Search Results (9,378)

Architectural design stands as a highly knowledge-intensive field, with designers serving as the linchpin for its premium development. China’s construction industry is now navigating a transitional phase of slower growth, where a misalignment in designer capabilities significantly obstructs the nation’s shift from being a mere “construction giant” to becoming a true “construction powerhouse”. Based on the spatial mismatch model and Geodetector, this study empirically analyzes the mismatch relationship among designers and its influencing factors using panel data from 31 provinces in China from 2013 to 2023, and proposes strategies for cultivating architectural design talents. Findings reveal that China’s architectural designers exhibit spatial supply imbalance, and complex trends in designer allocation-simultaneous growth and decline coexist. China exhibits diverse types of architect mismatch: 22.58% of regions are in a state of Positive Mismatch, and 12.90% experience Negative Mismatch. In over one-third of regions, the architectural design talent market can no longer self-correct architect mismatch through market mechanisms, urgently requiring collaborative intervention policies from governments, design associations, and enterprises to address architect supply–demand governance. For a smooth transition during the transformation and upgrading of the construction and design industries, the architectural design talent market should accommodate frictional designer mismatch. The contribution of designer mismatch varies significantly, with factors such as innovation, industrial structure, and fiscal self-sufficiency exerting more direct influence, while other factors play indirect roles through dual-factor enhancement effects and nonlinear enhancement effects. The insights from the analysis results and conclusions for future designer cultivation include fostering an interdisciplinary teaching model for designers through university–enterprise collaboration, enhancing education in AI and intelligent construction literacy, and establishing an intelligent service platform for designer supply–demand matching to promptly build a new differentiated and precise designer supply system. Full article

The Aubrac cattle breed, native to France and increasingly adopted in Eastern Europe, is known for producing tender, flavorful, and well-marbled beef. Despite its growing popularity, limited data exist on its nutritional profile and implications for human health. This study evaluates carcass traits and protein quality in the Longissimus dorsi muscle of male and female Aubrac cattle raised under semi-intensive systems. Special attention was given to essential and semi-essential amino acids, which exceeded FAO/WHO reference requirements by 60.25%, 97.43%, and 221.49% for children, youth individuals, and adults, respectively, confirming superior protein quality. The high amino acid concentration (up to 30.59 g/100 g protein) and biological value confirm superior protein quality. Furthermore, the fatty acid profile reveals a favorable balance between saturated and unsaturated fats, with oleic acid predominance and a moderate atherogenic index, suggesting cardiovascular benefits. These findings support classifying Aubrac beef as a functional protein source with potential health advantages, reinforcing its role in sustainable cattle production, dietary planning, and consumer education. This study provides insights into factors influencing beef quality, connecting cattle breed and production system with nutritional value and health benefits. Full article

In this study, we present a professional development programme for teachers launched to introduce Computer Science and Informatics (CSI) in primary education in Slovenia. The study aims to examine which CSI core concepts teachers most frequently choose to integrate into their lessons when given the freedom to select the topics within the framework, and to explore how students engage with and respond to these activities, as reported in teachers’ reflections. This study is based on reflective feedback from forty-seven teachers from seven primary schools who implemented interdisciplinary lessons that integrate CSI content into existing primary school curricula. Qualitative data from 152 reflections were used to support our research findings. The results show that teachers most frequently introduced the concepts from the content area of algorithms and programming. In contrast, content areas such as computing systems, networks and the internet, data and analysis, and impacts of computing received less attention. Teachers reported that students were motivated and engaged, although some challenges emerged, including difficulties in solving tasks or following instructions. As this pilot study reports on the first year of a two-year initiative, the findings provide preliminary insights into how a structured professional development programme for teachers can support interdisciplinary approaches in CSI education. Full article

