Dengue, a perilous fever-type illness transmitted by mosquitoes, remains a significant global health concern. The incidence of dengue outbreaks is primarily influenced by climate factors, contributing to fluctuating dengue cases. Therefore, this study aims to develop predictive models for dengue outbreaks employing Machine Learning (ML) techniques. Four distinct ML models, namely K-Nearest Neighbor (KNN), Random Forest (RF), Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR), were employed in this study. Prior to model analysis, thorough data preprocessing was conducted. In some instances, certain attributes exhibiting sparse correlations with dengue occurrence were eliminated based on correlation analysis. Upon finalizing the models, performance evaluation was executed through comparison based on Mean Absolute Error (MAE) metrics. The findings of this comparative analysis revealed that the KNN model exhibited significantly superior performance compared to the other three models. This outcome underscores the potential of KNN in enhancing the accuracy of dengue outbreak predictions.

Multimedia resources, such as instructional videos, are currently enjoying a certain popularity in training programmes for medical and dental students. The major challenge is to create such resources that have quality content and are acceptable to students. We investigated the opinions of a sample of 551 students from 4 medical universities in Romania in order to identify the characteristics of the instructional videos that students prefer and we comparatively analysed these characteristics according to gender, age group, but also according to their general preferences for using Internet services. We used univariate (hypothesis testing) and multivariate (Two-Step Clustering) data analysis techniques and revealed three clusters of students, primarily determined by perceptions of the visual appearance of instructional videos. The structure of the clusters by gender and age group is relatively similar, but we recorded differences between them associated with students' expressed preferences for certain Internet services compared to others. Students who prefer instructional videos to contain images used only for aesthetic purposes, to fill in breaks, use Internet services mainly for communication, while students who prefer in videos the use of already drawn explanatory diagrams are slightly younger than the others and use Internet services mainly for information and communication.

Fraudulent transactions pose a significant threat to financial institutions and e-commerce platforms.Machine learning models, trained on historical labeled data (fraudulent vs. legitimate transactions), are often employed to identify and prevent fraud. However, real-world datasets frequently exhibit class imbalance, where fraudulent transactions (minority class) are significantly outnumbered by legitimate transactions (majority class). Machine learning models may perform poorly as a result of this imbalance, underestimating fraud and favouring the majority class. This paper proposes a novel approach to address class imbalance and improve fraud detection accuracy. We explore the implementation of FROST (Feature space RObust Synthetic saTuration) oversampling, a technique specifically designed to generate synthetic samples for the minority class. The FROST function leverages the k-nearest neighbors (KNN) algorithm and a user-defined amplification factor (m) to create synthetic data points that closely resemble existing minority class instances. We integrate the FROST-enhanced oversampling technique into the machine learning pipeline for fraud detection. The paper evaluates the effectiveness of this approach compared to traditional oversampling methods and analyzes its impact on classification accuracy metrics.

Build a special identical equation, use its calculation characters to prove and search for solution of any odd converging to 1 equation through (*3+1)/2^k operation, change the operation to (*3+2^m-1)/2^k, and get a solution for this equation, give a specific example to verify. Thus prove the Collatz Conjecture is true. Furthermore, analysis the sequences produced by iteration calculation during the procedure of searching for solution, build a weight function model, prove it decrease progressively to 0, build a complement weight function model, prove it increase to its convergence state. Build a (*3+2^m-1)/2^k odd tree, prove if odd in (*3+2^m-1)/2^k long huge odd sequence can not converge, the sequence must outstep the boundary of the tree after infinite steps of (*3+2^m-1)/2^k operation.

Acute lymphoblastic leukaemia is currently treated with bacterial L-Asparaginase; however, its side effects bring up the special need for improved and efficient novel enzymes development. Previously, we obtained low anti-asparaginase antibody production and high serum enzyme half-life in mice with the P40S/S206C mutant; however, its specific activity was significantly reduced. Thus, our aim was to test single mutants, S206C and P40S, for in vitro and in vivo assays. Our results showed that the drop in specific activity was caused by P40S substitution. Besides, our single mutants were highly stable in biological environment simulation, unlike double mutant P40S/S206C. The in vitro cell viability assay demonstrated that mutant enzymes have higher cytotoxic effect than WT on T-cells derived ALL and on some solid cancer cell lines. The in vivo assays were performed in mice to identify toxicological effects, to evoke immunological response and to study the enzymes pharmacokinetics. From these tests, none of the enzymes was toxic; however, S206C evoked lower physiological changes and immune responses. In relation to pharmacokinetic profile, S206C has two-fold higher activity than WT and P40S two hours after injection. In conclusion, we present bioengineered E. coli asparaginases with high specific enzyme activity and lesser side effects.

This study examines the role of using algorithmic HRM to make strategic decisions pertaining to HR activities in organizations. The study develops a scale to measure algorithmic HRM usage in its first phase, and in the second phase, it finds that algorithmic HRM having significant impact on the strategic HR decision making that helps and enables organization in creating the competitive advantage. Utilizing the author’s LinkedIn profile, 234 final participants considered for this research. Collected data analyzed by applying PLS SEM. It evaluates the mediation role of the HR strategic decision making, and the HR digital maturity as a moderator in seeing the impact of algorithmic HRM on the competitive advantage of the firm. The study finds a strong relationship between the algorithmic HRM usage and competitive advantage, a significant relationship between algorithmic HRM usage and the strategic HR decision making, and lastly, a significant relationship between strategic HR decision making and the competitive advantage. The moderating role of HR digital maturity was found to be insignificant in this research which paves the way for further research. This research, the model, and its findings contribute to the theory and implicate the practicality of algorithmic HRM. It's one of few papers that address the algorithmic HRM usage in the transitioning economy like Saudi Arabia.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

In Indonesia, types of meat are still identified manually due to increasing prices for beef and buf-falo ahead of Idul Fitri. Traders mix beef with pork to thwart the beef scam. Haar wavelet and GLCM, GLCM with angles of 0°, 45°, 90°, and 135°, as well as matrices using contrast, correlation, energy, homogeneity, and entropy, are used in feature extraction. The following are the results of meat image classification testing using k-NN, Haar wavelet, and GLCM: The k-NN algorithm shows superiority in identifying fresh (99%), frozen (99%), and rotten (96%) meat texture images with the most fantastic accuracy results in every situation. Meanwhile, GLCM routinely provides good results, especially regarding the texture image of fresh meat (183.21) and rotten meat (115.79). However, despite delivering less throughput than k-NN and GLCM, Haar wavelets are still helpful, especially when dealing with fresh meat texture images (89,96).

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers: (1) Background: It is important to get a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population. This work reviews currently available digital health solutions and their related characteristics to develop a decision support tool for older adults living with mild or major neurocognitive disorders and their informal caregivers. This knowledge will inform the development of a decision support tool to assist older adults and their informal caregivers in their search for adequate digital health solutions according to their needs and preferences, based on trustable information.; (2) Methods: We conducted an environmental scan to identify digital health solutions from a systematic review and targeted searches in grey literature covering the regions of Canada and Europe. Technological tools were scanned based on a preformatted extraction grid. We assessed their relevance based on selected attributes and summarized findings; (3) Results: We identified 100 available digital health solutions. The majority (56%) were not specific to NCDs. Only 28% provided scientific evidence of their effectiveness. Remote patient care, movement tracking, and cognitive exercises were the most common purposes of digital health solutions. Most solutions were presented as decision aid tools, pill dispensers, apps, web, or a combination of these platforms. (4) Conclusions: This environmental scan allowed the identification of current digital health solutions for older adults with mild or major neurocognitive disorders and their informal caregivers. Findings from the environmental scan highlight the need for additional approaches to strengthen digital health interventions for the well-being of older adults with mild and major NCDs and their informal and formal healthcare providers.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

In the field of business environments, the integration of novel artificial intelligence (AI) techniques has been identified in the literature and theoretical discourse as an essential catalyst for enhancing the decision-making processes. In the contemporary landscape of digital transformation, the application of these techniques becomes essential, despite encountering various hurdles that impede their seamless integration into the rational decision-making process within e-government, which constitutes a critical component of digital government initiatives. This study explores whether similar advancements can be observed within the e-government sector and investigates the impact of using machine learning (ML) as a technique of artificial intelligence on rational decision-making (RDM). Employing an empirical research approach, the study utilized a quantitative methodology, relying on an electronically structured questionnaire survey administered to 163 employees in the e-government sector in Jordan through purposive random sampling. Data analysis was conducted using the SPSS v25 program, complemented by a media-tion analysis using AMOS v23 software. The research findings revealed a significant contribution of using machine learning to enhance rational decision-making and trust levels, with trust positively impacting RDM. Trust was identified as a beneficial mediator in the relationship between machine learning and rational decision-making. Despite certain limitations, this study's outcomes offer substantial insights for researchers and government policy-makers alike, contributing to the advancement of sustainable practices in the e-government domain.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

In this project the EEG – electroencephalogram - channel(s) will be characterized to diagnose PTSD – Post-traumatic stress disorder – cases. For this aim, we applied boosting methods including a combination of K-mean and Support Vector Machine (SVM) models to find the feature weights to detect the PTSD cases. We classified 32 channels of 12 subjects including 6 PTSD and 6 healthy controls using a 6-mean classifier. The linear SVM found the weights of distinguished channels within each subject for each cluster. It was found that the significant SVM weights of F4, F8, and Pz are smaller in PTSD than in healthy subjects. This new method can be used as a tool to better understand the interaction of EEG signals and diagnosis.

Background Apolipoprotein E (APOE) gene polymorphism has been implicated in the pathogenesis of various metabolic disorders, including type 2 diabetes mellitus (T2DM). Type 2 diabetes mellitus (T2DM) is a major public health concern worldwide, including in Pakistan. Cardiovascular problems linked with T2DM have a significant impact on people and society. The study's goal is to investigate the relationship between Apolipoprotein E (ApoE) genotypes, lipid profiles, and cardiovascular complications such as ischemic heart disease (IHD) and stroke. Methods: This study was carried out on 260 subjects, divided into control D1: Diabetics without cardiovascular issues. D2: Diabetics with heart disease. D3: Diabetics with stroke. D4: Diabetics with both heart disease and stroke. Anthropometric parameters (age, BMI) and risk factors (smoking, diabetes duration, hypertension) were assessed in all groups. Serum levels of TC, TG, LDL, HDL, VLDL, creatinine, BSF, and HbA1c were measured. Apolipoprotein E gene polymorphism was determined using PCR-RFLP. Results: Hypertension, BMI, and dyslipidemia, defined as elevated levels of total cholesterol, triglycerides, LDL, HDL, and VLDL, as well as uncontrolled hyperglycemia (elevated fasting blood sugar and glycated hemoglobin) in T2DM, were linked to vascular complications such as IHD and stroke. Hypertension was prevalent in 75.4% of the population, with greater rates among the elderly. Stage 2 hypertension was more prevalent in all age groups. Apolipoprotein E gene polymorphism was discovered, with genotypes 3/3, 4/4, 2/3, and 3/4 being the most prevalent. Genotype 3/4 was more common in diabetics who had IHD/stroke or both problems, whereas genotype 2/3 was linked to DM and stroke. Conclusion: It is concluded that BMI, hypertension, hyperglycemia, atherosclerosis, and dyslipidemia are linked with cardiovascular complications of type 2 diabetes. Apolipoprotein E gene polymorphism is associated with cardiovascular disease in diabetic patients by affecting the lipid profile.

