Search Results (169)

Background/Objectives: Patient trust and satisfaction are critical components of effective healthcare delivery, particularly within health welfare social cooperatives. This study investigates the impacts of administrative procedures, courtesy, physical accessibility, collaborative management, and community health relations on patient trust and satisfaction. Methods: Using Partial Least Squares Structural Equation Modeling (PLS-SEM), we analyzed survey data collected from 658 members of a health welfare social cooperative to assess the hypothesized relationships. Results: The findings reveal that administrative procedures significantly enhance trust but do not directly affect satisfaction. Courtesy and community health relations positively influence both trust and satisfaction. Physical accessibility, collaborative management, and trust also significantly enhance patient satisfaction. Conclusions: These results highlight the multifaceted nature of patient trust and satisfaction, emphasizing the importance of efficient administrative practices, respectful treatment, collaborative decision-making, and strong community engagement. For practitioners, the study underscores the need for a comprehensive approach to healthcare management that integrates operational efficiency with patient-centered care. Full article

Background/Objectives: Older adults with frailty are at-risk of worse outcomes following respiratory-viral-infections such as COVID-19. Data on effectiveness of vaccination/boosting in frail older adults during Omicron is lacking. Methods: National healthcare-claims data and COVID-19 registries were utilized to enroll a cohort of older Singaporeans (≥60 years) as of 1 January 2022, divided into low/intermediate/high-risk for frailty; matching weights were utilized to adjust for sociodemographic differences/vaccination uptake at enrolment across frailty categories. Competing-risk-regression (Fine-Gray) taking death as a competing risk, with matching weights applied, was utilized to compare risks of COVID-19-related hospitalizations and severe COVID-19 across frailty levels (low/intermediate/high-risk), with estimates stratified by booster status. Individuals were followed up until study end-date (20 December 2023). Results: 874,160 older adults were included during Omicron-predominant transmission; ~10% had intermediate/high-frailty-risk. Risk of hospitalization/severe COVID-19 was elevated in those with intermediate/high-frailty-risk up to XBB/JN.1 transmission. Boosting was associated with decreased risk of COVID-19-related hospitalization across all frailty categories in infection-naïve individuals. However, in infection-naïve older adults with high-frailty-risk, while receipt of first boosters was associated with lower risk of COVID-19-hospitalization/severe COVID-19, additional booster doses did not reduce risk. In reinfected older adults, first boosters were still associated with lower hospitalization risk (adjusted-hazards-ratio, aHR = 0.55, 95% CI = 0.33–0.92) among the non-frail, but not in the intermediate/high-frailty-risk minority. Conclusions: First boosters were associated with reduced adverse COVID-19 outcomes across all frailty categories in infection-naïve older adults during Omicron. However, in the high-frailty minority, boosting did not additionally reduce risk in reinfected individuals with hybrid immunity, and beyond the first booster for infection-naïve individuals. Full article

Transportation agencies often rely on manual surveys to monitor seat belt compliance; however, these methods are limited by surveyor fatigue, reduced visibility due to tinted windows or low lighting, and restricted geographic coverage, making manual surveys prone to errors and unrepresentative of the broader driving population. This paper presents an automated seat belt detection system leveraging the YOLO11 neural network on video footage captured by a tethered uncrewed aerial vehicle (UAV). The objectives are to (1) develop a robust system for detecting seat belt use at stop-controlled intersections, (2) evaluate factors affecting detection accuracy, and (3) demonstrate the potential of UAV-based compliance monitoring. The model was tested in real-world scenarios at a single-lane and a complex multi-lane stop-controlled intersection in Iowa. Three studies examined key factors influencing detection accuracy: (i) seat belt–shirt color contrast, (ii) sunlight direction, and (iii) vehicle type. System performance was compared against manual video review and large language model (LLM)-assisted analysis, with assessments focused on accuracy, resource requirements, and computational efficiency. The model achieved a mean average precision (mAP) of 0.902, maintained high accuracy across the three studies, and outperformed manual methods in reliability and efficiency while offering a scalable, cost-effective alternative to LLM-based solutions. Full article

