Metaverse represents a multifaceted digital universe integrating diverse technologies to create immersive, interconnected virtual environments. Key components foundational to its structure include the infrastructure layer for hardware and network support, the human interface layer utilizing virtual reality (VR) and augmented reality (AR) devices, and a decentralized layer leveraging blockchain for secure digital asset management. Further components encompass spatial computing for realistic 3D environments, the creator economy for content generation and monetization, and discovery mechanisms for navigation within Metaverse. VR, AR, blockchain, AI, the fifth-generation (5G) networks, and the Internet of Things (IoT) are central to Metaverse functionality, enabling real-time interactions and data integration. Real-Time Metaverse aims to replicate instantaneous real-world interactions, requiring advanced technological infrastructure for seamless data exchange. Critical challenges include ensuring low latency, high bandwidth, scalability, and robust security measures. Metaverse’s potential spans various domains, promising to revolutionize social interactions, entertainment, workplaces, and education through dynamic, immersive experiences. Ongoing advancements in high-performance computing, cloud services, and AI-driven technologies are essential for addressing existing barriers and achieving a cohesive, secure, and inclusive Metaverse ecosystem. Future research must focus on enhancing user experience, accessibility, and standardized interoperability to fully realize the transformative capabilities of a Metaverse.

Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combinations of factors/genes/proteins that might be affecting the pathway under certain conditions. In colorectal cancer (CRC) cells treated with ETC-1922159, many genes were found up and down regu- lated, individually. A recently developed search engine ranked combinations of BCL-X (X, a particular gene/protein) at 2nd order level after drug administration. These rank- ings reveal which BCL-X combinations might be working synergistically in CRC. If found true, oncologists can further test the combination of interest in wet lab and deter- mine the mechanism of functioning between the BCL and X. In this research work, we cover combinations of BCL with Interleukin (IL), Selenbp1, TP53, caspase (CASP), mucin (MUC) and exosome (EXOSC).

The capability of large food retail chains to respond quickly to changes in consumer behaviour and their dominant market position affects all food market players and often conflicts with the interests of national food producers, which can reduce the presence of locally sourced products in the food product mix in the country. In Latvia, there have been several proposals to limit retailers' opening hours on weekends and public holidays to increase the viability of small local food producers, retailers, and catering enterprises; however, limiting retailers' opening hours without research-based arguments is unacceptable. The research studies conducted in Europe also do not give a unified conclusion. Household consumer behaviour in the food market is viewed as an essential argument for increasing domestic demand and economic stability. Accordingly, the present research aims to identify the impacts of diversification of opening hours of food supermarkets on consumer shopping habits and the implications for creating an advantage for small and medium agri-food producers in selling their products. The research applied a quantitative approach to identify the main trends in society (n=2738), with a survey including 31 variables to quantify consumer behaviour, values, and opinions and seven socio-demographic variables. If a decision were made in Latvia to close grocery shops on Sundays or reduce their opening hours on weekends, 85% of consumers indicated that they would be unlikely to change their usual shopping location and would plan to shop at a supermarket on other days. The choice between farmers' markets and local food shops on Sundays would be made by 45% of consumers, with more than half (53%) of them shopping at local food shops at least a few times a month. It could, therefore, be argued that reducing the opening hours of supermarkets and closing them on Sundays and public holidays do not provide a competitive advantage and do not divert consumers to small and medium agri-food producers.

Muscle ultrasound quantification is a valuable complementary diagnostic tool for diabetic peripheral neuropathy (DPN). DPN significantly impacts the lives of individuals with diabetes, leading to pain, lower limb amputation, and disability, affecting patient quality of life. This work develops a computer-aided diagnostic (CAD) system based on muscle ultrasound that integrates the bag of features (BOF) and an ensemble subspace k-nearest neighbour (KNN) algorithm for DPN detection. The BOF creates a histogram of visual word occurrences to represent the muscle ultrasound images and trains an ensemble classifier through cross-validation, determining optimal parameters to improve classification accuracy for the ensemble diagnosis system. The dataset includes ultrasound images of six muscles from 53 subjects, consisting of 27 control and 26 patient cases. An empirical analysis was conducted for each binary classifier based on muscle type to select the best vocabulary tree properties or K values for BOF. The result indicates that ensemble subspace KNN classification, based on the bag of features, achieved an accuracy of 97.23%. This study suggests muscle ultrasound as a promising diagnostic tool with the potential for image recognition and interpretation. CAD systems can accurately diagnose muscle pathology, helping to overcome limitations and identify issues in individuals with diabetes.

Wave and tidal energy, recognized as vital renewable resources, harness the ocean's kinetic and potential power. This study aims to provide an in-depth patent analysis of the technological landscape within these sectors. We applied a dual approach: first, a descriptive analysis was conducted to explore patent publication trends, technology lifecycle stages, patent activity by country, top assignees, and IPC classifications. Our analysis provided a detailed overview of the sector's growth and the key players involved. Second, we utilized topic modeling, specifically BERTopic enhanced with large language models (LLMs), to identify and fine-tune key technolog-ical themes within the patent data. In this study, we identified seven distinct clusters each for wave and tidal energy using this approach. This method led to a novel categorization of the pa-tents, revealing latent themes within the patent data. Although our categorization differs from traditional methods, it provides deeper insights into the thematic focus of the patents, highlight-ing emerging trends and areas of innovation within wave and tidal energy technologies to better exploit and optimize ocean energy conversion infrastructure.

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

Polymeric nanoparticles (NPs) have garnered significant interest due to their potential in drug delivery. Specifically, nanopolymers functionalized with molecules such as proteins or peptides serve as versatile vehicles for this purpose. Curcumin (Cur) is a widely studied anticancer compound known for its positive effects on human health. Nevertheless, its insolubility and low bio-distribution hinder the exploitation of its beneficial traits. In this study, our team developed a nanodelivery system using a nanopolymer called poly(ε-caprolactone)-poly(ethylene glycol) (PCL-PEG), functionalized with A6 peptide to enable targeted delivery of Cur. The designed system exhibited favorable characteristics, including a stable zeta potential of -13.8 mV, a small size of 76.4 nm, uniform surface morphology, and high hydrophilicity with a contact angle of 31.53°. Additionally, the targeted delivery system demonstrated high encapsulation efficiency (EE%) (93 ± 0.89%), drug loading (DL%) (16.7 ± 0.9%), and a slow and gradual release profile with a release of approximately 83.1 ± 0.12%. The MTT assay results showed significant cell death in MDA-MB-231 cancer cells (IC₅₀ = 21.3 ± 1.57 µM) when treated with the Cur-NPs-A6 formulation, while the toxicity of the designed NPs was reduced on non-cancerous MCF-10A cells. Moreover, both the RT-qPCR and invasion assays demonstrated the system's effectiveness in activating apoptosis pathways and inhibiting cell invasion. These findings suggest that the engineered intelligent delivery system, equipped with the A6 peptide, which has a strong affinity for CD44 (a protein with increased expression in malignancy), could be an exceptionally effective strategy for cancer treatment.

In this paper, the distribution of prime numbers is expressed based on proving the Riemann hypothesis. The relationship between three numbers, three, six, and nine, and the modality to the distribution of prime numbers, is one of the results of Riemann's zeta function. Prime numbers are classified into six groups of single-digit numbers. There are no prime numbers in groups of three, six, and nine. The groups are made based on the sum of the internal digits. And for each set, there is an angle in the complex plane. The distance between the prime numbers in each group has a regular pattern. This pattern is a multiple of the numbers three, six, and nine. According to Euler's number, for an angle of 60 degrees, the real part of the cosine is 1/2. Accordingly, all prime numbers are related to angles greater than 60 degrees to 90 degrees. As a result, based on the relationship between the golden spiral and the complex conjugate of the zeta function, the function in The 1/2 point becomes zero based on the prime numbers.

This paper explores the concept of agency behaviour within complex adaptive systems, leveraging the Mindset Agency Theory (MAT) framework. The connection between agents within an agency population reveal a remarkable capacity for adaptation. MAT can help one understand the "why" behind adaptability through the key dualities: affect-cognition and tangible-intangible. The affect-cognition duality acknowledges the interplay between emotions and rational thought, enabling understanding of how internal states like emotions influence behaviour and shape the social structures that agents inhabit. Similarly, the tangible-intangible duality illuminates how agencies interact with their environment, recognising that observable behaviours are just one piece of the puzzle. Are also important, and previously missing from MAT are beliefs, both core beliefs and self-efficacy beliefs. These can be formalised as traits, taking value states from within a spectrum ranging between tangible and intangible poles. This becomes relevant in the digital age, where navigating information complexities requires acknowledging the dynamics of beliefs and values. With respect to environmental influences on agency, technology is special since it acts as an amplifier with the potential to intensify both positive and negative aspects of the proposed dualities by elaborating emotional responses (affect) while simultaneously creating echo chambers that limit exposure to diverse viewpoints (cognition). By understanding how core beliefs and self-efficacy beliefs interact, strategies can develop to navigate these complexities.

Global dust events have become more frequent due to climate change and increased human activity, significantly impacting air quality and human health. Previous studies have often focused on simulating cross-regional dust transport based on atmospheric parameters; however, comprehensive monitoring of dust events remains challenging. Therefore, this study utilized Fengyun-4A (FY-4A) satellite Advanced Geostationary Radiation Imager (AGRI) imagery, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar, and other auxiliary data to conduct three-dimensional spatiotemporal monitoring and cross-regional transport analysis of two typical dust events in the Beijing–Tianjin–Hebei (BTH) region of China using four dust intensity indices (Icsd, Dust Detection Index (DDI), Dust value (DV), and Dust Strength Index (DSI)) and the HYSPLIT model. We found that among the four indices, DDI was the most suitable for studying dust in the BTH region, with a detection accuracy (POCD) of > 88% at all times and reaching a maximum of 96.14%. Both the 2021 and 2023 dust events originated from large-scale deforestation in southern Mongolia and the border area of Inner Mongolia, with dust plumes distributed between 2 and 12 km being transported across regions to the BTH area. Further, when dust aerosols are primarily concentrated below 4 km and PM10 concentrations consistently exceed 600 µg/m³, large dust storms are more likely to occur in the BTH region. The findings of this study provide valuable insights into the sources, transport pathways, and environmental impacts of dust aerosols.

Objectives: To develop a risk prediction model for the identification of features involved in the prediction of erectile dysfunction (ED) at 12 months following COVID-19 recovery. Methods: We performed an observational prospective multicentre study. Participants were classified according to their history of COVID-19: I) Patients with a past history of COVID-19; and II) Patients without a previous microbiological diagnosis of COVID-19. A total of 361 patients (Past history of COVID-19, n=166; No past history of COVID-19, n=195) were assessed from January 2022 to March 2023. Patients with a past history of COVID-19 were assessed at 12 months following COVID-19 recovery. The primary outcome measure was ED, assessed through the 5-item International Index of Erectile Function (IIEF-5). Data concerning epidemiologic variables, comorbidities and active treatment were also collected. We performed a binary logistic regression to develop a risk predictive model. Among the models developed, we selected the one with the higher Area Under the Curve (AUC). Results: The median age was 55 years in both groups. The ED prevalence was 55.9% in patients with past history of COVID-19 and 44.1% in those with no past history of COVID-19. The best predictive model developed for ED comprised 40 variables and had an AUC of 0.8. Conclusions: We developed a regression model for the prediction of ED 12 months after COVID-19 recovery. The application of our predictive tool in a community setting could eventually prevent the adverse effects of ED on cardiovascular health, and the associated unfavourable economic impact.

There are few longitudinal studies on the association between dietary vitamin C and sleep disorders. The aim of this study was to investigate the association between dietary vitamin C intake and various types of sleep disorders, including sleep apnea and insomnia, as well as recommended dietary intakes. A total of 68,221 participants from the UK Biobank were enrolled in the study. Dietary vitamin C intake was calculated by a 24-hour dietary recall questionnaire. We used Cox regression model to assess the association between dietary vitamin C and sleep disorders and restricted cubic spline models to explore potential nonlinear relationships. Stratified analyses and sensitivity analyses were also performed to further test the results. The results showed that vitamin C intake at the Q4 level (132.88-191.51 mg/d) was significantly protective against sleep disorders with an HR (95% CI) of 0.78 (0.65-0.94), and against sleep apnea with an HR (95% CI) of 0.75 (0.62-0.92). The protective effect remained significant in stratified analyses of men and age ≤60 years, and the results were robust in sensitivity analyses. Adequate dietary vitamin C intake may have a protective effect in preventing sleep disorders.

Neuropathic pain (NeP) is a complex and debilitating condition that impacts millions of people globally. Although various treatment options exist, their effectiveness is often limited, and they can be accompanied by significant side effects. In recent years, there has been increasing interest in targeting the N-methyl-D-aspartate receptor (NMDAR) as a potential therapeutic approach to alleviate different types of neuropathic pain. This narrative review aims to provide a comprehensive examination of NMDAR antagonists, specifically ketamine, memantine, methadone, amantadine, carbamazepine, valproic acid, phenytoin, dextromethorphan, riluzole, and levorphanol, in the management of NeP. By analyzing and summarizing current preclinical and clinical studies, this review seeks to evaluate the efficacy of these pharmacologic agents in providing adequate relief for NeP.

This article introduces a novel two-step fifth-order Jacobian-free iterative method aimed at efficiently solving systems of nonlinear equations. The method leverages the benefits of Jacobian-free approaches, utilizing divided differences to circumvent the computationally intensive calculation of Jacobian matrices. This adaptation significantly reduces computational overhead and simplifies the implementation process while maintaining high convergence rates. We demonstrate that this method achieves fifth-order convergence under specific parameter settings, with a broad applicability across various types of nonlinear systems. The effectiveness of the proposed method is validated through a series of numerical experiments which confirm its superior performance in terms of accuracy and computational efficiency compared to existing methods.

