Search Results (1,202)

Driven by the “dual-carbon” strategy, the development of zero- and low-carbon parks has become a crucial approach to resolving the conflict between urban expansion and ecological limits. Using urban functional zoning and land use data, this study estimates carbon emissions in Xiamen and examines their spatial distribution at the functional zone level, along with an assessment of carbon balance zoning. The results indicate that (1) Carbon sources far exceed sinks, with spatial concentrations in southern and northern areas, respectively. Commercial, transportation, and industrial zones are major emission sources. (2) A significant negative spatial correlation in carbon emissions exists among functional zones, manifesting as an alternating pattern of high- and low-carbon zones. (3) 72% of the zones have an ecological support coefficient below one, indicating severe carbon imbalance. (4) Xiamen can be categorized into four carbon balance functional zones, with carbon-source regulation zones accounting for 70%, core carbon-source zones accounting for 5%, and carbon-sink stressed zones accounting for 25%. No core carbon sink zones are identified. Based on these findings, targeted strategies are proposed: ecological restoration in northern Xiamen, carbon emission regulation in central areas, and source reduction in the south. These measures provide a scientific foundation for supporting Xiamen’s low-carbon transition and sustainable development. Full article

As concrete exhibits localized strain softening, for example, under tension, fracture-energy consistency is essential for obtaining mesh-insensitive results of finite-element (FE) analyses. Accordingly, element- and structural-level parametric studies of uniaxial tensile behavior are performed within an FE framework coupling the Concrete Damaged Plasticity (CDP) model, the Crack Band Theory, and the Newton–Raphson solver in Abaqus. The effects of several CDP parameters and the mesh size are quantified using a sensitivity index ($SI$). A damage evolution law with several tensile parameters is proposed for energy consistency in addition to scaling of the softening strain. Besides tensile strength, elastic modulus, and an estimated uniaxial stress–strain curve, three key parameters are validated: the ratio between fracture energy from pure tension in the crack band and that from direct-tension tests, and two mesh-independent damage evolution parameters. An inverse calibration is proposed, in which the damage parameters and the fracture-energy ratio are identified in one-element ($SI\le 5\%$) and multi-element models, respectively. With these calibrations, the tensile response of the crack band is obtained, and multi-element analyses achieve mesh insensitivity when meshes are not smaller than the crack-band width. For finer meshes violating continuum assumptions, the initial damage rate parameter is reduced to preserve energy consistency. Full article

For polar ships, navigation in ice-covered regions can lead to high risk to structural safety. To study the structural risk induced by ice loads, a risk assessment framework is proposed based on a probabilistic analysis. The fatigue failure probability is derived with the first-order second-moment (FOSM) method. Typical ice load cases are extracted as a joint probability distribution of ice thickness and ship speed, based on shipboard measurements. Equivalent fatigue stresses for each case are calculated using a coupled discrete element method (DEM) and finite element method (FEM), and fatigue failure probabilities are obtained via linear cumulative damage theory. The ultimate strength failure probability is derived from the reliability theory. The probabilistic distribution of load-carrying capacity for the bow structure, determined by the moment estimation method, is used as the structural resistance, while the ice load distribution identified from shipboard monitoring is treated as the external load. Considering both the likelihood and consequence of failure, a risk matrix is constructed to assess structural failure risk. Inspection and maintenance intervals are then proposed according to the assessed risk levels. This approach offers a quantitative basis for structural risk management, supporting safe navigation and efficient maintenance planning for polar ships. Full article

Modern power distribution systems are increasingly stressed as they operate closer to their voltage stability limits, driven by growing electricity demand, complex load behaviors, and the evolving structure of power networks. Radial distribution systems, in particular, are highly susceptible to voltage instability under critical loading conditions, where even minor load increases can trigger voltage collapse. Such events threaten the continuity and quality of power supply and can cause damage to infrastructure and sensitive equipment. While large-scale cascading failures are typically associated with transmission systems, localized cascading effects such as sequential voltage drops, feeder outages, and protective device operations can still occur in distribution networks, especially under high loading. Therefore, reliable and timely voltage stability assessment is essential to maintain system reliability and prevent disruptions. This study presents a comprehensive comparative analysis of four voltage stability indices designed for radial distribution networks. The performance of these indices is evaluated on the IEEE 33-bus and 69-bus test systems under various critical loading conditions and multiple static load models, including Constant Power Load (CPL), Constant Current Load (CIL), Constant Impedance Load (CZL), Composite Load (COML), and Exponential Load (EXL). The analysis investigates each index’s effectiveness in identifying voltage collapse points, estimating critical load levels, and calculating load margins, while also evaluating their robustness across diverse operating scenarios. The findings offer practical insights and serve as a valuable benchmark for selecting suitable voltage stability indicators to support monitoring and planning in modern distribution networks. Full article