Concerns over ground-mounted photovoltaics (PVs) on cropland have encouraged a shift toward rooftop PV systems on livestock and poultry farms. Using ex-post observational data and a doubly robust estimation approach, this study examines the determinants and economic effects of PV adoption among chicken farmers in Taiwan. Based on a population-wide agricultural census, we assess how socio-demographic factors, production practices, household composition, and electricity infrastructure influence adoption decisions. The results show that education level, household structure, and access to electricity are key drivers of adoption. PV adopters exhibit a 5.8% higher sales value of chicken products, mainly due to increased production volume rather than quality improvements. These findings highlight the potential dual benefits of integrating solar energy with poultry farming and provide policy-relevant insights for sustainable agricultural development. Full article

Teacher preparation programmes must now ensure instructional continuity and quality across face-to-face, online, and hybrid modes, even amid health, climate, or security crises. This mixed-methods study examined which principles policymakers and teacher education directors deem essential for such resilience, and how those principles align with prior research and leadership theory. Semi-structured elite interviews (N = 25) were analyzed inductively to surface field-driven themes and deductively through two models: the ten evidence-based training principles synthesized by Hadad et al. and the six capacities of Striepe and Cunningham’s Crises Leadership Framework (CLF). Results show strong consensus on theory–practice integration, university–school partnerships, and collaborative learning, mapping chiefly to the CLF capacities of adaptive roles and stakeholder collaboration. Directors added practice-oriented priorities—authentic field immersion, formative feedback, and inclusive pedagogy—extending the crisis care and contextual influence dimensions. By contrast, policymakers uniquely stressed policy–academic co-decision-making, reinforcing complex decision-making at the system level. Reflective thinking skills and digital pedagogy, though prominent in the literature, were under-represented, signalling implementation gaps. Overall, the integrated model offers a crisis-ready blueprint for curriculum design, partnership governance, and digital capacity-building that can sustain continuity and quality in pre-service teacher education. Full article

Background: Vitamin K antagonist oral anticoagulant (VKA) therapy, using warfarin or acenocoumarol in our health system, is indicated, according to clinical guidelines, for the prophylaxis of thromboembolic events. In Málaga, the VKA patient management program currently includes a total of 856 patients. Hypothesis: The use of an AI-based application can enhance treatment adherence among VKA patients participating in self-monitoring and self-management programs. Furthermore, it can support the comprehensive implementation of the system, leading to reduced costs and fewer interventions for anticoagulated patients. Methods: The study will be conducted in several phases. The first phase involves the development of the application and the integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The second phase includes preliminary testing and validation of the developed application. The third phase consists of full implementation, along with an assessment of user-identified needs and potential quality improvements. Expected Results: The implementation of the AIto-Control app is expected to reduce healthcare-related costs by decreasing primary care visits and hospital admissions due to thromboembolic or bleeding events. Additionally, it aims to ease the workload on both primary care and hospital services. These outcomes will be achieved through the involvement of advanced practice nurses who will supervise app-based monitoring and patient education. Full article

Legionella is an environmental bacterium capable of causing severe respiratory infections, with outbreaks posing significant public health challenges in developed countries. Understanding public awareness of Legionella transmission, risk perception, and preventive behaviors is crucial for reducing exposure and guiding health education strategies. This study aimed to evaluate the Portuguese population’s knowledge of Legionella infections and their readiness to adopt preventive measures. A structured questionnaire was developed and administered to 239 participants aged 18–76 years across Portugal, collecting socio-demographic data and assessing literacy through statements organized into domains related to Legionella risk, control measures, and public health impact. The results indicate that participants possess moderate to high awareness of Legionella severity, transmission routes, and preventive strategies, yet gaps remain in understanding key risk factors, optimal water system maintenance, and the influence of temperature on bacterial growth. Age, educational attainment, and occupational status were associated with differences in self-assessed literacy levels. Artificial neural network models were applied to classify literacy levels, achieving a near 90% accuracy and demonstrating higher confidence in low and moderate categories. These findings provide insights for designing tailored educational programs, improving public health communication, and enhancing preventive behaviors to reduce Legionella infection risks. Full article

