Search Results (1,731)

Emotion regulation is essential for mental health. However, many people ignore their own emotional regulation or are deterred by the high cost of psychological counseling, which poses significant challenges to making effective support widely available. This review systematically examines the convergence of multimodal sensing technologies and large language models (LLMs) for the development of Automated Emotional Regulation (AER) systems. The review draws upon a comprehensive analysis of the existing literature, encompassing research papers, technical reports, and relevant theoretical frameworks. Key findings indicate that multimodal sensing offers the potential for rich, contextualized data pertaining to emotional states, while LLMs provide improved capabilities for interpreting these inputs and generating nuanced, empathetic, and actionable regulatory responses. The integration of these technologies, including physiological sensors, behavioral tracking, and advanced LLM architectures, presents the improvement of application, moving AER beyond simpler, rule-based systems towards more adaptive, context-aware, and human-like interventions. Opportunities for personalized interventions, real-time support, and novel applications in mental healthcare and other domains are considerable. However, these prospects are counterbalanced by significant challenges and limitations. In summary, this review synthesizes current technological advancements, identifies substantial opportunities for innovation and application, and critically analyzes the multifaceted technical, ethical, and practical challenges inherent in this domain. It also concludes that while the integration of multimodal sensing and LLMs holds significant potential for AER, the field is nascent and requires concerted research efforts to realize its full capacity to enhance human well-being. Full article

This study presents a cross-cultural comparison of two fortified residences—Palazzo Farnese in Italy and Dong’s Fortified Compound in China—through a triadic analytical framework encompassing architectural form, symbolic ornamentation, and public perception. By combining field observation, iconographic interpretation, and digital ethnography, the research investigates how heritage meaning is constructed, encoded, and reinterpreted across distinct sociocultural contexts. Empirical materials include architectural documentation, decorative analysis, and a curated dataset of 4947 user-generated images and 1467 textual comments collected from Chinese and international platforms between 2020 and 2024. Methods such as CLIP-based visual clustering and BERTopic-enabled sentiment modelling were applied to extract patterns of perception and symbolic emphasis. The findings reveal contrasting representational logics: Palazzo Farnese encodes dynastic authority and Renaissance cosmology through geometric order and immersive frescoes, while Dong’s Compound conveys Confucian ethics and frontier identity via nested courtyards and traditional ornamentation. Digital responses diverge accordingly: international users highlight formal aesthetics and photogenic elements; Chinese users engage with symbolic motifs, family memory, and ritual significance. This study illustrates how historically fortified residences are reinterpreted through culturally specific digital practices, offering an interdisciplinary approach that bridges architectural history, symbolic analysis, and digital heritage studies. Full article

Background and Aim: Artificial intelligence (AI) is among the most promising innovations for transforming nursing education, making it more interactive, personalized, and competency-based. However, its integration also raises significant ethical and practical concerns. This scoping review aims to analyze and summarize key studies on the application of AI in university-level nursing education, focusing on its benefits, challenges, and future prospects. Methods: A scoping review was conducted using the Population, Concept, and Context (PCC) framework, targeting nursing students and educators in academic settings. A comprehensive search was carried out across the PubMed, Scopus, and Web of Science databases. Only peer-reviewed original studies published in English were included. Two researchers independently screened the studies, resolving any disagreements through team discussion. Data were synthesized narratively. Results: Of the 569 articles initially identified, 11 original studies met the inclusion criteria. The findings indicate that AI-based tools—such as virtual simulators and ChatGPT—can enhance students’ learning experiences, communication skills, and clinical preparedness. Nonetheless, several challenges were identified, including increased simulation-related anxiety, potential misuse, and ethical concerns related to data quality, privacy, and academic integrity. Conclusions: AI offers significant opportunities to enhance nursing education; however, its implementation must be approached with critical awareness and responsibility. It is essential that students develop both digital competencies and ethical sensitivity to fully leverage AI’s potential while ensuring high-quality education and responsible nursing practice. Full article