Exposure to cadmium sulfate (CdSO4) can lead to neurotoxicity. Nevertheless, the precise molec-ular mechanisms underlying this phenomenon remain unclear, and effective treatment strategies are scarce. This study explored the protective effects of ellagic acid (EA), a natural polyphenolic compound, against CdSO4 exposure-induced neurotoxicity in HT22 cells. Additionally, the inves-tigation sought to elucidate the molecular mechanisms underlying this phenomenon. Our findings demonstrated that exposure of HT22 cells to CdSO4 resulted in apoptosis, which was effectively reversed by EA supplementation. EA supplementation also decreased reactive oxygen species (ROS) and mitochondrial ROS productions, reduced malondialdehyde (MDA) levels, and restored the activities of superoxide dismutase (SOD) and catalase (CAT). Additionally, EA supplementation at 5–20 μM significantly counteracted Cd-induced mitochondrial membrane potential and ATP losses and reduced the ratio of Bax/Bcl-2 and cleaved-caspase-3 protein expression. Furthermore, EA supplementation upregulated Nrf2 and HO-1 protein expression while downregulating the phosphorylation of JNK and p38 proteins. Pharmacological inhibition of JNK partially inhibited CdSO4-induced Nrf2/HO-1 activation and exacerbated its cytotoxicity. In conclusion, our results indicate that EA supplementation provides protection against CdSO4-induced cell apoptosis in HT22 cells by inhibiting oxidative stress and activating the Nrf2 pathway. Activation of the JNK pathway plays a protective role in CdSO4-induced cell apoptosis in HT22 cells.

The electric network frequency (ENF), often referred to as the industrial heartbeat, plays a crucial role in the power system. In recent years, it has found applications in multimedia evidence identification for court proceedings and audio-visual temporal source identification. This paper introduces a ENF region classification model named UniTS-SinSpec within the UniTS framework. The model integrates the si-nusoidal activation function and spectral attention mechanism while also redesigning the model frame-work. Training is conducted using a public dataset on the open science framework platform (OSF), with final experimental results demonstrating that after parameter optimization, the UniTS-SinSpec model achieves an average validation accuracy of 97.47%, surpassing current state-of-the-art and baseline models. Accurate classification can significantly aid in ENF temporal source identification. Future re-search will focus on expanding dataset coverage and diversity to verify the model's generality and ro-bustness across different regions, time spans, and data sources. Additionally, it aims to explore extensive application potential of ENF region classification in preventing crimes such as telecommunications fraud, terrorism, and child pornography.

A prospective clinical-epidemiological study was conducted to evaluate the dynamics of biomarkers in hospitalized patients with moderate to severe COVID-19 (according to the National Institute of Health severity scale) treated with Anakinra, compared to those receiving standard treatment. The study included 65 patients with a mean age of 75.51±9.54 years, ranging from 44 to 99 years. Among the study participants, 38 (58.5%) were male and 27 (41.5%) were female. The patients were divided into two groups: control group (standard treatment): 24 patients (36.9%) and target group (Anakinra treatment): 41 patients (63.1%). The results showed a significant relationship between the dynamics of leukocytes, ASAT, LDH, D-dimer, ferritin, and IL-6 and the administration of Anakinra. In the control group, no significant dynamics were observed in leukocyte count, D-dimer, ferritin, or IL-6. A statistically significant decrease in ASAT and LDH values in the control group was noted only on Day 7. In the Anakinra group, significantly (or with borderline statistical significance, p<0.1) lower mean values were observed for leukocytes, NLR, D-dimer, ferritin, and IL-6 on Days 3 and 7 compared to the control group. Additionally, significantly lower CRP values were detected in the Anakinra group on Day 7 compared to the control group.

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. The study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline's failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation's results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation.

Most available studies on the mechanical properties of apples lack the comprehensive results needed for the construction and validation of FEM models. Researchers typically focus on either the flesh and epidermis or the whole fruit, often overlooking the maturity stage of the examined apples. They usually report only firmness or the starch index as indicators of maturity. Furthermore, many studies use store-bought apples, which is impractical for industrial applications since this fruit have already undergone various treatments before reaching the shelf. This article aims to determine the mechanical properties of apples necessary for constructing FEM models that are both adequate and useful for the industry. The new Polish apple variety, Chopin, was selected as the research material. The study was conducted for three stages of apple maturity: development, ripening, and senescence. Mechanical properties of the flesh and skin were determined as material data for FEM models. Force-displacement curves and pressure-force functions were examined for future model validation. Using micro-computed tomography, the bruise volumes of fruit subjected to 20%, 50%, and 80% of the destructive force were determined. Significant differences were found between apples in the senescence stage and those in the development and ripening stages. Results of Micro-Ct and the results of modified and real compression tests of whole fruit have allowed us to formulate the research hypothesis regarding the influence of flesh cracking (characterized by local drops of force), influencing the bruise visibility and detection.

Lignin is nature's second most abundant vascular plant biopolymer, playing significant roles in mechanical support, water transport, and stress responses. This study identified 90 lignin biosynthesis genes in the rice based on phylogeny and motif constitution, and they belong to PAL, C4H, 4CL, HCT, C3H, CCoAOMT, CCR, F5H, COMT, and CAD families. Duplication events contributed largely to the expansion of these gene families, such as PAL, CCoAOMT, CCR, and CAD families mainly attributed to tandem and segmental duplication, respectively. Microarray data of 33 tissue samples covering the entire life cycle of rice suggested, fairly high PAL, HCT, C3H, CCoAOMT, CCR, COMT, and CAD gene expression, and rather variable C4H, 4CL, and F5H expression. Some members of lignin-related genes (OsCCRL11, OsHCT1/2/5, OsCCoAOMT1/3/5, OsCOMT, OsC3H, OsCAD2, and OsPAL1/6) were expressed in all tissues examined. The expression patterns of lignin-related genes can be divided into two major groups with eight subgroups, each showing a distinct co-expression in tissues representing typically primary and secondary cell wall constitutions. Some lignin-related genes were strongly co-expressed in tissues typical of secondary cell walls. The combined HPLC analysis showed increased lignin monomers (H, G, and S) in five genotypes from young to old growth stages. Based on 90 genes' microarray data, 27 genes were selected for qRT-PCR gene expression analysis. Four genes (OsPAL9, OsCAD8C, OsCCR8, and OsCOMTL4) were significantly negatively correlated with lignin monomers. Furthermore, eleven genes were co-expressed in certain genotypes during secondary growth stages. Among them, six genes (OsC3H, OsCAD2, OsCCR2, OsCOMT, OsPAL2, and OsPAL8) were overlapped with microarray gene expressions, highlighting their importance in lignin biosynthesis.

The Sentinel-1 SAR Extra Wide swath mode with its 40 meters pixel size allows accurate lead mapping in Arctic sea ice areas. We present an improved winter lead detection algorithm based on a modified U-Net convolutional neural network. We introduce a preprocessing procedure that balances normalized radar cross section (NRCS) values between sub-swaths. This results in more consistent Sentinel-1 SAR images as input for the classifier, which is especially important for the cross-polarization HV channel. In turn, image consistency is essential for automatic image semantic segmentation. We develop a new lead detection algorithm and compare it with a previously published version. We produce pan-Arctic, 40 meters resolution lead maps and present pan-Arctic lead area fraction on a 12 km grid for January 2019. Within different Arctic regions, the lead area fraction is stable and varies only within the expected natural variability during the one month studied here. The average Arctic-wide lead area fraction is 2.44 % with 0.25 % standard deviation during January 2019. The improved lead detection algorithm leads to a better lead discrimination and extends the applicability area to the entire Arctic.

In this work, an attempt is made to the theoretically substantiate the experimentally known facts of the influence of halogen concentration on the catalytic properties of the neodymium-based Ziegler–Natta system. Based on the structural and thermochemical data obtained using modern methods of quantum chemistry, the process of the 1,3-butadiene cis-1,4-polymerization under the model active centers of the neodymium Ziegler-Natta catalysts with different content of chloride ions was studied. Results are presented that explain the increase in the cis-stereospecificity and activity of the polymerization system with an increase in the content of the chloride ions in the neodymium catalytic system. There were established the reasons for the decrease in the concentration of active centers relative to the introduced Nd(III) with an excess of chloride ions and the occurrence of the anti-syn isomerization as a source of the formation of the trans-1,4-structures in the cis-1,4-polybutadiene.

Avian Metapneumovirus (aMPV) is a significant poultry pathogen with a global presence, primarily causing respiratory issues in turkeys. It also affects chickens, although the severity of its impact is often lessened in this species. In Morocco, aMPV has been detected in broiler flocks, prompting the need to deeply analyze circulating strains to understand better the epidemiology and develop control measures accordingly. This research focuses on the sequencing and molecular characterization of aMPV in these flocks. Additionally, aMPV isolated from turkeys displaying Turkey Rhinotracheitis (TRT) signs, were included in the study to compare the findings. RNA extracted from positive swabs was subjected to nested PCR, targeting the attachment protein of the G gene, followed by gel electrophoresis. Amplicons were purified and sequenced using the Sanger method. Bioinformatics tools facilitated sequence analyses, including BLAST for similarity searches and Mega® for phylogenetic analysis using the maximum likelihood method with 1000 bootstrap replicates. The investigation unveiled the existence of three distinct clades of the same aMPV/B strain, two of which originated from used vaccines and one from field recombination, all circulating in broilers and turkeys and indicating potential virus transmission between both poultry species. This article presents the first-ever molecular characterization of aMPV isolated from Moroccan broilers and turkeys, encompassing comprehensive investigations on its presence and subtype, and genetic characterization.

Introduction: Inflammation is a significant contributor to cardiovascular disease (CVD) in people with HIV (PWH), who face twice the risk of CVD compared to the general population. The presence of co-existing rheumatic disease (RD) may further exacerbate inflammation and increase the incidence of CVD events in this population. Methods: We conducted a retrospective study using electronic health record (EHR) data from the Veterans Affairs Medical Center in Atlanta, covering the period from 2000 to 2019. The study included 3,930 veterans with HIV, and assessed the impact of rheumatic disease therapies (RDT) on CVD outcomes. The primary outcome was the first occurrence of a CVD event. Results: Rheumatic disease was significantly associated with an increased risk of CVD events (OR = 2.67; p < 0.001). Additionally, exposure to multiple RDTs (aHR = 2.121, p = 0.047), NSAIDs (aHR = 1.694, p = 0.003), glucocorticoids (aHR = 2.332, p < 0.0001), and hypouricemic agents and colchicine (aHR = 3.445, p < 0.0001) were all significantly associated with increased CVD events. Conclusion: The co-existence of HIV infection and rheumatic disease, along with the use of RDTs, may amplify the risk of CVD events in PWH. These findings underscore the need for further investigation into the relationship between RD, RDTs, and CVD risk in larger, controlled studies, given the potential implications for treatment decisions in this patient population.

GR4J (Genie Rural a 4 parame`tres Journalier) is a rainfall-runoff model widely used to modelling rainfall into discharge. In this model, the input data used are daily rainfall and evapotranspiration data, calibrated using daily observed discharge data. This model seeks the optimum parameter value that produces the minimum deviation or error. The Nash-Sutcliffe Coefficient and Relative Volume Error (RVE) are used to estimate the errors that occur. One of the modelling parameters, namely X4 (peak time), has a value that does not match the observed hydrograph peak time (Tp). For this reason, it is necessary to adjust the modelling equation so that the unit hydrograph of the model appropriately in terms of value and shape with observed unit hydrograph. This study examines ten watersheds in Java Island so that it is expected to represent catchment conditions in tropical areas and developing countries. A relationship was obtained between the difference peak time from modelling (X4) and observed Tp. Adjustments Formula can be made to the general GR4J modelling equation for unit hydrograph in Java Island watersheds.

The optimal combination of five components to develop a concrete for high-temperature applications was studied through a response surface methodology known as mixture design of experiment. The selected components were water, an alkali-activated binder based on ferronickel slag activated with potassium silicate and potassium hydroxide, and three aggregate sizes corresponding to 0-4 mm, 4-8 mm, and 8-16 mm. Selected response parameters were slump and compressive strength before and after heat exposure. Six cubes of side 150 mm were cast for each concrete mix, three for ambient and three for residual (post-heat exposure) compressive strength. All 20 concrete mixes were exposed to a thermal load of 600 °C for two hours. The optimal concrete mix was adapted for large-scale applications, by increasing slump and replacing limestone with olivine aggregates for enhanced residual compressive strength. The adapted mix resulted in concrete with 76 MPa and 32 MPa compressive strength before and after high-temperature exposure. The CO2 emissions were found to be 77 % lower when compared to traditional OPC concrete.

This narrative review synthesizes findings from empirical studies to explore the factors influencing the adoption of ChatGPT in higher education. The review highlights several critical determinants, both confirmed and debatable, of ChatGPT acceptance among students and educators. Previous studies have predominantly utilized theories such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Diffusion of Innovations (DoI) theory. Confirmed factors include performance expectancy, effort expectancy, social influence, facilitating conditions, and trust, which significantly predict user attitudes and intentions toward adopting ChatGPT. Perceived usefulness and ease of use are core components influencing adoption positively. However, some factors have shown inconsistent impacts. While generally critical, effort expectancy and facilitating conditions vary based on context. Social influence, demographic characteristics (age, gender), extrinsic motivation, and technology readiness exhibit inconsistent effects, suggesting that intrinsic motivations may be more critical. Data collection primarily used online surveys with structured questionnaires, varying widely in sample sizes from small pilot studies to large-scale surveys and covering diverse academic disciplines. Practical implications suggest enhancing perceived usefulness and ease of use through training and technical support, building trust by addressing privacy concerns, and leveraging social influence to drive adoption. The review underscores the need to refine technology acceptance models to incorporate broader psychological and contextual factors, integrate intrinsic motivation theories, and adopt a systems thinking approach. Addressing limitations such as potential selection bias and the quality and scope of existing studies, future research can develop robust models and provide deeper insights into ChatGPT adoption dynamics in higher education, supporting its effective integration to enhance learning outcomes and foster educational innovation.

