Search Results (1,957)

Water is essential for ecological balance, environmental sustainability, and food security, particularly in arid regions where effective water management increasingly depends on farmer cooperation. The Samarkand region of Uzbekistan, known for its favorable climate and leading role in grape production, is facing rising drought conditions. This study explores the factors influencing grape farmers’ willingness to collaborate on water management in the districts of Ishtikhan, Payarik, and Kushrabot, which together produce 75–80% of the region’s grapes. A quantitative survey of 384 grape-producing households was conducted across 19 county citizens’ gatherings (38.7% of such gatherings), and structural equation modeling was employed to analyze a framework consisting of four dimensions: norms, environmental concerns, economic barriers, and the intention to adopt sustainable practices. The results indicate that norms and environmental concerns positively influence collaboration, suggesting a collective orientation toward sustainability. In contrast, economic barriers such as high costs and limited financial capacity significantly hinder cooperative behavior. Furthermore, a strong individual intention to adopt sustainable practices was associated with a greater likelihood of collaboration. These findings highlight the critical drivers and constraints shaping collective water use in agriculture and suggest that targeted policy measures and community-led efforts are vital for promoting sustainable water governance in drought-prone regions. Full article

Background: Population persistence for organisms to survive in a world with a rapidly changing climate will require either dispersal to suitable areas, evolutionary adaptation to altered conditions and/or sufficient phenotypic plasticity to withstand it. Given the slow growth and geographically isolated populations of many tree species, there is a high likelihood of local adaption or the acclimation of functional traits in these populations across the UK. Objectives: Given the slow growth and often isolated populations of Tilia cordata (lime tree), we hypothesised that there is a high likelihood of local adaptation or the acclimation of metabolic traits in these populations across the UK. Our aim was to test if the functional metabolomic traits of Tilia cordata (lime tree), collected in situ from natural populations, varied within and between populations and to compare this to neutral allele variation in the population. Methods: We used a metabolic fingerprinting approach to obtain a snapshot of the metabolic status of leaves collected from T. cordata from six populations across the UK. Environmental metadata, longer-term functional traits (specific leaf area) and neutral allelic variation in the population were also measured to assess the plastic capacity and local adaptation of the species. Results: The metabolic fingerprints derived from leaf material collected and fixed in situ from individuals in six populations of T. cordata across its UK range were similar, despite contrasting environmental conditions during sampling. Neutral allele frequencies showed almost no significant group structure, indicating low differentiation between populations. The specific leaf area did vary between sites. Conclusions: The low metabolic variation between UK populations of T. cordata despite contrasting environmental conditions during sampling indicates high levels of phenotypic plasticity. Full article

Space-based gravitational wave detectors, such as the Laser Interferometer Space Antenna (LISA) and Taiji, will observe GWs from $O\left({10}^8\right)$ galactic binary systems, allowing a completely unobscured view of the Milky Way structure. While previous studies have established theoretical expectations based on idealized data-analysis methods that use the true catalog of sources, we present an end-to-end analysis pipeline for inferring galactic structure parameters based on the detector output alone. We employ the GBSIEVER algorithm to extract GB signals from LISA Data Challenge data and develop a maximum likelihood approach to estimate a bulge-disk galactic model using the resolved GBs. We introduce a two-tiered selection methodology, combining frequency derivative thresholding and proximity criteria, to address the systematic overestimation of frequency derivatives that compromises distance measurements. We quantify the performance of our pipeline in recovering key Galactic structure parameters and the potential biases introduced by neglecting the errors in estimating the parameters of individual GBs. Our methodology represents a step forward in developing practical techniques that bridge the gap between theoretical possibilities and observational implementation. Full article