Several efforts have been made to estimate the prevalence of different types of antibiotic resistance in different regions of Nigeria. The study investigated the prevalence of Klebsiella pneumoniae encoding genes for CTX-M, TEM, and SHV-1 extended-spectrum beta-lactamases (ESBL) enzymes isolated from urine samples of non-hospitalized patients with suspected UTI in Lagos State, Nigeria. A 4-month retrospective study, spanning from May 2023 to August 2023, was conducted. K. pneumoniae was isolated from urine samples using standard microbiological methods. The modified Kirby-Bauer disc diffusion method was used to test for antibiotic susceptibility, and Clinical and Laboratory Standard Institute (CLSI) guidelines were followed for interpretation. The double-disk synergy method was used to confirm the phenotypic identity of ESBL producers, and the results were interpreted in accordance with CLSI guidelines. The phenotypic method was utilized for ESBL screening, employing the standard disk diffusion method. The CTX-M ESBL gene, TEM gene, and SHV gene were found using multiplex PCR. Results revealed that 41 K. pneumoniae isolates were resistant to third-generation Cephalosporins; the isolates showed resistance to ceftazidime in 100% of cases and ceftriaxone in 80.49% of cases respectively. It was determined that 8 (19.51%) of the isolates produced ESBL. Among Klebsiella isolates, the frequencies of the SHV, TEM, and CTX-M genes were 31 (75.61%), 4 (9.76%), and 10 (24.39%), in that order. Four isolates (9.67%) had the SHV, TEM, and CTX-M genes, while eight (19.51%) of the isolates possessed both the SHV and CTX-M genes. This investigation demonstrates high frequency, wide range of patterns and coexistence of ESBL genes in K. pneumoniae isolates from outpatient UTI patients. Although several phenotypic tests have been used for ESBL detection, testing directly for the presence of ESBL genes is always more accurate. The majority of the isolates of Klebsiella pneumoniae ESBL producers had the SHV gene identified.

Conclusions: Our findings suggest that the NMS-E represents a valuable preoperative diagnostic tool for endometriosis, effectively correlating with the disease's severity and surgical outcomes. Incorporating the NMS-E into clinical practice could significantly enhance the management of endometriosis by addressing current diagnostic limitations and guiding surgical planning.

The aim of this study was to identify factors, that influence satisfaction and dissatisfaction in the use of public e-procurement. The use of IT solutions promotes sustainable development. Hence, there is a need to conduct research that will allow for the best possible adjustment of e-procurement solutions in order to implement them as widely as possible in business practice. This study used a quantitative exploratory survey-based approach. The obtained research results were analyzed using statistical methods, including factor analysis PCA. Factor analysis identified three main satisfaction factors and two dissatisfaction factors in e-procurement use, highlighting the importance of support, intuitiveness, and security in user satisfaction. This study contributes to the existing literature by providing a nuanced understanding of the factors influencing user satisfaction and dissatisfaction within e-procurement systems, specifically highlighting the role of intuitive design and technical support. It offers a unique perspective by integrating these insights with the specific requirements of public procurement, thereby filling a gap in research on enhancing user experience in the context of sustainable purchasing practices.

In this work, several random Boolean networks (RBN) are generated and analyzed from two characteristics: their time evolution diagram and their transition diagram. To do this, its randomness is estimated using three metrics, of which algorithmic complexity is the only one capable of revealing both transitions towards the chaotic regime and the algorithmic contribution of certain states to the transition diagram and their relationship with the order they occupy in the temporal evolution of the respective RBN.

Abstracts In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted, and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x10^4 – 2x10^7 CFU per ml and has a sensitivity of S = 1.655x10^5 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10^-9 grams (g), which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).

Salidroside, a valuable phenylethanoid glycoside, is obtained from plants belonging to the Rhodiola genus, known for its diverse biological properties. At present, salidroside is still far from large-scale industrial production due to the lower titer and higher process cost. In this study, we constructed a biosynthetic pathway from L-tyrosine to salidroside in Saccharomyces cerevisiae. To increase sali-droside production, we for the first time constructed an in vivo UDP-glucose regeneration system that sucrose synthase GmSUS worked in conjunction with UDP-glucose transferase RrUGT33 to improve the UDP-glucose availability with inexpensive sucrose as the consumed substrate. Finally, the molar conversion rate of L-tyrosine could reach 95%. To further reduce the cost, co-culture with E. coli that synthesized L-tyrosine de novo resulted in an 81% reduction in the final substrate cost per 1 kg of salidroside compared to the initial cost. The final titer of salidroside obtained 3.8 g/L and was the highest titer achieved at the Shake-Flask-Level in the existing reports. And this marked the first successful synthesis of salidroside in an in situ enhanced UDP-glucose system using sucrose. This accomplishment laid a robust groundwork for further investigations into the synthesis of other notable glycosides and natural compounds.

Predictions of mean values of statistical variables of large scale turbulent flow by the widely used basic k-ϵ model and a new fundamentally based model are verified against published results of Direct Numerical Simulations DNS of the Navier-Stokes equations. The verification concerns turbulent channel flow at shear Reynolds numbers of 950, 2000 and 104. The basic k-ϵ model is largely based on empirical formulations accompanied by calibration constants. This contrasts with the new model where descriptions of leading statistical quantities are based on the general principles of statistical turbulence at large Reynolds number. Predicted values of major output variables such as turbulent viscosity, diffusivity of passive admixture, temperature, and fluid velocities compare well with DNS in case of the new model. Significant differences are seen in case of the basic k-ϵ model.

Current VAT rules for cross-border e-commerce companies in the EU are not sustainable, because they are extremely complex and often opaque, due to the lack of tax harmonization. The aim of the research is to explore, using a qualitative method, what kind of harmonization would make the current legislation more uniform, simpler, more transparent, and easier to understand, without conflicting with the rules of any Member State. To this end, the aspects of the new platform regulation introduced on 1 July 2021 and its potential for expansion are assessed through information from possible sales models. The research suggests that the rules on platforms do not cover all possible sales models, which in our view imposes an unnecessary extra administrative burden on some businesses and makes their tax activities less transparent. In the light of the results of the research, we propose that the current EU platform regulation should be extended to cover B2B, B2C transactions and services. As a result of this suggested harmonization, a simpler, more transparent, uniform and sustainable tax system would contribute to the whitening of the economy, generating additional tax revenue for Member States.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (>1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

The Distributed eLearning Center (DeLC) is a portal, providing extensive support in the day-to-day work when it comes to e-learning content – it helps students and teachers organize their learning materials, fill the gaps in knowledge (for students) and educational approaches (for teachers), organize and conduct exams, and overall, with providing proactive and personalized e-learning environment. The scope of DeLC as a project involves many extensions, covering the aspects of learning, teaching, exams, and collecting statistical information. Such extension is an agent-oriented environment, which enriches the functionalities with intelligent components, that are reactive and proactive, referred to as agents or assistants. This paper is focused on presenting the latest step in the evolution of FraudDetector software agent, which started with base functionality for fraud detection, and now it aims at usage of AI to accomplish its tasks, taking advantage not only from its knowledgebase, but from a much larger one, used by ChatGPT – through integration with it, which is the main contribution of this research, although the real results from production environment are still pending. In this process, agent’s architecture should stay open for collaboration with another external AI provider if necessary, trying to decouple the components, responsible for integration. As of now, the experiments show that involving ChatGPT in FraudDetector’s functionality enriches it and the agent’s precision could be improved this way.

We show that Universe inflation occurs when Einstein's gravity couples to nonlinear electromagnetic fields with cosmic stochastic magnetic fields background. Nonlinear electrodynamics with two parameters is used. The strength of magnetic fields to have the Universe inflation is obtained. It is shown that singularities of the energy density and pressure are absent for any scale factors. At large scale factors one arrives at equation of state for ultra-relativistic case. It is demonstrated that the curvature invariants do not have singularities. By computing the deceleration parameter we show that graceful exit takes place with reasonable e-folding number. The duration of Universe inflation as a function of model parameters is obtained. The classical stability and causality are analyzed by calculating the speed of the sound.

This paper provides a new discovery that adds to the contemporary theory of modelling of non-stationary queues, by capturing analytically the behavior of the root parameter, for the G1/M/1 PSFFA model of non-stationary Ek/M/1 queue. Additionally, it has been also revealed that the resulting root parameter reduces to the PSFFA model of non-stationary queue. Potential applications of PSFFA to Computer engineering are provided. Some challenging open problems are addressed combined with closing remarks and future research directions.

The significance of Kashmir conflict as one of the world’s longest running conflicts has frequently drawn the attention of both communication and international relations’ scholars which makes it an important issue from the perspective of interdisciplinary approach. The researchers have attempted to assemble a brief history of the Indian held Jammu and Kashmir Conflict from the time of partition in 1947 to the developments which took place till 2019 in the light of the available literature. The paper provides substantial historical context of the important events like instrument of accession, UN resolutions on Kashmir conflict, Simla Accord, Gawkadal Massacre , Lahore Declaration, Kargil War, killing of Burhan Wani, Uri attack and Article 370’s abrogation .

Mangrove plant seedling cultivation is crucial for the protection, management and restoration of mangrove ecosystem. In this study, we focused on Kandelia obovata, a typical mangrove, and evaluated nursery cultivation with different combinations of three salinity levels (S1: 0 ppt, S2: 10 ppt, and S3: 20 ppt), three genealogies (EZD, JX, and YZ), and five growth media (M1: 100% loess, M2: 100% sandy, M3: 50% loess + 50% sandy, M4: 40% loess + 40% sandy + 20% peat, and M5: 40% loess + 40% sandy + 20% coir), by measuring the growth parameters such as mortality rate, seedling height, diameter, and biomass partition. These growth indexes were significantly affected by salinity and medium, and genealogies also had significant effects on mortality rate and biomass accumulation. S2 or S3 both had lower mortality and higher growth indexes than S1. M1 was the medium that increased seedlings height, diameter and biomass the most and had the lowest death rate. EZD and JX were also higher levels than YZ in these indicators, but the difference between them was not obvious. S3, M1, and EZD consistently performed well in fuzzy evaluation and quality assessment. Furthermore, combinations involving these treatments also produced highly favorable results. These results furnish both a theoretical and practical foundation for advancing nursery cultivation techniques and germplasm breeding of K. obovata in mangroves.

Shiga-like toxin producing Escherichia coli (STEC) is a well-known cause of foodborne acute diarrheic diseases especially in children and the elderly. The potentially fatal complications associated with toxin production range from bloody diarrhoea and ischemic colitis to kidney failure, haemolytic-uremic syndrome (HUS) and colon perforation. We describe a case and literature review of STEC – induced colitis, highlighting the clinical features, and the necessary tools for the best diagnosis approach and management. Facing challenging differential diagnosis ranging from ischemic colitis, inflammatory bowel disease, to infectious process due to a pathogenic or opportunistic agent, we practiced a step-by-step exploration. Beginning with bacteriological investigation, imagistic screening, and colonoscopy, we could rule out some of initial suppositions and reach the final diagnosis, also considering the pathological results. Although antibiotics are not indicated in this pathology, our patient did receive antibiotics, given the risk of translocation and colon perforation, without associating any complications, as HUS or peritonitis. Detailed and rigorous investigations along with a multi-speciality team are required for a prompt medical support. Coping the symptoms and refraining from further complications are the mainstem of the treatment.

In a context of increasingly necessary energy transition, precise modelling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSO) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modelling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow the estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

This study investigates the application of regression neural networks, in particular the fitrnet model, in predicting the hardness of steels. The experiments involve extensive tuning of hyperparameters using Bayesian optimization and employ 5-fold and 10-fold cross-validation schemes. The trained models are rigorously evaluated, and their performances are compared using various metrics such as mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The results provide valuable insights into the effectiveness of the models and their ability to generalize to unseen data. In particular, Model 4208 (8-85-141-1) emerges as the top performer with an impressive RMSE of 1.0790 and an R² of 0.9900. The research paper contains an illustrative example that demonstrates the practical application of the developed model in determining the hardenability band for a specific steel grade and shows the effectiveness of the model in predicting and optimizing heat treatment results.

This study investigated the presence, distribution, and antimicrobial resistance profiles of extend-ed-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae in a dairy herd located in Northern Italy. A questionnaire was administered, and the feces of clinically healthy pre-weaned dairy calves, their mothers, and the cows treated for mastitis, waste milk, water, and environmental samples, were collected and inoculated on Chromagar ESBL™ medium. The questionnaire identi-fied several risk factors including administration of waste milk to male calves, lack of routine cleaning of calf feeding and housing equipment, and blanket dry cow therapy. Escherichia coli was identified by MALDI-TOF MS in the feces of 28 of 37 (75.67%) calves, 2 of 3 (66.67%) treated cows, 8 of 14 (57.15%) environmental samples, and the waste milk. Six of 14 (42.85%) environmental samples were also positive for ESBL Acinetobacter baumannii, while all fecal samples were negative. ESBL production was confirmed for all E. coli isolates based on the double disk susceptibility test (DDST), while none were carbapenemase producers. Upon minimal inhibitory concentration (MIC) analysis, all of them showed multiple resistances and were categorized as multi-drug resistant (MDR). This study confirms the widespread presence of MDR, ESBL-E. coli in dairy calves and highlights their diffusion in the farm environment.