Previous reviews have examined specific facets of Geographic Information Systems (GIS) in transportation planning, such as transit-focused applications and open source geospatial tools. However, this study offers the first systematic, PRISMA-guided longitudinal evaluation of GIS integration in transportation planning, spanning thematic domains, data models, methodologies, and outcomes from 2004 to 2024. This study addresses this gap through a longitudinal analysis of GIS-based transportation research from 2004 to 2024, adhering to PRISMA guidelines. By conducting a mixed-methods analysis of 241 peer-reviewed articles, this study delineates major trends, such as increased emphasis on sustainability, equity, stakeholder involvement, and the incorporation of advanced technologies. Prominent domains include land use–transportation coordination, accessibility, artificial intelligence, real-time monitoring, and policy evaluation. Expanded data sources, such as real-time sensor feeds and 3D models, alongside sophisticated modeling techniques, enable evidence-based, multifaceted decision-making. However, challenges like data limitations, ethical concerns, and the need for specialized expertise persist, particularly in developing regions. Future geospatial innovations should prioritize the responsible adoption of emerging technologies, inclusive capacity building, and environmental justice to foster equitable and efficient transportation systems. This review highlights GIS’s evolution from a supplementary tool to a cornerstone of data-driven, sustainable urban mobility planning, offering insights for researchers, practitioners, and policymakers to advance transportation strategies that align with equity and sustainability goals. Full article

Background: Preimplantation genetic testing for polygenic diseases (PGT-P) is a reproductive technology that has made it possible to assign risk scores to embryos for various complex polygenic conditions such as diabetes, hypertension, breast cancer, and schizophrenia. Whether there is public interest in utilizing PGT-P and what public opinions are regarding this technology is unknown. Therefore, the objective of our study was to evaluate the opinion of the general United States (US) public regarding PGT-P. Methods: A web-based questionnaire consisting of 25 questions was administered to a nationally representative sample of adult US residents according to age and sex. The survey contained a description of PGT-P, followed by questions with Likert-scale responses ranging from strongly agree to strongly disagree. Results: Of the 715 respondents recruited, 673 (94%) completed the survey. Most respondents agreed that use of PGT-P is ethical (54%), and another 37% were neutral; however, approximately 9% of respondents disagreed and were opposed to the use of PGT-P. Those that opposed PGT-P cited that it was “unethical” (46%) or “not natural” (39%), believed children could be negatively affected (31%), or stated that it went against their religion (15%). The majority of respondents did not know whether PGT-P was safe for embryos (68%) or children (67%) and felt that anyone should be able to utilize it (53%). Conclusions: Participants who were younger, were Atheist, or were Democrats were more likely to agree that “PGT-P is ethical”. This study identified that more than half of respondents supported the use of PGT-P. However, concerns regarding its safety and ethical implications persist. Full article

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

This paper shows that artificial intelligence is fundamentally transforming college curricula by enabling data-driven personalization, which enhances student outcomes and better aligns educational programs with evolving workforce demands. Specifically, predictive analytics, machine learning algorithms, and natural language processing were applied here, grounded in constructivist learning theory and Human–Computer Interaction principles, to evaluate student performance and identify at-risk students to propose personalized learning pathways. Results indicated that the AI-based curriculum achieved much higher course completion rates (89.72%) as well as retention (91.44%) and dropout rates (4.98%) compared to the traditional model. Sentiment analysis of learner feedback showed a more positive learning experience, while regression and ANOVA analyses proved the impact of AI on enhancing academic performance to be real. Therefore, the learning content delivery for each student was continuously improved based on individual learner characteristics and industry trends by AI-enabled recommender systems and adaptive learning models. Its advantages notwithstanding, the study emphasizes the need to address ethical concerns, ensure data privacy safeguards, and mitigate algorithmic bias before an equitable outcome can be claimed. These findings can inform institutions aspiring to adopt AI-driven models for curriculum innovation to build a more dynamic, responsive, and learner-centered educational ecosystem. Full article

This article investigates the revolutionary potential of AI-powered virtual assistants in augmented reality (AR) and virtual reality (VR) environments, concentrating primarily on their impact on special needs schooling. We investigate the complex characteristics of these virtual assistants, the influential elements affecting their development and implementation, and the joint efforts of educational institutions and technology developers, using a rigorous quantitative approach. Our research also looks at strategic initiatives aimed at effectively integrating AI into educational practices, addressing critical issues including infrastructure, teacher preparedness, equitable access, and ethical considerations. Our findings highlight the promise of AI technology, emphasizing the ability of AI-powered virtual assistants to provide individualized, immersive learning experiences adapted to the different needs of students with special needs. Furthermore, we find strong relationships between these virtual assistants’ features and deployment tactics and their subsequent impact on educational achievements. This study contributes to the increasing conversation on harnessing cutting-edge technology to improve educational results for all learners by synthesizing current research and employing a strong methodological framework. Our analysis not only highlights the promise of AI in increasing student engagement and comprehension but also emphasizes the importance of tackling ethical and infrastructure concerns to enable responsible and fair adoption. Full article

