Search Results (9,935)

Urban green spaces are increasingly recognized for their capacity to support mental health and enhance positive affect through interaction with nature. As a significant component of urban green infrastructure, urban forests provide restorative environments that contribute to individuals’ subjective well-being. This study investigates the effects of quality of experience in urban forest visits on individuals’ restorative experiences and subjective well-being levels. Data were collected via a structured questionnaire from 385 participants who visited an urban forest and analyzed using structural equation modeling (SEM). The findings reveal that quality of experience exerts both direct and indirect positive effects on subjective well-being, with restorative experience serving as a partial mediator in this relationship. Full article

Aiming at the issue of time-varying measurement noise with heavy-tailed characteristics and outliers generated by the polarization compass (PC) in the micro-electro-mechanical system–inertial navigation system (MEMS-INS) and PC-integrated navigation system when it is subject to internal and external disturbances, an improved Variational Bayesian Innovation Saturation Robust Adaptive Kalman filter (VISKF) algorithm is proposed. This algorithm utilizes the variational Bayesian (VB) method based on Student’s t-distribution (STD) to approximately calculate the statistical characteristics of the time-varying measurement noise of the PC, thereby obtaining more accurate measurement noise statistical parameters. Additionally, the algorithm introduces an innovation saturation function and proposes an adaptive update strategy for the saturation boundary. It mitigates the problem of innovation value divergence in PC caused by outliers through a two-layer structure that can track the changes in the innovation value to adaptively adjust the saturation boundary. To verify the effectiveness of the algorithm, static and dynamic experiments were conducted on an unmanned vehicle. The experimental results show that compared with adaptive Kalman filter (AKF), variational Bayesian robust adaptive Kalman filter (VBRAKF), and innovation saturate robust adaptive Kalman filter (ISRAKF), the proposed algorithm improves the dynamic orientation accuracy by 76.89%, 67.23%, and 84.45%, respectively. Moreover, compared with other similar target algorithms, the proposed algorithm also has obvious advantages. Therefore, this method can significantly improve the navigation accuracy and robustness of the INS/PC integrated navigation system in complex environments. Full article

Determining sow (Sus scrofa domesticus Erxleben) estrus status requires considerable labor investment, and continuous real-time monitoring is impractical. Workers typically identify estrus at scheduled intervals and determine artificial insemination timing based on experience. However, experience-based methods are subjective, vary with operator expertise, and impede standardized management in large-scale farms. This study employs cameras and deep learning to detect sows and analyze postural changes, enabling estrus detection and optimal insemination timing prediction. Experimental results indicate that the proposed method achieved an accuracy of 70% (42/60), where the recommended insemination timing differed by less than 24 h from human decisions. This approach facilitates data-driven estrus detection and insemination scheduling, potentially reducing labor intensity and improving reproductive outcomes, particularly beneficial for labor-intensive and large-scale swine production systems. Full article

Background: Unlike medical training, science teacher training in Brazil does not include PBL as a curricular methodology. However, there is a Pedagogical Residency Program (PRP) that allows teaching experiences that are different from those provided in the undergraduate course. Thus, in this research, we propose a formative intervention in PBL for scholarship holders in the Pedagogical Residency Program (hereinafter Residents), aiming to answer the following question: “What are the perceptions of pre-service teachers about the planning, implementation, and evaluation of a PBL intervention in physics teaching?”. Methods: Five Residents taught an elective course specially designed for the application of PBL to teach secondary school physics. The training of the Residents in PBL occurred almost simultaneously with the offering of the elective subject. To reveal their perceptions, we collected Residents’ teaching plans, problem scenarios, and reflective analyses. Results: The results demonstrate that the Residents encountered several difficulties in developing and implementing the PBL methodology when teaching physics. Regarding development, the difficulties lie in coherently aligning the learning objectives with the highly complex active methodology of PBL. In addition, another clear difficulty is developing a problem situation appropriate to the knowledge that one wishes to develop. During the intervention, the Residents realized how difficult it is to implement PBL to allow students to develop skills and knowledge in a reflective way. Conclusions: The results indicate that PRP is necessary to develop methodologies such as PBL, as it allows supervision and reflection on practice. However, we also observed that the results point to the urgent need to introduce PBL in the initial training of science teachers; this process can be established in three stages: strategically studying lesson planning for the implementation of PBL, developing problem situations that align with the knowledge that one wishes to develop, and developing metacognitive regulation and argumentation skills to conduct interventions based on PBL. Full article

