The article addresses the problem of course development in virtual teaching and learning spaces by teachers to support blended learning in the Ecuadorian unified baccalaureate. For this purpose, a documentary analysis of 465 papers selected by a search in Scopus and Google Scholar about blended learning and 145 papers selected by a search in Scopus and Google Scholar about development of virtual courses was carried out. The definition of the first concept is qualitatively different from the previous ones by analysing it as a form of organisation and assessing the configuration of face-to-face and distance learning depending on the educational objective. The second concept defined presents the unrepeatable and unique character of each course given by the configuration of its digital resources, the characteristics of these resources and the new qualities that are conferred on them. Subsequently, based on them, the methodology that contributed to the development of courses in virtual spaces as a support to blended learning is proposed. Unlike other methodologies, the proposal explicitly states its conceptual apparatus and the necessary requirements for its introduction in an educational organization. It incorporates important actions that do not appear in other methodologies such as cross-cutting processes including quality assurance with its corresponding metrics, maintenance, recall and evaluation of previous actions.

Increased proliferation of IT services in all sectors has reinforced the adoption and diffusion across all levels of education and training institutions. However, lack of awareness of and knowledge about the key challenges and opportunities of elearning, seem to allude policymakers, resulting in low adoption or increased failure rate of many e-learning projects. Our study tries to address this problem through a review of relevant literature in e-learning. Our goal was to draw from the existing literature, insights into the opportunities and challenges of e-learning diffusion, and the current state-of-research in the field. To do this, we employed a systematic review of literature on some of the salient opportunities and challenges of e-learning innovation for educational institutions. These results aimed to inform policymakers and suggest some interesting issues to advance the research and adoption and diffusion of e-learning. Moreover, the bibliometric analysis shows that the field is experiencing high research attraction among scholars. However, several research areas in the field witnessed relatively low research paucity. Based on these findings, we discussed topics for possible future research.

The learning system is primarily based on teaching, and teaching through digital resources is referred to as e-learning. As the world progresses towards success day by day, the use of technology, digital devices, and modern techniques is becoming increasingly prevalent. The global shift from traditional paperwork to digital learning is one of the most significant changes in the education sector. However, many factors have created numerous hurdles during the online setup. The Covid-19 pandemic has led to serious problems all over the world, with the education sector being one of the most affected. One of the greatest challenges students face during online education is the lack of digital infrastructure, especially in remote areas of Pakistan. The biggest challenge is connecting students with teachers due to limited internet access. Without proper internet connectivity, both students and teachers cannot access educational materials. In this context, the government plays a crucial role in providing adequate facilities to students, particularly in primary schools. If proper infrastructure is not made available during this pandemic, students will be deprived of a good quality education. Therefore, good infrastructure is essential for effective online education. With the proper resources in place, students will be able to receive a quality education.

In recent years, online learning has become one of the most popular methods of educational delivery due to advances in technology, which has been made even more evident in the COVID-19 lockdown period. Online education has evolved into a distinct field of study within the educational system over the last few years. It is also important to note that parallel with the growth in this field, there has also been an increase in the number of scholarly journals that regularly publish research in this field, reflecting the importance of this field in the modern day. In spite of the fact that online learning offers a wide range of educational options, from short courses to full-time degrees, as well as being accessible, flexible, environmentally friendly, and affordable, there are also certain challenges associated with this educational approach. These challenges include the lack of social interaction, technical errors, a lack of hands-on training, and difficulties in assessing students. It is, therefore, imperative to ask the crucial question of whether online learning can replace traditional classroom learning or whether it can supplement it in hybrid models with it, as well as what factors and conditions are likely to determine this in the short- and long-term, as well as how it will be blended together in the future. The purpose of this commentary is to provide a brief summary of the current status of both learning models, as well as their pros and cons, in order to answer the question that was posed above.

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.

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.

In the age of digital revolution technology is being used more and more in education around the world to improve student learning. By enabling ongoing skill development and knowledge acquisition through digital platforms e-learning has become a crucial tool. Through E-Learning online learning is becoming increasingly popular and effective in addition to traditional methods of instruction as highlighted by the latest statistics from Badan Pusat Statistik Indonesia (BPS). In order to address the issues of scalability, interactivity and security in e-learning platforms. This study introduces a web-based learning environment that is focused on teaching programming. Leveraging the MERN stack, while also integrating TypeScript for improved code reliability, Next.js for accelerated React.js functionality, Tailwind CSS for responsive design. Backend features include media management with Cloudinary, secure video streaming with VdoCipher, data storage with MongoDB, and caching with Redis. Iterative development will be following agile methodology. In order to create a vibrant and encouraging learning environment the platform includes interactive course pages multimedia content real-time feedback mechanisms and community-building tools. Despite some early difficulties the implementation phase effectively achieved development goals. To further support international online learning initiatives further efforts will be directed toward improving platform security and functionality.

Sexual issues and treatment side effects are not routinely discussed with men receiving treatment for prostate cancer and support to address these concerns is not consistent across settings. This study evaluates a brief e-learning resource designed to improve sexual wellbeing support and examine its effects on healthcare professionals’ sexual attitudes and beliefs. Healthcare professionals (n=44) completed an online questionnaire at baseline which included a modified 12-item sexual attitudes and beliefs survey (SABS). Follow-up questionnaires were completed immediately after the e-learning and at 4 weeks. Data were analysed using one-way, repeat measures ANOVAs to assess change in attitudes and beliefs over time. Significant improvements were observed at follow-up for a number of survey statements including ‘knowledge and understanding’, ‘confidence in discussing sexual wellbeing’ and the extent to which participants felt ‘equipped with the language to initiate conversations’. The resource was seen as concise, relevant to practice, and as providing useful information on potential side effects of treatment. Brief, e-learning has potential to address barriers to sexual wellbeing communication and promote delivery of support for prostate cancer survivors. Practical methods and resources should be included with these interventions to support implementation of learning and long-term changes in clinical behaviour.

E-learning with many outstanding advantages in training has drastically changed the self-study process due to the ability to personalize and effectively meet the learning activities of learners. E-learning and building an e-learning environment are currently paying attention and being deployed in many universities in Vietnam with different scope and levels. Especially in the current period, when science and technology are developing, many applications of technology and technology products have been applied in the field of education, changing the way of teaching and learning activities, the practice of both lecturers and students. Big Data and Artificial Intelligence (AI) technologies have replaced people not only for manual labor but also for intellectual labor, including the teaching of teachers. Many software applications have been used to replace people in the transmission of knowledge, testing, and evaluation of training quality, especially E-learning online training programs. However, in Vietnam today, the output quality of these online training programs has not been highly appreciated compared to similar programs in the world. The cause of this situation is that the training, teaching, and learning are not effective. Therefore, in this article, I will give some analysis, evaluate the current teaching and learning methods and propose solutions to enhance the interaction and initiative in the teaching and learning process of lecturers and students to improve the quality of online training in the future.

This review paper delves into using micro-credentials in higher education ecosystems as a digital enablers. Micro-credentials, which are digital credentials that attest to a learner’s mastery of a specific skill or knowledge area, are becoming more popular in higher education. The paper examines the successful implementation of micro-credential frameworks in higher education, using case studies to demonstrate the advantages of micro-credentials. The review emphasizes the agility and flexibility of microcredentials, which enable learners to acquire new skills quickly and respond to changes in the job market. In addition, the paper discusses the digital nature of micro-credentials and how they allow institutionsto provide targeted, skills-based training that isrelevant to employers. It also explores how micro-credentials are delivered through online platforms, making them convenient and easily accessible for learners. The review underscores the significance of digital infrastructure, connectivity, and public utility for promoting micro-credentials. The paper argues that micro-credentials function as a digital enabler for higher edu- cation ecosystems, allowing learners to acquire targeted training and enabling institutions to expand their offerings and reach more students. The paper concludes by highlighting the potential for micro-credentials to help bridge the skills gap and equip learners with the skills necessary to succeed in today’s digital economy.

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

There is limited evidence showing how developing universities in South Africa have successfully adopted and effectively used online learning to support students for positive learning experiences. Presently, there are numerous challenging factors with regards to Information and Communication Technology (ICT) adoption in South African developing universities. The purpose of this paper was to investigate the extent of online learning support for student learning at developing universities in South Africa. The study resides in an interpretive framework from a philosophical perspective as it adopts a hermeneutic framework, with the literature obtained being classified, mapped, critically assessed, and themes and arguments developed. There is scant evidence of studies conducted and published between 2000 and 2024 on online learning support as a pedagogical strategy for student learning in the developing universities in South Africa. The findings resulted in five emerging themes from the literature review. These major themes include lack of ICT governance; poor digital infrastructure; lack of ICT skills; budget constraints; and accessibility and inclusivity challenges. This study is expected to have a significant impact on the development of universities' online learning policies and practices. It will also contribute to the pedagogical strategies and frameworks of academics and scientific knowledge on how scholars should perceive online learning support in the context developing universities.

The Digital Bangladesh initiative is a comprehensive strategy aimed at transforming Bangladesh into a digitally advanced, economically competitive, and socially inclusive nation. This term paper explores the multifaceted causes and effects of the initiative, including the roles of government policies, economic imperatives, social factors, and technological advancements. The initiative leverages emerging technologies such as artificial intelligence, blockchain, and the Internet of Things to drive innovation, improve public service delivery, and enhance quality of life. Economic growth, improved governance, enhanced social inclusion, and environmental sustainability are key outcomes of this digital transformation. However, challenges such as cybersecurity threats, the digital divide, and infrastructural constraints must be addressed to sustain progress. Looking forward, the future prospects of the Digital Bangladesh initiative are promising, with potential for significant advancements in various sectors. By prioritizing strategic policymaking, fostering public-private partnerships, and ensuring sustainability and resilience, Bangladesh can realize its vision of becoming a Digital, prosperous, and inclusive nation.

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.

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.

The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students' environments.