In the context of China’s increasingly competitive agricultural product branding, authenticity has become a pivotal mechanism for shaping consumer trust and willingness to pay. This study takes Perceived Brand Authenticity (PBA) as its focal construct and builds a chained mediation framework incorporating experiential quality (EQ) and consumer trust. Employing a dual-evidence strategy that combines structural discovery and causal validation, the study integrates Jaccard similarity clustering and PLS-SEM to examine both behavioral patterns and psychological mechanisms. Drawing on 636 valid survey responses from across China, the results reveal clear segmentation in channel choice, certification concern, and premium acceptance by gender, age, income, and education. Younger and highly educated consumers rely more on e-commerce and digital traceability, while middle-aged, older, and higher-income groups emphasize geographical indications and organic certification. The empirical analysis confirms that PBA has a significant positive effect on EQ and consumer trust, and that the chained mediation pathway “PBA → EQ → Trust → Purchase Intention” robustly captures the transmission mechanism of authenticity. The findings demonstrate that verifiable and consistent authenticity signals not only shape cross-group consumption structures but also strengthen trust and repurchase intentions through enhanced experiential quality. The core contribution of this study lies in advancing an evidence-based framework for sustainable agricultural branding. Theoretically, it reconceptualizes authenticity as a measurable governance mechanism rather than a rhetorical construct. Methodologically, it introduces a dual-evidence approach integrating Jaccard clustering and PLS-SEM to bridge structural and causal analyses. Practically, it proposes two governance tools—“evidence density” and “experiential variance”—which translate authenticity into actionable levers for precision marketing, trust management, and policy regulation. Together, these insights offer a replicable model for authenticity governance and consumer trust building in sustainable agri-food systems. Full article

Background: Cardiovascular disease (CVD) is the leading global cause of death and is shaped by interacting biological, environmental, lifestyle, and social factors. Traditional models often treat risk factors in isolation and may miss dependencies among exposures and biomarkers. Objective: To map interdependencies among environmental, social, behavioral, and biological predictors of CVD risk using Bayesian network models. Methods: A cross-sectional analysis was conducted using NHANES 2017–2018 data. After complete-case procedures, the analytic sample included 601 adults and 22 variables: outcomes (systolic/diastolic blood pressure, total/LDL/HDL cholesterol, triglycerides) and predictors (BMI, C-reactive protein (CRP), allostatic load, Dietary Inflammatory Index, income, education, age, gender, race, smoking, alcohol, and serum lead, cadmium, mercury, and PFOA). Spearman’s correlations summarized pairwise associations. Bayesian networks were learned with two approaches: Grow–Shrink (constraint-based) and Hill-Climbing (score-based, Bayesian Gaussian equivalent score). Network size metrics included number of nodes, directed edges, average neighborhood size, and Markov blanket size. Results: Correlation screening reproduced expected patterns, including very high systolic–diastolic concordance (p ≈ 1.00), strong LDL–total cholesterol correlation (p = 0.90), inverse HDL–triglycerides association, and positive BMI–CRP association. The final Hill-Climbing network contained 22 nodes and 44 directed edges, with an average neighborhood size of ~4 and an average Markov blanket size of ~6.1, indicating multiple indirect dependencies. Across both learning algorithms, BMI, CRP, and allostatic load emerged as central nodes. Environmental toxicants (lead, cadmium, mercury, PFOS, PFOA) showed connections to sociodemographic variables (income, education, race) and to inflammatory and lipid markers, suggesting patterned exposure linked to socioeconomic position. Diet and stress measures were positioned upstream of blood pressure and triglycerides in the score-based model, consistent with stress-inflammation–metabolic pathways. Agreement across algorithms on key hubs (BMI, CRP, allostatic load) supported network robustness for central structures. Conclusions: Bayesian network modeling identified interconnected pathways linking obesity, systemic inflammation, chronic stress, and environmental toxicant burden with cardiovascular risk indicators. Findings are consistent with the view that biological dysregulation is linked with CVD and environmental or social stresses. Full article

