so that the results of the comparative analysis are fully representative. This condition is met for the selected base and comparative year for the CHP plant and DHS of Białystok, so the detailed results of analysis are presented for this facility. As a result of the application of TES in Białystok CHP plant, significant environmental effects related to the reduction of particulates emission have been achieved, for example, the total amount of annual Particulate Matters (PM) emission (PM10 and PM2.5) has been reduced by 27% and the maximum emission by 29%. On the other hand, the average decrease in particulates emission in the heating season varied in the range of 10 - 50%, while in the summer season the values of particulates emission were at a comparable level. A significant decrease in annual and one-hour average concentrations for PM10 and PM2.5 and particulates fallout for these two analyzed years was also found. The use of TES to reduce the occurrence and nuisance of the smog phenomenon, the main components of which are PM, is proposed, and selected models of forecasting concentrations of pollutants in the air, including particulates emission, are presented in order to implement this type of activities.

Introduction: Rural areas face additional challenges in preventing, preparing for, responding to, and recovering from disasters. This study aimed to understand how rural General Practitioners PHCPs perceive their roles, involvement, and capacity in disaster health management. Methods: For this qualitative descriptive research, semi-structured interviews were carried out with convenience and purposive samples of rural PHCPs before and during the COVID pandemic. Open, axial, and selective coding were employed to analyse the data inductively. Results: five interviews were conducted pre-COVID and ten interviews during the second and third waves of COVID. Identified themes were similar between the two periods. Rural PHCPs were underutilised due to a lack of awareness of their capacity and a lack of infrastructure and support for greater involvement. Conclusion: Rural PHCPs can be better integrated and supported in readiness for a whole of system response to future disasters.

Market dynamics is based on classical electrodynamics and uses quantum electrodynamics as a reference model framework. Its construction is always based on Bourbaki structuralism. Market dynamics studies the interaction between price, demand and supply. Quantum electrodynamics studies the interaction between photons, electrons and positrons. Both belong to the category of single charge dynamics and share a symmetry group. Market dynamics introduces market charge and defines demand and supply respectively. By examining the market hesitation phenomenon, spin is introduced as the intrinsic property of demand and supply. Therefore, demand and supply can be defined by Dirac spinors. By introducing the coin cone and valence shell, virtual prices are defined; demand and supply interact by exchanging virtual prices. These interactions can be described by Feynman diagrams. The cognitive field has the function of polarizing decision-making and is described by the magnetic field. Market dynamics believes that the social economy itself is an experiment and every market participant is an observer. We established the non-commutative relationship of market observation and the market version of the uncertainty principle of observation information, and defined the quantum version of the invisible hand. On the basis of classical electrodynamics, the relationship between price field and Maxwell field is discussed, and the concept of gauge potential is introduced. Market fluctuations (including mesoscopic and quantum fluctuations) caused by high-order cognition (including gaming, decision-making and reasoning). The fluctuation phenomena inherent in various markets are the basis for understanding both the cognition of market participants and the phase transition of the market. Six components of the market wave function are defined, namely the global phase factor, global gauge potential and global gauge field strength, as well as the local phase factor, local gauge potential and local gauge field strength. Gauge transformation is a integral part of quantum electrodynamics and market dynamics. The gauge principle is then given to show that global symmetry is a necessary condition for local symmetry. Four operators are introduced, namely the Newton mean operator, the Einstein cone operator, the Schrödinger evolution operator and the Dirac field theory operator. These four operators are applied to the market wave function respectively, presenting four operator phases of the market wave function. The change of operator state is called the phase transition of the market wave function.

Accurate measurement of pulverized coal concentration (PCC) is crucial for optimizing the production efficiency and safety of coal-fired power plants. Traditional microwave attenuation methods typically rely on a single frequency for analysis while neglecting valuable information in the frequency domain, making them susceptible to the varying sensitivity of the signal at different frequencies. To address this issue, we propose an innovative frequency selection method based on principal component analysis (PCA) and orthogonal matching pursuit (OMP) algorithms and implement a multi-frequency microwave sensing system for PCC measurement. This method transcends the constraints of single-frequency analysis by employing a developed hardware system to control multiple working frequencies and signal paths. It measures insertion loss data across the sensor cross-section at various frequencies and utilizes PCA to reduce the dimensionality of the high-dimensional full-path insertion loss data. Subsequently, the OMP algorithm is applied to select the optimal frequency signal combination based on the contribution rates of the eigenvectors, enhancing measurement accuracy through multi-dimensional fusion. Experimental results demonstrate that the multi-frequency microwave sensing system effectively extracts features from high-dimensional PCC samples and selects the optimal frequency combination. Filed experiments conducted on five coal mills show that, within a common PCC range of 0–0.5 kg/kg, the system achieves a minimum mean absolute error (MAE) of 1.41% and a correlation coefficient of 0.85. These results indicate that the system can quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability.

The dietary proteins are one of the most important factors determining health conditions in human. The sufficient digestion and absorption of dietary proteins in the digestive tract have positive effects on performance and recovery in sportspeople or athletes. Improving of protein digestibility is a strategy for maintaining health status and optimal performance in sport or exercise activities. The hypothesis of the present study is that Weizmannia coagulans BC 99 (BC99) can increase muscle mass and strength. This randomized double-blind, controlled trial assigned 72 male college students to receive probiotics (n = 36, 20.25±1.03 years; 1.79±5.94 cm; 73.55±8.73 kg, protein powder with BC99) or placebo (n = 36, 20.19±0.79 years; 179.25±5.16 cm; 73.61±8.24 kg, protein powder) for 12-week. At the baseline and final stages of the study, strength tests and body composition assessment were performed; Blood and stool samples were taken at the end of the 12-week intervention, digestive enzymatic activity of stool samples, biochemical parameters, amino acids and hormone level of plasma were analyzed. BC99 administration significantly improved strength performance, skeletal muscle mass, activity of pepsin and trypsin, the concentrations of branched chain amino acids and essential amino acids, reduced activities of creatine kinase and lactic dehydrogenase and urea nitrogen (BUN) level, and increased testosterone and glucagon-like peptide-1 level in male college students. Therefore, BC99 supplementation can be an important nutritional strategy to improve strength performance, body composition, protein digestion and body metabolism in various groups of individuals.

Background/Objectives: Urinary tract infections represent a global problem with implications on mortality and morbidity. Published data present different bacterial incidence and different antibiotics resistances. With this study, we aimed to evaluate bacteria distribution and antibiotic resistance in a tertiary care hospital from the Western part of Romania. Methods: we evaluated all the positive urine culture from the year 2021 from the Emergency County Hospital “Pius Brinzeu” from Timisoara, Romania. We evaluated 1264 urine cultures and identified the following bacteria: Escherichia Coli, Klebsiella spp, Proteus spp., Pseudomonas auruginosa, Staphylococcus aureus, Enteroccocus spp., Enterobacter spp., Acinetobacter baumanii, Providencia spp., Corynebacterium spp. Results: Median age was 67 with 65.6% females. Diabetes mellitus incidence was 12%. Most common bacteria was E. coli – 44.1%, followed by Enterococcus spp. – 17.1%, Klebsiella spp. -15.7% and Proteus spp. – 5.4% E. coli presented the highest resistance rate to amoxicillin-clavulanic acid (50%), Enterococcus spp. to ciprofloxacin (71.3%), Klebsiella spp. to piperacillin-tazobactam (43.3%) and Proteus spp. to trimetroprime-sulfometoxazole (33%). The highest incidence of MDR bacteria was among Acinetobacter baumanii (40%), followed by MRSA (31.8%) and Klebsiella spp. (25.3%). Conclusions: Bacteria distribution is similar in all the Romanian regions among the positive urine cultures. Antibiotics resistance differ among regions and the MDR bacteria incidence is rising.

Despite the increasing number of placenta accreta spectrum (PAS) cases in recent years, its im-pact on neonatal outcomes and respiratory morbidity has not yet been extensively studied. In this context, it is crucial to understand the underlying mechanisms of neonatal complications. Moreover, no study has yet demonstrated the effectiveness of antenatal corticosteroid therapy (CT) for prevention of the respiratory distress syndrome (RDS) in newborns of mothers with PAS at the molecular level. In this regard, miRNA profiling was performed on 160 blood plasma sam-ples from preterm infants (gestational age 33–36 weeks) and their mothers diagnosed with or without PAS. The samples with PAS were categorized into groups: without antenatal RDS prophylaxis, and with CT admin-istered either 2–7 days, 7–14 days, or more than 14 days before delivery. These groups were compared to a control group without PAS in the absence of antenatal CT. Deep sequencing was conducted using the NEB-Next® Multiplex Small RNA Library Prep Set for Illumina® on the NextSeq 500/550 platform, followed by validation by quantitative real-time PCR. A significant increase in hsa-miR-199a-3p and hsa-miR-382-5p levels was observed in the blood plasma of newborns with PAS (placenta accreta and increta) compared to the control group. In maternal blood, hsa-miR-199a-3p levels were markedly higher than hsa-miR-382-5p. The timing of antenatal CT significantly influenced the levels of hsa-miR-199a-3p and hsa-miR-382-5p in neonatal plasma from mothers with placenta accreta or increta. A clear trend toward normalization was observed when CT was administered within 14 days before delivery, particularly in the seven days before delivery, but not beyond 14 days. Among newborns with PAS, higher levels of hsa-miR-382-5p were significantly associated with increased Neomod scale severity scores of 2, 4, and 5 compared to a score of 0. Additional-ly, a direct correlation was found between hsa-miR-382-5p level in neonatal plasma and hsa-miR-199a-3p level in the same sample (r = 0.49; p = 0.0001), oxygen requirements in the NICU (r = 0.41; p = 0.0016), duration of NICU stay (r = 0.31; p = 0.019), and the severity of the newborn’s condition based on the NEOMOD scale (r = 0.36; p = 0.0051). Logistic regression mod-els based on maternal plasma levels of hsa-miR-199a-3p and hsa-miR-382-5p predicted the need for cardiotonic therapy, invasive mechanical ventilation, or high-frequency oscillatory ventila-tion in newborns during the early neonatal period, with a sensitivity of 95-100%. It was con-cluded that elevated circulating levels of miRNAs, hsa-miR-199a-3p and hsa-miR-382-5p, in ma-ternal and fetal blood are crucial in the development of respiratory and cardiac complications in newborns from pregnancies affected by PAS. These miRNAs regulate surfactant synthesis in al-veolar cells, fetal organogenesis via IGF-1, the formation of proper lung tissue architecture, and vascular tone.

