Search Results (2,017)

Higher technical education plays a strategic role in equipping the workforce to navigate rapid technological advancements and evolving labor market demands. Within the Rome Technopole framework, Spoke 4 targets ITS Academies, promoting the development of flexible, modular programs that integrate advanced technical skills with ethical, legal, and societal perspectives. This study reports on a pilot training initiative on Artificial Intelligence (AI) co-designed by the Istituto Superiore di Sanità (ISS), aimed at exploring the ethical, practical, and educational relevance of AI in higher technical education. The module was developed and tested through a multi-stakeholder collaboration involving educators, institutional actors, and learners. A four-phase approach was adopted: (1) initial stakeholder consultation to identify needs and content directions, (2) collaborative design of the training module, (3) online delivery and engagement using a CAWI-based focus group, and (4) mixed-method evaluation, combining quantitative assessments and open-ended qualitative feedback. This design facilitated asynchronous participation and encouraged critical reflection on the real-world implications of AI. Through the four-phase approach, the pilot module was developed, delivered, and assessed with 37 participants. Quantitative analysis revealed high ratings for clarity, relevance, and perceived utility in terms of employability. Qualitative feedback highlighted the interdisciplinary design, the integration of ethical reasoning, and the module’s broad applicability across sectors—particularly Healthcare and Industry. Participants suggested including more real-world case studies and collaborative learning activities to enhance engagement. The findings support the feasibility and added value of embedding ethically informed, interdisciplinary AI education in professional technical training pathways. Developed within the Rome Technopole ecosystem, the pilot module offers a promising approach to fostering critical digital literacy and preparing learners for responsible engagement with emerging technologies. Full article

Cadmium (Cd) contamination in agricultural soils originates mainly from atmospheric deposition, irrigation water, fertilizers, pesticides, and industrial waste discharges. This human-induced pollution adversely affects soil fertility and structure, disrupts plant growth and physiological activities, and poses severe health risks through food-chain accumulation. Despite increasing research attention, comprehensive assessments that integrate global patterns, remediation strategies, and knowledge gaps remain limited. Therefore, this literature review critically synthesizes findings from 1060 peer-reviewed studies (screened using PRISMA guidelines) retrieved from Scopus and Web of Science databases, focusing on Cd sources, environmental behavior, plant responses, and soil remediation techniques. Results show that most research has been concentrated in Asia—particularly China—and Latin America. The most frequently investigated topics include Cd accumulation in crops, soil amendments, phytoremediation, and microbial-assisted remediation. Among remediation strategies, assisted phytoremediation and integrated biological–chemical approaches (biochar, PGPR, and soil amendments) emerged as the most promising for sustainable Cd mitigation. In conclusion, this review highlights regional disparities in research coverage, emphasizes the effectiveness of combined remediation approaches, and identifies the need for interdisciplinary and field-scale studies to advance sustainable solutions for Cd pollution control in agricultural systems. Full article

It has been recognized that Blockchain technology contributes to environmentally sustainable development goals (SDGs). It has emerged as a disruptive innovation capable of transforming various economic and social sectors significantly. This conceptual paper is driven by the need to explore how blockchain, specifically a consortium-based Ethereum architecture, can be integrated into higher education institutions to ensure data sovereignty, integrity, and verifiability while adhering to legal and ethical standards such as GDPR. We propose a multi-layered blockchain-based model for Kazakhstan’s Unified Platform of Higher Education (UPHE). This model employs hybrid on-chain/off-chain data storage, smart contract automation, and a Proof-of-Authority consensus mechanism to address system limitations, including data centralization and inadequate verification of academic credentials. Empirical simulations using Blockscout and Ethereum-compatible tools demonstrate the model’s feasibility and performance. This paper contributes to the growing discussion on educational blockchain applications by presenting a scalable, secure, and transparent architecture that aligns with institutional governance and Environmental, Social, and Governance (ESG) principles. It also supports the objectives of UN SDG 4 (i.e., Quality education) by fostering trust, transparency, and equitable access to verifiable educational credentials. Full article