Many athletes consume caffeine before late afternoon/evening training sessions or competition, yet the impact on subsequent sleep remains unclear. This systematic review with meta-analysis examined the effects of late afternoon/evening caffeine consumption on sleep in athletes. Ten studies (n = 128 athletes) involving randomized controlled trials and quasi-experimental designs were included if caffeine was consumed prior to late afternoon/evening training and subsequent sleep was measured. Meta-analysis followed PRISMA guidelines with risk of bias assessed using RoB-2 and ROBINS-I tools. Meta-analysis of randomized controlled trials revealed a small reduction in sleep efficiency with evening caffeine consumption: mean difference −4.87%, 95% CI −7.45 to −2.29, p = 0.04, though this effect was not robust in leave-one-out sensitivity analyses. Total sleep time showed a non-significant trend toward reduction: mean difference −32.47 min, 95% CI −69.93 to 4.99, p = 0.08, I² = 0%. Athletes consistently reported substantial subjective sleep impairment following evening caffeine intake (3–6 mg/kg BM), creating a pronounced objective–subjective disconnect. The most notable finding is that athletes consistently perceive substantial sleep disruption despite inconsistent objective changes, highlighting the importance of subjective sleep experience in athletic populations. These findings should be interpreted cautiously given the small number of studies and predominance of male participants, limiting generalisability. Full article

Accurate correspondence of complex neuroanatomical surfaces under non-rigid deformations remains a formidable challenge in computational neuroimaging, owing to inter-subject topological variability, partial occlusions, and non-isometric distortions. Here, we introduce the Dynamic Graph Analyzer (DGA), a unified hybrid framework that integrates simplified structural descriptors with spatial constraints and formulates matching as a global linear assignment. Structurally, the DGA computes node-level metrics, degree weighted by betweenness centrality and local clustering coefficients, to capture essential topological patterns at a low computational cost. Spatially, it employs a two-stage scheme that combines global maximum distances and local rescaling of adjacent node separations to preserve geometric fidelity. By embedding these complementary measures into a single cost matrix solved via the Kuhn–Munkres algorithm followed by a refinement of weak correspondences, the DGA ensures a globally optimal correspondence. In benchmark evaluations on the FAUST dataset, the DGA achieved a significant reduction in the mean geodetic reconstruction error compared to spectral graph convolutional netwworks (GCNs)—which learn optimized spectral descriptors akin to classical approaches like heat/wave kernel signatures (HKS/WKS)—and traditional spectral methods. Additional experiments demonstrate robust performance on partial matches in TOSCA and cross-species alignments in SHREC-20, validating resilience to morphological variation and symmetry ambiguities. These results establish the DGA as a scalable and accurate approach for brain shape correspondence, with promising applications in biomarker mapping, developmental studies, and clinical morphometry. Full article

Background/Objectives: This study aimed to assess whether income was associated with dental caries experience and dental care levels among 12-year-old children in two contrasting economic contexts, Sri Lanka (lower-middle-income) and Wales (high-income), regardless of national income status. Methods: An ecological study design was used with published data. For Sri Lanka, the income parameters used included household income, mean per capita income, and the Gini coefficient. For Wales, the Welsh Index of Multiple Deprivation was used. Dental caries was assessed using the DMFT index and its components (DT, MT, FT), while dental care was assessed using the care index, restorative index, and treatment index. Pearson correlations were used to explore associations between income measures and both caries experience and dental care indices across districts in Sri Lanka and unitary authorities in Wales. Results: The mean DMFT for 12-year-old children was 0.6 in both Sri Lanka and Wales, with caries prevalence of 30.4% and 29.6%, respectively. In Sri Lanka, both mean household income and per capita income showed moderate, statistically significant positive correlations with DMFT (r = 0.47, p = 0.01). Income inequality, measured by the Gini coefficient, was positively associated with caries experience (r = 0.42, p = 0.03). In Wales, higher deprivation (lower income) was moderately associated with increased DMFT, in areas within the 20% (r = 0.54, p < 0.01), 30% (r = 0.53, p < 0.01), and 50% (r = 0.61, p < 0.01) deprived quintiles. The dental care indices showed no clear association with income in either of the countries. Conclusions: Income-related disparities in dental caries were evident in both countries. Prevention strategies should focus on higher-income groups in Sri Lanka and on deprived populations in Wales. However, as this was an ecological study, the results are subject to ecological fallacy and should therefore be interpreted with caution. Full article

