Search Results (34,922)

Adequate ventilation is essential for maintaining indoor environmental quality in schools, where ventilation standards are often based on an indoor concentration of human-generated carbon dioxide (CO₂) above ambient levels. Low-cost non-dispersive infrared (NDIR) CO₂ sensors offer a practical solution for ventilation monitoring, yet variability between sensors can compromise accuracy, particularly when applications depend on the determination of precise concentration differences. This study evaluates the performance of twenty-three low-cost CO₂ sensors, developing normalisation functions to improve comparability across sensors, introducing an accessible methodology for on-site sensor calibration without the need for laboratory-grade reference equipment. The sensors were co-located for three independent test periods in 2025 representing typical school internal conditions in Ireland. Pre-normalisation analysis showed strong linearity (coefficient of determination (R²) = 0.999) but notable variability, with a mean root mean square error (RMSE) of 18.3 ppm and 0.45% of measurements outside manufacturers stated accuracy. Normalisation models were trained and validated using a leave-one-period-out approach. Regression-based correction yielded the greatest improvement, reducing RMSE by 16%. When applied to the full dataset, final correction factors reduced RMSE by 27%, out-of-range measurements by 43%, and proportional bias by 31%. Corrected sensors demonstrated highly consistent performance, particularly within the CO₂ ranges most relevant for classroom ventilation assessment, with an RMSE = 7.4 parts per million (ppm) at ambient concentrations and 11.9 ppm at concentrations below 1500 ppm. Field-based co-location in the deployment environment across full CO₂ cycles, combined with a network-derived global reference, produced effective correction factors. Performance declined marginally above 1500 ppm and during dynamic occupancy, while overall accuracy remained strong. The study presents a practical and accessible methodology for evaluating and normalising low-cost CO₂ sensors without specialised laboratory equipment, supporting reliable ventilation assessments in schools. Full article

Background/Objectives: Socioeconomic status (SES) and health insurance are critical determinants of chronic disease outcomes. This study evaluates their impact on the hypertension and diabetes “care cascade” (diagnosis, treatment, and control) across three distinct health systems: China, the United States (US), and the United Kingdom (UK). Methods: We analyzed cross-sectional data from pooled survey waves of the China Health and Retirement Longitudinal Study (CHARLS), the US National Health and Nutrition Examination Survey (NHANES), and the English Longitudinal Study of Ageing (ELSA). The final analytic sample comprised a total of 46,054 participants with hypertension and 11,805 with diabetes. Logistic regression model was employed to estimate the associations of education, wealth, and health insurance with disease management outcomes. Results: Significant cross-national heterogeneity was observed. China exhibited the steepest attrition in the care cascade, with disparities strongly linked to insurance fragmentation; notably, Urban Employee Insurance was associated with significantly better outcomes compared to the Rural Cooperative Medical Scheme. In the US, health insurance was strongly associated with diagnosis and treatment initiation but showed attenuated associations with disease control, suggesting that financial barriers (“underinsurance”) may persist. The UK demonstrated the highest equity in access due to universal National Health Service coverage, though education remained a predictor for diabetes identification; moreover, a persistent wealth-based gradient in disease control remained despite universal access. Conclusions: Universal health coverage effectively mitigates access barriers but does not eliminate inequalities driven by cumulative socioeconomic disadvantage. Achieving equity requires context-specific strategies: reducing insurance fragmentation in China, minimizing out-of-pocket costs in the US, and addressing upstream social determinants in the UK. Full article

Implementing effective geospatial data discovery mechanisms in geoportals is crucial for facilitating easy access to geospatial data and services. Despite existing efforts to formulate geoportal design requirements, understanding end-user issues beyond a single geoportal in the context of geodata discovery is still lacking. To address this gap, this study reports on a usability study conducted in Germany and Namibia, with the aim of examining issues faced by users during geodata search and discovery. The study employed a mixed-method approach combining Retrospective Think-Aloud (RTA) interviews and structured questionnaires. The results reveal key usability issues, including inefficient search mechanisms, inefficient presentation of search results, lack of user guidance, inefficient map interactions, and inefficient metadata descriptions. Additionally, the study revealed a difference in user perceptions regarding user experience aspects between the two user groups. The findings are of interest to the designers of geoportals in the context of open data reuse and spatial data infrastructure. Full article

