This work investigates mixed convection flow over a vertical thin needle with variable surface heat, mass, and microbial flux, incorporating the influence of gyrotactic microorganisms. The governing partial differential equations are transformed into ordinary differential equations using appropriate similarity transformations. These transformed equations are then numerically solved employing MATLAB's Bvp4c solver. The study's primary focus lies in examining the influence of various dimensionless parameters, including the mixed convection parameter, power-law index, buoyancy parameters, bioconvection parameters, and needle size parameter, on the velocity, temperature, concentration, and microbe profiles. The results demonstrate that these parameters significantly impact surface (wall) temperature, surface fluid concentration, surface motile microbe concentration, and the corresponding velocity, temperature, concentration, and microorganism profiles. The study's findings offer valuable insights into the intricate dynamics of mixed convection flow with bioconvection and have potential applications in diverse fields such as biomedicine and engineering.

This study aims to assess the impact of deforestation and carbon sequestration within the Gandoca-Manzanillo Wildlife Refuge, Costa Rica, using high-resolution satellite imagery from Planet NICFI and Sentinel-2. The research evaluates the impact of forest degradation on forest health and carbon absorption during two periods in 2024 (January and August). Advanced vegetation indices (NDVI, GNDVI, EVI, and SAVI) were applied to assess changes in forest cover and health. Planet NICFI data revealed a 0.41% loss in forest cover, identifying subtle degradation less detectable with Sentinel-2. In terms of carbon sequestration, Sentinel-2 showed a modest increase in CO₂ absorption from 180,231.88 tons to 186,211.33 tons, while Planet NICFI indicated a decrease from 3,984,470.82 tons to 3,820,917.83 tons, suggesting forest degradation. These findings highlight the importance of high-resolution satellite imagery in detecting fine-scale disturbances that lower-resolution data might miss. However, the study’s short timeframe, covering only two periods in 2024, limits long-term trend analysis. The research underscores the need for improved remote sensing technologies and stronger legal frameworks to protect areas like Gandoca-Manzanillo from illegal logging. Despite programs like Payment for Ecosystem Services (PES) in Costa Rica, significant challenges remain in protecting biodiversity-rich regions.

A new family of inequality indices based on the deviation between the expected maximum and the expected minimum of random samples, called the nth Gini index is presented. These indices generalize the Gini index. At the same time, this family of indices and the S-Gini index are generalised by proposing the uv−Gini index, which turns out to be a convex combination of the S-Gini index and the Lorenz family of inequality measures. This family of Gini indices provides a methodology for achieving perfect equality in a given distribution of incomes. This is achieved through a series of successive and equal increases in the incomes of each individual.

Recommending products effectively based on historical transaction data and metadata is crucial for improving user satisfaction and increasing sales. This study presents a recommendation system evaluated using Mean Average Precision (MAP@12), leveraging a diverse dataset that includes apparel types, customer demographics, product descriptions, and images. Our approach integrates Mult-Recall methods and LightGBM Ranker, utilizing various recall strategies and advanced feature engineering techniques to enhance recommendation accuracy. By combining these advanced machine learning models and ensemble techniques, our proposed solution outperforms existing methods, providing a robust and efficient recommendation system tailored to diverse customer needs and product characteristics. This integrated approach not only addresses the challenges of data sparsity and cold start but also adapts to the dynamic nature of user preferences and market trends. The results demonstrate significant improvements in both recommendation precision and user satisfaction, highlighting the potential of our approach for real-world e-commerce applications.

Obviously, the discussion of different factors that could have contributed to the origin of life and evolution represents a clear speculation, since there is no way to check the validity of the most of the related hypotheses on practice, as the corresponding events are not only already happened, but took place in a very distant past. However, there are a few undisputable facts obviously present at the moment, such as the existence of a broad variety of living forms and the abundant presence of intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) in all those living forms. Since it seems that the currently existing living forms have originated from a common ancestor, their variety represents a result of evolution. Therefore, one could ask a logical question of what role(s) those structure-less and highly dynamic but vastly abundant and multifunctional IDPs/IDRs might have in evolution. This study represents an attempt to consider various ideas pertaining to the potential roles of protein intrinsic disorder in origin of life and evolution.

Terpenoids are crucial secondary metabolites found in plants, essential for numerous physiological functions such as defense strategies, signal communication, and adaptation to environmental stresses. The enzymes referred to as Terpene Synthases (TPS) play crucial roles in the production of these compounds, fulfilling an essential role throughout the entire biosynthetic pathway.Despite their importance, systematic studies on the TPS genome in Physcomitrium patens (P. patens) remain inadequate. This research offers an extensive bioinformatics evaluation of the TPS genes in P. patens, aiming to clarify their possible functions in plant development, growth, and responses to stress. Preliminary examinations were conducted on the physicochemical characteristics, secondary protein structures, subcellular distribution, and genetic configurations of the TPS genes in P. patens. Initial analyses were performed on the physicochemical properties, protein secondary structures, subcellular localization, and gene structures of the TPS genes in P. patens. The findings demonstrate that TPS family members are dispersed across six chromosomes, with ten TPS family members identified. Analysis of conserved motifs revealed that the PpTPS members exhibit high sequence conservation, suggesting that these enzymes maintain stable structural characteristics during terpene synthesis. Further examination of evolutionary pressures indicated that TPS family members are predominantly subjected to purifying selection, which helps preserve the structural stability of TPS enzymes. Furthermore, an analysis of cis-acting elements indicated that TPS genes might respond to various factors, including light, plant hormones, tissue development, and environmental stressors. This suggests that TPS genes could be vital in managing how plants adapt to changes in their environment. Tissue expression profiling revealed that TPS family members have significant functions across various developmental stages and tissues. This is demonstrated by qRT-PCR analyses, indicating that the expression of the PpTPS gene is influenced by abscisic acid (ABA), methyl jasmonate (MeJA), sodium chloride (NaCl), and polyethylene glycol (PEG). The findings suggest that the PpTPS genes could play an essential role in the functional development of plant leaves and in their responses to abiotic stress.In summary, this research presents a comprehensive examination of the TPS family members in P. patens, yielding important perspectives on the functions of the PpTPS7 and PpTPS8 genes in the development of leaves and responses to abiotic stress.The findings contribute to a deeper understanding of the functions and regulatory mechanisms of TPS genes and present new perspectives and strategies for the enhancement and application of P. patens.

Federated Learning (FL), as a distributed machine learning method, is particularly suitable for training models that require large amounts of data while meeting increasingly strict data privacy and security requirements. Although FL effectively protects the privacy of participants by avoiding the sharing of raw data, balancing the risks of privacy leakage with model performance remains a significant challenge. To address this, this paper proposes a new algorithm—FL-APB (Federated Learning with Adversarial Privacy-Performance Balancing). This algorithm combines adversarial training with privacy protection mechanisms to dynamically adjust privacy and performance budgets, optimizing the balance between the two while enhancing and ensuring performance. Experimental results demonstrate that the FL-APB algorithm significantly improves model performance across various adversarial training scenarios, while effectively protecting the privacy of participants through adversarial training of privacy data.

To explore cast HEAs reinforcement by MC carbides three equimolar CoNiFeCrC alloys without or with Carbon and either hafnium or tantalum were investigated. Their microstructures were specified and tests at 1100°C in oxidation by air and flexural creep tests were carried out. The HEAbase was single–phased. The HEAhfc and HEAtac contained eutectic script HfC and TaC carbides respectively, in the interdendritic spaces. After oxidation for 50h at 1100°C all alloys were covered by a (Cr,Mn)2O3 scale with various proportions in Cr and Mn. HfO2 or CrTaO4 also formed. The subsurface was depleted in Cr and especially in Mn. The HEAbase alloy deformed quickly. The MC carbides greatly improved the creep resistance, and divided deformation by five to ten times.

Interactive conversational agents, also known as chatbots, have the potential to increase the success rate of digital technology interventions to promote healthy behaviors. However, due to their newness and limited use, little is known about their integration, usefulness, and effectiveness in promoting smoking and vaping cessation. The aim of this mixed methods systematic review was to assess the effectiveness and characteristics of current interactive conversational agents in promoting and supporting smoking and vaping cessation. A mixed methods systematic review was conducted to identify studies published in the last 20 years in five relevant databases. Eight studies, including seven on smoking cessation and one on smoking and vaping cessation, were included. The results showed that, compared to other smoking cessation methods, chatbots can lead to better engagement in treatment, resulting in higher rates of sustained abstinence and improved quality of life. In addition, chatbots can be perceived as empathetic and establish a decent therapeutic alliance thanks to their communication skills. This knowledge could be useful for the development of interactive conversational agents to support smoking and/or vaping cessation. Alternative intervention tools targeting younger generations, such as chatbots, may offer an additional way for public health professionals to reach them.

Background/Objectives: Energy availability (EA) is essential for maintaining physiological func-tions, significantly influencing athletes' health and performance. Nutritional behaviours, how-ever, vary across sports. This study aims to assess EA levels in athletes from different disciplines, focusing on the relationship between EA and body composition in endurance athletes compared to rugby players. Methods: The study involved 18 endurance athletes (15 men, 3 women) and 36 rugby players (all men). Data were gathered through interviews, questionnaires, and bioim-pedance analysis. Energy intake (EI) was measured with a 24-hour dietary recall, and exercise energy expenditure (EEE) was calculated using the IPAQ questionnaire. EA was calculated as EA = (EI - EEE) / fat-free mass (FFM), with results categorized into clinical, subclinical, and optimal ranges. Results: The endurance group had a lower average FFM (57.81 kg) compared to the rugby players (67.61 kg). EA was also significantly lower in endurance athletes (11.72 kcal/kg FFM) than in rugby players (35.44 kcal/kg FFM). Endurance athletes showed more restrictive nutritional behaviour with lower EI and higher EEE, but both groups maintained body composition within normal ranges. Conclusions: Endurance athletes exhibit greater nutritional restrictions compared to rugby players, though their body composition remains healthy. Further research is required to investigate the long-term effects of low EA on performance, injury risk, and potential impairment when EA falls below the optimal threshold of 45 kcal/kg FFM/day.

In recent years, the demand for solid, thin, and flexible energy storage devices has surged in modern consumer electronics, which require autonomy and long duration. In this context, hybrid supercapacitors have become strategic, leading to significant efforts to develop cells with an energy density close to that of batteries, while maintaining the power density of conventional supercapacitors. Motivated by these requirements, we report the development of a new high-performance dual-redox-mediator supercapacitor. In this study, cells were constructed using fully moldable buckypapers (BPs), composed of carbon nanotubes and cellulose nanofibers, as electrodes. We evaluated the compatibility of BPs with hydrogel polymer electrolytes, based on 1 mol L-1 H2SO4 and polyvinyl alcohol (PVA), supplemented with different redox species: methylene blue, indigo carmine, and hydroquinone. Solid cells were constructed containing two active redox species to maximize the specific capacity of each electrode. Considering the main results, the dual-redox-mediator supercapacitor exhibits a high energy density of 32.0 Wh kg-1 (at 0.8 kW kg-1) and is capable of delivering 25.9 Wh kg-1 at high power demands (4.0 kW kg-1). Stability studies conducted over 10,000 galvanostatic cycles revealed that the PVA polymer matrix benefits the system by inhibiting the crossover of redox species within the cell.

The relationship between Portugal and England spans centuries, encompassing political alliances, economic cooperation, cultural exchanges, and significant periods of tension and exploitation. This article provides a comprehensive and critical overview of the historical relations between Portugal and England from medieval times to the present, highlighting both the cooperation and the conflicts that have shaped this complex alliance. It explores key events, treaties, and figures that have influenced the trajectory of the relationship, including the heavy indebtedness Portugal accumulated with England and how this debt was transferred to Brazil in exchange for its independence—a factor that perpetuated social distortions such as slavery and inequality in Brazil. The article also discusses the contemporary context of Portugal-England relations, emphasizing the continued importance and challenges of this partnership in the modern world.

The current developments in the theory of quantum static triplet correlations and their associated structures (real r-space and Fourier k-space) in monatomic fluids are reviewed. The main framework utilized is Feynman’s path integral formalism (PI) and the issues addressed cover quantum diffraction effects and zero-spin bosonic exchange. The structures are associated with the external weak fields that reveal their nature, and due attention is paid to the underlying pair level structures. Without the pair level one cannot fully grasp the triplet extensions in the hierarchical ladder of structures, as both the pair and the triplet structures are essential ingredients in the triplet response functions. Three general classes of PI structures do arise: centroid, total continuous linear response, and instantaneous. Use of functional differentiation techniques is widely made and, as a bonus, this leads to identify an exact extension of the “classical isomorphism” when the centroid structures are considered. In this connection, the direct correlation functions, as borrowed from classical statistical mechanics, play a key role (either exact or approximate) in the corresponding quantum applications. Additionally, as an auxiliary framework, the traditional closure schemes for triplets are also discussed, owing to their potential usefulness for rationalizing PI triplet results. To illustrate some basic concepts, new numerical calculations (path integral Monte Carlo PIMC and closures) are reported. They are focused on the purely diffraction regime and deal with supercritical helium-3 and the quantum hard-sphere fluid.