The optimization of ligand-receptor binding affinities is essential for enhancing therapeutic efficacy and specificity, particularly in the design of peptide-based drugs. ziconotide, a potent blocker of the N-type calcium channel CaV2.2, has demonstrated therapeutic potential in the treatment of moderate to severe chronic pain. However, there is limited structural and binding affinity data available for scaling the design of ziconotide analogues with improved efficacy and specificity. In this study, I present a structural biophysics-based approach to develop a scalable in silico framework for generating and analyzing ligand-receptor binding affinity landscapes, focusing on ziconotide and its receptor, CaV2.2. This framework integrates advanced computational structural tools and binding affinity calculations to produce high-accuracy structural and intermolecular binding data. The insights gained from this scalable approach will guide the design of ziconotide analogues with enhanced efficacy, offering a powerful computational workflow for high-throughput ligand optimization. Additionally, when combined with artificial intelligence (AI) algorithms, this computational workflow generates high-accuracy structural and biophysical data, towards an AI- and structural biophysics-driven paradigm shift in peptide discovery and design.

Soil stabilization using Portland cement is a widely adopted technique. Previous research has demonstrated that molasses, which contains sugars, enhances the reaction between cement and aggregates. This study investigates the impact of adding molasses to soil stabilized with Ordinary Portland Cement (OPC) on geotechnical properties. Expansive clay soil samples from Taru Jabba, District Nowshera, Pakistan, were treated with various combinations of molasses and cement. The concentrations of each stabilizer were varied at 0%, 4%, 8%, and 12% by dry weight of the soil. Additionally, the soil was treated with constant molasses contents of 4%, 8%, and 12%, while varying the cement content at 4%, 8%, and 12% by dry weight. Geotechnical tests, including Proctor compaction, Atterberg limits, Unconfined Compressive Strength (UCS), California Bearing Ratio (CBR), and swelling potential, were conducted to assess the effects of the stabilizers. The results indicated that the addition of molasses improved soil strength, mitigated shrinkage cracks, and reduced brittleness. Specifically, the CBR value increased from 3.2% in the native soil to 12.3% with 12% molasses and 12% cement. The Plasticity Index (PI) decreased from 14.23% to 8.12%, and the CBR swell value reduced from 9.66% to 3.82%. Furthermore, the UCS of the stabilized soil increased by 64.7% compared to the untreated soil after a 7-day curing period.

In today’s rapidly evolving digital landscape, the significance of password guessing techniques in both offensive and defensive strategies is paramount. Passwords serve as a crucial line of defense for both individuals and corporations, safeguarding their sensitive systems and data. Therefore, assessing the effectiveness of these access credentials is a critical task. However, existing research in this field often encounters limitations, such as a lack of sufficient training data and extended model training times. Current methods often struggle with limited training data and lengthy training times. This paper introduces BBPE-AE, a novel Auto Encoder Network (AE) designed for password guessing. BBPE-AE utilizes Byte-level Byte Pair Encoding (BBPE) to extract frequent tokens from password datasets without length restrictions, employing a dynamic window technique to capture complex patterns. Experimental results on Hotmail and Myspace datasets demonstrate exceptional performance, achieving high similarity rates (BLEU-Unigram: 0.90, BLEU-Bigram: 0.82 for Hotmail; BLEU-Unigram: 0.90, BLEU-Bigram: 0.81 for Myspace). BBPE-AE generates realistic passwords that meet HIBP (Have I Been Pwned) standards, minimizing duplication. These findings highlight the effectiveness of BBPE-AE in enhancing security by generating realistic passwords, ultimately safeguarding sensitive systems and data.

With the increased global attention to environmental protection, social responsibility and corporate governance (ESG) standards, integrating ESG into supply chain management (SCM) is becoming a strategic requirement for companies to achieve competitiveness and sustainable development. This study reviews the impact factors of ESG practices on supply chain competitiveness, and empirically examines the mechanism of ESG performance on supply chains through a questionnaire survey with a sample of Chinese SMEs. It was found that normative pressure, coercive pressure and imitative pressure in SMEs have a significant positive effect on cognition and attitude and perceived behavioral control; good corporate cognition and attitude, perceived behavioral control and corporate pressure also enhance the level of ESG practices. Further analysis shows that cognition and attitude and perceived behavioral control play a mediating role in the impact of ESG practices, and ESG performance promotes sustainable development of SMEs. The article puts forward the following suggestions: (1) close supply chain partnerships to enhance green innovation; (2) the government should give more resource support to ESG-invested enterprises and support the development of advantageous enterprises; (3) improve the corporate disclosure mechanism and strengthen the supervision; and (4) strengthen the training of professionals in supply chain ESG management.

Sick leave is influenced by various modifiable lifestyle factors and sex differences. This study examines the impact of body mass index, fruit and vegetable consumption, physical activity, smoking, and alcohol consumption on sick leave among Serbia's working population, focusing on sex differences. Data from the 2019 National Health Survey of Serbia were analyzed, focusing on a representative sample of 4,652 individuals aged 18-65. Chi-square tests and logistic regression models assessed the relationships between lifestyle factors and sick leave, adjusting for sociodemographic, work-related, and health-related variables. Among respondents, 15.8% reported sick leave in the past 12 months, with higher rates among women in both, short-term (13.9% vs. 10.6%) and long-term sick leave (3.4% vs. 2.2%). For men, obesity (OR = 2.6), poor dietary habits (fruit OR = 2.1; vegetables OR = 2.8), smoking (OR = 1.9), and risky alcohol consumption (OR = 4.1) significantly increase the likelihood of sick leave. In women, smoking (OR = 1.8) and risky alcohol consumption (OR = 3.1) are major predictors, while BMI and physical activity show less impact. Fruit and vegetable consumption and physical activity have inconsistent effects on sick leave, indicating the need for further research. This study identifies obesity, poor dietary habits, smoking, and alcohol consumption as key predictors of sick leave in men. In women, smoking and risky alcohol consumption are major predictors. Smoking is a risk factor for both sexes, while risky alcohol consumption emerges as a prominent predictor and is a significant predictor overall. These findings highlight the need for targeted public health interventions to address these lifestyle factors and reduce sick leave rates. Further research is needed to clarify the roles of dietary habits and physical activity in influencing sick leave.

Harvesting is a serious issue in oil palm plantations after 15-20 years owing to the increased height of the trees (&gt;20 feet). The slow vertical growth of the oil palm dura genotypes is desired for increasing the DxP progenies productivity and economic life span upto ten years. Reduced height increment has a long-term impact on harvesting costs. The current study assessed 308 genotypes generated from African germplasm. Over a three year period, the biometric properties of eleven DxD crosses were evaluated in order to quantify genetic parameters, phenotypic correlations, and principal component analysis for genetic attributes of the better performing dwarf progenies in terms of yield. The evaluated genotypes have a highly significant influence (p &lt; 0.01) on the majority of characteristics. The progenies yielded between 165 and 208 kg of fresh fruit bunches (FFB) per palm every year. The Height increment (HI) varied between 17% and 19%, with an overall average of 18%. Genotypes G8, G300, and G221 had the lowest yearly height increments, measuring 28.98, 29.19, and 30.87 cm, respectively. The outcome of the present study shows that they are slow height increment genotypes with a high FFB yield (&gt; 25 T/Ha). The creation of dura parents with slow height increment in combination with a high bunch weight helps for prolonging the productive life of the palm to more than 35 years, adding value to obtaining distinct oil palm varieties. Overall, this targeted breeding effort towards developing dwarf oil palm hybrids reflects a strategic approach to addressing specific challenges in oil palm cultivation, ultimately helping to promote the oil palm sector globally.

The energy supply for isolated systems remains a current challenge in Brazil and worldwide, particularly when known solutions are compared regarding cost, the ability to supply energy on demand, and sustainability. In this context, green hydrogen, which has been considered one of the main paths for the decarbonization of the energy chain, is also seen as a potential solution for energy supply in isolated systems. Based on a literature review of articles addressing the topics of green hydrogen and isolated systems, an analysis is conducted on the application of green hydrogen as an energy supply solution for isolated systems. The review identified and collected data on important parameters for comparing solutions, such as CAPEX, OPEX, energy cost, and the price per kilogram of hydrogen. Using these data, analyses were performed to provide an overview of the application of green hydrogen in isolated systems. One of the objectives of this work is to present a comprehensive analysis of the green hydrogen chain and its application in the context of electricity generation, particularly for isolated systems in Brazil.

: We report the synthesis and characterization of Mn(III) chloride (MnIIICl3) complexes coordinated with N-oxide ylide ligands, namely trimethyl-N-oxide (Me3NO) and pyridine-N-oxide (PyNO). The compounds are reactive and, while isolable in the solid-state at room temperature, readily decompose into Mn(II). For example, “[MnIIICl3(ONMe3)n]” decomposes into the 2D polymeric network compound complex salt [MnII(µ-Cl)3MnII(µ-ONMe3)]n[MnII(µ-Cl)3]n•(Me3NO•HCl)n (4). The reaction of MnIIICl3 with PyNO forms varied Mn(III) compounds with PyNO coordination and these react with hexamethylbenzene (HMB) to form the chlorinated organic product 1-cloromethyl-2,3,4,5,6-pentamethylbenzene (8). In contrast to N-oxide coordination to Mn(III), the reaction between [MnIIICl3(OPPh3)2] and 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) resulted in electron transfer forming d5 manganate of the [TEMPO] cation instead of TEMPO–Mn(III) adducts. The reactivity affected by N-oxide coordination is discussed through comparisons with other L–MnIIICl3 complexes within the context of reduction potential.

Acute Respiratory Distress Syndrome (ARDS) is a severe lung condition with a high mortality rate for which there are no effective therapeutics. The failure of the alveolar-capillary barrier, composed of lung endothelial (EC) and alveolar epithelial (AEC) cells, is a critical factor leading to excessive inflammation and edema characteristics of acute lung injury (ALI). Phosphodiesterases (PDE) are enzymes well-recognized for their roles in regulating endothelial permeability and inflammation. Although PDE inhibitors are used as therapeutics for inflammatory diseases like COPD (chronic obstructive pulmonary disease), their efficacy in treating ARDS has not yet been established. In this study, we investigate the effects of ensifentrine, an FDA-approved novel dual PDE 3/4 inhibitor, on lung endothelial and epithelial dysfunction caused by methicillin-resistant S. aureus (MRSA), a pathogen involved in bacterial ARDS. Human primary lung endothelial cells and alveolar epithelial cell lines (A549 and immortalized AEC) were treated with heat-killed MRSA, and their responses were assessed in the presence or absence of ensifentrine. Ensifentrine given either pre- or post exposure attenuated MRSA-induced increased lung endothelial permeability. VE-cadherin junctions, which serve to stabilize the EC barrier, were disrupted by MRSA; however, ensifentrine effectively prevented this disruption. Pre-treatment with ensifentrine protected against MRSA-induced EC pro-inflammatory signaling by inhibiting the expression of VCAM-1, ICAM-1, and by reducing the IL-6 release. In AEC, MRSA caused upregulation of ICAM-1, activation of NF-kB and production of IL-8, all of which were inhibited by ensifentrine. These results indicate that dual inhibition of phosphodiesterases 3 and 4 by ensifentrine is barrier protective and attenuates MRSA-induced inflammation in both lung endothelial and epithelial cells. The PDE3/4 inhibitor ensifentrine may represent a promising novel strategy for the treatment of ALI.

In recent times, the adoption of cloud computing by small and medium-sized 9 enterprises (SMEs) has become a crucial issue. These businesses face substantial difficulties in 10 accessing reliable and affordable IT infrastructure due to economic constraints and technological 11 restrictions. Hybrid cloud computing solutions which incorporate Infrastructure as a Service 12 (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) offer a feasible approach to 13overcoming these challenges. This study proposes a systematic literature review of cloud 14 computing's impact on SME performance emphasizing cost-efficiency, reliability, and 15 competitive advantages, using the 2020 Preferred Reporting Items for Systematic Reviews and 16 Meta-Analyses (PRISMA) framework. The inclusion criteria are bounded by (1) publication date 17 between 2014 and 2024, (2) English-language publications, (3) research focused on cloud 18 computing for SMEs, and (4) studies with a clear analytical framework for evaluating SME 19 performance. Following this process, 90 eligible research studies were included. The average 20 total cost for cloud services varies significantly, with operational costs reflecting the scalability 21 of the services and the specific needs of SMEs. This analysis offers valuable guidance for SMEs 22 and stakeholders in optimizing cloud-based strategies for enhanced performance.

Wheat is threatened by global warming. This study aimed to characterize based on DNA profile and identify heat-tolerant wheat genotypes. Fifteen wheat genotypes were sown in Nov 21 and Dec 21 and evaluated within 13 SSR markers. A dendrogram classified the genotypes into two main groups. The highest genetic distances (0.93) were drawn between BAW 1290 and BARI Gom 28, and the lowest one between Nadi 2 and BAW 1147. Heat susceptibility index (HSI) values for 1000-grain weight (TGW) and grain yield indicated moderate heat tolerance in Cluster I genotypes (HSI 0.50-1.00), closely matching Group A's Cluster II members. In Group B, Cluster III genotypes had higher HSI (1.04-1.23) and significant reductions in TGW and grain yield under heat stress, indicating heat susceptibility. The varieties BARI Gom 25, 26, 27, 28, 29, and 30 were identified as heat-stress tolerant. This research provides insights for future heat stress-molecular breeding programs.

