Search Results (6,651)

Background and Objectives: Chronic obstructive pulmonary disease (COPD) is a systemic condition in which muscle wasting, malnutrition, and altered fluid balance strongly influence prognosis. While spirometry remains essential for diagnosis and staging, it often fails to reflect the heterogeneity of outcomes. Multifrequency bioelectrical impedance analysis (MF-BIA) enables the assessment of body composition and fluid distribution, offering additional prognostic information. This systematic review aimed to evaluate the prognostic significance of MF-BIA in COPD, with emphasis on outcomes such as mortality, exacerbations, and hospital admissions. Materials and Methods: We systematically searched PubMed, Web of Science and Scopus from inception to 29 April 2025. The earliest record retrieved was published in 1996 but was excluded during screening. Studies including COPD patients in whom MF-BIA-derived parameters were related to clinical outcomes were eligible. Risk of bias was assessed using the Newcastle–Ottawa Scale. Data on design, population, methodology, and endpoints were extracted and narratively synthesized due to heterogeneity. The review protocol was not registered. Results: Eight studies were included. Phase angle (PhA) consistently showed prognostic value, being inversely related to mortality and rehospitalizations. Fat-free mass index (FFMI) was integrated into multidimensional models, but its independent role was inconsistent. Parameters describing fluid distribution, such as Extracellular Water/Total Body Water ratio, also appeared relevant, though interpretation was often limited by the absence of consistent consideration of underlying cardiac disease. Conclusions: MF-BIA provides useful prognostic insights in COPD patients, particularly through PhA. It may refine risk stratification beyond spirometry, yet further prospective studies with standardized methods are needed to confirm its independent value. Heterogeneity of methods and small sample sizes remain important limitations. Full article

Agriculture has been widely practiced for food production, yet food insecurity remains a critical issue, especially in Africa. Due to the significant role played by small-scale farmers, urban agriculture has been acknowledged as a viable strategy for reducing food insecurity in urban areas of Sub-Saharan Africa. This review analyzes urban household food insecurity factors through a systematic literature approach, retrieving data from various online databases. These databases include ScienceDirect, Wiley Online Library, Web of Science, UNIZULU online library, and PubAg. The search process involved the use of keywords to obtain relevant information along with the application of filters such as geographic location, publication period, language, article type, and accessibility. A total of 37 articles was included in this review after the application of the review eligibility criteria. This was achieved following PRISMA guidelines. Findings reveal a growing trend in the publication of articles on urban farming and an increasing acknowledgment of its importance by high-impact journals. It also shows various factors that determine household food insecurity, categorized as socioeconomic (11), institutional (5), and environmental factors (2). This led to the recommendation that urban government structures including policy makers and stakeholders should support food production and ensure an efficient urban food supply system. Full article

Background/Objectives: With global population aging, long-term care (LTC) facilities play an essential role in supporting older adults. However, residents are vulnerable to dignity loss in these institutional settings. Understanding dignity from the perspectives of residents, staff, and relatives is critical for informing person-centered care and policy. This review aimed to synthesize qualitative evidence on dignity in LTC facilities across multiple stakeholders. Methods: Following the PRISMA guidelines, we systematically searched six databases (PubMed, Scopus, Web of Science, Wan Fang, VIP, and CNKI) for qualitative studies published in 2010–2023. Eligible studies explored experiences of dignity among older LTC residents, staff, or relatives. Methodological quality was appraised using the Critical Appraisal Skills Programme (CASP) checklist. Data were analysed through thematic synthesis, and findings were compared across stakeholder groups. Results: A total of 1948 records were identified, of which 27 qualitative studies met the inclusion criteria. Two themes emerged from residents’ perspectives: institutionalization and resilience in preserving dignity. From staff perspectives, three themes were identified: understaffing and workload pressures, general approaches to dignity care, and person-centered care. Relatives’ accounts highlighted two themes: uneasiness regarding indignity and ethical expectations in a caring culture. Integrating these perspectives, we propose a triangular model in which residents, staff, and relatives collaboratively sustain dignity. Conclusions: Older adults’ dignity in LTC is shaped by complex interactions among institutional conditions, caregiving practices, and family involvement. Enhancing dignity requires adequate staffing, structural support for person-centered care, and greater involvement of relatives in decision-making. The proposed triangular model offers a framework for guiding interventions, staff training, and policy reforms aimed at safeguarding dignity in LTC facilities. Full article

