Search Results (8,281)

Malaria and Typhoid fever are prevalent diseases in tropical regions, and both are exacerbated by unclear protocols, drug resistance, and environmental factors. Prompt and accurate diagnosis is crucial to improve accessibility and reduce mortality rates. Traditional diagnosis methods cannot effectively capture the complexities of these diseases due to the presence of similar symptoms. Although machine learning (ML) models offer accurate predictions, they operate as “black boxes” with non-interpretable decision-making processes, making it challenging for healthcare providers to comprehend how the conclusions are reached. This study employs explainable AI (XAI) models such as Local Interpretable Model-agnostic Explanations (LIME), and Large Language Models (LLMs) like GPT to clarify diagnostic results for healthcare workers, building trust and transparency in medical diagnostics by describing which symptoms had the greatest impact on the model’s decisions and providing clear, understandable explanations. The models were implemented on Google Colab and Visual Studio Code because of their rich libraries and extensions. Results showed that the Random Forest model outperformed the other tested models; in addition, important features were identified with the LIME plots while ChatGPT 3.5 had a comparative advantage over other LLMs. The study integrates RF, LIME, and GPT in building a mobile app to enhance the interpretability and transparency in malaria and typhoid diagnosis system. Despite its promising results, the system’s performance is constrained by the quality of the dataset. Additionally, while LIME and GPT improve transparency, they may introduce complexities in real-time deployment due to computational demands and the need for internet service to maintain relevance and accuracy. The findings suggest that AI-driven diagnostic systems can significantly enhance healthcare delivery in environments with limited resources, and future works can explore the applicability of this framework to other medical conditions and datasets. Full article

The current study proceeded to reduce the environmental hazards spreading worldwide due to synthetic dyes. To overcome these problems, eco-friendly natural dyes are introduced as alternative sources of synthetic dyes. The present study was focused on exploring the bio-colorant of the aqueous and acidic extract of the bark of Melia azedarach L. for the dyeing of both silk and cotton samples. The results of the extraction medium specified that the aqueous extract gave maximum colorant solubility and upon fabric dyeing produced higher color strength in contrast to the acidic medium. The optimization experimentation data showed that excellent color strength of silk fabric was found at 45 min dyeing time duration, in 35:1 mL dye extract, and using 2% salt (NaCl) as an exhausting agent, whereas cotton fabric showed the maximum K/S value at 60 min dyeing time, in a 45:1 mL liquor ratio, and with the use of 2% salt. Bio-mordants produce different shades on both fabrics. Bio-mordanting experiments on silk revealed that pre-mordanting with 2% turmeric and 3% pomegranate, and post-mordanting using 3% turmeric and 2% pomegranate produced a darker shade. In the case of cotton, the pre-mordanted samples with 2% turmeric and 3% pomegranate and the post-mordanted samples with 4% turmeric and 4% pomegranate gave the highest color strengths. All the mordanted samples gave excellent fastness ratings. Overall, it has been found that Bakain bark proved to be an excellent source of tannin. The result of this study showed that it could be a cost-effective and eco-friendly dye source for textile progress. Full article

The rapid advancement of digital technology has necessitated a reevaluation of traditional educational methodologies, particularly in literature and visual arts. This study investigates the application of metaverse technology to integrate contemporary poetry and visual arts, aiming to enhance university-level education. The purpose is to develop a convergent teaching method that leverages the immersive and interactive capabilities of the metaverse. The research involves a joint exhibition project with students from Sangmyung University and international participants, incorporating a metaverse-based educational program. A sample of 85 students participated in the program, and their experiences were evaluated through surveys and focus group interviews (FGIs). The findings reveal significant correlations between content satisfaction and method satisfaction, underscoring the importance of engaging and interactive methods. The study also identifies technical challenges and provides insights for optimizing digital platforms for educational purposes. The implications suggest that integrating metaverse technology in arts education can significantly enhance creativity, critical thinking, and interdisciplinary skills, offering a sustainable and innovative approach to modern education. Based on these implications, this paper proposes methods for incorporating the insights gained from case analyses and implications into the design of educational programs. It is anticipated that this approach will contribute to enhancing the quality of convergence education in higher education institutions. Furthermore, it is expected that this program will serve as a starting point for the systematic implementation of integrated education and the use of digital platforms, thereby helping to reduce disparities in integrated education between countries. Full article