Artificial Intelligence (AI) and Generative AI are transformative yet double-edged technologies with evolving risks. While research emphasises trustworthy, fair, and responsible AI by focusing on its “what” and “why,” it overlooks practical “how.” To bridge this gap in financial services, an industry at the forefront of AI adoption, this study employs a qualitative approach grounded in existing Responsible AI and Corporate Digital Responsibility (CDR) frameworks. Through thematic analysis of 15 semi-structured interviews conducted with professionals working in finance, we illuminate nine non-technical barriers that practitioners face, such as sustainability challenges, trade-off balancing, stakeholder management, and human interaction, noting that GenAI concerns now eclipse general AI issues. CDR practitioners adopt a more human-centric stance, emphasising consensus-building and “no margin for error.” Our findings offer actionable guidance for more responsible AI strategies and enrich academic debates on Responsible AI and AI-CDR symbiosis. Full article

Ensuring sustainable food systems is an urgent global priority as populations grow and environmental pressures mount. Technological innovations such as genetic engineering (GE) and nanotechnology (nano) have been promoted as promising pathways for achieving greater sustainability in agriculture and food production. Yet, the sustainability of these technologies is not defined by technical performance alone; it hinges on how they are perceived by key stakeholders and how well they align with broader societal values. This study addresses the critical question of how expert stakeholders evaluate the sustainability of GE and nano-based food and agriculture (agrifood) products. Using a multi-method online platform, we engaged 42 experts across academia, government, industry, and NGOs in the United States to assess six real-world case studies—three using GE and three using nano—across ten different dimensions of sustainability. We show that nano-based products were consistently rated more favorably than their GE counterparts in terms of environmental, economic, and social sustainability, as well as across ethical and societal dimensions. Like prior studies, our results reveal that stakeholders see meaningful distinctions between nanotechnology and biotechnology, likely due to underlying value-based concerns about animal welfare, perceived naturalness, or corporate control of agrifood systems. The fruit coating and flu vaccine—both nano-enabled—received the most positive ratings, while GE mustard greens and salmon were the most polarizing. These results underscore the importance of incorporating stakeholder perspectives in technology assessment and innovation governance. These results also suggest that responsible innovation efforts in agrifood systems should prioritize communication, addressing meaningful societal needs, and the contextual understanding of societal values to build trust and legitimacy. Full article

Although intracranial hypertension (ICH) has traditionally been framed as simply a numerical escalation of intracranial pressure (ICP) and usually dealt with in its clinical form and not in terms of its complex underlying pathophysiology, an emerging body of evidence indicates that ICH is not simply an elevated ICP process but a complex process of molecular dysregulation, glymphatic dysfunction, and neurovascular insufficiency. Our aim in this paper is to provide a complete synthesis of all the new thinking that is occurring in this space, primarily on the intersection of glymphatic dysfunction and cerebral vein physiology. The aspiration is to review how glymphatic dysfunction, largely secondary to aquaporin-4 (AQP4) dysfunction, can lead to delayed cerebrospinal fluid (CSF) clearance and thus the accumulation of extravascular fluid resulting in elevated ICP. A range of other factors such as oxidative stress, endothelin-1, and neuroinflammation seem to significantly impair cerebral autoregulation, making ICH challenging to manage. Combining recent studies, we intend to provide a revised conceptualization of ICH that recognizes the nuance and complexity of ICH that is understated by previous models. We wish to also address novel diagnostics aimed at better capturing the dynamic nature of ICH. Recent advances in non-invasive imaging (i.e., 4D flow MRI and dynamic contrast-enhanced MRI; DCE-MRI) allow for better visualization of dynamic changes to the glymphatic and cerebral blood flow (CBF) system. Finally, wearable ICP monitors and AI-assisted diagnostics will create opportunities for these continuous and real-time assessments, especially in limited resource settings. Our goal is to provide examples of opportunities that exist that might augment early recognition and improve personalized care while ensuring we realize practical challenges and limitations. We also consider what may be therapeutically possible now and in the future. Therapeutic opportunities discussed include CRISPR-based gene editing aimed at restoring AQP4 function, nano-robotics aimed at drug targeting, and bioelectronic devices purposed for ICP modulation. Certainly, these proposals are innovative in nature but will require ethically responsible confirmation of long-term safety and availability, particularly to low- and middle-income countries (LMICs), where the burdens of secondary ICH remain preeminent. Throughout the review, we will be restrained to a balanced pursuit of innovative ideas and ethical considerations to attain global health equity. It is not our intent to provide unequivocal answers, but instead to encourage informed discussions at the intersections of research, clinical practice, and the public health field. We hope this review may stimulate further discussion about ICH and highlight research opportunities to conduct translational research in modern neuroscience with real, approachable, and patient-centered care. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

