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.

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 < 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 > 0.05). Up to the passage 9, CEF underwent adipogenic trans-differentiation. As passages increased, lipid accumulation and adipocyte size decreased significantly (p < 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<0.05) daily feed intake, backfat thickness at the first rib, P2 backfat thickness, fat area, and fat to meat ratio and decreased (P<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 < 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.

Pancreatic cancer is a serious and aggressive type of cancer that affects the digestive system and has a low chance of survival. Although traditional treatment methods have achieved some efficacy, the survival rate of patients remains low. Therefore, exploring novel treatment strategies is important. This article looks at the research done on bioactive compounds and plant extracts for treating pancreatic cancer. Bioactive compounds, such as naringenin and ziyuglycoside II, have significant anticancer activity and exert anti-pancreatic-cancer effects by inducing cell apoptosis, inhibiting the cell cycle, and blocking signaling pathways. Plant extracts, such as epigallocatechin-3-gallate and resveratrol, also demonstrate good anti-pancreatic cancer activity and inhibit tumor growth and metastasis. Additionally, the combined application of bioactive compounds and plant extracts may result in improved therapeutic effects. This article aims to provide a theoretical basis for the application of bioactive compounds and plant extracts in the treatment of pancreatic cancer and to help guide future medical research and practice.

Graphene nanoplatelets (UGZ-1004) are advancing as a promising biomaterial for regenerative medicine. This study provides a detailed assessment of UGZ-1004, emphasizing its physical properties, cytotoxicity, intracellular interactions, and particularly its effects on mesenchymal stem cells (MSCs). UGZ-1004 was characterized to have lateral sizes and layer counts in line with ISO standards and exhibited high carbon purity (0.08%). Cytotoxicity evaluations demonstrated that UGZ-1004 is non-toxic to various cell lines, including fibroblast 3T3, epithelial kidney VERO, microglia BV-2, and MSCs, in accordance with ISO-10993-5/2020/2023 guidelines. The study focused on MSCs, revealing that UGZ-1004 supports their self-renewal and proliferation. MSCs exposed to UGZ-1004 maintained their characteristic surface markers and proliferation rates. Importantly, UGZ-1004 promoted significant upregulation of genes crucial for cell cycle regulation and DNA repair, such as CDK1, CDK2, and MDM2. This gene expression profile suggests that UGZ-1004 enhances MSC self-renewal capabilities, ensuring robust cellular function and longevity. Moreover, UGZ-1004 exposure led to the downregulation of genes associated with tumor development, including CCND1 and TFDP1, mitigating potential tumorigenic risks. These findings underscore the potential of UGZ-1004 to not only bolster MSC proliferation but also enhance their self-renewal processes, which are critical for effective regenerative therapies. The study highlights the need for continued research into the long-term impacts of graphene nanoplatelets and their application in MSC-based regenerative medicine.

Background: Monogenic Alzheimer's disease (AD) has severe health and socioeconomic repercussions. Its rarest cause are presenilin 2 (PSEN2) gene mutations. We present two new cases with presumed PSEN2-AD, with unusual clinical and neuroimaging findings in order to provide more information on the pathophysiology and semiology of these patients. Methods: Women aged 69 and 62 years at clinical onset, marked by prominent behavioral and language dysfunction, progressing to severe dementia within three years. Neuroimaging, laboratory study, genetic testing. In addition, a systematic review of the PSEN2-AD were performed. Results: Neuroimaging revealed pronounced frontal white matter hyperintensities (WMH) and frontotemporal atrophy/hypometabolism. The genetic study unveiled PSEN2 variants: c.772G>A (p.Ala258Thr) and c.1073-2_1073-1del. Both cerebrospinal fluid (CSF) and experimental blood biomarkers shouldered AD etiology. Conclusions: Prominent behavioral and language dysfunction suggesting frontotemporal dementia (FTD) may be underestimated in the literature as a clinical picture in PSEN2 mutations. Thus, it may be reasonable to include PSEN2 in genetic panels when suspecting FTDL. PSEN2 mutations may cause striking WMH, arguably related with myelin disruption induced by amyloid accumulation.

The Aether Physics Model (APM) presents a radical reinterpretation of fundamental physics, offering potential solutions to long-standing problems in Quantum Mechanics and General Relativity. This paper explores the core concepts and equations of the APM, demonstrating how they provide a unified framework for understanding the nature of space, time, matter, and fundamental forces. We examine the implications of the APM's quantized Aether structure, the role of the Singularity and Gforce, and the reinterpretation of fundamental constants and forces. The model's predictions regarding dark matter, neutron content in stable matter, and the unification of forces are discussed, along with potential experimental tests. Additionally, we introduce the loxodrome concept and toroidal particle topology as central elements in explaining fundamental particles and forces. While speculative, the APM offers a thought-provoking alternative to standard physics models and warrants further investigation.

Demographic studies have revealed a strong association between exposure to high ambient temperatures during pregnancy and increased risks of preterm birth (PTB). The mechanism underlying this association is unclear, but it is plausible that altered placental function may contribute. In this study, we conducted differential gene expression analysis, gene set enrichment analysis (GSEA), and gene ontology (GO) analysis on bulk RNA-seq data from human placentas delivered at term and preterm during the warmer months compared to placentas delivered at term and preterm during the colder months in the UK. We detected 48 differentially expressed genes in preterm placentas delivered during the warmer months compared to preterm placentas delivered during the colder months, the majority of which were inflammatory cytokines and chemokines, including SERPINA1, IL1B, CCL3, CCL3L3, CCL4, CCL4L2, CCL20, and CXCL8. The GSEA positively enriched 17 signalling pathways, including the NF-κB, IL17, toll-like receptor, and chemokine signalling pathways, in warm-exposed preterm placentas, which were not observed in warm-exposed term placentas. The GO analysis revealed several biological processes, including neutrophil, granulocyte, monocyte, and lymphocyte chemotaxis, as well as inflammatory and humoral immune responses in warm-exposed preterm placentas, but not in warm-exposed term placentas. We conclude that maternal exposure to warm environmental temperatures during pregnancy alters the placental transcriptome towards inflammation and immune regulation, potentially leading to PTB.

The rise of antibiotic-resistant strains demands new alternatives in antibacterial treatments. Bacteriophages, with their precise host specificity and ability to target and eliminate bacteria safely, present a valuable option. Meanwhile, hydrogels, known for their excellent biodegradability and biocompatibility, serve as ideal carriers for bacteriophages. The combination of bacteriophages and hydrogels ensures heightened phage activity, concentration, controlled release, and strong antibacterial properties, making it a promising avenue for antibacterial treatment. This article provides a comprehensive review of different cross-linking methods for phage hydrogels and focuses on their application in treating infections caused by various drug-resistant bacteria.