Per- and polyfluoroalkyl substances (PFAS) are arguably the most common water contaminants in the world today. While several research experiments have been done to understand and remove PFAS from the environment, there is still a lot of unknown. Little has been known about the use of Machine learning (ML) to understand PFAS. This work hence reviews some leading ML approaches and applications in PFAS studies in the distribution, transport, removal, and occurrence predictions of PFAS. Several evaluation matrices were examined and used to perform this function. There are still a lot of areas whereby ML can be used to improve our PFAS knowledge base, some of these were briefly stated in this review.

The prediction of stock prices is a challenging task, particularly for retail investors who may lack the resources and expertise to perform sophisticated quantitative trading. This study focuses on enhancing stock price prediction for retail investors by employing advanced machine learning techniques on data from the stock exchange market. We utilize a comprehensive methodology that includes data preprocessing to handle missing values and outliers, feature engineering, cross-validation, and parameter tuning. The techniques applied include Keras Deep Neural Networks (DNN), LightGBM, LSTM, GRU, and linear regression (LR). Our proposed ensemble model, which combines time series and deep learning models, demonstrates superior performance compared to individual models. This integration of methods leads to significant improvements in prediction accuracy, providing a robust solution for retail investors.

This study presents an application of fractal mathematics to financial markets through the utilization of the Multifractal Model of Asset Returns (MMAR). The model is employed to analyse a 30-year dataset encompassing three distinct financial markets: the USD/NOK currency pair, the OMXS30 stock index, and the 12-month LIBOR rate. The MMAR model successfully captures essential stylized facts about financial markets, including high kurtosis, non-independent price movements, and clustered volatile days. Simulations generated by the model demonstrate realistic behaviour and multifractal characteristics. However, the model lacks a statistical method for assessing its accuracy and may underestimate kurtosis in high-kurtosis markets. Notably, the model is capable of producing simulations across a wide range of kurtosis values and can be instrumental in stress-testing portfolios. Despite its potential, the model is subject to limitations, such as the need for human judgment, ambiguous predictions, and interpretability issues. Furthermore, the model may become unreliable following a high-kurtosis event.

UML (Unified Modeling Language) diagrams are graphical representations used in software engineering which play a vital role in the design and development of software systems and various engineering processes. Large, good-quality datasets containing UML diagrams are essential for different areas in the industry, research and teaching purposes, however few exist in the literature and it is common to find duplicate elements in the existing datasets. This might affect the evaluation of the models obtained when using these datasets. This paper addresses the challenge of creating a ground truth dastaset of UML diagrams, including semi-automated inspection to remove duplicates and ensure the correct labeling of all UML diagrams contained in the dataset. In particular, a dataset of six UML diagram classes has been assembled, comprising a total of 2,626 images (426 activity diagrams, 636 class diagrams, 352 component diagrams, 357 deployment diagrams, 435 sequence diagrams, and 420 use case diagrams). Importantly, unlike other existing datasets, ours contains no duplicate elements and all diagrams are correctly labeled. Our curated dataset is a valuable and unique resource for the research community because it serves as a foundation for training and evaluating various models. In this paper, we demonstrate this by training and testing several deep learning models using our dataset, achieving highly satisfactory results compared to those presented in other works in the literature. Additionally, our experimental results highlight the potential of Visual Transformers for UML diagram classification, setting our approach apart from others that predominantly used Convolutional Neural Networks for similar tasks.

Indoor air quality (IAQ) is a critical determinant of human health, with fungal contamination posing significant risks. In 2023, a total of 160 samples were collected from 40 selected rooms. These samples were cultured on Sabouraud Dextrose Agar (SDA) medium using a portable air sampler and incubated at 28°C for 7 days. Initial identification of fungal isolates was performed based on their morphology. Suspected isolates underwent further analysis using internal transcribed spacer (ITS) rDNA analysis. The results revealed 11 species across 8 genera in various rooms. The most prevalent fungi were Aspergillus niger (183 CFU) , Penicillium chrysogenum (139 CFU) and Cladosporium halotolerans (135 CFU). On the other hand, Curvularia hawaiiensis and A. ustus were rarely isolated (10 and 19 respectively). Effective treatment involves a combination of preventive measures, such as controlling humidity and ensuring proper ventilation, alongside targeted interventions like antifungal treatments and thorough cleaning. Continuous monitoring and management of indoor environments are essential to reduce fungal contamination, enhance air quality, and protect human health from the harmful effects of airborne fungi. This abstract underscore the importance of addressing indoor fungal contamination to promote safer, healthier living and working spaces.

Music has been proposed for a long time as a treatment for mental disorders. However, some special types of music or stimulating sounds might induce negative emotions. Herein, 8-week-old male mice were exposed to two specific genres of music, hip-hop (HH) and heavy metal (HM), and construction noise (CN), and a series of behavioral experiments were performed to evaluate the impact of these music or sounds on the emotion of mice. The experiment lasted 1 week in which 8-week-old male mice were used as animal models. We found that long term exposure HM, HH, and CN induced depressive symptoms with a decrease in dopamine receptor 1 and BDNF in the mixture of hippocampus and frontal cortex of mice. Our results have highly addressed that certain special types of sound or music might induce negative emotions and loss of dopaminergic neurons in mice, and it is necessary to intervene in adolescences who are exposed to these music or sounds for a long time.

Recent advancements have been observed in the global legal framework, particularly in the recognition of Indigenous peoples' rights, among which the right to self-determination stands out. This right encompasses the ability to define their political status and to pursue economic, social, and cultural development autonomously. The Inter-American Commission on Human Rights (IACHR) has identified six criteria to evaluate adherence to these rights. This study aims to assess the progress made by Chile, Colombia, and Mexico in meeting these criteria. Employing a non-experimental, cross-sectional, and exploratory research design, the study utilized a questionnaire based on a Likert scale to gather data from residents of Indigenous communities within the three countries under consideration. Findings suggest that the criterion most adequately met is that of cultural identity and non-discrimination, whereas the criterion pertaining to the right to prior, free, and informed consultation and consent is the least fulfilled. Through principal component analysis, it was noted that Colombia exhibits a higher level of compliance with the right to self-determination, followed by Mexico, with Chile demonstrating a divergence and lagging in progress. The study concludes that a significant challenge for these countries lies in continuing efforts to effectively meet these standards and ensure the right to self-determination for Indigenous and tribal peoples.

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

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

Ribavirin and its analogues exhibit an in vitro antiproliferative effect in cancer cells. In this work we studied the biological activities of a number of oxymethyl derivatives of ribavirin’s aglycon – 1,2,4-triazole-3-carboxamide. Oxymethyl derivatives of 1,2,4-triazole-3-carboxamide with substitu-tions at the fifth or first position of the triazole ring, were synthesized and their antiproliferative and antimicrobial effects were assessed. For both series the presence of an antiproliferative effect was inves-tigated and in the case of 1-oxymethyl derivatives was shown an antimicrobial potential against a Gram-positive bacteria Micrococcus luteus and Gram-negative bacterium Pseudomonas aeruginosa. The obtained results showed that the n-decyloxymethyl derivatives induced leukemia cell death at low mi-cromolar concentrations. We confirmed that n-decyloxymethyl derivatives of ribavirin inhibited cell cy-cle progression and induced accumulation of leukemia cells in subG1-phase. The molecular docking results suggest that oxymethyl derivatives may act by inhibiting translation initiation due to interfering with eIF4E assembly. The outcome results relived that active derivatives (1- or 5-n-decyloxymethyl-1,2,4-triazole-3-carboxamides) can be considered as a lead compound for anti-cancer treatments.

Purpose: This systematic review investigates the implications of Industry 4.0 technologies on supply chain visibility and operational efficiency. The primary aim is to discern the impact of technological integration on contemporary supply chain dynamics. Design/Methodology/Approach: A comprehensive search strategy identified 67 pertinent studies published between 2015 and 2023. The review adheres to systematic methodologies, employing the Critical Appraisal Skills Programme framework for quality assessment. Data synthesis incorporates qualitative and quantitative analyses to distill key themes and patterns. Findings: The review unveils the pivotal role of information visibility in fortifying supply chain outcomes, emphasizing the need for a dual investment strategy encompassing technological solutions and a collaborative organizational culture. Regional variations in supply chain practices, insights from humanitarian supply chains, and the influence of environmental factors on agility broaden the understanding of Industry 4.0 implications. Research Limitations/Implications: The study acknowledges limitations in the geographical focus of the included studies and the evolving nature of Industry 4.0 technologies. These considerations prompt a call for ongoing research to capture emerging trends and global nuances. Practical Implications: Organizations are urged to adopt a context-specific, adaptive approach, recognizing the significance of intangible assets and tailoring strategies to local contexts for optimal supply chain performance. Originality/Value: This systematic review contributes a nuanced understanding of Industry 4.0's transformative potential in supply chain management, emphasizing the interplay between technology, organizational culture, and regional contexts.

To obtain high quality grain refiner, a new Al-5Ti-1B-1RE master alloy grain refiner was synthesised by melt-matching method. Thermodynamic calculations and kinetic analyses, which were seriously missing from the study of key issues during the preparation process, were investigated. The microstructure and properties, comparison of the refining effect of different grain refiners on industrial pure aluminium and its refining mechanism were analysed with the help of X-ray diffraction (XRD), optical microscopy (OM), scanning electron microscopy (SEM) and energy spectroscopy, transmission electron microscopy (TEM) and an electronic universal testing machine (CSS-44100). The experimental results show that the second-phase particles in the Al-5Ti-1B-1RE master alloy matrix synthesised by the melt-matching method are mainly TiB2、 A13Ti、Ti2A120RE, etc. The magnitude of the free energy ΔG of the synthesis reaction is calculated to be ΔGTiB2<ΔGAl3Ti<ΔGTi2A120RE. When the temperature is low (undercooling ΔT is large), the nucleation rate N mainly depends on the kinetic atomic diffusion activation energy Q, while the thermodynamic nucleation work becomes a secondary factor, and vice versa. The industrial pure aluminum refined by the new grain refiner has almost transformed from coarse columnar crystals to fine equiaxed crystals, with an average grain size of 70.2 μm, which was 36.18% and 20.66% smaller than that refined by domestic and imported Al-Ti-B wire master alloy grain refiner, and its mechanical properties of tensile strength σb was increased by 11.94%, 8.29%, and elongation at break δ was improved by 31.79%, 17.41%, respectively. The main mechanism for refining pure aluminum in Al-5Ti-1B-1RE master alloy is the formation of TiA13 on TiB2 particles, the release of RE atoms from Ti2A120RE phase surrounding TiAl3, and the partial transformation into TiA13 phase, which promotes the dual nucleation refinement mechanism and the pinning effect of rare earth elements on grain boundaries.

Childhood is an obvious period for motor learning since children’s musculoskeletal and nervous systems are still in development. Adults adapt movements based on reward feedback about success and failure but it is less established whether school-age children also exhibit such reward-based motor learning. We designed a new ‘circle-drawing’ task suitable for assessing reward-based motor learning in both children and adults. Participants drew circles with their unseen hand on a tablet. They received binary reward feedback after each attempt based on the proximity of the average radius of their drawing to a target radius set as double the radius of their baseline drawings. We rewarded about 50% of the trials based on a performance-dependent reward criterion. Both children (7-17 years old) and adults increased the radius of their drawings in the direction of the target radius. We observed no difference in learning between children and adults. Moreover, both groups changed the radius less following reward than following reward absence, which is a sign of reward-based motor learning. We conclude that school-age children, like adults, exhibit reward-based motor learning.

Objective: The main purpose of this meta-analysis was to assess the efficacy and safety of Oncolytic Viruses (OVs) in glioma therapy. Methods: We searched the literature in PubMed, EMBASE, Web of Science, and the Cochrane Library. The primary outcomes assessed were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs). The risk of bias was evaluated by sensitivity analysis and publication bias. Results: We identified 21 studies with 440 patients in this meta-analysis. In the single-arm analysis, the results showed that the 1-year OS rate was 47% (95% CI: 34%-61%, I2 = 75%) and the 2-year OS rate was 14% (95% CI: 10%-20%, I2 = 0%). The median OS was 12.48 months (95% CI: 10.71-14.25, I2 = 96%). The 1-year PFS rate was 13% (95% CI: 5%-24%, I2 = 0%), with the median PFS being 4.01 months (95% CI: 2.99-45.03, I2 = 96%). The pooled estimate of ORR was 7% (95% CI: 3%-12%, I2 = 23%). Funnel plots for median PFS were asymmetric with Egger’s test P < 0.01 indicating publication exists. The incidence of OVs-related AEs was 49% (95% CI: 20%-79%, I2 = 95%), and AEs > grade 3 was 8% (95% CI: 3%-16%, I2 = 62%). Conclusion: This meta-analysis indicated that OVs therapy was relatively safe but did not significantly extend survival in patients with gliomas.

This study provides a detailed examination of Natural Language Processing (NLP) for the complexscript of Nepali. We analyze available data resources today and discuss relevant points includingcharacter encoding, advanced tokenization methods and morphological complexity. This allows us tocontrast Nepal’s unique language and technology ecosystem with Hindi and Thai in terms of NLPadvancements. Quantitative assessment of existing tools and resources is offered by this investigationwhich highlights immediate weaknesses as well as areas that need more effort. Various ethicalconcerns are addressed here while potential topics for future research as e-governance, healthcare oreducation with a focus on new domain-specific applications, and cross-lingual transfer learning aresuggested. The objective of this attempt is to enhance understanding of natural language processing(NLP) in Nepali language and beyond aimed at developing NLP technologies that are more efficient,inclusive, culturally appropriate across diverse linguistic communities.