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system that affects women more frequently than men. This sex gap has widened over the past century, and appears to be shaped by lifestyle factors more than biological factors. This narrative review examines the evidence for sex-specific differences in lifestyle risk factors and their impact on both MS susceptibility and disease progression, with implications for diagnosis, monitoring, and treatment. Smoking, obesity, vitamin D deficiency, ultraviolet radiation exposure, and Epstein–Barr virus infection all interact with sex-related biological pathways to influence MS risk. Women appear to be more vulnerable to the pathogenic effects of smoking and obesity, both independently and in synergy with genetic risk alleles, while vitamin D and UV exposure confer stronger protective effects in females than in males. EBV infection also exhibits sex-dependent immune responses, shaped by hormonal regulation and host–virus genetic interactions. Sex-related lifestyle factors also modulate MS progression. Women experience more inflammatory activity and relapses, whereas men more often develop a progressive phenotype with greater neurodegeneration. Hormonal changes during female reproductive phases, such as pregnancy, breastfeeding, menopause, and hormone-based therapies, critically influence disease activity and progression in MS. Obesity, smoking, vitamin D status, diet, and gut microbiota further interact with sex hormones and genetic background, contributing to variable disease trajectories, also modulated by social determinants such as education level. These findings underscore the need to integrate into clinical practice the evaluation of lifestyle factors in a sex-specific way for diagnosis, monitoring, and treatment of MS. Full article

Electoral abstention is a growing phenomenon in contemporary democracies, raising concerns about the representativeness and legitimacy of elected governments, particularly in Portugal where youth participation remains low. This study explores the heterogeneity of non-voting behavior by comparing insights from voters and non-voters through online focus groups. Employing content analysis on qualitative data from 42 participants, the research identifies distinct non-voter profiles, systemic barriers, and potential pathways to increased participation. Key findings reveal heterogeneous abstainer types—including disbelieving citizens, disinterested youth, pragmatic non-voters, and protest non-voters—driven by distrust, practical obstacles, and insufficient political literacy. Despite non-voting, many express conditional willingness to participate in high-stakes scenarios or following reforms. The study concludes that addressing these barriers requires holistic measures, such as enhanced civic education, technological voting modernization, and improved political representation, to foster trust and democratic engagement. These insights offer actionable recommendations for policymakers to enhance voter turnout and strengthen democratic legitimacy. Full article

Seafood plays a key role in a healthy diet due to its high content of essential nutrients. However, its global trade and complex supply chains expose it to frequent mislabeling and food fraud. This study investigates Italian consumers’ willingness to pay (WTP) for traceable seafood products, exploring how blockchain technology (BT) can enhance transparency and economic sustainability in the fish supply chain. An online questionnaire, administered in 2022 and 2024, gathered responses from a diverse demographic, focusing on four representative seafood species: farmed sea bass, striped venus clams, giant red shrimp, and albacore tuna. Results indicate that most respondents—primarily with higher education levels—value traceability and are willing to pay a premium for certified, traceable seafood. The study models the economic feasibility of implementing BT at both national and regional levels and finds that the consumer’s WTP exceeds the additional costs incurred by adopting BT. These findings support the viability of traceability systems in improving food safety and sustainability, while reinforcing consumer trust. The results also underscore the importance of providing clear information at the point of purchase, particularly regarding species, origin, and production methods—factors critical to informed seafood choices and advancing more sustainable consumer behavior in Italy. Full article

This study adopts a systems perspective to examine the persistent effects of China’s One-Child Policy (OCP) on the subjective well-being of older adults, emphasizing structural persistence, reinforcing feedback, and path-dependent lock-in in complex socio-technical systems. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS-2014), we exploit the OCP’s formal rollout at the end of 1979—operationalized with a 1980 cutoff—as a quasi-natural experiment. A Fuzzy Regression Discontinuity (FRD) design identifies the Local Average Treatment Effect of being an only-child parent on late-life well-being, mitigating endogeneity from selection and omitted variables. Theoretically, we integrate three lenses—policy durability and lock-in, intergenerational support, and life course dynamics—to construct a cross-level transmission framework: macro-institutional environments shape substitution capacity and constraint sets; meso-level family restructuring reconfigures support network topology and intergenerational resource flows; micro-level life-course processes accumulate policy-induced adaptations through education, savings, occupation, and residence choices, with effects materializing in old age. Empirically, we find that the OCP significantly reduces subjective well-being among the first generation of affected parents decades later (2SLS estimate ≈ −0.23 on a 1–5 scale). The effects are heterogeneous: rural residents experience large negative impacts, urban effects are muted; men are more adversely affected than women; and individuals without spouses exhibit greater declines than those with spouses. Design validity is supported by a discontinuous shift in fertility at the threshold, smooth density and covariate balance around the cutoff, bandwidth insensitivity, “donut” RD robustness, and a placebo test among ethnic minorities exempt from strict enforcement. These results demonstrate how demographic policies generate lasting impacts on elderly well-being through transforming intergenerational support systems. Policy implications include strengthening rural pension and healthcare systems, expanding community-based eldercare services for spouseless elderly, and developing complementary support programs. Full article