Agrobacterium tumefaciens (A. tumefaciens) is a plant pathogenic bacterium that causes crown gall disease, leading to significant economic losses in various agriculturally important crops, including apple, pear, peach, and almond. The difficulty of controlling A. tumefaciens with conventional pesticides underscores the need for alternative antibacterial agents such as bacteriophages. In this study, a novel lytic bacteriophage, named Agrobacterium phage PAT1 (PAT1), with high lysis potential against A. tumefaciens, was isolated from wastewater. The interaction between PAT1 and A. tumefaciens cells, investigated using Transmission electron microscopy, revealed that PAT1 efficiently adsorb, infect, and replicate on A. tumefaciens in a very short time period (i.e., ≤30 min for a complete infectious cycle). Furthermore, the turbidity assay showed that PAT1 (MOI = 1) exerted a significant inhibitory effect on A. tumefaciens for 48 hours, resulting in an 82% reduction in bacterial growth. Additionally, stability tests showed that PAT1 was highly resistant to a broad range of pH (4-10) and temperatures (4-60°C). Bioinformatics analyses of the genomic sequence suggested that PAT1 is a new phage closely related to Agrobacterium phages of the genus Atuphduovirus within the family Autographiviridae. The genome size was 45,040 base pairs with a G+C content of 54.5%, consisting of 54 coding sequences (CDS), of which the functions of 22 CDS were predicted, including two endolysins genes which could be used as antimicrobials against A. tumefaciens. Additionally, no lysogenic mediated genes or genes encoding virulence factors, antibiotic resistance, or toxins were detected in PAT1 genome. Overall, PAT1 demonstrated suitability as a potential biocontrol agent for combating A. tumefaciens infections, expanding the limited catalog of such lytic A. tumefaciens phages. However, its efficacy in controlling crown gall disease in planta remains to be evaluated.

A topological representation theory of chiral spin liquid is proposed to unify the integral and fractional quantum Hall fluid based on hyperbolic geometry, knot lattice and Thurston's train track theory. The integral and fractional Hall resistivity obeys an exact unified equation, $R_{xy} = (h/e^2)B_{e}$, $B_{e} = (n+\nu)^{-1}$, with respect to the bulk energy gap ${\Delta}E = {\hbar{e}B_{e}}/{Mc}$. The Wen-Zee matrix formulation of topological fluid for quantum Hall effect is constructed by topological surgery and train track. The chirality of spin liquid is spontaneously distinguished by Jones polynomial. The integral Chern number for Hall conductance is fractionalized by generalizing Thurston's train track to folding laminations in three dimensions, which spontaneously bring fractional quantum Hall fluid and anyons into three dimensions and provided an theoretical explanation on the competing fractional quantum Hall states. The many body system of interacting fermions or bosons are mapped into many interacting liquid droplets that interwind into knot lattice, which provide an effective topological representation for superfluid and superconductor, the strange metal state in superconductor is explained by topological dislocation and topological surgery. The Kauffman decomposition rule in knot theory is extended to describe the topological relations between different two dimensional manifolds, which further reveals the non-trivial relationship between the partition functions of pairing fermions and free electrons. The minimal energy state is the most stable topological state, even thought it maybe shares the same topological number with the excited states. The topological representation theory predicts a circular motion of electrons in hyperbolic space, that is implementable and testable by inhomogeneous magnetic field in three dimensions. The folding lamination representation of topological quantum fluid provides an promising implementation of string theory in high energy physics.

Recognizing the critical impact of environmental factors on individuals, this study explores the relationship between environmental indoor pollutants (PM1, PM2.5, PM10, and CO₂) and students' basic emotional responses based on Ekman’s categorization. Conducted in a secondary school in Spain, it integrates IoT and image processing technologies to monitor air quality and emotions in real-time. Participants included 76 secondary school students and three teachers, with data collected over two months. The results showed significant correlations between PM levels and negative emotions such as anger and disgust, while CO₂ levels were associated with both negative and positive emotions, including happiness. Regression models demonstrated that environmental variables significantly predict basic emotions, highlighting the influence of indoor air quality. These findings emphasize the need for proactive air quality management in educational settings to enhance learning environments and support students' emotional well-being.

Neurodevelopmental disorders are characterised by an amalgam of genetic and epigenetic faults implicating neuronal protein-related loss-of-function and gain-of-function respectively, hence their inclusion into the category of complex diseases. Neurodevelopmental disorders are regarded as autism spectrum disorder due to this reason; that the risk factors and phenotype constitute a spectrum of faults and protein overactivity. One example of an epigenetic factor leading to the onset of neurodevelopmental delays constitutes a set of immune response-based dysregulations, as well as the excessive growth of the adaptive immune memory of the foetus or the baby following significant infectious disease during pregnancy, as well as in babies aged 0-2, given the existence of profound links between developmental immunity and developmental neurology. Given that genetic information very likely represents a form of energy, the intake of excessive pathogen-related information may transiently overload the adaptive immune memory similarly to the manner functional pathogens do whilst inducing significant illness, and if events as such occur during important stages of neuro-immunological development, then there could often be irreversible effects upon the rate of development in neurological networks that normally have a major importance in the modulation of the related cognitive and behavioural phenotype. The full extent of evidence may only be obtained via a thorough study of the applications of physical laws into biology and medicine, given the foundational role of the physical matter in the development and maintenance of life. A common misconception is that neurodevelopmental delays are characterised solely by an accumulation of protein loss-of-function incidences in the central nervous system area, rather than a disruption of neuronal region developmental rates. For example, an overexpression of neuronal proteins related to cognition factors that is accompanied by an underexpression of proteins related to social behaviour is phenotypically manifested in people with sharper rational thinking and poorer communication skills, with an impact on the abilities of decision-making as well, and this tends to be regarded as a classical example of the clinical manifestation of neurodevelopmental delays. More severe forms of autism spectrum disorder tend to implicate a more generalistic impact upon the developmental rates of key human behaviours, including those related with the development and maintenance of social and intimate relationships. Likewise, more severe implications upon regular developmental rates tend to bring a major impact upon the healthy function of related functions. As a result, lower functioning forms of neurodevelopmental delays bring fresh concerns with regards to a possible uncanny increase of incidences of deviated sexuality during years of adulthood, and in the worst cases, such deviations may lead to the planning and development of criminal activity, particularly in individuals who are or become prone to breaking the moral code that established the civilised society. What holds the concerns valid is the exponential increase in the number of lower functioning autism cases throughout the world and the major signs that such an increase will continue with a full force. One major solution to this potential future problem would be a much higher investment into awareness of the exact genetic and environmental factors that directly or indirectly result in the onset of lower-functioning autism and of the current research efforts to develop the matching support for people found in situations as such. The most important aim of future research with regards to such a scenario would be a separation of disease and disability with choices made to step into more severe forms of disease and into areas that are outside of the established moral circle.