There has been widespread criticism about the rates of participation of students enrolled on MOOCs (Massive Open Online Courses), more importantly, the percentage of students who actively consume course materials from beginning to the end. This study sought to investigate this trend by examining the factors that influence MOOC adoption and use by students in selected Ghanaian universities. The Unified Theory of Acceptance and Use of Technology (UTAUT) was extended to develop a research model. A survey was conducted with 270 questionnaires administered to students who had been assigned MOOCs; 204 questionnaires were retrieved for analysis. Findings of the study show that MOOC usage intention is influenced by computer self-efficacy, performance expectancy, and system quality. Results also showed that MOOC usage is influenced by facilitating conditions, instructional quality, and MOOC usage intention. Social influence and effort expectancy were found not to have a significant influence on MOOC usage intention. The authors conclude that universities must have structures and resources in place to promote the use of MOOCs by students. Computer skills training should also be part of the educational curriculum at all levels. MOOC designers must ensure good instructional quality by using the right pedagogical approaches and also ensure that the sites and learning materials are of good quality.

Higher education teaching staff members need to build a scientifically accurate and comprehensive understanding of the function of the brain in learning to optimize teaching and achieve excellent student learning. An international consortium developed a professional development six-module course on educational neuroscience and online community of practice applying design thinking. A mixed methods research design was employed to investigate the attitudes of thirty-two (N=32) participating academics using a survey comprising eleven closed and open questions. Data analysis methods included descriptive statistics, correlation, generalized additive model and grounded theory. The overall evaluation demonstrated a notable satisfaction level with regard to the quality of the course. Given the power of habits, mentoring and peer interactions are recommended to ensure the effective integration of theoretical neuroscientific evidence into teaching practice.

The COVID-19 outbreaks have caused universities all across the globe to close their campuses and forced them to initiate online teaching. This article reviews the pedagogical foundations for developing effective distance education practices, starting from the assumption that promoting autonomous thinking is an essential element to guarantee full citizenship in a democracy and for moral decision making in situations of rapid change, which has become a pressing need in the context of a pandemic. In addition, the main obstacles related to this new context are identified, and solutions are proposed according to the existing bibliography in learning sciences.

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.

Background: Serious games are conceptualized as a broad topic and overlap segments of more modern forms of education: e-learning, edutainment, game-based learning, and digital game-based learning. Serious Games aligns with digitalization and the modern era and creates novel opportunities for learning and assessment in medical education. Escape rooms, a type of serious games, merge mental and physical aspects to reinforce critical skills useful in daily life. It challenges logic and reasoning and demands careful analysis of situations to correlate and solve different stages of the escape room under pressurized, timed conditions. Furthermore, it serves as an adequate environment to build problem-solving skills, communication skills, and leadership skills through the collaboration of people to achieve a common goal. The aim of this study was to investigate the applications of escape rooms in Medical Education. Method: This study investigated the applications of escape rooms in medical education. Serious games are expanding in education and have attained great relevance due to their intriguing and intrinsically motivating attributes. Within serious games, we focused on escape rooms in which participants are locked in a room, faced with puzzles that must be solved to ‘escape the room’. Compiling the data from the first 100 hits of medical application of escape rooms, we found 72 cases and categorized them by year, specialty, participants structure, simulation experience, and design. Results: We reported on escape rooms in medical education by the year in which they were reported, the medical specialty, the participant structure, grouped or individual, the experience design; real, hybrid, or digital, and the modality of the delivery. 72% of the escape rooms focused on four main areas: nursing education (25.0%), emergency medicine (22.2%), pharmacy (12.5%), and interprofessional education (12.5%). Most of the escape rooms had a group-based physical design and little attention was given to provide a detailed description of the design considerations, such as the pathway type (linear, semi-linear, open). Conclusion: Escape rooms are applied in a wide range of medical education areas. In Medical Education, group-based on-site escape rooms with a focus on nursing, emergency medicine, pharmacy and interprofessional education dominates the implementation landscape. To further advance the field, stronger emphasis on making explicit the design considerations will advance the research and inform implementations.

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

Educational data-mining is an evolving discipline that focuses on the improvement of self-learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of educational data. In the arena of education, the heterogeneous data is involved and continuously growing in the paradigm of big-data. To extract meaningful information adaptively from big educational data, some specific data mining techniques are needed. This paper presents a clustering approach to partition students into different groups or clusters based on their learning behavior. Furthermore, personalized e-learning system architecture is also presented which detects and responds teaching contents according to the students’ learning capabilities. The primary objective includes the discovery of optimal settings, in which learners can improve their learning capabilities. Moreover, the administration can find essential hidden patterns to bring the effective reforms in the existing system. The clustering methods K-Means, K-Medoids, Density-based Spatial Clustering of Applications with Noise, Agglomerative Hierarchical Cluster Tree and Clustering by Fast Search and Finding of Density Peaks via Heat Diffusion (CFSFDP-HD) are analyzed using educational data mining. It is observed that more robust results can be achieved by the replacement of existing methods with CFSFDP-HD. The data mining techniques are equally effective to analyze the big data to make education systems vigorous.

The period of the COVID-19 pandemic resulted in a rapid development of innovative education methods, in particular using e-learning and remote work tools. The effects of this development are also post-pandemic changes in formal teaching regulations, in particular in higher education, allowing classes and lectures to be carried out with Blended Learning or Flipped Classroom methods. This paper provides information about a case study of implementing ICT technologies with elements of the mentioned methods in one of the subjects at a technical university. The implemented tools and solutions in the field of e-learning and interactivity are presented, along with information regarding their perception by students during two academic years in the post-COVID-19 period. The analysis of results of these information and student evaluations indicates their generally positive approach to such innovations in the educational path, and at the same time shows significant challenges for teachers to increase the attractiveness and effectiveness of the teaching process and the development of practical, technical skills of students.

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.

In recent years information and communication technologies (ICT) play a significant role in all aspects of modern society and impact socioeconomic development in sectors as education, administration, business, medical care and agriculture. The benefits of such technologies in agriculture can be appreciated only if farmers use them. In order to predict and evaluate the adoption of these new technological tools, the technology acceptance model (TAM) can be a valid aid. The paper measures the potential acceptance of an e-learning tool designed for EU farmers and agricultural entrepreneurs. Starting from a literature review of the technology acceptance model, by analyzing the most commonly used external variables in the fields of e-learning, Agriculture, and Virtual reality, the analysis shows that computer self-efficacy, individual innovativeness, computer anxiety, perceived enjoyment, social norm, content and system quality, experience and facilitating conditions are the most common determinants addressing technology acceptance. Furthermore, findings evidenced that the external variables have a different impact on the two main beliefs of the TAM Model, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). This study is expected to bring theoretical support for academics when determining the variables to be included in TAM extensions.

This research assess the effects of training program based on the usage of the digital learning objects in teaching practice at the Northern Borders University staff. E Assessment through the tablets and smart phones and the teachers’ attitudes towards such way of evaluation is the major objective of this study as the researcher expects that the assessment mechanism in the university through utilization of tablets and smart phones and its application will inevitably bring in a systematic improvement in the assessment and evaluation process of the curricula. Moreover, making use of the e learning objects in training will make a significant change in e training program of the university. Hence, the researcher has chosen voluntary random samples from the university teaching staff (men\women) from various different faculties (medicine, medical sciences, science, education and arts, business administration, home economics, and science and literature). These samples included 300 members of the teaching staff. In a group of 20 to 25 members, a personal training was conducted regarding the usage of tablets and smart phones and its applications in the assessment process. Each group participated by producing a complete e-assessment for their students in the Northern Borders University and by the e learning system i.e. Blackboard and Question Mark. The research also depends on the semi-experimental design of multiple groups and on testing the groups’ pre and post achievement tests. In addition, the research identifies the level of the university teaching staff in using the tablets and the smartphones and its applications in the assessment process by the note card that the individuals have during the test.

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.

This qualitative study explores the implementation and conformation process of digital devices in teaching and learning before, during, and after the COVID-19 pandemic in Nepal. Using Rogers' Diffusion of Innovation Theory as a framework, the study examines the adoption and adaptation of digital devices by in-service secondary mathematics teachers (n=62) and their perceptions and preferences towards instructional modality. The findings suggest that despite the increased reliance on digital devices during the pandemic, there is a less likelihood of using them in face-to-face classrooms in developing countries like Nepal. The adoption of online learning has not yet reached the confirmation stage, even after the onset of the COVID-19 pandemic. Prior to the pandemic, online learning was not widely implemented or confirmed by teachers in developing countries societies. The study also provides important insights into the challenges and opportunities of using digital devices in post-COVID-19 classrooms, and its implications for policymakers and educators in Nepal.

Introduction. Until now, the impact of learning variables on consumers' choices concerning Chinese product brands in the international online shopping framework remains unknown. Accordingly, this study aims to examine the effect of those learning variables on global consumers' choices of Chinese product brands. Method. A total of 44,704 transactions related to the buying process have been collected from a programming language and the Octopus Software within a Chinese International Online Shopping platform. Analysis. The 44,704 transactions have been analyzed through a Decision Tree. Results. The study points out that the number of e-retailers' subscribers reinforces the international consumers' trust online. At the same time, the pricing levels and quantity of product availability are used by global online consumers to assess the originality of Chinese product brands. Conclusions. First, this study extends the existing literature on consumer learning by going beyond the learning variables considered. Second, the study boosts consumer learning literature by elucidating the most significant learning variables guiding international online consumers' choices and purchases. The application of the results will enable brands and e-retailers to understand (1) the stages of the international online consumers' choice; (2) the buying strategies of global consumers.

The devastating COVID-19 pandemic forced academia to go virtual. Educational institutions around the world have stressed online learning programs in the aftermath of the pandemic. However, because of insufficient access to ICT, a substantial number of students failed to harness the opportunity of online learning. This study explores the latent digital divide exhibited during the COVID-19 pandemic while online learning activities are emphasized among Bangladeshi students. It also investigates the digital divide exposure and the significant underlying drivers of the divide. A cross-sectional survey was employed to collect quantitative data mixed with open-ended questions to collect qualitative information from the student community. The findings revealed that despite the majority of students have physical access to ICT but only 32.5% of students could attend online classes seamlessly, 34.1% of the students reported the data prices as the critical barrier, and 39.8% of students identified the poor network infrastructure is the significant barrier for them to participate in online learning activities. Although most students possess physical access to the device and the Internet, they face the first-level digital divide due to the quality of access and maintaining subscriptions. Consequently, they fail to take advantage of physical access, resulting in the third-level digital divide (Utility Gap) and submerging them into a digital divide cycle. This paper aimed to explore the underlying issues of the digital divide among Bangladeshi students to assist relevant stakeholders (e.g., the Bangladesh government, Educational Institutions, Researchers) in providing the necessary insights and theoretical understanding to arrange adequate support for students to undertake conducive online learning activities.