Background/Objectives: Ulcerative Colitis (UC) lacks longitudinal visual data, which limits both disease progression modeling and the effectiveness of computer-aided diagnosis systems. These systems are further constrained by sparse intermediate disease stages and the discrete nature of the Mayo Endoscopic Score (MES). Meanwhile, synthetic image generation has made significant advances. In this paper, we propose novel ordinal embedding architectures for conditional diffusion models to generate realistic UC progression sequences from cross-sectional endoscopic images. Methods: By adapting Stable Diffusion v1.4 with two specialized ordinal embeddings (Basic Ordinal Embedder using linear interpolation and Additive Ordinal Embedder modeling cumulative pathological features), our framework converts discrete MES categories into continuous progression representations. Results: The Additive Ordinal Embedder outperforms alternatives, achieving superior distributional alignment (CMMD 0.4137, recall 0.6331) and disease consistency comparable to real data (Quadratic Weighted Kappa 0.8425, UMAP Silhouette Score 0.0571). The generated sequences exhibit smooth transitions between severity levels while maintaining anatomical fidelity. Conclusions: This work establishes a foundation for transforming static medical datasets into dynamic progression models and demonstrates that ordinal-aware embeddings can effectively capture disease severity relationships, enabling synthesis of underrepresented intermediate stages. These advances support applications in medical education, diagnosis, and synthetic data generation. Full article

Introduction: Radon is a radioactive noble gas formed from uranium decay in the Earth’s crust. The most significant isotope, 222Rn, emits alpha particles capable of damaging lung tissue and inducing cancer. Radon exposure is affected by geophysical and building characteristics and is recognized as a Group 1 carcinogen by the IARC. Despite regulatory thresholds (e.g., EURATOM standards), health risks remain. Various mitigation methods aim to reduce indoor radon exposure and its impact. Materials and Methods: This systematic review followed PRISMA guidelines. PubMed, Scopus, and Web of Science were searched up to 28 February 2025, using a defined string. Studies with original data on radon exposure and lung cancer risk or mitigation efficacy were included. Independent screening and quality assessment (Newcastle–Ottawa Scale) were conducted by multiple reviewers. Results: Of the 457 studies identified, 14 met the inclusion criteria. Eleven of these investigated the link between indoor radon and lung cancer risk, and three evaluated mitigation strategies. Radon levels were commonly measured using passive alpha track detectors. Levels varied depending on geographical location, season, building design and ventilation, these were higher in rural homes and during the colder months. Case–control studies consistently found an increased lung cancer risk with elevated radon exposure, especially among smokers. Effective mitigation methods included sub-slab depressurisation and balanced ventilation systems, which significantly reduced indoor radon concentrations. Adenocarcinoma was the most common lung cancer subtype in non-smokers, whereas squamous and small cell carcinomas were more prevalent in smokers exposed to radon. Discussion and Conclusions: This review confirms the robust association between indoor radon exposure and lung cancer. Risks persist even below regulatory limits and are amplified by smoking. While mitigation techniques are effective, their application remains uneven across regions. Stronger public education, building codes, and targeted interventions are needed, particularly in high-risk areas. To inform future prevention and policy, further research should seek to clarify radon’s molecular role in lung carcinogenesis, especially among non-smokers. Full article