Rare ginsenoside compound K (CK), is an intestinal microbial metabolite with a low natural abundance that is primarily produced by physicochemical processing, side chain modification, or metabolic transformation in the gut. Moreover, CK exhibits potent biological activity compared to primary ginsenosides, which has raised concerns in the field of ginseng research and development as well as ginsenosides-related dietary supplements and natural products. Ginsenosides Rb1, Rb2, and Rc are generally used as a substrate to generate CK via several bio-conversion processes. Current research shows that CK has a wide range of pharmacological actions including boosting osteogenesis, lipid and glucose metabolism, lipid oxidation, insulin resistance, anti-inflammatory, and anti-apoptosis properties. Further research on the bioavailability and toxicology of CK can advance its medicinal application. The purpose of this review is to lay the groundwork for future clinical studies and the development of CK as a therapy for metabolic disorders. Furthermore, the toxicology and pharmacology of CK are investigated as well in this review. The findings indicate that CK primarily modulates signal-ing pathways associated with AMPK, SIRT1, PPARs, WNTs, and NF-kB. It also demonstrates a positive therapeutic effect of CK on nonalcoholic fatty liver disease, obesity, hyperlipidemia, diabetes, and its complications, as well as osteoporosis. Additionally, the analogues of CK showed more bioavailability, less toxicity, and more efficacy against disease states. Enhancing bioavailability and regulating hazardous variables are crucial for its use in clinical trials.

A novel educational platform called Shared Modeling and Simulation Environment (SMSE) was initiated in the ERASMUS+ “CybPhys” project. It integrates the Jupyter platform, including Ju-pyter Notebooks, for e-learning in the STEM field. A novel platform enhances e-learning by combining Moodle with Jupyter's capabilities to create virtual labs. A survey was conducted in the spring of 2023 among bachelor and master students of Chernihiv National Polytechnic Uni-versity aimed to gather feedback from students using SMSE in their e-learning process. Two student groups were involved: one of them consisted of students using SMSE in both the autumn and spring semesters and another represented the students starting with SMSE in the spring se-mester. The survey based on the adjusted Technology Acceptance Model (TAM) was conducted to understand the acceptance of this e-learning approach. A comprehensive analysis of students’ answers based on the TAM approach revealed the inside of the process of transformation of stu-dents’ perceptions during the acquisition of the SMSE platform. Our research demonstrates that SMSE effectively merges Moodle's online learning capabilities with Jupyter notebooks, provid-ing a flexible and interactive learning experience for both in-class and remote students. It pro-vides a web-based, multifunctional e-learning environment that combines a variety of tools and technologies, giving students the possibility to be involved in all sorts of teaching activities, such as lectures, exercises, simulations, etc., through the use of one single online environment.

Abstract:The digital landscape is rapidly reshaping under the influence of AI-powered cloud-based e-commerce platforms (PCEPs). These platforms leverage the transformative power of AI to personalize customer experiences, optimize pricing strategies, enhance security, and streamline operations, offering businesses a significant competitive edge. However, challenges surrounding data privacy, algorithmic bias, and potential job displacement raise crucial ethical questions regarding widespread AI adoption in e-commerce.This study delves into the untapped potential and ethical considerations of PCEPs, distinguishing itself by proposing practical strategies for responsible development and ethical implementation.Objectives: Investigate the transformative potential of PCEPs: Personalized product recommendations:Analyze effectiveness and potential bias. Dynamic pricing strategies:Explore impact on consumer fairness and market stability. Enhanced fraud detection:Evaluate accuracy and privacy implications. Optimized supply chain management:Assess efficiency gains and job displacement risks. Critically analyze the ethical considerations of AI in e-commerce: Data privacy:Assess current practices and develop mitigation strategies. Algorithmic bias:Identify potential sources and propose solutions for fairer decision-making. Job displacement:Evaluate impacts and propose reskilling initiatives. Propose comprehensive and practical strategies for responsible PCEP development and implementation: Transparency:Enhance user awareness and control over data usage. Fairness:Design AI systems to mitigate bias and uphold consumer rights. Accountability:Establish clear guidelines and oversight mechanisms for ethical AI development.Conclusion: While PCEPs offer a plethora of transformative benefits, their ethical implementation is paramount. By adhering to principles of transparency, fairness, and accountability, businesses can unlock the full potential of PCEPs while minimizing potential risks and shaping the future of online commerce in a sustainable and equitable manner

Background and objective K. pneumoniae appeared to be a significant problem due to its ability to accumulate antibiotic-resistance genes. After 2013, alarming colistin resistance rates among carbapenem-resistant K. pneumoniae have been reported in the Balkans. The study aims to perform an epidemiological, clinical, and genetic analysis of a local outbreak of COLr CR-Kp. Material and methods All carbapenem-resistant and colistin-resistant K. pneumoniae isolates observed among patients in the ICU unit of Military Medical Academy, Sofia from 1 January to 31 October 2023 were included. The results were analyzed according to the EUCAST criteria. All isolates were screened for blaVIM, blaIMP, blaKPC, blaNDM, and blaOXA-48. Genetic similarity was determined using the Dice coefficient as a similarity measure and the unweighted pair group method with arithmetic mean (UPGMA). mgrB genes and plasmid-mediated colistin resistance determinants (mcr-1, mcr-2, mcr-3, mcr-4, mcr-5) were investigated. Results There was a total of 379 MDR-K. pneumoniae isolates, 88% of which were carbapenem-resistant. Of them, there were 9 (2.7%) colistin-resistant isolates in six patients. A time and space cluster for five patients was found. Epidemiology typing showed that two isolates belonged to clone A (pts. 1, 5) and the rest to clone B (pts. 2-4) with 69% similarity. Clone A were coproducers of blaNDM-like and blaOXA-48-like and had mgrB-mediated colistin resistance (40%). Clone B isolates had only blaOXA-48-like and intact mgrB genes. All isolates were negative for mcr-1,-2,-3,-4,-5 genes. Conclusions The study describes a within-hospital spread of two clones of COLr CR-Kp with a 60% mortality rate. Clone A were coproducers of NDM-1 and OXA-48-like enzymes and had mgrB-mediated colistin resistance. Clone B isolates had only OXA-48-like enzymes and intact mgrB genes. No plasmid-mediated was found. The extremely high mortality rate and limited treatment options warrant strict measures to prevent outbreaks.

Meals on Wheels (MoWs) are critical in enabling adults with care and support needs to live independently. However, many individuals are unaware that the service exists. The aim of this study was to review the websites of local authorities in the UK, and those of 3^rd-party providers they signpost to, to establish the quality of online information available on MoWs services, and the websites’ overall quality. Two data capture forms were used to extract information from local authority and 3^rd-party providers, consisting of 35 items across five domains, and 36 items across five domains, respectively. Items were awarded a score based on whether certain criteria were met or not, resulting in a maximum total score of 50 and 43 points for each local authority, and 3^rd-party provider, website, respectively. A total of 271 websites (223 local authority and 48 3^rd-party provider) were reviewed. The mean total score was 14.9 (SD 10.6, range: 1-40 points) for local authority websites, and 21.4 (SD 5.3, range: 10-35 points) for 3^rd-party provider websites. For all websites combined, online provision of MoWs information was generally poor, with the vast majority of websites (69.4%, n=188) assessed as requiring improvement, whereas only 4.4% of websites (n=12) were assessed as very good. These findings suggest that local authorities and 3^rd-party providers in the UK should seek to improve their online information provision on MoWs to enhance awareness of the service, and ensure that potential service users, and individuals who refer them to the service, can access high-quality information on MoWs.

Urinary tract infections (UTIs) caused by Uropathogenic Escherichia coli (UPEC) are a serious healthcare concern that must be treated with appropriate antibiotic therapy. However, antibiotic resistance among UPEC strains is increasing, particularly among individuals with recurrent illness. The proliferation of Extended-Spectrum Beta-Lactamase (ESBL) generating UPEC, as well as the increase of UPEC strains that display resistance to several antimicrobial drugs, adds to the difficulty of managing UTIs. UPEC strain genetic variants have a significant influence in their capacity to resist antimicrobial agents and adapt to changing environments. Understanding the genomic landscape of developing UPEC strains is critical for understanding the genetic basis of their resistance. Furthermore, tracking these genetic strains is critical for identifying patterns of resistance spread, directing infection control efforts, and educating.

The present study aimed to clarify the relationship between brand awareness and word-of-mouth communication in the fast-food sector, Lambayeque Region, 2023. By adopting a quantitative approach, statistical tools were utilized to measure variables and address hypotheses and objec-tives. The study was correlational in nature, as it demonstrated the relationship between brand awareness and word-of-mouth communication. It was also applied in scope, disseminating learning based on the research that will assist the studied area. Furthermore, this study employed a nonexperimental, cross-sectional design because the variables were only analyzed in the workplace environment at a single point in time and were not manipulated. According to the results, it is evident that consumers will easily recall their favorite brands, provided these brands meet their expectations are deemed significant, and the information on social networks is updated, detailed, useful, and valuable. Moreover, they are likely to recommend them if they recognize and have a positive valuation of the brand, sharing favorable information about it on their social networks and with their peers. The study concludes that virtual interactivity and the quality of information are linked to the generation of brand awareness, which in turn was shown to be a predictor of eWOM.

This study employs molecular docking techniques to investigate a spectrum of targets within Escherichia coli (E. coli), with a specific focus on four key proteins: Beta-lactamase, MccE protein, Penicillin G acylase, and DNA polymerase II. The research explores the binding interactions of various natural compounds, emphasizing Hypericin. Through computational analyses, the study aims to unveil the potential interactions between these compounds and essential proteins in E. coli. Notably, Hypericin demonstrates remarkable binding energy scores of approximately -10.5 kcal/mol within the Ligand Binding Site of the specified proteins. This observation suggests Hypericin's potential as a potent modulator of E. coli targets, prompting further investigation into its antimicrobial properties and therapeutic applications.

In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

To delve into the structure-function relationship of transmembrane proteins (TMPs), robust protocols are needed to produce them in a pure, stable, and functional state. Among all hosts that express heterologous TMPs, E. coli has the lowest cost and fastest turnover. However, many of the expressed in E. coli TMPs are misfolded. Several strategies have been developed to either direct the foreign TMPs to E. coli’s membrane or retain them in a cytosolic soluble form to overcome this deficiency. Here, we summarize protein engineering methods to produce chimera constructs of the desired TMPs fused to either signal peptide or precursor maltose binding protein (pMBP) to direct the entire construct to the periplasm, therefore depositing the fused TMP in the plasma membrane. We further describe strategies to produce TMPs in soluble form by utilizing N-terminally fused MBP without signal peptide. Depending on its N- or C-terminus location, a fusion to apolipoprotein A-I can either direct the TMP to the membrane or shield the hydrophobic regions of the TMP, maintaining the soluble form. Strategies to produce G-protein coupled receptors, TMPs of Mycobacterium tuberculosis, HIV-1 Vpu, and other TMPs are discussed. This knowledge could increase the scope of TMPs’ expression in E. coli.

he paper offers an innovative cooking utensil design for remote, isolated, and even peri-urban communities at a low price, with high reliability and simple construction. It can alleviate energy poverty and improve food security. This utensil uses only local solar energy directly and allows comfortable indoor cooking. This paper provides the design principles of a solar cooker/frying pan or generic heater, based on a PV panel or a plurality of them, which are directly connected to a plurality of Positive Thermal Coefficient (PTC) resistors to match the power. PTCs are nowadays produced in massive quantities and are widely available at low cost. The proposed device does not require an electronic controller or a battery for its operation. The aim is for family use, although the design can be easily scaled to a larger size or power, maintaining its simplicity. Electric heating inside or attached to the cooking pot, plus the temperature self-limiting effect of PTCs, allows for thermally insulating the cooking pot from its outside using ordinary materials. Insulation en-hances energy efficiency during cooking and keeps cooked food warm for a long time. Clean development would receive a significant impulse with its application. A simple mathematical model describes its functioning and states guidelines for adequate design. The results indicate a successful proof of concept and high efficiency both for water and oil as representatives of cooking.