Under the spatial distribution of water resources, with more water resources in the southern regions and less in the northern regions, and the “north–south grain transport” pattern, calculating the virtual water flow in food trade between provinces in China and analyzing its sustainability is crucial for ensuring the country’s water resources and food security. By considering various products and consumption types, the virtual water flow in inter-provincial grain trade is estimated using the Minimum Transport Cost Method and the Penman-Monteith formula. The sustainability of this virtual water flow is evaluated at the provincial level. (1) The results show that the top three provinces with the largest net virtual water outflow from inter-provincial grain trade are Heilongjiang, Henan, and Anhui, with net outflows of 43.166 billion m³, 18.974 billion m³, and 13.089 billion m³, respectively. The top three provinces with the largest net virtual water inflows are Hebei, Guangxi, and Liaoning, with net inflows of 18.875 billion m³, 10.076 billion m³, and 8.795 billion m³, respectively. (2) The largest inter-provincial virtual water flow occurs from Henan to Hebei (15.06 billion m³), followed by Inner Mongolia to Hunan (9.57 billion m³), and Heilongjiang to Hubei (9.04 billion m³). (3) Overall, the current pattern of virtual water flow in China’s grain trade is sustainable, though several exporting provinces are under greater stress. In the actual scenario, the average water resource pressure index across all provinces is 0.43, 17.31% lower than the average of 0.52 in the scenario without inter-provincial grain trade. Compared with the scenario without inter-provincial grain product trade, in the actual scenario, Heilongjiang, Jilin, and Inner Mongolia show a higher increase in water resource pressure index, with increases of 94.74%, 73.68%, and 48%, respectively; Beijing, Shanghai, and Qinghai show a greater decrease in water resource pressure index, with reductions of 94.64%, 79.41%, and 66.67%, individually. And then, efforts should be made to adjust and optimize the structure of grain production and circulation; provinces with virtual water net outflow (such as Heilongjiang, Henan, Anhui, etc.) need to adjust their grain cultivation types and grain export structures.; provinces with virtual water net inflow (such as Hebei, Guangxi, Liaoning, etc.) can appropriately expand the scale of grain cultivation, while adjusting their diets to reduce the demand for water-intensive grains. Full article

Micro- and nanoplastics (MNPs) are increasingly recognized as emerging contaminants of concern for human health. Their small size, diverse composition, and reactive surface enable interactions with biological barriers and cellular systems. This comprehensive narrative review synthesizes and critically evaluates current evidence on the mechanistic effects of MNPs in humans and experimental models. Systemic mechanisms, including oxidative stress, inflammation, barrier disruption, and immune dysregulation, may underlie reported adverse effects in the gastrointestinal tract, cardiovascular, nervous and reproductive systems, as well as the placenta. Omics studies further reveal alterations in metabolic and stress-response pathways, providing systems-level insights and candidate biomarkers. Human data remain limited to biomonitoring studies, and causality has not yet been established. Toxicological data, though informative, often rely on pristine particles and high-dose, short-term exposures that exceed environmental estimates, highlighting the need for chronic, low-dose models. Major challenges include difficulties in detecting and quantifying MNPs in tissues, limited attribution of effects to polymers versus additives or adsorbed contaminants, and lack of standardized characterization and reporting. Emerging advances, such as reference materials, omics profiling, and organ-on-chip technologies, offer opportunities to close these gaps. Overall, the available data suggest biologically plausible pathways for health risks, but methodological refinement and harmonized research strategies are essential for robust human health assessment. Full article