Active learning promises richer engagement, yet transnational English-medium engineering classrooms can remain quiet even when students are motivated. This study aims to explain this silence by examining the factors that encourage students to participate, the barriers that discourage them, and how student characteristics and coping strategies influence their participation. We conducted a mixed-methods survey of 402 undergraduates (Years 2–4) in a China–United Kingdom (Sino-UK) joint engineering programme in China. We analysed the closed-ended responses using descriptive and inferential statistics (including effect sizes) and the open-ended responses using inductive thematic analysis. Quantitative results showed that interest in the subject (76.6%) and career relevance (72.8%) were the most potent motivators. In contrast, fear of making mistakes (56%) and low confidence in public speaking (51%) were the most common barriers to participation. Other constraints included language load, deference to instructors, and prior passive learning experiences. Gender and discipline differences were negligible (Cramér’s V ≤ 0.09; Cohen’s d < 0.20). A small year-of-study effect also emerged, with later-year students marginally more confident in English-medium interactions. Qualitative analysis revealed recurring themes of evaluation anxiety, demands for technical vocabulary, inconsistent participation expectations, and reliance on private coping strategies (e.g., pre-class preparation, peer support, and after-class queries). We propose a ‘motivated-but-silent’ learner profile and blocked-pathway model where cultural, linguistic, and psychological filters prevent motivation from becoming classroom voice, refining Self-Determination Theory/Expectancy–Value Theory (SDT/EVT) and Willingness to Communicate (WTC) theories for transnational engineering contexts. These findings inform practice by recommending psychological safety measures, discipline-specific language scaffolds, and culturally responsive pedagogy to unlock student voice in English-medium Instruction/Transnational Education (EMI/TNE) settings. Full article

High software reliability is essential for safety-critical systems in nuclear power plants. To improve the quality of software following the requirements phase, requirements inspections are conducted to detect defects. Traditional approaches enhance inspection outcomes by employing more effective techniques or by increasing team redundancy. This study investigates an alternative approach: introducing diversity within the inspection team. Inspection technique diversity and inspector background diversity are considered in this paper. We hypothesize that an inspection team in which the inspectors use diverse inspection techniques or have diverse backgrounds will have a better performance in defect detection compared to an inspection team with no diversity. This is because diversity can reduce the number of dependent failures in an inspection team. In this study, a controlled experiment is designed and conducted to examine our hypothesis. In the experiment, research subjects with different backgrounds inspect a software requirements specification using different inspection techniques. The results are collected and analyzed statistically. The experiment shows that using diverse techniques in an inspection team can improve the performance of the inspection team; however, using inspectors with diverse backgrounds will not affect the performance of an inspection team significantly. Full article