While green infrastructure (GI) offers numerous benefits, its implementation in low-resource settings remains constrained by limited policy support and upfront costs, highlighting the need for context-sensitive strategies. This paper highlights the value of integrating GI within sustainable agricultural systems and the effectiveness of various GI techniques in improving soil microbial communities and reducing greenhouse gas emissions. The transition to sustainable agricultural systems requires innovative strategies that balance productivity, environmental conservation, and resilience to climate change. Sustainable agriculture increasingly leverages technological innovations in GI to enhance productivity, biodiversity, and microclimate resilience. Green infrastructure has found direct application in agroforestry, conservation buffers, precision agriculture, soil health monitoring systems, and nature-based solutions such as regenerative soil management. These applications are crucial in enhancing soil health, water retention, and biodiversity, while mitigating microclimatic impacts. Precision agriculture tools, like IoT sensors, drones, and AI-driven analytics, allow farmers to optimize water, nutrient, and pesticide use, boosting yields and efficiency while minimizing environmental impact. Simultaneously, advanced soil health monitoring technologies track soil moisture, nutrients, and biological activity in real time, informing practices that maintain long-term soil fertility and carbon sequestration. This integrated approach yields practical on-farm benefits, such as higher crop stability during droughts and enhanced habitats for beneficial species. In conclusion, there is a need for supportive frameworks, like subsidies for GI adoption, application of precision tools, incentives for improving soil microclimate, development of innovative GI programs, and knowledge-sharing initiatives, to encourage farmer adoption. Full article

Background: The aim of this study was to investigate the relationship between postprandial glycemic levels based on flashmonitoring and the production of intestinal hydrogen (H₂) and methane (CH₄) gases based on the measurement of the amount of these gases in exhaled air. Materials and Methods: We studied 14 subjects with type 2 diabetes mellitus (T2DM) and 14 individuals without diabetes (control) with two food load tests, including two types of dietary fiber (inulin and guar gum), with the simultaneous determination of gases in exhaled air and the assessment of glucose levels. Results: All subjects in the control group had a significant increase in exhaled H₂. OR for increased hydrogen production in patients with T2DM was 0.17 (95% CI 0.031–0.93, p = 0.043). The level of H₂ in exhaled breath after food load in patients with T2DM was lower than in normoglycemic subjects. There was an inverse correlation between maximum glucose rise and maximum H₂ in exhaled air after food load in normoglycemic subjects (r = −0.569, p = 0.034). Patients with T2DM had direct correlations between the level of CH₄ in exhaled air and the parameters of postprandial glycemia in the lactulose test (p < 0.05). Conclusions: The confirmation of a causal relationship between decreased H₂ production, increased intestinal CH₄ production, and more severe postprandial glycemia may identify new therapeutic targets in the correction of postprandial glycemia in patients with T2DM. Full article

Reduced graphene oxide (rGO) was synthesized by chemically reducing graphene oxide (GO) using a reducing agent. The product, rGO, showed excellent hydrophobicity, as indicated by its high-water contact angle, which was greater than 150°. Characterizations using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and X-ray diffraction (XRD) were used to analyze the composition and structural differences between GO and the superhydrophobic rGO material. Scanning electron microscopy (SEM) showed that GO particles exhibited a plate-like morphology with layers of stacked plates, while rGO displayed fewer stacks that show a more separated structure of layers. The increasing demand for superhydrophobic materials in advanced materials industries, due to their potential to enhance performance, durability, and safety, makes rGO a promising candidate for use in composite materials. Full article