Abstract: There are a large number of cross-linked chemical bonds such as tight disulfide bonds, hydrogen bonds,and salt bonds in keratin, which makes it difficult to break the structural stability of the protein using conventional methods. The degradation of feather waste using keratinases produced by microorganisms has the advantage of being efficient and environmentally friendly. In this study, 23 strains capable of producing transparent circles were obtained via preliminary screening with skim milk as the sole carbon and nitrogen source, and 9 strains capable of degrading feathers were obtained via rescreening with feathers as the sole carbon and nitrogen source. Finally, through the determination of enzyme activity, the strain CY-A with a high ability to degrade feathers was obtained. The strain was identified as Bacillus tequilensis via morphological observation, physiological and biochemical identification, and 16 S rRNA molecular biology. The keratinase gene (bta) of Bacillus tequila was cloned, and its full-length gene sequence was 1110 bp, containing an open reading frame of 1089, encoding 369 amino acids (GeneBank accession number OR733336). The physicochemical properties, secondary structure, and tertiary structure of the recombinant protein were analyzed using bioinformatics tools such as ProtParm, SOPMA, MEGA, and SWISS-MODELS. It was found that the relative molecular mass was 37.953 kD and that the isoelectric point was 8.48. The protein was a hydrophilic protein. The keratinase bta gene was ligated to the expression vector pET28a(+) using T4 ligase, and the recombination expression plasmid pET28-bta was constructed and transformed into E. coli BL21(DE3) to obtain recombinant engineered bacteria. The expressed keratinase was purified using a Ni2+ affinity chromatography column to obtain recombinant bta keratinase bta with a molecular weight of 37.953 kD. The identification and characterization of this keratinase gene provides some theoretical basis for the further enhancement of keratinase activity by means of genetic engineering.

The core motivation for this study emanates from Voronin S.'s seminal work on the universality of the zeta function. This universality positions the zeta function as a pivotal element in the conceptual framework of global artificial intelligence, suggesting its potential as a foundational component. A critical barrier to harnessing this promising universality has been the absence of efficient algorithms capable of actualizing this concept.

Malaria, leishmaniasis, and African trypanosomiasis are protozoan diseases that constitute a major global health problem, especially in developing countries; however the development of drug resistance coupled with the toxicity of current treatments have hindered their management. The implication of certain enzymes (dihydrofolate reductase, DHFR) or proteins (potassium channels) in the pathogenesis of these protozoan diseases is undeniable. In this study, a series of three DHFR inhibitors (6-5 fused heterocyclic derivatives X, Y and Z) and one K+ channel blocker (E4031) were screened for their inhibitory effect on Leishmania donovani, Plasmodium falciparum, and Trypanosoma brucei. Resazurin assay was used to assess antitrypanosomal and antileishmanial activities of test compounds, whereas the antimalarial activity was appraised through SYBR Green I test. Moreover, cytotoxicity of test compounds was evaluated on Vero, Raw 264.7 and HepG-2 cells using the resazurin-based test, whilst their pharmacokinetic properties were predicted using the online tool pkCSM. As a result, compound Y revealed a selective (selectivity index range: 2.69 - >61.4; Vero, Raw 264.7 and HepG-2 cells) and broad-spectrum antiprotozoal activity against L. donovani promastigotes (IC50: 12.4 µM) and amastigotes (IC50: 4.28 µM), P. falciparum (IC50: 0.028 µM), and T. brucei brucei (IC50: 0.81 µM). In addition, compound X inhibited the growth P. falciparum (IC50: 0.0052 µM) and T. brucei brucei (IC50: 6.49 µM). In silico screening of the active antiprotozoal compounds revealed positive drug-likeness scores as none of Lipinski's rule of five’s criteria was violated by these compounds. However, in-depth pharmacokinetic and mechanistic studies are warranted to support discovery of novel antiprotozoal agents against malaria, leishmaniasis, and African trypanosomiasis by repurposing K+ channel blocker and DHFR inhibitors.

By examining Planck's equation E=hν, one finds an analogy with accounting billing for electricity. Frequency and power have a physical dimension T-1, so one obtains an energy value accounted for over a time interval by multiplying them by this time interval. By investigating this analogy, one finds a surprising mistake in Planck's law for the frequency of black body radiation: confusion between two contexts, one for radiation power and one for a timeless energy density. One goes from one to the other by an accounting-type transformation: a multiplication by 4π/c or c/4π. Correcting this mistake makes a Planck constant h timeless, invalidating the photon definition and de Broglie’s wave-particle duality. Despite this mistake, one obtains the same value for the black body radiation; it goes unnoticed. Consequently, the Planck relation becomes P=hν, with the energy of a cycle equal to h, whatever the frequency. One can consider this cycle as a new photon, which behaves like a particle by its radiation pressure. Its energy-mass equivalence h=mɣc2 gives a mass of 4.134883524·10-15 eV, in the range referenced by the Particle Data Group. This correction of Planck's relation calls quantum physics into question.

Collecting and recording physiological parameters and forwarding this data via telemedicine or remote surveys may significantly increase the health and safety of people working under extreme environmental conditions, like firefighters, mountain rescuers, disaster control employees, military personnel, etc. First, ruggedized systems, as small, lightweight, and flexible as possible, are needed to optimize the goal of increasing occupational health and safety of persons at risk and maximizing their performance during missions. Previous systems could only record a very limited number of parameters, and a few could forward the data online to return information to the user. Therefore, in order to record several meaningful, valid, and reliable physiological parameters synchronized, an extension of existing systems is required. This review highlights this problem and gives an overview of the historical development. The actual status of the systems available was listed and described comparatively. In the end, a proven, promising, and innovative solution is presented that can solve the problem and allow people to work more safely in extreme environments, which may represent the future.

Energy management systems (EMS) play a central role in improving the performance of microgrids by ensuring their efficient operation while minimizing operational costs and environmental impacts. This paper presents a comprehensive study of a MILP-based EMS developed and implemented in MATLAB using Yalmip software for the energy management of a new positive energy district in the city of Savona, Italy, as part of the Interreg Alpine Space Project ALPGRIDS. The main objective of this research is to optimize the functioning of the microgrid, focusing on cost efficiency and environmental sustainability. In pursuit of this objective, the EMS undergoes comprehensive testing and analysis, replicating actual conditions and addressing the diverse demands of end-users across typical days throughout the year considering real electricity selling and purchase price. The EMS also accounts for the reactive power capabilities of the various technologies integrated into the microgrid. The levelized cost of electricity (LCOE) serves as a metric for assessing curtailment costs, while penalties related to reactive power absorption from the distribution network are appraised in alignment with prevailing regulatory guidelines. The case study provides valuable insights into the practical implementation of EMS technology in microgrids and demonstrates its potential for sustainable energy management in complex urban energy districts. The insights and strategies developed through this research contribute to the overall goals of improving energy efficiency and reducing the environmental footprint of future energy districts.

The hepatitis E virus (HEV) is a zoonotic pathogen with a variety of hosts, including pigs, which act as reservoirs. In industrialized countries, sporadic cases caused by genotype 3, contracted by ingestion of contaminated uncooked or undercooked meat, have been reported. However, in developing countries, HEV infection is mainly dominated by genotype 2 and often associated with poor hygiene conditions and drinking water supplies. In West Africa, HEV infection and its circulation in domestic fauna are very poorly documented. The aim of this study was to assess the presence of HEV in pork sold in Saint-Louis. Meat products were collected between 20 and 25 August 2022 in three location of Saint-Louis region. After purchasing 250 g of sample, we minced 2 g of sample for extraction of total nucleic acids using the Purelink™ Viral DNA/RNA kit and then RT-PCR using the One-Taq™ One-Step RT-PCR kit targeting the HEV ORF2 genomic region. The products obtained were visualized on a 1% agarose gel. Of a total of 74 samples, divided into pork meat (n=65) and pork liver (n=9), 5.4% (n=4) were tested positive for HEV. In both cases, 2 samples were positive, representing a rate of 3.1% and 22.2% for meat and pork liver respectively. All new viral sequences obtained form a monophyletic group within HEV genotype 3. These preliminary results reveal a potential circulation of HEV in the pig population. The high proportion of contamination in the pork liver samples highlights a major risk associated with their consumption.

Online learning is gaining massive popularity with time. The e-learning platforms operate differently from traditional educational institutions and hence need different strategy for course recommendations. This survey aims to cover the major emerging research areas in e-learning recommender systems. Our study covers different areas of research including graph-based methodologies, ITS, query optimization, content-based, and collaborative filtering, big data, and association rules mining. This survey aimed to explore all major emerging directions of recommender systems in education. This study analyzed existing literature in all of the areas mentioned before and performed objective-based analysis. A brief performance analysis was also done for the researches where the values were comparable. Limitations of existing researches were also identified and studied to shed some light on future directions.

Recently, Shehata et al. [37] introduced the r+1Rs(B;C; z) matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, dierential properties, new integral representations, k- Beta transform, Laplace transform, fractional k-Fourier transform, fractional integral properties, the k-Riemann{Liouville and k-Weyl fractional integral and derivative operators an extended version of r+1Rs;k matrix function. We establish its relationships with other well known special matrix functions which have some particular cases in the context of three parametric Mittag-Leer matrix function, k- Konhauser and k-Laguerre matrix polynomials. Finally, some special cases of the established formulas are also discussed.

Slave Province in Canada is an Archean granite-supracrustal terrane at the northwestern corner of the Canadian Shield. It is bordered by the Thelon–Taltson orogen (2.0 to 1.9 Ga) to the south-east and the Wopmay orogen (1.9 to 1.8 Ga) to the west. Acasta gneisses exposed in the western-most Slave province and the Wopmay rocks close to the gneisses were collected systematically for K-Ar and laser step-heating 40Ar /39Ar analyses of the biotite and amphibole. The K-Ar biotite ag-es of the four Wopmay samples range from 1816 ± 18 Ma to 1854 ± 26 Ma, which is within the reported U-Pb zircon age range of the Wopmay orogen. The K-Ar biotite ages of the fifteen Acasta gneisses range from 1779 ± 25 Ma to 1877 ± 26 Ma, except for a younger sample (1711 ± 25 Ma). The 40Ar/39Ar biotite analyses of the three samples from the Wopmay orogen give the plateau ages of 1826 ± 21 Ma, 1886 ± 13 Ma, and 1870 ± 18 Ma. On the other hand, the 40Ar/39Ar analyses of the biotite crystals from the Acasta gneiss show a variety of ages. Three samples show the plateau ages of 1877 ± 8 Ma, 1935 ± 14 Ma, and 1951 ± 11 Ma. These plateau ages are a little older than the total gas ages. The 40Ar/39Ar analyses of the amphibole crystals show more varied age rela-tions. The two samples show consistent age relations between the plateau ages (1814 ± 22 Ma and 1964 ± 12 Ma) and the total gas ages (1789 ± 23 Ma and 1967 ± 11 Ma), respectively. Some sam-ples have the apparent old age of 2000 Ma in the middle temperature fractions. These old frac-tions are due to that the originally existed amphibole crystals formed in Archean were affected by the thermal events during the Wopmay orogeny. but did not fully reset. The results suggest that the K-Ar system ages of the biotite and amphibole of the Archean Acasta gneiss that is aged from 4200 to 2600 Ma of zircon U-Pb ages were rejuvenated in the Paleo–Proterozoic ages. The heat source that rejuvenated the K-Ar system ages may have arisen due to the asthenospheric intrusion into the wedge mantle, which took place because of the subduction rollback.

The symmetries of a Riemann surface $\Sigma \setminus \{a_i\}$ with $n$ punctures $a_i$ are encoded in its fundamental group $\pi_1(\Sigma)$. Further structure may be described through representations (homomorphisms) of $\pi_1$ over a Lie group $G$ as globalized by the character variety $\mathcal{C}=\mbox{Hom} (\pi_1,G)/G$. Guided by our previous work in the context of topological quantum computing (TQC) and genetics, we specialize on the $4$-punctured Riemann sphere $\Sigma=S_2^{(4)}$ and the \lq space-time-spin' group $G=SL_2(\mathbb{C})$. In such a situation, $\mathcal{C}$ possesses remarkable properties (i) a representation is described by a $3$-dimensional cubic surface $V_{a,b,c,d}(x,y,z)$ with $3$ variables and $4$ parameters, (ii) the automorphisms of the surface satisfy the dynamical (non linear and transcendental) Painlev\'e VI equation (or $P_{VI}$), (iii) there exists a finite set of $1$ (\mbox{Cayley-Picard})+$3$ (\mbox{continuous platonic})+$45$ (\mbox{icosahedral}) solutions of $P_{VI}$. In this paper we feature on the parametric representation of some solutions of $P_{VI}$, (a) solutions corresponding to algebraic surfaces such as the Klein quartic and (b) icosahedral solutions. Applications to the character variety of finitely generated groups $f_p$ encountered in TQC or DNA/RNA sequences are proposed.