Background/Objectives: Clinical Research Nurses (CRNs) have emerged as pivotal actors in the conduct, coordination, and oversight of clinical trials globally. Over the past three decades, the role of the CRN has evolved in response to the increasing complexity of research protocols, ethical standards, and regulatory frameworks. Originating as task-oriented support figures, CRNs have progressively assumed broader responsibilities that include patient advocacy, protocol integrity, ethical vigilance, and interprofessional coordination. By mapping the global literature on CRNs, this review will examine how their role has been defined, implemented, and evaluated over the past three decades. Methods: A scoping review was conducted using JBI methodology and PRISMA-ScR guidelines. The search covered the peer-reviewed and gray literature from 1990 to 2024 across major databases. Data analysis combined traditional extraction with topic modeling, Multiple Correspondence Analysis, and k-means clustering to identify key themes. Results: From the 128 included studies, four major themes emerged: clinical trial management, role perception and team integration, professional competencies and development, and systemic barriers. Despite formal competency frameworks, CRNs face inconsistencies in role recognition, unstable contracts, and limited career pathways. Emotional strain and professional isolation are recurrent. Over time, their functions have evolved from task execution to broader responsibilities, including advocacy and ethical oversight. However, no studies reported patient-level outcomes, revealing a critical gap in the evidence base. Conclusions: CRNs play a vital but undervalued role in clinical research. Persistent structural challenges hinder their development and visibility. Enhancing institutional support and generating outcome-based evidence are necessary steps toward fully integrating CRNs into research infrastructures. Full article

Marine biomass represents a valuable yet underexploited resource for the development of high-value biomaterials. Recent advances have highlighted the significant potential of marine-derived polysaccharides, proteins, and peptides in biomedical applications, most notably in drug delivery and wound healing. This review provides a comprehensive synthesis of current research on the extraction, processing and pharmaceutical valorization of these biopolymers, with a focus on their structural and functional properties that allow these materials to be engineered into nanocarriers, hydrogels, scaffolds, and smart composites. Key fabrication strategies such as ionic gelation, desolvation, and 3D bioprinting are critically examined for their role in drug encapsulation, release modulation, and scaffold design for regenerative therapies. The review also covers preclinical validation, scale-up challenges, and relevant regulatory frameworks, offering a practical roadmap from sustainable sourcing to clinical application. Special attention is given to emerging technologies, including stimuli-responsive biomaterials and biosensor-integrated wound dressings, as well as to the ethical and environmental implications of marine biopolymer sourcing. By integrating materials science, pharmaceutical technology and regulatory insight, this review aims to provide a multidisciplinary perspective for researchers and industrial stakeholders seeking sustainable and multifunctional pharmaceutical platforms for precision medicine and regenerative therapeutics. Full article

Parkinson’s disease (PD) is a progressive neurological disorder with motor and non-motor symptoms that are inadequately addressed by current pharmacological and surgical therapies. Brain–computer interfaces (BCIs), particularly those based on electroencephalography (eBCIs), provide a promising, non-invasive approach to personalized neurorehabilitation. This narrative review explores the clinical potential of BCIs in PD, discussing signal acquisition, processing, and control paradigms. eBCIs are well-suited for PD due to their portability, safety, and real-time feedback capabilities. Emerging neurophysiological biomarkers—such as beta-band synchrony, phase–amplitude coupling, and altered alpha-band activity—may support adaptive therapies, including adaptive deep brain stimulation (aDBS), as well as motor and cognitive interventions. BCIs may also aid in diagnosis and personalized treatment by detecting these cortical and subcortical patterns associated with motor and cognitive dysfunction in PD. A structured search identified 11 studies involving 64 patients with PD who used BCIs for aDBS, neurofeedback, and cognitive rehabilitation, showing improvements in motor function, cognition, and engagement. Clinical translation requires attention to electrode design and user-centered interfaces. Ethical issues, including data privacy and equitable access, remain critical challenges. As wearable technologies and artificial intelligence evolve, BCIs could shift PD care from intermittent interventions to continuous, brain-responsive therapy, potentially improving patients’ quality of life and autonomy. This review highlights BCIs as a transformative tool in PD management, although more robust clinical evidence is needed. Full article