This study assesses the development of professional skills in university students using serious games (SG), from a sustainability perspective. The Sustainable Development Goals (SDGs) were set by the United Nations’ 2030 Agenda for Sustainable Development. Universities are strategic agents in the transformation process towards sustainability. This way, they should be committed to promoting such sustainable values in the students through curricular sustainability, implementing active methodologies and SG for that purpose. Transversal skills are essential for the development of future graduates. The objective of this study was to assess which professional skills should be developed through the SG called The Island, to improve the degree of student satisfaction with the incorporation of a sustainable curriculum. The data were obtained using a questionnaire, and then analysed using linear regression models, with their inference estimated through the goodness of fit and ANOVA. The first results indicated that the implementation of the SG promoted a strengthening of the students' sustainable curriculum through the development of those skills. It was concluded that the key to success in education for sustainable development is improving the development of strategic thinking, collaborative thinking, and self-awareness, in addition to encouraging systemic, critical, and problem-solving thinking.

Purpose: The purpose of this study is to further explore how e-loyalty and E-marketing influences E-trust and satisfy the demand by offering fresh perspectives based on research as well as emphasis on the factors influencing the E-trust such as culture as a mediator. This study not only contributed theoretically but also presented practical implementations. Design/methodology/approach: Online survey was used to obtain data by focusing the Hospitality sector (Hotel Industry) and verifying the conceptual framework. Data was collected in multiple time lags. Findings: Findings showed that the E-trust influenced by E-loyalty and E-Marketing. E-trust comes from the previous experiences, e-loyalty and e-marketing. Further, some trends such as culture influenced the e-trust. Research limitation/implications: The present study is quite suitable for those Researchers interested in learning more about the effects of E-loyalty and E-marketing on user E-trust and how to mitigate cultural influences can benefit from the current study. This research also has implications for those who wish to improve market allure and survival in digital world. This study focused on the hospitality sector (Hotel Industry) in China; however, the sector and geography could be altered to suit the needs of the study's participants. Practical implications: The present study delivers the practical guidelines which are quiet suitable for understanding the formation of E-loyalty, E-marketing, and E-trust through which specific E-marketing strategy can be designed to deal with the consumer’s E-loyalty and their expectations as per their Cultural perspective. At some particular regions/countries, cultural trends are more important than practical market. This research study practically showed that how culture changed the consumer set of mind. Originality/value: The relationship between E-loyalty, E-marketing, E-trust, specifically with the cultural influence in digital market has been the subject of few research.

We transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphone or tablet with the option for further enhancement of presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicate a positive impact of the program using a robot as compared to the program without robot. In-situ observations and interviews with day care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

Development of supervised AI algorithms requires a large amount of labeled images. Image labelling is both time-consuming and expensive. Therefore, we explored the value of e-learning derived annotations for AI algorithm development in medical imaging. Methods We have developed an e-learning platform that involves image-based single click labelling as part of the educational learning process. Ten radiology residents, as part of their residency training, trained the recognition of pneumothorax on 1161 chest X-rays in posterior-anterior projection. Using this data, multiple AI algorithms for detecting pneumothorax were developed. Classification and localization performance of the models was tested on an independent internal testing dataset and on the public NIH ChestX-ray14 dataset. Results The AI models F1 scores on the internal and the NIH dataset were 0.87 and 0.44, respectively. Sensitivity was 0.85 and 0.80 for classification and specificity 0.96 and 0.48 for classification. F1 scores were 0.72 and 0.66, sensitivity 0.72 and 0.72. False positive rate was 0.36 and 0.32 for localisation. Conclusion Our results demonstrated that e-learning derived annotations are a valuable data source for algorithm development. Further work is needed to include additional parameters such as user performance, consensus of diagnosis, and quality control in the development pipeline.

The objective of the present study is to isolate phages targeting multidrug resistant (MDR), extended spectrum beta lactamase (ESBL) positive clinical isolate of E. coli ( U1007), sequence and analyze the phage genome and use machine learning tools to predict host cell surface receptor and finally evaluate the efficiency of monophage and phage cocktail in vitro and in vivo in a zebrafish model. Phage specific for E. coli U1007 was isolated from Ganges River (designated as U1G), Cuoom River (designated as CR) and Hospital waste water (designated as M phage). The obtained phages were triple purified and enriched. U1G phages had a greater burst size of 124 PFU/cell and a latent time of 25 min.M phage had a burst size of 150 PFU/cell with a shortlatent time of 20min. Similarly CR phage has a short latent 20 min and a burst size of 115 PFU/cell. Based on capsid architecture, U1G phage resembles Podoviridae, CR phage is structurally similar to Myoviridae and M phage has morphology that resembles Siphoviridae. Genome sequencing and analysis revealed that the size of the U1G phage genome is 73275 bp Whereas that of CR phage and M phage are 45236 bp and 45294 bp, respectively. All three genomes were marked by the absence of genes encoding tRNA sequence, antibiotic resistant or virulent genes. A machine learning (ML) based multi-class classification model using algorithms such as Random Forest, Logistic Regression, and Decision Tree were employed to predict the host receptor targeted by all 3 phages and the best performing algorithm Random Forest predicted LPS O antigen , LamB or OmpC for U1G FhuA, OmpC for CR phage and FhuA, LamB, TonB or OmpF for the M phage as the host receptor targeted by the receptor binding protein (RBP) of the phages. In vitro time kill assay showed that treatment with monophages alone and along with colistin resulted in regrowth whereas phage combinations significantly reduced the regrowth and by 24h the phage cocktail along with colistin produced a significant 3 log declinein cell counts relative to the untreated control. In vivo intramuscular infection study in zebrafish showed that phages were non toxic and a cocktail of dual (U1G +M) phage along with colsitin resulted in a significant 3.5 log decline in cell counts whereas triple phage combination along with colistin resulted in 3 log decline in cell counts probably due to host receptor competition. Our study highlights the potential of phage cocktail therapy in mitigating MDR clinical isolate of E. coli in vitro and in vivo.

Numerous goods and services are now offered through online platforms due to the recent growth of online transactions like e-commerce. Users have trouble locating the product that best suits them from the numerous products available in online shopping. Many studies in deep learning-based recommender systems (RSs) have focused on the intricate relationships between the attributes of users and items. Deep learning techniques have used consumer or item-related traits to improve the quality of personalized recommender systems in many areas, such as tourism, news, and e-commerce. Various companies, primarily e-commerce, utilize sentiment analysis to enhance product quality and effectively navigate today's business environment. Customer feedback regarding a product is gathered through sentiment analysis, which uses contextual data to split it into separate polarities. The explosive rise of the e-commerce industry has resulted in a large body of literature on e-commerce from different perspectives. Researchers have made an effort to categorize the recommended future possibilities for e-commerce study as the field has grown. There are several challenges in e-commerce, such as fake reviews, frequency of user reviews, advertisement click fraud, and code-mixing. In this review, we introduce an overview of the preliminary design for e-commerce. Second, the concept of deep learning, e-commerce, and sentiment analysis are discussed. Third, we represent different versions of the commercial dataset. Finally, we explain various difficulties facing RS and future research directions.

The use of Learning Management Systems (LMS) has had a rapid growth over the last decades. Great efforts have been recently made to assess the level of performance of the students online due to the COVID-19 pandemic. Faculty members with limited experience in the use of LMS such as Moodle, Edmodo, MOOC, Blackboard and Google Classroom can have some problems creat-ing online tests. In this work, a new plugin for Moodle is presented: FastTest PlugIn. This plugin is based on a Microsoft® Excel spreadsheet and it can be used to export questions to Moodle. Us-ers of FastTest PlugIn can create question pools in an easy and intuitive way. A literature review about plugins used to import/export questions in Moodle is carried out. Then, the characteristics of FastTest PlugIn are presented. At the end, the characteristics of the main plugins found in the literature are discussed and compared with the ones of FastTest PlugIn.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

Background and Objectives: The site types of Eucalyptus urophylla × Eucalyptus grandis clonal plantations in southern Yunnan were compared, aiming to provide basis for site selection and scientific plantations management. Materials and Methods: In this study, 80 standard plots were set up in the 6−9-year-old Eucalypts plantations in Pu'er City and Lincang City. Furthermore, the quantitative theory I model and canonical correlation analysis were used to analyze the relationship between dominant tree growth traits and site factors, and evaluate the growth potential of E. urophylla × E. grandis plantation. Results: The multiple correlation coefficient between 8 site factors (altitude, slope, slope level, soil thickness, slope direction, texture, soil bulk density, and litter thickness) and the quantitative growth of the dominant wood was 0.825 (P < 0.05). According to the correlation coefficient of the quantitative regression model, slope, altitude, and soil thickness were the main factors for the classification of E. urophylla × E. grandis plantations in southern Yunnan. In addition, E. urophylla × E. grandis plantations grew best downhill and mid uphill at relatively low altitude, where the soil layer was thick and composed of weathered red soil. Contrastingly, E. urophylla × E. grandis plantation growth was extremely poor in uphill sites at higher altitude, where the soil layer was thin and composed of semi-weathered purple soil. Furthermore, total N, and available B, Cu, and Zn content, as well as soil organic matter content in the soil had a great influence on the growth of E. urophylla × E. grandis. Conclusions: Nitrogen and phosphate fertilizer as well as trace elements such as B, Zn, and Cu can be properly applied in middle- and low-yield forests to promote the growth and development of E. urophylla × E. grandis plantations.

Background: Electronic cigarette (e-cigarette) use among youth in Poland has become very popular. The aim of this study was to identify potential points of access to these products among students aged 16-17 before implementation of sales restrictions to minors in Poland in November 2016. Methods: A school-based, cross-sectional survey was administered in 2015-2016 in 21 secondary/technical schools across two regions of Poland. Analyses focused on 341 students aged 16-17 who reported past 30-day use of e-cigarettes. Pearson chi-square analyses were utilized to examine associations between access-related items, e-cigarette use, and demographics. Results: Among youth e-cigarette users, the most common access to their first e-cigarette was from a friend (38%), followed by purchasing from vape shops (26%). Similar patterns emerged when students were asked about the access to their currently used e-cigarette. Most youth reported no difficulty purchasing cartridges/e-liquid containing nicotine (90%); the majority of users (52%) reported buying such products in vape shops. Conclusions: Prior to implementing age-related sales restrictions, youth access to e-cigarettes and paraphernalia did not pose any significant barriers. Poland’s introduction of a new age limit on e-cigarette sales may help limit the number of youth who purchase e-cigarettes from vape shops.