People are exposed to pesticides daily through food, drinking water, and the environment, both in urban and rural settings. These chemicals, while offering economic and agricultural benefits through pest control and increased productivity, may pose a growing risk to human health and ecosystem biodiversity. While the European regulatory framework offers a robust foundation for risk assessment, significant limitations persist, especially in addressing cumulative exposure, low-dose effects, and chemical mixtures. This review focuses on selected scientific and regulatory challenges by reviewing recent European Food Safety Authority (EFSA) conclusions, Organization for Economic Co-operation and Development (OECD) test guidelines updates, and current European legislative approaches. Particular attention is given to the regulation of endocrine-disrupting and reprotoxic substances, highlighting progress and remaining gaps in implementation. A brief mention will also be made of immuno-toxic substances, for which no specific hazard class has yet been established. Building on official reports and peer-reviewed literature, this review provides a structured evaluation of the scientific and regulatory landscape, including underexplored issues like the transition to animal-free toxicology and integration of biomonitoring with health data. The goal is to propose realistic, evidence-based improvements to current frameworks using integrated, interdisciplinary approaches that connect toxicology, policy, and implementation science. A shift to a holistic, systems-based, and precautionary paradigm is vital to address emerging challenges and ensure strong protection of health and environment, as well as supporting the needs of the agricultural sector. Full article

Bridges, as critical transportation infrastructure, are highly vulnerable to aerodynamic forces, particularly vortex-induced vibrations (VIV), which severely compromise their structural integrity and operational safety. These low-frequency, high-amplitude vibrations are a primary challenge to serviceability and fatigue life. Ensuring the resilience of these structures demands advanced understanding and robust mitigation strategies. This paper comprehensively addresses the multifaceted challenges of bridge aerodynamics, presenting an in-depth analysis of contemporary testing methodologies and innovative solutions. We critically examine traditional wind tunnel modeling, elucidating its advantages and inherent limitations, such as scale effects, Reynolds number dependence, and boundary interference, which can lead to inaccurate predictions of aerodynamic forces and vibration amplitudes. This scale discrepancy is critical, as demonstrated by peak pressure coefficients being underestimated by up to 64% in smaller-scale wind tunnel environments compared to high-Reynolds-number open-jet testing. To overcome these challenges, the paper details the efficacy of open-jet testing at facilities like the Windstorm Impact, Science, and Engineering (WISE) Laboratory, demonstrating its superior capability in replicating realistic atmospheric boundary layer flow conditions and enabling larger-scale, high-Reynolds-number testing for more accurate insights into bridge behavior under dynamic wind loads. Furthermore, we explore the design principles and applications of various aerodynamic mitigation devices, including handrails, windshields, guide vanes, and spoilers, which are essential for altering airflow patterns and suppressing vortex-induced vibrations. The paper critically investigates the innovative integration of green energy solutions, specifically solar panels, with bridge structures. This study presents the application of solar panel arrangements to provide both renewable energy production and verifiable aerodynamic mitigation. This strategic incorporation is shown not only to harness renewable energy but also to actively improve aerodynamic performance and mitigate wind-induced vibrations, thereby fostering both bridge safety and sustainable infrastructure development. Unlike previous studies focusing primarily on wind loads on PV arrays, this work demonstrates how the specific geometric integration of solar panels can serve as an active aerodynamic mitigation device for bridge decks. This dual functionality—harnessing renewable energy while simultaneously serving as a passive geometric countermeasure to vortex-induced vibrations—marks a novel advancement over single-purpose mitigation technologies. Through this interdisciplinary approach, the paper seeks to advance bridge engineering towards more resilient, efficient, and environmentally responsible solutions. Full article

Family caregivers provide most daily care for people living with chronic illness or frailty, yet they remain under-recognized in health and social care systems. To address this gap, we co-designed the Caregiver-Centered Care Champions Education Program, which equips frontline providers with the competencies needed to lead caregiver-inclusive change. Guided by the Kirkpatrick-Barr Health Workforce Education Framework, we conducted a mixed methods interpretive description evaluation of learner satisfaction, knowledge and confidence gains, and self-reported behaviour change. Sixty-seven interdisciplinary participants completed three online modules. Quantitative results from pre/post surveys (Wilcoxon signed rank tests) showed significant improvements across all competencies (p < 0.001; large effect sizes) alongside high satisfaction (means 6.56–6.96/7). Qualitative findings revealed that 94% of participants applied program content within three months, and 61% implemented five or more distinct behaviour changes (e.g., collaborative care planning, system navigation support). The analysis illuminated how learners integrated caregiver-centred principles with change leadership strategies. Time constraints and staffing shortages emerged as key barriers. Our co-designed, theory-informed approach effectively bridged individual learning and system change, demonstrating the potential to transform caregiver inclusion practices when supported by organizational policies. Full article