The present study investigates the relationship between cocaine- and amphetamine-regulated transcript (CART) expression, leptin, and hormone profiles (progesterone, testosterone, androstenedione, estradiol, FSH, and hCG) across four ovulation induction protocols (HMG, HMG/hCG, rFSH, and rFSH/hCG), as well as the association between FSH receptor (FSHR) Ser680Asn polymorphisms, CART expression, and IVF outcomes. Data were acquired from 94 women who underwent controlled ovarian stimulation (COS). The outcomes showed no significant variations in BMI between the four stimulation protocols (p-values ranged from 0.244 to 0.909). CART expression had no significant correlation with hormone levels in the entire cohort (progesterone, testosterone, androstenedione, FSH, hCG, and estradiol; p > 0.05). However, CART levels were shown to be adversely linked with the number of follicles >12 mm (r = -0.251, p = 0.018), total oocytes (r = -0.247, p = 0.019), and oocyte maturity (r = -0.212, p = 0.048). A significant negative association was also revealed between CART expression and the thyroid hormone T3 (r = -0.319, p = 0.048). In terms of FSHR polymorphisms, the SER/SER genotype was linked to greater CART levels (mean 4.198 ± 2.257) than the SER/ASN and ASN/ASN groups (p = 0.031). These data indicate that CART expression and FSHR polymorphisms may affect ovarian response and oocyte quality in IVF patients.

Academic performance is the level of achievement that students reach in their educational activities. It is influenced by several factors that should be analysed and prioritised, especially in engineering courses, characterised by their difficulty and low success rates compared to other careers. This paper analyses the impact of these factors on academic performance during exams in a technical college in southwestern Spain, with a particular focus on environmental conditions, identified as a relevant and independent variable. The results show a significant connection with thermal comfort and academic performance. Temperatures within the comfort range (23-26°C) improved students' satisfaction with exams. In contrast, those who experienced thermal discomfort pointed to environmental conditions as the main obstacle to their performance, overcoming factors such as prior preparation and coincidence of exams. These findings underline the importance of optimising the classroom's thermal environment through strategies that promote a more favourable learning space, improving both students' well-being and their academic performance.

Bone age assessment is essential for evaluating skeletal maturity, especially in cases where chronological age is uncertain, such as in unaccompanied foreign minors. Traditional methods, such as the Greulich-Pyle atlas and the Tanner-Whitehouse system, while effective, often result in variability due to manual interpretation and are not fully adapted to ethnically diverse populations. Although automated systems are available, they are typically proprietary, expensive, and require programming expertise, which limits their accessibility. This paper introduces an open-source domain-specific language specifically designed for bone age estimation, offering a balance between flexibility and ease of use. The system provides a straightforward, user-friendly syntax, allowing healthcare professionals without programming knowledge to perform accurate bone age assessments. It integrates well-established bone age methodologies, such as the Greulich-Pyle and Tanner-Whitehouse systems, ensuring flexibility in its application. The system is developed using a test-driven development approach, which guarantees both accuracy and reproducibility in bone age assessments. By offering a customizable, open-source solution, this system reduces costs and eliminates the reliance on proprietary software. Its ability to simplify the bone age estimation process makes it a valuable tool in clinical and forensic settings, particularly for professionals involved in the assessment of unaccompanied foreign minors and other populations where accurate bone age determination is crucial.

As studies have shown, out of all 884 sequenced and analyzed samples, 722 (81.7%) of them have genotype D; 156 (17.7%) - genotype A; 3 (0.3%) - genotype C and the only 1 (0.1%) – genotype B. For two cases (0.2%) a recombinant form of the hepatitis B virus was detected. Genotype D was found representing by subgenotypes D1 (145/20.1%), D2 (371/51.4%), D3 (201/27, 8%) and D4 (5/0.7%); A – A2; C – C1 and C2; B – B4; recombinant forms C2/ D and A2/ С2 were detected. The epidemic process of hepatitis B in the country is supported mainly by the circulation of “local” variants of the virus. At the same time, there are occasional introductions of new variants from outside the country.

Chikungunya is mosquito born disease that is spread across continents. This research provides valuable insights into the potential functional significance of the hydrophobic tail and cysteine-rich regions in E2 proteins. These findings lay the groundwork for future investigations into the specific roles of the C-terminal domain and post-translational modifications, which could ultimately lead to a better understanding of viral mechanisms and potential therapeutic targets..

Endogenous androgens are pivotal in the development and progression of prostate cancer (PC). We investigated nanoparticle formulations of curcumin and piperine in modulating steroidogenesis within PC cells. Using multiple PC cell lines (LNCaP, VCaP, DU145 and PC3) we studied the effects of curcumin, piperine, and their nanoparticle formulations—curcumin nanoparticles, piperine nanoparticles, and curcumin-piperine nanoparticles (CPN)—on cell viability, migration, and steroid biosynthesis. Curcumin and its nanoparticle formulations significantly reduced cell viability in PC cells, with curcumin-piperine nanoparticles showing the highest efficacy. These treatments also inhibited cell migration, with CPN exhibiting the most pronounced effect. In assays for steroid biosynthesis, curcumin and its nanoparticle formulations, as well as piperine and its nanoparticles, selectively inhibited 17α-hydroxylase and 17,20-lyase activities of cytochrome P450 17A1 (CYP17A1). Abiraterone, a CYP17A1 inhibitor, displayed a broader inhibition of steroid metabolism including cytochrome P450 21-hydroxylase activity, whereas curcumin and piperine provided a more targeted inhibition profile. Analysis of steroid metabolites by liquid chromatography-mass spectrometry revealed that CPN caused significant reduction of androstenedione and cortisol, suggesting potential synergistic effects. In conclusion, nanoformulations co-loaded with curcumin and piperine offer an effective approach to targeting steroidogenesis and could be promising candidates for therapies aimed at managing androgen-dependent PC.

The paper is concerned with the problem of assigning value to a transport service that moves a mass M with velocity vAB in a time τAB from a first point A to a more distant point B. It is argued that the value of such a transport service can be measured in an objective and physically accessible way by calculating the physical action WAB(M,vAB,τAB) upon moving a mass M along a specific path joining points A and B. In the specific case of a linear straight-line motion in a force-free field this action attains a minimum value of WAB_ideal= 12MvAB2τAB=12MvABLAB which shows that the function WAB_ideal(M,LAB,τAB) contains all those quantities which in practice determine the money-value of the related transport service. It is argued that with the sensor hardware routinely available in modern cars, the accumulation of transport value with driving can be continuously monitored inside a car. Such accumulation allows the transport value gained at the final destination B to be compared to the intrinsic value of a transport service that connects points A and B. In this way, the potential for optimizing transport services with regard to economic and ecological constraints can be quantitatively assessed and possible improvements be identified.

The theoretical and conceptual frameworks commonly used to study university-to-industry technology transfer (i.e., university technology transfer) are potentially distorting our understanding of the phenomenon and impeding knowledge creation about it. Reification is a particularly chronic pathology in university technology transfer research. Additionally, studies are predominantly from the perspective of universities. Examination of university technology transfer from the perspective of private sector firms (i.e., the demand side perspective), particularly small and medium-sized enterprises, seems to be lacking. Moreover, the quantitative correlational methodologies which are predominantly used to research university technology transfer cannot adequately capture the casual complexity to which the phenomenon is likely subject. This myopia in university technology transfer research is likely driven in part by the theories and conceptual frameworks that scholars have chosen to apply in their studies. This paper presents a human-centered framework for examining macro level organization phenomena that mitigates the problem of reification in technology transfer studies and enables better examinations of the phenomena from the perspective of demand side actors and well as supply side participants. Its usefulness is demonstrated using a mini case study that applies the framework to critique a previously published paper.

The evolution and acceleration of the effects of climate change on the water cycle demand adaptation and mitigation plans. Consequently, the implementation of public policies (management, governance, and strategy) regarding flood risk management or prevention (such as levee heights and spillway dimensions of dams) is based on the characterization of flood hazards. This requires understanding extreme climate phenomena and conducting a rigorous probabilistic analysis of hydrometric data. This study aims to estimate the flood quantiles for lake Nokoue. To achieve this, the adopted methodology involved fitting the Generalized Extreme Value (GEV) distribution, the Gumbel distribution, and the Generalized Pareto (GPA) distribution to the annual maximum water levels of lake Nokoue from 2015 to 2022. We estimated experimental probabilities using the Weibull formula. The assessment of the fit quality of the theoretical probability distributions to our data sample indicated that the Gumbel distribution was the most suitable, with a root mean square error (RMSE) of 0.0724, compared to 0.0754 and 0.0761 for the GEV and GPA distributions, respectively. The position and scale parameters (φ; α) of the Gumbel distribution were estimated to be 3.802 and 0.249, respectively. This allows for the calculation of the probability of an extreme water level occurring within a return period in a single day. Thus, the extreme water levels (flood quantiles) associated with return periods of 10, 50, and 100 years, as determined by the Gumbel distribution, are 4.36m, 4.77m, and 4.95m, respectively. These values are of crucial importance for the design of flood prevention structures (infrastructure) intended to mitigate flood risk.