In the dynamic landscape of online shopping, predicting user behaviors such as clicks, cart additions, and orders is crucial for optimizing sales strategies. Traditional recommendation systems often focus on a single objective, limiting their effectiveness in a multifaceted e-commerce environment. This article proposes a multi-objective recommendation system that leverages previous events in user sessions to forecast these key metrics, addressing challenges such as imbalanced positive and negative samples, varying session lengths, and the need for effective sampling techniques. Our approach integrates LightGBM, XgBoost, and Recbole GRU4Rec through ensemble learning, combining the strengths of these models to enhance prediction performance. Extensive evaluations demonstrate that our model outperforms existing methods, offering significant improvements in accuracy and robustness. This work provides a comprehensive solution for online retailers to better predict user behaviors and optimize their sales strategies, ultimately enhancing customer satisfaction and business outcomes.

Objective: Fludeoxyglucose F18 positron emission tomography (FDG PET) can give early clues for diagnosing Alzheimer’s disease (AD). Our objective was to use the same scan to predict Apolipoprotein E4 (ApoE4), known to be a risk factor. A second objective was to determine the brain regions and imaging features associated with this gene allele that can potentially help elucidate the mechanisms of the disease and better comprehend the images. Method: We employed data from 112 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). PET and structural MRI data were co-registered with ANTx, and the Freesurfer tool delineated 95 whole brain, 19 hippocampal, and 9 amygdala regions. Using PyRadiomics we extracted 120 radiomic features from these segments. We employed a hybrid feature selection strategy. The HistGradientBoosting (HGB) classifier was evaluated using stratified five-fold cross-validation. Results: The proposed radiomics model predicted the homozygous ApoE4 genotype, with an AUC of 0.945 an accuracy of 0.875, a sensitivity of 0.914, and a specificity of 0.838. Reducing the feature set to seven key features resulted in a slightly decreased performance (AUC: 0.889). The mean values of the features showed statistically significant (p<0.05) incremental deterioration between different groups of homozygous ApoE4 carriers. Conclusion: Our findings underscore the critical role of specific brain regions and associated features in differentiating ApoE4 carriers. The hippocampus, entorhinal cortex, amygdala, thalamus, and pars orbitalis exhibited significant associations with the ApoE4 genotype. By employing SHAP analysis, we identified key features driving model predictions, enhancing interpretability, and providing insights into the underlying pathophysiology.

E-tourism is one of the most important modern services to achieve the development of the tourism sector while relying on sophisticated communication technologies. Certainly, these innovations in the field of tourism have disrupted this sector with new and different dimensions of tourism development. This has led various regions and countries to accelerate the search for the tools that are necessary to achieve excellence and sustainable development in tourism. This research aims to study the development factors of e-tourism to achieve excellence and sustainable development in the tourism of the Ha’il region. Therefore, we applied two analyses: in the first one, we used a statistical analysis based on the survey sent to employees from tourism companies. The objective of this analysis is to determine the main factors of e-tourism to achieve excellence in tourism in the Ha’il region. The results of the statistical analysis have given us the following elements: There are only four main factors that allow authorities to achieve excellence in tourism in the Ha’il region, namely ST, CP, HRS, and SC factors. Then we proceed with a second analysis, to determine the main factors of excellence in tourism that drive the achievement of sustainable development in tourism in the Ha’il region. For this reason, we applied an artificial intelligence method based on the unsupervised machine learning technique. The results obtained from the machine learning technique show that five factors determine the excellence in tourism and reveal the sustainable development of Ha’il’s tourism. These factors are ST, CP, FP, HRS, and GC. Consequently, we consider that all the factors found in both analyses are important to realise excellence in tourism and sustainable development in tourism. However, to achieve sustainable development in tourism in Ha’il, Saudi authorities must develop the three common factors found in the two analyses, namely ST, CP, and HRS.

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.

Various metals and semiconductors containing Printed Circuit Boards (PCBs) are abundant in any electronic device equipped with controlling and computing features. These devices inevitably constitute E-waste after the end of service life. The typical construction of PCBs includes mechanically and chemically resistive materials, which significantly reduce the reaction rate or even avoid accessing chemical reagents (dissolvents) to target metals. Additionally, the presence of relatively reactive polymers and compounds from PCBs requires high energy consumption and reactive supply due to the formation of undesirable and sometimes environmentally hazardous reaction products. Preliminarily milling PCBs into powder is a promising method for increasing the reaction rate and avoiding liquid and gaseous emissions. Unfortunately, current state-of-the-art milling methods also lead to the presence of significantly more reactive polymers still adhered to milled target metal particles. This paper aims to find a novel single and two-stage disintegration-milling approach that can provide the formation of metal-rich particle size fractions. The morphology, particle fraction sizes, bulk density, and metal content in produced particles were measured and compared. Research results show the highest bulk density (up to 6.8 g·cm-3) and total metal content (up to 95.2 wt. %) in finest sieved fractions after the single-step milling of PCBs. Therefore, the concentrations of about half tested metallic elements are higher in the single milled specimen and with lower adhered plastics concentrations, as compared to double milled specimens.

Eucalyptus, a therapeutic plant mentioned in the ancient Algerian pharmacopeia, specifically two species belonging to the Myrtaceae family - E. radiata and E. cinerea, were investigated in this study for their antibacterial, antioxidant, and anti-inflammatory properties. The study used aqueous extracts (AE) obtained from these plants, and the extraction yields were found to be dif-ferent. The in vitro antibacterial activity was evaluated using a disc diffusion assay against three typical bacterial strains. The results showed that E. radiata EAq was effective against all three strains, while E. cinerea EAq was only effective against E. coli. Both extracts displayed significant antioxidant activity compared to BHT. The anti-inflammatory impact was evaluated using a pro-tein (BSA) inhibition denaturation test. The E. radiata extract was found to inhibit inflammation by 75% at a concentration of 250 g/ml, significantly higher than the placebo. Ellagic acid, a pri-mary phytochemical found in the extracts, demonstrated noteworthy toxic and pharmacokinetic characteristics and a maximum binding energy of -7.53 kcal/mol for its anti-TyrRS activity in sili-co. The study suggests that the extracts and their primary phytochemicals could enhance the effi-cacy of antibiotics, antioxidants, and non-steroidal anti-inflammatory drugs (NSAIDs). As phar-maceutical engineering experts, we believe this research contributes to developing natural-based drugs with potential therapeutic benefits.

Communication and effective interactions are inevitable necessities in every organizational setting. In this era of information and communication technology, where limitations and difficulties in proper communication and interactions between different entities of various organizations have been reduced maximally, the government, stakeholders, and citizens of the different nations should also utilize these available tools in a way to improve the maximum performance in governance through interactions and e-participation between the citizens, stakeholders, and the government parastatals. This research focuses on examining the available and most preferred applications or platforms which encourage the best level of communication and interaction through E-participation among the citizens, stakeholders, and government from the local government lev-el taking Nigeria as a case study

We are calling for a paradigm shift in engineering education. In times of the Fourth Industrial Revolution (“4IR”), a myriad of potential changes is affecting all industrial sectors leading to increased ambiguity that makes it impossible to predict what lies ahead of us. Thus, incremental culture change in education is not an option any more. The vast majority of engineering education and training systems, having remained mostly static and underinvested in for decades, are largely inadequate for the new 4IR labor markets. Some positive developments in changing the direction of the engineering education sector can be observed. Novel approaches of engineering education already deliver distinctive, student centered curricular experiences within an integrated and unified educational approach. We must educate engineering students for a future whose main characteristics are volatility, uncertainty, complexity and ambiguity. Talent and skills gaps across all industries are poised to grow in the years to come. The authors promote an engineering curriculum that combine timeless didactic tradition, such as Socratic inquiry, project-based learning and first-principles thinking with novel elements (e.g. student centered active and e-learning by focusing on the case study and apprenticeship pedagogical methods) as well as a refocused engineering skillset and knowledge. These capabilities reinforce engineering students’ perceptions of the world and the subsequent decisions they make. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent communicators better navigating increasingly complex multistakeholder ecosystems.

According to the World Health Organization, approximately 20 million people worldwide are infected annually with the hepatitis E virus (HEV). There are 4 main genotypes of HEV. Genotype 1 and genotype 2 are common in developing countries and are transmitted by contaminated water from a fecal-oral route. Genotype 3 and genotype 4 are common in developed countries and can lead to occasional transmission to humans by undercooked meat. Hepatitis E virus 1 and HEV3 can lead to fulminant hepatitis, and HEV3 can lead to chronic hepatitis and cirrhosis in immunocompromised patients. The majority of patients with HEV infection are asymptomatic and usually have spontaneous viral clearance without treatment. However, infection in immunocompromised individuals can lead to chronic HEV infection. Both acute and chronic HEV infections can have extrahepatic manifestations. No specific treatment is required for acute HEV infection, no treatment has been approved in chronic infection and no HEV vaccine has been approved by the (United States) Food and Drug Administration. This review focuses on the molecular virology (HEV life cycle, genotypes, model systems, zoonosis), pathogenesis, clinical manifestation, and treatment of chronic HEV infection, especially in immunocompromised patients, to provide clinicians a better understanding of the global distribution of these infections and the significant effect they can have on immunocompromised patients.

Popular, industry, and academic attention is increasingly being paid to Electrically-Assisted Pedal Cycles (EAPCs), also known as electric bikes, or e-bikes. Attention has also begun to be given to ideas of the electric bicycle as a component of “electric velomobility” or “e-velomobility” and to the particular benefits of electric bicycles over conventional bicycles. We present here the effects of EAPCs on the tangible quantitative levels of greenhouse gas emission reductions, increased mobility performance, and greater accessibility of cycling; and the intangible qualitative level of perceptions of electric cycling and those who engage in it, harmonized with transhumanist lines of thought in order to articulate a sociotechnical imaginary of the electric bicycle as an augmentation to a cyclist’s physical body. Through a combination of original research and drawing on prior literature, we articulate the idea of a “cyborg cyclist” as a vision for present and future e-velomobilities, and emphasize the ability of appropriate technology to augment the capabilities of cyclists, viewing rider and machine as a single unit, while also warning of the possible risks of inappropriate types of electric bicycle. Such a view, we believe, adds a much-needed technology-positive view to present debates, and highlights especially the ability of the EAPC as a rehabilitative and augmentative mobility tool, and as a means of displacing more carbon-intensive means of transportation, particularly the private car.