Electrochemical water splitting provides a sustainable method for hydrogen production. However, the primary challenge for electrochemical hydrogen generation is the high cost and limited availability of platinum-based noble-metal catalysts. Transition-metal chalcogenides have been identified as low-cost and efficient electrocatalysts to promote the hydrogen evolution reaction (HER) in alkaline electrolytes. Nonetheless, the identification of active sites and the underlying catalytic mechanism remain elusive. In this study, phosphorus-doped nickel sulfide has been successfully synthesized, demonstrating enhanced activity for alkaline HER. Investigating surface chemistry through X-ray photoelectron spectroscopy (XPS), depth profiling revealed that surface restructuring occurs during the HER process. The presence of phosphorus significantly influences this transformation, promoting the formation of a novel active Ni-O layer. This Ni-O layer is responsible for enhanced catalytic activity by upshifting the d-band center and increasing the density of states near the Fermi level, along with expanding the electrochemical surface area. This study reveals that the surface restructuring of transition-metal sulfides is highly tied to the electronic structure of the parent catalysts. Gaining a comprehensive understanding of this surface restructuring is essential for predicting and exploring more efficient non-precious transition-metal sulfide electrocatalysts. Full article

Soybean is the primary oilseed crop in the United States, with significant industrial value. Understanding the molecular mechanisms of heat stress tolerance in soybean plants is critical for developing stress-resistant cultivars. Current knowledge about the role of fatty acid desaturases (FADs) in modulating membrane fluidity under abiotic stress prompted this investigation into the impact of mutations in the FAD genes on seed germination from heat-stressed plants. In soybean plants, exposure to heat stress during anthesis is known to significantly reduce seed germination. In silico expression analysis indicated high expression levels of the soybean FAD2 and FAD3 genes in the leaves. Therefore, a detailed expression analysis of these genes was conducted using qRT-PCR from leaf tissue. Generally, downregulation of these genes was observed in the mutants; however, two genes, FAD3A and FAD2-3, showed a more than 2-fold increase in expression in six out of ten mutants under heat stress. This upregulation was particularly pronounced (7-fold) in the mutant S17CR-170. Correlation analysis revealed a positive correlation (up to 0.48) between the expression level of FAD3A, FAD3B, FAD3C, and FAD2-3 and the decline in germination from heat-stressed plants. This suggests these FAD genes may act as negative regulators of germination under heat stress conditions. Full article

Low hydrogen cyanide (HCN) concentration is a high-priority trait for cassava varieties targeting their fresh and dry product profiles. To be acceptable, varieties bred and developed for these market segments must meet international safety standards for maximum acceptable residual levels of cyanide in cassava food and food products. The discovery of molecular markers that co-segregate with low HCN has not yet resulted in widespread usage in marker-assisted selection (MAS) in breeding programs. To deploy these HCN markers in regular MAS, assessing their reliability in various genetic backgrounds is crucial. The aim of this study was to assess the predictive accuracy of trait specific markers for HCN. The study used six HCN kompetitive allele-specific polymerase chain reaction (KASP) markers that had previously been developed in a Brazilian population and verified in segregating West African cassava populations. For most markers used in the study, the average call rate was more than 91.7%. Three markers—snpME00404, snpME00405 and snpME00406—showed a significant co-segregation of genotypes with the HCN phenotype. On average, genotypes that carried at least one copy of the favourable allele had lower HCN scores. The proportion of phenotypic variance accounted for by the three most important markers was 14% (snpME00406), 17% (snpME00405) and 27% (snpME00404). The validation of identified HCN SNP-markers marks a significant step in their deployment to support selection and advancement decisions in cassava breeding programs. Full article

There is an increasing need for virtual reality (VR) health applications. In the field of pain, VR has been used mainly as a distraction, with minimal use of VR to answer basic clinical questions. Pain is multifactorial and inherently threatening. Our lab recently designed two VR clinical environments with varying threat values; the present study sought to validate these environments. Subjects were randomly allocated into either the threatening or non-threatening VR consultation room and both subjective (threat questionnaire) and physiological (salivary cortisol) measurements were taken. As hypothesised, subjects in the threat condition recorded a higher threat score (p < 0.001; effect size = 0.76). There was a cortisol change across time in the threat condition (χ²(2) = 13.83, p < 0.001), but there were unexpected decreases at both 20 (p = 0.001) and 26 min (p = 0.03) following VR. While the physiological findings need further clarification, this study provides some validation of the threat value of our VR clinical tools. As such, these VR environments can potentially be used in pain experiments to help better our understanding of basic pain mechanisms. It is only with such understanding that we might offer new avenues for pain management. Full article