This study investigated the impact of six high-intensity interval training (HIIT) running sessions at 1% or 10% slope on various physiological and performance parameters in 25 men. The partic-ipants underwent assessments of VO2max, time to exhaustion at 1% slope (TLim1%), and time to exhaustion at 10% slope (TLim10%) in the initial three visits. They were then randomly assigned to control (CON), HIIT at 1% slope (GT1%), or HIIT at 10% slope (GT10%) groups. Over three weeks, participants performed six HIIT sessions with equalized workload based on their indi-vidual maximal oxygen uptake (vVO2max). The sessions comprised 50% of TLim, with a 1:1 ratio of exercise to recovery at 50% vVO2max. Results indicated significant improvements in VO2max and peak velocity (VPeak) after HIIT at both slopes. Heart rate (HR) behavior differed between sessions for GT1%, while no significant differences were observed for GT10%. Rating of perceived exertion (RPE) significantly reduced for GT1% after the third session, with a similar trend for GT10%. In summary, six sessions of 1% or 10% slope HIIT effectively enhanced VO2max and VPeak, but there was no improvement in TLim performance, suggesting no adaptive transfer between training groups.

Traditional chemical research often relies on trial-and-error synthesis and characterization methods. Now, modern machine learning (ML) offers data-driven approaches for predicting properties, like water solubility, directly from chemical structure. But with various data representation schemes for molecular structure and model approaches to select from, it can be difficult for non-experts to determine best practices for utilizing ML. To clarify this landscape of choices, this study uses the ESOL molecular solubility dataset to compare the performance of a selection of different models on different data representations. First, we compare three classical regression methods (linear, ridge, LASSO) on three common data representations (RDKit fingerprint, Morgan fingerprint, intuition-selected molecular features). Then, we demonstrate how two distinct deep learning approaches (multilayer perceptron, graph convolution) can achieve accurate predictions even when prior intuition about feature-property correlations are absent. Finally, we outline a modern attention-based approach, inspired by successes in language modeling and fine-tuned by Bayesian optimization, to achieve a prediction methodology that is more general and performant than the previous approaches. This attention-based approach operates directly on the common SMILES string molecular representation, without requiring as many model parameters as other deep learning approaches or preprocessing into a representative fingerprint or vector of intuitively selected features. In short, when selected molecular features are known to likely correlate with a feature of interest, it may be possible to achieve good predictive modeling without turning to massive deep learning approaches. When particular features are not known a priori, graph approaches are a common solution, and we further demonstrate how a modern hyperparameter optimized attention approach can perform even better.

Due to the inherent limitations of a single viewpoint, reconstructing 3D human meshes 1 from a single image has long been a challenging task. While deep learning networks enable us to 2 approximate the shape of unseen sides, capturing the texture details of the non-visible side remains 3 difficult with just one image. Traditional methods utilize Generative Adversarial Networks (GANs) 4 to predict the normal maps of the non-visible side, thereby inferring detailed textures and wrinkles 5 on the model’s surface. However, we have identified challenges with existing normal prediction 6 networks when dealing with complex scenes, such as a lack of focus on local features and insufficient 7 modeling of spatial relationships.To address these challenges, we introduce EMAR—Enhanced 8 Multi-scale Attention-driven Single Image 3D Human Reconstruction. This approach incorporates 9 a novel Enhanced Multi-Scale Attention (EMSA) mechanism, which excels at capturing intricate 10 features and global relationships in complex scenes. EMSA surpasses traditional single-scale attention 11 mechanisms by adaptively adjusting the weights between features, enabling the network to more 12 effectively leverage information across various scales.Furthermore, we have improved the feature 13 fusion method to better integrate representations from different scales. This enhanced feature fusion 14 allows the network to more comprehensively understand both fine details and global structures 15 within the image. Finally, we have designed a hybrid loss function tailored to the introduced attention 16 mechanism and feature fusion method, optimizing the network’s training process and enhancing the 17 quality of reconstruction results.Our network demonstrates significant improvements in performance 18 for 3D human model reconstruction. Experimental results show that our method exhibits greater 19 robustness to challenging poses compared to traditional single-scale approaches.

Storied Rocks (Tumpituxwinap) is a term of reference used by the Numic Speaking tribal elders whom we have worked with for over 60 years on an estimated 200 ethnographic studies. Key in this analysis are the protocols for approaching, interacting, and using the places where Storied Rocks have been located. Concomitant with these traditional protocols are ones established to resolve the curiosity of non-Natives about why they are in a particular place and what they mean. This analysis shares the cultural understandings of Tribal representatives who participated in these ethnographic studies. Studies used in the analysis were funded by U.S. federal agencies, supported by federally recognized Native American tribal governments, and composed with the cultural understandings shared and made public by tribally appointed elders to clarify the conundrums that are Storied Rocks.

Previous research has indicated that ultra-high pressure (UHP) technology is useful in speeding up the extraction process of cold brew (CB) coffee. However, the impact of different degrees of roasting on UHP CB coffee is still unclear. Therefore, this study aimed to investigate the effects of three different degrees of roasting (light, medium, and dark) on the physicochemical and flavor characteristics of UHP CB coffee. The results of this study showed that most physicochemical characteristics of UHP coffee were similar to those of conventional CB coffee, regardless of the degree of roasting. However, the majority of physicochemical characteristics, non-volatile components, and sensory evaluation significantly increased with an increase in roasting degree. The HS-SPME-GC/MS analysis showed that most volatile components, such as pyrazines, furans (except furfural), esters, pyrrole, pyridine, and most aldehydes, increased from light to dark roasting, and this was significantly evident in CB coffee compared with UHP. The content of volatile components in UHP coffee was significantly (P<0.05) higher than that in CB coffee at the same degree of roasting, especially with dark roasting. The combination of orthogonal partial least squares-discriminant analysis (OPLS-DA) and principal component analysis (PCA) indicated that the distance between coffee samples at different degrees of roasting under CB coffee was greater than that under UHP coffee. However, the distance between these two extraction methods at medium roasting was evidently closer than that at light and dark roasting. Moreover, 15 representative differential compounds, such as were Hazelnut pyrazine, linalool, butane-2,3-dione, 3- methylbutanal found by the calculation of odor-active values (OAVs) indicating the main contributing compounds to odor. Overall, the effect of roasting degrees on UHP coffee was less than that on CB coffee, which was consistent with the results of physicochemical characteristics, volatile components, and sensory evaluation.

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more “clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient’s cancer cells. Clonally mutated proteins can potentially be targeted by inhibitors or E3 ligase small molecule glues, but developing new small molecule drugs for each patient is not feasible currently. Achilles Therapeutics is currently the only company specifically targeting clonal mutations. However, they are doing so with tumor-derived T cells. To address the potential limitations of immunotherapy, I have devised another approach for exploiting clonal mutations, which I call “Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement” (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

The proliferation of intelligent monitoring devices has led to the widespread adoption of background extraction technology across a multitude of domains, including intelligent transportation, video surveillance, human-computer interaction, and medical diagnosis. In this work, the model employs a multi-layer convolutional neural network structure, which enables the extraction and fusion of scene features from different scales in a layer-by-layer manner. This approach facilitates the comprehensive capture of complex scene information. The convolutional network comprises multiple layers, with each layer responsible for extracting features at a specific scale. The shallower layers capture more detailed feature information, whereas the deeper layers focus on more global scene features. The strategy of multi-scale feature fusion allows the model to fully capture multi-level and multi-dimensional information in the context of large-scale scenes. Furthermore, the incorporation of an attention mechanism enables the model to adaptively allocate attention to salient regions, thereby enhancing its capacity to discern intricate scenes by assigning greater significance to pivotal features. The experimental results demonstrate that the proposed method is effective in practice, as evidenced by its performance on public datasets.

Cancer and infectious diseases are two of the world's major public health problems. Gemcitabine (GEM) is an effective chemotherapeutic agent against several types of cancer. In this study, we developed macrocapsules by incorporating GEM into a chitosan matrix blended with magnetite and zeolite. The physico-chemical characterization of the precursor materials and the new delivery system was carried out by HRTEM-ED, XRD, FESEM-EDS, FT-IR, TGA, encapsulation efficiency (%E.E.) and release profiles at pH 7.4 and 5.0. Cell viability tests on A549 and H1299 cell lines and microbiological properties against staphylococcal strains were performed. Our results revealed the successful production of hemispherical capsules with an average diameter of 1.22 mm, a rough surface and characteristic FT-IR material interaction bands. GEM encapsulation rates exceeded 80%, and release profiles were well-controlled over 24 hours at tested pH levels. Notably, cell viability in H1299 cells was lower than the free GEM control. Moreover, the formulation exhibited potent antimicrobial activity against Staphylococcus epidermidis, highlighting its dual action as a chemotherapeutic and antimicrobial agent. This dual effect underscores the potential of these macrocapsules as innovative delivery system for treating lung cancer in patients who are also at risk of infectious diseases and who are immunosuppressed.

European Union (EU) regulations on in vitro diagnostics (IVD) and on serious cross-border threats to health provide for the establishment of European Reference Laboratories (EURLs) and their harmonisation and cooperation with National Reference Laboratories (NRLs). While the EURLs under the IVD Regulation will be operational by 1 October 2024, the EURLs under the Regulation on serious cross-border threats to health will be operational by January 2025. Although NRLs may have been operating for a long time on the basis of national legislation, they should now cooperate with each other and with EURLs in a network of centres of excellence for the authorisation and post-market surveillance of IVDs and for the epidemiological surveillance and control of communicable diseases. The term "reference laboratory" has long been used colloquially to refer to many kinds of laboratories, regardless of their tasks, competencies, responsibilities and designation. To clarify the roles and functioning of EURLs and NRLs, we evaluated the relevant current EU provisions and compared the findings with those of reference laboratories designated by other organisations, calibration (reference) laboratories and referral laboratories, which are simply referred to as "reference laboratories".

Drought and water scarcity are significant factors limiting the development of China's maize industry. Deep sowing, as a method to mitigate drought and preserve soil moisture and seedlings, can effectively mitigate the adverse effects of drought stress on their growth. However, deep sowing can influence the emergence of maize seedlings and has a certain impact on their growth and development. To investigate the physiological and transcriptomic changes in maize inbred lines under deep sowing stress, and the alleviation effects of exogenous hormones, this study investigated the response of mesocotyl in deep-seeding tolerant maize inbred line Qi319 and deep-seeding sensitive maize inbred line Zi330 to deep-seeding stress under exogenous MeJA treatment. The physiological and transcriptomic mechanisms underlying the alleviation of deep-seeding stress by exogenous MeJA were elucidated. Results showed that compared to normal sowing depth, mesocotyl length (MES), mesocotyl and coleoptile length (MESCOL) significantly increased under deep-seeding stress for both inbred lines, while seedling length (SDL) was significantly inhibited. However, after adding 1.5 μmol·L^-1 MeJA, MES, MESCOL, and SDL significantly increased compared to deep-seeding stress alone. Exogenous MeJA promoted cell elongation, enhanced mesocotyl length, and improved seedling emergence ability. RNA-Seq sequencing revealed differentially expressed genes (DEGs). Under deep-seeding stress compared to normal sowing depth conditions, 1248 DEGs were identified in Qi319 and 1288 DEGs were identified in Zi330. After adding exogenous MeJA under deep-seeding stress compared to normal sowing depth with exogenous MeJA treatment conditions, 538 DEGs were identified in Qi319 and 2284 DEGs were identified in Zi 330. GO enrichment analysis showed that differentially expressed genes were mainly concentrated in biological processes, cell components and molecular functions. KEGG enrichment analysis showed that differentially expressed genes were mainly concentrated in transport and catabolism, signal transduction, amino acid metabolism and lipid metabolism processes. Compared with the deep-seeded treatment, 12 differentially expressed genes were co-expressed in the two inbred lines under exogenous MeJA treatment, and 10 key genes, including ornithine decarboxylase, terpene synthase 7 and ethylene reaction transcription factor 11, were screened out. Our findings elucidate the molecular mechanism underlying maize's tolerance response to deep seeding and offer valuable insights into candidate gene resources for improving deep seeding tolerance in maize.

Telemedicine has become an interesting research topic in recent years, especially since the start of the COVID-19 pandemic. This article conducts research using a systematic literature review to identify paradoxes in telemedicine services. The research method follows the steps in a systematic literature review, by accessing the Scopus journal database to search for relevant articles between 2018 and 2024. The selected articles were selected based on certain inclusion and exclusion criteria, resulting in 28 relevant articles which were then analyzed to understand findings related to paradoxes in telemedicine services. The research results show four main clusters of paradoxes in telemedicine research, namely health services, health quality, the COVID-19 pandemic, and technology. Each cluster shows complex opportunities and challenges in efforts to improve health services through telemedicine. Understanding the clusters for each article can then be mapped to the organizational categories in the Dynamic Equilibrium Model. In conclusion, this study provides a comprehensive insight into the paradoxes in telemedicine services, highlighting the importance of understanding the various aspects involved in the adoption and implementation of this technology. With a better understanding of this paradox, it is hoped that society and health practitioners can overcome the challenges and exploit the opportunities offered by telemedicine to improve the accessibility and quality of health services in the future.