Klebsiella pneumoniae complex is one of the most commonly isolated bacteria within human infections. These microorganisms are opportunistic pathogens that pose a serious threat to public health due to possibility of transmission in the human population. Resistance to carbapenems is one of the most important antimicrobials resistance mechanisms amongst them. In this situation therapeutic options are limited. Therefore, the aim of this study was to evaluate fosfomycin, colistin, ceftazidime-avibactam and meropenem-vaborbactam in vitro activity against multidrug-resistant K. pneumoniae complex strains. The study involved 160 strains of Gram-negative rods: K. pneumoniae – 138 and K. variicola - 22. Minimal inhibitory concentration of fosfomycin was estimated by agar dilution method and for colistin by microdilution method. The susceptibility to ceftazidime-avibactam and meropenem-vaborbactam was determined by gradient strip method. All of the analysed K. pneumoniae complex isolates produced extended-spectrum beta-lactamases and 60.0% carbapenemases. The most of the analysed strains were susceptible to fosfomycin and colistin (62.5%). Among pandrug-resistant K. pneumoniae complex isolates the most were susceptible to colistin (43.9%). Fosfomycin has good activity against ESBL- and VIM-positive isolates from this complex. In turn, colistin has satisfactory in vitro activity against KPC- and VIM-positive isolates from K. pneumoniae complex. Ceftazidime-avibactam has good activity against K. pneumoniae complex strains producing ESBL, KPC and OXA enzymes. In turn, meropenem-vaborbactam has satisfactory in vitro activity against ESBL- and KPC-positive isolates from this complex.

The cooking method is extremely important for the production of low-salt, wet-marinated, fermented golden pomfret because it strongly influences its flavor components and organoleptic quality. There are also significant differences in flavor preferences in different populations. The present study analyzed differences in the aroma characteristics of wet-marinated fermented golden pomfret after boiling, steaming, microwaving, air frying and baking using a combination of an electronic nose, GC-IMS and SPME-GC-MS. Electronic nose PCA showed that the flavors of the boiled (A), steam (B) and microwave (C) treatment groups were similar, and the flavors of baking (D) and air frying (E) were similar. A total of 72 flavor compounds were detected in the GC-IMS analysis, and comparative analysis of the cooked wet-marinated and fermented golden pomfret yielded a greater abundance of flavor compounds. SPME-GC-MS analysis detected 108 flavor compounds, and the results were similar to the baking and air frying. Twelve key flavor substances, including hexanal, isovaleraldehyde, and (E)-2-dodecenal, were identified by orthogonal partial least squares discriminant analysis (OPLS-DA) and VIP analysis. These results show that cooking method is a key factor in the flavor distribution of wet-marinated fermented golden pomfret, and consumers can choose the appropriate cooking method accordingly.

O26 enteropathogenic Escherichia coli (EPEC), possesses a unique pseudocapsule composed of polysaccharides identical to the O antigen in their lipopolysaccharide (LPS) membrane. Therefore, the impact of O26 polysaccharides on the immune evasion mechanisms of capsulated O26 EPEC was investigated. Our findings reveal that the concentration of GlcNAc, an immunodominant unit of O26 polysaccharides capable of activating the MBL (Mannose Biding Lecting) pathway of the complement system, was found to be lower in capsulated EPEC O26 compared to naked shiga toxin-producing E. coli (STEC) O26 strain. It was noted that, unlike the naked STEC strain, the capsulated EPEC O26 strain was protected against lysis by the alternative pathway of the com-plement system by inhibiting C3b adhesion to its bacterial surface. Capsulated EPEC O26 strains were also able to avoid phagocytosis by macrophages. However, the immune evasion provided by the capsule was overcome in the presence of anti-O26 polysaccharide antibodies. Additionally, these antibodies were able to recognize O26 EPEC in the presence of biofilm and inhibit their adhesion to human epithelial cells. Overall, the results indicate that the O26 polysaccharides can generate an effective humoral immune response, making them promising antigens for the de-velopment of a vaccine against capsulated O26 E. coli

The pandemic was an enormous experience all over the world. The type of living, working and study were changed irreversibly. Facing the opportunity to establish old frames of education in universities is impossible. The adoption of new ways of teaching and assessments reveal their convenience and in the same way their weak points. In response to that stage, on 14 December 2022, the EU parliament accepted the "Digital Decade Policy Programme 2030", for the establishment of a digital transformation community (EU 2022). Trakia University had an online assessment system, quizzes for self-training, and final exams, developed in 2008 on Moodle virtual learning environment. During the pandemic, online exams and lectures were conducted using platforms like BigBlueButton in Moodle or Google Meets. The article gives the results of online exams before, during, and after the pandemic. The outcome, without doubt, displays the lowering knowledge level or performance during the social isolation due to COVID-19, and after, and the reasons are discussed. During the second year of the pandemic was mentioned also a high dropout of students. Now the situation is returning to the previous levels, before the pandemic, but the quality of education is not yet reached. The article values the grades results of session exams and has the intention to clarify the influence of the pandemic period on the excellence of high institution education.

Introduction: Dental students’ use of online material to supplement learning has been studied, but educator awareness and reaction to the findings of this research is unknown. This small local study aimed to investigate dental students’ use of online content as a learning tool from an educator’s perspective.Methods: Educators at an Irish dental school completed a survey based on dental students’ use of online learning. Quantitative descriptive analyses were carried out as appropriate on the data collected, and a subsequent focus group was held to gain deeper insight into survey results. Data were analysed for themes by deductive and inductive coding methods.Results: This study found a sample of educators were aware of some student behaviours around online videos. Most educators correctly thought that students are likely to refer to online videos to prepare for dental procedures. Several educators believed that teachers should incorporate videos into their learning, but do not themselves upload or recommend online videos. Most recalled discussing accuracy and/or relevancy of online content with their students. Fewer thought that students would discuss contradictory videos with them. Focus group participants expressed concern over the accuracy of online content. This along with a lack of time were some reasons deterring them from referring students to online videos. Conclusions: An opportunity exists for dental educators and their students to have local dialogue around (1) student use, critical appraisal, and sharing of dental procedural video material; and (2) perceived benefits and challenges of incorporating both school-produced and online videos into teaching and learning. Although arguably non-generalizable beyond this context, this study may inform future research and serve to spark conversations within schools regarding video use for teaching clinical dental procedures.

Cardiotonic steroids (CTS) are a group of steroid compounds derived from certain plants and animals. CTS are selective inhibitors of Na,K-ATPase, so for a long time they were widely used for medical purposes to treat heart failure and some other diseases. However, over time, doctors gradually began to refuse this group of drugs due to their narrow therapeutic range and a number of serious side effects. However, in parallel with the rise and fall of interest in CTS as a drug, interest in them as a single class of high-affinity Na,K-ATPase inhibitors has only increased. Numerous data on the effect of CTS on signaling cascades and cell viability made impelling a search for a rationale for the existence of such a subtle biological regulator. A large number of studies devoted to the potential use of CTS in the treatment of neurodegenerative, oncological, immune and other diseases "revitalized" the already "written off" group of the drugs. If initially the role of exogenous (mainly plant origin) CTS was studied, then by the 90s of the XX century the study of the role of endogenous CTS and their regulatory effects became a popular trend in biology and physiology. The role of endogenous CTS was studied in details in the pathogenesis of cardiovascular diseases [1]. A large number of researchers have unanimously stated that endogenous CTS are very complex regulators of the development of pathological processes; however, the exact cause-and-effect relationship that would unambiguously explain the processes of synthesis, utilization, and the role of endogenous CTS has not yet been established. The effects of CTS in the frame of various regulatory schemes have been described, but the predominant number of studies was devoted to arterial hypertension, heart and renal failure, cancer [2–4], aging [5,6], and neuroinflammation. The effects of both endo- and exogenous CTS on blood cells and have been studied to a much lesser extent.

Printed Circuit Boards (PCBs) are essential to most electronic devices. Digitalization and upgradation of gadget generates lots of PCB-containing electronic waste. Conserving resources and protecting the environment requires recycling such e-waste. The present paper is focused on the recovery of metals from PCBs by physical pretreatment and hydrometallurgical processes. Initially, the waste PCBs were pre-treated to separate metallic and non-metallic fractions. The metallic concentrate was leached using nitric acid (strong oxidative agent) for dissolution of metals. The system was fully jacketed with scrubber and condenser so that no emission of toxic gases to the environment. The process parameters viz. effect of acid concentration, pulp density, temperature, time, etc. were optimized and the obtained data were scientifically validated. Kinetics leaching fitted well with the Shrinking core model, XB = kc.t for Cu, (1-(1-XB)1/2) for Ni and 1-3(1-XB)2/3 + 2(1-XB) for Pb. The optimized conditions derived from these studies will be useful for recovery of metals from waste PCBs, and tin left in the residue could be further treated for the purpose of safe disposal or the utilization in an environmentally friendly manner. The developed process provides environmental benefits and has potential to be commercialized after scale-up studies.

In an era driven by technology and connectivity, where the sphere of learning goes beyond conventional classrooms, e-Service-Learning (e-SL) merges the possibilities of technology with the principles of experiential education in a powerful blend [1]. Service-learning (SL) is an educational proposal that has been cited by UNESCO [2] as an innovative educational tool through which to address the complex challenges of our society. The Sustainable Development Goals [3] provide a framework around which to structure the SL projects and thus develop the skills needed to act on the full range of goals. Embedding digital means open a debate on the intricate relationship between technology, education, and societal impact [4]. By analyzing two focus groups involving faculty, students and community partners, this contribution aims to explore the potential of combining SL and digital empowerment (DE). The focus group participants discussed the opportunities for innovation, the expected impact on them and the society at large, their needs and the pre-conditions needed to make SL and DE successful, and limitations. The results are presented according to the six principles of sustainability education in the university environment, highlighting the transformative potential of combining these principles within SL and DE.

Abstract: Background: chronotype is generally defined as the variability of the phase angle of en-trainment, while the latter reflects the relationship between the timing of a certain rhythm (e.g., sleep-wake cycle) and the timing of an external temporal cue. Individuals can be placed on a spectrum from "morning types" (M types), to "evening types" (E types). E-chronotype has been proposed as a transdiagnostic risk factor for psychiatric conditions and associated with psycho-pathological dimensions. Eveningness seems correlated with both suicidal ideation (SI) and suicidal behavioral (SB), through several possible mediating factors. Immunological alterations also have been linked to later chronotypes and SI/SB. Objective: This narrative review aims to summarize the evidence supporting the possible association between chronotypes and suicide, with the eventual mediating role of neuroinflammation and several psychopathological dimensions. Material and methods: A search of literature (2003-2023) was conducted, using various databases: PUBMED, EMBASE, Scopus, UpToDate, PsycINFO, Cochrane Library. English-language articles were col-lected and screened for eligibility. Results: Despite the apparent absence of a direct correlation between E-chronotype and suicidality, E-chronotype promotes a chain of effects that could be in-volved in an increased risk of SB, in which with neuroinflammation possibly play an intriguing role and some psychopathological dimensions may stand out.

For years, effort has been devoted to establishing an effective bull breeding soundness evaluation procedure; usual research on the subject is based on BBSE (Bull Breeding Soundness Examination) methodologies, which have significant limitations in terms of their evaluation procedure, such as high cost, time-consuming and administratively difficult. This research focuses on the creation of a prediction model to supplement and/or improve the BBSE approach, through the study of two algorithms, Clustering and Artificial Neural Network (ANN), to find the optimum Machine Learning (ML) approach for our application, with an emphasis on data categorization accuracy. The tool is designed to assist veterinary medicine and farmers in identifying key factors and increasing certainty in their decision-making during the selection of bulls for breeding purposes, providing data from a limited number of factors generated from a deep pairing study of bulls. Zebu Bulls, European Bulls, and Crossbred Bulls were the general groupings. The data utilized in the model's creation (N =359) considers five variables that influence improvement decisions. This approach enhances decision-making by 12%. ANN obtained an accuracy of 90%; Precision was 97% for satisfying, 92% for unsatisfying, and 85% for Bad.