Oxidative stress observed in schizophrenia and other psychiatric disorders can induce neuronal damage and modulate intracellular signaling, ultimately leading to neuronal death by apoptosis or necrosis. The aim of this study was to estimate in vitro the possible antioxidant properties of curcumin, the natural polyphenolic antioxidant, and its protective effects against lipid peroxidation induced by the atypical antipsychotic Ziprasidone. Curcumin (5 µg/mL, 12.5 µg/mL, 25 µg/mL, 50 µg/mL) was added to human plasma and incubated for 1 and 24 h, alone and in the presence of Ziprasidone (40 ng/mL, 139 ng/mL, 250 ng/mL). Control plasma samples were incubated for 1 and 24 h. The concentration of thiobarbituric acid-reactive substances (TBARSs; lipid peroxidation marker) was determined by the spectrophotometric method according to Rice-Evans. Curcumin at the tested concentrations significantly inhibited lipid peroxidation in human plasma by about 60%. Ziprasidone (40 ng/mL, 139 ng/mL, 250 ng/mL) significantly increased TBARS levels, but in the presence of the studied curcumin concentrations, its pro-oxidative effects were reduced by about 56%. Our results confirm that Ziprasidone in vitro may induce lipid peroxidation in human plasma, whereas curcumin protects against lipid peroxidation in human plasma caused by the antipsychotic Ziprasidone. Full article

Cow bunching is a behavioral phenomenon where cattle aggregate in tight groups to protect themselves from biting by stable flies (Stomoxys calcitrans L.). The incidence of bunching varies between dairies and even among pens within the same dairy, as it is associated with the location-specific biting intensity of stable flies, which largely varies with dairy management and local environmental factors. Bunching may be associated with decreased feeding and laying times, as well as heat stress due to cattle aggregation. Thus, bunching may affect dairy cows’ milk production by reducing dry matter intake and rumination. To our knowledge, there are no previous studies specifically addressing the effect of cow bunching on milk production in lactating dairy cows. The objectives of our study were to estimate the economic impact of cow bunching against stable flies on milk production on a commercial California dairy and to estimate the economic losses associated with cow bunching and stable fly biting per cow per year. A longitudinal study was conducted from 1 May 2017 through 31 July 2017 on a 5000-cow Holstein herd housed in free stall pens in Tulare County, California. Pen-level cow bunching in four lactating cow pens was recorded weekly for 12 weeks. Bunching observations each day were matched to daily milk records for the study dairy. Two-piece spline linear mixed models were used to estimate the impact of cow bunching and stable fly counts on milk production. Cows in pens where bunching occurred experienced a significant milk reduction of 0.45 kg ± 0.104 (SE) per cow (p < 0.01) on the day of bunching in comparison to cows in pens without bunching. There was a significant reduction of 0.6 kg/cow/day in milk production associated with each increase in one stable fly per cow leg (standard metric for recording stable fly biting activity) after adjusting for parity, temperature humidity index (THI), and days in milk (DIM). Based on the economic analysis conducted on weekly bunching and fly counts, modeled milk production losses were reported as weekly loss in milk revenue per cow. The estimated economic loss associated with cow bunching and stable fly counts was highest during the last week of May (USD 0.34/cow/week and USD 1.86/cow/week, respectively) and was lowest during the last week of July (USD 0.03/cow/week and USD 0.29/cow/week, respectively). To mitigate the most substantial economic loss, dairy producers should focus their efforts on controlling stable flies during the early stable fly season, when stable fly abundance tends to be highest. Full article

Accurate crop yield prediction is challenging in environmentally diverse areas. This study evaluated the potential of different satellite sensors to predict winter wheat grain yield at the field level in Kansas, the U.S.’s leading winter wheat producer. Using Landsat NDVI data from late February to June, a linear regression model was able to reduce the standard deviation of predicted yields by over 20% (with a normalized root mean square error (nRMSE) of 80%). The NDVI during the anthesis and grain fill stages was essential for precise yield estimation. A subregional approach that incorporated weather and management data improved results, accounting for 51%, 63%, and 68% of the nRMSE in W, SC, and NC. Results indicate that NDVI-based yield models at the field scale are environmentally dependent, particularly in south-central and western Kansas, areas prone to heat stress and water deficit, respectively. Our findings showed the benefits of an environmental subregional model integrating remote sensing and field-specific weather and management data to improve yield prediction accuracy, particularly in large, environmentally diverse regions. Full article