This work investigated the effects of manufacturing variations including coil resistance, initial pod mass, and e-liquid color on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime with light color e-liquid was (mean) = 149, (standard deviation) = 10.7 puffs while pods with dark color e-liquid was = 185, = 22.7 puffs with a difference of ~36 puffs (p &lt;0.001). Total mass of e-liquid consumed until coil failure was = 1.93, = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was = 0.0123, = 0.0003 [g]. During usage, TPM yield per puff of pods with light color e-liquid was relatively steady while it was continuously decreasing for pods with dark e-liquid. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. There is a potential correlation of e-liquid color with both coil lifetime and TPM yield per puff. Change of e-liquid color might have been a result of oxidation which changed some nicotine into nicotyrine.

This study focuses on a new class of functions called sub-b-s-preinvex, that is a generalization of sub-b-s-convex and preinvex functions, and discusses some of their properties. A new sub-b-s-preinvex programming is introduced and the sufficient conditions of optimality under this type of function is established.

The alkylation of 1,1,2-trimethyl-1H-benzo[e]indole with 2-chloroacetamide, followed by work-up of the reaction mixture with a base and the subsequent treatment of a crude product with acetic acid gives 10a,11,11-trimethyl-10a,11-dihydro-8H-benzo[e]imidazo[1,2-a]indol-9(10H)-one. The structure assignments were based on data from ¹H, ¹³C and ¹⁵N NMR spectroscopy. The optical properties of the obtained compound were studied by UV-vis and fluorescence spectroscopy.

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 E-learning system has achieved great development after the pandemic. In this work, we proposed three artificial intelligence-based enhancements to our linguistic interactive E-learning system from different aspects. Compared with the original phonetic transcription exam system, our enhancements include an MFCC+CNN-based disordered speech classification module, a Transformer-based Grapheme-to-Phoneme converter, and a Tacotron2-based IPA-to-Speech speech synthesis system. This work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.

Multi-sensor data fusion of E-tongue and E-nose can provide a more comprehensive and more accurate analysis results. However, it also brings some redundant information, it is a hot issue to reduce the feature dimension for pattern recognition. In this paper, the taste-olfactory data fusion based on E-tongue and E-nose combined with Support Vector Machine (SVM) was used to classify five different beers. First, the taste and olfactory feature information were obtained based on E-tongue and E-nose. Second, the original feature data of single system were fused, then Principal Component Analysis (PCA) was applied to extract principal components, Genetic Algorithm-Partial Least Squares (GA-PLS) was used to select the characteristic variables, 20 subsets were generated with those variables based on the best Variable Importance of Projection (VIP) score. Finally, the classification models based on SVM were established, also c and g of SVM were calculated by Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the classification results of all subsets were obtained. The results showed that the classification accuracy using data fusion was much higher over single E-tongue and single E-nose, and the variable selection method by VIP had the best classification performance in #12 subset coupled with GA-SVM.

This qualitative research explores the transformative role of Artificial Intelligence (AI) in Supplier Relationship Management (SRM) within the e-commerce sector. SRM is critical for e-commerce platforms to maintain efficient supply chains, optimize supplier interactions, and ensure competitive advantage in a dynamic marketplace. AI technologies offer advanced capabilities such as predictive analytics, machine learning algorithms, and natural language processing, which revolutionize traditional SRM practices by enhancing decision-making accuracy, mitigating supply chain risks, and fostering personalized supplier relationships. Through semi-structured interviews with 20 e-commerce professionals and industry experts, this study investigates AI's impact on supplier selection, operational efficiencies, and strategic supplier relationships. Findings highlight AI's ability to streamline supplier evaluation processes, improve demand forecasting accuracy, and optimize inventory management strategies. AI also facilitates personalized supplier engagement through sentiment analysis and real-time insights, promoting collaboration and trust. Ethical considerations, including algorithmic bias and data privacy, emerge as significant concerns in AI adoption for SRM. Addressing these challenges is crucial to maintaining stakeholder trust and ensuring responsible AI deployment. Furthermore, technological integration barriers and organizational readiness are identified as critical factors influencing successful AI implementation. Looking forward, the study underscores the potential of AI to drive innovation and competitiveness in e-commerce SRM, emphasizing the importance of ethical AI practices, technological infrastructure investments, and organizational preparedness for sustainable growth.

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.

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

Background - Chronic kidney disease with unknown aetiology (CKDu) is a progressing disease which is affecting many Sri Lankans’ yearly, this disease is slow progressive, irreversible and asymptomatic disease. Patients suffering from CKDu over the past two decades have been evaluated using the estimated glomerular filtration rate (e-GFR). This is the standard test performed under WHO guidelines to investigate and grade the CKDu, and this creatinine clearance is measured in this in order to grade the patient. Backache has been a common symptom presented in most of the chronic kidney disease patients (CKD), patients with CKDu are liable to get backache due to the renal failure that takes place (Jayathilake et al., 2013; Redmon et al., 2016). Objective – To detect a correlation between serum creatinine values and level of backache presented in the patient. Method -Using an interview based questionnaire to assess patients’ body condition and the degree of backache is assessed, 59 patients were part of the study for a period of five months and had an average age of 60.3 years. The questionnaire answers are scaled into four main types of backache from the least to the most painful based on the pain scale adapted from Kapkia. Serum creatinine is measured using an automated analyzer which is measured using Jaffe’s reaction. Using Pearson R correlation, the relationship was determined between serum creatinine and backache (Kafkia et al., 2011). Results – The results were obtained for 58 patients (n=58), where the mean backache score was 2.30 and mean serum creatinine value 2.77. The Pearson R value obtained was 0.01 which is indicating almost no relationship between backache and serum creatinine. Patients with stage 3 kidney disease (n=14) had an average E-GFR of 38.0, stage 4 (n=38) with 22.3 and stage 5 (n=6) with 14.0. Conclusion – Backache can be used an indicator of CKDu since it is presented in most patients’ suffering from the disease but unable to be used to determine the stage of CKDu suffered by the patient due to the external causes that leads to backache. Several predisposing factors such as temperature, water source and agricultural activity can influence the backache.

The past 40 years have seen automotive Electronic Control Units (ECUs) move from being purely mechanical controlled to being primarily digital controlled. While there has been significant improvements in terms of passenger safety and vehicle efficiency including optimised fuel consumption, rising ECU numbers have resulted in increased vehicle weight, greater demands placed on power,more complex hardware and software, ad-hoc methods for updating software, and subsequent rise in costs for both vehicle manufacturer and consumer. To address these issues, the research presented in this paper proposes virtualisation technologies to be applied within automotive Electrical/Electronic (E/E) architecture. To proposed approach is evaluated through a comprehensive study of the CPU and memory resource requirement in order to support container-based ECU automotive functions. This comprehensive performance evaluation reveals that lightweight container virtualisation has the potential to welcome a paradigm shift in the E/E architecture, promoting consolidation and enhancing the architecture through power, weight and cost savings. Container based virtualisation will also enable a robust mechanism to facilitate online dynamic software updates throughout the lifetime of a vehicle.

The use of e-scooters and e-bicycles has been on the rise with an increased medical and financial burden. Our purpose was to identify risk factors for increased medical charges and recommend appropriate steps. We studied a retrospective cohort presenting to a level 1 urban trauma center from January 2018 through July 2019 due to micro-mobility platforms. The primary outcome for comparison was total billing cost and a regression analysis was performed to identify variables associated with higher cost. A total of 4073 patients were identified. The majority of which were males (67%), aged 20-30 years (41%). Helmet use reported in only 39.8%. Radiologic studies were performed more often in the e-bicycle group. Total billing charges amounted to 28.3 million New Israeli Shekels ($7.9 million). Average total cost was higher for e-bicycle injuries and in non-helmet users. Other factors associated with higher cost were age, and time of day 12:00-18:00. We recommend that urban cities invest in infrastructure in advance to micro-mobility introduction, regulate the use of e-platforms, designate resources for education on personal protective equipment and prepare medical centers in advance.

The investment in digital e-Health services is a priority direction in the development of global health care systems. While people are increasingly using the Web for health information, it is not entirely clear what is the physicians’ attitude towards digital transformation, and the acceptance of new technologies in healthcare. The aim of this cross-sectional survey study was to investigate physicians’ self-digital skills, and their opinions on obtaining online health knowledge by patients, as well as the recognition of physicians’ attitudes towards e-Health solutions. Principal Component Analysis (PCA) was performed to emerge the variables from self-designed questionnaire, and cross-sectional analysis comparing descriptive statistics and correlations for dependent variables using the one-way ANOVA (F-test). 307 physicians participated in the study, reported using the internet mainly several times a day (66.8%). Most participants (70.4%) were familiar with new technologies and rate their e-Health literacy high, although 84.0% reported the need for additional training in this field, and reported a need to introduce a larger number of subjects shaping digital skills (75.9%) in medical studies 53.4% of physicians perceived Internet-sourced information as sometimes reliable, and in general assessed the effects of using it by their patients negatively (41.7%). Digital skills increased significantly with frequency of internet use (F = 13.167; p = 0.0001), and decreased with physicians’ age, and the need for training. Those who claimed that patients often experienced health benefits from online health showed higher digital skills (-1.06). Physicians most often recommended their patients to obtain laboratory test results online (32.2%), and to arrange medical appointments via the Internet (27.0%). Along with the deterioration of physicians’ digital skills, the recommendation of e-Health solutions decreased (r = 0.413), and lower the assessment of e-Health solutions for the patient (r = 0.449). Physicians perceive digitization as a sign of the times, and frequently use its tools in daily practice. The evaluation of Dr. Google’s phenomenon and online health is directly related to their own e-Health literacy skills, but there is still a need for practical training to deal with digital revolution.