This essay examines the complex interplay between human rights developments in Saudi Arabia and the country's Vision 2030 initiative, which aims to modernize its social, economic, and political landscape. The research question posed is: How are human rights being addressed within the framework of Vision 2030? The goal of the essay is to provide a qualitative analysis of the reforms and policies emerging under Vision 2030, highlighting both advancements and ongoing challenges. Key discussions include historical human rights perspectives, specific strategies aimed at enhancing women’s rights and labor rights, and the implications of legal reforms. The essay draws upon a range of scholarly sources to underscore the intricate relationship between human rights improvements and socio-economic objectives in Saudi Arabia. The main conclusions suggest that while significant strides have been made, particularly in women's empowerment and labor rights, substantial obstacles—rooted in cultural norms and institutional practices—persist. Ongoing international scrutiny and a robust domestic dialogue on human rights remain critical for the success of these reforms. The essay ultimately advocates for sustained efforts to uphold human rights as a cornerstone of the Vision 2030 agenda.

The SARS-CoV-2 virus (COVID-19) has led to an initiative to develop safe and effective vaccines for public health safety. In December 2020, the United States Food and Drug Administration (FDA) administered an Emergency Use Authorization (EUA) for the Pfizer-BioNTech COVID-19 vaccine. Other vaccines from Johnson & Johnson, Moderna, and AstraZeneca shortly followed. This paper aims to examine the EUA process for COVID-19 vaccine approvals, including the requirements for the safety and efficacy of data, along with the role of the FDA and EMA in the approval process. Further, public concerns about vaccine approvals, including issues on the approval process's safety, efficacy, and speed, were also discussed. Using qualitative analysis of the extracted studies, trends and insights into the factors influencing public acceptance of COVID-19 vaccines, such as vaccine hesitancy and misinformation, were discussed. Overall, a transparent and rigorous regulatory process for vaccine approval is critical for education efforts between policymakers, vaccine developers, and the public to address concerns for increased population vaccine uptake.

Photodynamic therapy (PDT) is a minimally invasive treatment that elicits tumor apoptosis using laser light exclusively applied to the tumor site. IR-783, an HMC dye, impedes the proliferation of breast cancer cells, even without light. However, the mechanism by which IR-783 exerts its antiproliferative effects remains unclear. We aimed to determine the efficacy of PDT using IR-783 liposomes. A heptamethine cyanine (HMC) dye excited by long-wavelength infrared light and with high tissue permeability was used for PDT after liposomization to enhance tumor tissue accumulation. PDT was performed using IR-783 in two patients with tongue and breast cancers. IR-783 liposomes similarly inhibited cell proliferation in lung cancer cells even when not excited by light. Tumor size was markedly reduced in both cases, with no significant adverse events. Furthermore, the patient with tongue cancer exhibited improved respiratory, swallowing, and speech functions, which were attributed not only to the shrinkage of the tumor, but also to the improvement of airway narrowing. In conclusion, PDT using IR-783 liposomes effectively reduces tumor size in tongue and breast cancers.

With the development of human-computer interaction, the importance of emotion recognition is increasing. Emotion recognition technology provides practical benefits in various industries such as improving user experience, education, and organizational productivity. In education, emotion recognition can enable real-time understanding of students' emotional states and provide tailored feedback, and in the workplace, by monitoring employees' emotional states, it can improve work performance and job satisfaction. Therefore, multimodal-based research that combines text, speech, and video data for emotion recognition is being conducted in various industries. In this study, we propose an emotion recognition method that combines text and speech data, reflecting the characteristics of the Korean language. For text, KoELECTRA is used to perform embedding, and for speech, MFCC and pitch analysis are used to extract features. Finally, a multimodal transformer model is proposed that combines these two data types to perform emotion recognition. The multimodal transformer model processes text and speech data separately, and then learns the interaction between the two modalities through a Cross-Modal Attention mechanism. Through this, the complementary information from text and speech is effectively combined, improving emotion recognition performance. Experimental results show that the proposed model outperforms single-modality models, achieving a high accuracy of 73.13% and an F1-Score of 0.7344 in emotion classification. This study contributes to the advancement of emotion recognition technology by combining various language and modality data, and higher performance can be expected through the integration of additional modalities in the future.

Aim: This study aims to analyze the collaborative networks and identify key players in autoimmune pancreatitis (AIP) research from 2000 to 2023. Using data from the Web of Science (WoS) Core Collection, I assess the structure and evolution of co-authorship networks to understand collaboration trends and influential researchers in the field.Method: I conducted a network analysis of co-authorship patterns in AIP research using Python (Version 3.10.5) in the PyCharm development environment (Software Version 2022.1.3). The analysis included macro-level indicators: network density, clustering coefficient, components, and average distance, as well as micro-level indicators: degree centrality, closeness centrality, and betweenness centrality. These metrics were used to evaluate the connectivity, clustering, and key nodes within the network across three distinct periods: 2000-2009, 2010-2019, and 2020-2023.Result: The analysis revealed that the co-authorship network in AIP research evolved from a fragmented structure with limited collaboration in the early 2000s to a more interconnected but still dispersed network in recent years. Despite an increase in network density and a decrease in the number of disconnected components over time, the overall structure remains highly clustered, with many researchers operating within isolated groups. Key figures, such as Kazuichi Okazaki, Terumi Kamisawa, and Shigeyuki Kawa from Japan, consistently ranked high in centrality measures, highlighting their significant influence and leadership in the field. The findings suggest that while local collaborations are strong, broader international connections are still developing.Conclusion: This study provides a comprehensive overview of the collaborative landscape in AIP research, identifying central researchers and highlighting persistent fragmentation within the network. The prominent role of Japanese researchers in shaping the field underscores the importance of fostering greater international collaboration to bridge gaps between research clusters. Enhancing global partnerships could lead to more integrated and impactful research outcomes, ultimately advancing the understanding and management of autoimmune pancreatitis.

Aspergillus flavus is a medically relevant fungus, particularly in tropical regions. Thermotolerance is a key virulence factor as an opportunistic pathogen, as well as its ability to form biofilms, which can impact therapeutic outcomes. To know how temperature affects the growth and biofilm formation of an A. flavus isolate, we assessed its growth on solid media and described the morphological changes during conidial germination. We also examined formation and composition of in vitro biofilm incubated at different temperatures and compared the susceptibility of planktonic and biofilm cells to antifungal agents. Our results showed that temperature promotes conidiation on solid media. The radial growth was higher at 28 °C, but total conidia was higher at 37 °C, however, conidial density was stronger at 42 °C. Moreover, incubation at 37 °C accelerates conidial germination and is the optimal temperature for biofilm formation. We described four distinct phases in A. flavus biofilm development: initiation (0-12h), consolidation (12-48h), maturation (48-72h), and dispersion (&gt;72h), where the presence of aspergillar heads was notable at 42 °C. Carbohydrates and proteins are the main components of the extracellular matrix. We observed lipid droplets within the biofilm hyphae, and mature biofilms are resistant to amphotericin B and itraconazole, with MICs exceeding 16 g/mL for both antifungals, regardless of the incubation temperature.

A biobased and conductive ink composed of elastomeric vinyl acetate-vinyl laurate copolymer (PVAc-VL) and carbon nanofibers (CNF) has been developed to create stretchable and flexible tactile devices (taxels) for robotics and prosthetics applications. The ink can be sprayed onto elastomeric surfaces (Ecoflex) to produce an electronic skin for applications such as the iCub robot and the Hannes prosthetic hand. Electron microscopy analysis confirms good dispersion of the CNF within the ink, and the ink remains conductive even after 150 mechanical cycles of stretching up to 25% and unloading. Compression tests up to 50% deformation show a small influence on the coating, and stretching cycles allow for rearrangement of the CNF, improving the electrical behaviour due to mechanical energy dissipation. The measured electrical performance exhibits a twofold increase in the R/R0 ratio, succeeded by a rapid decline (recovery), and eventually stabilizes near the initial value, indicating enhanced electronic performance.

Transactive response DNA-binding protein of 43 kDa (TDP-43) is a major component of pathological inclusions in various neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The detection of TDP-43 in biofluids is crucial for the development of diagnostic and prognostic indicators of disease and therapeutic development for TDP-43 related proteinopathies. Despite its potential as a biomarker for numerous neurological disorders, the lack of a sensitive and reproducible TDP-43 assay hinders progress in TDP-43-based therapy development, underscoring the need for an effective and standardized method for accurate quantification. In this study, we developed and validated a sensitive immunoassay for the detection of TDP-43 in human biofluids using the Meso Scale Discovery (MSD) platform. We used this immunoassay to quantify TDP-43 levels in the plasma and serum of healthy controls and ALS patients. Our results indicate a reduction of total TDP-43 in the blood of ALS patients compared to healthy controls.

Nitrogen loss in water from farmland has become a highly concerned environment issue due to the different nitrogen-fertilized input, which is the main cause of agricultural non-point source pollution in the Lake Basin. However, characteristics of nitrogen forms loss from farmland and how the root system responds is lacking. The effectiveness of 100–0% (T1), 75–25% (T2), 50–50% (T3), 25–75% (T4), and 0–100% (T5) nitrate-ammonium nitrogen fertilizer treatment was investigated to determine nitrogen loss in water and root morphological parameters of tobacco in Mile and Chengjiang Counties. Two sites result suggested that: Compared with the T1, T4, and T5 treatments, the TN loss of the T2 and T3 treatments in runoff was reduced by 4.67–27.32%, 11.85–23.20%, and 9.56–31.43%, respectively. Similar results in the nitrogen loss of infiltration were observed with that from runoff. Correlation analysis suggested that the root biomass was negatively correlated with the nitrogen loss. T2 and T3 treatments were larger than those of the T1, T4, and T5 treatments in terms of root biomass, root surface area, and root spatial distribution. This study suggested that 50–50% nitrate-ammonium nitrogen fertilizer can facilitate the root growth of tobacco and reduce nitrogen loss, which provides a reference for agricultural sustainable development.

Background/Objectives: Nephrolithiasis is a common urologic condition and a significant source of patient morbidity and healthcare expenditure. Despite the higher prevalence of metabolic risk factors for nephrolithiasis among Black women, there have been few epidemiologic studies of kidney stones focusing on this group. Methods: We describe demographic and health characteristics, diagnostic, and metabolic profiles of women with self-reported kidney stones among participants in the Black Women’s Health Study (BWHS), a large prospective cohort of U.S. Black women. Results: Among the 2,750 BWHS participants who completed an online supplemental questionnaire assessing urologic health, 201 women reported nephrolithiasis. Of this number, 62% had completed ≥16 years of education and 82% reported access to health care. Overall, 39% reported experiencing ≥2 stones in their lifetime and 29% required surgery to treat the condition. Thirty-two percent reported having completed a metabolic evaluation, while 70% had undergone a CT-scan to diagnose nephrolithiasis. The frequency of metabolic evaluation increased with the number of metabolic components reported: 3% (0 components) to 43% (3-4 components). Conclusions: Our findings are consistent with reports of lower rates of metabolic evaluation among Black patients despite their having multiple risk factors for nephrolithiasis. Further study is needed to identify the barriers and facilitators of metabolic and diagnostic workup of nephrolithiasis in Black women.

CTC numbers in the blood of cancer patients can indicate the progression and invasiveness of tumors and their prognostic and predictive value has been repeatedly demonstrated. However, the standard baseline CTC count at the beginning of treatment, while informative, is not completely reliable and may not adequately reflect the state of the disease. The growing number of studies indicate that long-term monitoring of CTC numbers in the same patient provides more comprehensive prognostic data and should be incorporated into clinical practice, as a factor that contributes to therapeutic decisions. This Review describes the current status of CTC enumeration as a prognostic and predictive factor, highlights the shortcomings of current solutions and advocates for longitudinal CTC analysis as a more effective method of the evaluation of developing disease, treatment efficacy, and long term-monitoring of the minimal residual disease.

Ternary ZnS/ZnO/graphitic carbon nitride (gCN) photocatalysts were prepared by coupling gCN sheets with ZnO nanorods under solvothermal conditions followed by sulfurization using Na2S. SEM and TEM analyses show that small-sized ZnS particles (ca. 7.2 nm) deposit homo-geneously on the surface of ZnO/gCN nanohybrids. Photoluminescence and electrochemical impedance spectroscopy show that ZnS allows an enhanced charge separation efficiency as well as prolonged lifetime of photogenerated charge carriers, leading to improved hydrogen photo-production under UV light irradiation compared to ZnO/gCN. Moreover, the deposition of ZnS nanoparticles improves the photostability of the ZnS/ZnO/gCN catalyst for hydrogen produc-tion. A double Z-scheme mechanism is proposed for hydrogen photoproduction using the ZnS/ZnO/gCN heterojunction.