Background/Objectives: Misperception of body weight might be associated with the likelihood of being in a pre-contemplation phase and with a limited intention to initiate a healthy behavioral change toward weight management. The current study investigates factors associated with the misperception of body weight, body weight satisfaction, and intentions for body weight modifications. Methods: This study utilized a cross-sectional design to reach adults from Jazan, in the southwest of Saudi Arabia. The data collection tool measured demographics, the participants’ latest height and weight, body weight perception, satisfaction, and intentions concerning body weight modification. Chi-squared tests were used to compare the demographic characteristics between those who had correct perception and those who had a wrong one. Results: A sample of 685 adult participants was included in the current analysis. The mean age of the participants was 31.3 years (standard deviation: 11.1). The proportion of female participants was 52%. Fifty-four percent of the participants had a wrong perception of their body weight. Gender, employment, smoking, khat chewing, having a diagnosed condition, and BMI levels were statistically associated with the perception of body weight (p-values < 0.05). Conclusions: The detected misestimating, especially underestimation, might be associated with the likelihood of participants being in a precontemplation phase and with a limited intention to initiate a healthy behavioral change toward weight management. The practical implications of these findings indicate the importance of incorporating the assessment of weight perception alongside actual BMI measurement in clinical settings. Full article

This paper explores statistical techniques for estimating unknown lifetime parameters using data from a progressive first-failure censoring scheme. The failure times are modeled with a new Weibull–Pareto distribution. Maximum likelihood estimators are derived for the model parameters, as well as for the survival and hazard rate functions, although these estimators do not have explicit closed-form solutions. The Newton–Raphson algorithm is employed for the numerical computation of these estimates. Confidence intervals for the parameters are approximated based on the asymptotic normality of the maximum likelihood estimators. The Fisher information matrix is calculated using the missing information principle, and the delta technique is applied to approximate confidence intervals for the survival and hazard rate functions. Bayesian estimators are developed under squared error, linear exponential, and general entropy loss functions, assuming independent gamma priors. Markov chain Monte Carlo sampling is used to obtain Bayesian point estimates and the highest posterior density credible intervals for the parameters and reliability measures. Finally, the proposed methods are demonstrated through the analysis of a real dataset. Full article

Background/Objectives: With the rising trend of out-of-home dining in China, the use of iodized salt (IS) in eating-out venues plays a key role in preventing iodine deficiency disorders (IDDs). However, the coverage rate of iodized salt (CRIS) and the utilization rate of adequately iodized salt (URAIS) in these venues in China remain underexplored, potentially undermining IDD prevention strategies. This study aims to assess the CRIS and URAIS in such venues across China and identify the factors influencing their prevalence. Methods: From 2021 to 2024, a nationwide cross-sectional study was conducted in China, involving 19,346 venues. A 50 g sample of cooking salt was collected from each venue, and the iodine content was measured. The CRIS and URAIS were calculated, and associations with various factors were assessed using Chi-square tests, the Cochran–Armitage trend test, and multivariate logistic regression. Results: Of the 19,346 samples, 18,519 tested positive for IS, and 17,588 contained adequately iodized salt (AIS), resulting in a CRIS of 95.7% and a URAIS of 90.9%. Significant regional differences were found, with coastal areas showing a lower CRIS and URAIS than inland areas (87.0% vs. 97.8%; 81.0% vs. 93.2%) and urbanized areas having lower rates compared to less urbanized areas (94.1% vs. 97.3%; 88.9% vs. 92.9%). Higher per capita income was associated with a lower CRIS and URAIS (Z = −19.72, p < 0.0001; Z = −13.85, p < 0.0001). Lower per capita income (OR = 3.24, OR = 1.36, p < 0.0001), inland areas (OR = 4.14, OR = 2.68, p < 0.0001), and mountainous areas (OR = 2.48, OR = 1.27, p < 0.0001) were associated with a higher likelihood of IS and AIS use. Conclusions: While the CRIS and URAIS in dining venues meet national standards, regional disparities persist, particularly in coastal, plain, and economically advanced areas. Strengthening regulatory oversight and public education on iodized salt’s health benefits is essential. Full article