Background/Objectives: Problematic smartphone use is common among nursing students and has been linked to academic and psychosocial difficulties. This PROSPERO-registered systematic review (CRD42024559668) identified the instruments used to assess smartphone addiction in nursing students and, secondarily, pooled typical addiction levels using the Smartphone Addiction Scale–Short Version (SAS-SV; 10–60) and examined psychosocial correlates. Methods: Following PRISMA 2020, we searched PubMed, Scopus, Web of Science, CINAHL and ScienceDirect from 1 January 2014 to 9 May 2024. Eligible studies assessed problematic smartphone use in undergraduate nursing students with validated instruments, while development-only studies and pandemic-specific contexts were excluded. Methodological quality was appraised using the JBI checklist, and a random-effects meta-analysis was performed to estimate pooled scores and explore cross-study variability. Results: Fifty-three studies met inclusion; eleven contributed to the SAS-SV meta-analysis (N = 5586). The pooled mean score was 29.5 (95% CI 27.7–31.3), with very high heterogeneity (I² = 98%). Sensitivity analyses yielded similar results, and no publication bias was detected. Across studies, higher smartphone addiction was correlated with elevated stress and anxiety, sleep disturbance, and poorer academic and clinical performance. Conclusions: Nursing students’ SAS-SV scores cluster around ~29/60, with substantial between-study variability. Higher addiction scores were consistently associated with stress, anxiety, poor sleep, and reduced academic and clinical performance. However, interpretation is limited by the cross-sectional nature of the included studies and the very high heterogeneity observed. Standardising measurement is essential, but equally important is developing targeted educational interventions to foster healthier smartphone habits in nursing education. These results may guide nursing educators and institutions to design programs that foster healthier digital habits and support students’ academic and clinical performance. Full article

Background/Objectives: Robust, state-level LGBTQ+ health surveillance is scarce in Kentucky, limiting evidence-based healthcare planning and policy. We aimed to evaluate the feasibility and early public-health utility of a community-partnered annual survey and compare selected mental health stressors between Kentucky and non-Kentucky respondents. Methods: We conducted a cross-sectional online survey (13 April–15 July 2024) developed with a statewide LGBTQ+ nonprofit. Recruitment occurred via organizational channels and community events. A content warning preceded the survey, which was administered via Qualtrics. Data quality was screened using reCAPTCHA. We assessed feasibility metrics including recruitment and completion rates. Mental health stressors were captured with a six-item scale. Group differences were estimated with Welch’s t-tests. Results: Of 3852 survey starts, 1559 were retained as analyzable completes (completion rate: 40.47%), with 78.7% residing in-state. Initial analysis revealed a significant divergence in mental health patterns: while Kentucky participants reported lower stress regarding their personal mental health, they reported significantly higher stress stemming from socio-political issues like homophobia and transphobia compared to out-of-state respondents. Conclusions: An annual, community-partnered surveillance platform is a feasible strategy for generating actionable mental health signals relevant to healthcare. These findings will inform targeted outreach and guide health system partnerships to enhance LGBTQ+-affirming care in Kentucky. Full article

Cold stress is a critical factor restricting the cultivation of subtropical evergreen species such as Camellia sinensis and C. japonica in temperate climates. This study aimed to develop an integrated framework for evaluating cold tolerance by combining visual assessment, electrolyte leakage (EL), Evans blue staining, and nonlinear regression modeling. All experiments were conducted with n = 3 samples per treatment, and statistical analyses were performed at a significance level of α = 0.05. Under freezing treatment at −6 °C, C. japonica exhibited faster and more severe damage, including leaf curling and vein darkening, compared to C. sinensis. Electrolyte leakage and cell death increased rapidly in C. japonica, and a sharp rise in cell death occurred in both species when EL exceeded 55%. Logistic regression of EL data estimated LT₅₀ values of −10.96 °C for C. sinensis and −9.38 °C for C. japonica, while EL Temp₅₀ values were −9.59 °C and −8.97 °C, respectively, indicating higher membrane stability in C. sinensis. The difference in LT₅₀ between the two species was statistically significant (p < 0.05). Biochemical and heatmap analyses from 25 °C to −12 °C showed that C. sinensis maintained higher chlorophyll, antioxidant activity, and sugar levels, reflecting stronger cold tolerance. In contrast, C. japonica accumulated more proline and MDA, indicating higher stress sensitivity and membrane damage. This study presents a reproducible, quantitative framework for evaluating cold tolerance in Camellia species, offering valuable insights for breeding and expanding cultivation under climate change. Full article