In response to the growing complexity of global exploration targets, traditional Euclidean geometric and linear statistical methods reveal inherent theoretical limitations in characterizing hydrocarbon reservoirs as complex geological bodies that exhibit simultaneous local disorder and global order. Fractal theory, with its core parameter systems such as fractal dimension and scaling exponents, provides an innovative mathematical–physics toolkit for quantifying spatial heterogeneity and resolving the multi-scale characteristics of reservoirs. This review systematically consolidates recent advancements in the application of fractal theory to oil and gas resource assessment, with the aim of elucidating its transition from a theoretical concept to a practical tool. We conclusively demonstrate that fractal theory has driven fundamental methodological progress across four critical dimensions: (1) In reservoir classification and evaluation, fractal dimension has emerged as a robust quantitative metric for heterogeneity and facies discrimination. (2) In pore structure characterization, the theory has successfully uncovered structural self-similarity across scales, from nanopores to macroscopic vugs, enabling precise modeling of complex pore networks. (3) In seepage behavior analysis, fractal-based models have significantly enhanced the predictive capacity for non-Darcy flow and preferential migration pathways. (4) In fracture network modeling, fractal geometry is proven pivotal for accurately characterizing the spatial distribution and connectivity of natural fractures. Despite significant progress, current research faces challenges, including insufficient correlation with dynamic geological processes and a scarcity of data for model validation. Future research should focus on the following directions: developing fractal parameter inversion methods integrated with artificial intelligence, constructing dynamic fractal–seepage coupling models based on digital twins, establishing a unified fractal theoretical framework from pore to basin scale, and expanding its application in low-carbon energy fields such as carbon dioxide sequestration and natural gas hydrate development. Through interdisciplinary integration and methodological innovation, fractal theory is expected to advance hydrocarbon resource assessment toward intelligent, precise, and systematic development, providing scientific support for the efficient exploitation of complex reservoirs and the transition to green, low-carbon energy. Full article

Systemic Lupus Erythematosus (SLE) is a multifaceted autoimmune disease that requires individualized care and informed patient counseling. Pharmacists are well-positioned to support SLE patients, yet gaps in knowledge and preparedness among pharmacy professionals may hinder optimal care. This study aimed to identify unmet educational and clinical needs related to SLE among pharmacy students and faculty, with the goal of informing strategies to incorporate SLE-focused education into pharmacy curricula. A systematic review of existing needs assessments was conducted, followed by a survey exploring participants’ confidence, knowledge, and perceived preparedness in managing SLE. Results revealed significant disparities in understanding and confidence, particularly among students. Faculty demonstrated moderate confidence in areas such as medication counseling and lifestyle guidance, while students reported low confidence in discussing self-care, psychosocial support, and disease management. Both groups expressed uncertainty about tools and strategies for patient education and engagement. These findings highlight educational gaps in pharmacy students’ and faculty’s preparedness to manage SLE, underscoring the need to use these insights as a foundation for curricular development. Integrating these materials into pharmacy curricula and continuing education programs can enhance pharmacists’ ability to deliver empathetic, informed, and patient-centered care. This study supports a broader effort to improve chronic disease management through interdisciplinary collaboration and educational innovation. Full article