The new need to move to an online mode of administration has necessitated the adoption of Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS). The conventional paper-based administrative memorandum is relatively costly, requires manpower, insecure and non-confidential, prone to unauthorized access and has a relatively slow cycle time; among others. An electronic memo (e-memo) can save cost, offer high speed of processing, reliability and security. The aim of this work was to conceptualize, design and develop a novel semantic web-based memo platform that allows for handling memos within an organization. The tools used include HTML, CSS, PHP, JavaScript, jQuery and AJAX, MySQL. The developed system was tested in three stages. Testing was done in the Department of Computer Science of the institution of case study, then in the Faculty of Science and finally in the entire Lagos State University. Agile development method was used in the development process. The designed system was hosted on a cloud-server and a total of 43 test cases were considered and an average of four minutes was recorded for a complete memo cycle. eMemo allows users to generate, sign, treat and memo electronically. It is such a useful tool that will enhance information processing in a faster, standardized and more secure manner.

The transport sector is heavily relying on the use of fossil fuels that are causing major environmental concerns. Solutions relying on the direct or indirect use of electricity, through e-fuels production, are emerging to power the transport sector. To ensure environmental benefits over this transition, an accurate estimation of the impact of the use of electricity is needed. This work presents a temporal analysis of carbon intensity of e-fuels using grid electricity in countries members of the European Network of Transmission System Operators (ENTSO-E). It also provides an estimation of the potential load factor for to produce low-carbon e-fuels according to the European Union legislative framework. This was achieved, building on top of the existing EcoDynElec tool, by developing EcoDynElec_xr a python tool enabling, with an hourly time resolution, the calculation, visualisation and the analysis of the historical time-series of electricity mix from the ENTSO-E. The results highlight that, in 2023, a minority of European countries were reaching low carbon intensity of electricity that enables the use of grid electricity for green electrolytic hydrogen production. The methodological hypothesis to consider the consumed electricity mix instead of the production mix, and the considered time step, are of paramount importance and drastically impact the potential load factor of green hydrogen production. The developed tool and calculated data are released under an open-source license to ensure transparency, results reproducibility, reuse on newer data, or for other purposes.

Industrial products e-commerce refers to the specific application of the e-commerce concept in the field of industrial products transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industry literature such as policies, reports and standards related to industrial products e-commerce contains abundant and crucial information. Through systematical analysis of the literature information, it is beneficial to explore and grasp the development characteristics and trends of the industrial products e-commerce. To study the characteristics and development status of industrial products e-commerce in China, literature comprising 18 policy documents, 10 industrial reports and 5 standards is deeply analyzed by employing text mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial products commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the results of word frequency statistics are visually displayed. Subsequently, the feature set is obtained by combining the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in word2vec, and the feature words are transformed into word vectors in the multi-dimensional space. The k-means algorithm is used to cluster the feature words into groups. Moreover, the latent dirichlet allocation (LDA) method is also utilized to further group and discover the features. The research results based on text mining provide supportive decisions for uncovering the development characteristics and trends of industrial products e-commerce in China.

E-petitioning is a useful object of study for observing the potential emergence of a new relationship to politics and new forms of political participation. Access to a dataset of hundreds of thousands of users of an electronic petitioning platform, provides the opportunity to overcome a certain number of limitations that are associated with traditional methods of studying political participation, since it allows us to focus on the reality of the signatories’ behaviour rather than on their declarations. We follow the traces left by the petitioners on this site to better understand the process of dissemination of an online petition, and its linked with offline activities. Our examination of the three most signed petitions in the ‘environment’ category, combining an analysis of their petitioning dynamics and an analysis of the comments attached to them, allows us to show: firstly, that there is an interwoven relationship between the local anchoring of the mobilisation and the processes of dissemination by which petitions extend from local signatories to signatories who are geographically more distant; and secondly, that it is not accurate to imagine that just anyone can sign any petition, since petitioning dynamics proceed from one person to the next, whether these dynamics start from a pre-existing local anchorage on the ground, or act through a platform effect which is dependent on the attractiveness of the petition in question.

Enteroaggregative Escherichia coli (EAEC) is an emerging pathogen frequently associated with acute diarrhea in children and travelers to endemic regions. EAEC was found the most prevalent bacterial diarrheal pathogen from hospitalized Bolivian children less than five years of age with acute diarrhea from 2007 to 2010. Here, we further characterized the epidemiology of EAEC infection, virulence genes, and antimicrobial susceptibility of EAEC isolated from 414 diarrheal and 74 non-diarrheal cases. EAEC isolates were collected and subjected to a PCR-based virulence gene screening of seven virulence genes and a phenotypic resistance test to nine different antimicrobials. Our results showed that atypical EAEC (a-EAEC, AggR-negative) was significantly associated with diarrhea (OR, 1.62, 95% CI, 1.25 to 2.09, P < 0.001) in contrast to typical EAEC (t-EAEC, AggR-positive). EAEC infection was most prevalent among children between 7 - 12 months of age. The number of cases exhibited a biannual cycle with a major peak during the transition from warm to cold season (April – June). Both typical and a-EAEC infections were graded as equally severe; however, t-EAEC harbored more virulence genes. aap, irp2, and pic were the most prevalent genes. Surprisingly, we detected 60% and 52.6% of multidrug resistance (MDR) EAEC among diarrheal and non-diarrheal cases. Resistance to ampicillin, sulfonamides, and tetracyclines was most common, being the corresponding antibiotics, the ones that are frequently used in Bolivia. Our work is the first study that provides comprehensive information on the high heterogenicity of virulence genes in t-EAEC and a- EAEC and the large prevalence of MDR EAEC in Bolivia.

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

For better export performance in cross border e-commerce, a contingency model integrates e-commerce into traditional export marketing strategy (EMS) with internal and external determinants of EMS. However, EMS of Micro, small, and medium-sized enterprises (MSMEs) is understudied. This study validates and modifies existing model for MSMEs. As a qualitative study, multiple sources of data including interviews, internal documents, and group discussions were used regarding business cases of entrepreneurs and supporting organizations in Mongolia and Korea. This research suggets contingency model for MSMEs with modified factors and different strategies in each factor. Specifically, intermal determinants are managerial capability, product competitiveness, and strategic marketing orientation. External determinants are export market competitivceness, export market infrastructure and entry barriers. EMS for MSMEs consists of the same factors with the original model but come up with different strategies. Theoretical and managerial implications were discussed.

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.

(1) Background: Spain launched an official campaign, #EsteVirusLoParamosUnidos, to try and unite the efforts of the entire country through citizen cooperation to combat coronavirus. The research goal is to analyze the Twitter campaign’s repercussion on general citizen feeling. (2) Methods: The research is based on a composite design that triangulates from a theoretical model, a quantitative analysis and a qualitative analysis. (3) Results: Of the 7357 tweets in the sample, 72.32% were found to be retweets. Four content families were extracted: politics, education, messages to society and defense of occupational groups. The feelings expressed ranged along a continuum, from unity, admiration and support at one end to discontent and criticism regarding the health situation at the other. (4) Conclusions: The development of networked sociopolitical and technical measures that enable citizen participation facilitates the development of new patterns of interaction between governments and digital citizens, increasing citizens’ possibilities of influencing the public agenda and therefore strengthening citizen engagement vis-à-vis such situations.

A E. Crassipes is considered a problem in different aquatic ecosystems, due to its abundance could become a solution to design and build economic and efficient treatment plants, and especially for the production of biofuels such as bioethanol. The objective of this research is to design and implement a sustainable development process between phytoremediation and bioethanol production with E. crassipes, evaluating the incidence of chromium adhered to the biomass of this plant in the production of bioethanol. Materials and methods: A system was installed to evaluate the phytoremediation with E crassipes with water loaded with chromium, determining the effectiveness of this plant to remove this heavy metal even if it is alive in a body of water. After this process, we proceeded to bring the biomass loaded with chromium to bioreactors to evaluate the production of bioethanol, assessing three types of biomass, one without chromium adhered and the other two with chromium adhered to its plant structure. There was an impact of the ethanol production of the E crassipes due to the presence of chromium, but this production can be taken into account for the assembly of an integral system of phytoremediation and bioethanol production, making the most of this biomass.

In the present work we study the properties of geodesic sub-$ (\alpha,b,s) $-preinvex functions on Hadamard manifolds and establish some basic properties in both general and differential cases. Further, we study sufficient conditions of optimality and proved some new inequalities under geodesic sub-($ \alpha,b,s $)-preinvexity.

The Internet of Things (IoT) was born from the fusion of virtual and physical space and became the initiator of many scientific fields. Economic sustainability is the key to further development and progress. Today, the need for electronic commerce has become an economic priority in the transition period between Industry 4.0 and Industry 5.0. Unlike mass production in Industry 4.0, customized production in Industry 5.0 should reach its true potential in vertically organized management and decision-making systems. The authors focused their research on e-commerce based on the three-level vertical IoT environment and the edge, fog, and cloud computing. The paper presents hands-on machine learning (ML) algorithms to facilitate the transition from a flat to a vertical e-commerce concept. The authors also propose practical ML algorithms for a few e-commerce types: consumer-consumer relationships and consumer-company-consumer relationships. These algorithms are mainly composed of convolution neural networks (CNN), natural language understanding (NLU) and sequential pattern mining (SPM), reinforcement learning (RL for agent training), algorithms for clicking on the item prediction, consumer behavior learning, etc. All presented concepts, algorithms, and models are described in detail.

This review is devoted to present the history of CARDIOSIM© software simulator platform, which was developed in Italy to simulate the human cardiovascular and respiratory system. The first version of CARDIOSIM© was developed at the Institute of Biomedical Technologies of the National Research Council in Rome. The first platform version published in 1991 ran on PC with disk operating system (MS-DOS) and was developed using the Turbo Basic language. The last version runs on PC with Microsoft Windows 10 operating system; it is implemented in Visual Basic and C++ languages. The platform has a modular structure consisting of seven different general sections, which can be assembled to reproduce different pathophysiological conditions. The software simulator can reproduce the most important circulatory phenomena in terms of pressure and volume relationships. It represents the whole circulation using a lumped-parameter model and enables the simulation of different cardiovascular conditions according to Starling’s law of the heart and a modified time-varying elastance model. Different mechanical ventilatory and circulatory devices have been implemented in the platform including thoracic artificial lung, ECMO, IABP, pulsatile and continuous right and left ventricular assist devices, biventricular pacemaker and biventricular assist devices. CARDIOSIM© is used in clinical and educational environment.