Background: Peripheral Artery Disease (PAD) affects tens of millions of Americans, and is characterized by the accumulation of plaque within arteries in the arms and legs. Advanced age is a risk factor for PAD, and early recognition through health literacy is imperative to mitigate limb loss. The influence of health literacy on PAD outcomes remains poorly understood, particularly in minoritized communities. The objective of this study is to examine understanding of PAD within San Francisco’s Chinese-speaking population, while discerning preferences regarding PAD educational methods. Material and Methods: An anonymous 14-question survey in Mandarin and English was designed to gauge basic knowledge of PAD and preferred methods for obtaining health information. It was distributed at San Francisco Chinatown health fairs on May 6 and October 14, 2023. Inferential analysis was concentrated on the associations between age, self-reported gender and English proficiency versus PAD baseline knowledge as well as preferred methods to obtain health information. Results: Combining the two surveyed cohorts, 32% of the survey population (29/91) reported prior knowledge about PAD. individuals aged 65-74 were the most prevalent age group. 29/91 had prior knowledge of PAD. While many survey respondents thought that diabetes was a leading cause for PAD (47/76) and arthritis was thought to be the leading symptom related to PAD (32/65). Half of respondents (44/88) expressed a preference for consulting a family doctor for foot wounds, followed by a podiatrist (27/88) and a general surgeon (19/88). The two cohorts that were surveyed had similar and suboptimal understanding of PAD and its complications which confirmed a health literacy gap among the Chinese-speaking population. The top three methods to receive health information were radio, television and newspaper. Interestingly, 65 years old and above (OR 0.124, 95% CI [0.021- 0.0728]) as well as participants who were proficient in English (OR 0.078; 95% CI [0.012-0.52]) were less preferred using radio to receive health information. Male gender was statistically significant to use newspapers to receive health information as opposed to female (p=0.003, OR 5.26; 95% CI [1.76-15.69]). Discussion: Conclusion: The two cohorts that were surveyed had similar and suboptimal understanding of PAD and its complications, which confirmed a health literacy gap among the Chinese-speaking population in San Francisco. To address this gap, factors such as age, education level, and gender need to be better understood in their relation to the impact of learning methods in this population.

Single-stranded breaks (SSBs) are the most frequent DNA lesions threatening genomic integrity-understanding how DNA sensor proteins recognize certain SSB types is crucial for studies of the DNA repair pathways. During repair of damaged DNA the final SSB that is to be ligated contains a 5'-phosphorylated end. The present work employed molecular simulation (MD) of DNA with a phosphorylated break in solution to address multiple questions regarding the dynamics of the break site. How does the 5'-phosphate group behave before it initiates a connection with other biomolecules? What is the conformation of the SSB site when it is likely to be recognized by DNA repair factors once the DNA repair response is triggered? And how is the structure and dynamics of DNA affected by the presence of a break? For this purpose, a series of MD simulations of 20 base pair DNAs, each with either a pyrimidine-based or purine-based break, were completed at a combined length of over 20,000 ns simulation time and compared with intact DNA of the same sequence. An analysis of the DNA forms, translational and orientational helical parameters, local break site stiffness, bending angles, 5’-phosphate group orientation dynamics, and the effects of the protonation state of the break site phosphate group provides insights into the mechanism for the break site recognition.

This study aims to examine how Green Human Resource Management (GHRM) practices influence the development of an environmentally sustainable culture that encourages employees to exhibit pro-environmental behaviours in public and private hospitals in Egypt. A total of 491 healthcare employees were surveyed and the data was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The research identified significant positive correlations between GHRM practices, a pro-environmental psychological climate, environmental knowledge, and employees' environmentally favourable behaviours. The results emphasised the significance of tailored GHRM strategies for different sectors and showed how psychological climate and knowledge mediate the conversion of human resource management (HRM) practices into sustainable behaviours. The study extends the literature by highlighting the relevance of GHRM practices within a healthcare setting in a developing country and indicates that the success of environmental practices is closely linked to their visibility and integration into routine operations. The focus of future studies should be on the long-term effects of GHRM practices, the impact of individual differences, and comparative studies across different sectors and countries to obtain a deeper understanding of how organisational sustainability is influenced by GHRM practices.

The article proposes various new approximate analytical solutions of the boundary value prob-lem for the non-stationary system of Nernst-Planck-Poisson (NPP) equations in the diffusion layer of an ideally selective ion-exchange membrane at overlimiting current densities. As is known, the diffusion layer in the general case consists of a space charge region and a region of local electroneutrality. The proposed analytical solutions of the boundary value problems for the non-stationary system of Nernst-Planck-Poisson equations are based on the derivation of a new singularly perturbed nonlinear partial differential equation for the potential in the space charge region (SCR). This equation can be reduced to a singularly perturbed inhomogeneous Burgers equation, which, by the Hopf-Cole transformation, is reduced to an inhomogeneous singularly perturbed linear equation of parabolic type. Inside the extended SCR, there is a suffi-ciently accurate analytical approximation to the solution of the original boundary value prob-lem. The electroneutrality region has a curvilinear boundary with the SCR, and with an un-known boundary condition on it. The article proposes a solution to this problem. The new ana-lytical solution methods developed in the article can be used to study non-stationary boundary value problems of salt ion transfer in membrane systems.

This article explores the potential of yoga to enhance social intelligence in business executives, with mindfulness as a mediating factor. Utilising a randomised controlled experiment design, 247 executives undertaking professional development programmes were allocated to intervention and control groups. The intervention comprised a 10-week yoga regimen including asanas, pranayama, and meditation. “Tromsø Social Intelligence Scale” was used to measure Social intelligence, whilst mindfulness was assessed via the Mindful Attention Awareness Scale. Results indicate that yoga practice positively influences social intelligence both directly and indirectly through increased mindfulness. The partial mediation observed suggests that whilst mindfulness is a crucial mechanism, it is not the sole pathway through which yoga enhances social intelligence. These findings contribute to the nascent field of contemplative practices in professional development by empirically demonstrating yoga's efficacy in cultivating social intelligence. The study underscores the potential of integrating ancient contemplative practices into contemporary business management, offering a novel approach to developing crucial competencies for navigating complex stakeholder relationships and societal challenges.

This article explores how Artificial Intelligence (AI) is drastically changing the logistics industry by transforming operations and significantly improving customer satisfaction. Through meticulous analysis of real-life cases and extensive examination of numerical data, this comprehensive research thoroughly investigates the profound impact of AI on supply chain management. The findings clearly reveal the multifaceted role of AI in significantly reducing costs, greatly improving delivery accuracy, and significantly enhancing inventory control. AI is not just an incremental advancement, but rather a revolutionary leap forward for the future logistics industry, firmly paving the way for unparalleled automation, digital transformation, and operational effectiveness

One of the most crucial aspects of the user experience in virtual reality (VR) is the sense of presence. To evaluate this, both subjective and objective methods can be employed. While subjective methods are easy to implement and interpret, they may not fully capture user feedback, and the results can sometimes lack consistency. In contrast, using objective methods, such as electroencephalography (EEG), can provide more reliable insights. To investigate the influence of realism on the sense of presence, we conducted an EEG study with 21 participants who experienced two VR environments—one realistic and one non-realistic. During the study, we continuously measured their brain activity using an EEG device. Our findings showed that alteration in the level of realism in an environment can be detected through changes in brain activity. Notably, we observed that users take longer to adapt to a non-realistic environment when transitioning from a realistic scene, compared to the reverse. Although our study has limitations, such as the total number of participants, we gained valuable initial insights into how realism may influence brain activity. These findings suggest that higher realism may lead to reduced cognitive load, increased attention, improved decision-making, and suppression of irrelevant information.

In recent decades, several discoveries have been made that force us to reconsider old ideas about mitochondria and energy metabolism in the light of these discoveries. In this review, we discuss metabolic interaction between various organs, metabolic significance of the primary substrates and their metabolic pathways, namely aerobic glycolysis, lactate shuttling, and fatty acids β-oxidation. We rely on the new ideas about the supramolecular structure of the mitochondrial respiratory chain (respirasome), the necessity of supporting substrates for fatty acids β-oxidation, and the reverse electron transfer via succinate dehydrogenase during β-oxidation. We conclude that ATP production during fatty acid β-oxidation has its upper limits and thus cannot support high energy demands alone. Meanwhile, β-oxidation creates conditions that significantly accelerate the cycle: glucose-aerobic glycolysis-lactate-gluconeogenesis-glucose. Therefore, glycolytic ATP production becomes an important energy source in high energy demand. In addition, lactate serves as a mitochondrial substrate after converting to pyruvate + H+ by the mitochondrial lactate dehydrogenase. All coupled metabolic pathways are irreversible, and the enzymes are organized into multienzyme structures.

Background: Suicidal behavior has been a dilemma in Alzheimer's disease. Many ethical debates have been raised about euthanasia in patients with neurodegenerative diseases, and there is a finding of increased suicide rates in the early stages of dementia. However, little is known about the history of suicide ideations or attempts in people with Alzheimer's disease. We aim to measure questionnaire adequacy and acceptability in this specific study to investigate the history of behaviors and factors associated with suicidal behavior across the lifespan in patients with Alzheimer's disease. Methods: This study is an excerpt from case-control research, where the sample was calculated at 150 participants, 75 for the case group and 75 for the control group. Here, the descriptive statistics of the first third of the case group sample, 25 participants, were made. Adequacy was observed by comprehension of questionnaires, and acceptability was measured by participants' understanding of the study object.Results: The prevalence of suicidal ideation throughout life was 8%, and 4% attempted suicide at some point in their lives. The total score of QLoS had a median of 71, which demonstrated the consideration of a moderate quality of life. The total score of the SAF-quest had a median of 12, which showed a low suicidal behavior history. All patients were included in understanding the questionnaires.Conclusions: This study demonstrated the adequacy, acceptability, and scarcity of suicidality histories throughout life in Alzheimer’s disease patients.