This study aimed to describe and distinguish shot characteristics between set winning and losing pairs in high-level male padel players from Finland. Between 2022 and 2023, we analyzed 4,469 points across 38 matches, examining factors such as match type, set outcome, effectiveness of the last shot, generator of forced error, and shot type. Results showed that set-winning players produced more winners (CSR = 7.7; CSR = 6.8) and committed fewer forced (CSR = 4.2; CSR = 2.8) and unforced errors (CSR = 4.0; CSR = 4.3) compared to set losing players, both in pressure training and competition matches. In addition, irrespective of the set outcome, these players achieved more winners and generated more forced errors with the smash, bandeja, forehand volley, and backhand volley. Nevertheless, a significant number of errors (both forced and unforced) are committed with the bandeja and volley (forehand and backhand). Furthermore, notable errors (forced and unforced) are observed in shots following one bounce and without a wall rebound, particularly in the forehand, backhand, and return. In conclusion, the ability to produce winners while minimizing forced and unforced errors proves to be crucial for securing sets in high-level men’s padel.

Light is dispersive in gravitational field. It results in that, under the condition of strong gravitational field, the observed numbers, size, distance and spectrogram of a celestial object is different from the real ones. Therefore, the observed jets of the Sgr A* and M87 need be understood further with the orbit of the stars around them. And, the observed orbits of the S-stars around the Sgr A* is different from the real ones. It implies that the observed optical images of the distant celestial body with strong gravitational field need be further understood with other observations and physics laws to accurately and precisely know the real physical configuration of it.

The aim of this study was to evaluate the quality of legends associated with diagnostic images in the published oral and maxillofacial radiology literature using a novel rating scale. Images and their corresponding legends were randomly selected from published manuscripts over the last ten years in the Oral Radiology journals, namely Dentomaxillofacial Radiology, Imaging Science in Dentistry, Oral Radiology, and Oral Surgery Oral Medicine Oral Pathology Oral Radiology. An Image Quality Rating Scale (IQRS) was introduced to assess the quality of the legends associated with images. A program was developed for the rating scale form using Google Apps Script API to gather and analyze the data. The rating scale ranged from 1 to 5, with 5 as the highest rating. The highest average IQRS rating for one journal was 3.04. The overall IQRS rating average across all four journals was 2.87, which is 2.13 rating scores lower than the ideal score of 5. There is room for improvement in the legends that accompany diagnostic images and figures in the oral and maxillofacial radiology literature. A proper legend provides an excellent diagnostic teaching opportunity for the reader and enhances the quality of a publication.

Cardiovascular disease is a major global health concern, with early detection being critical. This study assesses the effectiveness of the portable ECG device, based on Internet of Medical Things (IoMT) technology, for remote cardiovascular monitoring during daily activities. We conducted a clinical trial involving 2,000 participants who wore the HiCardi device while engaging in hiking activities. The device monitored their ECG, heart rate, respiration, and body temperature in real-time. If an abnormal signal was detected while a physician was remotely monitoring the ECG at the IoMT monitoring center, he notified the clinical research coordinator (CRC) at the empirical research site, and the CRC advised the participant to visit a hospital. Follow-up calls were made to determine compliance and outcomes. Of the 2,000 participants, 318 showed abnormal signals, and 182 were advised to visit a hospital. Follow-up revealed that 139 (76.37%) responded, and 30 (21.58% of those who responded) sought further medical examination. Most visits (80.00%) occurred within one month. Diagnostic approaches included ECG (56.67%), ECG and ultrasound (20.00%), ultrasound alone (16.67%), ECG and X-ray (3.33%), and general treatment (3.33%). Seven participants (23.33% of those who visited) were diagnosed with cardiovascular disease, including conditions such as arrhythmia, atrial fibrillation, and stent requirements. The portable ECG device using the patch-type electrocardiograph detected abnormal cardiovascular signals, leading to timely diagnoses and interventions, demonstrating its potential for broad application in preventative health care.

The sub-economic dynamics studies the relationship between people's economic impulses and market behavior. Using Bourbaki structuralism as a philosophical consideration and quantum chromodynamics as a conceptual and modeling method, sub-economic dynamics theory is constructed. In this theory, we discuss the deep structure of the free market and analyze the errors in Mises' anthropological arguments. Sub-economic dynamics is the psychological basis of market dynamics. Guided by the preface, this paper is divided into six sections: (1) The Free Market and Impulse Flavor Charge, including topics such as the fate of the free market, the food chain and psychology, and the flavor charge of economic impulses; (2) The Nature of Economic Impulses, including topics such as the flavor and generation of impulses and counter-impulses, and the bound state of impulses and fractional market charges; (3) Freud's Color Charge Space and Spin, including topics such as the Pauli exclusion rule and color charge, and Freud's personality theory; (4) Consciousness and Gluons; (5) Gauge Transformations and SU(3) Symmetry Group; and (6) General Discussion.

In this work, several random Boolean networks (RBN) are generated and analyzed from two characteristics: their time evolution diagram and their transition diagram. To do this, its randomness is estimated using three measures, of which Algorithmic Complexity is the only one capable of both a) revealing transitions towards the chaotic regime, and b) disclosing the algorithmic contribution of certain states to the transition diagram and their relationship with the order they occupy in the temporal evolution of the respective RBN. The results obtained from both types of analysis are useful for the introduction of both Algorithmic Complexity and Perturbation Analysis in the context of Boolean networks, and their potential applications in regulatory network models.

In this paper, we describe the synthesis and characterization of iridium (III) half sandwich complexes of stoichiometry [Cp+IrCl2L] with Cp = 5-C5 EtMe4; L = alanine anhydride (I), ortho- (II) and para-aminophenol (III). For comparative purposes, the ionic complex [Cp*IrCl(o-phen)](PF6); Cp* = (5-C5Me5) (IV) has been also synthesized and characterized. All the isolated complexes have been characterised by C, H and N elemental analysis; infrared and 1H nuclear magnetic resonance spectroscopies; 1H-1H COSY; mass spectrometry (ESI/TOF), thermogravimetry and, in the case of (IV), by conductivity measurements. The cytotoxic behaviour of the isolated complexes was studied against HeLa and complexes (III) and (IV) were found to have an IC50 close to 160-170 m, quite close to the IC50 value of cisplatin which was found to be 134,7 m, indicating that they are good cytotoxic agents. However, complexes (I) and (II) showed IC50 values above 250 m indicating their low cytotoxicity.

All-inorganic perovskite materials are promising in optoelectronics but their morphology is a key parameter for achieving high device efficiency. We prepared CsPbBr3 perovskite microcrystals with different shape, grown directly on planar substrate by conventional drop casting. We observed the formation of CsPbBr3 microcubes on bare indium tin oxide (ITO) coated glass. Interestingly, with the same technique CsPbBr3 microrods were obtained on (3-Aminopropyl) triethoxysilane (APTES) modified ITO-glass, which we ascribe to modification of formation kinetics. The obtained micro-crystals exhibit orthorhombic structure. Green photoluminescence (PL) emission is revealed from the CsPbBr3 microrods. Contact angle measurements, Fourier-transform infrared and PL spectroscopies confirmed that APTES linked successfully to the ITO-glass substrate. We propose a qualitative mechanism to explain the anisotropic growth. The microrods exhibited improved PL and slower PL lifetime compared to the microcubes, likely due to diminished occurrence of defects. This work demonstrates the importance of the substrate surface to control the growth of perovskite single crystals and to boost the radiative recombination in view of high performance optoelectronic devices.

