Search Results (15,429)

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

Background/Objectives: The aim of this analysis of data from the multi-year nationwide SARSTer program in Poland was to compare the clinical presentation and course of COVID-19 in the last two infectious seasons. Methods: Clinical data from 719 consecutive patients hospitalized between April 2023 and March 2024 were compared with data from 360 patients hospitalized between 1 April 2024 and 31 March 2025. Results: In the 2023/2024 season, hospitalizations due to COVID-19 occurred primarily between September and January, and in the 2024/2025 season, the majority of hospitalizations occurred between July and November. In the 2024/2025 season, we documented a change in the age structure, with an increasing predominance of hospitalized patients over 70 years of age (68% vs. 60% in 2023/2024), a milder disease manifestation, reflected in a significantly lower percentage of patients with pulmonary lesions (19% vs. 24%), an improvement in the clinical course of the disease, reflected in a halving of the number of hospitalizations, a significantly higher percentage of patients with clinical improvement in subsequent weeks of hospitalization, including those discharged from the hospital within the first week (39% vs. 30%), and a significantly lower mortality rate (4.7% vs. 7.9%), especially among patients over 70 years of age (5.4% vs. 10.4%). This indicates that the trend of a milder disease course initiated by the emergence of the Omicron variant continues. Conclusions: In conclusion, our findings provide real-world clinical evidence of the evolution of the COVID-19 situation in the post-pandemic era. Full article

Understanding the reproductive ecology of birds and the factors influencing nest predation is essential for developing scientifically sound and effective bird conservation strategies. Certain pheasant species sensitive to environmental changes are vulnerable to threats and face survival pressures such as habitat destruction and human activities. However, research related to their reproductive ecology is lacking. Here for the first time we reported information on breeding biology of the Chinese francolin (Francolinus pintadeanus). This study was conducted during the breeding seasons of the Chinese francolin in 2021, 2023, 2024, and 2025, combining traditional survey and infrared camera technology to monitor its reproductive ecology and nest predators in the Datian and Bangxi Reserves and to identify its potential predators through artificial nest experiments. All nests were open-ground nests located at the roots of dwarf shrubs and grasses. Our findings revealed that the breeding season of the Chinese francolin was mainly in March–September, peaking in May; its clutch size was 4.09 ± 1.27 (N = 22), reproductive success was 27.27%, and 16 nests were failed; and all failed nests were predated, with abandoned nests accounting for 93.75% of the failed nests. In artificial nest experiments, the predation rates of Datian Reserve and Bangxi Reserve were 70.91% (N = 55) and 60.00% (N = 30), respectively, with no significant difference in predation rates between the fully covered and exposed groups (Datian: χ² = 0.258, p = 0.612; Bangxi: p = 0.710). Natural nest monitoring and artificial nest experiments on the Chinese francolin identified snakes and the small Indian civet (Viverricula indica) as the main predators in Datian Reserve, as well as the greater coucal (Centropus sinensis) and wild boar (Sus scrofa) as potential predators. In contrast, the main predators in Bangxi Reserve were snakes and rodents. These findings indicate differences in nest predator taxa between the two reserves. We recommend prioritizing the restoration of dwarf scrub vegetation and optimizing the habitat management strategy in these reserves to better protect the breeding habitats of pheasants while promoting long-term stability and continuation of their populations. Full article

This study investigated the effects of different forage-to-concentrate (F:C) ratios during cold-season supplementation on growth performance, serum biochemical parameters, hormone levels, and antioxidant capacity in yak calves on the Qinghai–Tibet Plateau. Eighteen 8-months-old male yaks with similar body weights (110.01 ± 2.08 kg) were randomly assigned to two groups receiving diets with high (F:C = 7:3) or low (F:C = 3:7) forage. The trial lasted 60 days, including early (days 0–30) and late (days 31–60) experimental stages. Body weight was measured, and serum samples were collected on days 30 and 60 for biochemical and hormonal analyses. Yaks in the low-forage group showed significantly greater average daily gain during both stages and the entire experiment (p < 0.05), with a 7.92% increase in final body weight. Serum total protein and globulin levels were significantly higher in the low-forage group throughout the trial (p < 0.05 or p < 0.01), while other biochemical parameters remained unaffected. Growth hormone concentrations were significantly elevated in the low-forage group at both stages (p < 0.05). Additionally, malondialdehyde levels tended to decrease in the early stage (p = 0.056), and total antioxidant capacity was significantly lower in the late experimental stage (p = 0.040) in the low-forage group. A higher net economic benefit was observed in the group fed an F:C ratio of 3:7 than in the 7:3 group. These findings suggest that cold-season supplementation with a low-forage diet improves growth performance and protein utilization in yak calves but may negatively impact antioxidant status. An optimal F:C balance should therefore be considered to support both performance and health in yak husbandry under harsh environmental conditions. Full article