The increasing demand for operational efficiency in small and medium-sized manufacturing enterprises (SMEs) has sparked interest in Lean Six Sigma (LSS) methodologies. LSS integrates Lean’s waste elimination focus with Six Sigma’s variability reduction, offering a comprehensive framework for process improvement. Despite its potential, SMEs face unique challenges in implementing LSS, such as financial limitations and resistance to change. This systematic review evaluates the application of LSS in SMEs, analyzing its impact on operational, financial, and quality performance across different industries and geographical regions. The study identifies key success factors, barriers, and research gaps while proposing regression models to predict financial gains associated with LSS adoption. The review followed PRISMA guidelines, sourcing literature from SCOPUS, Web of Science, and Google Scholar published between 2014 and 2024. The inclusion criteria targeted studies involving LSS implementation in manufacturing SMEs. Data extraction included study characteristics, methodologies, and outcomes. A risk of bias assessment was conducted using the Newcastle-Ottawa Scale. The synthesis involved descriptive statistics, effect measures, and sensitivity analyses. Out of 150 initially identified studies, 109 met the inclusion criteria. The findings demonstrate that LSS implementation significantly improves operational performance, with 77.98% of studies showing reductions in cycle time and defect rates. Financial outcomes, including cost savings and ROI, showed moderate to large effects, with 63.58% of the reviewed studies reporting cost reductions. Quality improvements were noted across studies, particularly in First Pass Yield, with 67% of studies demonstrating enhanced quality metrics. The geographic distribution indicated strong research activity in India (23.85%), the United States (6.42%), and Europe (5.50%). Both developed (46.79%) and developing (45.87%) economies contributed extensively. Key barriers included resource constraints (reported in 45% of studies) and resistance to change (noted in 31%). LSS offers substantial benefits for SMEs, driving process efficiency, cost reduction, and quality improvements. However, challenges such as limited resources and organizational resistance must be addressed for successful adoption. This review provides insights into best practices, highlights research gaps, and suggests areas for future investigation, emphasizing the need for customized LSS strategies tailored to the unique contexts of SMEs.

Recently, it has been hypothesized that alpha-synuclein protein strain morphology may be as-sociated to clinical subtypes of alpha-synucleinopathies like Parkinson’s disease and multiple system atrophy. However, direct evidence is lacking due to a caveat of conformation-specific characterization of protein strain morphology. Here we present a new cell model based in-vitro method to explore various alpha-synuclein (αsyn) aggregates morphotypes. We performed a spectroscopic investigation of the HEK293 cell model transfected with human wildtype-αsyn and A53T-αsyn variants using the amyloid fibril specific heptameric luminescent oligomeric thio-phene h-FTAA. The spectral profile of h-FTAA binding to aggregates displayed a blue-shifted spectrum with a fluorescence decay time longer than in PBS, suggesting a hydrophobic binding site. In-vitro spectroscopic binding characterization of h-FTAA with αsyn pre-formed fibrils suggested a binding dissociation constant Kd < 100 nM. The cells expressing the A53T-αsyn and human wildtype-αsyn were exposed to recombinant pre-formed fibrils of human αsyn. The en-suing intracellular aggregates were stained with h-FTAA followed by evaluation of spectral features and fluorescence lifetime of intracellular syn/h-FTAA, in order to characterize aggregate morphotypes. This study exemplifies the use of cell-culture together with conformation-specific ligands to characterize strain morphology by investigating the spectral profiles and fluorescence lifetime of h-FTAA based upon its binding to a certain αsyn aggregate. This study paves the way for toxicity studies of different αsyn strains in-vitro and in-vivo. Accurate differentiation of specific alpha-synucleinopathies is still limited to advanced disease stages. However, early sub-type-specific diagnosis is of utmost importance for prognosis and treatment response. The po-tential association of αsyn aggregates morphotypes detected in biopsies or fluids to disease phenotypes would allow for subtype-specific diagnosis in subclinical disease stage and potentially reveal new subtypes specific treatment targets. Notably, the method may be applied to the entire spectrum of neurodegenerative diseases by using a combination of conformation-specific ligands in a physicochemical environment together with other types of polymorphic amyloid variants and assess the conformation specific features of various protein pathologies.

Pressure from population growth and climate change stress the limited water resources in the Mediterranean region and threaten food security and social stability. Enhancing food production requires the transformation of irrigation systems and enhancement of local capacity for sustainable water and soil management in irrigated agriculture. The aim of this work is the conversion of traditional irrigation practices, by introducing the practice of optimal irrigation scheduling based on local ET estimation and soil moisture monitoring, and the use of continuous feeding by fertigation to enhance both water and nutrient use efficiency. For this, two trials were established between August and November 2023 in two different pedoclimatic zones (Serein and Sultan Yacoub) of the inner Bekaa plain of Lebanon, characterized by semi-arid and dry subhumid conditions and different soil types. Protected cucumber was tested to compare the prevailing traditional farmer’s practice of empirical nutrient and water management using closed tanks with the advanced methods of water accounting and soil moisture monitoring using differential injector that allow more homogeneous application of nutritive solutions and simple tensiometers. Results showed a significantly higher amount of water applied by the farmers to the protected cucumber with a potential for average saving of 105 mm by improved practices. Water input was accompanied by higher amplitude of variation of soil moisture in the farmer’s practice before and after the irrigation cycle revealing potential stress to plant performance caused by higher water depletion followed by over irrigation. With more than 20% increase in cucumber yield by the transformed practices, a general trend in both locations was observed in the fertilization approach and amounts resulting in lower nutrient recovery in the farmer’s plots. The science-based practices of water and nutrient management showed higher application and agronomic water use efficiency of full fertigation, exceeding 60%, associated with double and triple higher nitrogen use efficiency, compared to those results obtained by the traditional water and fertilizer application methods. The monitored factors contribute to severe economic and environmental consequences from nutrient buildup in the soil-groundwater system in the Mediterranean region.

Altruistic punishment has been found to promote cooperation and address social dilemmas in both small and large societies. For many years, peer punishment has been viewed as a decentralized sanction to promote cooperation. Recent studies have found that centralized sanctions and punishments are more effective. In this paper, we incorporate centralized sanctions (third-party sanctions) into the repeating public goods game to investigate how different patterns of third-party punishment impact public cooperation and the organization’s profit, given enough information. Furthermore, the study assesses the influence of various punishments on cooperative behavior and examines the asymmetric roles of punishments in centralized sanctions. As a result: (1) Given enough information, high-intensity and non-random punishment can maintain long-term and high-level cooperation. (2) Punishment successfully deters free riding, regardless of intensity or randomness. (3) Under punishment, people can swiftly establish cooperative social norms to avoid punishment and, eventually, increase profits, regardless of the pattern applied. Therefore, our study sheds light on the heterogeneity of human cooperative behaviors under different centralized sanctions and proves the effectiveness of punishment in promoting human cooperation.

In today’s Agile and DevOps-driven software development landscape, the need for rapid and accurate bug reporting is more critical than ever. This paper presents a next-generation automation tool powered by large language models and machine learning, aimed at innovating the bug reporting process. The tool automates every phase of bug reporting, from failure detection to severity assessment, duplicate detection, and report generation. By addressing the limitations of manual bug reporting such as inconsistency, scalability challenges, and time inefficiencies, the proposed solution enhances the software testing workflow. Initial findings demonstrate significant time savings, reduced manual errors, and improved collaboration between testers and developers. This work establishes a foundation for fully automated bug reporting, poised to accelerate software development cycles while maintaining high-quality standards.

The Colombian Orinoquia is an ecosystem of major importance due to its hydrological and bio-logical richness. However, these natural landscapes share space and land use with livestock production systems. This study was developed to identify the perceptions and experiences of traditional livestock producers and institutional representatives on human welfare, animal wel-fare and the environment and to identify environmental challenges and opportunities for im-provement within the One Welfare concept. Focus groups were held with producers (men and women) and institutional representatives from Vichada. Cultural and identity dynamics define the concept of human welfare. Animal welfare was based on favoring the animals' natural behavior, maintaining the animal's physical health and good care. The environment was focused on the conservation of the natural savannah. Climate change, solid waste management and the use of controlled burns were major challenges. As solutions, it was proposed that institutional work, partnerships, environmental governance and education should be promoted.

In recent years, UAV-enabled wireless energy transfer (WET) has attracted significant attention for its ability to provide efficient and stable power for ground devices by flexibly navigating 3-dimensional (3-D) space and utilizing the favorable line-of-sight (LoS) channels. Meanwhile, energy beamforming utilizing multiple antennas has been touted as a key technology to substantially enhance the radio frequency (RF)-based WET efficiency by focusing energy beams towards devices in desirable directions. However, energy beamforming design for UAV-enabled WET systems has not been studied, despite its tremendous utility. In this paper, we propose a joint design of the UAV’s altitude and channel statistics based energy beamforming to minimize the overall charging time required for all energy havesting devices (EHDs) to meet their energy demands, while alleviating the additional resources and cost for channel estimation. Unlike previous works that considered only the LoS dominant channel without small-scale fading, we adopt a more general air-to-ground (A2G) Rician fading channel, where the LoS probability as well as the Rician factor depends on the UAV’s altitude. To tackle the highly non-convex and non-linear problem, we first examine a single EHD scenario in order to draw insights by deriving an optimal energy beamformihng in a closed-form, and then devise the efficient methods to jointly design the altitude and energy beamforming for a multiple EHDs scenario. Our numerical results exhibit that the proposed joint design considerably reduce the overall charging time, while benefiting from significantly lowering the computational complexity compared the conventional methods.

The Amazon Biome is home to an extraordinary diversity of wildlife, many of which are reservoirs or vectors for infectious and parasitic diseases that can impact not only the health of wild animals but also human and domestic animal populations. This review highlights the critical importance of studying infectious and parasitic diseases in wild animals within the Amazon, particularly in the context of the One Health approach, which recognizes the interconnectedness of human, animal, and environmental health. The review examines key pathogens, including viruses, bacteria, and parasites, that pose significant risks to wildlife conservation and public health. Through a synthesis of recent literature, the article emphasizes the need for comprehensive surveillance, research, and collaboration between veterinary, medical, and environmental sectors. The results underscore the urgent necessity for an integrated response to emerging diseases, particularly as environmental changes and human activities increasingly disrupt ecosystems in the region. The conclusions advocate for the reinforcement of One Health initiatives in the Amazon Biome to ensure the protection of biodiversity and the prevention of zoonotic disease transmission to human populations.