Background: Resistant hypertension (HTN) is associated with high risk of cardiovascular complications. Our study aimed to assess prevalence, characteristics and treatment of patients with resistant HTN; Methods: We screened 4340 consecutive cardiovascular patients and identified 3762 with HTN. Of them 128 fulfilled criteria for resistant HTN and were included in our study. We matched these patients to 128 hypertensive patients with controlled HTN; Results: Resistant HTN patients were 3.4% of all hypertensives. Most of these patients (67.2%) were at high or very high cardiovascular risk compared to controlled HTN patients (40.6%), p&lt;0001. Resistant HTN patients had more frequently concomitant chronic kidney disease (CKD) (60.9%), overweight/obesity (52.3%), dyslipidemias (35.2%), smoking (27.3%) and diabetes (21.9%) compared to controlled HTN patients (37.5%, 29.7%, 28.1%, 14.1% and 7.8% respectively), p&lt;0.001. Regression analysis showed strongest association of resistant HTN with CKD (OR 6.64), stage III HTN (OR 3.07) and obesity/overweight (OR 2.60). In contrast, single-pill combinations (SPCs) were associated with lower likelihood of uncontrolled HTN (OR 0.58); Conclusions: Resistant HTN represented a small proportion of all hypertensives in our study, but it was characterized by high/very high cardiovascular risk. Optimized therapy including increased usage of SPCs could improve blood pressure control and long-term prognosis of these patients.

This literature review aims to gain a deeper understanding of the anatomy behind the jaw strength of Tyrannosaurus rex and analyze how these features contribute to its predatory behavior. This review will examine various studies and fossil excavations, exploring ideas such as the bite force of T. rex and its variations across different life stages. This will be obtained from numerous biomechanical models of both juvenile and adult Tyrannosaurus rex, as well as reference animals and dinosaurs for comparison. To provide additional information behind T. rex’s hunting techniques, we will also discuss the fauna of herbivorous dinosaurs that were part of T. rex’s diet. Furthermore, we will explore how mandibular stress concentration can vary between ages, a crucial topic in determining what T. rex could consume at certain stages of its life. Finally, we obtain a well-evidenced analysis of the various aspects of Tyrannosaurus rex’s hunting strategies throughout its lifetime.

The cellular behavior of Voronoi tessellation has generated interest due to its applicability in various fields and its notable structural properties. Controlling factors such as the gradient of the cells, the position of seed points and the thickness of the arms allows for adjusting rigidity and flexibility according to specific needs. This article analyzes the state of the art of this technique, exploring its modification for applications in engineering and design, complemented with information on natural structural properties. This comprehensive analysis provides a complete overview of Voronoi tessellation and its potential in engineering and design, categorizing methodologies according to selected processing methods and highlighting techniques for altering structural behavior. Additionally, it emphasizes the integration of biomimetic approaches, connecting nature with technology to foster continuous innovation. Finally, the article addresses encountered limitations, offering future perspectives for the cellular technique and highlights the complexity of reproducibility due to reserved or generalized steps, despite the significant diversity in implemented techniques.

Background: Glutathione and its related enzymes constitute one of the most important antioxidant defense mechanisms against oxidative stress and cancer formation in the body. Bladder cancer is the second most common urological malignancy after prostate cancer. Oxidative stress plays a significant role in the development and prognosis of bladder cancer. The aim of this study was to examine the effect of glutathione on the prognosis of non-muscle-invasive bladder cancer. Methods: The 98 patients with bladder tumors were those with T1G3 pathology who had undergone intravesical Bacillus Calmette-Guérin therapy, while the 30 controls were healthy individuals with no history of transitional cell carcinoma of the bladder. The 128 participants were divided into four groups: Group 1 comprised 41 patients who did not experience recurrence during follow-up, Group 2 included 28 patients who had recurrent tumors, Group 3 consisted of 29 patients who progressed to muscle-invasive stages, and Group 4 was composed of 30 healthy volunteers. Blood samples were collected from all participants. Glutathione levels were measured, and statistical analysis were performed. Results: There was a statistically significant difference in reduced glutathione levels among the groups (p < 0.001), attributed to Group 4 exhibiting higher reduced glutathione levels compared to Groups 1, 2, and 3 (p < 0.001). No significant differences were observed in reduced glutathione levels between Groups 1 and 2, Groups 1 and 3, or Groups 2 and 3 (p > 0.999). Total glutathione levels varied significantly among the groups (p < 0.001), with Group 4 having higher levels than Groups 1, 2, and 3 (p < 0.001). However, there were no significant differences between Groups 1 and 2, Groups 1 and 3, or Groups 2 and 3 in terms of total glutathione levels (p = 0.473, p = 0.747, and p > 0.999, respectively). Regarding oxidized glutathione levels, a significant difference was observed (p < 0.001), with Group 4 showing lower levels than the remaining three groups (p < 0.001). No significant differences were found between Groups 1 and 2, Groups 1 and 3, or Groups 2 and 3 in relation to oxidized glutathione levels (p > 0.999, p = 0.171, and p > 0.999, respectively). Conclusions: The current study revealed that glutathione is a factor influencing the development of new bladder cancer but did not affect its prognosis. Nevertheless, we recommend that future studies with larger bladder cancer patient cohorts should be conducted to comprehensively determine the effect of glutathione on the prognosis of bladder cancer.

An over-active renin-angiotensin system (RAS) is characterized by elevated angiotensin II (Ang II). While Ang II can promote metabolic and mitochondrial dysfunction in tissues, little is known about its role in the gastrointestinal system (GI). Here, we treated rat primary colonic epithelial cells to Ang II (1-5000 nM) to better define its role in the GI. We hypothesized that Ang II would negatively affect mitochondrial bioenergetics as these organelles express Ang II receptors. Ang II increased cellular ATP production but reduced mitochondrial membrane potential (MMP) of colonocytes. However, cells maintained mitochondrial oxidative phosphorylation and glycolysis with treatment, reflecting metabolic compensation with impaired MMP. To determine whether lipid dysregulation was evident, untargeted lipidomics were conducted. 1949 lipids were detected in colonocytes spanning 55 distinct (sub)classes. Ang II (1 nM) altered the abundance of some sphingosines [So(d16:1)], ceramides [Cer-AP(t18:0/24:0)], and phosphatidylcholines [OxPC(16:0_20:5(2O)], while 100 nM Ang II altered some triglycerides and phosphatidylserines [PS(19:0_22:1). Ang II did not alter the relative expression of several enzymes in lipid metabolism; however, expression of pyruvate dehydrogenase kinase 2 (PDK2) was increased and PDK2 can be protective against dyslipidemia. This study is the first to investigate the role of Ang II on colonic epithelial cell metabolism.