This article is an effort to scrutinize the role of Information Technology development in the chronological transformation of Urban Planning domain using the exploratory research approach. In this research, it is argued that the theoretical and practical understanding of Urban Planning should absorb and integrate the bright outcome of the rise of Information and Technology to foster congruent future urban development. The article addresses the trends of transformation in the urban planning domain through the myopic lens of the expansion of information and communications technology era followed by investigating the key drivers shaping the interaction between modern-day urban planning and information technology considering both the dark and bright sides into account.

Feline infectious peritonitis (FIP) is a severe and invariably fatal disease affecting both domestic and wild felines with limited effective therapeutic options available. By considering the significant immunomodulatory effects of vitamin E observed in both animal and human models under physiological and pathological conditions, we have provided a full in-silico investigation of vitamin E and related compounds and their effect on the crystal structure of feline infectious peritonitis virus 3C-like protease (FIPV-3CLpro). This work revealed the β-tocotrienol and δ-tocotrienol analogues as inhibitor candidates for this protein, suggesting their potential as possible drug compounds against FIP or their supplementary use with current medicines against this disease.

E-commerce is the general concept of using new technologies to establish chain communication between producers, sellers, suppliers, generally providers of goods and services on the one hand and buyers, consumers or customers in general on the other hand, in order to make a decision. The best ways are to optimize goods and services, reduce costs and open new channels. This article tried to propose an e-commerce model for fresh agricultural products, which can not only maximize producer and consumer satisfaction, but also reduce waste, increase marketing efficiency, and provide environmental protection and sustainable development. The proposed model is based on a coherent and real-time monitoring system, designed by managers and clarification for producers and consumers. The components of this system are manufacturers, retailers, banks, sales and purchase brokers, logistics systems, supervisors and management of the e-commerce system. This system manages information flow, money flow and goods flow accurately and transparently. In this presented model, the duties of each member and how they work were explained, and its implementation requirements were also specified. This model paves the way for the future of sustainable food and preserving the environment with two functions, reducing waste and increasing consumer satisfaction through the supply of unprocessed and fresh products.

This study describes the development of an image-based insect trap diverging from the plug-in camera insect trap paradigm. In short, a) it does not require manual annotation of images to learn how to count targeted pests and, b) it self-disposes the captured insects, and therefore is suitable for long-term deployment. The device consists of an imaging sensor integrated with Raspberry Pi microcontroller units with embedded deep learning algorithms that count agricultural pests inside a pheromone-based funnel trap. The device also receives commands from the server which configures its operation while an embedded servomotor can automatically rotate the detached bottom of the bucket to dispose of hydrated insects as they begin to pile up. Therefore, it completely overcomes a major limitation of camera-based insect traps: the inevitable overlap and occlusion caused by the decay and layering of insects during long-term operation, thus extending the autonomous operational capability. We study cases that are underrepresented in literature such as counting in situations of congestion and significant debris using crowd counting algorithms encountered in human surveillance. Finally, we perform comparative analysis of the results from different deep-learning approaches (YOLO7/8, crowd counting, deep learning regression) and we open-source the code and a large database of Lepidopteran plant pests.

Vitamin E facilitates testicular development and semen quality in farm animal. And most research tends to investigate antioxidant roles of Vitamin E in reproductive health; some research also find potential non-antioxidant roles of Vitamin E. To further uncover the mechanism by which Vitamin E modulates reproductive health, the paper reviews specific function of Vitamin E and candidate genes involved in male reproductive performance promoted by Vitamin E. The review found that cell proliferation (PDPN, BMP, Myc, AMPKa, GSK3β, PPARγ, CDK4, CDK6, Ki67, PCNA, Cyclin A2, Cyclin B1, Cyclin B3, BLM, REL, KLHL25)-, cell apoptosis (BCL-2, Caspase 9, Bax)-, spermatogenesis (CatSper1, CatSper2, NDRG1, CYP26B1, FSCN3, FLNA, SPCS3, YBX3, RARS)-, hormone receptor (PGR, FSHR, AR)-related genes are the underlying key points. And two miRNAs, miR-107 and miR-493-3p, which mediate cell cycle process, are also identified in response to Vitamin E treatment. The paper paves the way for a comprehensive understanding about effect of Vitamin E on testis development and semen quality in domestic animals.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

Internet-led labour market has become so competitive forcing many organisations from different sectors to embrace e-recruitment. However, realising the value of the e-recruitment from a Requirements Engineering (RE) analysis perspective is challenging. This research is motivated by the results of a failed e-recruitment project conducted in military domain which is used as a case study in this research. After reviewing the various challenges faced in that project through a number of related research domains, this research focuses on two major problems which are the (1) difficulty of scoping, representing, and systematically transforming recruitment problem knowledge towards e-recruitment solution specification; and (2) the difficulty of documenting e-recruitment best practices for reuse purposes in an enterprise recruitment environment. In this paper, a Problem-Oriented Conceptual Model (POCM) with a complementary Ontology for Recruitment Problem Definition (Onto-RPD) is proposed to contextualise the various recruitment problem viewpoints from an enterprise perspective and to elaborate those problem viewpoints towards a comprehensive recruitment problem definition. The POCM and Onto-RPD are developed incrementally using action-research conducted on three real case studies: (1) Secureland Army Enlistment, (2) British Army Regular Enlistment, and (3) UK Undergraduate Universities and Colleges Admissions Service (UCAS). They are later evaluated in a focus group study against a set of criteria. The study showed that the POCM and Onto-RPD provide a strong foundation for representing and understanding the e-recruitment problems from different perspectives.

Despite the uptake of tobacco smoking declining in the UK, smoking is still the leading cause of preventable poor health and premature death. While improved approaches to smoking cessation are necessary, encouraging and assisting smokers to switch by using substantially less toxic non-tobacco nicotine products may be a possible option. To date few studies have investigated the rates of smoking cessation and smoking reduction associated with the free provision of electronic-cigarettes (e-cigarette) to smokers. In this study the Blu Pro e-cigarette was given to smokers for use in place of tobacco for 90 days. The rates of smoking abstinence and daily smoking patterns were assessed at baseline 30 days, 60 days and 90 days. The response rate was 87%. After 90 days, the complete abstinence rate was 36.5% from 0% at baseline. Frequency of daily smoking reduced from 88.7% to 17.5% (P<0.001) and median consumption of cigarettes/day from 15 to 5 (P<0.001). Median days per month participants smoked also dropped from 30 to 13 after 90-days (P<0.001). On the basis of these results there may be value in smoking cessation services and other services ensuring that smokers are provided with e-cigarettes at zero or minimal costs for at least a short period of time.

The contents of Education for Sustainable Development (ESD) should be included in teachers’ initial and advanced training programs. In order to determine the key competences for sustainability, creating a Sustainable Consciousness is one of the main foundations. However, there are not many empirical studies that deal with consciousness from education. In this context, e-portfolio appears as a tool that promotes reflection and critical thinking, key competences for consciousness development. This work intends to propose a categorization system to extract types of consciousness and identify trainee teachers’ levels of consciousness. For this research work, of an eminently qualitative nature, we have selected twenty-five portfolios of students in the last year of the School of Education at the University of Macerata (Italy). The qualitative methodological procedure followed allowed to deduce three bases that shape trainee teachers’ consciousness: thinking, representation of reality and type of consciousness. We concluded that the attainment of a Sustainable Consciousness in teachers requires activating and developing higher levels of thinking, as well as a projective and macrostructural representation of reality.

Clinical training in medical schools in Spain is performed by rotations in university hospitals. During these internships, students are expected to acquire and master basic procedural skills. However, the assessment tools available rarely check whether these skills are completely acquired by the students. We have used an e-portfolio to determine the optimal number of times the students need to repeat a procedure to be able to perform it independently. The results were compared with the actual performance during the internships. An e-portfolio collected qualitative information about the internships. Quantitative information was also requested about the number of times each clinical skill was performed. Later, a survey asked these students and their teachers the optimal number of times each skill should be repeated before it could be considered fully acquired. The questionnaire was answered by 98.6% of the students and 70.3% of their teachers. Out of the 21 clinical skills and procedures selected, both students and their tutors agreed in a similar optimal value in 16 of them; only in five of them, teachers thought that students needed a greater number of times than that selected by the students. When these optimal values were compared with the actual values recorded in the portfolio during the internships, it was found that about half of the clinical skills were carried out less frequently than expected, thus providing an important feedback about the internships. Quantitative information collected in portfolios reveals a moderate mismatch between students and tutors perceptions of their training needs.

For any odd positive integer $x$, define $(x_n)_{n\geqslant 0} $ and $(a_n )_{n\geqslant 1} $ by setting $x_{0}=x, \,\, x_n =\cfrac{3x_{n-1} +1}{2^{a_n }}$ such that all $x_n $ are odd. The 3x+1 problem asserts that there is an $x_n =1$ for all $x$. Usually, $(x_n )_{n\geqslant 0} $ is called the trajectory of $x$. In this paper, we concentrate on $(a_n )_{n\geqslant 1} $ and call it the E-sequence of $x$. The idea is that, we consider any infinite sequence $(a_n )_{n\geqslant 1} $ of positive integers and call it an E-sequence. We then define $(a_n )_{n\geqslant 1} $ to be $\Omega-$convergent to $x$ if it is the E-sequence of $x$ and to be $\Omega-$divergent if it is not the E-sequence of any odd positive integer. We prove a remarkable fact that the $\Omega-$divergence of all non-periodic E-sequences implies the periodicity of $(x_n )_{n\geqslant 0} $ for all $x_0$. The principal results of this paper are to prove the $\Omega-$divergence of several classes of non-periodic E-sequences. Especially, we prove that all non-periodic E-sequences $(a_n )_{n\geqslant 1} $ with $\mathop {\overline {\lim } }\limits_{n\to \infty } \cfrac{b_n }{n}>\log _23$ are $\Omega-$divergent by using the Wendel's inequality and the Matthews and Watts's formula $x_n =\cfrac{3^n x_0 }{2^{b_n }}\prod\limits_{k=0}^{n-1} {(1+\cfrac{1}{3x_k })} $, where $b_n =\sum\limits_{k=1}^n {a_k } $. These results present a possible way to prove the periodicity of trajectories of all positive integers in the 3x + 1 problem and we call it the E-sequence approach.