Background/Objectives: Fats, although essential for the proper functioning of the body, have been linked to an increased risk of developing chronic diseases, especially cardiovascular disease. The aim of this study was to evaluate the intake of total fat, and its components (saturated, monounsaturated, polyunsaturated, and trans fats) in men and women aged 15 to 65 years of the urban population in eight Latin American countries. Methods: Survey data were collected for the ELANS, including 9218 subjects from Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru, and Venezuela. Results: In general, 76.2% of the subjects consumed fat within normal ranges (20-35% of the total caloric value (TCV)). When analyzing its components, a majority of the subjects consumed saturated and polyunsaturated fats within the recommended ranges. However, 94.5% of the population does not comply with the recommended maximum intake of MUFA (10-20%) and only 57.5% comply with the intake recommendation for TFA (0 - 2%). Likewise, on average, women had a significantly higher intake of all types of fat compared to men. Finally, the average fat intake by age indicates that regardless of the age range, the consumption of all fats except MUFA and TRANS are within the recommended ranges, with MUFA being slightly below and TRANS above. Conclusions: Even though the fat intake of the population falls within the recommended range, it is necessary to improve the quality by favoring the consumption of MUFA and reducing the consumption of TRANS.

The clinical and genetic studies strongly support a significant connection between nonalcoholic fatty liver disease (NAFLD) and atherosclerotic cardiovascular disease (ASCVD) and identify ASCVD as the primary cause of death in NAFLD patients. Understanding the molecular factors and mechanisms regulating these diseases, is critical for developing novel therapies that target them simultaneously. Our preliminary immunoblotting experiments demonstrated elevated expression of nidogen 2 (NID2), a basement membrane glycoprotein, in human atherosclerotic vascular tissues and murine steatotic livers. Therefore, we investigated the role of NID2 in regulating hepatosteatosis and atherosclerosis utilizing Western diet-fed Apoe-/- mice with/without NID2 overexpression. Quantitative real-time PCR confirmed increased NID2 mRNA expression in multiple organs (liver, heart, kidney and adipose) of NID2-overexpressing mice. Male mice with NID2 overexpression exhibited higher liver and epididymal white adipose tissue mass, increased hepatic lipid accumulation and fibrosis. Additionally, these mice developed larger atherosclerotic lesions in the whole aortas and aortic roots, with increased necrotic core formation. Mechanistic studies showed reduced AMPK activation in the livers of NID2-overexpressing mice compared with controls, without any effects on hepatic inflammation. In conclusion, these findings suggest that NID2 plays a deleterious role in both hepatosteatosis and atherosclerosis, making it a potential therapeutic target for these conditions.

In this paper, $(\alpha,\beta)$-fuzzy sublattices and $(\alpha,\beta)$-fuzzy ideals of a lattice, where $\alpha\in\{ \in_{\gamma}, q_{\delta}, \in_{\gamma}\vee q_{\delta}\}$, $\beta\in\{ \in_{\gamma}, q_{\delta}, \in_{\gamma}\vee q_{\delta},\in_{\gamma}\wedge q_{\delta}\}$, are introduced and studied. In the special case, $(\in_{\gamma}, \in_{\gamma}\vee q_{\delta})$-fuzzy sublattices and $(\in_{\gamma}, \in_{\gamma}\vee q_{\delta})$-fuzzy ideals of a lattice are presented and their characterizations by three level sublattices and ideals are given.

Hypofunction of the glutamate system in the brain is one of the pathophysiological hypotheses for schizophrenia. Accumulating animal and clinical studies show that sarcosine (N-methylglycine), a glycine transporter-1 inhibitor, is effective for ameliorating the negative and cognitive symptoms of schizophrenia. The aims of the present study were to observe the effects of sarcosine on neuronal activity in the dorsal CA1 (dCA1) hippocampal neurons within an NMDA receptor hypofunction model induced by MK801. We applied in vivo calcium imaging to observe the dynamics of fluorescence from the dCA1 hippocampal neurons when the mice were exploring in an open field. Using this tool, we directly measured and compared neuronal properties between sarcosine-treated and untreated mice. At the same time, the physiological function of the neurons was also quantified by measuring their place fields. Our data demonstrated that MK-801 (0.2 mg/kg) diminished the fluorescence intensity of dCA1 neurons that had been genetically modified with a calcium indicator. MK-801 also significantly increased the correlation coefficient between the fluorescence dynamics of pairs of cells, a feature that may be linked to the symptom of disorganization in human patients with schizophrenia. The spatial correlations of place fields in the mice were impaired by MK-801 as well. Injected sarcosine (500 mg or 1000 mg/kg) significantly alleviated the abovementioned abnormalities. Our data provide evidence to support the use of sarcosine to alleviate symptoms of schizophrenia, especially hippocampus-related functions.

The demand for rice varieties with lower amylose content (AC) is increasing in Southeast Asia, primarily due to their desirable texture and cooking qualities. This study presents the development of whole-grain rice lines with low to intermediate glycemic index (GI) and reduced AC. We selected six rice lines for in vivo GI assessment based on their starch properties. We successfully identified two lines with low AC that exhibited low and intermediate GI values, respectively. Our findings indicate that dietary fiber (DF) content may significantly influence rice GI. The selected whole-grain low-GI line showed a higher ratio of soluble dietary fiber (SDF) to insoluble dietary fiber (IDF) compared to control varieties, highlighting SDF's potential positive role in lowering whole-grain rice's GI. This study underscores the feasibility of developing rice varieties with desirable agronomic traits, nutritional traits, and culinary attributes, particularly for individuals managing their blood sugar levels. Additionally, we proposed the positive role of starch composition, especially DF content, in modulating the GI of rice. This study reinforces the importance of incorporating starch properties and DF content into rice breeding programs to produce more health-oriented and marketable rice varieties.

Two-phase evaporative spray cooling technology can significantly reduce power consumption in data centre cooling applications. However, the literature lacks an established methodology for assessing the overall performance of such evaporation systems. The current study develops a Lagrangian-Eulerian computational fluid dynamics modelling approach to examine the functionality of these two-phase evaporative spray cooling systems. To replicate a modular system, a hollow spray cone nozzle with Rosin-Rammler droplet size distribution is simulated in a turbulent convective natural-air environment. The model was validated against the available experimental data from the literature. A new formulation for the coefficient of performance (COP) is derived to assess the performance of the system. Parametric studies of geometric, flow and climate parameters, namely, domain length, droplet size, water mass flow rate, temperature, and humidity were performed with a specific focus on the climatic conditions in Dublin, Ireland. The findings indicate that at elevated temperatures and low humidity, evaporation results in a bulk temperature reduction of up to 12℃. The efficiency of the evaporation system showed a systematic improvement with a reduction in the droplet size and the mass flow rate. A close to 100 % evaporation rate was achieved in comparison to only a 1 % evaporation rate when the spray Sauter mean diameter (SMD) is reduced to 8-15 μm from 292 μm. It was concluded that the utilization of a fine droplet spray nozzle provides an effective solution for the reduction in water consumption (97 % in our case) for data centres, whilst concomitantly augmenting the proportion of evaporation.

The study is part of the research on the advanced envelope systems aimed at the interaction with the principles of the environmental sustainability at a functional and energetic level, of the reduction of consumption and of polluting emissions. The purpose of the study concerns the analysis of the multi-layer façade systems defined, in general, by the execution of double-skin façades integrated by the devices capable of gaining and transforming the external and internal environmental loads. The methodology concerns the detection of the main functional modes and the proposal of a scientific categorization of the types of multi-layer façade systems, through the examination of experimental case studies. The objective is to determine, as a result of the study, a reference contribution for researchers, manufacturers and expert designers engaged in the field of sustainability combined with the advanced façade systems, detecting the analysis criteria focused on the constructive and functional aspects, transferable also to situations of diffuse character and with different uses. In addition, the results of the study are oriented to provide a scientific reference for subsequent research on the analytical evaluation with respect to the reduction of energy consumption and environmental comfort conditions.

Today, the facility location planning issue mainly belongs to the long-term operational and strategic level of large public and private organizations, and the significant costs associated with facility location, construction, and operation have turned location research into long-term decision-making. Presenting a hub location model for the green supply chain can address the current status of facilities and significantly improve demand coverage at an acceptable cost. Therefore, in this study, a network of facilities for hub location in the service site domain, considering existing and potential facilities under probable scenarios, has been proposed. After presenting the mathematical model, validation was performed on a small scale, followed by sensitivity analysis of the main parameters of the model. Furthermore, a metaheuristic algorithm was employed to analyze the NP-Hardness of the model. Additionally, to demonstrate the efficiency of the model, two metaheuristic algorithms, NSGAII and MOPSO, were developed. Based on the conducted analysis, it can be observed that the computational time increases exponentially with the size of sample problems, indicating the NP-Hardness of the problem. However, the NSGAII algorithm performs better in terms of computational time for medium-sized problems compared to the MOPSO algorithm.

While a number of studies focused on pre-service teachers’ belief change in teacher education programs, the process of English Language Teaching (ELT) pre-service teachers’ belief change on technology integration remains underexplored. Adopting Cabaroglu and Roberts (2000)’s framework, this study investigated the process of belief change among three ELT pre-service teachers in a digital humanity course in a teacher education program in the US. The data were collected from interviews, the “story of self” of the participants, bi-weekly reflective journals, end-of-the semester reflection papers, and lesson plans. The study revealed that student teachers’ beliefs experienced different processes of change during the course, including awareness and realization, confirmation and consolidation, elaboration and polishing, addition, disagreement, and reversal. The paper provides a new understanding of the benefit of a digital humanity course with a technology integration focus in a teacher education program, which could exert a significant effect on affecting pre-service teachers’ beliefs on technology integration.