The intensifying global competition for cobalt resources and the increasing likelihood of trade decoupling and disruption are profoundly impacting the global energy transition. In a globalized trade environment, a decline in cobalt supply from exporting countries can spread through the trade network, negatively affecting demand countries. Quantitative analysis of the negative impacts of export supply declines in various countries can help identify early risks in the global supply chain, providing a scientific basis for energy security, industrial development, and policy responses. This study constructs a trade network using trade data on metal cobalt, cobalt powder, cobalt concentrate, and ore sand from the upstream (mining, selection, and smelting) stages of the cobalt industry chain across 155 countries and regions from 2000 to 2023. Based on this, an impact diffusion model is established, incorporating the trade volumes and production levels of cobalt resources in each country to measure their resilience to shocks and determine their direct or indirect dependencies. The study then simulates the impact on countries (regions) when each country’s supply is completely interrupted or reduced by 50%. The results show that: (1) The global cobalt trade network exhibits a ‘one superpower, multiple strong players’ characteristic. Congo (DRC) has a far greater destructive power than other countries, while South Africa, Zambia, Australia, Russia, and other countries have higher destructive power due to their strong storage and production capabilities, strong smelting capabilities, or as important trade transit countries. (2) The global cobalt trade network primarily consists of three major risk areas. The African continent, the Philippines and Indonesia in Southeast Asia, Australia in Oceania, and Russia, the United States, China, and the United Kingdom in Eurasia and North America form the primary risk zones for global cobalt trade. (3) When there is a complete disruption or a 50% reduction in export supply, China will suffer the greatest average demand loss, far exceeding the second-tier countries such as the United States, South Africa, and Zambia. In contrast, European countries and other regions worldwide will experience the smallest average demand loss. Full article

Purpose: This paper examines the differences between transgender persons who self-identify as bisexual (n = 4129) and those who self-identify as pansexual (n = 5056) when it comes to experiencing anti-transgender harassment, discrimination, and violence, serious psychological distress, and suicidal ideation. Methods: Data from the 2015 U.S. National Transgender Survey were used to evaluate the differences between bisexual and pansexual persons in a sample of transgender Americans aged 18 or older. The Kessler-6 scale assessed psychological distress, and a dichotomous measure of past-year suicidal ideation was used. A 20-item scale assessed the extent to which people experienced anti-transgender harassment, discrimination, and violence. Multivariate analysis and structural equation analysis were used to analyze the data. Results: Compared to their bisexual counterparts, pansexual persons experienced more anti-transgender harassment, discrimination, and violence, were more likely to experience serious psychological distress, and were more likely to report suicidal ideation. A structural equation analysis revealed that the bisexual–pansexual distinction is important when understanding transgender persons’ likelihood of experiencing suicidal ideation. It operates indirectly through its direct impact on the number of anti-transgender experiences incurred. Conclusions: Pansexual individuals fare more poorly than their bisexual counterparts on measures of anti-transgender experiences, serious psychological distress, and suicidal ideation. The bisexual–pansexual distinction is a meaningful one when trying to understand the transgender persons’ odds of thinking about dying by suicide. Full article

Background/Objectives: Dietary quality plays a crucial role in maintaining liver function. In this study, we examined sex differences in the association between dietary quality and elevated liver enzyme levels in Korean adults. Methods: This study included a nationwide sample of 15,997 males and 22,300 females in South Korea. Dietary assessment was performed using the Korean Healthy Eating Index (KHEI), an evidence-based dietary quality index that quantitatively reflects adherence to Korean dietary guidelines (range 0–100). Serum levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were measured, with individuals classified as having elevated AST or ALT levels when values were ≥40 IU/L or ≥35 IU/L, respectively. Logistic regression analysis was performed to examine the association between the KHEI and elevated AST or ALT levels stratified by sex. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined. Results: Among the males, a 10-point increase in the KHEI score was inversely associated with the likelihood of having elevated AST (OR: 0.90; 95% CI: 0.85–0.96) and ALT (OR: 0.96; 95% CI: 0.92–1.00) levels, respectively. Among the females, there was no clear association between the KHEI and elevated AST (OR: 0.98; 95% CI: 0.91–1.05) or ALT (OR: 1.00; 95% CI: 0.95–1.05) levels. Conclusion: Further research is warranted to elucidate the underlying mechanisms of the observed sex-specific associations and guide the development of targeted dietary interventions for liver health in males and females. Full article