C. canephora exhibits high genetic variability, and to estimate this variability, morphological descriptors associated with coffee quality are used. Bean size is a physical trait of great importance for coffee classification. Manual classification is known to be inaccurate and time-consuming, which is why researchers have adopted digital imaging techniques to improve classification efficiency. The objective of this study was to quantify the genetic diversity in 43 C. canephora clones using the Ward-MLM strategy and to estimate genetic parameters and correlations from digital phenotyping of beans and cherries. The experiment was conducted on a crop consisting of 43 C. canephora genotypes, where the cherries were manually pulped and dried until they reached 12% moisture content. Using GroundEye^® equipment, four replicates of 50 beans and cherries were evaluated for each treatment, and the software generated spreadsheets with the results of the geometric traits. To determine the existence of genetic variability among the genotypes, the data obtained were subjected to analysis of variance, estimation of genetic parameters, Ward-MLM analysis, and Pearson correlation. The genotypic variance was higher than the environmental variance for all variables analyzed, both for beans and cherries, indicating that the genotypes evaluated have high genetic variability. The greatest genetic distance was observed between groups I and IV, suggesting favorable conditions for crosses between the genotypes of these groups. Phenotypic correlation analysis revealed significant positive and negative correlations between the variables. Digital seed analysis successfully detected genetic divergence among the 43 C. canephora clones. The variables ‘area’, ‘maximum diameter’, and ‘minimum diameter’ are the most suitable for selecting genotypes with larger beans. Full article

Background/Objectives: Social sciences have described the 21st century as the ‘era of loneliness’, a time marked by the subjective and often distressing experience of lacking meaningful social connections. While loneliness has been linked to poorer health outcomes, its relationship with dietary practices remains underexplored. Methods: This ethnographic study examines the impact of loneliness on the eating habits of older adults, based on fieldwork conducted in Galicia and Extremadura (Spain) between November 2024 and April 2025. Using semi-structured interviews (n = 25) and participant observation in domestic settings, we examined everyday food practices. Data were examined using thematic analysis. Results: Participants acknowledged the connection between diet and health, although their dietary practices often failed to meet nutritional recommendations. Loneliness and social isolation influenced food choices and cooking routines, often leading to less nutritious diets. These effects were shaped by gender and social class. Many participants associated the decline of shared meals and food-related sociability with a diminished quality of life. The absence of a meaningful companion was experienced as a profound loss, prompting various coping strategies. Conclusions: The findings highlight that food holds both nutritional and symbolic value. Health promotion strategies should address the social and emotional dimensions of eating. Loneliness disrupts food practices at multiple levels, calling for public health responses that integrate biological, cultural, and care perspectives. Full article

Background/Objectives: Population aging and its associated chronic conditions have become an unprecedented challenge in the United States and worldwide. Many aged individuals experience certain forms of cognitive decline, which increases their risk of developing a pre-dementia condition called mild cognitive impairment and even dementia. No effective pharmacological treatments are available to treat normal age-associated cognitive decline or mild cognitive impairment. Our previous study has shown the potent anti-inflammatory effects of shiitake mushroom-derived vesicle-like nanoparticles (S-VLNs) in vitro and in an acute inflammatory disease model. In this study, we aimed to investigate the potential benefits of orally administered S-VLNs in aged mice. Methods: S-VLNs were extracted from fresh shiitake mushrooms. S-VLNs in phosphate-buffered saline (PBS) or vehicle only was orally administered to 13-month-old male C57BL/6J mice weekly for 9 months. These mice were subjected to a series of physiological tests, followed by euthanasia at 22 months of age. Their fecal samples were subjected to 16S rRNA and untargeted metabolomics analyses, followed by comprehensive bioinformatics analyses. Results: The long-term oral administration of S-VLNs significantly improved the cognitive function of aged mice. Orally administered S-VLNs did not travel to the brain. Instead, they impacted the composition of the gut microbiota and reshaped the fecal metabolome. Functional predictions of the gut microbiota and fecal metabolome suggested that S-VLNs regulated tryptophan metabolism. Specifically, S-VLNs markedly decreased the tryptophan-related metabolite kynurenic acid (KYNA). The integrative analyses of omics data identified a strong correlation between 18 gut bacterial genera and 66 fecal metabolites. KYNA was found to highly correlate with five genera positively and twelve genera negatively. Conclusions: The oral intake of S-VLNs represents a new and superior dietary approach with the ability to modulate the gut microbiota and fecal metabolome and to improve cognitive function during aging. Full article