The successful advancement of xenotransplantation has led to the development of highly sensitive detection systems for the screening for potentially zoonotic viruses in donor pigs and preventing their transmission to the recipient. To validate these methods, genetically modified pigs generated for xenotransplantation, numerous minipig and other pig breeds have been tested, thereby increasing our knowledge concerning the pig virome and the distribution of pig viruses. Of particular importance are the porcine cytomegalovirus, a porcine roseolovirus (PCMV/PRV) and the hepatitis E virus genotype 3 (HEV3). PCMV/PRV has been shown to reduce the survival time of pig transplants in non-human primates and was also transmitted in the first pig heart transplantation to a human patient. Here, we determined the sensitivities of our methods to detect PCMV/PRV, HEV3, porcine lymphotropic herpesvirus - 1 (PLHV-1), PLHV-2, PLHV-3, porcine circovirus 2 (PCV2), PCV3, PCV4 and porcine parvovirus 1 (PPV1) efficiently and used the methods to screen indigenous Greek black pigs. Since porcine endogenous retroviruses (PERVs) of type A and B are integrated in the genome of all pigs, but PERV-C is not, the animals were screened for PERV-C and PERV-A/C. Our detection methods were sensitive and detected PCMV/PRV, PLHV-1, PLHV-1, PLHV-3, PVC3 and PERV-C in most animals. PPV1, HEV3, PCV4 and PERV-A/C were not detected. These data are of great interest since the animals are healthy and very resistant to diseases.

Information and telecommunications technology (ITT) have expanded into many aspects of modern life and have positively affected human life even in the most remote areas of developing countries. The rapid growth in ITT has led to an improvement in the capacity of computers but simultaneously to a decrease in the product’s lifetime as a result of which increasingly large quantities of e-waste are generated annually. It contains hazardous components that if it is not properly managed, can have adverse environmental and health effects. The management of e-waste poses significant challenges in developing countries. Due to the lack of adequate infrastructure, e-waste is burned or dumped in open areas. Informal and inefficient recycling practices are generally employed which further exacerbate pollution and health risks. So, the implementation of e-waste management, adequate recycling, and waste disposal facilities have become crucial concerns. This article reviews the concept of e-waste generation, challenges, disposal, and its impact on human health & environment in detail.

Hepatitis E virus is a major etiological agent of chronic hepatitis in immunosuppressed individuals. Studies on HEV in the context of liver transplantation have produced mixed results, most of the data coming from studies conducted in high-income countries. This was a prospective cohort study of liver transplant recipients in southeastern Brazil. Recipients were systematically followed for one year, with the objective of determining the prevalence, incidence, genotype, and natural history of HEV infection in this population. We included 107 liver transplant recipients and 83 deceased donors. Positivity for anti-HEV IgG was detected in 11 (10.2%) of the recipients and in eight (9.7%) of the donors. None of the patients tested positive for HEV RNA at baseline or during follow-up. There were no episodes of reactivation or seroconversion, even in cases of serological donor-recipient mismatch or in recipients with acute hepatitis. Acute and chronic HEV infections seem to be rare events in the region studied. That could be attributable to social, economic, and environmental factors. Our data indicate that, among liver transplant recipients, hepatitis E should be investigated only when there are elevated levels of transaminases with no defined cause, as part of the differential diagnosis of seronegative hepatitis after transplantation.

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, we selected and analyzed 199 SCI and SSCI papers on HEI published from 2000 to 2023 by VOSviewer and CiteSpace software. The results indicate that the publication volume of HEI research has grown significantly in recent years, with China and the US being the most productive and influential countries. The author network shows the collaboration and contribution of different researchers and institutions, while the journal network reveals the multidisciplinary nature and scope of the field. The keyword network and the burst keyword analysis identify the main research themes and the emerging hot topics in HEI, such as online learning, big data, and artificial intelligence. The co-citation network of sources illustrates the theoretical and methodological foundations and influences of the field. The paper concludes with some implications and suggestions for future HEI research.

Historically, macrophages have been long implicated in the control of the severity of infectious diseases. This has been based on the observations of a higher risk of severe disease and death upon rechallenge with viral variants due to antibody dependent enhance-ment (ADE) of infection into macrophages. The question remains as to what can account for this potent heterologous protection in macrophages? Here it is argued that the elusive defense mechanism of M1-like pro-inflammatory macrophages may pertain to a novel virus anti-virus response. This system initiates with high replication of human endogenous retrovirus K102 (HERV-K102), a non-pathogenic, protector foamy retrovirus of humans which generates M1-like pro-inflammatory foamy macrophages, glycolysis, and epigenetic changes, all characteristic of trained immunity. This virus-anti-virus system kills virally infected cells by several mechanisms, amplifies the innate interferon response via ‘viral mimicry’, has many unique components that interfere with exoge-nous virus replication, and may be especially adept at neutralizing enveloped exogenous pandemic viruses, such as SARS-CoV-2 and HIV-1. The goal of this treatise is to introduce the multifaceted HERV-K102 protector system, to illustrate how SARS-CoV-2 may target the HERV-K102 protector system by ADE, and to explore how this innate defense system may be exploited for pandemic preparedness.

It is time-consuming for acquiring complete data by fully phase encoding in two orthogonal directions along with one frequency encoding direction. Undersampling in the 3D k-space is promising in accelerating such 3D MRI process. Though 3D undersampling can be conducted according to predefined probability density, the density based method is not optimal. Because of the large amount of 3D data and computational cost, it is challenging to perform data-driven and learning-based 3D undersampling and subsequent 3D reconstruction. To tackle this challenge, this paper proposes a deep neural network called EEUR-Net, realized by optimizing specific undersampling patterns for the fully-sampled 3D k-space data. Innovatively, our undersampling algorithm employs an end-to-end deep learning approach to optimize phase encoding patterns and uses a 3D U-Net for image reconstruction of undersampled data. Through end-to-end training, we obtain an optimized 3D undersampling pattern, which significantly enhances the quality of the reconstructed image under the same acceleration factor. A series of experiments on a knee MRI dataset demonstrated that, in comparison to standard random uniform, radial, Poisson and equispaced Cartesian undersampling schemes, our end-to-end learned undersampling pattern considerably improves the reconstruction quality of undersampled MRI images.

: Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America, and to enhance the utility of drought monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impacts information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and the colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and the warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and indicators are changing over time as the climate warms, and by recommending ways to strengthen the use of indices and indicators in drought decision-making.

E-waste is considered the fastest-growing global waste stream and has become an emerging environmental challenge. The widespread usage of digital devices has generated a large amount of e-waste. According to the Ministry of Commerce, India annually generates ~14.5 lakh metric tons of e-waste and recycles only ~5 % of e-waste. Annually, the global production of e-waste has been expected to increase by 4–5 %. Advancements in IT and communication divisions have improved the usage of electronic equipment. Heavy metals such as (Pb), mercury (Hg), arsenic (As), tin (Sn), and organic chemicals such as polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), polybrominated biphenyls (PBBs), polybrominated dibenzo-p-dioxins (PBDDs), polybrominated diphenyl ethers (PBDEs) are subsequently released from e-wastes and contaminates soil and water sources. These toxic compounds are hazardous to human health and the environment. They are capable of entering various biological systems and causing alterations in respiratory functions of the lungs, DNA damage, impaired functioning of the thyroid, and increased risk of chronic diseases such as cancer and cardiovascular ailments. Such concerns raise the quintessential need to manage e-waste to prevent future hazards. This manuscript critically reviews the sources, health and environmental impact, disposal techniques, recycling, and regulation of e-waste.

This study assessed the impacts of genotypes, environments, and their interaction on the performance of elite cowpea lines for key adaptive, grain yield, and associated traits across different locations. A total of 42 elite genotypes were evaluated in five Nigerian environments, representing various savanna ecologies during the 2021 growing season. The experimental design employed was an alpha lattice arrangement, replicating each genotype three times. The results revealed significant differences among genotypes, environments, and genotype-by-environment interaction for most traits, including days to maturity, 100 seed weight, and grain yield. GGE biplot showed G21 (IT14K-2111-2) and G25 (IT15K-2386-1) as the most stable genotypes across the five environments, G41(IT1K-61-82) was best adapted to Ibadan and Shika, G5 (245-1) was best adapted to Bagauda and Gumel while G30 (IT16K-2365-1) was best adapted to Bauchi. G21 and G25 could be recommended across the five test environments while G41, G30 and G5 are specific to the adapted environments.

This study aimed to assess the microbiological quality of set of fruits and vegetables sold on stalls in the streets and open markets of Dakar, the capital city of Senegal. Samples purchased in seven sites were analyzed to isolate E. coli, Salmonella spp. and Vibrio spp. Some primary samples with a positive microbiological culture were subjected to DNA extraction and subsequent metagenomic analysis. A total of 240 fresh fruit and vegetable samples were collected including lettuce (n=40), tomatoes (n=40), mango slices (n=40), onion slices (n=40), mint leaves (n=40), strawberries and grapes (respectively n=20). Of these samples, 50.83% (122/240) and 60.41% (145/240) was contaminated with Escherichia coli and Vibrio spp. respectively, while Salmonella was not isolated in any product. Levels of contamination with both E. coli (1.3 103 to 6 106 CFU/g) and Vibrio spp. (4.55 102 to 8.73 106 CFU/g) were significantly above the thresholds acceptable for human consumption. The most contaminated samples were lettuce with a prevalence of 98% (39/40) for E. coli and for Vibrio spp. followed by mint leaves with 100% (40/40) and 93% (37/40) of the samples containing for E. coli and Vibrio spp. respectively. Out of 46 samples sequenced, metagenomic analysis revealed high contamination rates for E. coli, Vibrio spp. and Salmonella spp. with 100%, 67.39% and 93.47% of prevalence respectively. On the other hand, the alpha diversity analysis shows a high bacterial diversity in lettuce and mint leaf samples while beta diversity analysis highlighted the presence of two major clusters. Our results stress the need of a surveillance system that extends this investigation to a national scale while increasing the number of sampling sites and products analyzed.

High concentrations of sodium (Na+), chloride (Cl-), calcium (Ca2+), and sulphate (SO42-) are fre-quently found in saline soils. Crop plants cannot successfully develop and produce because salt stress impairs the uptake of calcium, potassium, and water into plant cells. Different intracellular and extracellular ionic concentration changes by salinity, including those of calcium, potassium, and protons. These cations serve as stress signaling molecules in addition to being essential for ionic homeostasis and nutrition. Maintaining an appropriate K+: Na+ ratio is one crucial plant mechanism for salt tolerance, which is a complicated trait. Another important mechanism is the ability for fast extrusion of Na+ from the cytosol. Calcium is established as a ubiquitous secondary messenger, which transmits various stress signals into metabolic alterations that cause adaptive responses. When plants are under stress, the cytosolic-free Ca2+ concentration can rise to 10 times or more from its resting level of 50-100 nanomolar. Reactive oxygen species (ROS) are linked to the calcium alterations, and are produced by stress. Depending on the type, frequency and intensity of the stress, the cytosolic calcium signals oscillate, are transient, or persist for a longer period and exhibit specific "signatures". Both the input and efflux of Ca2+ from the cytosol affect the length and amplitude of the signal. According to several reports, under stress calcium alterations can occur not only in the cytoplasm of the cell but also in the cell walls, nucleus and other cell organelles and the calcium waves propagate through the whole plant. Here, we will focus on how wheat and other important crops absorb Na+, K+ and Cl- when plants are under salt stress, as well as how calcium, potassium, and pH cause intracellular signaling and homeostasis. Similar mechanisms in the model plant Arabidopsis will also be considered.