Non-suicidal self-injury (NSSI) has become an increasingly salient mental health concern among adolescents, and it commonly co-occurs with depression, anxiety, borderline personality disorder, substance use, and childhood maltreatment, forming a complex psychological risk structure. Despite a growing body of literature, a systematic understanding of the structural links between NSSI and psychiatric comorbidities remains limited. This study uses bibliometric and visualization methods to map the developmental trajectory and knowledge structure of the field and to identify research hotspots and frontiers. Drawing on the Web of Science Core Collection, we screened 1562 papers published between 2005 and 2024 on adolescent NSSI and comorbid psychological problems. Using CiteSpace 6.3.R1, VOSviewer 1.6.20, and R 4.3.3, we constructed knowledge graphs from keyword co-occurrence, clustering, burst-term detection, and co-citation analyses. The results show an explosive growth of research in recent years. Hotspots center on comorbidity mechanisms of mood disorders, the impact of childhood trauma, and advances in dynamic assessment. Research has evolved from describing behavioral features toward integrative mechanisms, with five current emphases: risk factor modeling, diagnostic standard optimization, cultural sensitivity, stratified intervention strategies, and psychological risks in special populations. With big data and AI applications, the field is moving toward dynamic prediction and precision intervention. Future work should strengthen cross-cultural comparisons, refine comorbidity network theory, and develop biomarker-informed differentiated interventions to advance both theory and clinical practice. Full article

Electoral abstention has emerged as a critical challenge to democratic legitimacy, with rising rates observed globally. For example, in Portugal, the turnout declined from 91.5% in 1975 to 51.4% in 2022. This systematic review synthesizes multidisciplinary literature to identify key determinants of voter nonparticipation and their interactions, aiming to inform adaptive strategies to enhance civic engagement amid social, organizational, and technological changes. Following PRISMA guidelines, we searched five databases (Academic Search Complete, MEDLINE, Psychology and Behavioral Sciences Collection, PsycINFO, and Web of Science) from 2000 to August 2025 using terms such as “electoral abstention” and “non-voting.” Inclusion criteria prioritized quantitative empirical studies in peer-reviewed journals in English, Portuguese, Spanish, or French, yielding 23 high-quality studies (assessed via MMAT, with scores ≥ 60%) from 13 countries, predominantly the USA and France. Results reveal abstention as a multidimensional phenomenon driven by three interconnected categories: individual factors (e.g., health issues like smoking and mental health trajectories, institutional distrust); institutional factors (e.g., electoral reforms such as biometric registration reducing abstention by up to 50% in local contexts, but with mixed outcomes in voluntary voting systems); and contextual factors (e.g., economic inequalities and urbanization correlating with lower turnout, exacerbated by events like COVID-19). This review underscores the need for integrated public policies addressing these factors to boost participation, particularly among youth and marginalized groups. By framing abstention as an adaptive response to contemporary challenges, this work contributes to the political psychology and democratic reform literature, advocating interdisciplinary approaches to resilient electoral systems. Full article

The aim of the study was to identify doctoral and postdoctoral dissertations that were created between 2003 and 2023 and based on tourism research, and the promotion procedures were conducted within the discipline of ‘Physical Culture Sciences’ (PCS). An attempt was made to identify the connections between such theses and other fields/disciplines of science and the methodological approaches used in them. The conducted research was empirical in nature, and its result is the opinions of the authors of 119 doctoral theses and 42 postdoctoral dissertations addressing tourism issues on the scientific disciplines within which these works were located. An attempt was also made to estimate the contribution that PCS had in their creation. The research results revealed strong connections between ‘tourism’ Ph.D. and postdoctoral theses completed in the PCS discipline, especially with the fields of ‘Social Sciences’ and ‘Humanities’. The results also allowed for determining and performing multi-aspect analyses regarding the methodological profiles of the examined works, visualising such profiles in the form of radar charts, which included information on their 16 most important methodological features. In the research, it was shown that doctoral and postdoctoral dissertations devoted to tourism issues completed within the discipline of PCS are characterised by great diversity concerning the applied methodological approaches. They are largely multi-/inter-disciplinary in nature, and the doctoral theses are dominated by empirical methods focused on cultural research. At the same time, these profiles are strongly diversified depending on the other field of science to which the works formally assigned to the PCS are related. The research results presented in this article suggest that typical bibliometric analyses regarding the disciplinary structure of advance tourism research fail to capture the diversity and methodological specificity of research conducted within various scientific disciplines. This necessitates further research, particularly empirical studies identifying their methodological profiles and demonstrating their differences. These studies can be a valuable source of information not only for methodological refinement and improving the quality of tourism research, but may also provide a basis for discussion on the placement of PCS in the classification of sciences and the role that tourism research should play within this discipline. Full article