Urinary incontinence after Radical prostatectomy (RALRP) has been associated with older age, longer operative time, higher BMI, short membranous urethral length and preoperative erectile function. We sought to assess the association between the neuromuscular characteristics and postoperative urinary incontinence. Methods: RALRP specimens from 29 men who underwent bilateral nerve sparing were reanalyzed. Urinary incontinence was evaluated using the International Consultation on Questionnaire-Short Form (ICIQ-SF) at 6 weeks post surgery and last follow-up. Linear and logistic regression analyses were performed to assess neuromuscular characteristics and incontinence. Results: At a median follow-up of 11 months (IQR 9-12), 11 patients (38%) reported on severe incontinence (>12 ICIQ-SF score). Median number of peripheral nerves observed at the base and apex of the specimens were 52 (IQR 13-139) and 59 (IQR: 28-129), respectively. Ganglia were present in 19 patients (65%) at the base and 12 patients (41%) at the apex. Additionally, the median proportional area of detrusor smooth muscle fibers at the base was 0.54 (IQR 0.31-1), while the median proportional area of striated muscle fibers at the apex was 0.13 (IQR 0.08-0.24). No statistical significant associations were found. Conclusion: Histologic neuromuscular characteristics were not associated with postoperative urinary incontinence. Enhanced intraoperative evaluation and larger scale studies may prove useful for prediction of post prostatectomy incontinence.

The Antarctic photopsychrophile, Chlamydomonas priscuii UWO241 is adapted to extreme environmental conditions, including permanent low temperatures, high salt and shade. During long-term exposure to this extreme habitat, UWO241 appears to have lost several short-term mechanisms in favor of constitutive protection against environmental stress. This study investigated physiological and growth responses of UWO241 to high light conditions, evaluating the impacts of long-term acclimation to high light, low temperature, and high salinity on its ability to manage short-term photoinhibition. We found that UWO241 significantly increased its growth rate and photosynthetic activity at growth irradiances far exceeding native light conditions. Furthermore, UWO241 exhibited robust protection against short-term photoinhibition, particularly in photosystem I. Last, pre-acclimation to high light or low temperatures, but not high salinity, enhanced photoinhibition tolerance. These findings extend our understanding for stress tolerance in extremophilic algae. In the past 2 decades climate change-related increasing glacial stream flow has perturbed long-term stable conditions: in the form of has been associated with lake level rise, thinning of ice covers, and expansion of ice-free perimeters. Our findings have implications on phytoplankton survival and response to change scenarios in the light-limited environment of Antarctic ice-covered lakes.

This study investigates the energy profile of a regional hospital in North America using an ASHRAE Level 2 Energy Audit. The audit aimed to assess the efficiency of existing systems, identify areas for improvement, and recommend cost-effective measures to reduce energy consumption and environmental impact. The analysis revealed a well-maintained heating system with efficient boilers. However, a critical concern emerged regarding operational risks due to the lack of redundancy in the cooling system. To address this vulnerability, the study recommends installing an air-cooled chiller for increased operational resilience. The economic feasibility of proposed improvements was evaluated, highlighting the balance between initial investment and long-term savings in energy costs and reduced greenhouse gas emissions. The findings contribute to the discourse on sustainable healthcare practices, emphasizing the importance of energy audits, strategic planning, and redundancy measures for optimized performance and environmental responsibility in hospitals.

It was aimed evaluate the nutritive value of three foods (Cecropia sp., Pterodon sp., and Inga sp.), for sloths (Bradypus variegatus), based on in vitro gas production. After a 14-day adaptation period to these foods, approximately 500g of gastric contents were collected from three female sloths, processed, and incubated with food samples to evaluate digestibility and in vitro degradation kinetics. The neutral detergent fiber (NDFcp) was greater (P&lt;0,05) in the leaves of Cecropia sp. The non-fibrous carbohydrate contents were greater in Pterodon sp. The greatest cellulose content was found in the leaves of C. pachystachya, as well as lowest value for hemicellulose. There were differences in the in vitro digestibility of crude protein (P&lt;0.05), higher for Inga sp. In terms of kinetic parameters, Pterodon sp. demonstrated higher production of total gases (Vt) and digestion rates of fibrous carbohydrates (kdNFC) (P&lt;0.05), possibly related to the lower NDF content and higher values of soluble carbohydrates, which favored fermentative processes. The leaves of Pterodon sp. and Inga sp. demonstrated potential for feeding B. variegatus. Feeding B. variegatus with Cecropia sp., due to the NDF content, can cause negative effects on dry matter consumption.

The study of Internet of Vehicle (IoV) based on Fog Computing (FC) and Artificial Intelligent (AI) has attracted more and more attention. However, there are still many problems require to investigate such as time-critical, scalability, load-balancing, energy consumption, and so on. Focusing on these problems, we proposed an AI-based Vehicle-to-Everything (V2X) model for tasks and resource offloading model for IoVs network, which ensures reliable low-latency communication efficient tasks offloading in IoV network by using Software Defined Vehicular based FC (SDV-F) architecture. To fit to time-critical data transmission task distribution, the proposed model reduces unnecessary task allocation at the fog computing layer by proposing an AI-based task-allocation algorithm in IoV layer to implement task allocation of each vehicle. By applying AI technologies of Reinforcement Learning (RL), Markov decision process, and Deep Learning (DL), the proposed model intelligently makes decision on maximizing resource utilization at the fog layer, and minimizing the average end-to-end delay of time-critical IoV applications. The experiment demonstrates the proposed model can efficiently distribute the fog layer tasks while minimizing the delay.

Blockages in sewers and drains often result in overflows and flooding that cause significant environmental pollution and public health risks particularly in hospitals where the consequences can be catastrophic. Due to their low “visibility”, sewers and drains are inherently difficult to monitor and maintain, resulting in a reactive management approach whereby maintenance or repair is carried out only after a system failure has occurred. This study investigates the application of the reflected wave technique, a unique sonar-like monitoring system, capable of identifying changes to the geometry of closed-pipe-conduits, as a means of active system monitoring to enable maintenance to be conducted in a pro-active basis. An experimental setup was developed to simulate a horizontal drain using standard pipework of 100 mm diameter and 70 m length. Blockages representing 30% and 75% coverage of the drain’s cross-sectional area, with lengths from 30 mm to 3000 mm, were added to the drain. A sinusoidal air pressure wave of 10 Hz was applied and the resultant system pressure response recorded. All but the two smallest blockages (30% with 30 mm length and 30% with 100 mm length) were detected and located with good accuracy. The reflected wave technique could provide a novel and non-invasive method for blockage detection and overall system monitoring for sewers and drains.