Spondyloarthritis (SpA) describes a group of diseases characterized by chronic inflammation in the spine and peripheral joints. While pathogenesis is still unclear, proinflammatory gut-derived immune cells have been identified in the joints of SpA patients. We previously identified an enriched population of integrin-expressing cells in the joints of SpA patients. Entry of gut-derived cells into joints may be mediated by these integrins. In the current study, we used the SKG murine model of SpA to study the impact of integrin blockade. Mice were injected with antibodies against the integrin α4β7 or the β7 monomer twice a week. Treatment with antibodies against α4β7 reduced disease severity in curdlan-injected SKG mice, with disease scores being comparable between treatment initiation times. Targeting the β7 monomer led to reduced arthritis severity compared to targeting the α4β7 dimer. Treatment with antibodies against α4β7 or β7 decreased expression of these integrins in CD4+ T cells, with the frequency of αE+β7+ T cells in the spleen and lymph nodes correlating with disease severity. In summary, we showed that integrin blockade showed potential for ameliorating disease in a murine model of SpA, lending support for further studies testing integrin blockade in SpA. Full article

This study investigated the perception of drought by cocoa farmers and explored the effectiveness of adaptive strategies (ASs) used in smallholding farms in the transboundary region between Ghana and Togo. Drought significantly threatens cocoa production in this region, affecting farmers’ livelihoods and cocoa supply chains. This study used a multistage sampling approach, which involved surveys with questionnaires administered to 330 cocoa farmers throughout the study area, along with on-site observations. Statistical analysis included binary logistic and Poisson regression models to explore the relationship between farmer socioeconomic characteristics and adaptation practices. The findings revealed that cocoa farmers in the region have a nuanced understanding of drought, attributed to changing climatic patterns and unsustainable land management practices such as deforestation. To mitigate its impacts, farmers employ a variety of ASs, including investment in farm management, soil management, and intercropping with crop diversification. Furthermore, socioeconomic factors, including age, formal education, household size, land tenure right, adaptation cost assessment, and an underestimation of self-efficacy, were shown to affect the choice in the AS. Among the ASs adopted, only farm management practices (weeding, pruning, fertilizer application, etc.) significantly improved the cocoa yield. This study contributes to understanding drought as a critical issue for cocoa farmers and the adaptation practices used by smallholder cocoa farmers. Given that among the strategies adopted, only farm management practices, also known as good agricultural practices (GAPs), significantly improves yield, this study recommends well-designed and innovative packages of sustainable farm management based on farm and owner characteristics. These include irrigation schemes, timely soil fertilizer monitoring and supply, and the provision of drought-resistant varieties along with technical itineraries. Additional interventions require drought emergency responses, with other factors such as education and financial support mechanisms expected to improve farmers’ timely decision-making to adapt and improve cocoa production resilience to drought episodes in international transboundary regions with complex governance structures. Full article