Plasma surface modification has emerged as a powerful, versatile tool for tailoring the surface properties of biomedical devices and implants without altering the material characteristics in the bulk. This comprehensive review critically examines the current state-of-the-art in plasma-based surface engineering techniques, with a focus on enhancing biocompatibility, bio-functionality, and long-term performance of medical implants. The article systematically explores various plasma processes and their roles in modifying surface chemistry, topography, energy, and wettability. These alterations directly influence protein adsorption, cell adhesion, antibacterial activity, and corrosion resistance, all of which are crucial for successful clinical integration. Special emphasis is placed on the plasma treatment of metallic (e.g., titanium, stainless steel), polymeric (e.g., polytetrafluoroethylene, polyetheretherketone), and composite substrates commonly used in dental, orthopedic, and cardiovascular applications. This review also highlights synergistic strategies, such as plasma-assisted grafting of bioactive molecules and nanostructuring, that enable multifunctional surfaces capable of promoting osseointegration, mitigating inflammation, and preventing biofilm formation. Emerging trends such as atmospheric cold plasmas and the integration of plasma technology with additive manufacturing are outlined as promising future directions. By synthesizing insights from surface science, materials engineering, and biomedical research, this review provides a foundational framework to guide future innovations in plasma-treated biomaterials. It aims to inform both academic researchers and medical device developers seeking to optimize implant–tissue interactions and achieve improved clinical outcomes. Full article

Introduction: Aesthetic surgery addresses subjective desires for morphological enhancement and differs from reconstructive surgery due to its elective, non-therapeutic nature. This distinction introduces complex medico-legal challenges, particularly concerning informed consent, patient expectations, and the legal evaluation of aesthetic damage. Materials and Methods: A narrative review was conducted using national legislation, Italian and international clinical guidelines, peer-reviewed literature from PubMed, Scopus, and Web of Science, and Italian Supreme Court rulings. Eight commonly litigated aesthetic procedures were analyzed in terms of clinical indications, public reimbursement criteria, and medico-legal risk. Results: Findings revealed significant variability in medico-legal exposure among procedures. Fully elective interventions such as liposuction and breast augmentation carried the highest litigation risk. Common legal claims included inadequate informed consent, poor psychological assessment, and mismatched expectations. The review emphasizes the need for personalized consent processes and comprehensive preoperative evaluations. Discussion: Italian case law increasingly adopts a “mixed obligation” model for aesthetic surgery, requiring not only technical skill but also a prognostic and relational evaluation of the intervention. Informed consent must be detailed, individualized, and well-documented, as it holds greater legal weight than in therapeutic procedures. Predictive medico-legal tools such as psychological profiling and structured consent protocols are essential for risk mitigation. Conclusions: Modern aesthetic surgery requires a redefined approach to damage assessment that incorporates psychological, relational, and identity factors. In both clinical and surgical practice, an approach tailored to the patient’s psychological profile must be increasingly taken into consideration, both when proposing and carrying out treatments and in medical-legal assessments. A legally and ethically sound practice depends on transparency, documentation, and patient-centered care, especially in the absence of therapeutic indications. Full article

The rapid proliferation of multimodal misinformation across diverse news categories poses unprecedented challenges to digital ecosystems, where existing detection systems exhibit critical limitations in domain adaptation and fairness. Current methods suffer from two fundamental flaws: (1) severe performance variance (>35% accuracy drop in education/science categories) due to category-specific semantic shifts; (2) systemic real/fake detection bias causing up to 68.3% false positives in legitimate content—risking suppression of factual reporting especially in high-stakes domains like public health discourse. To address these dual challenges, this paper proposes the DATTAMM (Domain-Adaptive Tensorized Multimodal Model), a novel framework integrating category-aware attention mechanisms and adversarial debiasing modules. Our approach dynamically aligns textual–visual features while suppressing domain-irrelevant noise through the following: (a) semantic disentanglement layers extracting category-invariant patterns; (b) cross-modal verification units resolving inter-modal conflicts; (c) real/fake gradient alignment regularizers. Extensive experiments on nine news categories demonstrate that the DATTAMM achieves an average F1-score of 0.854, outperforming state-of-the-art baselines by 32.7%. The model maintains consistent performance with less than 5.4% variance across categories, significantly reducing accuracy drops in education and science content where baselines degrade by over 35%. Crucially, the DATTAMM narrows the real/fake F1 gap to merely 0.017, compared to 0.243–0.547 in baseline models, while cutting false positives in high-stakes domains like health news to 5.8% versus the 38.2% baseline average. These advances lower societal costs of misclassification by 79.7%, establishing a new paradigm for robust and equitable misinformation detection in evolving information ecosystems. Full article