In the realm of molecular science, intricate relationships between molecular structures and their biomedical and pharmacological characteristics have been revealed through empirical experiments. This exploration hinges on the application of numerical descriptors, known as Topological Indices, which illuminate the inherent properties of diverse molecular structures. With particular significance in the medical and pharmaceutical domains, these indices facilitate the prediction of biological features for new chemical compounds and drugs by quantifying weighted entropies. In the context of this paper, we delve into the concept of graph entropy, weaving it intricately with the topological properties of the crystalline framework of the copper oxide molecule, denoted as Cu\textsubscript{2}O$[i,j,t]$. Our primary objective is to unravel the mathematical symphony underlying the structural intricacies of Cu\textsubscript{2}O$[i,j,t]$ and to imbue it with the conceptual essence of entropy. We accomplish this through the computation of entropy, leveraging various topological indices, including weight. In addition to our analytical journey, we present a graphical comparison that juxtaposes the computed indices and entropies, shedding light on the interplay between mathematical analysis and the structural elegance of Cu\textsubscript{2}O$[i,j,t]$. This endeavor contributes to a deeper understanding of the material's multifaceted applications, spanning domains from chemical sensors to solar cells, photocatalysis, and batteries, where Cu\textsubscript{2}O's crystallographic structure plays a pivotal role.

The Internet of Things (IoT) signifies a revolutionary technological advancement, enhancing various applications through device interconnectivity while introducing significant challenges due to these devices' limited hardware and communication capabilities. To navigate these complexities, the Internet Engineering Task Force (IETF) has tailored the Routing Protocol for Low-Power and Lossy Networks (RPL) to meet the unique demands of IoT environments. However, RPL struggles with traffic congestion and load distribution issues, negatively impacting network performance and reliability. This paper presents a novel enhancement to RPL by integrating learning automata designed to optimize network traffic distribution. This enhanced protocol, the Learning Automata-based Load-Aware RPL (LALARPL), dynamically adjusts routing decisions based on real-time network conditions, achieving more effective load balancing and significantly reducing network congestion. Extensive simulations reveal that this approach outperforms existing methodologies, leading to notable improvements in packet delivery rates, end-to-end delay, and energy efficiency. The findings highlight the potential of our approach to enhance IoT network operations and extend the lifespan of network components. The effectiveness of learning automata in refining routing processes within RPL offers valuable insights that may drive future advancements in IoT networking, aiming for more robust, efficient, and sustainable network architectures.

High consequence pathogens such as Ebola, Marburg and Lassa viruses are handled in maximum containment Biosafety Level 4 (BSL-4) laboratories. Genetic material is often isolated from such viruses and subsequently removed from BSL-4 for a multitude of downstream analyses using readily accessible technologies and equipment available at lower biosafety level laboratories. However, it is essential to ensure that these materials are free of viable viruses before removal from BSL-4 to guarantee sample safety. This study details the in-house procedure used for validating the inactivation of Ebola, Marburg and Lassa virus cultures after incubation with AVL lysis buffer (Qiagen) and ethanol. This study’s findings showed no viable virus was detectable when high-titer cultures of Ebola, Marburg, and Lassa viruses were incubated with AVL lysis buffer for 10 minutes, followed by an equal volume of 95% ethanol for 3 minutes, using a method with a sensitivity of ≤0.8 log10 TCID50 as the limit of detection.

This study delves into the dynamics of 'Variations' and 'Claims' within construction projects, specifically under the FIDIC-Red Book 1999 framework. The study aims to identify, categorize, and devise mitigation strategies for key types of variations and claims aligning with the FIDIC conditions of contract. The research is drawing on inputs from construction industry professionals including contract administrators and project managers, focusing on the MENA region. This choice is driven by the region's extensive adoption of FIDIC standards and its rapidly growing construction sector. Data collection encompassed a questionnaire distributed to 80 industry experts predominantly through interviews that focused on countries like Saudi Arabia, UAE, Kuwait, and Egypt. These locations were chosen to reflect diverse construction practices and the involvement of international firms. Utilizing SPSS-V.25 for statistical analysis, the study uncovers the most prevalent and impactful causes of variations and claims, highlighting the critical need for managerial intervention. A key feature is the integration of scientometric analysis for a quantitative finding. A significant addition to the methodology is the implementation of a k-means clustering analysis. The survey had high internal consistency with a Cronbach's alpha of 0.97, and respondents reported frequent and significant claims like delayed drawings, ambiguous documents, and client changes. The results showed that effective claims management requires clear communication and balanced contracts, while poor design and contract documentation cause variations and claims. Spearman's correlation showed strong positive relationships between certain claim types and causes, emphasizing the importance of dealing with these factors to reduce claims. Most respondents said the survey could predict and reduce claims.

The issue of antibiotic resistance represents a significant threat that extends beyond human health, encompassing animal welfare and the sustainability of the natural environment. The inappropriate use of antibiotics, poor sanitation and inadequate control measures, have contributed to the emergence of drug-resistant bacteria, which can spread at the human-animal-environment interface. The documented presence of antimicrobials in agriculture, veterinary medicine and human medicine has convinced all stakeholders of the need to contribute to the development of a "One Health" approach, which recognises the interrelationships between animals, humans and their environment and the need to adopt a common strategy encompassing these sectors to limit the spread of antimicrobial resistance (AMR). Although a number of countries have implemented integrated surveillance systems to monitor antibiotic use and antimicrobial resistance, available data suggest that the use of antibiotics in humans, animals and the environment is increasing worldwide. Consequently, the emergence of antibiotic-resistant pathogens is becoming a recurring concern. This review provides a comprehensive overview of the measures that are necessary to be taken and implemented in order to guarantee global health security.

Classifiers face a myriad of challenges in today’s data-driven world, ranging from overfitting and high computational costs to low accuracy, imbalanced training datasets, and the notorious black box effect. Furthermore, many traditional classifiers struggle with the robust handling of noisy and missing feature values. In response to these hurdles, we present classification methods that leverage the power of feature partitioning learning and outranking measures. Our classification algorithms offer an innovative approach, eliminating the need for prior domain knowledge by automatically discerning feature intervals directly from the data. These intervals capture essential patterns and characteristics within the dataset, empowering our classifiers with newfound adaptability and insight. In addition, we employ outranking measures to mitigate the influence of noise and uncertainty in the data. Through pairwise comparisons of alternatives on each feature, we enhance the robustness and reliability of our classification outcomes. The developed classifiers are empirically evaluated on several data sets from UCI repository and are compared with well-known classifiers including k Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), Naive Bayesian (NB) and Nearest Centroid (NC). The experiments result demonstrate that the classifiers based on feature interval learning and outranking approaches are robust to imbalanced data and to irrelevant features and achieve comparably and even better performances than the well-known classifiers in some cases. Moreover, our proposed classifiers produce more explainable models whilst preserving high predictive performance levels.