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and promoting economic development. Existing studies are inadequate for accurately evaluating the efficiency of an urban public health surveillance system from a comprehensive perspective. In this work, an integrated framework was proposed for the evaluation of the spatial allocation efficiency of urban public health surveillance. This integrated approach incorporates three key aspects, spatial coverage, overlap, and accessibility, enabling a measurable evaluation of the overall spatial allocation efficiency. We utilized the proposed method to investigate the placement efficiency of the nucleic acid testing sites during the epidemic in Nanchang, China. The findings showed that using the integrated evaluation method based on coverage, overlap, and accessibility provides a more accurate reflection of the efficiency of existing site placements. It offers a flexible measurement system for evaluating urban surveillance site allocation strategies. This study introduces a novel perspective for the efficiency assessment of public health surveillance site placements, contributes to the development of public health emergency response systems, and provides a technical foundation for future contingency planning in public health surveillance. Full article

Background/Objectives: D-dimer, a fibrin degradation product, is associated with tumor growth and metastasis. In breast cancer, high concentrations of D-dimer are linked to more advanced disease stages and metastatic spread. This research aimed to examine the relevance of D-dimer levels in estrogen and progesterone hormone receptor (HR)-positive breast cancer. Methods: This retrospective single-center cohort study included patients with HR-positive breast carcinoma who underwent adjuvant or palliative radiotherapy in Türkiye. Pre- and post-radiotherapy blood test results, including D-dimer levels, were required. D-dimer, lymphocyte percentage, and interleukin-6 levels were measured for evaluation. All statistical analyses were performed using R software (version 4.4.2) to evaluate associations between D-dimer levels and other laboratory parameters. Univariate and multivariate Cox proportional hazards regression were performed to identify prognostic factors for progression-free survival (PFS) and overall survival (OS). Statistical significance was defined as p < 0.05. Results: Elevated D-dimer levels were associated with worse Eastern Cooperative Oncology Group performance status, advanced disease stages, metastasis, elevated IL-6 and CRP levels, and lower lymphocyte counts. Pre-RT D-dimer was a strong prognostic factor. Patients with D-dimer ≤ 0.3 µg/mL showed significantly superior OS and PFS (>60 months; p < 0.001), with only one event, and this remained significant in multivariate analysis (OS: HR 4.55, 95% CI 1.89–11.3; p = 0.002; PFS: HR 3.43, 95% CI 1.54–7.8; p = 0.004). Similarly, D-dimer ≤ 0.5 µg/mL was associated with improved OS (4/72 vs. 19/40 events; p < 0.001) and longer PFS, confirmed in multivariate analysis (OS: HR 4.37, 95% CI 1.72–9.86; p = 0.002; PFS: HR 3.88, 95% CI 1.67–9.1; p = 0.003), whereas levels > 0.5 µg/mL predicted worse outcomes. Using a 0.65 µg/mL cutoff, patients with D-dimer > 0.65 µg/mL had significantly shorter OS (median 25.5 months; 95% CI, 18–NA) compared with those ≤0.65 µg/mL (median not reached; p < 0.001), and this remained independently significant (OS: HR 5.10, 95% CI 1.9–13.6; p < 0.001; PFS: HR 4.68, 95% CI 1.83–11.9; p = 0.002). Conclusions: D-dimer is an accessible, non-invasive biomarker with predictive and prognostic significance in HR-positive breast cancer. Elevated D-dimer levels are suggestive of a more aggressive disease and poorer survival outcomes. This has the potential to facilitate early assessment of treatment efficacy and disease progression. This study has several limitations. Its retrospective, single-center design may introduce selection bias and limit generalizability. Although the sample size was sufficient to detect significant associations, validation in larger, multi-center cohorts is warranted to confirm the prognostic value of D-dimer. Full article

Sugar beet (Beta vulgaris L.) is an economically important crop that accounts for approximately 20% of global sugar production. The success of future breeding programs depends on the effective utilization of existing genetic resources. The aim of this study was to assess the genetic diversity and population structure of 192 sugar beet (Beta vulgaris L.) genotypes, including commercial cultivars and accessions obtained from the USDA gene bank, using SCoT and ISSR molecular markers, and to identify potential genetic resources for sugar beet breeding programs. In this study, a total of 192 sugar beet genotypes, including 187 accessions from the USDA (U.S. Department of Agriculture) gene bank and 5 commercial cultivars, were evaluated for genetic diversity using Start Codon Targeted (SCoT) and Inter Simple Sequence Repeat (ISSR) markers. A total of 68 scorable bands were obtained from five SCoT and three ISSR primers, and all bands were found to be polymorphic (100% polymorphism). Parameters such as polymorphic information content (PIC), Nei’s genetic diversity, and Shannon’s index indicated a high level of variation within the gene pool, with SCoT markers being more informative than ISSR markers. Dendrogram analyses based on Nei’s genetic distance revealed that the populations were separated into two main groups, while the sub-clusterings contained broad genetic variation. STRUCTURE analysis identified four (K = 4) populations for the SCoT data and three (K = 3) populations for the ISSR data; the inclusion of a high number of individuals in the admixture population indicated extensive gene flow. Principal component analysis (PCA) revealed both homogeneous groups and differentiated genotypes contributing to within-population diversity. The results demonstrate that the combined use of SCoT and ISSR markers provides powerful and complementary tools for assessing genetic diversity in sugar beet. The findings provide a solid scientific basis for the development of new, high-yielding and high-quality sugar beet cultivars as well as for the conservation of existing genetic resources. Molecular data constitute an important reference for guiding sugar beet breeding programs and for the effective utilization of genetic resources. Full article