Rankings drive consequential decisions in science, sports, medicine, and business. Conventional evaluation methods typically analyze rank concordance, dispersion, and extremeness in isolation, inviting biased inference when these properties co-move. We introduce the Concordance–Dispersion–Extremeness Framework (CDEF), a copula-based audit that treats dependence among these properties as the object of interest. The CDEF automatically detects forced versus non-forced ranking regimes, then screens dispersion mechanics via ${\chi }^2$ tests that distinguish independent multinomial structures from without-replacement structures and, for forced dependent data, compares Mallows structures against appropriate baselines. The framework estimates upper-tail agreement between raters by fitting pairwise Gumbel copulas to mid-rank pseudo-observations, summarizing tail co-movement alongside Kendall’s W and mutual information, then reports likelihood-based summaries and decision rules that distinguish genuine from phantom agreement. Applied to pre-season college football rankings, the CDEF reinterprets apparently high concordance by revealing heterogeneity in pairwise tail dependence and dispersion patterns that inflate agreement under univariate analyses. In simulation, traditional Kendall’s W fails to distinguish scenarios, whereas the CDEF clearly separates Phantom from Genuine and Clustered agreement settings, clarifying when agreement stems from shared tail dependence rather than stable consensus. Rather than claiming probabilities from a monolithic trivariate model, the CDEF provides a transparent, regime-aware diagnosis that improves reliability assessment, surfaces bias, and supports sound decisions in settings where rankings carry real stakes. Full article

Background/Objectives: The global aging population faces rising rates of cognitive decline and neurodegenerative disorders. This review explores how physical exercise influences brain health in aging, focusing on mechanisms, moderators, and personalized strategies to enhance cognitive resilience. Methods: A narrative review methodology was applied. Literature published between 2015 and 2025 was retrieved from PubMed, Scopus, and Web of Science using keywords and MeSH terms related to exercise, cognition, neuroplasticity, aging, and dementia. Inclusion criteria targeted peer-reviewed original studies in humans aged ≥60 years or aged animal models, examining exercise-induced cognitive or neurobiological outcomes. Results: Evidence shows that regular physical activity improves executive function, memory, and processing speed in older adults, including those with mild impairment or genetic risk (e.g., APOE ε4). Exercise promotes neuroplasticity through increased levels of BDNF, IGF-1, and irisin, and enhances brain structure and functional connectivity. It also improves glymphatic clearance and modulates inflammation and circadian rhythms. Myokines act as messengers between muscle and brain, mediating many of these effects. Cognitive benefits vary with exercise type, intensity, and individual factors such as age, sex, chronotype, and baseline fitness. Combined interventions—physical, cognitive, nutritional—show synergistic outcomes. Digital tools (e.g., tele-exercise, gamification) offer scalable ways to sustain engagement and cognitive function. Conclusions: Physical exercise is a key non-pharmacological strategy to support cognitive health in aging. It acts through diverse systemic, molecular, and neurofunctional pathways. Tailored exercise programs, informed by individual profiles and emerging technologies, hold promise for delaying or preventing cognitive decline. Full article