The dispersive and polar properties of materials, and especially of polymers and copolymers play an important role in several engineering applications implying their surfaces and interfaces. The surface energetic properties of poly(styrene-co-butadiene) have never been studied. We proposed in this study an accurate determination of such properties by using the inverse gas chromatography (IGC) at infinite dilution. Background: The IGC surface technique led to the dispersive and polar properties of poly(styrene-co-butadiene) rubber (SBR) by adsorption of organic solvents at various temperatures. Methods: Our new methodology based on the thermal Hamieh model and the London dispersion interaction energy was used to determine the London dispersion surface energy, the polar acid-base surface energy, and the Lewis acid-base properties of the copolymer. Results: The different surface energy parameters of the SBR were obtained as a function of temperature from the chromatographic measurements. Conclusions: The dispersive and polar free energies of adsorption of the various n-alkanes and polar molecules on poly(styrene-co-butadiene) were determined at different temperatures. A decrease of the London dispersive surface energy and the polar Lewis acid-base surface energies of SBR was highlighted when the temperature increased. It was showed a Lewis amphoteric character of poly(styrene-co-butadiene) with a highest basic constant 10 times larger than its acidic constant.

The rising popularity of UAVs and other autonomous control systems, coupled with real-time operating systems, has increased the complexity of developing systems with the proper robustness, performance, and reactivity. Concurrently, the growing demand for more sophisticated computational tasks, proportionally bigger payloads, battery limitations, and smaller take-off mass necessitates higher energy efficiency for all avionics and mission computers. The purpose of this paper is to develop the technology for experimental studies of indicators of reactivity and energy consumption of the computing platform for unmanned aerial vehicles (UAVs). The paper provides an experimental assessment of the ’Boryviter’ 0.1 computing platform, which is implemented on the ATSAMV71 microprocessor and operates under the open-source FreeRTOS operating system. The results obtained are the basis for developing algorithms and energy-efficient design strategies for the mission computer to solve the optimization problem. The paper provides experimental results of measurements of the energy consumed by the microcontroller and estimates of the reduction in system energy consumption due to additional time costs for suspending and resuming the computer’s operation. The results show that the ’Boryviter’ 0.1 computing platform can be used as a UAV mission computer for typical flight control tasks that require real-time computing under the influence of external factors. As the further work direction, authors plan to carry out the investigation of the proposed energy saving algorithms in scope of the planned NASA’s F’Prime software flight framework. Such an investigation that should be done with the real flight computation load for the mission computer, will help to qualify the obtained energy saving methods and their implementation results.

Tissue engineering is an interdisciplinary field that combines methods, materials, and biological molecules to fabricate newly formed tissues to replace or restore functional organs. Biomaterials-based scaffolds play a vital role in developing new tissue by interacting with human cells. Tissue Engineering scaffolds with ideal characteristics, namely, nontoxicity, biodegradability, and appropriate mechanical and surface properties, are vital for tissue regeneration applications. Although commonly utilized biomaterials can provide physical and chemical properties needed for tissue regeneration, inadequate biomimetic properties, as well as insufficient interactions of cells-scaffolds interaction, still need to be improved for the application of tissue engineering in vivo. Consequently, developing innovative biomaterials-based stimulus-responsive 3D scaffolds that can enhance the mediators of cell adhesion and cellular functioning and that can form functional tissues by providing structural integrity within an appropriate time is much needed. It is possible to achieve some essential features using a single material, so combining two or more materials may fulfill the requirements. In order to achieve a proper scaffold design, a suitable fabrication technique and combination of biomaterials with controlled micro or nanostructures are needed to achieve the proper biological responses. This review highlights the natural polymers, smart materials, and recent advanced techniques currently used to create emerging scaffolds for tissue regeneration applications.

Cationic Antimicrobial Peptides (AMPs), also called Host Defence Peptides have established antimicrobial and anticancer activities. Conjugation of an AMP to a bioactive molecule with complementary activity can address some of the clinical limitations of the peptide candidate. This approach has been particularly applied in antimicrobial applications of AMPs, but remains relatively less explored in the generation of anticancer candidates. Herein, two usnic acid derivatives, based on hydrazinothiazole and benzylidenefuranone pharmacophore moieties, respectively, have been conjugated to L-K6, a lysine/leucine rich AMP, through a new pyrazole ligation intrinsically driven by the cargo molecule. Both components, the usnic acid derivative and the peptide, are selectively active against cancer cells, by targeting the human DNA repair enzyme tyrosyl-DNA phosphodiesterase 1 (TDP1) and through DNA damage, respectively. The two conjugates, based on a hydrazone linkage, exhibited pleiotropic effects, ranging from, overall, reduction of the activity from the parent drugs to their conservation or even enhancement. Notably, the conjugates retain some anti-TDP1 activity and display intermediate, or even higher, cytotoxicities against glioblastoma cells, compared to their individual components.

The effectiveness of a comprehensive maintenance and reliability management process can be assessed through an in-depth analysis of various factors that, collectively, represent the maintenance contribution to the operational and production processes of an industrial asset. There are no simple formulas for designing an integrated maintenance and reliability model within an asset management framework (in accordance with the ISO 55001 standard), nor are there fixed or universal rules that apply equally to all production assets over time. In light of this, the primary goal of this article is to provide an overview of the implementation project of the AMORMS (Asset Management, Operational Reliability Survey), based on the Mainte-nance Management Model (MMM) developed by INGEMAN, at the SINEA PERÚ plant, a leading company in Latin America specializing in the industrial production of recycled plastic containers for commercial beverages (PET preforms - Polyethylene Terephthalate). Lastly, the article outlines the recommendations and high-impact action plans that will support SINEA PERÚ in strengthening the efficiency of its maintenance and reliability management process-es, while effectively optimizing the value of its industrial assets throughout their life cycle.

This study investigates the fundamental equations governing photon behaviour in external gravitational fields due to electromagnetic-gravitational interaction, emphasizing their energy, momentum, and wavelength relationships. Building upon the pioneering contributions of Max Planck and Louis de Broglie, the analysis highlights key equations such as E = hf, ρ = h/λ, and ℓp/tp = c, which elucidate the wave-particle duality and energy conservation principles applicable to photons. The conservation of photon energy in gravitational fields, expressed by Eg = E, underscores the symmetrical nature of photon interactions as they traverse strong gravitational environments. The observed phenomena of redshift and blueshift are interpreted within this framework, alongside a reinterpretation of gravitational lensing as a consequence of the momentum exchange between photons and the curvature of external gravitational fields. This perspective challenges conventional understandings and suggests that established theories may require refinement. The study advocates for the integration of alternative frameworks, such as quantum gravity and flat spacetime models, to address discrepancies between observed photon behaviour and current gravitational theories. By exploring these interactions, this research aims to enhance our understanding of the fundamental laws governing the universe, contributing to ongoing efforts toward a unified theory that reconciles quantum mechanics and gravity.

Current language models have achieved remarkable success in NLP tasks. Nonetheless, individual decoding methods face difficulties in realizing the immense potential of these models. The challenge is primarily due to the lack of a decoding framework that can integrate language models and decoding methods. We introduce the DecoStrat which bridges the gap between language modeling and the decoding process in D2T generation. By leveraging language models, DecoStrat facilitates the exploration of alternative decoding methods tailored to specific tasks. We fine-tune the model on the MultiWOZ dataset to meet task-specific requirements and employ it to generate output(s) through multiple interactive modules of the framework. The Director module orchestrates the decoding processes, engaging the Generator to produce output(s) text based on the selected decoding method and input data. The Manager module enforces a selection strategy, integrating Ranker and Selector to identify the optimal result. Evaluations on the stated dataset show that DecoStrat effectively produces diverse and accurate output, with MBR variants consistently outperforming other methods. DecoStrat with the T5-small model surpasses some baseline. Generally, the findings highlight DecoStrat's potential for optimizing decoding methods in diverse real-world applications.

Background:Lower socioeconomic status (SES) has been associated with increased mortality from coronary heart disease. This excess risk, relative to affluent patients, may be due to a combination of more adverse cardiovascular‐risk factors, inequalities in access to cardiac investigations, longer waiting times for cardiac revascularisation and lower use of secondary prevention drugs. We sought to investigate whether socio-economic status influenced long-term all-cause mortality after PCI in a large metropolitan city (London), which serves a population of 11 million people with a mixed social background over a 10-year period. Methods: We conducted an observational cohort study of 123,780 consecutive PCI procedures from the Pan-London (United Kingdom) PCI registry. This data set is collected prospectively and includes all patients treated between January 2005 to December 2015. The database includes PCI performed for stable angina and ACS (ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI) and unstable angina). Patient socio-economic status was defined by the English Index of Multiple Deprivation (IMD) score, according to residential postcode. Patients were analysed by quintile of IMD score (Q1, least deprived; Q5, most deprived). Median follow-up was 3.7 (IQR: 2.0-5.1) years and the primary outcome was all-cause mortality. Results: The mean age of the patients was 64.3±12.1 years and 25.2% were female. 22.4% of patients were diabetic and 27.3% had a history of previous myocardial infarction. The rates of long-term all-cause mortality increased progressively across quintiles of IMD score, with patients in Q5 showing significantly higher long-term mortality rates compared with patients in Q1 (p=0.0044). This persisted following the inclusion of a propensity score in the proportional hazard model as a covariate (HR for Q5 compared to Q1: 1.15 [95% CI: 1.10-1.42]). Conclusion: This study has demonstrated that low SES is an independent predictor of adverse clinical outcomes following PCI for in a large diverse metropolitan city of London. Hence, attention to reduce the burden of cardiovascular risk factors and improve primary prevention, particularly in patients with lower SES, is required.

