Search Results (61)

Artificial intelligence (AI) holds considerable promise to transform education, from personalizing learning to enhancing teaching efficiency, yet it simultaneously introduces significant concerns regarding ethical implications and responsible implementation. This exploratory survey investigated the perceptions of 376 teachers, university students, and future educators from the University of Salerno area concerning AI integration in education. Data were collected via a comprehensive digital questionnaire, divided into sections on personal data, AI’s perceived impact, its usefulness, and specific applications in education. Descriptive and inferential statistical analyses, including mean, mode, standard deviation, and 95% confidence intervals, were applied to the Likert scale responses. Results indicated a general openness to AI as a supportive tool for personalized learning and efficiency. However, significant reservations emerged regarding AI’s capacity to replace the human role. For instance, 69% of participants disagreed that AI tutors could match human feedback efficiency, and strong opposition was found against AI replacing textbooks (81% disagreement) or face-to-face lessons (87% disagreement). Conversely, there was an overwhelming consensus on the necessity of careful and conscious AI use (98% agreement). Participants also exhibited skepticism regarding AI’s utility for younger learners (e.g., 80% disagreement for ages 0–6), while largely agreeing on its benefit for adult learning. Strong support was observed for AI’s role in providing simulations and virtual labs (89% agreement) and developing interactive educational content (94% agreement). This study underscores a positive inclination towards AI as an enhancement tool, balanced by a strong insistence on preserving human interaction in education, highlighting the need for thoughtful integration and training. Full article

Background: The Museum for Anatomy and Pathology at the Radboud University (The Netherlands) has created a permanent teratological exhibition, which is enhanced with augmented reality (AR) modalities. This exhibition serves various (post)graduate educational purposes and is open to the general public. However, data on visitors’ views and experiences regarding the teratological collection and AR models are currently lacking. Methods: To address this, a qualitative study was conducted to explore visitors’ opinions and experiences. One-on-one in-depth interviews were conducted using a predefined topic list, with audio recordings transcribed verbatim. Thematic analysis was applied to the twenty-six interview transcripts. Results: The findings indicate that publicly displaying teratological specimens alongside AR modalities is valued and positively received by both (bio)medical students and laypeople alike. AR enhances understanding of dysmorphology and provides a more interactive and engaging learning experience for complex topics. Conclusion: The use of AR within a teratological exposition holds tremendous educational potential and improves public awareness and acceptance of developmental anomalies. Moreover, it provides a unique opportunity to reflect on both historical and contemporary bioethical issues. Full article

Background/Objectives: Surgical pathology of tubo-ovarian and peritoneal cancer carries a well-recognised diagnostic workload, partly due to the large amount of non-primary tumour-related tissue requiring assessment for the presence of metastatic disease. The lymph nodes and omentum are almost universally included in such resection cases and contribute considerably to this burden, principally due to volume rather than task complexity. To date, artificial intelligence (AI)-based studies have reported good success rates in identifying nodal spread in other malignancies, but the development of such time-saving assistive digital solutions has been neglected in ovarian cancer. This study aimed to detect the presence or absence of metastatic ovarian carcinoma in the lymph nodes and omentum. Methods: We used attention-based multiple-instance learning (ABMIL) with a vision-transformer foundation model to classify whole-slide images (WSIs) as either containing ovarian carcinoma metastases or not. Training and validation were conducted with a total of 855 WSIs of surgical resection specimens collected from 404 patients at Leeds Teaching Hospitals NHS Trust. Results: Ensembled classification from hold-out testing reached an AUROC of 0.998 (0.985–1.0) and a balanced accuracy of 100% (100.0–100.0%) in the lymph node set, and an AUROC of 0.963 (0.911–0.999) and a balanced accuracy of 98.0% (94.8–100.0%) in the omentum set. Conclusions: This model shows great potential in the identification of ovarian carcinoma nodal and omental metastases, and could provide clinical utility through its ability to pre-screen WSIs prior to histopathologist review. In turn, this could offer significant time-saving benefits and streamline clinical diagnostic workflows, helping to address the chronic staffing shortages in histopathology. Full article