In response to the increasing demand for environmentally friendly products and the parallel rise of deceptive green marketing practices, this study examines the impact of greenwashing awareness and green perceived benefits on consumers’ propensity to purchase green products, with a focus on the mediating role of green consumer confusion. Drawing upon data collected from 300 consumers in Greece through an online questionnaire, this study employed validated measurement scales and used multiple regression analyses to test its hypotheses. The findings reveal that both greenwashing awareness and green perceived benefits positively influence green purchase propensity. Additionally, green consumer confusion mediates the relationship between greenwashing awareness and green purchase propensity, indicating that the awareness of greenwashing reduces confusion and enhances consumers’ likelihood to choose genuinely green products. This study contributes to the literature by offering an integrated model that connects greenwashing awareness, green consumer confusion, and green perceived benefits in shaping green purchase propensity. Finally, the findings offer valuable insights for organizations to design clearer, more trustworthy green marketing strategies that minimize consumer confusion and foster informed green purchasing decisions. Full article

Background and Objectives: The extraction of mandibular third molars poses challenges due to their proximity to the mandibular canal and risk of inferior alveolar nerve (IAN) injury. Accurate preoperative evaluation is essential to minimize complications. This study assessed the three-dimensional positional relationship between the mandibular canal and lower third molars using cone-beam computed tomography (CBCT), aiming to identify anatomical positions associated with increased surgical risk. Materials and Methods: This retrospective study analyzed 253 CBCT scans of fully developed lower third molars. The mandibular canal position was classified as apical (Class I), buccal (Class II), lingual (Class III), or interradicular (Class IV). Contact was categorized as no contact, contact with a complete or defective white line, or canal penetration. In no-contact cases, the apex–canal distance was measured. Statistical analysis included descriptive and contingency analyses using the Chi-Square Likelihood Ratio test. Results: Class I was most common (70.8%) and presented the lowest risk, while Classes III and IV showed significantly higher frequencies of canal contact or penetration. Class II exhibited shorter distances even in no-contact cases, suggesting residual risk. Statistically significant associations were found between canal position and both contact type (p < 0.001) and apex–canal distance (p = 0.046). Conclusions: CBCT offers valuable insight into the anatomical relationship between third molars and the mandibular canal. High-risk positions—particularly lingual and interradicular—require careful assessment. Even in the absence of contact, close proximity may pose a risk and should inform surgical planning. Full article

Introduction: Chronic pain affects approximately 20% of U.S. adults, imposing significant burdens on individuals and healthcare systems. Medical cannabis has emerged as a potential therapy, yet its impact on healthcare utilization remains unclear. Methods: This retrospective cohort study analyzed administrative data from a telehealth platform providing medical cannabis certifications across 36 U.S. states. Patients were classified as cannabis-exposed if they had used cannabis in the past year, while unexposed patients had no prior cannabis use. Outcomes included self-reported urgent care visits, emergency department (ED) visits, hospitalizations, and quality of life (QoL), measured using the CDC’s Healthy Days measure. Targeted Maximum Likelihood Estimation with SuperLearner estimated causal effects, adjusting for numerous covariates. Results: Medical cannabis users exhibited significantly lower healthcare utilization. Specifically, exposure was associated with a 2.0 percentage point reduction in urgent care visits (95% CI: −0.036, −0.004), a 3.2 percentage point reduction in ED visits (95% CI: −0.051, −0.012) and fewer unhealthy days per month (−3.52 days, 95% CI: −4.28, −2.76). Hospitalization rates trended lower but were not statistically significant. Covariate balance and propensity score overlap indicated well-fitting models. Conclusions: Medical cannabis use was associated with reduced healthcare utilization and improved self-reported QoL among chronic pain patients. Full article