Understanding how environmental conditions affect broiler comfort across different seasons is crucial for enhancing welfare in commercial poultry production. This study aimed to identify the relationship between housing environment, litter conditions, and broiler discomfort at different growth stages using data collected from two flocks reared during winter and summer. Environmental variables (temperature, humidity, ammonia, pH, and CO₂) and broiler responses were recorded and analyzed weekly. Discomfort was defined as a binary variable based on threshold deviations in temperature and air quality. Non-parametric statistical tests and a Random Forest model were employed to explore associations and predict comfort status. Results showed that discomfort was significantly higher during winter, particularly in weeks 1 and 6, likely due to thermal instability and rising ammonia levels. Summer flocks exhibited more stable comfort profiles. The predictive model achieved a high test accuracy (97.1%) and identified broiler weight, ammonia, and temperature as the strongest predictors of discomfort. Weekly discomfort patterns and feature importance analyses revealed critical intervention points and variables. These findings provide actionable insights for automating welfare monitoring in commercial broiler production, offering valuable information for season-specific management strategies and demonstrating the potential for integrating predictive models into automated welfare monitoring systems to support precision livestock farming. Full article

Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and their influence on the various parameters and characteristics of the contaminant’s fate through accurate numerical simulations can aid in developing a rapid remediation strategy. This paper develops a numerical model using the CactusHydro code, which is based on a high-resolution shock-capturing (HRSC) conservative method that accurately follows sharp discontinuities and temporal dynamics for a three-phase fluid flow. We analyze nine different emergency scenarios that represent the breaking of a diesel oil onshore pipeline in a porous medium. These scenarios encompass conditions such as dry season rupture, rainfall-induced saturation, and varying pipeline failure pressures. The influence of the spilled oil pressure and water saturation in the unsaturated zone is analyzed by following the saturation contour profiles of the three-phase fluid flow. We follow with the high-accuracy formation of shock fronts of the advective part of the migration. Additionally, the mass distribution of the expelled contaminant along the porous medium during the emergency is analyzed and quantified for the various scenarios. The results obtained indicate that the aquifer contamination strongly depends on the pressure outflow in the vertical flow. For a fixed pressure value, as water saturation increases, the mass of contaminant decreases, while the contamination speed increases, allowing the contaminant to reach extended areas. This study suggests that, even for LNAPLs, the distribution of leaked oil depends strongly on the spill pressure. If the pressure reaches 20 atm at the time of pipeline failure, then contamination may extend as deep as two meters below the water table. Additionally, different seasonal conditions can influence the spread of contaminants. This insight could directly inform guidelines and remediation measures for spill accidents. The CactusHydro code is a valuable tool for such applications. Full article

Advanced transportation, especially electric transportation, plays an increasingly significant role in the reduction of CO₂ emissions in urban traffic. A life-cycle CO₂ emission model in which traditional fossil fuels and electricity are considered is a key method to analyze the potential of transportation emission reduction. In this study, the life-cycle CO₂ emissions of gasoline, diesel, natural gas, and electricity generated during the production, transportation, and consumption were modeled and calculated. The influence of coal power generation, coal combustion, seasonal energy consumption, and travel patterns on the CO₂ emissions of electric vehicles was discussed. The analysis results show that the life-cycle CO₂ emissions of automobile fuels in the process of combustion, processing, mining, and transportation are from the largest to the smallest. If the proportion of coal power generation is reduced to 50% by replacing gasoline vehicles with electric vehicles, emissions can be reduced by about 48.2%. At the same time, the scale of traffic in different months and in different periods of time of the day causes seasonal energy consumption fluctuations and regular fuel consumption variations of electric vehicles. The cyclical carbon reduction effect can be amplified if measures such as replacing fuel cars in spring and fall, and during peak hours, are used. Full article

Background/Objectives: Archery is a technical sport involving repetitive and asymmetrical movements that requires trunk stability to enable good performance of the upper extremities. Being an asymmetrical sport, imbalances between sides might appear in the abdominal and back muscles. To assess trunk muscle function and symmetry in young competitive archers. Methods: Analyzing pre-season screening evaluation tests from medical files. This included an ultrasound examination of back and abdominal muscles (transverse abdominus and internal oblique) during rest and contraction and trunk muscle clinical strength tests. Results: Data on 15 elite archery athletes (mean age 17.2 (±2.7) years) were included. No athletes reported low back pain. No differences were found between the dominant and non-dominant sides in all outcome measurements (absolute thickness and percentage difference). Internal oblique muscle thickness during rest and contraction for the dominant side was higher in males compared with females (p < 0.05). The back muscles were more symmetrical than the abdominal muscles. Conclusions: Despite the asymmetrical functional demands of sport archery, young athletes displayed trunk muscle symmetry, particularly in their back muscles. While some variability in abdominal muscle asymmetry was observed, these differences were not statistically significant. Full article