The majority of E-commerce transactions reveal private information such as customers' identities, order contents, and payment information during the transaction. Other personal information such as health conditions, religion, and even ethnicity may be also deduced. Even when deploying electronic cryptocurrencies such as Bitcoin, anonymity cannot be fully guaranteed. Also, many anonymous payment schemes suffer from possible double spending circumstances. E-commerce privacy is basically a difficult problem as it involves parties with concurring interests. Three major e-commerce requirements are highly difficult to resolve: anonymous purchase, anonymous delivery, and anonymous payment. This work presents a possible e-commerce system addressing all three anonymity requirements for electronic-items business on open networks. The system offers anonymous entities authentication mechanisms up to completing a fair anonymous e-commerce transaction. The system is based on deploying a physically clone-resistant hardware token for each relevant involved party. The tokens are made clone-resistant by accommodating a Secret Unknown Cipher (SUC) in each hardware-token as a digital PUF-like identity. A set of novel generic system-setups for units, protocols and e-commerce schemes is introduced. The proposed anonymization is basically attained by virtually-replacing relevant e-commerce entities by low-cost, unique and clone-resistant tokens/units using SUCs. The units act as trustable anonymous, authenticated and non-replaceable entities monitored by their acting users.

Escherichia coli is a gram-negative commensal bacterium living in human and animal intestines. Its pathogenic strains are cause of high morbidity which can adversely affect people by causing urinary tract infections, food poisoning, septic shock, or meningitis. Humans can contract E. coli by eating contaminated food—such as raw or undercooked raw milk, meat products, and fresh produce sold in open markets—as well as by coming into contact with contaminated settings like wastewater, municipal water, soil, and faeces. Some pathogenic strains of E. coli have been identified in Nigeria such as enterohemorrhagic (EHEC), as well as enterotoxigenic (ETEC), enteropathogenic (EPEC), enteroinvasive (EIEC), enteroaggregative (EAEC), and verotoxigenic (VTEC). This causes acute watery or bloody diarrhoea, stomach cramps, and vomiting. Apart from the virulence profile of E. coli, antibiotic resistance mechanisms such as the presence of blaCTX-M found in humans, animals and environmental isolates which are of great importance and require surveillance and monitoring for emerging threats in resource-limited countries. This review is aimed at understanding the underlying mechanisms of evolution and antibiotic resistance in E. coli in Nigeria and highlighting the use of improving One Health approaches to combat the problem of emerging infectious diseases.

Soluble inorganic pyrophosphatase (sPPase), a pyrophosphate hydrolase, has been shown to play an important role in several physiological processes such as plant growth and development, metabolic activities, and response to abiotic stresses, but sPPase has been less studied in woody plants. In order to preliminarily verify whether the soluble inorganic pyrophosphatase in Eucommia ulmoides Oliver (E. ulmoides) has a role in resistance to drought stress, we amplified the EuSIP5 (E. ulmoides soluble inorganic pyrophosphatase 5) cDNA sequence from E. ulmoides by RT-PCR. In order to study the drought resistance of the Eucommia ulmoides soluble inorganic pyrophosphatase 5 (EuSIP5) gene, the cDNA sequence of the EuSIP5 gene was amplified from Eucommia ulmoides Oliver by RT-PCR. Bioinformatic analysis indicated that EuSIP5 might be an unstable amphipathic protein, mainly located in the cytoplasm. E. ulmoides, the highest expression of the EuSIP5 gene was found in male leaves and pericarp from April to October, and in leaves of E. ulmoides in July and September. During drought, the expression of EuSIP5 in seedling E. ulmoides leaves was significantly higher than that of the control. An overexpression vector harboring the EuSIP5 was constructed and introduced into the tobacco (Nicotiana tabacum cv. Xanthi). We found that during drought stress, the appearance of wilting was delayed by 4 days in transgenic tobacco plants (OE) compared with wild type plants (WT), and the expression of drought-related genes DET2, CYP85A1, P5CS, ERF1 and F-box was found to be increased in transgenic tobacco leaves, as well as the enzyme activities of the protective enzymes: peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT) were significantly higher than those of the WT, and the malondialdehyde (MDA) content was lower than the WT. These results indicated that the introduction of EuSIP5 gene into tobacco increased the expression of drought-related genes, enhanced the anti-membrane oxidation ability of tobacco, and reduced the oxidative stress damage, thus improving the drought resistance of tobacco.

This paper examines the impact of stringent regulations on personal data protection on customer perception of data security and online shopping behavior. In the context of the rapidly expanding e-commerce landscape, ensuring the security of personal data is a complex and crucial task. The study of several legal frameworks, including Malaysia's compliance with EU regulations and Indonesia's Personal Data Protection Law, provides valuable insights into consumer data protection. The challenges of balancing data safeguarding and unrestricted movement and tackling misuse by external entities are significant and require careful consideration. This research elucidates the pivotal role of trust in e-commerce environments and the deployment of innovative e-commerce models designed to minimize personal data sharing. By integrating advanced privacy-enhancing technologies and adhering to stringent regulatory standards such as the GDPR, this study demonstrates effective strategies for robust data protection. The paper contributes to the academic discourse by providing a comprehensive framework that synergizes legal, technological, and procedural elements to fortify data security and enhance consumer trust in digital marketplaces. This approach aligns with international data protection standards and offers a pragmatic blueprint for achieving sustainable data security in e-commerce.

This study aims to explore the E-marketing orientations and relationship management constructs in Jordanian startup enterprises to examine their influence on brand visibility and loyalty in the context of the digital market . The sample consists of 161 managers in startup companies, and structural equation modeling is used to study the relationships between the constructs of e-marketing orientation, capabilities, E-relationship management, brand visibility, and loyalty. The results illustrate that the realization of e-marketing orientation is directly achieved by capabilities and visibility, thereby stressing the importance of a formulated digital market approach and that the realization of effective e-relationship management directly expression by e-marketing capabilities, demonstrating the significance of the digital market concept’s approach. The results further demonstrate that e-marketing capabilities and visibility serve as mediators between the realization of e-marketing orientations and loyalty, Two explanations may be drawn, one from the R resource-Based View theory, and another derived from R elationship M arketing T heory Thus, the study has theoretical implications in terms of R esource-Based V iew and R elationship M arketing T heory. The study offers essential managerial insights for practitioners into the entrepreneurship domain concerned with the necessity of e-marketing capabilities and E-RM attitudes at a customer-centered approach and the strategic application of digital channels to enhance visibility in the intense competition context. Therefore, the empirical results have contributions as essential insights for both stakeholders and account for practical, theoretical, and managerial perspectives in the entrepreneurship domain.

(1) E-governance is defined as the application of electronic means in the interaction between government and citizens and government and business, as well as in internal government operations to simplify and improve democratic, governmental, and business aspects of governance. Thus, e-governance is built from a paradigmatic dimension such as e-democracy (relationship between government and citizens) and an operational one such as e-government. The objective was to design and validate an instrument to measure e-governance based on three factors: a) e-administration, b) e-services, and c) e-democracy; (2) Methods: Based on the level of importance given to each factor (sample of 2042 Latin American citizens), as well as the relationships between them, an analysis of the importance of each factor is carried out; (3) Results: After the confirmatory analysis, the definitive instrument with which e-governance can be measured by other researchers and future research is obtained, considering the three selection factors, namely: e-administration, e-services and e-democracy; (4) Conclusions: This research contributes to political science through the design and validation of an instrument consisting of 39 items that can be used to measure e-governance according to the dimensions proposed by the United Nations Educational, Scientific and Cultural Organization.

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.

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.

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.

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.

Serotonergic neurons constitute one of the main systems of neuromodulators, whose diffuse projections regulate the functions of the cerebral cortex. Serotonin (5-HT) is known to play a crucial role in the differential modulation of cortical activity related to behavioral contexts. Certain aspects of the 5-HT signaling framework hint at its potential role as a modulator of activity-dependent synaptic changes within the critical period of the primary visual cortex (V1). Cells of the serotonergic system are among the first neurons to differentiate and operate. During postnatal development, ramifications from raphe nuclei become massively distributed in the visual cortical area, remarkably increasing the availability of 5-HT for the regulation of excitatory and inhibitory synaptic activity. A substantial amount of evidence has demonstrated that synaptic plasticity at pyramidal neurons of the superficial layers of V1 critically depends on a fine regulation of the balance between excitation and inhibition (E/I). Therefore, 5-HT could play an important role in controlling this balance, providing the appropriate excitability conditions that favor synaptic modifications. In order to explore this possibility, the present work used in vitro intracellular electrophysiological recording techniques to study the effects of 5-HT on the E/I balance of V1 layer 2/3 neurons, during the critical period. Serotonergic modulation of the E/I balance has been analyzed on spontaneous activity, evoked synaptic responses, and long-term depression (LTD). Our results pointed out that the predominant action of 5-HT implies a reduction of the E/I balance. 5-HT promoted LTD at excitatory synapses while blocking LTD at inhibitory synaptic sites, thus shifting the Hebbian alterations of synaptic strength towards lower levels of E/I balance.

Vitamin E is a group of eight compounds divided into two subgroups: four tocopherols (α-, β-, γ-, and δ-) and four tocotrienols (α-, β-, γ-, and δ-). α-Tocopherol is considered the most biologically active form. This review paper summarizes the current knowledge and historical progression of vitamin E research, with particular emphasis on its role in animal nutrition. Early studies in the 1920s identified vitamin E’s role in preventing neonatal mortality in rats. Over the following decades, scientists discovered the compound’s chemical structure and its importance for the immune system, skin health, anti-inflammatory properties, hormonal balance, and other bodily functions. Production of vitamin E products has evolved, starting with isolating the vitamin from natural sources and advancing to synthesizing it with greater efficiency and standardized potency units. Early animal studies focused on reproductive health and growth disorders, but further research demonstrated the importance of vitamin E in preventing encephalomalacia in domestic fowl and muscular dystrophy in rabbits and other animals. Today, vitamin E is commonly used as a feed additive to meet animals’ requirements and assure immune function and overall health. Despite much knowledge on vitamin E’s role in animal nutrition, many questions remain unanswered, and current research aims to determine optimal supplementation levels, interactions with other nutrients, impacts on gene expression, cell signaling and communication, and effects of supranutritional dosages in livestock. Vitamin E has a long and fascinating history in scientific research, with significant advancements in understanding its chemical structure and biological activity. In animal nutrition, vitamin E continues to play an important role in improving animal health, and ongoing research will continue to expand our understanding of its benefits and mechanisms of action.