Background/Objectives: Pacifier use is a widespread soothing practice during infancy, but extended use has been linked to adverse dental outcomes, particularly malocclusion. This review aimed to evaluate the association between pacifier use and dental developmental issues in infants and toddlers and to identify key influencing factors. Methods: A scoping review using PubMed, Scopus, Web of Science, and Dentistry and Oral Sciences Source was performed. Peer-reviewed, full-text articles published in English between 2014 and 2024 were screened by two independent reviewers using predefined criteria. Eligible studies were thematically analyzed. Results: From 262 records, 35 studies met the inclusion criteria. Pacifier use was consistently associated with an increased prevalence of malocclusions, including anterior open bite, posterior crossbite, and overjet. The risk and severity of dental issues were strongly influenced by the duration, frequency, and intensity of pacifier use. Prolonged use beyond three years significantly increased the likelihood of structural changes requiring intervention. Conclusion: There is strong evidence linking pacifier use to negative dental developmental outcomes, particularly when use is prolonged or frequent. Early intervention, caregiver education, and timely weaning are critical to minimizing long-term oral health risks. Future research should explore pacifier design, objective measures of use, and how socioeconomic factors may influence pacifier use patterns and oral health outcomes. Understanding these relationships can support the development of more targeted and equitable prevention strategies. Full article

The structural modal parameter identification method can be classified into time-domain and frequency-domain methods. Practically, two types of methods are characterized by different advantages, and the estimated modal parameters are always subjected to statistical uncertainties due to measurement noise. In this work, an uncertainty-based fusion method for structural mode identification is proposed to merge the advantages of different methods. The extensively applied time-domain AutoRegressive (AR) and frequency-domain Left-Matrix Fraction (LMF) models are expressed in a unified parametric model. With this unified model, a generalized framework is developed to identify the modal parameters of structures and compute variances associated with modal parameter estimates. The final modal parameter estimates are computed as the inverse-variance weighted sum of the results identified from different methods. A numerical and an experimental example demonstrate that the proposed method can obtain reliable modal parameter estimates, substantially mitigating the occurrence of extremely large estimation errors. Furthermore, the fusion method demonstrates enhanced identification capabilities, effectively reducing the likelihood of missing structural modes. Full article

Predictive maintenance (PdM) is a proactive strategy that enhances safety, minimizes unplanned downtime, and optimizes operational costs by forecasting equipment failures before they occur. This study presents a novel Field Programmable Gate Array (FPGA)-accelerated predictive maintenance framework for UAV engines using a Singular Value Decomposition (SVD)-optimized Long Short-Term Memory (LSTM) model. The model performs binary classification to predict the likelihood of imminent engine failure by processing normalized multi-sensor data, including temperature, pressure, and vibration measurements. To enable real-time deployment on resource-constrained UAV platforms, the LSTM’s weight matrices are compressed using Singular Value Decomposition (SVD), significantly reducing computational complexity while preserving predictive accuracy. The compressed model is executed on a Xilinx ZCU-104 FPGA and uses a pipelined, AXI-based hardware accelerator with efficient memory mapping and parallelized gate calculations tailored for low-power onboard systems. Unlike prior works, this study uniquely integrates a tailored SVD compression strategy with a custom hardware accelerator co-designed for real-time, flight-safe inference in UAV systems. Experimental results demonstrate a 98% classification accuracy, a 24% reduction in latency, and substantial FPGA resource savings—specifically, a 26% decrease in BRAM usage and a 37% reduction in DSP consumption—compared to the 32-bit floating-point SVD-compressed FPGA implementation, not CPU or GPU. These findings confirm the proposed system as an efficient and scalable solution for real-time UAV engine health monitoring, thereby enhancing in-flight safety through timely fault prediction and enabling autonomous engine monitoring without reliance on ground communication. Full article