Search Results (49,331)

The impact of agricultural practices and changes in land use on soil microarthropod communities was investigated by analyzing the data from 53 sample sites with five different land-use categories (natural habitats, orchards, arable crops, olive groves and vineyards). These datasets are a mix of published and unpublished studies and were analyzed using statistical techniques that enabled a determination and comparison of the values of the biological soil quality index for each of the five land-use systems based on the richness and community composition of the biological forms of the microarthropods identified (QBS-ar), and the chemical and physical properties of the soil [e.g., pH, soil organic carbon (SOC), dominant particle sizes present (e.g., clay) and texture] for each locality. Our results confirm that different agricultural practices diminish, in different ways, the dominance and variety of species present in soil microarthropod communities. Furthermore, these agroecosystem communities represent a sub-sample of the soil microarthropod communities found in natural habitats; presumably due to the stress factors experienced from impact(s) of the differing chemical and physical properties of the soils, and the resultant selection pressures placed upon the biological forms present in the soil. Full article

The spaceborne-airborne bistatic radar (SABR) system employs a spaceborne transmitter and an airborne receiver, offering significant advantages, such as wide coverage, outstanding anti-stealth capabilities, and notable resistance to jamming. However, SABR operates in a downward-looking configuration, and due to the separation of the transmitter and receiver, non-side-looking array reception, and the effects of Earth’s rotation, clutter exhibits both spatial-temporal coupling and distance dependence. These factors cause substantial expansion in spatial and temporal frequency domains, leading to severe degradation in radar detection performance for moving targets. This paper establishes an SABR clutter signal model that applies to arbitrary geometric configurations to respond to these challenges. The paper uses this model to analyze the non-side-looking clutter characteristics in a geostationary spaceborne-airborne bistatic radar configuration. Furthermore, the paper investigates the impact of various observation areas and geometric configurations on detection performance, using SCNR loss as the performance index. Finally, this paper gives suggestions on the transceiver’s geometric configuration and the observation area selection. Full article

This study delves into the once-in-a-century extreme precipitation events in the northern region of the Pearl River Basin during the 2022 Dragon Boat Festival period. Through a comprehensive analysis spanning various temporal scales, from synoptic-scale systems to subseasonal oscillations, including the rare triple-peaked La Niña phenomenon, we illuminate the intricate interactions among these factors and their impact on extreme precipitation events. Specifically, we present a conceptual model of multiscale interaction systems contributing to extreme precipitation in the BeiJiang Basin. Our findings reveal that, during the 2022 Dragon Boat Festival period, precipitation in the BeiJiang Basin exhibited characteristics across multiple time scales, with the synoptic-scale environment proving highly conducive. Systems such as the South Asian High, Western Pacific Subtropical High, and South China Sea summer monsoon were identified as the direct influencing factors of precipitation. Importantly, our study highlight the pivotal role of subseasonal oscillation propagation stagnation in extreme precipitation in the BeiJiang Basin, with synoptic-scale systems playing a contributing role. We emphasize the indirect influence of ENSO signals, regulating not only monsoons but also the propagation of subseasonal oscillations. The interplay of these factors across different temporal scales significantly impacts flood hazards. Overall, our study significantly enhances the understanding of mechanisms driving extreme precipitation events in the Pearl River Basin, with profound implications for water resource management and disaster prevention. Full article