In recent years, the chemo-photodynamic combinational therapy has become increasingly popular in treating breast cancer. However, the limited accumulation of nanodrugs into tumor (less than 1% of injected dose) extremely impacts therapeutic efficacy. Herein, the photosensitizer Chlorin e6 (Ce6) and the chemotherapeutic drug rhein (Rhe) were self-assembled to form a carrier-free nanodrug (RC NPs) with good stability and high drug loading rate. Ultrasound (US) irradiation was applied to increase the permeability of tumor blood vessels thus greatly enhance the drug accumulation of RC NPs in tumor tissues. After uptake by tumor cells, Ce6 could produce a sig-nificant amount of reactive oxygen species (ROS) when exposed to laser irradiation, while rhein could inhibit tumor cell proliferation and affect mitochondrial membrane potential, inducing tumor cell apoptosis through the mitochondria-dependent apoptosis pathway, thus effectively realizing the combined effect of PDT and chemotherapy. Taken together, RC NPs have an enhanced EPR effect when exposed to US irradiation and exhibit better tumor suppression, which provides new insights into chemo-photodynamic combination treatment for clinical breast cancer.

Global climate change, characterised mainly by an upsurge in extreme rainfall events, is affecting the precarious economies of most vulnerable countries. The aim of this study is to analyse extreme rainfall events in the Oti watershed, which is characterised by high climatic variability. Daily observed and simulated rainfall and temperature data from two models (CCLM and REMO) in the Cordex programme were used. The data is subjected to statistical processing methods. Climatic indices were calculated using RclimDex software. The results obtained show a spatio-temporal variability in observed and simulated rainfall that follows an increasing north-south gradient. Both models overestimate observed rainfall, with deviations of 1.95 for the CCLM and 8.53 for the REMO. This shows that the CCLM is more realistic in reproducing observed rainfall, is therefore validated for the rainfall projection. The rainfall indices show a non-statistically significant increase in PRCPTOT, R99p, RX1day, RX5 days and CWD on the one hand, and a decrease in the SDII, R10 mm, R20 mm and R95p indices on the other for the observed rainfall. For simulated rainfall, the RCP 8.5 and RCP 4.5 scenarios predict an upward trend in some indices and a downward trend in others from 2025 to 2069.

Cellulose nanocrystals are of major research interest because of their use in biodegradable bioplastcs and food packaging, biomaterials, medical and pharmaceutical applications, cosmetics, electronics, and construction materials. This study introduces an approach combining microwave-assisted extraction (MAE) of cellulose from Aloe Vera plant residue and subsequent isolation of cellulose nanocrystals (CNCs) utilizing sulfuric acid hydrolysis. The MAE process, characterized by its rapid heating and penetrating ability, was optimized to maximize cellulose yield from raw biomass sources under various conditions (microwave power, solvent ratio, and time). Following extraction, the purified cellulose was subjected to sulfuric acid hydrolysis under controlled conditions to yield CNCs, with the aim of preserving the intrinsic crystalline structure while enhancing the material's physicochemical properties. The search for biocompatible and biodegradable materials suitable for biomedical applications has led to significant interest in hydrogels composed of natural polymers. Among these, hydrogels synthesized from cellulose and polyvinyl alcohol (PVA) have emerged as promising candidates due to their unique physical properties and compatibility with biological tissues. This study presents the formulation, characterization, and potential biomedical applications of a cellulose/PVA hydrogel. The hydrogel was synthesized to enable the formation of a semi-crystalline network that imparts the material with enhanced mechanical properties.

This paper proposes a paradigm shift in AI governance by integrating Indigenous knowledge systems to foster inclusivity and cultural sensitivity. Traditional AI governance frameworks are primarily Western-centric, often overlooking the community-oriented values and ethical considerations essential to Indigenous cultures. This study highlights principles such as Kaitiakitanga from Māori culture, which emphasizes guardianship and environmental stewardship, and Hózhó from Navajo philosophy, which stresses harmony and balance. By engaging Indigenous leaders and knowledge holders throughout the AI lifecycle, this approach ensures technology aligns with community values, addressing critical issues like data sovereignty, ethical technology use, and cultural sensitivity. This paper underscores the necessity of relational accountability in AI governance, which includes prioritizing the health of ecosystems alongside community welfare. This model advocates for an AI framework that not only rectifies historical marginalization but also empowers Indigenous communities to shape the technologies affecting their lives. Furthermore, integrating Indigenous perspectives strengthens the ethical foundation of AI systems, advancing sustainability, social justice, and cultural responsiveness in technology applications. The proposed framework illustrates how Indigenous ethical concepts can transform AI governance by aligning technological progress with values of ecological stewardship and community welfare, creating an AI landscape that respects and reflects diverse cultural contexts. Ultimately, this research demonstrates that Indigenous knowledge systems can significantly enhance AI’s effectiveness and equity, paving the way for more sustainable and culturally attuned technological solutions.

The SARS-CoV-2 virus, responsible for the COVID-19 pandemic, has impacted the health of millions globally, with many individuals experiencing persistent symptoms even after testing negative, a condition known as Post-acute Sequelae of SARS-CoV-2 infection (PASC), or “Long COVID”. This study analyzes demographic influences on the severity and timeline of PASC symptoms, with emphasis on physiological and cognitive effects. Using a self-reporting survey method, data was collected from a sample of 110 participants (n=110) and analyzed using techniques such as Exploratory Factor Analysis (EFA), Pearson Correlation, and Two-Factor ANOVA Test. Based on the study, females generally reported higher severity for cognitive and physiological symptoms compared to males, and symptom severity was generally lower among vaccinated individuals. Correlation analysis revealed a significant relationship between depression and cognitive impairments, underscoring the psychological impact of PASC. This study emphasizes the complexity of PASC, demonstrating how demographic characteristics such as age, sex, and vaccination status influence the severity and duration of symptoms, contributing to the growing understanding of PASC. Further research should consider SARS-CoV-2 variant-specific impacts and broader population samples.

Amid the current multi-country mpox outbreak, analyzing monkeypox virus (MPXV) and vaccinia virus (VACV) genomes is vital for understanding evolutionary processes that may impact vaccine efficacy and design. This study aimed to elucidate the phylogenetic relationships and structural features of viral antigens, which are crucial for developing effective vaccines. By aligning 1,903 MPXV genomes from the NCBI Virus repository (released between 2022 and 2024), an increase in phylogenetic diversity was observed compared to previous studies. These genomes grouped into Clade I (25 genomes) and Clade IIB (1,898 genomes), with a new Clade I sub-lineage emerging from samples collected in Sud-Kivu province, Democratic Republic of the Congo. Homology-based modeling of six key neutralization determinants encoded by the highly conserved Clade I MPXV genes revealed several amino acid variants near potential antibody binding sites compared to those of vaccinia and variola virus templates. Despite these structural differences, the long-standing vaccinia vaccines, initially created for smallpox, still play a crucial role in safeguarding humanity against mpox today. The findings have deepened our understanding of disparate evolutionary mechanisms for MPXV and VACV, influencing vaccine efficacy. The workflows for viral genomic analysis and structural modeling in CLC Genomics Workbench will facilitate MPXV research and vaccinology. Finally, this study highlights the critical role of MPXV metagenomic surveillance in identifying viral evolution and potential vaccine resistance.

Tropical cyclones, hurricanes and typhoons (“cyclones”) threaten the lives and livelihoods of many millions of people. The magnitude of this threat justifies scrutiny of all potential mitigation strategies. Here we consider a neglected factor: forests. Forests may influence storm formation, intensity, and behaviour through interactions involving temperature, friction, moisture and aerosols. Understanding these relationships could guide cyclone mitigation and preparedness. With global deforestation continuing and reforestation efforts expanding, the relationships between forests and cyclones are not simply academic—it's a critical consideration for climate adaptation, disaster risk reduction, and sustainable development. Here we show that, despite major unknowns and uncertainties, forest conservation and expansion are likely to reduce cyclone frequency and severity.

Introduction: There are no clear guidelines to support adequate nutrition and growth for our neonates. We have used the difference in weight Z-score medians between birth and discharge (∆ Z-score) to assess the nutritional outcomes in EpicLatino. The ∆ Z-score is often negative, accounting for the desirable fluid contraction at birth that sends the preterm baby usually between 0.5-1 weight Z-score point down the curve. From then on, most researchers accepted a healthy and safe growth parallel to the intrauterine rate. No consensus on the optimal timing for assessment or the ideal growth monitoring tool has been achieved, and an ongoing debate persists on the appropriate terminology to express poor postnatal growth.Methods: We analyzed data from the past 8 years (2015-2022) in surviving home to at least 34 weeks corrected age infants with ≤ 32 weeks gestational age at birth (GA). We conducted a series of statistical comparisons with variables that have been mentioned as potential causes of poor nutrition in the literature. We used the weight ∆ Z-score from birth to discharge as a surrogate for nutrition. We obtained the weight median and interquartile range (IQR) from all the EpicLatino units. We also calculated the correlation between weight ∆ Z-score and gestational age and head circumference (HC) at discharge.Results: There were 480 cases that meet the established criteria. Gestational age at birth, necrotizing enterocolitis (NEC), unit of origin, rupture of membranes (ROM) > 24 hours, temperature at admission, and intraventricular hemorrhage (IVH) were significantly different. There was a negative correlation between ∆ Z-score and corrected gestational age at discharge. Head circumference at discharge also correlated with weight ∆ Z-score.Discussion: There is an important variability in the different units of origin. Also, when looking for risk factors, we confirmed that the characteristics of the study population are determinant to extrauterine growth restriction (EUGR) at discharge. As is known, these associations do not establish causality, some of these variables may identify the challenge of nourishing a sick or very small preterm infant, but the unit of origin variable identifies nutrition policies and practices that can be modified through a quality improvement program.

Phytophthora-induced crop diseases, commonly known as “plant plagues,” pose a significant threat to global food security. In this study, strain ASG80 was isolated from sisal roots and demonstrated broad-spectrum antagonistic activity against several Phytophthora species and fungal pathogens. Strain ASG80 was identified as Streptomyces luteireticuli via phylogenetic analysis, digital DNA-DNA hybridization (dDDH), and average nucleotide identity (ANI). Whole-genome sequencing identified 40 biosynthetic gene clusters (BGCs) related to secondary metabolite production, including antimicrobial compounds. Strain ASG80 extract exhibited broad-spectrum inhibitory activity against Phytophthora nicotianae, P. vignae, P. cinnamomi, and P. sojae. Pot experiments showed that strain ASG80 extract significantly reduced sisal zebra disease incidence, with efficacy comparable to the fungicide metalaxyl. These findings suggest that strain ASG80 is a promising biocontrol agent with substantial potential for managing Phytophthora-related diseases in agriculture.