Background: Diabetic ketoacidosis (DKA) in patients with kidney failure receiving dialysis presents a formidable clinical challenge. Standard DKA protocols, designed for patients with preserved renal function, often fail in this cohort and can be unsafe when applied without modification. Patients are at risk of iatrogenic fluid overload, dyskalaemia, and hypoglycaemia due to altered insulin kinetics, impaired gluconeogenesis, and the absence of osmotic diuresis. Purpose: This narrative review aims to synthesise current understanding of DKA pathophysiology in dialysis patients, delineate distinct clinical phenotypes, and propose individualised management strategies grounded in physiology-based reasoning, comparative guideline insights, and consensus-supported literature. Methods: We searched PubMed/MEDLINE, Embase, and Google Scholar (January 2004–June 2024) for adult dialysis populations, using terms spanning DKA, kidney failure, insulin kinetics, fluid balance, and cerebral oedema. Reviews, observational cohorts, guidelines, consensus statements, and physiology papers were prioritised; case reports were used selectively for illustration. Evidence was weighted by physiological plausibility and practice relevance. Nephrology-led authors aimed for a pragmatic, safety-first synthesis, seeking and integrating contradictory recommendations. Conclusions: Our findings highlight the critical need for a nuanced approach to fluid management, a tailored insulin strategy that accounts for glucose-insulin decoupling and prolonged insulin half-life, and careful consideration of potassium and acidosis correction. We emphasise the importance of recognising specific volume phenotypes (hypovolaemic, euvolaemic, hypervolaemic) to guide fluid therapy, and advocating the judicious use of variable-rate insulin infusions (‘dry insulin’) to mitigate fluid overload. We also show that service-level factors are critical. Dialysis-specific pathways, interdisciplinary training, and quality improvement metrics can reduce iatrogenic harm. By linking physiology with workflow adaptations, this review provides a physiologically sound, bedside-oriented map for navigating this complex emergency safely and effectively. In doing so, it advances an individualised model of DKA care for dialysis-dependent patients. Full article

Antimicrobial resistance (AMR) is widely recognized as a major global public health threat, yet its origins and implications extend beyond the simple misuse or overuse of antibiotics. This study explores AMR as a complex, multifactorial phenomenon shaped by biological, clinical, dental, environmental, and social dynamics, with particular attention to the emerging role of dentistry. A narrative literature review was performed, drawing from textbooks, peer-reviewed articles, and official World Health Organization (WHO) reports, with emphasis on recent findings on periodontal biofilms as reservoirs of resistance genes. The analysis shows that AMR develops through bacterial mutations, horizontal gene transfer, environmental contamination, healthcare-associated practices, and patient behaviors, all of which interact to sustain its spread. Within dentistry, subgingival microresistances are gaining relevance, complicating treatment strategies and underscoring the need for more conscious clinical decision-making. The findings suggest that reducing antibiotic prescriptions or developing new drugs alone will not suffice; instead, a systemic, interdisciplinary approach is required, integrating microbiology, clinical practice, public health, and institutional responsibility. Such awareness is essential to confront the significant clinical, economic, and social implications of AMR and to foster strategies capable of addressing its complex and evolving nature. Full article

Cultural heritage museums, as integral components of the urban built environment and public cultural space, not only preserve historical memory but also subtly shape visitors’ psychological experiences and well-being. Yet the mechanisms linking museum environmental quality with visitor mental experiences remain insufficiently explored. Drawing on 10,684 visitor reviews collected from Dianping, Weibo, and Ctrip, this study applies text mining and semantic analysis to construct an evaluation framework of visitor behavioral preferences and psychological experiences in heritage museums. The findings show that attention to spatial remains, historical artifacts, and cultural symbols is closely associated with positive emotions such as mystery, awe, and beauty, while adverse environmental conditions such as queuing and crowding often trigger negative feelings including fatigue, disappointment, and boredom. Further analysis reveals a clear pathway linking objects, behaviors, and experiences: spatial remains evoke psychological resonance through immersive perceptions of authenticity; artifacts are primarily linked to visual pleasure and emotional comfort; and cultural symbols are transformed into cognitive gains and spiritual meaning through interpretation and learning. Cross-regional comparison highlights significant differences among museums with distinct cultural backgrounds in terms of architectural aesthetics, educational value, and emotional resonance. This study not only offers a practical framework for the refined management and spatial optimization of heritage museums, but also demonstrates that high-quality cultural environments can promote mental health and emotional restoration. The results extend the interdisciplinary framework of museum research and provide empirical evidence for environmental improvement and public health promotion in cultural heritage spaces in the digital era. Full article