The regional disparity in higher education development is critical for the sustainable advancement of the national education system. To address this issue, the Chinese government has implemented targeted support policies for higher education in underdeveloped regions, with the “Ministry-Province Co-construction Policy” serving as a notable example. This study investigates the impact of such policies on the development of universities in China’s underdeveloped central and western regions. First, the study analyzes policy documents to identify six primary policy pathways through high-frequency word extraction, social semantic analysis, and path integration. These policy pathways are quantified using representative indicators, which constitute the independent variables of the study. Second, by employing the framework of modern university functions, the study develops a sustainable development indicator system for higher education institutions. The performance scores for the sustainable development of 14 universities, derived using the entropy method, serve as the dependent variables. The study subsequently measures the effects of individual and combined policy pathways through two equations. The results indicate that some pathways are more effective than others. While all combined policy pathways yield positive effects, an excessive number of combinations can lead to diminishing returns. Finally, the study elucidates the measurement results, emphasizing that effective pathways highlight the essential roles of faculty, research, and teaching. Conversely, less effective pathways stem from inadequate inputs or slow responses. Although combined policy pathways generally exert positive impacts, an overabundance of combinations can dilute these benefits. The study suggests that administrative support for higher education in underdeveloped regions is advantageous. It underscores the necessity of distinguishing between more and less effective input methods, concentrating on resource allocation, and ensuring universities’ autonomy in utilizing support resources to achieve sustainable development in higher education within these regions. Full article

As Sustainable Development Goals (SDGs) gain traction in Chinese society, fostering sustainable entrepreneurship among university students has emerged as a key priority for universities and governments. Methods for increasing students’ sustainable entrepreneurship skills and knowledge for the creation of sustainable startups have attracted substantial attention. This study constructs a moderated mediation model based on entrepreneurial cognition theory to investigate the mediating roles of opportunity identification and attitude in the relationship between sustainable entrepreneurship education and sustainable entrepreneurial intention among university students, in addition to the moderating effect of empathy. The study surveyed 307 students from universities in the Yangtze River Delta region and employed hierarchical regression analysis to test the hypotheses. The results indicate that sustainable entrepreneurship education enhances students’ sustainable entrepreneurial intention by fostering their opportunity identification and attitude, and this enhancement effect is stronger when their level of empathy is higher. These findings enrich entrepreneurial cognition and empathy theories within the context of sustainable entrepreneurship and offer valuable insights for universities and policymakers in developing strategies to support sustainable entrepreneurship among university students. Full article

Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects the optimal solution based on the distance of each alternative from the average solution, making it suitable for multi-attribute decision-making with conflicting attributes. This study proposes a new scoring function for ILNs and develops an evaluation method combining ILNs with EDAS (IL-EDAS). Experts’ evaluations of each alternative’s indices are expressed using ILNs, and the EDAS method ranks the alternatives to select the optimal solution. We apply this method to assess innovation and entrepreneurship education capabilities in universities, and compare the results with those from other methods to verify their applicability and practicality. Full article

This study introduces a novel recommender system that integrates academic performance and socio-demographic variables to provide personalised and contextually relevant recommendations for university degree selection. The system aims to optimise the alignment between students’ profiles and potential academic programmes by utilising advanced machine learning models, including XGBoost, Random Forest, GLMNET, and KNN. The research addresses a critical gap identified in the literature, where most existing systems rely solely on academic data, neglecting the significant impact of socioeconomic factors on educational decision-making. The proposed system demonstrates superior predictive accuracy through rigorous cross-validation and hyperparameter tuning compared to simpler models, such as linear regression. The results show that integrating socio-demographic data enhances the relevance of the recommendations, supporting students in making more informed choices. This approach contributes to educational equity by ensuring that guidance is tailored to each student’s unique circumstances, aligning with the sustainable development goal of quality education. The findings highlight the value of incorporating a comprehensive data-driven approach to improve educational outcomes and support more equitable decision-making processes. Full article

Notably, 56 worldwide experts gathered for the Antimicrobial Assessment on Global Aquaculture Production (AGAP) series of workshops to (1) evaluate the current state of knowledge on antimicrobial use and identify existing gaps; (2) formulate strategies to identify ecologically relevant impact indicators and establish thresholds for assessment; (3) identify pivotal socioeconomic factors and effective governance mechanisms essential for implementing monitoring practices in aquaculture and extending them across sectors and countries for aquaculture sustainability; (4) develop pathways to enhance our comprehension between antibiotic use in aquaculture and antimicrobial resistance; and (5) explore potential antibiotic monitoring tools that can be universally adapted and implemented across region and sectors. The main outcomes were a roadmap for establishing investigation priorities on the relevant topics regarding antibiotic use in aquaculture, socioeconomic drivers for using antibiotics and behaviors that need more robust and transparent regulatory frameworks to guide farmers, training on antimicrobial use, and access to veterinarians and extension services agents for education. Overall, the workshop evidenced the power of collaboration in addressing complex global challenges to achieve sustainable aquaculture. Despite diligent efforts, some constraints may have inadvertently narrowed the possibility of having more experts and left some pertinent topics unaddressed, but they are needed in the discussion. Full article