The integration of Genetic Algorithms (GAs) into Serious Games (SGs) has gained traction as a method to optimize game mechanics and personalize user experiences. While GAs are well-known for their effectiveness in solving complex optimization problems, their application in SGs remains relatively under-explored. This review aims to address this gap by systematically mapping the existing literature on the intersection of these two fields. The primary objective of this scoping review is to identify and synthesize the existing research on the application of GAs in SGs, with a focus on understanding the current state of the field, identifying common applications, challenges, and potential future directions. The review includes studies published in English that focus on the use of GAs within SGs. The search encompassed articles from academic journals and conference proceedings without restrictions on publication dates. Exclusion criteria included studies that did not specifically address the integration of GAs in SGs. A systematic search was conducted in databases such as ACM Digital Library, Web of Science, Scopus and Inspec in July 2024. The search terms used included "genetic algorithm," "evolutionary algorithm," "computational algorithm," and "serious games." Unpublished data and articles were not considered. Data were charted using a PRISMA flowchart developed by the author VV. Key categories for data extraction included study objectives, methods, outcomes, type of study and GA used and the specific applications of GAs in SGs. Data charting was conducted independently by two reviewers, with disagreements resolved through discussion and consensus. The search identified 154 studies, of which 23 met the inclusion criteria. The included studies highlight the diverse applications of GAs in SGs, ranging from optimizing game scenarios to personalizing learning experiences. Challenges identified include the computational complexity of GAs and difficulties in their integration into existing game frameworks. The findings of this review suggest that while the use of GAs in SGs is a promising area of research, it remains in its nascent stages. Future research should focus on addressing the technical challenges of integrating GAs into SGs and exploring their application across a wider range of game genres and educational contexts. Limitations of the review include the potential for publication bias and the exclusion of non-English language studies.

Scientific knowledge evolves in small steps, with occasional backsteps to correct inaccuracies, all occurring within a competitive environment. This perspective for the first time looks at the history of latency-related RNA (LR-RNA) that was later renamed latency-associated transcript (LAT). At the 1986 International Herpesvirus Workshop (IHW) meeting in Leeds, England, Daniel L Rock and Anthony B Nesburn first reported the discovery of human herpes virus 1 (HSV-1) latency-related (LR)-RNA that is antisense to ICP0. Less than a month after the IHW meeting a paper was submitted to Science magazine and 8 months later appeared in print thanking “D. Rock for suggesting RNA complementary to the ICP0 message may be present in latently infected cells”. This perspective is not a review of LAT literature but intends to clarify the timeline of LAT discovery and subsequent breakthroughs such as reactivation, apoptosis, CD8+ T cell exhaustion, and LAT expression in different cell types detected during latency. While many review articles have been written about LAT since 1987, the most comprehensive and balanced review about LAT was written by Dr. David Bloom’s group (1). In this overview, I will discuss our original collaboration with Dr. Dan Rock and subsequent work that our group performed, which is still ongoing. Finally, I will discuss the controversies associated with LAT from its inception to current times.

The purpose of this paper is to compare various indicators of microbiological contamination in coastal areas near estuaries around the world. A major factor contributing to the presence of fecal coliforms is the geomorphology of the area, and, more particularly, whether the area concerned is an open or enclosed bay, the climate of the area, its tourism development, and, lastly, the urban, agricultural, livestock, or industrial activities carried out near river mouths. The aim was also to attempt to systematize the microbiological contamination of the above – mentioned estuaries around the world for broader applicability. The method used and the experimental apparatus for the isolation of bacteria was the membrane filtration method described in ISO 7704:1985. For the growth and enumeration of total coliforms and Escherichia coli the method described in ISO 9308-1 was used, while for enterococcus the one described in ISO 7899-2:2001. No statistically significant difference was found at many points in Greece and Spain, for either of the two patho-genic bacteria. In this work, the documentation of the microbiological contamination of river del-tas was achieved in similar areas (Greece and Spain) and could be applicable throughout the Mediterranean.

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is widespread in European pig production, and although it is not an important food-borne pathogen, it constitutes a potential occupational hazard to farm workers and possibly to their household members. Farm workers can be exposed to LA-MRSA via direct contact with pigs and via airborne transmission. Bacteria can then be carried home in the nose or on the skin, potentially exposing household members. Therefore, it is important to consider LA-MRSA in a one-health context, studying human exposure by investigating LA-MRSA levels in pigs and in the farm environment, air, and dust. In the present investigation, we quantified LA-MRSA levels in nasal swab samples, air samples, and dust, collected at three different time points in a farm rearing pigs from appr. 30 kg until slaughter. Sampling was repeated across seven batches of pigs, resulting in the analysis of 504 nasal swab samples, together with air and dust samples. LA-MRSA was cultured and quantified on MRSA2 agar plates. Our findings revealed a significant batch-to-batch variation and a significant decrease of 94.1 % in LA-MRSA levels during the rearing period. Despite this decrease, all nasal swab samples tested positive, with the highest level reaching 353,000 cfu in a sample. In the 42 air samples collected, we found low to moderate LA-MRSA levels, with a maximum of 568 and an average of 63 cfu/m3. In the 28 dust samples collected during the second and third sampling periods, LA-MRSA counts were high, reaching up to 37,272 cfu/g, with an average of 17,185 cfu/g. The results indicate that while LA-MRSA levels in pigs gradually decrease with age and reach low levels before slaughter, the bacterium remains highly abundant in dust, which may pose an occupational hazard to farm workers.

The nEDM experiment at Oak Ridge’s Spallation Neutron Source will probe for an electric dipole moment of the neutron at an unprecedented level of sensitivity. Polarized 3He atoms dressed by a radio-frequency field are a crucial component. For field parameters comparable to the parameters being used in the nEDM experiment, numerical studies using a fourth-order Runge-Kutta solver reveal inadequacies in earlier analyses of 3He spin dynamics. It’s seen that neutron absorption is influenced by avoided level-crossings omitted previously. Also, the critical dressing condition, used to eliminate effects of the static magnetic field, requires modification. First-order perturbative corrections to eigenstates and third-order corrections to eigenenergies are needed to account for the impact of avoided level-crossings and the changes in the critical dressing condition, respectively.

Burnout, characterized by emotional and physical exhaustion, poses a significant challenge to adolescent athletes, particularly in high-intensity sports like basketball. Emotional Intelligence (EI) is the ability to manage emotions, which is negatively associated with burnout. Emotional labor, including strategies of surface acting (SA), deep acting (DA), and genuine expression (GE), is a potential key role in emotion management between EI and burnout for athletes. This study aims to investigate the relationship between EI and burnout, as well as the mediating role of emotional labor strategies among adolescent basketball players. Our cross-sectional study, conducted in youth sports schools in four different places of China, involved 260 basketball players. Our study found EI to be negatively associated with burnout. SA and GE were identified as significant mediators in this relationship, with SA positively associated with burnout and GE negatively associated. These findings suggest that enhancing EI and optimizing emotional labor strategies could be key in mitigating burnout among young athletes, thereby improving their well-being and performance.

Background/Objectives: Intracranial Epidermoid Cysts (IECs) are extremely rare intracranial tumors. The primary treatment is surgery; however, cyst adherence results in difficult removal; subtotal resection yields high recurrence rates. The mechanisms of IECs remain unknown, consequently, advances in treatment have fallen short. Tumor genetic profiling has rendered targets for drug development and for which FDA-approved options exist, reshaping cancer treatment. The genetics of IECs has not been explored. We applied Whole Exome Sequencing (WES) in IECs to gain insights into the mechanisms of oncogenesis and identify actionable targets. Methods: We performed WES in tumor tissue and matching blood, when available. Read processing, quality control and somatic variant calling followed GATK best practices. Read alignments were also used for somatic copy-number inference. Data analyses and visualizations were conducted in R. Results: Top altered genes were associated with immune system and microenvironment, suggesting an immune evasion mechanism. Recurrent and deleterious NOTCH2 and USP8 alterations were identified in 50% and 30% of the cohort, respectively. Frequent amplifications in deubiquitinases and beta-defensins, strengthened the involvement of an immune mechanism for oncogenic transformation. Drug-gene interactions highlighted NOTCH2 as clinically relevant for which FDA-approved treatments exists. Conclusions: Top altered genes may have a role in shaping an epidermoid cyst-permissive tumor microenvironment and modulating tumor immune evasion. USP8 and NOTCH2 may be clinically relevant drivers of IECs. NOTCH2 may be an interesting candidate for drug repurposing.

Emerging evidence suggests that patients suffering from COVID-19 may experience neurocognitive symptoms. Besides, other studies indicate a probable association between leukocyte telomere length (LTL) and neurocognitive changes in subjects with post-COVID-19 condition. Our study was designed to determine the correlation between telomere length and cognitive changes in subjects post-COVID-19. The study included 256 subjects, categorized based on SARS-CoV-2 infection from 2020 to 2023. On the other hand, those subjects who have a psychiatric diagnosis are considered. Besides, the MoCA and MMSE scales were applied. Telomere length was determined using a Polymerase Chain Reaction, and statistical analysis was employed ANOVA and X2 tests. We identified a decrease in LTL in individuals with post-COVID-19 conditions compared to those without SARS-CoV-2 infection (p≤0.05). However, no association was found between LTL and cognitive impairment in subjects post-COVID-19. The findings suggest that LTL is affected by SARS-CoV-2 infection. Nonetheless, this important finding requires further research by monitoring neurological changes in subjects with post-COVID condition.

The quality of wine depends upon the quality of the grapes, which, in turn, are affected by different viticulture aspects and the climate during the grape-growing season. Obtaining wine professionals’ judgments of the intrinsic qualities of selected wine products is a time-consuming task. It is also expensive. Instead of waiting for the wine to be produced, it is better to have an idea of the quality before harvesting, so that wine growers and wine manufacturers can use high-quality grapes. The main aim of the present study was to investigate the use of machine learning aspects in predicting wine quality and to develop a pipeline which represents the major steps from vineyards to wine quality indices. This pipeline outputs the predicted yield, values for basic parameters of grape juice composition, values for basic parameters of the wine composition, and quality. We also found that the yield could be predicted because of input data related to the characteristics of the vineyards. Finally, through the creation of a web-based application, we have investigated the balance berry yield and wine quality. Using these tools further developed, vineyard owners should be able to predict the quality of the wine they intend to produce from their vineyards before the grapes are even harvested.

Work disparities experienced by nurses in long-term care (LTC) can impact the retention, well-being, and health of this workforce. Despite the significant impact disparities experienced by nurses have on the workforce and LTC sector, a review of the available literature on work disparities has not been conducted on work disparities experienced by nurses in LTC. Consequently, this scoping review aimed to explore the nature and extent of research on meso-level work disparities experienced by nurses in LTC and how such disparities are linked with nurse health and well-being. Five databases were searched: MEDLINE (Ovid), EMBASE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCO host). Of the 5,652 articles retrieved, 16 studies published between 1997 and 2024 met the inclusion criteria. The average number of work disparities within each study was 3.06 (minimum = 1, maximum = 6, SD = 1.62). Types of work disparities across the 16 studies were work opportunities (n = 19), work treatment (n = 18), job security (n = 8), and work compensation (n = 8). Only four articles investigated the association of a work disparity with a variable of health and well-being. Future research on how macro-level disparities intersect with meso-level work disparities may inform a contextual understanding of how disparities transpire in the work of nurses in LTC. Studies are required to address the gaps in knowledge regarding how work disparities negatively influence the health of nurses to inform better retention, well-being, and health of nurses in LTC.

Objectives: To develop and validate the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk), aimed at aiding community healthcare workers in the early identification of individuals at high risk of Mild Cognitive Impairment (MCI); Methods: Based on nationally representative community survey data, backward stepwise regression was employed to screen the variables, and logistic regression was utilized to construct the CGMCI-Risk. Internal validation was conducted using bootstrap resampling, while external validation was performed using temporal validation. The area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA) were employed to evaluate the CGMCI-Risk in terms of discrimination, calibration, and net benefit, respectively; Results: The CGMCI-Risk model included variables such as age, educational level, sex, exercise, garden work, TV watching or radio listening, Instrumental Activity of Daily Living (IADL), hearing, and masticatory function. The AUROC was 0.781 (95% CI = 0.766 to 0.796). Calibration curve showed strong agreement, and the DCA suggested substantial clinical utility. In external validation, the CGMCI-Risk model maintained similar performance with an AUROC of 0.782 (95% CI = 0.763 to 0.801); Conclusions: CGMCI-Risk is an effective tool for assessing cognitive function risk within the community. It uses readily predictor variables, allowing community healthcare workers to identify the risk of MCI in older adults over a three-year span.

Stem cell-derived therapies have shown substantial promise in regenerative medicine for the treatment of degenerative diseases and injuries. Mesenchymal Stem Cells (MSCs) exhibit a remarkable capacity to differentiate into diverse cell types, modulate immune responses, and facilitate tissue repair. Nevertheless, concerns regarding their potential to induce tumors arise from their intrinsic properties, environmental factors, and genetic mutations that occur during handling. This review explores the intricate challenges associated with the tumorigenic potential of stem cell-derived therapeutic products and examines the underlying mechanisms contributing to this risk, such as oncogene activation, suppression of tumor suppressor genes, and the influence of the microenvironment on stem cell behavior. Furthermore, it delves into the role of epigenetic modifications and chromosomal aberrations in cell culture and expansion. This article provides an overview of strategies to mitigate tumorigenic risks, encompassing rigorous quality control measures, refined differentiation protocols, and advanced screening techniques. It also highlights innovative approaches, such as gene editing technologies and small-molecule modulation of stem cell behavior, as promising avenues to enhance safety. Despite these challenges, ongoing research and technological advancements are actively addressing these concerns to ensure safer and more effective utilization of stem cell-based therapies in clinical settings.