Background: Insomnia is markedly more prevalent in rheumatoid arthritis (RA) patients than in the general population and is closely linked to pain, fatigue, psychological comorbidities, and systemic inflammation. Evidence suggests a bidirectional relationship, where active disease worsens sleep quality, while poor sleep amplifies inflammatory activity and symptom severity. Methods: A narrative review was conducted using PubMed, Scopus, Web of Science, and Embase to identify studies from the last 15 years involving adult RA patients. Inclusion criteria required assessment of insomnia or sleep quality in relation to disease activity, treatment outcomes, or inflammatory markers. Data from clinical trials, cohort studies, and reviews were synthesized to examine prevalence, mechanisms, and therapeutic implications. Results: Insomnia affects up to 45% of RA patients and correlates with higher DAS28 scores, elevated CRP/ESR, increased pain sensitivity, and reduced quality of life. Contributing factors include chronic pain, stiffness, elevated IL-6 and TNF-α, depression, anxiety, and medication side effects. Conventional DMARDs, corticosteroids, and biologics indirectly improve sleep via inflammation control, with IL-6 inhibition showing potential sleep-specific benefits. Psychotropic agents may help in comorbid depression/anxiety but are best combined with cognitive behavioral therapy for insomnia (CBT-I). Conclusions: Insomnia is a prevalent, multifactorial problem in RA that adversely affects disease activity, symptom burden, and functional outcomes. Integrating sleep evaluation into routine RA management and adopting interdisciplinary strategies that address both inflammation and sleep disturbance may enhance patient outcomes. High-quality longitudinal studies using objective sleep measures are needed to clarify causal relationships and optimize therapy. Full article

This study investigates the applicability of the Japanese forest education model, exemplified by the Whole Earth Nature School (WENS), to environmental education programs within urban parks and botanical gardens. Focusing on WENS’s approach—characterized by immersive natural experiences, innovative facilitation techniques, and support from interdisciplinary educator teams to foster independent thinking through experiential learning—the research identifies three transferable insights: (1) Reorienting educational philosophy to prioritize nature-based learning for holistic development, particularly within urban green spaces; (2) Developing localized curricula that leverage the unique ecological resources of specific park and garden environments; (3) Establishing dedicated professional development systems for educators focused on site-based pedagogy. The findings demonstrate that adapting the forest education model can significantly enhance environmental education initiatives in urban parks and botanical gardens, which offers actionable strategies for integrating experiential nature learning into their educational planning. Full article

Background/Objectives: Combining orthognathic surgery with orthodontic therapy is a crucial approach for correcting severe dentofacial deformities that orthodontics alone cannot address. This study aimed to quantify skeletal, dental, and soft tissue alterations following orthognathic surgery and to assess correlations among cephalometric parameters to improve understanding of treatment outcomes. Methods: A prospective observational study was conducted on 25 Romanian patients (44% female and 56% male; median age, 28 years) who underwent orthognathic surgery. Standardized pre- and postoperative lateral cephalometric radiographs were analyzed using WebCeph 2.0.0 software. The evaluated parameters included the SNA angle (sella–nasion–point A, indicating maxillary position), SNB angle (sella–nasion–point B, indicating mandibular position), ANB angle (maxillo-mandibular relationship), Pog-N-Perp (distance from pogonion to the nasion-perpendicular line), U1–NA° (inclination of the upper incisor relative to the maxillary base), L1–NB° (inclination of the lower incisor relative to the mandibular base), nasolabial angle, and facial convexity. Statistical analyses included paired t-tests and correlation analysis. Results: Significant anterior repositioning of the maxilla was observed, with SNA increasing from 83.6° to 86.3° (p = 0.019). The SNB angle remained stable, while ANB increased toward normalized sagittal relationships (0.9° to 3.0°, p = 0.060). Soft tissue analysis revealed a slight increase in the nasolabial angle (102° to 105°) and improved facial convexity. Strong correlations were found between skeletal parameters (SNB and ANB, r = −0.852, p < 0.001) and between skeletal and dental variables (ANB and L1–NB°, r = 0.652, p < 0.001), confirming coordinated skeletal–soft tissue adaptation. Conclusions: Orthognathic surgery significantly enhances skeletal balance and facial harmony, particularly through maxillary advancement. The integration of virtual surgical planning and interdisciplinary collaboration improves accuracy, predictability, and patient-centered outcomes in surgical orthodontics. Full article

The review “Symbolic Approaches for Explainable Artificial Intelligence” discusses the potential of symbolic AI to improve transparency, contrasting it with opaque deep learning systems. Though connectionist models perform well, their poor interpretability means that they are of concern for bias and trust in high-stakes fields such as healthcare and finance. The authors integrate symbolic AI methods—rule-based reasoning, ontologies, and expert systems—with neuro-symbolic integrations (e.g., DeepProbLog). This paper covers topics such as scalability and integrating knowledge, proposing solutions like dynamic ontologies. The survey concludes by advocating for hybrid AI approaches and interdisciplinary collaboration to reconcile technical innovation with ethical and regulatory demands. Full article