Background: The absence of interdental papillae in dental prosthetics often results in unsatisfactory esthetic outcomes, such as black triangles and elongated clinical crowns. Although previous research has shown that gingival papillae can regenerate in a coronal direction, the mechanisms behind this phenomenon are not fully understood. Various theories have been proposed as potential explanations. Materials and Methods: This study evaluated several factors potentially influencing papilla growth, including adjacent elements, buc-cal-lingual papilla width, contact point position, convergent neck, crown overcontour, and intraoral negative pressure. A conceptual map was created to organize these factors, followed by their classification using a modified Overton Window. The principle of parsimony (Occam's Razor) was applied to identify the most plausible cause-related factors, categorizing them as causal relationship factors, filtered out factors, essential factors, or influencing factors. A mind map was used for visual grouping. Results: The analysis identified intraoral negative pressure as the most plausible cause-related factor for spontaneous papilla growth. Factors such as inflammation and drug-induced hyperplasia were excluded due to their association with unhealthy tissue. Other factors were classified as essential or influencing, but without direct causal links to papilla growth. Conclusions: Intraoral negative pressure is likely a key contributor to spontaneous papilla growth around implants. This finding, supported by abductive reasoning and the exclusion of less plausible factors, offers a new direction for enhancing esthetic outcomes in dental prosthetics, though further research is needed to confirm this causal relationship.

Olivine-like NaFePO4 glasses and nanocomposites are promising materials for cathodes in sodium batteries. Our previous study concerned the influence of high pressure on DC electric conductivity of NaFePO4 glasses. This work presents the results of AC measurements of glasses and nanocomposites from pressure treatment. Depending on the temperature range, the electronic conduction mechanism changed from variable range hopping (between Fe2+/Fe3+centers) to phonon-assisted hopping. For DC electric conductivity the portrayal via the classic Mott’s Variable Range Hopping is limited to low temperatures. Spectra of AC conductivity for glasses and pressure-formed nanocomposites fulfill Jonscher’s scaling law with power exponents ranging from 0.3 to 0.9 depending on temperature and the electron hopping mechanism. Due to the decrease in distance between hopping centers, an increase of AC conductivity around 2-3 orders of magnitude was observed after high pressure-high temperature treatment. Up to 200 K temperature dependencies of AC conductivity follow the pattern suggested by Mott's theory. Above that temperature corresponds to phonon-assisted hopping with activation energies EAC≈0.40 eV (for glass: amorphous solid) and EAC≈0.18 eV (for glass + nanocrystallites nanocomposite). Notable that they are considerably lower than values of EDC for DC conductivity. Results obtained show that high-temperature compressing, just below the glass temperature, significantly leads to a stable decrease in distance between hopping centers related to nanocrystallites in a glassy matrix. Consequently, it leads to an essential rise in electric conductivity and volumetric capacity. AC spectra of electronic conductivity are disturbed by the conduction of Na+ mobile ions, which impacts polaron conductivity and can be a limiting factor for conductivity.

Small wind turbines placed at City locations are affected by variable speed winds that frequently also change the direction. Architectural constructions, buildings of different height and abrupt orography of Cities make the winds that occur at City locations, more variable than in flat lands or at sea. However, performance of Small-wind turbines under this type of variable winds is not deeply studied in specialized literature. Therefore, this article analyses this important issue, also considering three types of power conversion configurations utilized in small-wind turbines; the generally used Maximum Power Point Tracking (MPPT) configuration, the simple only-rectifier configuration and an intermediate configuration in terms of complexity called Pseudo-MPPT. This general-purpose analysis is applied to a specific type of wind turbine, i.e. the Ayanz wind turbine with screw blades, which presents very adequate characteristics for city locations such as; safety, reduced visual and acoustic impacts and birds’ casualties avoidance. Thus, a wide simulation and experimental tests-based analysis is carried out, identifying which are the main factors affecting to the maximization of energy production of small-wind turbines in general and the Ayanz turbine in particular. It is concluded that depending how the wind turbine is designed in terms of these identified main factors, the simple Pseudo-MPPT power conversion configuration could even extract more energy than more complex MPPT configurations, especially in quickly varying wind situations.

Transcriptomes from stem-inoculated Scots pine saplings were analyzed to identify unique and enriched H. annosum transcripts in the early stages of infection. Comparing different time points since inoculation identified 131 differentially expressed H. annosum gene with p values ≤ 0.01. Our research supports the results of previous studies on the Norway spruce – Heterobasidion annosum s.l. pathosystem, indicating the role of carbohydrate- and lignin degradation genes in pathogenesis at different timepoints post inoculation and the role of lipid metabolism genes (including but not limited to the delta-12 fatty acid desaturase gene previously reported to be an important factor). The results of this study indicate that malic enzyme could be a potential gene of interest in the context of H. annosum virulence.

This study examines stress distributions in adhesive joints under various loading and temperature conditions. Finite element analysis (FEA) was employed to compute the peel and shear stresses at the adhesive interface and bondline mid-section. Dependency analysis shows that mid-section peel stress significantly impacts the experimental shear strength of SLJs more than shear stress. This insight highlights the need to carefully analyze peel stress and bending moment factors. The analytical solutions proposed by Goland and Reissner were analyzed with modifications by Hart-Smith and Zhao. Hart-Smith’s approach performed more effectively, especially when the adhesive layer thickness (t_a) is 0.5 mm and the overlap length to thickness ratio (c/t_a) is ≥20. FEA revealed stress distributions at the adhesive/adherend interface and bondline mid-section. DP490 adhesive joints exhibited lower stresses than EA9696. Temperature variations significantly affected joint behavior, particularly above the adhesive’s glass transition temperature (T_g). Both EA9696 and DP490 adhesive joints displayed distinct responses to stress and temperature changes. The parabolic and biquadratic solutions for functionally graded adhesive (FGA) joints were compared. The biquadratic solution consistently yielded higher shear and peel stress values, with an increase ranging from 15% to 71% compared to the parabolic solution at various temperatures because of larger gradient of the Young's modulus distribution near the overlap ends. The ratio of peak peel stress to peak shear stress suggests selecting an adhesive with a superior peel strength or primarily reducing the peak peel stress by functionally grading is advisable, particularly if the adhesive is brittle. Comparison of stress distributions emphasize the importance of selecting adhesives based on stress type, temperature, and solution methods in optimizing adhesive bonding applications. These findings provide valuable insights for thermomechanical applications where thermal stimuli may be used for controlled debonding.

A comparative study of the photocatalytic decoloration of methylene blue (MB) dissolved in water was conducted, using three semiconductor oxides: zinc oxide (ZnO), tin oxide (SnO2) and titanium dioxide (TiO2) in the form of thin films and varying their thickness ~ 100, 200, and 300 nm for each film. All the films were deposited using the cost-effective dip-coating technique, at moderate temperature processing (400 °C) with sol-gel solutions on cheap glass substrates. The structural, morphological, and compositional properties of the films were analyzed by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Raman spectroscopy, respectively. The degradation of MB was studied by varying both thickness and type of semiconductor oxides through measurements of optical absorbance of decolorated liquid by photocatalytic process. Structural analysis shows that ZnO and SnO2 films were polycrystalline with preferential growth of (002) and (110) planes respectively, whereas, an amorphous structure was observed for TiO2 films. In addition, morphological properties confirms that the surfaces of all the films are conformed with nano grains in round and irregular shapes. Based on all results reported in this work, that authors believe that the degradation efficiency of MB depends on the thickness of the film and the type of semiconductor material used as a catalyst. The highest degradation efficiencies were recorded with an exposure time of 120 min and with an initial concentration of 10 mg/L for ZnO, SnO2, and TiO2 films were: 100, 88 %, and 76 %, respectively.

Burnout in healthcare affects the quality of patient care. In 2020, Mayo Clinic implemented Advanced Care at Home (ACH), a new hospital-at-home program. We aimed to assess burnout levels among ACH providers, analyzing data from quarterly surveys. Physicians and nurse practitioners registered in ACH completed a 16-question anonymous survey distributed via email. Ten questions from the original survey used the Maslach Burnout Inventory to measure the three domains associated with burnout: depersonalization, emotional exhaustion, and personal achievement. We conducted a descriptive analysis using frequency distribution and percentages. A total of 27 providers participated, with response rates of 38%, 23%, and 66% in the first, second, and third quarters. Over 75% of the participants responded satisfactorily to nine of the ten questions associated with the risk of burnout. Moreover, 77% of providers felt joyful at work "always or most of the time." Of the 74% of participants who responded to the question about feeling burned out from work, 48% of the participants "strongly” or “somewhat” disagreed, while only 26% "strongly” or “somewhat” agreed. Mayo Clinic's ACH has demonstrated low levels of burnout among providers, positively impacting the well-being of healthcare workers and contributing to a high standard of patient care.

This study explores the industrial property market in Hong Kong, a sector characterized by its unique features and atypical market behaviour. Particularly, this research employs machine learning techniques to predict property prices based on a set of features, including location, square footage, floor level, accessibility to mass transit railway station and the like. To ensure transparency and understanding, the Shapley value is employed to quantify the relative importance of each feature in predicting property prices. Our analysis reveals the existence of non–linear relationships among these features, as demonstrated by the wide distribution of SHAP values for most features, which are illustrated in a beeswarm plot that span both sides of the baseline. This finding indicates a complex interaction among such features as square footage, age, floor level, carpark, proximity to mass transit railway stations, location, and property prices. The results contribute valuable insights into the relationships between industrial property characteristics and their corresponding values, thereby equipping stakeholders with enhanced understanding of the market to support informed decision–making.

In physics we construct idealized mathematical models in order to explain various phenomena which we observe or create in our laboratories. In this article, I recall how sophisticated mathematical models evolved from the concept of a number created thousands years ago and I discuss some challenges and open questions in quantum foundations and in the standard model. We liberated nuclear energy, landed on the Moon and built ‘quantum computers’. Encouraged by these successes many believe, that when we reconcile the general relativity with the quantum theory then we will have the correct theory of everything. Perhaps, we should be much more humble. Our perceptions of reality are biased by our senses and by our brain bending them to meet our priors and expectations. Our abstract mathematical models describe only in an approximate way different layers of physical reality. To describe the motion of a meteorite we can use a concept of a material point but the point-like approximation breaks completely, when the meteorite hits the Earth. Similarly, thermodynamic, chemical, molecular, atomic, nuclear, elementary particle layers of physical reality are described using specific abstract mathematical models and approximations. In my opinion, the theory of everything does not exist.

The development of the finite element method (FEM) combined block polynomial interpolation with the concepts of finite difference formats and the variation principle. Because of this combination, FEM overcomes the shortcomings of traditional variation methods while maintaining the benefits of current variation methods and the flexibility of the finite difference method. As a result, FEM is an advancement above the traditional variation methods. The aim of the study is to experimentally determine the thermal behavior of two stomatognathic systems, one control and the other presenting orthodontic treatment by means of a fixed metallic orthodontic appliance, both being subjected to several thermal regimes. In order to carry out this experimental study, we examined the case of a female subject, who was diagnosed with Angle class I malocclusion. The patient underwent a bimaxillary CBCT investigation before initiating the orthodontic treatment. A three-dimensional model with fully closed surfaces was obtained by using the InVesalius and Geomagic programs. Like the tissues examined in the patient, bracket and tube-like components, as well as orthodontic wires, can be included to these models. Once it is finished and geometrically accurate, the model is exported to a FEM-using program, such as Ansys Workbench. The intention was to study the behavior of two stomatognathic systems (with and without a fixed metallic orthodontic appliance) subjected to very hot food (70 ⁰C) and very cold food (-18 ⁰C). From the analysis of the obtained data, it was concluded that, following the simulations carried out in the presence of the fixed metallic orthodontic appliance, significantly higher temperatures were generated in the dental pulp.

Extracorporeal membrane oxygenation (ECMO) is increasingly used in intensive care units; however, ECMO can modify drug pharmacokinetics (PK), leading to underexposure and associated treatment failure. The aim of the present study was to determine the effect of ECMO on the PK of dexmedetomidine (DEX). In vivo rat models were developed, both of which involved a bolus injection of DEX and concentration monitoring. In the in vivo model experiment, rats which underwent ECMO were compared with a control group. PK analysis of in vivo data (noncompartmental analysis and nonlinear mixed-effects modelling) was carried out to determine the effect of ECMO. In vivo PK exploration showed that ECMO induced a decrease in DEX clearance. Because the effect of ECMO on the PK of DEX is not clinically significant, normal DEX dosing for critically ill patients should be effective for patients undergoing ECMO.

The LTTD process for highly concentrated crude oil-contaminated soil was studied to evaluate the remediation efficiency. In addition, the environmental impact difference between HTTD and LTTD was studied. OpenLCA software obtained from PE International was used to perform the analyses. The total ADP environmental impact of the HTTD process was 1.63E-04 MJ, whereas the total GWP impact was 4.14E+02 kg CO2-eq. In contrast, the LTTD process exhibits total ADP and GWP environmental impacts of 1.29E-04 MJ and 2.78E+02 kg CO2 eq, respectively. Analysis of the overall environmental impact reduction revealed that replacing the HTTD process with the LTTD process resulted in a total ADP reduction of 3.40E-05 MJ (20.5%) and a GWP reduction of 1.36E+02 kg CO2 -eq (32.9%). It is inferred that the LTTD treatment of contaminated soil can significantly reduce the environmental impact compared with conventional incineration and HTTD processes. Additionally, the LTTD-treated soil with coke or carbonized residue could act like biochar as a soil amendment. Approximately 50% of organic hydrocarbon contaminants are sequestered into coke or carbonized residues on the soil surface. With additional analyses of various oil-contaminated soils, the potential utility of LTTD-treated soils is expected to be maximized.