Background: With population aging and the increasing incidence of pancreatic and periampullary malignancies, more elderly patients are being considered for pancreaticoduodenectomy (PD). Although robotic pancreaticoduodenectomy (RPD) is steadily adopted, evidence regarding its safety in patients aged ≥ 75 years remains limited, particularly in centers with restricted access to robotic platforms. Materials and Methods: We conducted a retrospective single-center study including patients who underwent PD between January 2019 and September 2025. Outcomes after RPD were compared between patients aged < 75 and ≥75 years. In addition, elderly patients undergoing RPD were compared with elderly patients undergoing open pancreaticoduodenectomy (OPD) using 1:2 propensity score matching. The primary endpoint was major postoperative morbidity (Clavien–Dindo grade ≥ III). Results: Among 525 PDs, 130 (25%) were performed robotically, including 29 patients aged ≥ 75 years. Within the RPD cohort, age ≥ 75 years was not associated with an increased risk of major complications compared with younger patients (OR 0.68, 95% CI 0.23–1.76; p = 0.45), nor with higher 90-day mortality. In the propensity score-matched elderly cohort, major morbidity was similar between RPD and OPD (10% vs. 7%; p = 0.68). RPD was associated with a significantly lower 30-day readmission rate, despite a higher incidence of delayed gastric emptying, mainly driven by mild (grade A) cases. Conclusions: RPD appears to be safe in carefully selected patients aged ≥ 75 years, with morbidity and mortality comparable to those observed in younger RPD patients and in elderly patients undergoing open surgery. These findings support the selective use of RPD in elderly patients, even in centers with limited access to robotic platforms. Full article

Thyroid hormones profoundly modulate hepatic fatty acid and cholesterol synthesis and turnover. Although nonalcoholic fatty liver disease (NAFLD) shows epidemiological links to hypothyroidism, the genetic substrates of this relationship remain unresolved. Integrating large-scale genome-wide association studies with single-cell transcriptomics, spatial transcriptomics, and single-cell chromatin accessibility via state-of-the-art computational approaches, we interrogated the association between NAFLD and hypothyroidism across organ systems, cellular expression landscapes, and molecular–genetic strata. We uncovered pronounced spatial specificity in genetic risk within the liver, prioritized hepatocytes as the principal shared cell type affected, and, leveraging spatial transcriptomics, advanced a dynamic spatiotemporal two-hit model. We further nominated MAGI3, RRNAD1, and PRCC as high-confidence candidate genes and pinpointed a key risk locus, rs926103. These findings deliver a dynamic, testable framework for the full pathophysiological continuum linking NAFLD and hypothyroidism and yield new targets and leads for precision intervention. Full article