This paper establishes the Brain Booster Buildings framework, the first model to demonstrate how daily stair use can elevate brain-derived neurotrophic factor (BDNF), a vital molecule for lifelong neurogenesis and brain health in humans. Through a novel framework of the associations between metabolic equivalents (METs) data and BDNF response studies, we establish that stairs are generally higher in METs than any indoor activity. We further explain how architectural parameters (riser height, floor number, pace) predictably modulate exercise intensity during stair use. We identify two implementable patterns: moderate-intensity continuous use (≥20 min, 1–3 floors) and high-intensity interval training (6 min, carrying loads while using stairs in a building with three floors or less, or using stairs in a building with ≥3 floors, load-free). Based on BDNF responses to comparable exercise intensities, 6 min of high-intensity stair climbing is predicted to increase serum BDNF by up to 40%. Since people spend ~90% of their time indoors while neurogenesis declines fourfold throughout the adult lifespan, affecting mood, stress resilience, and memory, vertical architecture emerges as a vital, accessible, and cost-effective infrastructure that boosts BDNF for neurogenesis, plasticity, and brain health. We conducted scenario-based modelling using the Brain Booster Buildings framework to estimate how the use of stairs in residential, office, educational, hospital, and commercial buildings may boost BDNF levels based on established intensity–BDNF relationships. The framework provides architects, policymakers, and clinicians with evidence-based estimated specifications to use buildings as daily brain boosters. Full article

Background: A cataract is a clouding of the normally clear lens that obscures the passage of light, effectively reducing clarity and sharpness of vision. Although this disease can affect both children and adults, the most common type is the age-related cataract (ARC). The literature describes many potential agents associated with cataract development. However, this study focuses on modifiable factors, especially nutritional ones and those that may induce oxidative stress. The objective of the present study was to assess serum selenium (Se), copper (Cu), and zinc (Zn) concentrations, as well as the copper/zinc molar ratio (Cu/Zn molar ratio), total antioxidant status (TAS), total oxidant status (TOS), and oxidative stress index (OSI), of patients with ARC in relation to their dietary habits. Methods: A total of 68 patients with ARC and 64 healthy volunteers, with ages ranging from 48 to 92 years, were included in this study. The experimental material collected from the participants consisted of blood samples, which were tested for Se, Cu, and Zn concentrations using atomic absorption spectrometry (AAS). Oxidative stress (OS) parameters, such as TAS and TOS, were estimated spectrophotometrically. In addition, a food frequency questionnaire (FFQ) was used to collect information on the dietary habits of ARC patients. Results: Statistical analysis of the data revealed that the concentrations of Se, Cu, and Zn in serum were significantly lower in ARC patients compared to the controls. In the ARC group, some elements of dietary behavior had a significant effect on the levels of the examined elements and OS parameters. Conclusions: Thus, eventual alterations to one’s diet appear to be worth considering in the context of maintaining homeostasis and adequate mineral levels in ARC patients. Full article

Understanding the influence of weather on human well-being and mobility is essential to promoting healthier lifestyles. In this study we employ data collected from 151 participants over a continuous 30-day period in Switzerland to examine the effects of weather on well-being and mobility. Physiological data were retrieved through wearable devices, while mobility was automatically tracked through Google Location History, enabling detailed analysis of participants’ mobility behaviors. Mixed effects linear models were used to estimate the effects of temperature, precipitation, and sunshine duration on well-being and mobility while controlling for potential socio-demographic confounders. In this work, we demonstrate the feasibility of combining multi-source physiological and location data for environmental health research. Our results show small but significant effects of weather on several well-being outcomes (activity, sleep, and stress), while mobility was mostly affected by the level of precipitation. In line with previous research, our findings confirm that normal weather fluctuations exert significant but moderate effects on health-related behavior, highlighting the need to shift research focus toward extreme weather variations that lie beyond typical seasonal ranges. Given the potentially severe consequences of such extremes for public health and health-care systems, this shift will help identify more consistent effects, thereby informing targeted interventions and policy planning. Full article