This study employed e-Vol DX cone beam computed tomography (CBCT) software to assess dentin remnants in the furcation area of mesial canals in mandibular molars during root canal retreatment (RCR). Four groups (Reciproc®, ProTaper Next®, Race Evo®, Protaper Gold®) were subjected to RCR, and CBCT images were captured before (T1) and after (T2) treatment. Measurements of remaining dentin thickness at 1 mm and 3 mm below the furcation were scrutinized. Results revealed no significant differences in mean thicknesses of mesiobuccal (MB) and mesiolingual (ML) canals at 1 mm and 3 mm from the furcation pre-treatment (T1). Post-treatment (T2) showed analogous findings, with no significant differences in mean thicknesses. However, disparities surfaced between MB and ML canals at both distances, both before and after retreatment. In essence, the evaluated instruments exhibited safety in RCR, implying their appropriateness for use in critical areas of mandibular molars without inducing excessive wear. This study underscores the instruments' reliability in navigating danger zones during RCR, contributing valuable insights for dental practitioners handling complex root canal scenarios in mandibular molars.

A rapid and efficient technique using an electronic nose based on a mass detector combined with headspace sampling (HS-SPME-MS e-nose) and chemometric tools was applied to classify beer samples between fresh and aged and between samples contained in aluminium cans or glass bottles, and to predict the shelf life of beer. The mass spectra obtained from the HS-SPME-MS e-nose contain information on the volatile compounds, recorded as the abundance of each ion at different mass-to-charge (m/z) ratios. The analysis was performed on 53 samples aged naturally for eleven months in the absence of light and with a controlled temperature of around 14° C +/- 0.5° C. Principal Component Analysis (PCA) was performed on the data, showing a grouping of samples between fresh and aged. Partial Least Square Discriminant Analysis (PLS-DA) allowed discriminating fresh from aged beers but was not able to discriminate samples packaged in aluminium cans or in glass bottles. Finally, Partial Least Square Regression (PLSR) was applied to build a prediction model and showed to be effective to predict beer shelf life.

The goal of the current study was to discover a novel potential probiotic strain of Lactobacillus spp. with anti-Escherichia coli activity from locally produced yogurt in Tongi, Gazipur, Bangladesh, compare its antagonistic activity with a commercial probiotic mixture of several strains, and approve a novel method for confirming the viability and relative abundance of the microbial community in a probiotic mixer. We carried out 16S sequencing, 16S metagenomics, Transmission Electron Microscopy (TEM) analysis, and other in vitro laboratory experiments to reach this objective. The strain TY-11 was identified as Lactobacillus delbrueckii subsp. indicus (16S sequence accession number OQ652026). It was gram-positive, anaerobic, lactose fermenting, and round-ended rod that typically measured 0.7 to 1.3 µm by 2.2 to 9 µm. In addition to having seven probiotic characteristics, it also showed an antagonistic impact on six different pathogens, but what's more noteworthy is that E. coli was the pathogen it inhibited most strongly (inhibition zone diameter was 18.88±0.18 mm). The most important and ground-breaking finding of this work was determining the probiotic features of a new probiotic strain, TY-11, whose antibacterial activity was virtually as effective as that of the probiotic combination with three different strains. Furthermore, the results of 16S high throughput sequencing and the conventional plate count method demonstrated a strong correlation (0.999) at the genus level, indicating that the use of both of these approaches in combination may be a practical way to assess the relative abundance of the microbial community and their viability in commercially available probiotic blends.

Lignin, and its by-products in the effluent of most agrochemical-based industries like pulp and paper, increase environmental pollution. There is, therefore, an increasing demand to degrade lignin and its derivatives using bacteria-produced ligninolytic enzymes. This study focused on optimizing growth and lignin peroxidase production of ligninolytic potential bacterial strains (E. coli accession no: LR0250096.1 and P. aeruginosa accession no: CP031449.2) for the first time. A submerged fermentation process was used to simultaneously optimize growth and crude lignin peroxidase production using kraft lignin as the substrate. The E. coli and P. aeruginosa were separately cultured under different pH, temperature, lignin (substrate) concentration and incubation periods. It was observed that the enzyme production was growth dependent. The optimum conditions for E. coli were pH 7.5, temperature 30 °C and lignin concentration 1 g/L. For P. aeruginosa the best conditions were pH 6.5, temperature 40 °C and lignin concentration 1 g/L. The enzyme production peaked after 7 days of incubation for both organisms were 21.53 ± 3.11 mg/ml and 18.13 ± 2.1 mg/ml respectively. It is apparent that both E. coli (LR0250096.1) and P. aeruginosa (CP031449.2) are mesophiles bacteria. E. coli function best in alkaline pH while P. aeruginosa prefers a slightly acidic environment. Hence, they are promising candidates in the reduction of lignocellulosic wastes.

The rapid advancement of technology has led to increased electronic consumption and a corresponding rise in e-waste generation. To address this issue, this study develops a low-carbon e-commerce closed-loop supply chain (LCE-CLSC) system with remanufacturer, platform, and the government as key stakeholders. An evolutionary game approach is employed to investigate the system's dynamics, analyzing the impact of stakeholder strategies on system equilibrium. Numerical simulations reveal important findings: Firstly, government initiatives promoting recycling, carbon taxes on traditional products, can incentivize remanufacturers to produce low-carbon items and encourage platform investment in recycling services. Secondly, higher sales revenues motivate remanufacturers to produce low-carbon products. Thirdly, consumer sensitivity to recycling services strengthens waste recovery when platforms increase investments in these services, leading to remanufacturers choosing low-carbon production. Lastly, government subsidies may become ineffective if the cost of remanufacturers' carbon reduction and platforms' recycling services exceeds their affordability. These findings offer insights for the sustainable development of obsolete electronic product recycling systems.

The treatment of critically ill patients remains an evolving and controversial issue. Mechanical circulatory support through a percutaneous approach for the management of cardiogenic shock has taken place in recent years. The combined use of IABP and Impella 2.5 device may have a role to play for this group of patients. A simulation approach may help with a quantitative as-sessment of the achievable degree of assistance. In this paper, we analyse the interaction be-tween Impella 2.5 pump applied as LVAD and IABP using the numerical simulator of the cardi-ovascular system developed in our laboratory. Starting with pathological conditions reproduced using literature data, the simulations were performed setting different rotational speeds for the LVAD and driving the IABP in full mode (1:1) or partial mode (1:2, 1:3 and 1:4). The effects in-duced by drug administration during the assistance were simulated too. The haemodynamic pa-rameters under investigation were: mean aortic pressure, systolic and diastolic aortic pressure, mean pulmonary arterial pressure, mean left and right atrial pressure, cardiac output, cardiac index, left and right ventricular end-systolic volume, left ventricular end-diastolic volume and mean coronary blood flow. The energetic variables considered in the study were: left and right ventricular external work and left and right atrial pressure-volume area. The outcome of our simulations shows that the combined use of IABP and Impella 2.5 achieves adequate support in the acute phase of cardiogenic shock compared to each standalone device. This would allow fur-ther stabilisation and transfer to a transplant centre should escalation of treatment be required.

Currently, with the rapid growth of the population, the demand for metals has increased, especially for the manufacture of electronic devices such as cell phones, computer equipment, among others. Once these devices stop working, most are sent to landfills, which represents a danger since these wastes contain metals and other materials that must be properly managed to prevent them from having a negative effect on the environment and the human being. On the other hand, e-waste contains valuable metals such as copper, gold, and silver, the concentration of which in these materials makes it cost-effective to recover. This paper presents a review of the extraction and recovery of valuable metals from electronic waste by hydrometallurgical methods, as well as patents and industrial processes related to the management and treatment of this waste.

Presence of lipopolysaccharides (LPSs) in the outer layer of outer membranes (OMs) is an almost universal molecular signature of Gram-negative bacteria. The O-antigen or O-polysaccharide (OPS) chains attach to millions of LPS molecule to form a continuous layer on the surface of most of Escherichia coli strains. OPS structure is one of the most variable features of bacteria, with about 200 E. coli O-serotypes currently described. In this review a analyze accumulating evidence suggesting that a vast majority of these OPS types provide robust shields that restrict the access of large molecules to the OM surface. Sophisticated mechanisms employed by bacteriophages to penetrate the OPS barrier are also considered. These are initiated with specific recognition of OPS molecules by phage receptor-binding proteins (RBP), or of other cell-surface molecules that are exposed above the OPS layer. Only after can virions gain access to secondary receptors found closer to the OM surface. The mechanisms of breaking through OPS in most if not all cases appear to rely on mechanical force generated by molecular motors of processive depolymerization or deacetylation of cell surface polysaccharides by enzymatically active RBPs, or by internal rearrangement of the virion.

Background In many African countries, clinical samples are not routinely tested for carbapenem-resistant bacteria, the resistance data remaining limited. Material and methods In March 2020 –June 2022, we collected extended spectrum β-lactamase (ESBL) -producing Enterobacterales (ESBL-PE) isolates from five hospitals in Burkina Faso. The species were identified using API20E and ESBL production confirmed by double-disc synergy test. Production of carbapenemases and AmpC-β-lactamases and phenotypic co-resistance were determined. Results Among the 473 ESBL-PE, 356 were ESBL- E. coli (ESBL-Ec) and 117 Klebsiella spp. (ESBL-K). Of the isolates, 5.3% were carbapenemase and 5.3% AmpC-β-lactamase positive Three types of carbapenemases were identified: 19 NDM, 3 OXA-48 like and 1 VIM. Two isolates produced both NDM and OXA48-like carbapenemases. Carbapenemase rates were highest among isolates in tertiary hospitals. Co-resistance rates were up to 85% for aminoglycosides, 90% for sulfonamides, 95% for fluoroquinolones and 25% for chloramphenicol, Fosfomycin resistance was 6% for ESBL-Ec and 49% for ESBL-K (49%). Conclusion Many ESBL-Ec and ESBL-K co-produced carbapenemases and/or AmpC-β-lactamases, at all healthcare levels and in various samples, with high co-resistance rates to non-betalactams. Carbapenem resistance is no longer rare, calling for testing in routine diagnostics, vigorous resistance surveillance system, and infection control within healthcare.

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by the dimensions of its re-entrant corners and the overall building height. The present study aims to find the wind effects and study of the pressure distribution with different flow patterns. Plan area of the building is around 300 square meter while the height of the building is 50 meters by keeping the equal length of the re-entrant corners. The research is performed using ANSYS CFX academic version and the results are depicted in various forms such as pressure coefficient (Cpe), stream lines in both vertical as well as in specific surface and pressure contours. The analysis is carried out by varying the wind incident angles, from 0° to 90° at the interval of 15°. The building dimension are scale down to perform the test on length scale of 1:100. Since the considered building model exhibits symmetry along both the axes, present study mostly emphasis on examining re-entrant corners located in the building. This method yields valuable information about how air circulates and how pressure is distributed across a broad spectrum of wind angles. This study provides valuable insights into flow circulation and pressure distribution for a wide range of wind angles.

Shared micromobility has gained significant attention in the field of transportation engineering in recent years as an environmentally friendly, convenient, and easily accessible transportation mode. Like other medium-sized cities, Birmingham, Alabama implemented a shared micromobility pilot program in 2021 that captured the attention of local travelers. This study examined shared e-scooter usage and associated travel patterns in Birmingham using 2021-2022 field data. From these data, ArcGIS maps were used to showcase trip origins and destinations. To gain a further understanding of e-scooter travel patterns in the study area, zip code and block group densities were calculated. Additionally, a negative binomial regression model was constructed to identify determinants of shared e-scooter trips. The analysis results showed that the usage of shared e-scooters was the highest during the nighttime, on weekends, and in the fall season. Furthermore, the research findings indicated that shared e-scooters experienced their highest utilization rates in areas with a higher proportion of educated and higher-income individuals. These findings suggest that travelers’ mode choice related to the use of micromobility modes is influenced by environmental and demographic factors. Overall, this case study offers valuable contributions to the understanding of the role of shared e-scooters in Birmingham's transportation landscape and can guide transportation authorities in other medium-sized cities in their efforts to plan for micromobility options.

As distinct human societies, three unique intentional communities are investigated regarding their preferred consensus decision-making practices. It is Identified that each has adopted a different form of consensus decision-making to solve potential group-wide interpersonal conflict. The individual attributes of these three consensus decision-making practices are considered, both from the perspective of maintaining group stability and in relation to individual member's mental health. The communities are a Canadian self-directed public senior elementary and secondary school, an annual English conference for those self-identifying as on the autistic spectrum, and a self-producing Korean popular music (K-pop) group. It is found that the intentional community and participants’ mental health are sustained regarding each of the three consensus decision-making practices. Nevertheless, the resulting decisions generate various stresses within the communities, both as a whole and concerning the individual members. To retain group cohesion and maintain individual mental health, these stresses must be recognized and understood by participants. The novel finding of this research is that, dependent on the time available for decision-making, and the members’ perspective adopted, intentional communities might practice more than one form of consensus decision-making and still support both group cohesion and individual mental health, maintaining the democracy of these distinct societies.