Background/Objectives: Identification of tools to minimize opioid-related harms is critical in the U.S. The purpose of this study was to better understand community responder and healthcare provider perceptions and preferences regarding the design and function of a potential new opioid sensor device (OSD). Methods: Adults aged ≥ 18 years employed as community responders or healthcare providers in Alabama were recruited via email to participate in an anonymous online cross-sectional survey informed by the Unified Theory of Acceptance and Use of Technology (UTAUT). Primary outcomes were assessed via multiple-choice and 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree) and included the following topics: (1) past OSD utilization (4 items); (2) perceived importance of OSD design elements (15 items); (3) OSD function and cost preferences (3 items); and (4) UTAUT measures including perceived usefulness of OSDs (3 items), ease of use (4 items), social factors (4 items), resources (4 items), concerns (3 items), and intentions (3 items). Differences in UTAUT measures across professions were assessed via Mann–Whitney U tests, and predictors of OSD utilization intention were analyzed via multiple linear regression. Results: Respondents (N = 145) included pharmacists (40.0%), nurses (23.4%), physicians (14.5%), behavioral health (4.8%), social work (4.8%), and law enforcement (0.7%). Availability in hospital emergency departments was rated as the most important device element (mean [SD] score: 6.66 [0.80]), followed by sensitivity and specificity of the test (6.42 [0.98]), rapid detection time (6.42 [0.88]), ability to detect opioids in a broad range of substance (6.42 [0.93]), and availability in law enforcement offices (6.33 [1.08]). A 2–5 min detection time was rated as reasonable by 32.6% of respondents, with 53.0% preferring to pay <USD 15 per test. There were no statistically significant differences in UTAUT scale scores across professions. Perceived usefulness (β = 0.493; p < 0.001), social acceptance (β = 0.281; p = 0.023), and resource availability (β = 0.708; p = 0.002) were positive predictors and perceived ease of use was a negative predictor (β = −0.472; p = 0.007) of intention to use an OSD. Conclusions: Newly developed OSDs should consider prioritizing accessibility in hospital emergency departments and law enforcement offices, ability to detect a broad range of opioids, detection time between 2 and 5 min, and cost less than USD 15 per test. Future research may explore perspectives from a more diverse sample across multiple states and different professional roles. Full article

Financial fraud has expanded rapidly with the growth of the digital economy, evolving from conventional transactional misconduct to more complex and data-intensive forms. Traditional rule-based detection methods are increasingly inadequate for addressing the scale, heterogeneity, and dynamic behavior of modern fraud. In this context, artificial intelligence (AI) has become a core tool in financial fraud detection research. This review systematically surveys AI-based financial fraud detection studies published between 2015 and 2025. It summarizes representative machine learning and deep learning approaches, including tree-based models, neural networks, and graph-based methods, and examines their applications in major fraud scenarios such as credit card fraud, loan fraud, and anti-money laundering. In addition, emerging research on cryptocurrency- and blockchain-related fraud is reviewed, highlighting the distinct challenges posed by decentralized transaction environments. Through a comparative analysis of methods, datasets, and evaluation practices, this review identifies persistent issues in the literature, including severe class imbalance, concept drift, limited access to labeled data, and trade-offs between detection performance and interpretability. Based on these findings, the paper discusses practical considerations for applied fraud detection systems and outlines future research directions from a data-centric and application-oriented perspective. This review aims to provide a structured reference for researchers and practitioners working on real-world financial fraud detection problems. Full article

(1) Background: Large language models (LLMs) show promise in healthcare but are constrained by hallucinations, static knowledge, and limited domain specificity. Fine-tuning (FT) and retrieval-augmented generation (RAG) offer complementary solutions, with FT embedding domain reasoning and RAG enabling dynamic, up-to-date knowledge access. Hybrid FT + RAG frameworks have been proposed to improve factual accuracy and clinical reliability. This scoping review synthesizes current evidence on such hybrids in healthcare AI. (2) Methods: The search across PubMed, IEEE Xplore, Google Scholar, and Embase identified studies implementing explicit FT + RAG hybrids in healthcare or biomedical tasks. Eligible studies reported empirical evaluations of LLM performance or behavior. Data were extracted on base models, FT strategies, RAG architectures, applications, and performance outcomes. (3) Results: Seven studies met inclusion criteria. FT + RAG systems consistently outperformed FT-only or RAG-only approaches across QA, clinical summarization, report generation, and decision support tasks. Parameter-efficient FT methods (e.g., LoRA) were common, while RAG implementations varied (dense, hybrid, hierarchical, multimodal, federated). Reported benefits included improved accuracy, reduced hallucination, and greater clinician preference and feasibility in protected settings. (4) Conclusions: FT + RAG frameworks represent a promising direction for clinically grounded healthcare AI, combining domain-specific reasoning with transparent, up-to-date retrieval. Future work should prioritize standardized evaluation, workflow integration, and governance to enable safe deployment. Full article