Background: Overweight or obese children and adolescents have a higher risk of developing cardiometabolic health problems compared with their healthy-weight peers, which are likely to progress to cardiovascular disease and are associated with a range of negative impacts. Objectives: To evaluate the effects of school-based physical activity (PA) interventions on cardiometabolic risk factors in children and adolescents with overweight or obesity. Method: A search of online databases (Web of Science, PubMed, and Embase databases) was conducted to identify relevant studies up to January 31, 2025. Results: Eleven studies were included, involving 963 participants aged 7 to 18 years. School-based PA interventions have a significant effect size (ES) in reducing body fat percentage (ES = −0.43, p < 0.01), diastolic blood pressure (ES = −0.27, p < 0.05), triglycerides (ES = −0.38, p < 0.01), fasting blood glucose (ES = −0.60, p < 0.01), blood insulin (ES = −0.62, p < 0.01), and homeostatic model assessment-insulin resistance (ES = −0.58, p < 0.01) in overweight or obese students. However, no significant improvements were observed in body mass index, body mass index z-score, waist circumference, waist-to-height ratio, maximal oxygen consumption, systolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol. Conclusion: School-based PA interventions lasting 6 weeks longer, twice a week or more, can significantly mitigate some cardiometabolic risks of overweight or obese children and adolescents. Effective, targeted PA programs should be considered in the school setting to promote the cardiometabolic health of this vulnerable group. Full article

Differences in the lifestyle and health-service-seeking behavior of persons experiencing homelessness (PEH) are well known. However, a comprehensive estimation of the resulting healthcare utilization differences and health outcome impacts are so far under-researched, especially at the national level. We aim to close this gap of evidence for lung cancer within the Hungarian universal healthcare system. We analyzed lung cancer-related information for the PEH population in the Hungarian national central health insurance register dataset and a matched control population between 2015 and 2021. In this period, 11,857 people were registered as homeless for the majority of at least one year. To capture the effect of homelessness, we created a categorical “homelessness length index” (HLI) according to the proportion of time an individual experienced homelessness during the investigation period (HLI 0: 0; HLI 1: >0–1/3; HLI 2: >1/3–2/3; HLI 3: >2/3). PEH individuals were matched 1:5 with a non-PEH control sample adjusted for age, sex and region. We conducted Kaplan–Meier survival analysis and Cox proportional hazards (CPH) regression adjusted for age, sex, HLI and average lung cancer-related healthcare costs. Our final analysis sample consisted of 641 patients (233 PEH, 408 control) who were newly diagnosed with lung cancer during the observation period. The lung cancer prevalence in the PEH group was 1.97% as opposed to 0.69% in the control group. The Kaplan–Meier curve showed lower average survival times for the PEH group, compared to the control group. Lung cancer associated costs between diagnosis and death/censoring were substantially different with average per patient cumulative costs of EUR 3668 in the PEH group compared to EUR 6827 in the control group (2018 prices). This translated to an average 47% lower annual lung cancer-related healthcare cost per PEH patient. CPH analysis showed that after disease severity, the degree of time spent in homelessness had the most significant effect on mortality, with a HR of 1.47 associated with both HLI 2 and 3 (95% CI: 1.08–2.00 and 1.01–2.14, respectively). We find that in Hungary, homelessness is associated with a much higher lung cancer burden linked to a three-times-higher prevalence, lower overall survival and almost 50% lower annualized disease-specific healthcare costs. Worse outcomes are mainly driven by long-term homelessness. Results could not be further refined according to lifestyle-related factors due to data availability limitations. Full article

Background/Objectives: Health locus of control (LOC) refers to one’s perceptions of who or what controls one’s health. Recent evidence has found that chance LOC (CLOC) is associated with improved quality of life (QoL) in multiple sclerosis (MS). The purpose of the current study was to identify mediators and moderators of the LOC-QoL relationship in MS. Methods: For this study, 5266 participants with MS completed a questionnaire pack that included the Multidimensional Health Locus of Control Scale, the Unidimensional Self-Efficacy Scale for MS (USE-MS), and the World Health Organization Quality of Life Scale—BREF (WHOQoL-BREF). The relationship between LOC and QoL was examined within a structural equation model (SEM). Results: In the total sample, self-efficacy was found to fully mediate the relationship between LOC and QoL for both internal (ILOC) and CLOC orientations. Powerful others LOC (PLOC) had no association with QoL. The same results were found for the relationship of LOC to functioning. In the secondary progressive MS subgroup, the relationship between CLOC and QoL was only partially mediated by self-efficacy. Conclusions: LOC influences QoL through its impact on self-efficacy, one of several potentially mediating factors between LOC and QoL in MS. Disability did not moderate the associations of LOC, but moderation of the CLOC-QoL relationship by disease subtype was found. Psychological training to improve self-efficacy in MS may be particularly useful in those subgroups where LOC-QoL is largely mediated by self-efficacy. Full article