Statistics modules are included in most university degrees, independent of the degree area, and this means that many students face these modules underprepared and struggle because of a lack of statistics knowledge. The Maths Support Centre (MSC) in the University College Dublin (UCD) provides support for various mathematics-related subjects, with statistics students being the second-largest cohort of visitors. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. The main data set for this study is the data from UCD students who have accessed the UCD MSC since 2015/16 for statistics support; the categorization of statistical concepts has been made with the statistics module description for each statistics subject at the Universidad Rey Juan Carlos (URJC). First, we conducted a categorization of statistical concepts taught in university (based on URJC’s catergorization); after that, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. The statistical issues presented were categorized as descriptive statistics (22.8%), probability (44%), statistical inference (29.2%), and statistical software (4%). Students struggled with material that was introduced at university level rather than material seen at secondary level. Our findings on students’ main statistical issues contribute to the development of a suite of evidence-based educational applications and games to support undergraduate students internationally in first- and second-year statistical modules. Full article

Dating violence (DV) is a form of intentional abuse carried out in young couples, which over the years has increasingly gained attention for its pervasiveness and high frequency. The present study represents an effort to expand and deepen the literature on factors associated with DV perpetration. The sample consisted of 225 Italian young people who completed an online survey. A model was tested, in which DV perpetration is affected by the presence of gender stereotypes and personal values oriented to power and dominance (i.e., self-enhancement) and to universalism and interest in others (i.e., self-transcendence) through the mediation of the perception of the romantic relationship quality, controlling for age. Sex was also considered in the model. The findings showed that self-enhancement and self-transcendence were, respectively, linked positively and negatively to a negative perception of the relationship quality, which in turn explained DV perpetration. The results also suggested that hostile sexism, self-enhancement and being male were directly linked to DV perpetration, thus representing potential risk factors for it. The study suggests the importance of working on gender role beliefs and personal orientation to power, which guide the way people perceive their romantic relationships and behave toward their partners, providing interesting insights for the implementation of DV prevention programs. Moreover, the findings highlight the importance of working with families and other educational agencies to foster a change in cultural terms. Full article

Background and Objectives: Chronic venous insufficiency negatively affects the quality of life and reduces the job performance of nurses, who are important components of the healthcare system. The aim of this study was to assess the risk factors of venous insufficiency according to demographic characteristics among nurses working at a foundation university hospital. Materials and Methods: This study used an analytical cross-sectional approach. The sample consisted of 100 nurses working at a foundation university hospital in a metropolitan city of Turkey. Data were collected using a demographic characteristics form, VEINESQOL/Sym, and a CEAP classification form. The condition of varicose veins among the nurses was diagnosed by a cardiovascular surgeon using Doppler ultrasonography. Results: The prevalence of chronic venous insufficiency (CVI) among nurses was 65%, with 48% at a C1 level according to the CEAP classification. CVI was higher among those with chronic diseases (p = 0.027) and those who had pregnancy (p = 0.021). In addition, the risk of CVI (+) was 7.68 times higher among those aged older than 26.5 years and 36.14 times higher for women (p < 0.001). A 0.9-fold increase in the risk of CVI (+) among nurses produced a one-unit decrease in venous-insufficiency-related quality of life (p = 0.006, OR = 0.94, 95% CI:(0.896–0.982)). Conclusions: The prevalence of CVI among nurses was found to be high, especially among women, those with chronic diseases, and pregnant individuals. In this context, it is recommended to implement risk screening and prevention education programs for CVI among nurses. Full article

Background: Antibiotic resistance presents a global challenge. Community awareness of antibiotic use has not been studied extensively in Saudi Arabia. This study aimed to assess public awareness of the appropriate use and indications of antibiotics in Riyadh, Saudi Arabia. Furthermore, the responses were compared across gender and age groups. Methods: We conducted a cross-sectional study between September 2022 and October 2022, including adult participants from Riyadh. The questionnaires were distributed via electronic channels and included sections about participants’ sociodemographic data and behavior concerning antibiotic use. Results: This study included 453 respondents. There were 281 (62%) female and 172 (38%) male respondents. Most respondents were between 46 and 55 years (n = 111; 24.5%) and above 56 years (n = 134; 29.6%). Two hundred seventy-two (60%) were college/university graduates, and 113 (24.9%) were at the secondary school level. Most participants (n = 410; 90.5%) were not affiliated with or working in the health sector. One hundred thirty-nine (30.7%) participants used an antibiotic within the past six months, and 171 (37.7%) kept antibiotics at room temperature. Most participants (n = 380; 83.9%) completed the treatment plan as prescribed. Sixty-eight percent of respondents stopped taking antibiotics when they felt better, and 11.5% believed antibiotics can treat bacterial and viral infections. The responses were compared between patients of both genders and patients aged ≤55 years or older. The comparison indicated that females tended to store antibiotics as instructed by the manufacturer (p = 0.004) and disposed of the remaining antibiotics immediately after completing the treatment (p < 0.001). Furthermore, the indications for antibiotic use differed between the genders, with no difference between the age groups. Participants > 55 years tended to complete the treatment plan (p = 0.007) and continued taking antibiotics at the same time and dose as prescribed (p = 0.002). Conclusions: This study’s findings suggest that public health authorities should implement awareness intervention programs to educate the Riyadh community on the proper use of antibiotics, with target interventions for specific gender and age groups. This study’s findings should be interpreted in the context of the Riyadh community and the potential biases of cross-sectional studies. Full article