Background: Language serves as a significant barrier to accessing dental services. Dental treatment options are often complex and involve terminology that is unfamiliar to most patients. In some cases, dental students may use technical terms that patients do not understand, leading to confusion and misunderstandings. Therefore, this study aimed to assess the language barriers faced by dental students and patients in Riyadh, Saudi Arabia. Methods: A mixed-methods research design was employed to evaluate language barriers between dental students and patients, as it provides an in-depth understanding and generates information beyond mere numerical data. The study was conducted from 1 September 2024, to 30 August 2025, in Riyadh, Saudi Arabia. Data collection primarily involved conducting interviews with focus group members using a comprehensive topic guide consisting of predetermined questions. Results: Forty dental students and forty patients agreed to participate in this study. The students encountered significant difficulty explaining terms such as crown lengthening (72.5%) and periodontitis (67.5%), while patients reported limited understanding of interim removable dental prosthesis (65%) and fixed dental prosthesis (60%). Comparative analysis indicated that sixth-year students reported significantly more difficulty explaining “crown lengthening” and “prefabricated post and core” compared to fifth-year students. It was also observed that patients’ educational level had a significant impact on their understanding of terms such as “interim dental prosthesis” and “removable dental prosthesis.” Qualitative analysis revealed patients’ partial understanding or misinterpretation of dental terminologies. Conclusions: Our findings indicate that language discordance, even among speakers of the same native language, can hinder effective communication, particularly when technical vocabulary is involved. Students may struggle to explain procedures in a manner that patients can easily understand. This can lead to incomplete patient comprehension and potential non-compliance with treatment recommendations. Hence, we recommend incorporating Arabic dental terminologies alongside English into the curriculum, developing bilingual glossaries, and using visual aids when communicating with patients. Full article

Mental health problems are increasing among young people in South Africa due to diverse determinants such as, poverty, social shame, and lack of proper access to health services. Although physical activity is a low-cost and non-medical way to help improve mental health, its effects in rural areas are still not clearly understood. A scoping review was carried out following the PRISMA-ScR guidelines. We systematically searched three online databases (PubMed, CINAHL, and Google Scholar) for studies published from 2014 through 2025. Studies met eligibility criteria if they targeted youth aged 14–35 years living in rural South Africa and reported on physical activity interventions designed for mental health. Two reviewers independently carried out data extraction and came up with the overall result. Overall, 42,384 records were identified, of which only 12 studies met all the specified criteria. The findings of the study were that participation in organised forms of physical activity (including school-based aerobic sessions, community-based walking groups, and charity training programmes) was associated with reductions in mental health issues. Even with these issues, the findings show that physical activity can be a useful, efficient, and practical way to support mental health among rural South African youth. To improve the evidence, strong trials, community-based plans, and sessions at schools and clinics are needed. In addition, policy cooperation across health, education, and sports sectors is essential for lasting impact. Full article

In high-density urban environments, residential design often faces a conflict between maximizing landscape access and maintaining energy-oriented compactness. This study proposes a target-based visibility analysis framework to optimize high-rise forms under strict performance constraints. Utilizing a Quad-mesh reconstruction strategy and Inverse Targeted Ray-Casting, the method accurately quantifies visibility via the cumulative Landscape Visible Surface (LVS) on the target building and Viewpoint-Specific Surface Visibility Rate (R_v) for precise verification against specific landscape targets. The framework is applied to evaluate three morphological prototypes: Compact Tower, Dispersed Tower, and Slab–Tower Hybrid. Quantitative simulations identified the Slab–Tower Hybrid as the optimal solution, demonstrating superior “Visual Morphological Efficiency.” While maintaining a moderate Shape Coefficient (SC = 0.326) to satisfy energy standards, the Hybrid achieved a cumulative Park-View LVS approximately 1.8 times that of the Compact Tower. Furthermore, environmental simulations indicated the Hybrid fosters stable wind environments (0.4–0.7 m/s) and equitable sunlight distribution. The research concluded that through differentiated massing, high-rise architecture can achieve a synergistic balance between visual openness and physical compactness, transforming view analysis from a passive check into an active design driver. Full article

This study explored how the chemical composition and molecular structure of black rice influence its glycemic index (GI), as well as how different processing methods regulate these relationships. Eight black rice varieties were analyzed for their nutritional composition, physicochemical and rheological properties, and protein structural characteristics. Results showed that higher protein and lipid contents were associated with lower GI values, likely due to reduced starch accessibility and slower enzymatic digestion. Varieties with more ordered protein conformations and stronger molecular interactions exhibited lower GI, indicating that protein structural organization plays an important role in starch digestibility. Among the tested varieties, “Huamoxiang” showed the highest GI (68.40 ± 2.04), while “Yanghei No. 3” exhibited the lowest GI (49.27 ± 4.14). Low-GI varieties were further subjected to different processing treatments. Fermentation effectively reduced GI by 8.44% by limiting starch gelatinization and enzymatic susceptibility, while puffing maintained a low GI through molecular rearrangement of starch. In contrast, steaming disrupted ordered starch structures and significantly increased GI. Overall, these findings provide practical guidance for selecting black rice varieties and processing strategies to develop low-GI black rice products, supporting the design of functional foods and dietary management for glycemic control. Full article