Background/objective: Tools to accurately and efficiently measure the dietary intake of Nigeria are lacking. We aimed to develop and assess the usability of a new online dietary assessment tool for Nigeria, myfood24 West Africa. Methods: We developed myfood24 West Africa database using data from existing food composition tables, back-of-pack labels of packaged foods and research articles. A 7-step approach was used: identified data sources, selected foods, processed/cleaned data, calculated nutrient content of recipes, created/allocated portion sizes, quality-checked database, and developed food accompaniments. To pilot myfood24 West Africa, we recruited 179 university staff living in Nigeria using a cross-sectional design; usability was assessed using a questionnaire that incorporated the System Usability Scale (SUS) and feedback session. Results: The database included 924 foods with up to 54 nutrients and 35 portion-size images allocated to foods. 60% of the data were sourced from the 2019 West Africa Food Composition Table, 17% from back-of-pack labels, 14% from the 2017 Nigeria Food Composition Table, 5% from generated recipes and 4% items from published literature. 30% (n=53) self-recorded their diet on their own and 1345 entries were made. The mean SUS score of 74 (95% CI: 68,79) indicated good usability. The feedback showed the tool was easy to use, educative, and included a variety of locally foods consumed. Conclusion: This new tool will enhance the dietary assessment of the Nigerian population. More work will cover more foods from other regions of Nigeria and West African countries.

The spread of false information can significantly harm public opinion, underscoring the importance of accurately identifying untrustworthy news. This paper presents an innovative machine learning (ML) tool, TMining, designed to evaluate news credibility and facilitate various text-mining tasks. By examining a range of ML methodologies alongside preprocessing techniques, we aim to boost the system's effectiveness. Our research meticulously assesses different datasets, highlights the impact of applying stemming techniques, and employs Local Interpretable Model-Agnostic Explanations (LIMEs) to shed light on the rationale behind model predictions. The outcomes reveal a notable enhancement in both the precision and clarity of the news verification process. The ultimate version of the model has been made available as an Application Program Interface (API), and its source code has been shared openly, encouraging further exploration and collaboration within the scientific community. This initiative advances our ability to discern manipulative context from fictitious content and promotes transparency and understanding in the domain of ML applications.

The purpose of this study was to investigate the effects of cognitive dual-tasking on gait initiation and sit-to-walk. Twenty-eight healthy young adults performed gait initiation and sit-to-walk under two conditions: while engaging in serial subtraction (dual-task) and without any additional task (single-task). Motion data were collected using a 10-camera optoelectronic motion capture system, synchronized with force plates and surface electromyography. We analyzed spatiotemporal parameters, center of mass displacement, center of pressure trajectory, and lower limb muscle activation patterns. We found that dual-task conditions significantly affected both gait initiation and sit-to-walk patterns, increasing the duration of transitions and mediolateral center of mass displacements, while reducing vertical center of mass displacements and forward propulsion. We also observed a more constrained and less efficient center of pressure path, with reduced posterior displacement during the weight shift phase. Muscle activation, particularly in the tibialis anterior and biceps femoris, decreased during dual-task conditions, indicating altered neuromuscular strategies. These findings suggest a shift in postural control demands and motor performance during dual-task transitions.

Keywords: construction; processes; optimization; polymers, carbon; emission; strategy.

An oceanographic cruise from southern Adriatic to the northern Ionian basins, during 2013 spring period, allowed us to describe spatial abundance and distribution of decapod crustacean larval assemblages with a multidisciplinary approach. Seventeen locations on the Apulian and Albanian shelves and offshore waters, including the Strait of Otranto, were sampled by BIONESS electronic multinet. In May 2013 a swarm of zoeae (11 Brachyura taxa, mostly at first instar, with Xantho granulicarpus at 87%) was recorded in the neuston of the Italian side. Decapod larvae were concentrated in the first 20-30 m surface layer, strongly linked to the thermocline and generally above the DCM, suggesting that they are involved in surface water circulation. The migratory behavior of decapod larvae in coastal stations is quite regular between 20 and 60 m depth and daily time independent. In offshore stations, migration is compatible with the day-night cycle, where a minimum WMD value is evident at about 20m at night. The availability of four satellite-tracked surface drifters in the same area and period of the larvae presence, represented a possibility to discuss the geographic dispersal of larvae linked to the surface circulation in successive days. Only one drifter crossed the south Adriatic passing from the Italian to the Balkan neritic area, employing about 40 days. The actual genetic homogeneity of many Brachyura coastal species populations on the opposite sides of the Adriatic Sea, suggests the existence of a genetic connection which should not rely exclusively upon larvae circulation and needs to be fueled by additional strategies of biological communication.

Objective: To develop and validate the short version of the JAEN Scale for use in women with Fibromyalgia Syndrome (FMS) to make the balance disorder measurement process more efficient. Methods: A Cross-sectional observational validation study was conducted. Fifty-six women with FMS and 44 healthy control were included. Certain items of the original tool were selected with the aim of 1) Improving internal consistency by reducing item redundancy 2) Obtaining a diagnostic capacity with an Area Under the ROC Curve (AUC) greater than 0.70 for discriminating FMS patients and fallers. The internal consistency, factorial validity, concurrent validity and diagnostic capacity of the new tool were analyzed. Results: Factorial analysis showed a two-factor structure that explained 72% of variance. Cronbach alpha coefficients of 0.904 were obtained for the total score of the JAEN-10 items. Concurrent validity analysis showed strong correlations of the JAEN-10 with other instruments that measured quality of life, postural balance or disability related to dizziness. The score of the JAEN-10 items showed an AUC of 0.858 with a sensitivity of 64.29 and a specificity of 95.45 for discriminating between FMS and healthy controls, and an AUC of 0.835 with a sensitivity of 90.48 and a specificity of 67.24 for discriminating between fallers and non-fallers.; Conclusions: The 10-item JAEN scale is a valid instrument for discriminating between subjects with or without FMS and between fallers and non-fallers. Its psychometric properties are good and similar to those of the original 20-item scale. Moreover, it is quicker to complete, which may be relevant in subjects with a tendency to experience fatigue.

The ECM is composed of a considerable number of biochemically and structurally diverse constituents. ECM is a highly dynamic system that constantly receives and sends biological, chemical and mechanical signals. Several studies suggest that mechanical signals derived from the extracellular microenvironment regulate skin regeneration and wound healing. We evaluated effects of a mixture of biomolecules extracted and purified from bovine colostrum on restoring the mechanical properties of ECM. Test measuring collagen contraction showed a significant difference in contraction activation in samples treated with the 2% colostrum derivative mixture compared to the control. The analysis of the supernatant showed an inhibition of metalloproteinase-2 expression and an increase in collagen secretion by fibroblasts in treatment samples. Our hypothesis is that the molecules extracted and purified from bovine colostrum restore the ECM environment qualitative and quantitative characteristics, thus guaranteeing through a mechanical action the restoration of the wound due to the transduction of the signal activated by the integrins.

This paper aims to present a robust computational technique utilizing finite difference schemes for accurately solving time fractional reaction-diffusion models, which are prevalent in chemical and biological phenomena. The time-fractional derivative is treated in the Caputo sense, addressing both linear and nonlinear scenarios. The proposed schemes were rigorously evaluated for stability and convergence. Additionally, the effectiveness of the developed schemes was validated through various linear and nonlinear models, including the Allen-Cahn equation, the KPP-Fisher equation, and the Complex Ginzburg-Landau oscillatory problem. These models were tested in one, two, and three-dimensional spaces to investigate the diverse patterns and dynamics that emerge. Comprehensive numerical results were provided, showcasing different cases of the fractional order parameter, highlighting the schemes' versatility and reliability in capturing complex behaviors in fractional reaction-diffusion dynamics.

Cell viability refers to the proportion of living, healthy cells within a given population. This information is crucial in any cell-based research, especially in toxicology. Over the past century, numerous methods for assessing cell viability have been developed. These methods can be categorized into five main types: non-invasive cell structure damage, invasive cell structure damage, cell growth, cellular metabolism, and cell membrane potential. Each method operates on different principles and has its own advantages and disadvantages, making it essential for researchers to choose the method that best fits their experimental design. Despite the variety of cell viability methods available, most rely on indirect measurements of cell viability, which may compromise their accuracy. In this sense, there is insufficient information regarding their accuracy, highlighting the need for researchers to investigate the accuracy of both existing and future methods.

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

Due to model errors caused by local variations in cloud precipitation processes, there are still significant uncertainties in current predictions and simulations of short-duration heavy rainfall. To tackle this problem, the effects of warming on cloud-precipitation efficiency was analyzed utilizing a weather research and forecasting (WRF) model. The analysis focused on a rainstorm corridor event that took place in July 2020. Rainstorm events from July 4 to 6 formed a narrow rain belt with precipitation exceeded 300 mm in the middle and lower reaches of the Yangtze River. Temperature sensitivity tests revealed that warming intensified the potential temperature gradient between north and south, leading to stronger upward motion on the front. It also strengthened the southwest wind, which also resulting in more pronounced precipitation peaks. Warming led to a stronger accumulation and release of convective instability energy. Convective available potential energy (CAPE) and convective inhibition (CIN) increased correspondingly with the temperature. The precipitation efficiency increased sequentially with 2℃ warming to 27.4%, 31.2% and 33.1%. Warming can affect the cloud precipitation efficiency by both promoting and suppressing convective activity, which may be one of the reasons for the enhancement of extreme precipitation under global warming. The diagnostic relationship between upward moisture flux and lower atmospheric stability during precipitation evolution was also revealed.

Incense is essential in religious ceremonies, even in relatively new religious movements such as New Age and Neopaganism. These garner little attention from ethnobotanists, although they trigger an international trade in wild-harvested plants. In this paper, we studied the botanical ingredients of smudge sticks (dried plant bundles burned for purification) in the Netherlands, and people’s motivations to use them posing the following questions: what plant species are included in smudge sticks? what are they used for? and are exotic plants preferred over native Dutch plant species? We visited online and physical shops in Dutch cities, acquiring a total of 29 different smudge sticks containing at least 15 species. We held semi-structured interviews with 11 users, vendors, and herbal experts, and collected data from 33 questionnaires. Salvia apiana L. was most frequently found, along with North American species of the genus Artemisia. The rise of the New Age movement resulted in North American ritual plant species being easily available in (online) shops and it being used for personal protection and cleansing. Despite its commercial demand there is no data regarding the pressure on wild populations, therefore, we call for the need to monitor the harvesting of these species in the wild.

Collapse calderas often experience large up and down movements, which rarely give rise to eruptions. The pattern of vertical deformation has generally an elliptical geometry, very close to a circular one. A simple and powerful method to explore second order anomalies of the volcanic caldera deformation patterns can enlighten important structural features. This method is here presented and applied to the case study of Campi Flegrei caldera ground deformation, representing a typical example of such a quasi-circular geometry, with dominant ground uplift occurring since 1950. Despite a markedly radial dependence of the vertical displacement, with a very constant shape in the time, we explore in the paper the second order anomalies, with respect to a purely radial behavior. To this aim, we have used a procedure based on the polynomial fit of the vertical displacement data, assuming they only depend on the distance from the maximum uplift point (i.e. deformation center); then, we have obtained anomalies map by subtracting from the theoretical deformation so determined the true data. We then obtain very peculiar results, which put in evidence a sharp separation between a less uplifted zone and a more uplifted one than expected, along a NE-SW alignment which approximately define the most seismically active area, in which most of the largest magnitude earthquakes occur. This very peculiar feature is likely to represent a main volcano-tectonic structure in the area, which can be of leading importance for evaluating both the highest seismic hazard area and the most likely zone of possible eruptive vent opening. The results obtained here indicate that the proposed method can be useful to analyze unrest related hazards.

This study quantitatively assessed the effectiveness of three main options for the adaptation of crop farming to climate change (i.e., shift of planting dates, increase/addition of irrigation, and resilient hybrids/cultivars) in a southern European country (Greece). The potential effect of each option on the yields of several crops in all Greek regions is estimated for 2021-2040 and 2041-2060 and compared with those under the historical local climate of 1986-2005, by using agronomic and statistical regression models, and data from different climatic simulations and climate change scenarios. Our results reveal that all the adaptation options examined have the potential to significantly reduce crop yield losses occurring under no adaptation, particularly during 2021-2040 when for many regions and crops more than half of the losses can be compensated for. Notably, in some cases during this period, the measures examined can lead to crop yields that are higher than those under the historic climate. However, the effectiveness of the measures was found to greatly diminish in 2041-2060 under very adverse climate change conditions, highlighting the dynamic nature of adaptation. The assessment of the effectiveness of combined adaptation options, and the evaluation of additional criteria (e.g., feasibility) represent main areas for future research.

This study analyzes groups about game performance elements and sport class composition in each country by utilizing official records provided by major international wheelchair basketball games. To achieve the objective of this study, major game factors were explored by analyzing descriptive statistics in each year regarding the latest trend of sport class composition and playing time of each sport class and conducting the difference test between the groups. To analyze performance details of international wheelchair basketball games, this study selected official records of 209 games of 24 teams that participated in major international wheelchair basketball games. A test for difference also was conducted to examine the sport class composition, playing time, and game details of each group. First, scoring factors directly affecting the game results were compared between the groups. The result of this difference test shows that the success rate of 2-point and 3-point shots was significantly different except for the free throw success rate. The numbers of assists, defense rebounds, and steals were significantly different. Second, the medal group was compared with the other group, the average class of the other group's participation in quarters was higher than that of the medal group and the difference was significant. Regarding the difference between groups in terms of game performance, the difference in playing time between the medal group and the other group was in the order of 2.5 points, 4.0 points, 3.0 points, and 1.5 points. Third, given the general trend in 2012 to 2022 international events, the sport class composition and para-athlete played minutes in quarterly participation changes.