Compassionate university practices can increase students’ sense of belonging and lead to higher wellbeing. This study presents qualitative data from a UK university collected as part of the Nurture-U Compassionate Campus project. Experiences of transition to university were gathered from 32 students across five focus groups. Data were analysed using narrative analysis, conducted jointly by an academic researcher and Nurture-U student advisors. Results are presented across three phases: (1) Expectations: participants hoped for liberal and inclusive university environments, but the university’s reputation as a white, middle-class university raised concerns for some. (2) Navigating a new social environment: on arrival, compassion was visible in welcoming individuals, but lacked where participants felt othered. (3) Finding your people: many found friends who had shared experiences, but this took time and could cause further isolation. Participants identified specific compassionate practices universities could implement in universities supporting transition. These included (i) implementing communication prior to arrival that actively promotes and highlights available support, (ii) creating structures where students and staff can interact and support each other in small groups, and (iii) holding accessible and free events for students to interact which are not reliant on societies. Full article

Background/Objectives: Smartphones, with their widespread popularity and diverse apps, have become essential in our daily lives, and ongoing advancements in information technology have unlocked their significant potential in healthcare. Our goal is to identify the future research directions of mobile health (mHealth) by examining its research trends and emerging hotspots. Methods: This study collected mHealth-related literature published between 2005 and 2024 from the Web of Science database. We conducted a descriptive statistic of the annual publication count and categorized the data by authors and institutions. In addition, we developed visualization maps to display the frequency of keyword co-occurrences. Furthermore, overlay visualizations were created to showcase the average publication year of specific keywords, helping to track the changing trends in mHealth research over time. Results: Between 2005 and 2024, a total of 6093 research papers related to mHealth were published. The data have revealed a rapid increase in the number of publications since 2011. However, it was found that research on mHealth has reached a saturation point since 2021. The University of California was the dominant force in mHealth research, with 248 articles. The University of California, the University of London, Harvard University, and Duke University are actively collaborating, which shows a geographical pattern of collaboration. From the analysis of keyword co-occurrence and timeline, the research focus has gradually shifted from solely mHealth technologies to exploring how new technologies, such as artificial intelligence (AI) in mobile apps, can actively intervene in patient conditions, including breast cancer, diabetes, and other chronic diseases. Privacy protection policies and transparency mechanisms have emerged as an active research focus in current mHealth development. Notably, cutting-edge technologies such as the Internet of Things (IoT), blockchain, and virtual reality (VR) are being increasingly integrated into mHealth systems. These technological convergences are likely to constitute key research priorities in the field, particularly in addressing security vulnerabilities while enhancing service scalability. Conclusions: Although the volume of core research in mobile health (mHealth) is gradually declining, its practical applications continue to expand across diverse domains, increasingly integrating with multiple emerging technologies. It is believed that mobile health still holds enormous potential. Full article

The integration of Artificial Intelligence (AI) in education has transformed academic learning, offering both opportunities and challenges for students’ development. This study investigates the impact of AI technologies on students’ learning processes and academic performance, with a focus on their perceptions and the challenges associated with AI adoption. Conducted at the National University of Science and Technology POLITEHNICA Bucharest, this research involved second-year students who had direct experience with AI-enhanced learning environments. Using purposive sampling, 85 participants were selected to ensure relevance. Data were collected through a structured questionnaire comprising 11 items as follows: seven closed-ended questions assessing perceptions, usage, and the effectiveness of AI tools; and four open-ended questions exploring experiences, expectations, and concerns. Quantitative data were analyzed using frequency and percentage calculations, while qualitative responses were subjected to thematic analysis, incorporating both vertical (individual responses) and horizontal (cross-dataset) approaches to ensure comprehensive theme identification. The findings reveal that AI offers significant benefits, including personalized learning, improved academic outcomes, and enhanced student engagement. However, challenges such as over-reliance on AI, diminished critical thinking skills, data privacy risks, and academic dishonesty were also identified. The study underscores the necessity of a structured framework for AI integration, supported by ethical guidelines, to maximize benefits while mitigating risks. In conclusion, while AI holds immense potential to enhance learning efficiency and academic performance, its successful implementation requires addressing concerns related to accuracy, cognitive disengagement, and ethical implications. A balanced approach is essential to ensure equitable, effective, and responsible learning experiences in AI-enhanced educational environments. Full article