The fuel electro-hydraulic servo valve is a core component of the aero-engine fuel control system, playing a crucial role in engine performance. Due to the operational characteristics of the aviation fuel supply and injection system, fuel is directly sprayed through the nozzle for combustion after passing through the pipeline. The working environment and medium are subject to a wide temperature range, and the medium lacks a circulating filtration process, making it difficult to effectively remove impurities. As a result, the fuel contains a high concentration of contaminant particles. Under high-temperature conditions, colloidal particles precipitated from the fuel medium collide and adhere to metallic and other contaminant particles carried by the fuel, subsequently attaching to the internal surfaces of the fuel servo valve, causing valve sticking. This study aims to establish an adhesion criterion suitable for colloidal particles in fuel systems based on a traditional particle collision model. The adhesion criterion incorporates the viscoelastic and surface energy characteristics of colloidal particles, providing a more accurate description of their deposition behavior under the conditions studied. A particle–particle and particle–wall collision test apparatus was designed, and experiments were conducted. A comparison between experimental results and theoretical calculations shows that the overall error for collisions between colloidal particles and walls is controlled within 10%, validating the feasibility of the adhesion criterion. The Young’s modulus, Poisson’s ratio, and surface free energy of the colloidal particles were measured as 688 MPa, 0.39, and 77 mJ/m², respectively. These results provide theoretical and experimental foundations for particle migration and deposition processes in fuel systems. The analytical method clarifies the key mechanism of adhesion caused by colloidal particles, providing guidance for improving the reliability, safety, and maintenance of fuel servo valves in aero-engine applications. Full article

The circadian rhythm controls the sleep/wake cycle and a wide variety of metabolic and physiological functions. Clock genes regulate it in response to both external and endogenous stimuli, and their expression may change because of aging, leading to an increased risk of health problems. Despite the well-described benefits of physical exercise as a circadian synchronizer, there is a lack of literature regarding the role of chronic exercise intensity in clock gene expression during aging. This article aims to analyze the differential expression of genes that regulate the biological clock under the effects of variable-intensity aerobic swimming training in aging mice, determining whether these exercise regimens interfere with the genomic regulation of the circadian rhythm. For this purpose, the mice were exposed to low- and high-intensity exercise and had their heart and gastrocnemius tissues molecularly analyzed by cDNA synthesis and qPCR to determine the expression levels of the selected genes: Clock, Arntl, Per1, Per2, Cry1, Cry2, and Nr1d1. The results showed that low-intensity exercise, performed at workloads below the anaerobic threshold, significantly changed their expression in the gastrocnemius muscle (p < 0.05), while high-intensity exercise had no statistically significant effects (p > 0.05), with the heart being immune to exercise influence except when it comes to the Per1 gene, for which expression was increased (p = 0.031) by low-intensity exercise. Additionally, both body weight and lactate thresholds had no change during the experiment (p > 0.05), while the maximum supported workload was maintained for high-intensity exercise (p > 0.05) and increased for low-intensity exercise (p < 0.01), with the control group experiencing a decay instead (p < 0.05). Thus, the present study highlights the importance of chronic exercise in modulating clock genes and opens exciting possibilities for circadian medicine, such as improvements in exercise capacity, heart condition, and lipid metabolism for subjects of low-intensity regimens. Full article

Mainstream experimental economics is characterized by its focus on theory testing and “treatment effects” on aggregate outcomes. The “agentic” alternative is concerned with the econometric specification of individual behavior. In this essay, first, a literature review of agentic experimental economics is provided, and a stylized workflow is proposed to produce and validate econometric models of individual behavior based on experimental data: (i) create a baseline (“optimal”) behavioral benchmark (by analytical means or reinforcement learning) for the considered multi-agent game, (ii) conduct experiments with human subjects, (iii) use the experimental results to characterize the structure of the deviations from the baseline behavior, and (iv) re-run the experiment with artificial agents calibrated in the previous step, and compare the outcomes with those of the human experiment. Two papers have been selected to illustrate the successful use of the proposed workflow. Finally, the relations between agent-based and experimental economics are discussed after deep learning has “tamed” the curse of dimensionality. Full article