Background/Objectives: This study aimed to identify various risk factors associated with breast cancer and explore different treatment strategies based on socio-economic, hormonal, and clinical perspectives.; Methods: We analyzed socio-economic, hormonal, genetic, and clinical variables using data from 356 questionnaires obtained from breast cancer patients at Hassan II Regional Hospital in Agadir, Morocco ; Results:The study reveals that the average age of breast cancer patients is 50 ± 10.72 years, with a mode of 47 years and an age range from 29 to 94 years. Notably, women aged 38 are most frequently diagnosed with triple-negative breast cancer. Significant socio-economic trends were observed among the participants, with the majority being housewives (91%) and nearly half residing in rural areas (48.60%). High rates of illiteracy (74.72%) and financial difficulties (54.2%) pose challenges in accessing healthcare services. Psychological distress is prevalent, with 40.7% experiencing anxiety and 30.1% experiencing sadness. The use of oral contraceptives varies, with implications for breast cancer risk. Additionally, statistics on menarche and menopause suggest hormonal influences on breast cancer development. Histological analysis indicates a predominance of grade II invasive ductal carcinoma and left breast localization. Metastases are present in nearly 38.20% of cases. Notably, surgery as the primary treatment effectively treats medium-sized tumors while limiting metastasis. Furthermore, a comparison of treatment strategies reveals a preference for letrozole among postmenopausal patients and tamoxifen among premenopausal patients; Conclusions:These findings highlight the complexity of breast cancer risk factors and therapeutic approaches, emphasizing the importance of personalized care and targeted interventions.

Facial artificial intelligence (AI) skincare applications offer patients simple and effective means of obtaining quantitative information regarding their skin characteristics. Advances in AI may facilitate dermatologic assessments by providing accurate and reliable scores for common skin concerns. The objective of our study was to assess the effect of different lighting on facial characteristic scores produced by an iPad-based AI skin analysis system. Participants were recruited from dermatology clinics. Images were captured using an AI skincare app in different lighting settings: below average lighting (L1), standard room lighting (L2), and enhanced studio lighting (L3). Raw scores produced for twenty facial characteristics were recorded. Higher raw scores indicated better skin health. Scores were compared between the three lighting conditions. Below average lighting had the highest mean raw scores for facial characteristics (79.67 ±10.56). Mean raw scores were lowest for enhanced studio lighting conditions (74.43 ±10.24). The difference in scores produced by the different lighting conditions was not statistically significant (p=0.79). Enhanced studio lighting did not appear necessary as scores were similar without the additional lighting. The application used in our study may serve as a cost-effective and convenient tool both within and outside clinical settings allowing enhanced quantitative analysis of facial characteristics.

A well known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e.\ the signals must be sufficiently similar. In the present technical note we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude, and flight speed. The method can be extended to be operated in real time.

Owing to the risk of atypical femoral fractures, total hip arthroplasty presents unique challenges for patients with ipsilateral osteoarthritis and localized periosteal thickening in the femoral subtrochanteric region. Stem length selection is critical for minimizing stress concentration in the thickened cortex to avoid such fractures. Herein, we report the case of a 78-year-old woman with ipsilateral hip osteoarthritis and localized subtrochanteric periosteal thickening. Preoperative planning included finite element analysis to assess stress distribution across various stem lengths. Simulation aimed to determine the optimal stem length to span the cortical thickening and reduce the risk of postoperative complications. The results of finite element analysis indicated that a stem length of &gt;150 mm was required to effectively reduce the stress at the site of cortical thickening. A 175-mm stem was selected for total hip arthroplasty, which provided a favorable stress distribution and avoided the risk of stress concentration. Therefore, in cases of ipsilateral osteoarthritis with localized subtrochanteric periosteal thickening, finite element analysis can be valuable for preoperative planning to determine the optimal stem length, thereby reducing the risk of atypical femoral fractures. Further studies with multiple cases are recommended to validate these findings and improve surgical outcomes.

Background: Diabetic foot sepsis (DFS) accounts for approximately 60% of hospital admissions in patients with diabetes mellitus (DM). Individuals with DM are at risk of severe COVID-19. This study investigated investigated factors associated with major amputation and mortality in patients admitted with DFS during the COVID-19 pandemic. Methods: Demographic information, COVID-19 and HIV status, clinical findings, laboratory results, treatment and outcome from records of patients with diabetic foot sepsis. The chi-square test, Fisher’s test, Student t-test or Mann-Whitney compare findings when appropriate. Multivariate logistic regression to determine factors that were associated with major amputation and mortality. Results of logistic regression were compared with outputs from analysis using machine learning algorithms. Kaplan-Meier survival curve to compare survival between COVID-19 positive and negative patients. Statistical was a p-value below 0.05. Supervised machine learning algorithms were used to compare their ability to predict major and deaths. Results: Overall, 114 records were found and 57.9% (66/114) were of male patients. The mean age of the patients was 55.7 (14) years and 47.4% (54/114) and 36% (41/114) tested positive for COVID-19 and HIV, respectively. The median c-reactive protein was 168mg/dl, urea 7.8mmol/l and creatinine 92µmol/l. The mean potassium level was 4.8±0.9mmol, and glycosylated haemoglobin 11.2±3%. The main outcomes included major amputation in 69.3% (79/114) and mortality of 37.7% (43/114) died. AI. The level of potassium, urea, creatinine and HbA1c were significantly higher in the deceased. Conclusions: The COVID-19 pandemic led to an increase in the rate of major amputation and mortality in patients with DFS. The in-hospital mortality was higher in patients above 60 years of age who tested positive for COVID-19. The Random Forest algorithm of ML can be highly effective predicting major amputation and death in patients with DFS.

Hands-on gardening is linked with healthy eating behaviors, increased outdoor activities, and overall well-being. Although these positive associations are widely established for adults and school-agers, little evidence can be found on how such relationships may extend to early childhood, especially in the preschool years (3-5 years). One recent study conducted in North Carolina (NC) showed that participating in hands-on gardening significantly increased preschoolers’ accurate identification of fruits and vegetables (FV) and FV consumption compared to children who did not participate in hands-on gardening, but no association was found between participation in hands-on gardening and children’s liking (eating preferences) of FV. FV identification and liking during the early years may lead to lifelong healthy eating behaviors and preferences, making hands-on gardening a critical health intervention in early childhood environments, especially in childcare centers where a majority of the 13 million children in the United States between the ages of 0 and 5 spend most of their waking hours. This research aimed to investigate how hands-on gardening in childcare centers may impact preschoolers’ (3-5 years old) FV knowledge (identification) and liking in a semi-arid climate zone with a high concentration of Hispanic families by conducting experimental research with eight childcare centers and one hundred forty-nine children (n=149) in Lubbock County located in West Texas. Findings showed changes in average liking scores are generally positive in the experiment group of children who participated in hands-on gardening (compared to the control non-gardening group), implying improved liking. The findings indicate that the benefits of hands-on gardening in childcare centers for enhancing healthy eating preferences are evident even in a semi-arid climate zone, where high temperatures and limited rainfall present significant gardening challenges. This research underscores the importance of integrating hands-on gardening into childcare programs, highlighting its potential as an effective obesity prevention strategy not only within the U.S. but also in other regions with similar environmental constraints.

Reliable access to electricity has become a necessity worldwide, and without it, no country can operate health systems and achieve sustainable development goals (SDGs). However, while developed countries have been successfully electrified for many decades, most developing countries have fallen short, contributing to significant impacts, particularly the health sector. The present study explores the relationship between electrification and health vulnerability in developing countries between 1990 and 2020 using the Feasible Generalized Least Square (FGLS) approach. The varied electrification across countries motivates the use of non-linear associations between electrification and health vulnerability. We demonstrate that electrification and health vulnerability have an inverted U-shaped association. Further analysis indicates that most developing countries have achieved a mature level of an inverted U-shaped curve, showing a reduction in health vulnerability with increasing electrification. There are few developing countries, mainly African countries, struggling to reach maturity. The results of this study indicate the need for increased access to electrification, in combination with a reduction in the use of biomass and fossil fuel feedstocks, to mitigate health vulnerability in developing countries.

N-Nitroso-3-morpholinosydnonimine 3 was prepared by nitrosation of SIN-1 and characterized by 1H-NMR, 13C-NMR and HRMS. Its structure, confirmed by single crystal X-ray diffraction analysis, was found in agreement with its mesoionic and aromatic character. Unlike SIN-1, which releases both nitric oxide and superoxide radical, decomposition of this nitrosylated sydonimine could yield nitric oxide as the only decomposition product, and thus without the formation of toxic peroxynitrite.

Klippel-Feil disease is a condition characterized by a defect in the spine, consisting in the fusion or non-separation of two or more vertebrae of the cervical tract. It usually affects 1 every 50.000 newborns, and the pathogenesis remains unknown to date, although the role of certain genes deputed in segmentation processes is being studied. A single case of gene Myosin Heavy Chain 3 (MYH3) mutation is described by researchers. Affected patients are often characterized by a relatively short neck and, therefore, poor mobility, a low hairline and obesity and may have other health problems of different nature. The frequent presence of comorbidities worsens the quality of life of these young patients. The following case describes the synergistic effect of Incobotulinum toxin type A and physiotherapy in a small patient with MYH3 mutation-related Klippel-Feil Syndrome (KFS) complicated by bilateral paraplegia, to improve the spasticity condition of the lower limbs. To assess improvements over time, the patient underwent rating scales to determine spasticity (Modified Ashworth Scale: MAS), the neck’s range of motion (ROM), and muscle tone by using MyotonProÒ. Specifically, measurements were taken on the day of the first medical examination (T0), the month after the injection and the startup of therapeutic exercise (T1), at three months (T2), and then once a month for a total of 6 months (T3, T4 and T5). This therapeutic approach led to entirely satisfactory results with the child’s well-being, prolonged until the sixth month and with a total absence of any side effects.

Extracellular electron transfer (EET) is key to the success of microbial fuel cells (MFCs). Clostridium sp. often occurs in MFC anode communities, but its ability to perform EET remains controversial. We have employed Clostridium pasteurianum DSM 525 as biocatalyst in a glycerol-fed MFC, designated MFC_DSM. We have also followed the EET of this biocatalyst in the presence of a mediator, namely soluble neutral red (NR), soluble methyl viologen (MV), neutral red film (FNR), or methyl viologen film (FMV). MFC_DSM provided power and current densities (j) of 0.39 mW.cm^-2 and 2.47 mA.cm^-2, respectively, which evidenced that the biocatalyst performs direct electron transfer (DET). Introducing 150.0 µM NR or MV into the MFC_DSM improved the current density by 7.0- and 3.7-fold (17.05 and 8.45 mA.cm^-2), respectively. After 20 cyclic voltammetry (CV) cycles, the presence of FNR in the MFC_DSM anodic chamber provided almost twofold higher current density (30.76 µA.cm^-2) compared the presence of NR in the MFC_DSM. Introducing MV or FMV into the MFC_DSM anodic chamber gave practically the same current density after 10 CV cycles. The MFC_DSM anodic electrode might interact with FMV weakly than with FNR, so FNR is more promising to enhance C. pasteurianum DSM 525 EET within MFC_DSM.

Background. The multisystemic features of Down syndrome (DS) in children are accompanied by an immunodeficiency, making them susceptible to infections and immune dysregulation with autoimmune, allergic, inflammatory, and hematological complications. This study was aimed at a better understanding of the abnormalities within the B and T cell compartments and their correlations with clinical immunophenotypes. Methods. Medical records of 35 DS children were retrospectively reviewed, referring to clinical symptomatology including history of infections, immune dysregulation disorders, and humoral and cellular immune response. Results. While the etiology of respiratory tract infections included typical viral and bacterial pathogens, SARS-CoV2-induced inflammatory disease and syndromic immunodeficiency contributed significantly to deterioration of the clinical course. Allergic diseases in the form of asthma, allergic rhinitis, and alimentary allergy were the most frequent manifestations of immune dysregulation and were followed by autoimmune disorders, such as Crohn disease, celiac disease, autoimmune thyroiditis, and alopecia, as well as inflammatory disorders, balanitis xerotica obliterans and lymphadenopathy, and a hematological disorder of myelopoiesis. Deficiency of serum immunoglobulin levels, reduced numbers of naïve B cells, and non-switched memory B cells along with low naïve T helper cells and significantly reduced regulatory T helper cells were the most prominent immune abnormalities. Conclusions. The loss of naïvete in B and T lymphocyte compartments with a deficiency of regulatory T cells may be underpinning pathomechanisms for the skewed immune response. The clinical immunophenotype in DS is complex and represents syndromic inborn error of immunity with immune dysregulation.

This study investigates job satisfaction, burnout, and well-being among first-generation migrant physicians in anesthesia and intensive care medicine in Germany, comparing them to their native German counterparts. Utilizing a cross-sectional survey design, the study collected data from 513 physicians, 110 of whom identified as having a migration background. Job satisfaction was measured using the German version of the Warr-Cook-Wall (WCW) Job Satisfaction Scale, burnout was assessed with the Copenhagen Burnout Inventory (CBI), and well-being was evaluated using the WHO-5 Well-Being Index. The job satisfaction ratings revealed no significant differences between migrant and German physicians in most dimensions, including physical workload, freedom to choose work methods, satisfaction with colleagues, responsibility, income, skill utilization, and variety in work tasks. However, migrant physicians reported significantly higher satisfaction with recognition received for their work and lower dissatisfaction with working hours. Burnout assessments showed that migrant physicians experienced higher psychological strain, perceiving every work hour as more exhausting and having significantly less energy for family and friends. Notably, migrant physicians reported higher difficulty and frustration in working with patients. Well-being ratings indicated that migrant physicians felt less energetic and active but found their daily life more filled with interesting activities. The findings underscore the unique challenges faced by migrant physicians, particularly in terms of recognition and patient-related burnout. These results highlight the need for targeted interventions to support migrant physicians, including cultural competence training and flexible working hours to enhance their job satisfaction and overall well-being. Addressing these issues is crucial for maintaining the quality of patient care and the occupational health of migrant physicians in Germany.