In recent years, Higher Education institutions have reviewed learning and teaching methodologies to align competencies with evolving socioeconomic scenarios. Challenge-Based Learning (CBL) has emerged as a key method for developing competencies and self-regulating capacities in university students. This study aimed to identify the teaching practices associated with CBL in Higher Education. Adhering to PRISMA 2020 guidelines, this systematic review analyzed open-access and peer-reviewed publications from 2013 to 2023. The selection process reviewed 64 articles from Web of Science (WoS) and Scopus. To assess the risk of bias, the Delphi method with expert panels from the University College of Northern Denmark (UCN) was used. The review identified 20 studies emphasizing a shift in teaching practices in CBL toward student-centered learning, categorized into four key dimensions: pedagogical approaches, technological integration, industry engagement, and support for development. These findings illustrate the transition from traditional teaching to facilitative roles that foster innovative problem-solving. Limitations included the scarcity of research on specific CBL teaching practices and detailed implementation strategies, highlighting the need for further research. This study underscores the importance of specialized educator training in addressing CBL adoption challenges and preparing students for complex future challenges, enhancing student learning and growth across disciplines. Full article

The purpose of this study is to examine the role of structural transformation in the energy sector to accelerate the decarbonization process in the world’s top five green leaders, Germany, Canada, Sweden, Denmark, and Poland. To test this empirically, we collected annual data from a panel of the top five green leaders from 2000–2023. A key contribution of our study lies in assessing multiple critical metrics, including CO₂ emissions, carbon intensity, carbon intensity of electricity, production-based carbon emissions, and consumption-based carbon emissions, to capture holistic progress towards carbon neutrality. We applied the augmented mean group (AMG) model to estimate the long-term results. The Dumitrescu–Hurlin test is used to test the causal relationship among the modeled variables. The findings of the AMG model reveal that renewable energy production and consumption significantly reduce CO₂ emissions, production-based CO₂ emissions, consumption-based CO₂ emissions, carbon intensity, and the carbon intensity of electricity. Conversely, fossil-fuel-derived energy exacerbates these metrics. However, the impact of these energy sources varies by country in terms of their magnitude. The outcomes of the Dumitrescu–Hurlin test indicate that a bidirectional causality exists between renewable energy production and CO₂ emissions and between renewable energy consumption and carbon intensity. However, a unidirectional causality exists between fossil fuel consumption and CO₂ emissions and between renewable energy consumption and the carbon intensity of electricity. Our results indicate the detrimental impacts of continued fossil fuel use and conclude that a structural transformation in the energy sector is critical to decarbonization. Based on our results, we suggest that policy efforts should prioritize structural reforms in the energy sector by emphasizing a shift towards renewable energy sources. Such reforms are essential for achieving net-zero carbon emissions and mitigating broader environmental degradation. Full article

Dental implant education is required to prepare students for independent general practice. This investigation aimed to assess students’ perceptions of their educational experience and training in a preclinical dental implant introduction course, using reflective logs anonymously extracted from course portfolios. Methods: This study employed qualitative research methodology to analyze second-year dental students’ reflections on their educational and development of psychomotor skills in a preclinical course focusing on dental implants at the University of Nevada, Las Vegas. These reflections served as the primary data source for qualitative analysis. The analysis was facilitated using NVivo software version 12 plus, which assisted in data coding and the organization of these codes into meaningful units, patterns, and themes. Results: Four themes emerged, which interrelated to each other and to the research question. Students reported positive course outcomes in dental implant learning, improvements in applying theoretical implant knowledge while developing practical skills, digitally scanning implant cases for the final restoration, and enhancement of their insight in evidence-based restoratively driven implant planning. They generally found the hands-on experience to have improved their understanding of the dental implant as an option for restoration. Although there were challenges, students viewed these as learning opportunities. For us, as educators, it provided invaluable feedback to understand students’ perceptions of difficulties in knowledge acquisition and psychomotor skill development in placing and restoring dental implants. Conclusions: Within the limitation of this study, students expressed a positive perception of their learning experience in the introductory course on dental implants. Full article