Gaps remain in our understanding of which factors contribute to concussion disclosure and how they contribute to this process, thereby limiting our ability to improve disclosure. This study aimed to characterize the most relevant extra-personal determinants of SC disclosure and to describe their influence on the disclosure process. To that aim, the first author conducted substantive qualitative interviews with nine university student–athletes and analyzed their content via constant comparative analysis (guided by Straussian grounded theory). Eleven (11) extra-personal concepts influencing concussion reporting were identified and described across two categories: Contextual Incentives and Socio-Cultural Pressures. These findings suggest that each identified concept can individually shape the context around the injury, creating either higher-stakes conditions that deter disclosure or lower-stakes conditions that encourage it. Further, the results posit that these concepts interact and collectively influence athletes’ decision-making process by modulating the perceived stakes of disclosing a concussion. If these findings hold true in more diverse populations and contexts, they suggest that adapting concussion prevention efforts to consider these contextual variables could improve SC disclosure. This study also highlights the benefits of using qualitative methods in the investigation of concussion reporting. Full article

Universities, as hubs for educating future leaders and decision-makers, hold a crucial role in advancing sustainable development. However, the challenge of effectively integrating sustainability into university practices and student behavior remains significant. The Ecological Footprint, subjective well-being, and academic performance are three critical dimensions that, when evaluated together, offer a comprehensive view of sustainability in the educational context. This study aims to apply a university sustainability assessment model called ’Sunshine’ to university students in a diverse sample of five different countries. Additionally, the study provides a critical analysis of the relationships among the indicators of Ecological Footprint, Happiness, and Academic Performance. This application seeks to test the robustness of the model and explore lifestyle differences among students, providing valuable insights for decision-making in the context of university sustainability. Data were collected through specific questionnaires administered to a representative sample of students, and analyses were conducted using descriptive and inferential statistical techniques. The results show that Brazilian, American, and Peruvian students exhibit an unsustainable lifestyle, requiring more than one planet to support their consumption habits. However, they are considered happy and perform well academically. These students were classified as environmentally distracted, highlighting a disconnect between their environmental awareness and practices. Chinese students showed a high ecological footprint, contrasting with the Italian group, which had an ecological footprint below one planet. However, both groups presented similar results, with low happiness indices and high academic performance. On the other hand, the group of Mexican students was the most sustainable, achieving acceptable levels in all three sustainability indicators. The analyses revealed that academic performance is related to happiness in some groups but not happiness in Ecological Footprint. This study significantly contributes by testing and validating the model in a multicultural and diverse sample, offering insights that can guide institutional policies to promote sustainability in the university environment. Full article

This study aims to explore the current state of research and the applicability of artificial intelligence (AI) at various stages of post-traumatic stress disorder (PTSD), including prevention, diagnosis, treatment, patient self-management, and drug development. We conducted a bibliometric analysis using software tools such as Bibliometrix (version 4.1), VOSviewer (version 1.6.19), and CiteSpace (version 6.3.R1) on the relevant literature from the Web of Science Core Collection (WoSCC). The analysis reveals a significant increase in publications since 2017. Kerry J. Ressler has emerged as the most influential author in the field to date. The United States leads in the number of publications, producing seven times more papers than Canada, the second-ranked country, and demonstrating substantial influence. Harvard University and the Veterans Health Administration are also key institutions in this field. The Journal of Affective Disorders has the highest number of publications and impact in this area. In recent years, keywords related to functional connectivity, risk factors, and algorithm development have gained prominence. The field holds immense research potential, with AI poised to revolutionize PTSD management through early symptom detection, personalized treatment plans, and continuous patient monitoring. However, there are numerous challenges, and fully realizing AI’s potential will require overcoming hurdles in algorithm design, data integration, and societal ethics. To promote more extensive and in-depth future research, it is crucial to prioritize the development of standardized protocols for AI implementation, foster interdisciplinary collaboration—especially between AI and neuroscience—and address public concerns about AI’s role in healthcare to enhance its acceptance and effectiveness. Full article