This study examines the combined influence of both meteorological and non-climatic factors on rice production in Bangladesh between 1990 and 2020, using the Autoregressive Distributed Lag (ARDL) model. The key variables consist of temperature, precipitation, urbanisation, fertiliser management (specifically potassium levels), and the area of permanent crops. The findings highlight the substantial detrimental impact of temperature on rice output over a prolonged period, whereas precipitation and urbanisation have a favourable affect on rice productivity. However, the utilisation of potassium fertiliser has a detrimental effect on crop productivity. Furthermore, it has been demonstrated that the development of permanent crop fields has a beneficial effect on rice output. These findings provide important information for policymakers and agricultural stakeholders, highlighting the need for adaptive strategies to improve the ability of rice production to withstand the impacts of climate change and urbanisation. The significance of these discoveries applies to rice-producing regions worldwide, offering a strategic blueprint for sustainable cultivation of rice and ensuring food security.

Piezoelectric ultrasonic motors (USMs) are actuators that use ultrasonic frequency piezoelectric vibration generated waves to transform electrical energy into rotary or translating motion. USMs are paid more attention because they offer distinct qualities over traditional magnet-coil-based motors, such as miniaturization, great accuracy, speed, non-magnetic nature, silent operation, straightforward construction, broad temperature operations, and adaptability. This review study focuses on the principle of USMs and their classifications, characterization, fabrication methods, applications, and future challenges. Firstly, the classifications of USMs, especially, standing wave, traveling wave, hybrid mode, multi degree of freedom USMs are summarized, and their respective functioning principles are explained. Secondly, the finite element modelling analysis for design and performance predictions, the conventional and nano/micro fabrication methods, and, the various characterization methods are presented. Thirdly, their advantages, such as high accuracy, small size, and silent operation and their benefits over conventional motors for the different specific applications are examined. In addition, the substantial contributions to a variety of tech-nical fields like surgical robots, industrial, aerospace, and biomedical applications are introduced. Finally, their future prospects and challenges in USMs development, with an emphasis on downsizing, increasing efficiency, and new materials are outlined.

Herbicides are widely used in agriculture to control weeds and enhance crop productivity. However, their application can have significant impacts on soil health and nutrient dynamics. This paper reviews the effects of herbicides on soil properties, microbial communities, and nutrient availability, with a particular focus on calcium deficiency. The review synthesizes findings from peer-reviewed journals and reports, including research conducted in Australia. The correlation between herbicide application and calcium deficiency is explored, highlighting both positive and negative impacts. The paper concludes with recommendations for sustainable herbicide use and alternative weed management strategies.

Recent developments in metallic additive manufacturing (AM) processes for the production of high-performance industrial pieces have been hampered by the limited availability of reliably processable or printable alloys. To date, most of the alloys used in AM are commercial grades that have been previously optimized for different manufacturing techniques. This study aims to design new alloys specifically tailored for AM processes, to minimize defects in the final products and optimize their properties. A computational approach is proposed to design novel and optimized austenitic alloy compositions. This method integrates a suite of predictive tools, including machine learning, calculation of phase diagrams (CALPHAD) and physical models, all piloted by a multi-objective genetic algorithm. Within this framework, several material-dependent criteria are examined and their impact on properties and on the occurrence of defects is identified. To validate our approach, experimental tests are performed on a selected alloy composition: powder is produced by gas atomization and samples are fabricated by laser powder bed fusion. The microstructure and mechanical properties of the alloys are evaluated and its printability is compared to a commercial 316L stainless steel taken as a reference.

In the framework of the H2020 CLEANDEM project a small robotic vehicle was equipped with a series of different sensors, developed for the preliminary inspection of areas possibly contaminated by radiation. Such unmanned inspection allows to identify dangerous locations prior to the possible start of human operations. One of the developed devices, named MiniRadMeter, is a compact, low-cost sensor to perform gamma and neutron radiation field mapping of the environment. The MiniRadMeter was successfully tested in a simulated field mission with four "hidden" radioactive sources and a neutron generator. In this work we describe the test procedure and the results, also supported by the outcome of dedicated Monte Carlo simulations.

Bio-char is a charcoal-like substance made through the pyrolysis of organic biomass. It has the potential to address issues related to agriculture and the environment. This thorough analysis examines the potentials of bio-char in Ethiopia to enhance crop productivity, reduce climate change, and improve soil fertility. Drawing from academic databases and peer-reviewed literatures, the review explores the production and characterization of bio-char, its impact on soil fertility and crop productivity, and its role in carbon sequestration and greenhouse gas mitigation. The review emphasizes on how bio-char may improve plant nutrition and soil fertility, which raises agricultural yields and quality while improving drought resistance. The review also emphasizes the potential of bio-char for greenhouse gas mitigation and carbon sequestration, enhancing Ethiopia's efforts to mitigate climate change. Yet the study also points out several challenges and opportunities that need to be addressed to allow Ethiopians to use bio-char technology on a large scale. These include the need for appropriate policy and regulatory frameworks, the availability and accessibility of bio-char feedstocks, and the importance of continued research and development to optimize production methods and application strategies. The review concludes by highlighting the groundbreaking potential of bio-char in promoting environmentally friendly agricultural practices and sustainable agriculture in Ethiopia. It necessitates a coordinated effort to solve the problems and grasp the opportunities by making sound decisions in policy integration, research, and development. Ethiopia can advance its sustainable development goals by using bio-char to create a road towards increased food security, healthy soil, and environmental resilience.

Recently, neglected and underutilized species (NUS) have deservedly come to the forefront of scientific interest because they can contribute to the human nutrition, due to the content of bio-active substances such as antioxidants. Despite the great diversity and rich tradition in use of Philippine NUS, the nutritional properties of many edible plants remain unexplored. The main objective of this study was to evaluate various parts of eleven NUS fruits and vegetables traditionally consumed in the Philippines, namely Allaeanthus luzonicus, Canarium ovatum, Dillenia philippinensis, Ficus pseudopalma, Flacourtia indica, Flacourtia inermis, Garcinia intermedia, Heliotropium arboreum, Posoqueria latifolia, Stelechocarpus burahol and Sterculia quadrifida for their total phenolic content (TPC) and in vitro antioxidant activity (DPPH and ORAC assays). The strongest antioxidant activity obtained in both assays were inflorescence of A. luzonicus (DPPH IC50 = 91.0 μg/mL, ORAC IC50 = 37.9 μg/mL) and fruit of S. burahol (DPPH IC50 = 253.7 μg/mL, ORAC IC50 = 32.2 μg/mL). These two species also had the highest TPC (202.1 and 133.0 µg GAE/mg extract, respectively). For all samples tested, the strong correlation was found between TPC and antioxidant activity. Based on our results, A. luzonicus and S. burahol have a promising potential as novel antioxidant rich food.

Background/Objectives: Airway management techniques, including mask ventilation and tracheal intubation, are vital across medical settings. However, these procedures can be challenging, especially when environmental conditions are less than ideal. This study explores how the height of the operating table affects the difficulty of surgical procedures involving mask ventilation and tracheal intubation. Methods: Twenty anesthesiologists participated in this study. We assessed the difficulty of procedures- such as mask ventilation, Macintosh laryngoscopy, and video laryngoscopy with McGRATH and AWS- on a four-level scale. The operating table’s height was adjusted at four points: operator's umbilicus, inferior margin of the 12th rib, xiphoid process, and nipple. Results: Mask ventilation was easiest at the operating table’s height aligned with the inferior margin of the 12th rib. Conversely, direct laryngoscopic exposure was perceived easier at higher table heights, with nipple height being optimal. McGRATH laryngoscopy showed consistent difficulty across table height, whereas AWS tended to be somewhat more difficult at greater heights. Conclusions: The optimal bed height for video laryngoscopy coincided with that for mask ventilation. Video laryngoscopy offers enhanced flexibility in optimal patient positioning compared to Macintosh laryngoscopy, contributing to its advantages in tracheal intubation procedures.

This research reviews a novel artificial intelligence (AI) based application called ‘TLDetect’, which filters and classifies anomalous glow curves (GCs) of thermoluminescent dosimeters (TLDs). Until recently, GCs review and correction in the lab were performed using an old in-house software, which uses Microsoft Access database and allows the laboratory technician to manually review and correct almost all GCs without any filtering. The newly developed application ‘TLDetect’ uses a modern SQL database and filters out only the necessary GCs for technician review. TLDetect first uses an Artificial Neural Network (ANN) model to filter out all regular GCs. Afterwards, it automatically classifies the rest of the GCs into five different anomaly classes. These five classes are defined by GCs typical patterns, i.e. high noise at either low or high temperature channels, untypical GC width (either wide or narrow), shifted GCs whether to the low or to the high temperatures, spikes, and the last class contains all other unclassified anomalies. By this automatic filtering and classification, the algorithm substantially reduces the amount of technician’s time of reviewing the GCs and makes the external dosimetry laboratory dose assessment process more repeatable, accurate and fast. Moreover, a database of GCs class anomalies distribution over time is saved along with all their relevant statistics, which can later assist with preliminary diagnosis of TLD reader hardware issues.

Data leakage by statistical officers represents a significant statistical crime under the Indonesian Statistics Law. However, despite the legal provisions, there has been a notable absence of enforcement actions against such breaches, raising questions about the effectiveness and applicability of the current legal framework for addressing statistical crimes related to data leakage. This study identifies a research gap in the enforcement and operationalization of existing laws, emphasizing the lack of empirical data on how these legal provisions are applied in practice. Utilizing an empirical research methodology, this study analyzes data and real-world instances of statistical data leakage. The findings reveal that unethical behavior among statistical officers, inadequate data security measures, and the threat of social engineering significantly contribute to the potential for data breaches. The study's strength lies in its focus on providing a comprehensive understanding of these issues and proposing actionable solutions. This research not only fills the existing gap by offering empirical insights but also advances practical recommendations for enhancing data protection and legal enforcement mechanisms within Indonesia’s statistical framework.

Costa Rica, widely acknowledged for its environmental leadership, is now facing a significant challenge in managing waste, a situation that could potentially compromise both its environmental and public health achievements. This analysis delves into the waste management issues in Costa Rica, particularly in urban areas such as San José, responsible for nearly half of the country's waste. The study identifies several pressing concerns, including the heavy burden on landfill capacities, a recycling rate of just 9.6%, and substantial regional differences in waste management practices.To address these challenges, the research employs a combined methodology, utilizing Linear Regression (LR) and AutoRegressive Integrated Moving Average (ARIMA) models to project future trends in CO2e emissions and waste minimization from 2024 to 2050. This method underscores the vital need for public involvement and the introduction of innovative strategies in waste management. The research also introduces a Waste Management Innovation Index to compare Costa Rica’s practices with those of leading nations like Germany and South Korea, identifying key areas for improvement.Furthermore, the study incorporates insights from stakeholders, revealing the intricate balance of cultural, economic, and regulatory factors that shape waste management policies. Despite efforts by the government, such as the Environmental Health Route and the National Circular Economy Strategy, results show limited progress, particularly in rural regions. The study highlights the urgent need for better infrastructure, targeted public awareness campaigns, and the use of advanced technologies like Artificial Intelligence (AI) and blockchain to enhance sustainable waste management practices. The research provides strategic recommendations to help Costa Rica improve its waste management systems in line with international standards, ensuring long-term environmental sustainability and protection of public health.

Cleomaceae is an important group that is medicinally and economically important. However, its systematic position has been controversial. In this study, we have obtained three chloroplast genomes sequencing results of Cleomaceae species. The genome sizes ranged from 157,073 bp (Sieruela rutidosperma) to 158,152 bp (Gynandropsis gynandra). These chloroplast genomes have a typical quadripartite formation with a large single-copy (LSC) region (86,422-87,242bp), a small single-copy (SSC) region (18,485-18,548bp), and a pair of inverted repeat (IR) regions (26,083-26,184bp). The chloroplast genomes encoded 131-132 genes, comprising 8 rRNA genes, 37 tRNA genes, and 79-84 protein-coding genes. The overall GC contents of the three chloroplast genomes are almost identical (35.81%-36.02%). The phylogenetic trees concluding 8 Cleomaceae plants were constructed based on ML and BI methods. The results showed that Gynandropsis gynandra and Sieruela rutidosperma were in the same branch, with Corynandra viscosa as their sister. Six hypervariable areas were identified, containing clpP, matK, ndhF, atpH-atpI, atpF-atpH and petN-psbM which could be used in species identification and population genetics studies. This study provides valuable information for further species identification, evolutionary and genetic studies of Cleomaceae in the future.