This study explores the effects of tempering on the precipitation behavior and impact toughness of high-nickel steel. The specimens underwent double quenching at 870°C and 770°C, followed by tempering at various temperatures. Advanced characterization techniques including optical microscopy (OM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were used to elucidate precipitation phenomena. Additionally, electron backscatter diffraction (EBSD) was employed to assess the misorientation distribution after tempering. Charpy impact tests were performed on specimens tempered at different temperatures to evaluate their toughness. The findings reveal that with increasing tempering temperature, the fraction of low-angle grain boundaries decreases, which correlates positively with enhanced impact toughness. The impact toughness peaks at 580°C and then diminishes with further temperature increases.

This study investigates the critical factors of trust, commitment, and adaptation within supplier relationship management (SRM) in the context of e-commerce. Through qualitative research methods, including semi-structured interviews and documentary analysis, the study explores how these factors influence relationship dynamics and organizational outcomes in digital business environments. Trust is examined as foundational to effective SRM, encompassing integrity, reliability, and shared values between buyers and suppliers. Commitment is analyzed in terms of long-term orientation, resource allocation, and relationship-specific investments aimed at mutual growth and sustainability. Adaptation emerges as essential for navigating the dynamic e-commerce landscape, encompassing proactive strategies, flexibility, and innovation to respond to market changes and technological advancements. The findings highlight the interplay and mutual reinforcement among trust, commitment, and adaptation, contributing synergistically to relationship resilience and organizational performance. However, challenges such as information asymmetry, cybersecurity risks, and organizational inertia are identified as barriers to effective SRM. Practical implications include strategies for enhancing trust, fostering commitment, and cultivating adaptive capabilities through continuous learning, collaborative innovation, and technology integration. By integrating these insights, businesses can strengthen supplier relationships, drive sustainable growth, and achieve competitive advantage in the digital economy.

The present paper deals with research on maintenance strategy and maintenance process improvement procedures to increase the efficiency and quality of the production system. It includes the design of maintenance performance indicators relevant to today's manufacturing systems to track improvements in the sustainable development of the manufacturing system. There are also the basic principles of maintenance strategy with linkages to the manufacturing system and selecting the strategy for the organization. The paper emphasizes maintenance management auditing and quality implementation in maintenance. Further, there is the process of changing the maintenance strategy described. This process includes reassessing the criticality of machines and equipment and their design units, then resource and capacity planning and input for maintenance management. It describes the impact of changing the maintenance management organization and maintenance capacity considering the change of strategy and the evaluation of maintenance choice alternatives, together with an analysis of the optimization procedure, which has an impact on social implication. The paper concludes by presenting the achieved impacts of maintenance strategy are: (1) increase in production efficiency (10%), (2) quality improvement in production (20%), (3) performance improvement (30%), (4) reduction of maintenance process costs (35%).

Our research assesses the effects of four forest species, namely Swietenia macrophylla King, Swietenia mahogany (L.) Jack., Pinus occidentalis Swartz, and Pinus caribaea Morelet var. Caribaea, on organic carbon (OC) dynamics and carbon dioxide equivalent balance (BCO2 Eq.) in the soils beneath these species. Reforestation projects in the study region cover 1,200, 543, 770, and 1,152 hectares, with these four species, respectively, being the most relevant species in reforestation projects within the country. To determine the BCO2 Eq. per unit area, we compared the greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) with the OC reserves found in the mineral soil to a depth of 30 cm and in the forest litter. For 18 months, we conducted field measurements in sixteen stands, four for each species. Our results indicate that S. macrophylla absorbed the highest amount of CO2, while S. mahogany released the highest amount into the atmosphere. BCO2 Eq. from S. macrophylla soils was -23.19 metric tons of CO2 Eq. ha-1 year-1, while for P. occidentalis, S. mahogany, and P. caribaea, the corresponding quantities were -3.838, -2.299, and +0.982, respectively. During the measurement period, soils under S. macrophylla, P. occidentalis, and P. caribaea were net sinks of CO2 Eq., while soils under S. mahogany behaved as a source. The absorption rate of CO2 Eq. from the atmosphere was approximately 6, 10, and 24 times higher in S. macrophylla when compared to the respective rates of P. occidentalis, P. caribaea, and S. mahagony.

Abstract: Obesity and overweight also increasingly affect women of childbearing age and pregnant women. In maternal obesity, the activation of metabolic, inflammatory, and oxidative stress pathways is proven, which appears to be a key step in placental and uterus function pathological changes. Several recent studies have evidenced that aquaporins (AQPs) are critical players in adipose tissue biology and are involved in the onset of obesity. Our studies aimed to investigate the changes in placental volume and vascularization and measure the AQP5 expression and total antioxidant capacity (TAC) in the placenta and uterus tissues in obese and normal-weight mothers. We also aim to measure the AQP5 plasma concentration. We found AQP5 dominance in the uterus and plasma at 34 weeks of normal pregnancy. The placental volume increased, and the vascularization decreased in obese mothers compared to the control. The AQP5 expression increased in the uterus of the obese group and did not change in the placenta. The TAC decreased in the plasma of overweight mothers. We hypothesize that increased AQP5 expression prolongs the length of pregnancy and inhibits the onset of contractions. Based on our findings, we can develop diagnostic tests and provide new targets for tocolytic drug development.

Previous literature has linked working for pay while attending university with negative academic and health outcomes, yet working students are often resilient when experiencing such adverse circumstances. This makes it crucial to explore potential psychological mechanisms which transform adverse experiences into sources of motivation and persistence for working students. We explore one mechanism – social identification – and its different foci – identifying as a student, employee, working student, or as a student of one’s discipline of study – as potential predictors of important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes in three cross-sectional studies. In Study 1, part-time working hours (but not identification processes) were associated with academic self-efficacy. In Study 2, discipline identification and part-time working hours were associated with using deep approaches to learning. In Study 3, student identification was associated with increased status in society. Overall, discipline identification may be solely linked to academic outcomes, yet student identification should be explored further as a potential enhancer of social and graduate outcomes. We discuss additional mechanisms which can help to transform working students’ experiences through their social identities and suggest boundary conditions which can affect the link between these identities and important outcomes.

Wave propagation in buildings analyzed from its response to earthquakes can be applied for tracking the dynamic characteristics changes based on impulse response functions. The velocity of traveling shear-waves and intrinsic attenuation in buildings can be retrieved for buildings. It is an approach of importance for system identification. The Factor Building at the University of California, Los Angeles campus (henceforth referred as the UCLA Factor Building), an instrumented 15-story steel-moment frame structure, are selected for dynamic response characteristics identification. They are inferred from wave propagation using seismic interferometry for recorded motions. The deconvolved waves are used to compute shear wave travel time and wave attenuation. The natural logarithm for the envelopes of the waveforms deconvolved with the signal at the basement constrains the attenuation. The waveforms from deconvolution with the motion at the basement suggest the fundamental mode of the building. The frequency and decay with time constrain the shear velocity and attenuation as well. The velocity are measured using arrival times picked from these deconvolved waves and the average velocity is 147.1 m/s. The quality factor is equal to 10.8 with the damping ratio at 5%. The shear wave velocity and damping ratio estimated from the deconvolved waves have a good match with these inferred from the waveforms deconvolved with the basement recording. This consistency suggests that wave deconvolution can be applied to extract the building response from the excitation and ground coupling. Based on the resonant frequencies and damping ratio, the finite element model of the building is updated. This study implies that wave deconvolution is powerful to extract the building dynamic characteristics. It helps to better the understanding of the dynamic response of buildings to earthquakes.