In smart buildings, time series forecasting of electrical load is essential for energy optimization, demand response, and overall building performance. However, the mid-term load forecasting (MTLF) can be particularly challenging due to several uncertainties, such as sensor malfunctions, communication failures, and external environmental factors. These problems can lead to missing data patterns that may impact the accuracy and reliability of forecasting models. The purpose of this study is to explore the impact of random missing data patterns on the MTLF predictions’ accuracy. Therefore, several data imputation techniques are evaluated using a complete dataset (i.e., with no missing values) acquired on a smart commercial building, and their influence on load forecasting performance is assessed when different percentages of randomly distributed missing data patterns are assumed. Moreover, the deep learning (DL) approach based on a recurrent neural network, namely, long short-term memory (LSTM), is employed to predict the smart building electrical energy consumption. The obtained outcomes demonstrate that the pattern of random missing data significantly impacts the forecasting accuracy, with machine learning (ML) imputation techniques having better results than statistical and hybrid imputation techniques. Based on these findings, it is evident that robust data preprocessing and the handling of missing values are important in order to improve the accuracy and reliability of mid-term electrical load forecasts. Full article

Artificial intelligence (AI) has emerged as a critical subject in global educational contexts, not only within computing majors but also across all academic disciplines. This shift mirrors the rise of digital literacy in the late 20th century, positioning AI literacy as a needed skill for future generations. Despite its importance, there is ongoing debate about what exactly AI literacy entails and the skills it requires. While previous research has explored how computational thinking and varying educational levels affect AI literacy, there is a gap in related research on the impact of coding experience and the age at which students first learn about AI, especially for university students in non-computer-based majors. This exploratory study revealed that South Korean university students with prior coding experience consistently demonstrated significantly greater AI literacy than did those without prior coding experience. However, the age when students first learn about AI does not seem to play a major role in their overall perception of AI. These results suggest that the idea that coding experience might not be necessary for AI literacy needs additional investigation. However, further research is needed to fully understand the factors that contribute to AI literacy in non-computer-based university majors. Full article

Background/objectives: Amino acids (AAs) play a critical role in diseases such as cystic fibrosis where Pseudomonas aeruginosa PAO1 adapts its metabolism in response to host-derived nutrients. The adaptation influences virulence and complicates antibiotic treatment mainly for the antimicrobial resistance context. D- and L-AAs have been analyzed for their impact on quorum sensing (QS), a mechanism that regulates virulence factors. This research aimed to reconstruct the genome-scale metabolic model (GEM) of P. aeruginosa PAO1 to investigate the metabolic roles of D- and L-AAs in QS-related pathways. Methods: The updated GEM, iJD1249, was reconstructed by using protocols to integrate data from previous models and refined with well-standardized in silico media (LB, M9, and SCFM) to improve flux balance analysis accuracy. The model was used to explore the metabolic impact of D-Met, D-Ala, D-Glu, D-Ser, L-His, L-Glu, L-Arg, and L-Ornithine (L-Orn) at 5 and 50 mM in QS-related pathways, focusing on the effects on bacterial growth and carbon flux distributions. Results: Among the tested AAs, D-Met was the only one that did not enhance the growth rate of P. aeruginosa PAO1, while L-Arg and L-Orn increased fluxes in the L-methionine biosynthesis pathway, influencing the metH gene. These findings suggest a differential metabolic role for D-and L-AAs in QS-related pathways. Conclusions: Our results shed some light on the metabolic impact of AAs on QS-related pathways and their potential role in P. aeruginosa virulence. Future studies should assess D-Met as a potential adjuvant in antimicrobial strategies, optimizing the concentration in combination with antibiotics to maximize its therapeutic effectiveness. Full article