Megaproject construction endeavors and technological innovation activities, led by industry–university–research (IUR) collaboration, demonstrate marked disparities in value orientations, implementing entities, and constituent components. These discrepancies lead to a mismatch between innovation demands and actual activities, as well as insufficient innovation motivation among construction entities, subsequently impacting innovation effectiveness and the commercialization of outcomes and failing to adequately support engineering construction needs. In response to this predicament, the academic community widely acknowledges IUR collaborative innovation as a solution. This research integrates fundamental theoretical analysis with a multi-case study approach and systematically dissects the distinctive features at the micro, meso, and macro levels, grounded in the collaborative innovation practices of IUR in three iconic railway engineering projects in China. Subsequently, it unravels the inherent operational mechanics of the IUR collaborative innovation system within large-scale projects. Specifically, at the micro level, the profound engagement of governments and project owners fosters a solid supportive environment and collaborative platform for IUR collaboration, while past successful cooperation experiences among key innovation entities enhance their technological and knowledge interactions. At the meso level, shared industry cognitions and values, hierarchical organizational structures, flexible institutional designs, and resource allocation strategies based on balancing risks and benefits collectively constitute the supporting system for megaproject collaborative innovation. At the macro level, the tight integration of the innovation chain and industrial chain promotes the formation of an open cooperation ecosystem, ensuring the continuity and systematic nature of innovation activities and accelerating the rapid commercialization and efficient utilization of innovation outcomes. This study not only enriches the theoretical connotations of IUR collaborative innovation in the context of major engineering projects but also provides theoretical foundations for strategy formulation and management practices for major project managers, holding significant value in guiding the innovation management of future major engineering projects. Full article

Modern technologies, particularly artificial intelligence methods such as machine learning, hold immense potential for supporting doctors with cancer diagnostics. This study explores the enhancement of popular machine learning methods using a bio-inspired algorithm—the naked mole-rat algorithm (NMRA)—to assess the malignancy of thyroid tumors. The study utilized a novel dataset released in 2022, containing data collected at Shengjing Hospital of China Medical University. The dataset comprises 1232 records described by 19 features. In this research, 10 well-known classifiers, including XGBoost, LightGBM, and random forest, were employed to evaluate the malignancy of thyroid tumors. A key innovation of this study is the application of the naked mole-rat algorithm for parameter optimization and feature selection within the individual classifiers. Among the models tested, the LightGBM classifier demonstrated the highest performance, achieving a classification accuracy of 81.82% and an F1-score of 86.62%, following two-level parameter optimization and feature selection using the naked mole-rat algorithm. Additionally, explainability analysis of the LightGBM model was conducted using SHAP values, providing insights into the decision-making process of the model. Full article

Background: During the COVID-19 pandemic, teledentistry was often employed for pediatric emergency treatments. Dental students acted as the first health providers using teledentistry under the supervision of faculties in most hospital-based or university-based medical centers during the lockdown period. The aims of this study were to assess the quality of using teledentistry among general dentists (GDs) and dental students (DSs) for managing pediatric dental emergencies. Methods: In total, 60 DSs and 85 GDs were recruited in this study. Each participant was assigned to one of five teledentistry emergency scenarios in pediatric dentistry using a stratified random assignment method. Teledentistry with five emergency scenario simulations was used to evaluate the quality of diagnosis (QD) and treatment (QT) and the detailed information (DI) among all participants. A post-visit survey collected demographic data, usability, confidence in diagnosis (CD), and confidence in treatment recommendation (CT). Descriptive and inferential statistics data were analyzed. The significance level was set as p < 0.05. Results: Overall, the study showed that GDs and DSs can use teledentistry to provide good quality of diagnosis (74.5%) and treatment recommendations (77.2%). When encountering pediatric dental emergency scenarios, GDs scored significantly higher (p < 0.001) than DSs regarding QD, QT, CD, and CT. Significant differences were noted in QD (p < 0.001), QT (p < 0.001), CD (p = 0.045), and DI (p = 0.042) when the subjects encountered five different scenarios. Significant correlations were noted between the amount of detailed information subjects obtained with the quality of diagnosis and treatment recommendation. Confidence in diagnosis is significantly correlated to the quality of diagnosis (p = 0.034) and treatment recommendation (p = 0.042). However, the confidence in treatment recommendation is not correlated with either QD or QT. Both GDs and DSs hold positive attitudes toward the usability of teledentistry. Conclusions: Teledentistry is effective for diagnosing and managing pediatric dental emergencies. Experienced users provided a better quality of visit compared to novice users, so dental students should be supervised when performing a teledentistry visit. Full article