Background and Aim: Natural hazard-related disasters such as wildfires, hurricanes, earthquakes, and floods pose significant risks to older adults, individuals with disabilities, and those with chronic health conditions. Transportation-related challenges during and after evacuation can severely impact their safety, mobility, and recovery. This scoping review examines the current evidence to identify research gaps and inform strategies to improve evacuation outcomes and long-term resilience for these at-risk groups. The STEPS framework (Spatial, Temporal, Economic, Physiological, Social) was applied to guide the analysis and interpretation of findings. Methods: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines and searched five databases, including PubMed, APA PsycINFO, CINAHL Complete, EMBASE, and Web of Science for primary studies on transportation and disaster evacuation among vulnerable populations. Results: Twenty studies were included. Four key areas of concern were identified: (1) immediate transportation barriers during evacuation, (2) prolonged transportation disruptions post-disaster, (3) anticipated logistical challenges in future evacuation planning, and (4) inconsistent and inaccessible communication of transportation-related information during emergencies. These challenges intersected with all five STEPS dimensions. Conclusions: Transportation barriers remain a persistent and under-addressed risk factor in disaster contexts for vulnerable groups. The STEPS framework helped reveal the multidimensional nature of these issues, emphasizing the need for integrated planning, assistive transport options, inclusive communication systems, and stronger public–private coordination. Future research should focus on collecting disaggregated data, evaluating interventions, and supporting inclusive policy reforms tailored to each type of disaster. Full article

Modeling loss data is a crucial aspect of actuarial science. In the insurance industry, small claims occur frequently, while large claims are rare. Traditional heavy-tail distributions, such as Weibull, Log-Normal, and Inverse Gaussian distributions, are not suitable for describing insurance data, which often exhibit skewness and fat tails. The literature has explored classical and Bayesian inference methods for the parameters of composite distributions, such as the Exponential–Pareto, Weibull–Pareto, and Inverse Gamma–Pareto distributions. These models effectively separate small to moderate losses from significant losses using a threshold parameter. This research aims to introduce a new composite distribution, the Gamma–Pareto distribution with two parameters, and employ a numerical computational approach to find the maximum likelihood estimates (MLEs) of its parameters. A novel computational approach for a nonlinear regression model where the loss variable is distributed as the Gamma–Pareto and depends on multiple covariates is proposed. The maximum likelihood (ML) and Approximate Bayesian Computation (ABC) methods are used to estimate the regression parameters. The Fisher information matrix, along with a multivariate normal distribution as the prior distribution, is utilized through the ABC method. Simulation studies indicate that the ABC method outperforms the ML method in terms of accuracy. Full article

This study conducts a bibliometric analysis of the scientific literature on digital, automated, and AI-assisted accounting systems. The data include documents listed in the Web of Science and Scopus databases. The analysis identifies the main authors, countries/territories, sources, and thematic trends. The results reveal that the scientific output within this research field has increased since 2018, emphasising the integration of artificial intelligence (AI), robotic process automation, and blockchain technologies in accounting. The findings also suggest that automation enhances efficiency, accuracy, and reliability while also raising concerns about ethics, cybersecurity, and job displacement. This study evaluates the accounting research from early discussions on information systems and automation to current topics such as digital transformation, sustainability, and intelligent decision-making. Furthermore, it contributes to the understanding of the scientific development of digital accounting and addresses future research directions involving AI and machine learning for predictive analytics and fraud detection, blockchain for secure and transparent accounting systems, sustainability through the integration of ESG reporting, and interdisciplinary collaboration between accounting, computer science, and business management to develop intelligent financial systems. The findings provide insights for academics and practitioners aiming to understand the ongoing digital transformation of accounting systems. Full article

Marine spatial planning (MSP) has emerged as a fundamental process for achieving the balanced development of marine ecology, economy, and society. However, increasing conflicts among multiple marine uses, particularly between port development, industrial activities, fisheries, recreation, and ecological protection, highlight the pressing demand for robust and science-based planning tools. In this study, we propose an integrated analytical framework for multi-objective spatial suitability evaluation to optimize MSP. Using the coastal waters of Dalian, China, as a case study, we evaluated the spatial suitability of five key marine activities (ecological protection, mariculture, port construction, wind energy farm development, and coastal tourism) and applied a multi-criteria decision-making approach to inform spatial zoning. The results emphasize the region’s ecological significance as providing critical habitats and migratory corridors for protected and threatened species as well as fishery resources, while also revealing substantial spatial overlaps between conservation priorities and human activities, particularly in nearshore zones. The optimized zoning scheme classifies 22.0% of the coastal waters as Ecological Redline Zones, 32.4% as Ecological Control Zones, and 45.6% as Marine Exploitation Zones. This science-based spatial classification effectively reconciles ecological priorities with development needs, providing a spatially explicit and policy-relevant decision support tool for MSP. Full article