Low temperature (LT) and low illumination (LI) are common meteorological factors posing a great risk to plants. This study aimed to clarify and quantify the effects of LT, LI, and their combined stress (LTLI) on the photosynthetic physiological processes of strawberry plants during the flowering stage. The results indicated that LI stress increased Chla and b levels in strawberry plants while lowering the chlorophyll a/b ratio. In contrast, LT and LTLI stress reduced chlorophyll content. All stress conditions (LT, LI, and LTLI) decreased net photosynthetic rate, stomatal conductance, transpiration rate, the maximum photochemical efficiency of photosystem II, photosynthetic electron transport rate, and actual photochemical quantum efficiency. These stresses also raised intercellular carbon dioxide concentration, non-photochemical quenching coefficient, and levels of malondialdehyde, proline, hydrogen peroxide, and peroxide ion content. Moreover, LI stress treatment boosted the activity of superoxide dismutase, peroxidase, and catalase, while LT and LTLI stress initially raised the activity of these enzymes before it eventually declined. Importantly, the previously mentioned photosynthetic physiological parameters showed notable changes under the combined stress conditions. Ultimately, the TOPSIS model was used to quantitatively evaluate the impact levels of different stressors and treatment durations on the photosynthetic system of strawberry plants. In conclusion, the synergistic impact of LT and LI results in a reduction in photosynthetic rate and photosystem II activity, a disruption in the equilibrium of the antioxidant system, and an intensification of photoinhibition, ultimately leading to diminished photosynthetic efficiency in plants. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by progressive cognitive decline, memory loss, and behavioral changes. It poses a significant global health challenge. AD is associated with the accumulation of amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain, along with chronic inflammation, dysfunctional neurons, and synapse loss. While the prevalence of AD continues to rise, the current FDA-approved drugs offer only limited effectiveness. Emerging evidence suggests that obesity, insulin resistance (IR), and type 2 diabetes mellitus (T2DM) are also implicated in AD pathogenesis, with epidemiological studies and animal models confirming the impact of IR on Aβ accumulation, and high-fat diets also exacerbating Aβ accumulation. Since neuroinflammation activated by Aβ involves the nuclear factor kappa-light-chain-enhancer of the activated B cell (NF-κB) pathway, the inhibition of NF-κB and NLRP3 inflammasome activation are potential therapeutic strategies in AD. Bioactive compounds, including polyphenols (resveratrol, epigallocatechin-3-gallate, curcumin, and quercetin), and omega-3 polyunsaturated fatty acids, show promising results in animal studies and clinical trials for reducing Aβ levels, improving cognition and modulating the signaling pathways implicated in AD. This review explores the interplay between obesity, IR, inflammation, and AD pathology, emphasizing the potential of dietary compounds and their role in reducing inflammation, oxidative stress, and cognitive decline, as viable strategies for AD prevention and treatment. By integrating epidemiological findings, observational studies, and clinical trials, this review aims to provide a comprehensive understating of how metabolic dysfunctions and bioactive compounds influence AD progression. Full article

Background: The COVID-19 pandemic represents a major global health crisis, with clinical manifestations ranging from asymptomatic infection to fatal outcomes. While all individuals are susceptible, specific populations, particularly those with pre-existing medical conditions, face a heightened risk of severe disease. This study aimed to assess the prevalence of severe COVID-19 among hospitalized patients with comorbidities in the Central Region of Romania, and to analyze the association between these conditions and mortality. Methods: We conducted a retrospective cohort study using data from the Corona Forms platform (2020–2022), encompassing hospitalized cases across three Romanian counties. A total of 1458 patients with confirmed SARS-CoV-2 infection and documented comorbidities were included. Demographic characteristics, comorbid conditions, and hospitalization outcomes were analyzed. Results: The overall mortality rate among comorbid patients was 89.3%. Renal, neurologic, hepatic disease, cardiovascular conditions, obesity, type 2 diabetes mellitus, and cerebrovascular accidents are significant risk factors for death outcomes in the SARS-CoV-2-infected study population. The strength of their association varies, with odds ratios ranging from 25.32 to 1. Conclusions: The findings underscore the critical impact of comorbidities on COVID-19 severity and mortality among the Central Romanian population, emphasizing the necessity of targeted clinical interventions and public health strategies to protect high-risk populations. Full article