As the demand for long-distance flights continues to increase, supersonic transport (SST) has once again become a hot research topic. However, due to its uniqueness, there was few corresponding evaluation methods to compare the supersonic civil aircraft with common subsonic aircraft. This paper proposed an evaluation method for the competitiveness of supersonic civil aircraft based on the Analytic Hierarchy Process (AHP). Key indicators were selected to form a competitiveness evaluation model from the perspective of four criterion factors of economy, comfort, adaptability, and environment. The evaluation method proposed in this paper could reflect characteristics of supersonic civil aircraft and other subsonic aircraft, and effectively compare their competitiveness. This work can be used to evaluate the social acceptance of supersonic civil aircraft and provide reliable decision-making support for airlines' design work.

Food insecurity remains a significant developmental challenge, particularly in rural areas, despite ongoing efforts to mitigate it. To better understand the persistence of this issue, this study investigates the causes of household food insecurity and the coping strategies employed by households in Zorkor Goo, Zorkor Kanga, and Zorkor Kadaare communities within the Bongo District of Ghana’s Upper East Region. A descriptive cross-sectional survey was conducted, sampling 196 households systematically from these communities. Data were collected through a structured questionnaire covering socio-demographic factors, causes of food insecurity, household coping strategies, and dietary intake. The analysis was performed using SPSS (Version 21.0), with food security status and dietary intake assessed via the FANTA Household Food Insecurity Access Scale (HFIAS) and Food Consumption Score, respectively. The study identified key factors contributing to food insecurity, including soil infertility, poor rainfall patterns, food spoilage, extravagant funerals, large family size, high unemployment, and lack of education. Major coping strategies among households included meal skipping, reducing meal size and frequency, migration, asset sales, and basket weaving. The findings revealed that 96.4% of households were severely food insecure, and over two-thirds (67.3%) exhibited poor dietary consumption. Notably, household employment levels, education, and food consumption scores were significantly associated with food insecurity (P&lt;0.001). These findings underscore the need for targeted interventions addressing the root causes of food insecurity and enhancing household resilience in these communities.

This study employed the Allium cepa bioassay to evaluate the toxic effects of contaminants in the Yucatan aquifer. Seven monitoring wells were studied during September and October 2021. Nutrient concentrations showed significant variation between sites, with samples closer to the coast (P3 and P7) presenting higher ammonia and phosphate concentrations. The pesticides found at the highest concentration were δ-HCH and chlorpyrifos, with 141.44 and 175.92 ng/L, respectively. Heptachlor and aldrin were present in sites P4oct and P2sept. Interestingly, DDT values were highly correlated with caffeine concentrations. Acenaphthylene, acenaphthene, fluorene, phenanthrene, and the sum of B(k)fluoranthene and B(b)fluoranthene presented the highest prevalence. B(k)fluoranthene and B(b)fluoranthene were the PAHs found at the highest concentration. The results of the A. cepa bioassay indicated no nuclear abnormalities. The study also found no statistical differences in the mitotic index, root length, biomarkers of oxidative stress, and inhibition of B-esterases between sites and controls. In summary, the wells sampled in the present study had low concentrations of contaminants that can be used as a proxy of anthropogenic discharges; the lack of effect in the biomarkers used at organism, cellular, and biochemical levels indicated no toxic effect on A. cepa roots.

Objectives: Epidemiologic and experimental animal studies have shown that stress can alter tumor growth and that adrenergic fibers from the sympathetic nervous system, acting through stromal β2-adrenergic receptors, promote tumor cell survival during the initial phases of cancer development. Recent epidemiological data suggest that beta blocker intake improves survival of prostate cancer patients. Methods: Signaling mediated by β-adrenergic receptors promotes neuroendocrine differentiation in prostate cancer cell line. Although neuroendocrine cells are a minor population in the epithelial compartment of normal prostate glands, the population of neuroendocrine-like cells that express markers such as SYN, Bcl-2, Dll-3, and AMACR correlates with cancer progression, androgen-independent state, and poor prognosis in prostate cancer patients. As recent studies show that an increase in neuroendocrine cell density occurs before development of benign prostatic hyperplasia (BPH), a non-lethal disease affecting the transition zone, in hypertensive rats, we investigated whether neuroendocrine differentiation is associated with BPH. Results: Our results showed that isobutyl-methyl-xanthine and forskolin leading to sustained activation of the cAMP/PKA pathway led to an increase in neuroendocrine differentiation markers in BPH-1 cell line. Similar results were observed by combining the β-adrenergic receptors agonist isoproterenol with forskolin. These treatments reduced BPH-1 cell proliferation rates by 40% and 60%, respectively. Effects on neuroendocrine markers expression and cell proliferation were fully reversed by the β2 blocker carvedilol. Conclusion: These data suggest that β-adrenergic receptors are linked to the development of neuroendocrine-like cells in BPH. As 20% of the prostate cancer tumors occur in this zone, this observation warrants further investigation.

Polymer-modified fertilizers (PMFs) with prolonged nutrient release present a promising solution to address the challenges associated with conventional fertilization practices, particularly for sensitive crops such as strawberries. This study investigates the effectiveness of biodegradable PMFs in maintaining nutrient availability at optimal levels while minimizing root burn and nutrient losses. A factorial field experiment was conducted to evaluate the impact of varying concentrations of polyvinyl alcohol (PVA) on the nutrient release rates from complex NPK fertilizer and monoammonium phosphate, as well as their subsequent effects on strawberry yield and soil properties. Results indicate that polymer modifications significantly slow down nutrient release, leading to prolonged nutrient retention in the soil at salt levels that are optimal for maximizing yield while remaining low enough to prevent the risk of root burn. Consequently, the application of PMFs not only enhances strawberry yield but also promotes healthier plant growth by ensuring a steady supply of nutrients throughout the growing season without inducing stress. The findings underscore the potential of biodegradable polymers to optimize fertilizer efficiency, reduce environmental impacts, and support sustainable agricultural practices. This research provides valuable insights into the development of more effective fertilization strategies for strawberry cultivation and other sensitive crops using PMFs.

This study presents the development and evaluation of a Multi-Task Long Short-Term Memory (LSTM) model with an Attention Mechanism designed to predict students' academic performance. The model concurrently addresses two tasks: predicting overall performance (total score) as a regression task and categorizing performance levels (remarks) as a classification task. By processing both tasks simultaneously, the model optimizes computational efficiency and resource use. The dataset includes detailed student performance records across various metrics such as Continuous Assessment, Practical Skills, Demeanor, Presentation Quality, Attendance, and Participation. The model's performance was evaluated using comprehensive metrics. For the regression task, it achieved a Mean Absolute Error (MAE) of 0.0249, Mean Squared Error (MSE) of 0.0012, and Root Mean Squared Error (RMSE) of 0.0346. For the classification task, it attained perfect scores with an accuracy, precision, recall, and F1 score of 1.0. These results highlight the model's high accuracy and robustness in predicting both continuous and categorical outcomes. The Attention Mechanism enhances the model's capabilities by identifying and focusing on the most relevant features. This study demonstrates the effectiveness of the Multi-Task LSTM with Attention Mechanism in educational data analysis, offering a reliable tool for predicting student performance and potential broader applications in similar multi-task learning contexts. Future work will explore further enhancements and wider applications to improve predictive accuracy and efficiency.

In this study, Fe, N co-doped biochar (Fe@N co-doped BC) was synthesized by carbonization-pyrolysis method and used as carbocatalysts to activate peroxymonosulfate (PMS) for sulfamethoxazole (SMX) removal. In the Fe@N co-doped BC/PMS system, the degradation rate of SMX (10.0 mg⋅L−1) was 90.2% within 40 min under optimal conditions. The radical quenching experiments, and electron spin resonance (ESR) analysis suggested that sulfate radicals (SO4•−), hydroxyl radicals (•OH) and singlet oxygen (1O2) participated in the degradation process. After the reaction, the proportion of pyrrolic N apparently decreased from 57.9% to 27.1%. Pyrrolic N served as active sites to break the inert carbon network structure and promote the generation of reactive oxygen species (ROSs). Besides, pyrrolic N showed stronger interaction with PMS and significantly reduced the activation energy required for the reaction (∆G = 23.54 kcal/mol). The utilization potentiality of Fe@N co-doped BC was systematically evaluated in terms of its reusability, and selectivity to organics. Finally, the intermediates of SMX were also detected.

The emergence of few-shot learning as a potential approach to address the problem of data scarcity by learning underlying pattern from a few training sample had so far given a mix-result especially on the suitability of model-agnostic meta learning, transfer learning, and optimization strategy to rapidly learn valid information from few sample. In this research, we did an in-depth evaluation of meta- learning to determine their plausibility and suitability for previously unknown cyberattack detection by first retrieving the original research artifacts of current state of the art meta learning to repeat the experiment with original dataset before replicating the experiment with two different malware dataset which had not been previously done with meta-transfer learning. On each of the experiments, meta-transfer learning gave good results on digital character recognition dataset but abysmal result on Malimg and Malevis malware images datasets thereby indicating its unreliability for detecting cyberattacks and the need for an improvement to the state-of-the-art meta transfer learning towards a better attack detection. Transfer learning performance is independent on imbalance and hence does not influence its performance since both malware dataset used for this experiment result in high validation loss and balancing the dataset doesn't result in reduced validation loss,the successful learning transfer seen on digital character recognition dataset is not unconnected to the fact that several languages have similar characters and digits thereby enhancing the successful learning transfer unlike malware datasets, and more importantly the finding that current meta-learning transfer approach doesn't generalize well on malware dataset and hence not suitable for detecting previously unseen out-of-distribution attack.

The minimum ignition energy (MIE) has been extensively studied via experiments and simulations. However, our literature review reveals little quantitative consistency, with results varying for f=1.0 from 0.324 to 1.349 mJ, and for f=0.9 from 0.22 to 0.944 mJ. Therefore, there is a need to resolve these discrepancies. This RANS study aims to partially address this knowledge gap. Additionally, it presents other flame evolution parameters essential for robust combustion design. Using the reactingFOAM solver we predict the threshold energy required to ignite the fuel mixture. For this, the single step using the Arrhenius law is selected to model ignition in the flame kernel of stochiometric and lean CH₄/air mixtures, allowing it to develop into a self-sustained flame. The ignition power density, an energy quantity normalised with volume is incrementally varied keeping the kernel critical radius r_s constant 0.5 mm in the quiescent mixture of two equivalence ratios fs 0.9, and 1.0, for varied operating pressures 1, 5 and 10 bar at constant initial temperature 300 K. The minimum ignition energy is validated with twelve independent 1 bar data sets both numerical and experiments. Finally, a mathematical formulation of MIE is devised, a function of pressure and equivalence ratio shows a slightly curved relationship.

Bicuspid aortic valve(BAV) is a common congenital heart defect often associated with ascending aorta dilation. Current guidelines suggest surgical intervention for diameters ≥45mm in conjunction with surgical aortic valve replacement(SAVR). However, the optimal management of ascending aortas measuring 40-44mm remains controversial. Objectives: This study aims to evaluate the evolution of aortic diameter in patients with BAV and ascending aorta diameters between 40 and 44 mm undergoing AVR, assessing whether a conservative approach is justified. Methods: We conducted a retrospective observational study, analyzing 88 BAV patients who underwent SAVR between January 2012 and December 2018. Patients were divided into two groups based on preoperative ascending aorta diameters: &lt;40 mm (Group 1, n=15) and ≥40 and &lt;45 mm (Group 2, n=11). Follow-up of at least 5 years included aortic dilation rates, survival, and reoperation rates. Results: No significant differences were observed in aortic dilation between the two groups during follow-up, with overall annual dilation rates of 0.2±0.07mm/year. Survival rates were 86.3% for Group 1 and 81.9% for Group 2, with no reoperations required in either group. Conclusions: Patients with BAV and ascending aorta diameters of 40-44 mm do not require prophylactic aortic replacement during AVR, provided they undergo regular follow-up. These findings support current guidelines advocating conservative management for ascending aorta diameters in this range. However, in younger patients or those nearing the 45 mm threshold, surgical replacement may still be considered to preempt future complications.

In this paper, we propose "Synergized Efficiency Optimization for Large Language Models" (SEO-LLM), a groundbreaking approach that integrates advanced data utilization and model compression techniques to significantly enhance the performance, efficiency, and scalability of large language models (LLMs). Our method synergistically combines Adaptive Data Augmentation (ADA), Transfer- Active Learning (TAL), Adaptive Iterative Pruning (AIP), and Synergistic Quantization and Distillation (SQD). These components work together to reduce the training data requirement by 30%, compress model size by 67.6%, and improve inference speed by up to 50%, while preserving or even enhancing model accuracy across various NLP tasks. ADA dynamically adjusts augmentation strategies to optimize model generalization, while TAL leverages pre-trained models to focus learning on the most informative data samples. AIP intelligently prunes less significant weights, and SQD harmonizes quantization with knowledge distillation to achieve high compression rates without significant performance loss. The synergy between these techniques makes SEO-LLM a robust solution for deploying LLMs in resource-constrained environments, maintaining state-of-the-art performance with a fraction of the computational and data resources.

This study investigates the necessity of particle asymmetry for self-propulsion in nanomotors. While conventional wisdom posits that asymmetric designs are crucial for generating phoretic forces or localized bubble propulsion, recent research suggests that symmetrical particles may also exhibit motility. To address this debate, we developed a robust workflow for synthesizing gold grafted silica nanoparticles with precise control over size and shape, enabling the direct comparison of their motile behavior by dynamic light scattering and particle tracking velocimetry. Our results indicate that the inherent asymmetry generated during isotropic gold nanoparticle deposition onto silica surfaces may enable particle motility.