Many children who live in the interior and mountainous areas of Papua-Indonesia do not get the right of education. This research aims to formulate a theoretical concept of boarding school-based character education by implementing Papuan cultural contextual education in the process of education. The method used is a qualitative method with a grounded theory approach. The research participants were 14 people. Data were collected through semi-structured interviews and textual analysis of the interview results. The data analysis technique uses the Atlas.ti application by using three levels of coding: open coding, axial coding, and selective coding. The research results show that there are six main concepts as a model of boarding school character education: personal development, spiritual development, extracurricular activities, clean and healthy lifestyles, learning from inspirational figures, and academic development. These six theoretical concepts can be divided into internal and external character building. One of the uniqueness of character education is the integration of local cultural values in the whole process of character education of the children, both in the school environment and in the dormitory. The results of the study provide insights for educators, schools, and government on different forms of character education models.

The Ulytau region located at the heart of Kazakhstan is one of the promising territories for setting up geopark. Here, in the centre of Kazakhstan is a geographical and economic region which consists of desert-steppe landscapes with small, steep low-mountain massifs. This is one of the largest regions of Kazakhstan in terms of industrial potential, wealth of minerals and raw materials, natural and cultural heritage. The world's largest copper-bearing province is located here. The geological history of this area tells of no less than 500 million years of planetary development. Despite the lengthy time that geology and the active use of resources were in focus, geoheritage objects were previously lacking attention and any characterization. In the Ulytau region, many preserved archaeological and ethnographic sites indicate that the Saryarka steppes were included in the trade and cultural sphere of the Great Silk Road. Geological, historical and sacred objects make this territory an extremely interesting object for the development of geotourism and the creation of geoparks as the basis for the sustainable development of the region.

Rapeseed is an important commercial crop in the world, which is used for animal fodder and human consumption. The varied insolation duration and intensity is one of the main reasons for effecting the seed yield and seed quality of Brassica napus (B. napus) in worldwide. In this study, a highly oil seed content rapeseed cultivar “Qingyou 3” was subjected to light supplementary trial at both vegetative growth period and the seed productive stage. Different light quantity conditions were stimulated by light-emitting diodes (LED), main plot factor was land condition under LED (Treatment) and without LED (Control) in natural condition. The size and thickness of leaves, photosynthesis efficiency, seed oil content of B. napus increased significantly after light supplementary. Eighteen cDNA libraries were constructed from leaf segments (30 days after transplanting, 30 DAT) and seed 30 and 40 days after pollination (DPA) for RNA transcriptome sequencing. It was found that genes encoding lipid transfer protein, phenylpropanoid biosynthesis and plant hormone signal transduction were enriched in differentially expressed genes. This study is aim to identify the differentially expressed genes and signaling pathways in the leaves and seed of B. napus at the vegetative and seed productive stages under different light quantity. All the results provide the knowledge for understanding sufficient light plays a critical role in promoting photosynthesis, and is the basis of material accumulation and yield formation.

Currently, many health workers have died of being infected by dangerous infectious diseases. One solution is to prevent the spread of transmissions by minimizing contact between patients and staff or others using a mobile robot for delivering logistics services. We propose an approach by applies a navigation system using a position driver and obstacle avoidance using a fuzzy controller and particle swarm optimization for path planning in an unknown environment for a holonomic mobile robot. A Fuzzy Controller was used for obstacle avoidance so that the mobile robot could avoid obstacles using existing proximity sensors as the perception of the robot. In the path planning section, Particle Swarm Optimization is used to find intermediate points that must be reached by the mobile robot to reach their target. First, we performed simulation under the condition that the simulation resolution was similar to that of real conditions. It was found that the Trigonometric Function Adaptive PSO (TFAPSO) was better for finding the optimal solution based on the safest, shortest path, and lowest time. Finally, the holonomic mobile robot is tested directly in an unknown environment with the trajectory path generated by TFAPSO in real condition.

The rapid advancement of artificial intelligence (AI) brought about significant opportunities and challenges in educational environment. It is disputable whether the application of AI to education is beneficial or not regarding human learning and teaching. This study aims at exploring the implications of the evolving educational landscape by comparing and discussing human and AI learning processes. Even though AI is not a conscient agent, it does not spell out any words randomly but provide meaningful texts with any reasoning. It helps us to understand human learning better by comparing learning in biological and artificial intelligences. Moreover, the new concepts in learning in AI come about the change of learning paradigm such as connectionism/connectivism. After all, AI will empower the abilities of learning and teaching for students as well as teachers. This study will give some implications for the future education with AI.

The purpose of this research is to find out the mediation role of employees’ brand knowledge between organizational citizenship behavior and employees behavior in hotels. Quantitative approach used in this research, and 204 online questionnaire used to collect the data from three, four, and five, hotel employees in Jordan. The findings proposed that there is a positive mediation role of employees’ brand knowledge between organizational citizenship behavior and employees’ behavior in hotels. Moreover, findings approved that organizational citizenship behavior has a positive effect on employees’ behavior and its dimensions, helping behavior, in-role performance, and creative behavior. On the other hand, organizational citizenship behavior proposed a negative effect on employees’ deviant behavior. The value and the originality of this research is to provide deep understanding and practical implications to the hotel managements and sector on how the employees in the hotels may behave and affected by their organizational citizenship behavior.

Foods that are fermented have a crucial role in global diets, these foods benefit from the process of fermentation, which enhances nutrition, flavor, and safety through the use of probiotics, anti-aging compounds, and antibiotics. Traditional fermentation is based on the spontaneous activity of microorganisms, while modern methods utilize defined cultures for consistency. The microorganisms in cheese are important for the flavor and texture of the product. These microorganisms are either non-starter or starter bacteria, yeast, and mold. The advances in sequencing technology have facilitated an increase in our understanding of these communities and their contribution to the quality and safety of cheese. Despite the health benefits of fermented dairy products, such as yogurt, they can pose a risk of contamination with pathogens. New methods of management and sequencing are crucial to ensuring the safety and quality of fermented foods, combining traditional methods with modern advances.

This study was conducted to analyse viability of primary chicken embryo fibroblasts by pre-plating and efficiency of adipogenic trans-differentiation for cultured meat production. Morphology and proliferative capabilities of chicken embryo fibroblasts (CEF) were compared with those of chicken satellite cells (CSC) isolated from chicken embryos. Isolated CEF exhibited significantly lower expression of Pax7 (paired-box protein 7) and MHC (Myosin Heavy Chain) than CSC (p &lt; 0.05). Over 90% of isolated CEF expressed CD29 and Vimentin. Analysis of proliferative capabilities of CEF revealed no significant differences in EdU-positive cell (%), cumulative cell number, doubling time, and growth rate from passage 1 to passage 9 (p &gt; 0.05). Up to the passage 9, CEF underwent adipogenic trans-differentiation. As passages increased, lipid accumulation and adipocyte size decreased significantly (p &lt; 0.05). This indicates that CEF can be isolated by 2 hours of pre-plating and survive stably up to the 9th generation. Moreover, efficient production of fat can be achieved by inducing adipogenic trans-differentiation of lower-generation CEF.

Human-elephant conflict has become a conservation challenge in Asia and Africa resulting in considerable human fatalities annually. We deployed an AI-embedded camera-alert system in a conflict hotspot in West Bengal, India to determine if AI algorithms could accurately detect elephants and if real-time alerts that triggered a rapid response could prevent serious incidents. The system successfully detected elephants near villages (266 events) and transmitted real-time alerts (x̄ = 42 seconds) permitting quick response by field personnel to prevent conflict (x̄ = 18.2, SD = 12.4 min to arrival). Matriarch herds of elephants were detected mostly at night when human traffic was minimal; lone adult bulls, the class most prone to conflict, were detected day and night. Frequent detections of humans (33,217 events) on routes used by elephants highlighted the value of real-time monitoring especially during daytime. Twelve human fatalities and eighteen serious injuries occurred in the study area between 2019-2023 but none during deployment of the AI system, supporting the hypothesis that alerts integrated with rapid response can reduce conflict. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to conflict-prone species to provide early warning and promote coexistence.

Acinar cell carcinoma (ACC) accounts for about 1% of pancreatic cancers. The molecular and clinical features of ACC are less characterized than pancreatic ductal adenocarcinoma. We retrospectively evaluated the clinical and molecular features of ACC patients who underwent germline and/or somatic molecular testing at The University of Texas MD Anderson Cancer Center from 2008 to 2022. Patient information was extracted from our institutional database with the approval of Institutional Review Board. We identified 16 patients with available molecular testing results. Fourteen patients had metastatic disease, 1 had borderline resectable disease, and 1 had localized resectable disease at diagnosis. Fifteen patients were wild type for KRAS (1 patient had unknown KRAS status). Somatic/germline mutations of DNA damage repair genes (BRCA1/2, PALB2, and ATM) were present in 5 of 12 patients tested for these genes. One patient was found to have RET fusion and responded favorably to selpercatinib for over 42 months. The median overall survival (OS) was 24 months for patients with metastatic disease. One of the additional two cases which had BostonGene tests was found to have NTRK1 fusion. RNA and TME analysis by BostonGene of the two cases reported immune desert features and relatively lower RNA levels of CEACAM5, CD47, CD74 and MMP1 and higher CDH6 compared with PDAC.

Croton grewioides Baill., a species native to the Caatinga, popularly known as canela de cunhã, is used in traditional medicine to treat gastrointestinal diseases such as diarrhea, gastritis and stomach ulcers. This study aimed to identify the chemical composition of the essential oil of C. grewioides (OECG) and evaluate its antibacterial and antibiotic-modulating activities against both standard and multidrug-resistant bacteria. To analyze the compounds, present in the oil, gas chromatography coupled with mass spectrometry (GC/MS) and gas chromatography with flame ionization detector (GC/FID) techniques were used. In the bacteriological tests, the Minimum Inhibitory Concentration (MIC) was obtained using the broth microdilution technique. The modulating effect of the essential oil was determined by calculating the subinhibitory concentration followed by serial microdilution of the antibiotics. The MIC reduction factor (FRC) was calculated and its data expressed as a percentage. Analysis of the chemical composition identified the presence of the major compound estragole with a relative abundance of 50.34%. The MIC values obtained demonstrated efficacy in K. pneumoniae isolated from urine with MIC values of 512 µg/mL. OECG potentiated the effects of all antibiotics tested on S. aureus ATCC 29213, K. pneumoniae Carbapnemase, E. coli ATCC 25922 and S. aureus ATCC 29213 strains with their FRC of 97.65 %, 99.80 %, 99.85 % and 99.88 %, respectively. Thus, the essential oil of C. growioides presents synergistic effects when combined with the tested antibiotics, in addition to acting in the fight against bacterial resistance to antibiotics.

The current study investigated the neuroprotective effects of rutin hydrate (RH) in an Alzheimer’s disease (AD)-like learning and memory impairments rat model. Since AD is an age-related degenerative brain disorder characterized by a progressive worsening in cognitive function and memory, RH may be a potential drug for the treatment of AD-like memory loss, and this work is aimed to evaluate whether RH has neuroprotective effects in memory deficits induced by scopolamine (SCO). In our study, RH demonstrated beneficial effects as a neuroprotector in the brain and improved learning, memory, and synaptic plasticity in a rat. Rats were administered RH (100 mg/kg) and SCO (1.5mg/kg), and performed behavioral tests such as Morris water navigation test, Y-maze test, and passive avoidance test to evaluate the ability of learning and memory. In accordance with these findings, RH behaviorally attenuated SCO-induced shortening of step-through latency in the PA test, increased the percent of alternation in the Y-maze, and increased the time spent in the target zone in the MWN. Moreover, the neuroprotective effect of RH on learning and memory was investigated through the long-term potential on organotypic hippocampal slice cultures. RH increased the total activity of field excitatory postsynaptic potential (fEPSP) following theta burst stimulation and attenuated SCO-induced blockade of fEPSP. This approach could potentially be used as a therapeutic strategy for the restoration of learning and memory function and the prevention of the progression of AD. SCO treatment decreased the levels of BDNF/TrkB/ERK/CREB/Bcl2 and increased the Bax protein level in rat hippocampus. RH ameliorated the expression of these proteins by attenuating SCO-induced up or downregulation in the hippocampus. Based on these findings, the results highlight the molecular and cellular mechanisms through which RH is proposed to exert its neuroprotective effects in the prevention and treatment of learning and memory deficit disorders.

Grape pomace is a winery byproduct rich in polyphenols with antioxidant capacity, which makes it an attractive product for use in pig diets. The study aimed to investigate the effect of 0, 5, and 10% inclusion of dehydrated grape pomace (DGP) in finishing pig diets. Including 10% of DGP in the diets increased (P&lt;0.05) daily feed intake, backfat thickness at the first rib, P2 backfat thickness, fat area, and fat to meat ratio and decreased (P&lt;0.05) the percentage of lean meat. Grape pomace did not affect TBARS and fresh meat quality characteristics, except for intramuscular fat. When 10% DGP was included in the diet, intramuscular fat, ΣSFA, ΣMUFA, and Σω-3 increased and ω-6:ω-3 ratio was reduced. In conclusion including up to 10% of DGP in the diet of finishing pigs did not affect growth performance, and the oxidative stability of processed meat, but increased the adiposity of the carcasses. Meat quality was improved through an increase in intramuscular fat and ω-3 fatty acids at 10% inclusion. It is feasible to include DGP in pig diets at a level of at least 10%, which would contribute to the rational use and reduction of environmental liability of by-products from the winery industry.