Background/Objectives: The presence of a child with special educational needs (SENs) necessitates that both the child and their family engage in adaptive processes and develop resilience in response to the developmental challenges that arise following an SENs diagnosis. Furthermore, it is critical to examine the impact of such a diagnosis on parental marital cohesion. Despite the recognized importance of this issue, the effects of SENs diagnoses on marital cohesion and flexibility, and the perceived stress experienced by parents, remain underexplored in the extant literature. Methods: Forty-seven participants (23 parents of children diagnosed with SENs and 24 parents of typically developing children, all aged between 32 and 60 years) completed this study. The instruments used were the Family Cohesion and Flexibility Evaluation Scale (couple version) and the Perceived Stress Scale. Results: No direct relationship was found between the SENs diagnosis and marital cohesion or flexibility. Furthermore, the perceived stress did not mediate the association between these variables. Nonetheless, both groups exhibited high levels of perceived stress. Conclusion: These results underscore the necessity for further investigation into the role of emotional support and coping strategies in alleviating the perceived stress among parents and caregivers of children with SENs. A deeper understanding of these factors is essential for the development of interventions aimed at promoting parental well-being and enhancing the quality of caregiving. Full article

Background: Children with medical complexity (CMC), a subset of children with special healthcare needs, have chronic conditions affecting multiple organ systems, require medical technology, and account for a significant share of pediatric healthcare spending despite comprising only 1% of the population. Their families experience unique stressors, including financial strain and high rates of workforce attrition, suggesting medical inequity is an independent risk factor for health inequity. The role of universal caregiver stress screening using a validated tool within the outpatient primary care medical home for CMC youth has not been explored in the literature. Methods: Caregivers of all patients in the Complex Care Program (CCP) within a large academic pediatric primary care Medical Home-certified practice at the Children’s National Hospital were screened for caregiver stress during routine primary care appointments using the University of Washington Caregiver Stress Scale 8-Item Short Form V. 2.0 (UW-CSS). Elevated scores prompted referrals to the CCP psychosocial team, and composite scores were recorded in the electronic medical record. Demographics, medical diagnoses, and technology support status were extracted from the medical chart. The childhood opportunity index (COI) was calculated as a proxy for socioeconomic position. Results: Screening for caregiver stress in our medical home for CMC was feasible and yielded unexpected results. We found no difference in levels of stress among caregivers based on the COI. This finding highlights the importance of universal rather than targeted screening. Future directions include measuring the impact of targeted interventions for families who initially screen positive via longitudinal follow-up. Conclusions: Screening for caregiver stress in a primary care medical home for CMC is feasible. As no single variable alone was a predictor of high caregiver stress, universal screening seems to be the most appropriate strategy to capture all families at the highest risk. Full article

China’s unique economic growth target system exerts significant economic growth pressure (EGP) on local officials, leading to notable economic and environmental consequences for urban land use. Consequently, this system is theoretically expected to have a significant impact on urban land green utilization efficiency (ULGUE). This study investigates the invisible institutional factors that shape ULGUE within China’s distinct economic growth target system. The results indicate an inverted U-shaped relationship between EGP and ULGUE, and this nonlinear relationship is statistically significant in central, western, and northeastern cities but not in eastern cities. EGP influences ULGUE in a non-monotonic manner by affecting land marketization, green technology innovation, and industrial structure upgrading. Furthermore, environmental regulation and financial technology investment moderate the relationship between EGP and ULGUE. Heterogeneity analysis reveals that the inverted U-shaped relationship is more pronounced in resource-dependent cities and cities with stringent target constraints. This study contributes empirical evidence on the interaction between EGP and ULGUE while offering both theoretical insights and practical implications. Full article