Exposure to pesticides such as paraquat and 2,4-dichlorophenoxyacetic acid (2,4-D) has been linked to harmful health effects, including alterations in male reproduction. Both herbicides are widely used in developing countries and have been associated with reproductive alterations, such as disruption of spermatogenesis and steroidogenesis. The thyroid axis and Ca²⁺-permeable ion channels play a key role in these processes, and their disruption can lead to reproductive issues and even infertility. This study evaluated the short-term effects of exposure to commercial herbicides based on paraquat and 2,4-D on gene expression in rat testes. At the molecular level, exposure to paraquat increased the expression of the thyroid hormone transporters monocarboxylate transporter 8 (Mct8) and organic anion-transporting polypeptide 1C1 (Oatp1c1) and the thyroid receptor alpha (TRα), suggesting a possible endocrine disruption. However, it did not alter the expression of the sperm-associated cation channels (CatSper1-2) or vanilloid receptor-related osmotically activated channel (Trpv4) related to sperm motility. In contrast, exposure to 2,4-D reduced the expression of the Mct10 transporter, Dio2 deiodinase, and CatSper1, which could affect both the availability of T3 in testicular cells and sperm quality, consistent with previous studies. However, 2,4-D did not affect the expression of CatSper2 or Trpv4. Deregulation of gene expression could explain the alterations in male reproductive processes reported by exposure to paraquat and 2,4-D. These thyroid hormone-related genes can serve as molecular biomarkers to assess endocrine disruption due to exposure to these herbicides, aiding in evaluating the health risks of pesticides. Full article

Graph Neural Networks (GNNs) have gained popularity in image matching methods, proving useful for various computer vision tasks like Structure from Motion (SfM) and 3D reconstruction. A well-known example is SuperGlue. Lightweight variants, such as LightGlue, have been developed with a focus on stacking fewer GNN layers compared to SuperGlue. This paper proposes the h-GNN, a lightweight image matching model, with improvements in the two processing modules, the GNN and matching modules. After image features are detected and described as keypoint nodes of a base graph, the GNN module, which primarily aims at increasing the h-GNN’s depth, creates successive hierarchies of compressed-size graphs from the base graph through a clustering technique termed SC+PCA. SC+PCA combines Principal Component Analysis (PCA) with Spectral Clustering (SC) to enrich nodes with local and global information during graph clustering. A dual non-contrastive clustering loss is used to optimize graph clustering. Additionally, four message-passing mechanisms have been proposed to only update node representations within a graph cluster at the same hierarchical level or to update node representations across graph clusters at different hierarchical levels. The matching module performs iterative pairwise matching on the enriched node representations to obtain a scoring matrix. This matrix comprises scores indicating potential correct matches between the image keypoint nodes. The score matrix is refined with a ‘dustbin’ to further suppress unmatched features. There is a reprojection loss used to optimize keypoint match positions. The Sinkhorn algorithm generates a final partial assignment from the refined score matrix. Experimental results demonstrate the performance of the proposed h-GNN against competing state-of-the-art (SOTA) GNN-based methods on several image matching tasks under homography, estimation, indoor and outdoor camera pose estimation, and 3D reconstruction on multiple datasets. Experiments also demonstrate improved computational memory and runtime, approximately 38.1% and 26.14% lower than SuperGlue, and an average of about 6.8% and 7.1% lower than LightGlue. Future research will explore the effects of integrating more recent simplicial message-passing mechanisms, which concurrently update both node and edge representations, into our proposed model. Full article

Ancient Near Eastern and Mediterranean cosmologies shared general assumptions about the interconnectivity of heaven and earth. Plato’s Myth of Er, the Book of the Watchers in 1 Enoch, and Cicero’s Dream of Scipio, narrate the travels of Er, Enoch, and Scipio, respectively, into the Beyond, where they each learn astonishing things about the cosmos, and are tasked with imparting a message to humanity. This comparative study argues that cosmic travel is an integral means of constructing a rhetoric of authority designed to recruit its audiences to its socio-political vision. By analysing literary conventions like pseudepigraphy and epiphany in the features that make up cosmic travel, we better understand how each story bridges the gap between the narrated (story) world and the external (real) world. The ability to blend the realities of a story and its audiences stems from the ways in which tropes of legitimacy render spatio-temporal reality malleable, but is also imperative to the very authority these tropes offer. Without arguing for deliberate intertextuality between all these sources, this study compares the use of heavenly voyages as a literary device for legitimising worldview across cultures, times, and places. Full article