It is commonly held that gravitation is a major force field influencing matter. Existing models regard gravitational interaction as a singular weak force; the weakest among the four fundamental forces defined in physics. Recent experimental findings, in both controlled laboratory experiments and natural occurrences, nevertheless, have unveiled the presence of a gravitational repulsion alongside gravitational attraction in the universe. This series of studies reveals that the observed gravitational force results from two immensely powerful distinct forces—gravitational repulsion and attraction—nearly equal and opposing thus in a state of near equilibrium in nature. While the theory of 'Universal Gravitation' established the proportionality of the gravitational force to mass, the recognition of gravitational repulsion force proportional to the temperature as a manifestation of thermal energy has only emerged from present experimental insights. Furthermore, the imbalance between these two forces has been identified as the Newtonian force, initiating the motion of an object. It provides a compelling explanation for the accelerating expansion of the universe: during atomic fusion in stars, a portion of mass is converted into energy. This process increases the energy and decreases the mass of stellar objects. The increase in energy enhances the repulsive force among them, while the reduction in mass diminishes their gravitational attraction, leading to the accelerating expansion of the universe.This paper introduces a model elucidating the characteristics of gravitational forces and the transmission of energy within matter through the concept of 'Gravitational Currents.' A set of postulates is formulated to elucidate the interaction of gravitational fields with matter and the presence of gravitational currents. The discussion is supported by experimental evidence substantiating these concepts.In this series of experiments, a gyroscope - a standard apparatus in the scientific community with a spinning wheel mounted at one end of a freely pivoted rod having full degrees of freedom - is utilized. When the wheel is set in rotation, the rod carrying the wheel precesses[1] around the vertical axis at the pivoted end, while levitating in free space defying the Earth's gravitational attraction. This paper establishes that the conventional explanation involving the cross product of two vectors—the torque due to weight and the angular force (change of angular momentum) of the wheel—fails to account for the observed revolving and lifting forces. Instead, it is demonstrated that these forces result from the upward shear force (which is the lifting force in this case) generated within the axis of the rod and the wheel itself. This phenomenon is attributed to the flow of energy, conceptualized as gravitational current, within the axial rod in the Earth's gravitational field. The described process can be envisioned as a gravitational motor with gravitational current flowing through matter in a gravitational field.The results of the experiments substantiate the conclusion that there exist two fields defined as the intrinsic field and the natural force fields. The intrinsic gravity field is innate (linked) to every object, matter or entity in the universe, and it is dispersed in all directions in free space independent of other entities. The actual force fields manifest between any two objects in the universe once they become cognizant of each other's existence through their intrinsic fields.The inherent force field exhibits a preference/tendency for existence within a medium rather than in free space, akin to the way a magnetic field runs within ferromagnetic materials rather than in open space. If external force fields pass/runs through the medium, it affects the internal force fields of the medium, depending on the magnitudes and the directions of the external force fields and intrinsic force fields. This implies that energy moves through the force field, and under the influence of the gravitational field, this energy flow can be conceptualized as a gravitational current.Gravitational waves and electromagnetic waves share similarities in their roles in transmitting energy through open space. The potential for an analogy within a unified theoretical framework connecting electromagnetic fields and gravitational fields has surfaced, echoing Einstein's attempted unified theory proposed in 1916. The paper delves into the parallels between electromagnetic motors and gravitational motors.Furthermore, alongside the concept of gravitational currents addressed in this paper, the research also elucidated a precise definition of the [Newtonian/mechanical] “force” and mechanism for its origination and function, termed: Intrinsic Energy Spin Force (IESpinF). The analysis presented here demonstrates that the Newtonian/mechanical force arises from a perturbation or imbalance within the equilibrium of gravitational IESpinF, which includes both repulsion and attraction forces. [1] One of the main properties of gyroscopic action is “precession”. Precession is a change in the orientation of the rotational axis of a rotating body. If the axis of rotation of a body is itself rotating about a second axis, that body is said to be precessing about the second axis.

Sensory processing challenges are crucial yet often neglected aspects in the care of children with neurodevelopmental disorders and genetic conditions. They represent a key area of interest in neuroscience, as they significantly impact children's daily functioning and quality of life. This observational study examines the characteristics of these challenges in a group of 614 children, aged 3 to 14 years and 11 months, divided into three groups: 183 with neurodevelopmental disorders (Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder, developmental delays, learning disorders), 89 with genetic conditions (22q11.2 Deletion Syndrome, Williams Syndrome, Pseudohypoparathyroidism), and 342 controls. Sensory processing was assessed using the Sensory Profile 2 (SP2). Results indicated that children with neurodevelopmental disorders and genetic conditions exhibited significant sensory processing difficulties compared to controls. The SP2 identified sensory challenges across different sensory systems, with varying configurations depending on the diagnosis. Children with neurodevelopmental disorders and genetic conditions show marked sensory processing challenges impacting daily lives and well-being. These findings highlight the importance of early identification and tailored evidence-based interventions to address these specific sensory processing issues. Further research should explore the long-term impact of these interventions in these different populations and their integration into broader therapeutic programs.

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box and ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context Zero shot, Few shot, Chain of Thought, Visualization of Thought, Self Consistency, logicLM and Emotional to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self Consistency techniques enabled GPT-4o to correctly evaluate 90% of logical-spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.

Background/Objectives: Rehabilitation helps reduce disability in dementia. The Australian National Dementia Action Plan identifies a gap in clear treatment pathways post-diagnosis, affecting the quality of life for those with dementia. This study assessed the impact of a one-day dementia training course and follow-up on GPs' and practice nurses' knowledge, attitudes, and confidence regarding dementia rehabilitation. Methods: The training, led by two experienced GPs and an academic physiotherapist, covered dementia diagnosis, allied health roles, care planning, and referrals. The follow-up involved applying the learnt material and completing a reflective task. Three longitudinal surveys (Dementia Knowledge Assessment Scale - DKAS, General Practitioners’ Attitudes and Confidence towards Dementia Survey - GPACS-D, and Dementia Rehabilitation Scale) and Likert-scale statements were conducted pre-course, post-course, and at 4-month follow-up, alongside a focus group. Descriptive and regression analyses were applied to survey data, and content analysis was used for focus group data. Results: Seventeen participants (14 GPs, 3 nurses) completed the pre-post course survey, with eight (6 GPs, 2 nurses) participating in follow-up and focus group discussions. Post-course, DKAS scores increased by 12.1%, GPACS-D by 10.1%, and the dementia rehabilitation scale by 9.4%. Likert-scale statements improved by 8-79%. At the four-month follow-up, there was a slight, non-significant decline in most measures. Focus groups highlighted the training’s impacts, useful components, barriers, and suggestions for improvement. Conclusion: Training GPs and practice nurses in dementia rehabilitation enhances knowledge, awareness, and confidence. Ongoing efforts are needed to sustain benefits and address referral barriers for better access to dementia rehabilitation services.

A presentation is provided of a structural approach for the concurrent teaching of introductory propositional calculus and set theory. The existence of isomorphism is shown between each law (or tautology) of propositional calculus and the form of a corresponding set which is equal to the universal set U considered.

Background: There has been a lack of tools to identify listening difficulties in school settings for both hearing and hearing-impaired Italian students. Thus, the present study aimed to realize cross-cultural adaptation and validation of the Listening Inventory for Education-Revised for Italian students (LIFE-R-ITA). Methods: Following the validation of two forward-backward translations by a multidisciplinary committee, the content validation for the LIFE-R-ITA was performed by pre-testing six implanted children (8-18 years old). After minor cross-cultural adaptations, normative data were collected from a sample of 223 hearing students enrolled in different school settings and educational degrees. Results: For the LIFE-R-ITA, hearing students showed an average score of 72.26% (SD=11.93), reflecting some listening difficulties. The subscales (LIFE total, LIFE class, and LIFE social) indicated good internal consistency. All items were shown to be relevant. Most challenging situations happened when listening in large rooms, especially when other students made noise. LIFE social scores were significantly worse than those of LIFE class (p &lt; 0.001). Conclusions: The LIFE-R-ITA may support teachers and clinicians in assessing students’ self-perception of listening at school. Such understanding may help students overcome their listening difficulties, by planning and selecting the most effective strategies among classroom interventions.

Big Epidemiology is an innovative framework that extends the interdisciplinary approach of Big History to understand disease patterns, causes, and effects across human history on a global scale. This comprehensive methodology integrates epidemiology, genetics, environmental science, sociology, history, and data science to address contemporary and future public health challenges through a broad historical and societal lens. The foundational research agenda involves mapping the historical occurrence of diseases and their impacts on societies over time, utilizing archaeological findings, biological data, and historical records. By analyzing skeletal remains, ancient DNA, and artifacts, researchers can trace the origins and spread of diseases, such as Yersinia pestis in the Black Death. Historical documents, including chronicles and medical treatises, provide contextual narratives and quantitative data on past disease outbreaks, societal responses, and disruptions. Modern genetic studies reveal the evolution and migration patterns of pathogens and human adaptations to diseases, offering insights into co-evolutionary dynamics. This integrative approach allows for temporal and spatial mapping of disease patterns, linking them to social upheavals, population changes, and economic transformations. Big Epidemiology also examines the roles of environmental changes and socioeconomic factors in disease emergence and re-emergence, incorporating climate science, urban development, and economic history to inform public health strategies. The framework reviews historical and contemporary policy responses to pandemics, aiming to enhance future global health governance. By addressing ethical, legal, and social implications, Big Epidemiology seeks to ensure responsible and effective epidemiological research and interventions. This approach aims to profoundly impact how we understand, prevent, and respond to diseases, leveraging historical perspectives to enrich modern scientific inquiry and global public health strategies.

This research investigates the relationships between occupational health and safety (OHS), staff resilience (SR), staff engagement (SE), and organizational resilience (HOR) within Saudi Arabian hospitals. Employing a quantitative, cross-sectional design, data were collected from 127 administrative staff members working in both public and private hospitals in Saudi Arabia. Using SmartPLS to test the hypothesized relationships and mediation effects, the findings reveal that OHS significantly impacts both SR and SE, and SR significantly influences HOR. Additionally, SE significantly affects HOR. The study also confirms a partial mediation effect of SE and SR in the relationship between OHS and HOR. The model demonstrates substantial explanatory power for HOR, SE, and SR. These results underscore the critical role of OHS in fostering a resilient healthcare environment by enhancing staff engagement and resilience. The study’s implications highlight the importance of targeted interventions to improve OHS practices, promoting overall hospital resilience in alignment with Saudi Arabia’s Vision 2030.

[3:46 PM] Anahita Zahertar This research explores the factors influencing bikeshare usage durations in the Detroit Metropolitan Area over two years, focusing on spatial, temporal, and COVID-19-related variables. Using a fully parametric hazard-based duration model with random parameters, we address data heterogeneity and uncover how different conditions affect bikeshare trips. Our findings reveal that a) intense environmental factors such as high traffic stress, poor weather, and high COVID-19 risk levels are associated with shorter trip durations b) in contrast, supportive initiatives like memberships, an affordable $5 Access Pass, a free one-month pass during the pandemic, and the introduction of new stations have been more likely to encourage longer rides c) furthermore, the study examines how variables like gym closures due to the pandemic, evening hours, and the addition of new stations, which were set as random variables in our model, exhibit both positive and negative relationships with ride durations. A key finding is the 20-minute mark in ride durations, which helps understand user behaviors and trip purposes. This insight aids urban planning by suggesting strategic bike station placements to enhance bikeshare system efficiency and meet diverse community needs. This study not only deepens our understanding of urban mobility dynamics but also underscores the effectiveness of adaptive strategies in promoting sustainable urban transportation.

This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics." Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach.

In recent years, artificial intelligence technology has seen increasingly widespread application in the field of intelligent manufacturing, particularly with deep learning offering novel methods for recognizing geometric shapes with specific features. In traditional CNC machining, computer-aided manufacturing (CAM) typically generates G-code for specific machine tools based on existing models. However, the tool paths for most CNC machines consist of a series of collinear motion commands (G01), often resulting in discontinuities in the curvature of adjacent tool paths, leading to machining defects. To address these issues, this paper proposes a method for CNC system machining trajectory feature recognition and path optimization based on intelligent agents. This method employs intelligent agents to construct models, analyze the key geometric information in the G-code generated during CNC machining, and uses the MCRL deep learning model incorporating linear attention mechanisms and multiple neural networks for recognition and classification. Path optimization is then carried out using mean filtering, Bezier curve fitting, and an improved novel adaptive coati optimization algorithm (NACOA) according to the degree of unsmoothness of the path. Taking the optimization of a gear model’s process file as an example, the effectiveness of the proposed method is verified. The research results indicate that the CNC system machining trajectory feature recognition and path optimization method based on intelligent agents can significantly enhance the smoothness of CNC machining paths, reduce machining defects, and has substantial application value.