Over the past two decades, the expanding environmental and ecological crises highlight the need to broaden the concept of sustainability to encompass support for cultural sensitivity and social well-being. This study explores the role of architectural education in fostering cultural sensitivity and social well-being in embassy architecture within a framework of environment–behavior studies. It starts from the premise that the architectural values of a culture are deeply rooted in the relationship between the users, architecture, and surrounding environment. State-sponsored architectural works (e.g., embassies, consulates, cultural centers) built outside the country are viewed as symbolic representations of a nation’s diplomatic and cultural influence. These architectural typologies hold a unique potential to act as bridges for cross-cultural dialogue and foster a collective sense of global citizenship. In order to develop and assess the teaching curriculum, a specific assignment was given to master’s students of the Faculty of Architecture, University of Belgrade, with the aim to explore how engineering education can be adopted to motivate students toward sustainable attitudes and design solutions. While traditional diplomatic architecture emphasizes inward-facing, fortress-like design strategies, establishing physical and symbolic barriers between the embassy’s territory and the surrounding context, this research advocates for a more holistic approach oriented toward cultural sustainability, openness, and integration within an urban context. Key findings highlight creative solutions for balancing cultural representation with functional requirements while prioritizing community engagement, environmental responsibility, and user well-being. By demonstrating the two distinctive architectural strategies, this study contributes to the culturally responsive embassy design within the broader context of sustainable architectural education. Full article

Creating a sustainable pipeline for the STEM workforce in the U.S. necessitates a significant improvement in the graduation rates of students of color enrolled in STEM majors. This is particularly important given the major demographic shifts projected over the next four decades, where students of color will constitute the majority of the student population. One way to increase graduation rates is to improve the mentoring of these students by implementing Culturally Responsive Mentor Training. Rooted in the Entering Mentoring curriculum, this approach has been shown to enhance mentoring competencies and shape mentoring behaviors of researchers across various disciplines and career stages. However, existing research has predominantly focused on mentor training programs within individual institutions, leaving a significant knowledge gap regarding the potential benefits of inter-institutional mentor training initiatives that share a common objective of supporting underrepresented students in STEM fields. Between 2019 and 2022, a structured mentoring program engaged 45 mentors from the Georgia–Alabama Louis Stokes Alliance for Minority Participation (GA-AL LSAMP). Noteworthy outcomes emerged from this initiative, with participants reporting substantial improvements in their mentoring skills post-training. A majority of participants implemented changes in their mentoring practices following the training program. The self-reported findings from mentors were corroborated by data collected from mentee surveys, which validated shifts in the mentors’ behaviors subsequent to the training. These results hold implications for LSAMP alliances nationwide and for all colleges and universities that aspire to create a sustainable pipeline for the STEM workforce in the U.S. Full article

The Ethnographic Museum in Dubrovnik holds an extensive textile collection which includes a number of dresses and costumes from Croatia and neighbouring countries. Until recently, the costumes were displayed on mannequins created by the academic artist Zvonimir Lončarić (1927–2004). His sculptures are expressive forms made of terracotta, fibreglass, wood, metal, acrylic paint and other materials chosen for their visual appeal. Due to their importance, the museum considered the mannequins to be protected works of art in the permanent exhibition; however, they had a harmful effect on the costumes displayed. In 2018, after completing a series of conservation–restoration projects within the collection, it was decided to replace the existing mounts with new, museum-quality mannequins. Two project-based learning workshops were organised, led by a team of textile conservators from the University of Dubrovnik and the Croatian Conservation Institute, in collaboration with the curator of the Ethnographic Museum. This case study highlights the challenges of exhibiting ethnographic costumes by discussing past presentation methods and how new solutions have been implemented in line with the modern conservation–restoration profession. The new solutions take into consideration ethics, decision-making processes, and an understanding of contemporary materials and methodology. Full article