This article investigates on the radial and non-radial geodesic structures of the generalized K-essence Vaidya spacetime. Within the framework of K-essence geometry, it is important to note that the metric does not possess conformal equivalence to the conventional gravitational metric. This study employs a non-canonical action of the Dirac-Born-Infeld kind. In this work, we categorize the generalized K-essence Vaidya mass function into two distinct forms. Both the forms of the mass functions have been extensively utilized to analyze the radial and non-radial time-like or null geodesics in great details inside the comoving plane. Indications of the existence of wormhole can be noted during the extreme phases of spacetime, particularly in relation to black holes and white holes, which resemble the Einstein-Rosen bridge. In addition, we have also detected the distinctive indication of the quantum tunneling phenomenon around the central singularity.

Sporadic Alzheimer’s disease (AD) derives from an interplay among environmental factors and genetic variants, while epigenetic modifications have been expected to affect the onset and progression of its complex etiopathology. Heterozygous carriers of the apolipoprotein E gene (APOE)4 allele have a 4-fold increased risk of developing AD, while APOE 4/4-carriers have a 12-fold increased risk in comparison with the APOE 3-carriers. The main longevity factor is the homozygous APOE ε3/ε3 genotype. In the present narrative review article, we summarized and described the role of APOE epigenetics in aging and AD pathophysiology. It is not fully understood how APOE variants may increase or decrease AD risk, but this gene is known to affect amyloid- and tau-mediated neurodegeneration directly or indirectly, also by affecting lipid metabolism and inflammation. For sporadic AD, epigenetic regulatory mechanisms may control and influence APOE expression in response to external insults. Diet, a major environmental factor, has been significant associated with physical exercise, cognitive function, and the methylation level of several cytosine-phosphate-guanine (CpG) dinucleotides sites of APOE.

Historic sites are important components of every city's cultural history because they preserve rich historical knowledge and distinctive values passed down from previous generations to the present. Due to the progress of urbanization and modernization, many historic sites face pressure from damage and transformation. In this paper, a method for assessing cultural heritage damage was developed to measure the extent of spatial damage in historic sites. Using sample data obtained in Xiyang, Qixian, and Xiaoyi, all historic cities in Shanxi Province, Mainland China, and combined weights were estimated using the Delphi technique and the CRITIC weight method. Following this, the Spatial Damage Degree Model (SDDM) based on K-means cluster analysis and K-nearest neighbor (KNN) classification was developed. The findings show that the model efficiently solves the problem of assessing spatial damage levels in historic sites. Through multiple linear regression analysis, it was shown that the damage to historic sites was predominantly caused by three factors: natural erosion, construction damage, and planning and policy. SDDM was used to calculate the spatial damage levels of historic sites, allowing conservators to fully comprehend the features and concerns related to historic sites. As a result, more scientific and rational preservation approaches may be developed, improving the efficiency of historic site restoration and conservation and encouraging the sustainable development of urban and rural heritage.

Urinary tract infections (UTIs) caused by pathogens, particularly E. coli, have spontaneously become resistant to antimicrobial drugs in recent years. Therefore, regular monitoring and alternative strategies for the antimicrobial agent are crucial for combating antimicrobial resistance and bacterial biofilms. Here, we report a new cobalt iron oxide-conjugated tin oxide nanocomposite that can kill bacteria and treat multidrug-resistant E. coli posing UTIs. Following the isolation and identification of E. coli, we tested 57/134 samples against sixteen commonly used antibiotics phenotypically using the disk diffusion method to determine their sensitivity pattern. Of the 57 E. coli isolates, 66% (38/57) were multidrug-resistant. The E. coli isolates were resistant to cephradine (70.17%), ceftriaxone (59.64%), and azithromycin (59.64%), followed by cefixime (54.38%), cefuroxime sodium (52.63%), and co-trimoxazole (50.87%). X-ray diffraction results showed the crystallite sizes were about 5.68 and 8.84 nm in pure SnO2 nanoparticles and 95% SnO2-5% CoFe2O4 nanocomposite, respectively. Energy-dispersive X-ray spectroscopy and Fourier transform infrared determined the fundamental structure of the nanocomposite, encompassing Co, Fe, Sn, and O. Moreover, FTIR measurements implied that the distinct functional groups in both SnO2 and CoFe2O4 nanoparticles existed in a 95% SnO2-5% CoFe2O4 nanocomposite. Field emission scanning electron microscope analysis uncovered that the SnO2-CoFe2O4 nanocomposite had a size of roughly 24 nm and was spherical. In addition, the biosynthesized SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite were evaluated for their antibacterial activity. At a minimum 100 µg/mL concentration, SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite showed high antibacterial activity. The SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite demonstrated antibacterial activity on multidrug-resistant E. coli at 10 ± 0.7 and 16 ± 0.8 mm zone of inhibition, respectively. In conclusion, the new SnO2-CoFe2O4 nanocomposite might be a potential candidate for treating UTIs caused by drug-resistant E. coli in the foreseeable future.

The Covid-19 crisis has been one of the most relevant economic shocks in the history of the modern economy, mainly due to the restrictions on travel and social interaction taken by the authorities (quarantines, closure of schools, artistic activities, bars, and restaurants, capacity in stores), to reduce the transmission of the virus (Sars-Cov2), having consequences on the national productions of all countries (about 7% for the loss of GDP worldwide). In our study, we analyze, through clustering methods, the effects of the level of contagion, economic projections, and economic mitigation measures taken by governments for managing the pandemic. According to the analyses, it can be concluded that a low infection rate implies a lower loss of product and economic savings when applying economic mitigation measures, taking relevance in the management of sanitary measures to reduce the transmission of the virus (and the temporality of these).

This article is a study on the (k,s)-Riemann-Liouville fractional integral, a generalization of the Riemann-Liouville fractional integral. Firstly, we introduce several properties of the extended integral of continuous functions. Furthermore, we make the estimation of the Box dimension of the graph of continuous functions after the extended integral. It presents that the upper Box dimension of the (k,s)-Riemann-Liouville fractional integral for any continuous functions is no more than the upper Box dimension of the functions on the unit interval I=[0,1], which indicates that the upper Box dimension of the integrand f(x) will not be increased by the σ-order (k,s)-Riemann-Liouville fractional integral ksD−σf(x) where σ>0 on I. Additionally, we prove that the fractal dimension of ksD−σf(x) of one-dimensional continuous functions f(x) is still one.

Understanding surface water evaporation in tropical catchments is pivotal for effective water management, but limited research exists on stable isotopic (δ2H and δ18O) assessment of water evaporation losses. Our study bridges that gap, examining stable isotopes in meteoric water and surface waters across tropical regions, both humid and semi-arid. Using the Craig-Gordon model, we calibrated evaporation-to-inflow (E/I) ratios, identifying distinct E/I variations between seasons and regions. Notably, the semi-arid region consistently exhibited higher E/I ratios due to climatic characteristics. By integrating the Hamiltonian Monte Carlo and the No-U-Turn Sampler, we were able to quantify uncertainties in isotopic and meteorological parameters, resulting in E/I estimates within 68% and 95% confidence intervals. Our Bayesian model insights are critical for freshwater resource optimization and hydrological modeling in tropical regions.

Energy efficiency considerations in terms of reduced power dissipation is a significant issue in the design of digital circuits for very large-scale integration (VLSI) systems. Quantum-dot cellular automata (QCA) is an emerging ultra-low power dissipation approach, distinct from the traditional complementary metal-oxide semiconductor (CMOS) technology, for building digital computing circuits. Developing fully reversible QCA circuits has the potential to significantly reduce energy dissipation. The multiplexer is a fundamental element in the construction of useful digital circuits. In this paper, a novel, multilayer, fully reversible QCA 8:1 multiplexer circuit, with ultralow energy dissipation, is introduced. The proposed multiplexer power dissipation is simulated using the QCADesigner-E version 2.2 tool, describing the microscopic physical mechanisms underlying the QCA operation. The results showed that the proposed reversible QCA 8:1 multiplexer consumes 89% less energy than the most energy-efficient 8:1 multiplexer circuit presented previously in the scientific literature.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

The COVID-19 pandemic was declared in March 2020 and is still ongoing. The course of the epidemic remains uncertain, and mutations in the coronavirus, as well as the emergence of new variants of concern, make it possible that there will be periodic surges in the number of cases. Moreover, it is not clear how quickly and to what extent the effectiveness of vaccination will decline as the virus continues to mutate. One possible solution to combat the rapidly mutating coronavirus is the development of pan-coronavirus vaccines that stimulate the production of antibodies against conserved elements of the virus. Another approach could be the creation of safe vaccine platforms that can be rapidly adapted to deliver new, specific antigens in response to viral mutations. Recombinant probiotic microorganisms that can produce viral antigens by inserting specific viral DNA fragments into their genome show promise as a platform and vector for mucosal vaccine antigen delivery. With a well-established safety profile and the ability to transform into vaccine candidates, probiotic bacteria have significant research potential. The authors of this study have developed a convenient and universal technique for inserting the DNA sequences of pathogenic bacteria and viruses into the gene that encodes the pili protein of the probiotic strain E. faecium L3. The paper presents data on the immunogenic properties of two E. faecium L3 vaccine strains, which produce two different fragments of the coronavirus S1 protein, and provides an assessment of the protective efficacy of these oral vaccines against coronavirus infection in Syrian hamsters.

Many studies have been conducted using pectin for modified drug delivery. In this regard, the goal of the work was to obtain interpolyelectrolyte complexes based on citrus or apple pectin and the Eudragit® EPO and study properties from the standpoint of using these carriers for oral drug delivery. Turbidity, gravimetry, viscosity, elementary analysis and FTIR spectroscopy, DSC analysis were used for physicochemical characterization. Diffusion-transport characteristics were studied to assess the swelling ability of the matrices and the release of diclofenac sodium. Mathematical modeling of the release parameters was carried out using the Krosmayer-Peppas equation. During the turbidity study, stoichiometry compositions were selected for the studied IPECs EPO/PeсA and EPO/PeсC at pH values = 4.0, 5.0, 6.0, 7.0. FTIR spectra of the complexes are characterized by an increase in the intensity of the bands at 1610 cm-1 and 1400 cm-1. According to the DSC analysis IPEC has a certain Tg = 57.3°C. The highest release rates are shown by IPEC EPO/PecC_1 and EPO/PecC_4. The mechanism of drug transport from the matrices IPEC EPO/PecC, IPEC EPO/PecA_3 and EPO/PecA_4 can be characterized as Super Case II. Anomalous (non-Fickian release) is typical for IPEC EPO/PecA_1 and EPO/PecA_2. Thus, the resulting systems are suitable for colon-specific drug delivery systems.

With the rise of internet technology and the growth of mobile communications, the global economy has undergone a significant transformation, shifting towards digital and soft markets. As a result, great efforts have been made to establish virtual marketplaces that provide customers with an exceptional shopping experience. One crucial aspect of this new paradigm is marketing, which has led to the emergence of a new stage known as E-marketing. In E-marketing, understanding customer behavior is of utmost importance. Marketing teams and companies are eager to gain insights into how different customer segments react to their products. Marketing strategies are now developed based on customer information such as financial status, location, age, gender, and more. As a result, the abundance of customer data generated by these new commerce technologies has surpassed the capabilities of traditional data analysis methods. To extract valuable knowledge from this vast amount of data, data mining technologies have come into play. Techniques such as clustering, classification, and prediction are utilized to mine marketing data and uncover hidden patterns and trends. The impact of data mining on E-marketing has been the subject of analysis in this study. A questionnaire-based review was conducted to collect the necessary data, which was then analyzed using SPSS 23 software. The study's results demonstrate that data mining can significantly enhance the performance of E-marketing by providing intelligent and efficient predictions of customer behaviour. Moreover, this technology offers similar advantages for end-customers as well. By leveraging the power of data mining, companies can gain valuable insights, tailor their marketing efforts, and ultimately provide better products and services to their customers in the digital marketplace.