This paper explores the application of machine learning in financial time series analysis, focusing on predicting trends in financial enterprise stocks and economic data. It begins by distinguishing stocks from stocks and elucidates risk management strategies in the stock market. Traditional statistical methods such as ARIMA and exponential smoothing are discussed in terms of their advantages and limitations in economic forecasting. Subsequently, the effectiveness of machine learning techniques, particularly LSTM and CNN-BiLSTM hybrid models, in financial market prediction is detailed, highlighting their capability to capture nonlinear patterns in dynamic markets. The study demonstrates the advancements in predictive accuracy and robustness achieved by deep learning methods through empirical analysis and model validation. The findings contribute significantly to academic discourse and offer practical insights for investors, financial analysts, and policymakers navigating market volatility and optimizing investment strategies. Finally, the paper outlines prospects for machine learning in financial forecasting, laying a theoretical foundation and methodological framework for achieving more precise and reliable economic predictions.

Digital marketing adoption in the multinational Fast-Moving Consumer Goods (FMCG) sector presents both challenges and opportunities that significantly impact organizational strategies and market competitiveness. This qualitative study explores the complexities surrounding digital marketing adoption through interviews with 45 participants from multinational FMCG companies. The research investigates key barriers such as organizational resistance, technological constraints, and concerns over data privacy and security, while also examining the benefits of enhanced consumer engagement, global market reach, and data-driven decision making. Findings reveal that organizational resistance remains a formidable barrier, driven by senior management's cautious approach to digital transformation and concerns over return on investment (ROI) amidst rapidly evolving digital landscapes. Technological challenges, including outdated systems and limited budgets for technology upgrades, further hinder comprehensive digital integration. Moreover, navigating regulatory frameworks and addressing consumer trust in data privacy emerge as critical considerations for FMCG companies seeking to leverage digital strategies effectively. Conversely, digital marketing adoption offers substantial opportunities. Enhanced consumer engagement through personalized and interactive campaigns allows companies to strengthen brand-consumer relationships and foster loyalty. The global reach facilitated by digital platforms enables multinational FMCG firms to expand market presence, penetrate new markets, and adapt marketing strategies to diverse consumer preferences worldwide. Data-driven decision making emerges as pivotal, leveraging analytics to optimize marketing strategies, measure campaign effectiveness, and anticipate consumer behaviors in real-time. Strategies for overcoming barriers emphasize building internal digital capabilities through training, recruitment, and cross-functional collaboration. Aligning digital strategies with overarching business objectives and integrating digital efforts with traditional marketing channels are crucial for creating cohesive and effective campaigns. Embracing innovation, flexibility, and agility in adapting to technological advancements are essential for maintaining competitiveness and relevance in a rapidly evolving digital landscape. Looking forward, emerging trends such as AI and machine learning integration for predictive analytics, sustainability-focused marketing initiatives, and the evolution towards omnichannel strategies are poised to reshape digital marketing practices in the FMCG sector. By aligning strategies with these trends, FMCG companies can harness digital technologies to drive sustainable growth, enhance market competitiveness, and meet evolving consumer expectations in a digitally-driven global marketplace.

The main objective of this study was the adaptation of the scale named AUTODDIS in the cultural and social dimensions and analyze its reliability and validity. The reliability and validity were assessed through a pilot study conducted with a population of students with intellectual disabilities. The linguistic adaptation was done through expert judgment, including each indicator: the adequacy, the coherence, the relevance, and the clarity. After the scale adaptation, the scale pilot was conducted to explore its technical properties. It was performed in a public school for students with intellectual disabilities. For the content, the validity coefficient result was 0,998 while the complete reliability result was α, 978. For the reliability subscales, the results were the following: Autonomy α, 941; self-initiation α, 925; self-direction α, 970; self-regulation α, 804, and self-concept α, 935. The results confirm the AUTODDIS scale as a valid and reliable instrument to evaluate the self-determination. However, it is necessary to apply to a larger number of people with intellectual disability to generalize these results.

Human T-cell lymphotropic virus (HTLV) infection lacks effective treatment. This review describes the virological, immunological and clinical outcomes of antiretroviral therapy (ART) in people with HTLV infection. This systematic review followed PRISMA reporting guidelines and was registered in PROSPERO: CRD42022350076. The Newcastle-Ottawa Scales, adapted for cross-sectional studies, and Rob-2 were employed to assess the methodological quality of studies. A systematic search was conducted in Medline (PubMed), Scopus (Elsevier), Cochrane Library, and Web of Science (Clarivate Analytics) databases. We retrieved data from 08 methodologically diverse articles, on treatment of patients infected by HTLV-1 or HTLV-2 alone, or coinfected by HIV-1 with Raltegravir, Tenofovir, Lamivudine and Zidovudine. Proviral load decreased in 3 of 7 studies, during 4 to 48 weeks of antiretrovirals use. Cellular immune response (CD4, CD8, CD25, CD69 and CD71 cells) were evaluated in six studies. There was no significant clinical improvement in the studies but all of them detected clinical stability during treatment. Despite the demonstrated antiviral activity of ART, in vitro, clinical improvement was not proven. Most studies showed disease stability during ART use, suggesting potential clinical benefits. There is a need of larger, well-controlled trials, to define the role of ART for treatment of HTLV infection.

Attention-Deficit/Hyperactivity Disorder (ADHD) is traditionally conceptualized within a framework emphasizing deficits in attention regulation and executive function. However, emerging evidence from the fields of predictive coding and active inference offers a novel lens through which to understand ADHD not merely as a disorder of attention but as a distinctive mode of neurodevelopmental variation. This article synthesizes current research and theoretical models to propose a redefined understanding of ADHD. By integrating insights from Ryan Smith, Paul B. Badcock, and Karl J. Friston (2020), we explore the premise that individuals with ADHD exhibit unique differences in how their brains generate and update predictions about the environment, leading to the characteristic behavioral patterns observed in ADHD. We argue that ADHD involves a divergence in the brain's predictive models and its ability to minimize prediction error, impacting sensory processing, attention allocation, and motor control. This perspective illuminates the adaptive aspects of ADHD, suggesting that what are often labeled as deficits could also reflect an adaptive fit to certain environmental contexts, underscoring the role of neurodiversity in human evolution. Furthermore, we discuss the implications of this reconceptualization for clinical practice, including diagnosis, treatment, and support for individuals with ADHD, emphasizing approaches that align with their unique neurocognitive profiles. This article calls for a shift in the narrative surrounding ADHD, advocating for a model that appreciates the complexity and adaptiveness of neurodevelopmental diversity.