In light of growing global supply chain instability and carbon neutrality initiatives, South Korea has highlighted the need for a circular economy to reduce its reliance on natural resources. As a critical strategy for promoting the circular economy, remanufacturing has become essential because of its ability to improve resource efficiency and reduce environmental impacts. The automotive sector, which accounts for 80% of the remanufacturing industry, plays a critical role in these efforts. Turbochargers, primarily made of cast iron, represent approximately 20% of sales in the sector and are significant contributors to greenhouse gas emissions, making them an important target for emission reduction. This study examined the greenhouse gas emissions associated with turbochargers across multiple remanufacturing cycles using the LCA method. The results indicated an approximate decrease of 50%, 48%, and 46%, based on the comparative analysis between brand-new products and those remanufacturing one-, two-, and three times. Comparing brand-new and remanufactured products does not fully capture the key advantage of remanufacturing. This advantage lies in its ability to extend the products life cycle by using core parts as primary raw materials and reducing the consumption of new resources. Therefore, it is important to consider the environmental impact of remanufacturing within an expanded process where brand-new products are included in the entire life cycle. Using this approach, the accumulated annual greenhouse gas reduction effect for multiple remanufacturing indicated decreases of approximately 25%, 32%, and 35% for remanufacturing one, two, and three times, respectively, compared to using only brand-new products. This study shows that multiple remanufacturing reduces greenhouse gas emissions compared to the use of brand-new products. In particular, as remanufacturing is repeated, the product lifespan can be extended from three years to up to 12 years with a concomitant decrease in annual greenhouse gas emissions. These findings provide valuable data for modeling and encouraging the greenhouse gas reduction potential driven by remanufacturing across various industrial sectors.

Acute myeloid leukemia (AML) is a severe blood cancer in myeloid cells which is found to be developed due to mutation in genes that causes dysregulation in the gene’s expression, affecting the cellular function and signaling pathways. STK24 is a protein belonging to the Germinal Center Kinase III (GCK III) sub-family, found to be related to many intracellular and intercellular processes. In the following study the expression of the gene STK24 is studied using the web-based tool TNM plot, in which the expression is found dysregulated in AML with a significant p-value of 9.76e - 23. In addition to expression analysis, survival analysis is carried out, the dysregulated expression of STK24 is found to be related to lower overall survivable outcome indicated by significant p-value of 1.6e - 05 with median survival for lower expression of the STK24 for 10.7 month time. In the protein-protein interaction analysis, the targeted protein STK24 was found to interact with several proteins, among them some of the proteins which are found to be related to AML pathogenesis are PDCD10, PPP2R1B, STK11, TCP1, STK25, STK26 and STRN3 with combined score between .5 to 1.00. Among the interacting proteins 20 proteins are found to have higher interaction efficiency which is represented in circular format. A correlation study of the target protein STK24 with AML and glutamine metabolism related protein FLT3, NPM1, RUNX1, RARA, IDH1, IDH2, GLS, SLC1A5, GLUD1 and SLC7A11 showed a significant correlation with Pearson’s coefficient r value between -1 to 1 and p-value &lt; 0.05. With the analysis of expression and survival and protein-protein interaction and gene correlation it can be indicated that STK24 may have a role in pathogenesis in AML. But to conclude the study, further expression of the gene STK24 in the AML is needed to prove its correlation with the disease progression and further in vitro and in vivo analysis are needed to be carried out.

A comprehensive understanding of the mechanisms underlying how Lentinula edodes handles heat stress (HS) is crucial for the development of superior HS-resistant strains. However, the mechanism by which the two sexually compatible haploid nuclei respond to heat stress remains largely unknown. Here, we examined the nuclei-specific (SP3 and SP30) HS-resistant mechanisms using integrated metabolomic and transcriptomic analysis. Results showed HS elicited the boost of ROS and hampered the mycelium growth for both monokaryons. Metabolome and transcriptome data demonstrated that the two sexually compatible monokaryons responded differently to HS. For SP3, the differentially expressed genes were significantly enriched in MAPK signaling, cell cycle and sugar metabolism, whereas those for SP30 were enriched in glyoxylate and dicarboxylate metabolism, and protein processing. The differentially accumulated metabolites of both strains were enriched in the glycerophospholipid metabolism, alpha-linolenic acid metabolism, biosynthesis of cofactors, etc, but with different regulatory modes. The enriched KEGG pathways for SP3 mostly tend to be down-regulated, whereas those in SP30 showed a contrary trend. The genes in MAPK signaling pathway might be associated with the glycerophospholipid metabolism in SP3, but not in SP30. Omics-integration analysis depicted distinguishable regulatory networks and discovered totally different hub genes of the two strains. Our findings revealed for the first time that the two sexually compatible nuclei responded to HS with different mechanisms and provided candidate metabolites, responsive genes and regulatory pathways for further experimental validation.

Low-cost sensors are widely used for air quality monitoring due to their affordability, portability and easy maintenance. However, the performance of such sensors, such as PurpleAir Sensors (PAS), is often affected by changes in environmental (e.g., temperature and humidity) or emission conditions, and hence the resulting measurements require corrections to ensure accuracy and validity. Traditional correction methods, like those developed by the US-EPA, have limitations, particularly for applications to geographically diverse settings and sensors with no collocated referenced monitoring stations available. This study introduces BaySurcls, a Bayesian-optimised surrogate model integrating deep learning (DL) algorithms to improve the PurpleAir sensors PM2.5 (PAS2.5) measurement accuracy. The framework incorporates environmental variables such as humidity and temperature alongside aerosol characteristics, to refine sensor readings. The BaySurcls model corrects the PAS2.5 data for both collocated and non-collocated monitoring scenarios. A case study showed that BaySurcls outperforms all tested standalone models (DL or classical machine learning based) and the US-EPA correction method in terms of reducing root mean square errors in PAS2.5 data and enhancing correlations with the reference data, under both the collocation and non-collocation monitoring scenarios. This improvement is evident across multiple locations in New South Wales, Australia, demonstrating the model's adaptability. The findings confirm BaySurcls as a promising solution for improving the reliability of low-cost sensor data, thus facilitating its valid use in air quality research, impact assessment, and environmental management.

In this study, gravity data were analyzed and interpreted to assess the ground water flow of Ziway Langano corridor. Gravity survey sets out to investigate the subsurface geology on the basis of anomalies causing gravity field to result from density properties of the subsurface rocks and also used in mapping geological boundaries between contrasting lithologies including (fractures and faults).The field data was qualitatively and quantitatively interpreted using geosoft oasis montaj software. The study area is located in the Central Main Ethiopian rift (CMER). The area ranges in elevation between 2150 and 1500 m above sea level. Geographically the Ziway- Langano corridor is bounded between 7045’N-800’N longitude and 38030’E- 39000’E latitude. In the present study, gravity data have been compiled, processed and interpreted to examine the subsurface geological structures and groundwater flow in the Ziway- Langano Corridor. Further, based on the results of gravity anomaly and profiles, this paper attempts to describe the tectonic and geologic implications of the stud yarea. The major rocks suspected to be found in the study area are volcanic ash, sediment deposit, rhyolite, ignimbrite, and basalt.

This paper explores the intersection of geometry and music, investigat- ing how mathematical structures shape musical theory, composition, and perception. It begins by examining the geometric foundations of pitch organization, including the circular representation of pitch classes and the tonal space. We then explore rhythmic structures through symmetry, analysing how patterns in time are geometrically conceived. Finally, the study examines more recent developments in computational music theory, such as the use of topological data analysis to model musical transformations and voice leading.

This article explores the critical role of SIM provisioning in modern telecommunications, emphasizing its importance in ensuring secure and scalable mobile connectivity. It delves into the evolution of SIM provisioning processes, from traditional physical SIMs to eSIMs and remote provisioning. The paper discusses the technical aspects of provisioning, including unique identifier assignment and security configurations. It examines the challenges faced in scaling these systems for the growing number of connected devices. Furthermore, it explores future directions in SIM provisioning, including the integration of AI and blockchain technologies. It also considers the economic implications and relationship to emerging network technologies like 5G and IoT.

This paper examines the transformative impact of data science, machine learning (ML), and artificial intelligence (AI) on network management in telecommunications, focusing on techniques such as network monitoring, predictive maintenance, anomaly detection, automated network configuration, and self-healing mechanisms. We analyze specific methodologies, including deep learning for anomaly detection and federated learning for predictive maintenance, and address current challenges such as data quality, system integration, and model interpretability. Emerging technologies like edge computing, federated learning, and quantum computing are explored for their potential to enhance predictive maintenance and network management. The paper provides an overview of how AI-driven solutions are revolutionizing telecom networks, offering unprecedented efficiency, reliability, and performance while highlighting the need for ongoing research to tackle complex issues of explainability and privacy.

The rapid advancement of 5G networks, coupled with the increasing complexity of resource management, traffic handling, and dynamic service demands, has underscored the need for more intelligent network optimization techniques. This paper comprehensively reviews AI-driven methods applied to 5G network optimization, focusing on resource allocation, traffic management, and network slicing. Traditional models face limitations in adapting to the dynamic nature of modern telecommunications, and AI techniques-especially machine learning (ML) and deep reinforcement learning (DRL)-offer scalable, adaptive solutions. These approaches enable real-time optimization by learning from network conditions, predicting traffic patterns, and intelligently managing resources across virtual network slices. AI's integration into 5G networks enhances performance, reduces latency, and ensures efficient bandwidth utilization. It is indispensable for handling the demands of emerging applications such as IoT, autonomous systems, and augmented reality. This paper highlights key AI techniques, their application to 5G challenges, and their potential to drive future innovations in network management, laying the groundwork for autonomous network operations in 6G and beyond.