This in vitro study aimed to analyze the surface roughness (Ra) and color stability (ΔEab, ΔE00) following simulated mechanical brushing, and to evaluate the microtensile (μTBS) to dentin of Self Adhering Resin Flowable (SARF). The selected materials were Constic, Yflow AS, and Tetric N flow (TNF/control). Thirty composite resin cylinders were fabricated for surface property evaluation. Ra and color were assessed both before and after simulated brushing. The thresholds of 50:50% perceptibility and acceptability of color difference of the evaluated resins were assessed. For μTBS analysis, fifteen molars were selected, sectioned to expose flat dentin surfaces, and restored according to manufacturers' instructions. Subsequently, they were sectioned into sticks for microtensile testing. Statistically significant differences in Ra among the groups, with Constic exhibiting the highest Ra value (p < 0.05), while Yflow AS showed the lowest Ra value. No statistically significant difference in color was observed among the groups (p > 0.05). The 50:50% perceptibility and acceptability thresholds set at 1.2 and 2.7 for ΔEab and 0.8 and 1.8 for ΔE 00. All the results fell within the acceptable limits. The mean μTBS values of Constic, Yflow AS, and TNF were 10.649 MPa, 8.170 MPa, and 33.669 MPa, respectively. The study revealed increased Ra and comparable color stability among all tested composite resins after abrasion. However, SARF exhibited lower μTBS compared to conventional using an adhesive system.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Cacalol (C), a sesquiterpene isolated from Psacalium decompositum, has demonstrated anti-inflammatory and antioxidant activities. Its cytotoxic, antiproliferative, and pro-apoptotic effects have been previously shown in an in vitro breast cancer model. A derivative, Cacalol Acetate (CA), shows potential in regulating these processes, which had not been previously reported. This study focused on an in vitro cervical cancer model, assessing CA's anti-proliferative, pro-apoptotic, cytostatic, and anti-migratory activities using the HeLa cell line. The natural anticancer agent I3C was used as a control for comparison. CA demonstrated significant antitumor activities, including inhibiting cell growth, inducing apoptosis, arresting cells in the G2 phase of the cell cycle, and inhibiting cell migration. These effects were notably greater compared to I3C. I3C, while following a similar trend, did not induce Cas-3 expression, suggesting a different apoptotic pathway. Neither CA nor I3C increased p62 and LC3B levels, indicating they do not stimulate autophagy marker expression. Both compounds inhibited HeLa cell migrate on and induced cell cycle arrest. Despite both holding promise as anticancer agents for cervical cancer, CA's lower cytotoxicity and stronger regulation of tumor phenotypes make it a more promising agent compared to I3C.

The rapid expansion of flexible and wearable electronics has necessitated a focus on ensuring their safety and operational reliability. Gel Polymer Electrolytes (GPEs) have become preferred alternatives to traditional liquid electrolytes, offering enhanced safety features and adaptability to the design requirements of flexible lithium-ion batteries. This review provides a comprehensive and critical overview of recent advancements in GPEs technology, highlighting significant improvements in their physicochemical properties, which contribute to superior long-term cycling stability and high-rate capacity compared to traditional organic liquid electrolytes. Special attention is given to the development of smart GPEs endowed with advanced functionalities such as self-protection, thermotolerance, and self-healing properties, which further enhance battery safety and reliability. The review also critically examines the application of GPEs in high-energy cathode materials, including Lithium Nickel Cobalt Manganese (NCM), Lithium Nickel Cobalt Aluminum (NCA), and thermally stable Lithium Iron Phosphate (LiFePO4). Despite the advancements, several challenges in GPE development remain unresolved, such as improving ionic conductivity at low temperatures and ensuring mechanical integrity and interfacial compatibility. The review concludes by outlining future research directions and the remaining technical hurdles, providing valuable insights to guide ongoing and future efforts in the field of GPEs for lithium-ion batteries, with a particular emphasis on applications in high-energy and thermally stable cathodes.

Background: Extra virgin olive oil is a fundamental component of the Mediterranean diet. It contains several molecules that sustain human well-being by modulating cellular metabolism and exerting antioxidant, anti-inflammatory, anti-ageing effects to protect normal tissues and can exert anti-angiogenic, and pro-apoptotic effects on cancer cells. Metabolites found in different parts of the olive tree, including leaves, also possess properties that might help in cancer prevention and promote wellness in aging. Olive mill wastewater (OMWW), a liquid residue produced during olive oil extraction, represents an environmental issue. However, it is enriched in phytochemicals with potential beneficial properties. Dietary supplements based on OMWW can be produced for nutritional supplementation with advantages to the ecology. Purpose: This work aims to measure hematochemical, anthropometric and metabolomic parameters in volunteers assuming an OMWW dietary supplement, OliphenoliaⓇ (OMWW-OL). Methods: The supplementation of OMWW-OL 25 mL twice daily for 30 days was tested on a pilot cohort of volunteers with characteristics close to metabolic syndrome. Hematochemical, anthropometric, and metabolomic parameters were analyzed before the intervention, at 30 days and 30 days after stopping consumption. Results: 29 volunteers were enrolled and 23 completed the study. The participants’ parameters at baseline were measured, and then twice daily at 30 days of treatment and 30 days after assumption discontinuation. Although treatment was with an olive derivative, weight and body mass index instead of increasing slightly decreased, particularly in women. Also, hydration increased, especially in women, while blood pressure, glycemia and insulin decreased. Cholesterol, low-density and high-density lipoproteins and triglycerides were stable while vitamin D levels, alongside calcium, sensibly increased. Albumin also increased and parameters related to sarcopenia displayed promising, although not statistically significant, trends toward positive effects. All the values were in support of an equilibrium with no damaging effects. By mass spectrometry analysis, we also found favorable changes in the vitamin D/histamine and homocysteine/methionine ratios, an increase in a new metabolite of unknown formula, and vitamin D/unknown metabolite ratio. Conclusions: Supplementation of OMWW-OL has no detrimental effects and, although with limited potency of a pilot study, might imply the beneficial modulation of several biological parameters, being potentially valuable for people at risk of metabolic syndrome. Some of these parameters could also be relevant as anti-ageing and in cancer prevention.

One of the main products of the forest, which has the greatest economic impact, is wood. Due to its characteristics, the wood requires certain types of vehicles for transport it. For this reason, the accessibility of the stands with forest roads plays significant role in the efficiency of the wood logging process, which aims to bring the wood from the forest to the harvesting area located, frequently, next to a permanent transport route. The process of wood transport from the forest initially takes place on forest roads and after that on public roads. The technological process of wood transport represents an important stage in this process, and its good organization can have implications on the final price of the wood material. Based on those mentioned above, the paper aims to highlight the factors that can influence productivity in the case of loading wood in forestry trucks and forestry platforms, in different conditions. Thus, the research was carried out in four counties in Romania and addressed the loading of wood in different forestry trucks and platforms, with or without trailers. Following the evaluation of the work phases specific to the process of round wood loading in vehicles of transport, it was found that sometimes a significant importance is given to the working phases that can be carried out before the loading process, as phases of preparation of the wooden material in order to load it. Also, the facilities of the transport vehicles, the assortments of wood material, as well as the experience of the operators are the main factors that can lead to an increase in productivity.

Background: The Victorian era in Great Britain was a historical period that brought about profound changes for humanity. The confluence of various factors fostered the development of numerous scientific disciplines. In the field of health sciences, Florence Nightingale played a central role. Following her training as a nurse and her role as superintendent during the Crimean War, she made decisive contributions to establishing a public health network. Methods: This is a retrospective historical heuristic and hermeneutic study analyzing documentation of Nightingale's contributions to public health from around 1890 to 1900. The historical method was used to collect, classify, and analyze primary and secondary sources relevant to the study's objectives. Results: Nightingale supported the development of the concept of “health at home” by training women to implement healthy measures that contributed to the well-being of families and communities. Through the training and development of a formal “Health Missioners program”, she provided the necessary guidance to improve the health of rural communities across the English countryside. Conclusion: The role of Health Missioners has persisted, as health visitors continue to visit homes in the United Kingdom. Therefore, the contribution of Florence Nightingale to public health is unquestionable. This study was not registered.

Intravaginal drug administration offers several advantages over other administration routes, primarily by bypassing the initial stages of metabolism. Additionally, this route has demonstrated both local and systemic effects. To prevent the disintegration of molecules in the mucous barriers of wet cavities, mucoadhesive polymeric systems can be utilized. In this study, the performance and characteristics of a mucoadhesive film composed of HPMC-PEG 400 containing retinol molecules was determined using various techniques. Scanning Electron Microscopy (SEM) was employed to determine the porous structure of the film. Thermogravimetric Analysis (TGA) was conducted at different temperatures to assess thermal stability. Fourier Transform Infrared Spectroscopy (FTIR) analyzed the functional groups and the intermolecular interactions between the film and the drug. Swelling and weight loss tests indicated that the film disintegrated within 3-4 days. For drug delivery evaluation based on the Higuchi equation, UV-VIS spectroscopy was used. Additionally, the surface wetting properties were assessed through contact angle measurements. The biocompatibility of the system was confirmed using the MTT assay. Finally, adhesion and glide tests demonstrated the film's interaction with porcine uterine tissue. This study shows that the HPMC-PEG 400 film containing retinol molecules interacts effectively with tissue and could be considered a novel tool for treating damaged epithelial tissues.

This study presents a novel approach to understanding evolutionary dynamics through topological analysis of genotypic structures. We model the genome of a simple organism as a topological torus undergoing mutations at a constant rate of 1% per generation. Employing persistent homology and other topological data analysis techniques, we investigate how these mutations influence the overall topology of the genomic structure over time. Our simulations reveal that specific critical mutations lead to significant changes in the homotopic and homologic properties of the torus. We interpret these topological shifts as potential markers for the formation of new subspecies. By identifying the precise points of topological "breaks" within the toroidal genomic representation, our model provides a quantitative framework for observing the incremental transformations that underpin major evolutionary developments. The results offer new insights into the thresholds of speciation and adaptation, demonstrating how gradual genetic changes can accumulate to produce qualitative shifts in organismal traits. This approach bridges the gap between microscopic genetic mutations and macroscopic evolutionary outcomes, potentially revolutionizing our understanding of evolutionary processes. Our findings have implications for various fields, including theoretical biology, genetic engineering, and conservation biology. The model provides a novel perspective on genetic resilience and adaptability, offering a foundation for future research on the relationship between genomic topology and evolutionary trajectories. It also emphasizes the innovative nature of the research and its potential impact on multiple fields of study.

Despite the allergen labeling of peanuts, reducing peanut allergenicity through material selection and breeding may provide an avenue to reduce the severity of allergy due to consumption of foods containing peanuts. This study’s objective is to select peanut lines (cultivar/variety) with lower potent allergenic peptides. One hundred and twenty-two peanut lines (harvested in 2015, New Mexico State, USA.), including 97 lines from the Core USDA- Griffin collections were used for SDS-PAGE analysis in order to find low allergen peanut lines. Eleven peanut lines (Coded MS-1~MS-11) were identified as having lower allergen (Ara h 1, Ara h 2 and Ara h 3) levels and were re-planted in 2016 for further analysis. One line named MS-7 was selected for lower Ara h 1 (8.5-9.5% of total protein) and Ara h 2 (4.2-6.6% of total protein) content in 2015 and 2016. Two-dimensional (2-D) gel electrophoresis (isoelectric focusing plus SDS-PAGE) was conducted to compare the protein (allergens) distributions of MS-7 and check line (MS-9). The 2-D results supported the SDS-PAGE analysis that MS-7 had lower quantities of Ara h 1 and Ara h 2, the two major peanut allergens. The identified peanut line (MS-7) has potential for processing into lower allergenic peanut food products.

The Third U.S. National Marine Environmental DNA Workshop on June 2–5, 2024 brought together researchers, practitioners, and policymakers to overview and discuss: (1) environmental (e)DNA – defined as “DNA in the environment” – as a strategic U.S. national priority, (2) eDNA tool readiness and approaches to support decision-making, (3) emerging eDNA technologies, and (4) plans for implementation and adoption for environmental monitoring and ecosystem assessment “from microbes through whales”. Uses and applications of eDNA have been revolutionizing exploration, measurement, and monitoring of biodiversity across ecosystems, including the marine and freshwater aquatic environments emphasized in the Workshop, as well as terrestrial and aerial systems. The Workshop featured the launch of the new U.S. National Aquatic Environmental DNA Strategy from the White House Office of Science and Technology Policy (2024), with aquatic defined as freshwater to ocean waters, across all salinities; the Strategy was developed using outputs and a taskforce from the 2022 Second Workshop. The 2.5-day Third Workshop included speaker presentations, panel discussions, and networking on eDNA tools, applications, use, upscaling, and their future. The Workshop led into Capitol Hill Ocean Week (CHOW) events (June 5–6, 2024), during World Ocean Week. Note that this summary paper represents the author’s take-away view and interpretation, and not necessarily the overall views or consensus of the U.S. Government, Smithsonian Institution, workshop organizers, or speakers.

Using polymethylmethacrylate (PMMA) bone cement is widespread in orthopedic surgeries for implant fixation and as a carrier for antibiotic delivery to prevent and treat infections. This review comprehensively evaluates in vitro studies investigating the antibiotic elution profiles and mechanical properties of PMMA bone cement. We explore the kinetics of antibiotic release, factors influencing elution efficiency, and the impact of various antibiotics on the mechanical properties of PMMA composites. At the same time, we examine how the inclusion of antibiotics affects the mechanical integrity of PMMA, including parameters such as compressive strength, tensile strength, and fatigue resistance. Through a detailed analysis of these studies, this review aims to provide insights into optimizing PMMA bone cement formulations for enhanced therapeutic efficacy and structural performance.