Optimizing aeration, fertilization, and irrigation is vital for improving greenhouse tomato production while mitigating soil greenhouse gas (GHG) emissions. This study investigated the combined effects of three aeration levels (A1: single Venturi, A2: double Venturi, CK: no aeration), two fertilization rates (F1: 180 kg/ha, F2: 240 kg/ha), and two irrigation levels (I1: 0.8 E_pan, I2: 1.0 E_pan) on tomato yield, CO₂, N₂O, and CH₄ emissions, net GHG emissions, net global warming potential (NGWP), and GHG intensity (GHGI) across Spring–Summer and Autumn–Winter seasons. Results showed that aeration and fertilization significantly increased CO₂ and N₂O emissions but reduced CH₄ emissions. Warmer conditions in Spring–Summer elevated all GHG emissions and yield compared to Autumn–Winter seasons. Tomato yield, net GHG emissions, NGWP, and GHGI were 12.05%, 24.3%, 14.46%, and 2.37% higher, respectively, in Spring–Summer. Combining the Maximal Information Coefficient and TOPSIS models, the optimal practice was A1-F1-I1 in Spring–Summer and A2-F1-I1 in Autumn–Winter seasons. These results provide a theoretical basis for selecting climate-smart management strategies that enhance yield and environmental sustainability in greenhouse tomato systems. Full article

We employed a global high-resolution inverse model to estimate sectoral methane emissions, integrating observations from the GOSAT-2 satellite for the first time, along with observations from the surface observation network. A similar set of inversions using GOSAT observations was carried out to evaluate the consistency between emissions estimates derived from these two satellites and to ensure that GOSAT-2 data could seamlessly integrate with the existing data series without disrupting the continuity of flux estimates. This analysis, covering the period from 2019 to 2022, utilized prior anthropogenic emissions data mainly from EDGAR v6 and incorporated additional natural sources and sinks as outlined by global methane budget, 2020. Our analysis reveals a general agreement between total methane emissions estimates from GOSAT and GOSAT-2. However, on a sectoral basis, we found notable regional differences in the flux estimates. While GOSAT inversion estimates ~8 Tg a⁻¹ more anthropogenic emissions for China and around 4 Tg a⁻¹ more wetland emissions for Brazil and Indonesia, the posterior error distribution suggests that GOSAT-2 inversion is closer to surface observations over Asia. These discrepancies are found in regions with significant differences in XCH₄ data from the two satellites, such as East Asia and North America, tropical South America, and tropical Africa. These regional biases persist due to limited representative surface reference sites for Level 2 bias correction. The relatively lower data volume from GOSAT also introduces seasonal biases in the flux estimates when the quality filtering of Level 2 data persistently reduces usable observations during certain seasons, resulting in inadequate representation of the seasonal cycle in regions such as East Asia. Similarly, in tropical South America, where the model is relatively under-constrained by the limited surface observations, the lower data volume of GOSAT-2 suffers. While the two inversions exhibit consistent overall performance across North America and Europe, the GOSAT-2-based inversion demonstrates a better performance over East Asia. Therefore, while the two satellite datasets are broadly consistent, considering the fact that the biases in the XCH₄ data overlap with regions under-constrained by surface observations, establishing additional surface reference measurement sites is desirable to ensure consistent inversion results. Full article

Background/Objectives: Metabolic syndrome (MetS) comprises a cluster of cardiometabolic risk factors that vary dynamically under environmental and behavioral influences. Although there are data suggesting seasonal variability in individual metabolic components, few studies have comprehensively assessed MetS as a composite condition across seasons using a large, nationally representative population. In this study, we aimed to evaluate the seasonal and monthly patterns of MetS prevalence and component burden, with a focus on sex-specific differences. Methods: We analyzed 5,507,251 health screening records from 2,057,897 Korean adults aged ≥40 years between 2013 and 2022, obtained from the National Health Insurance Service database. Seasons were categorized as: spring (March–May), summer (June–August), fall (September–November), and winter (December–February). Trends in MetS prevalence and its components were evaluated monthly and seasonally, stratified by sex. Results: MetS prevalence significantly varied by season in both sexes (p < 0.001), ranging from 30.2% to 34.5% in men and from 21.5% to 25.5% in women. Among men, a U-shaped pattern was observed, with the lowest prevalence during summer and a progressive increase through winter. Women showed a steady decline in prevalence from January to September, followed by a slight rebound. Winter was associated with increased odds of MetS in both sexes. A significant interaction between sex and season (p for interaction <0.001) indicated the presence of sex-specific temporal patterns. Conclusions: This nationwide study revealed clear seasonal variation in MetS prevalence and component burden, with sex-specific patterns. These findings highlight the importance of incorporating seasonality and sex in cardiometabolic risk assessments and public health interventions. Full article

This paper aims to explore Virtual Power Plants (VPPs) in combination with Demand Response (DR) concepts, integrating solar power generation, Electric Vehicle (EV) charging and discharging, and user loads to establish an optimal energy management scheduling system. Willingness curves for load curtailment are derived based on the consumption patterns of industrial, commercial, and residential users, enabling VPPs to design DR mechanisms under Time-of-Use (TOU), two-stage, and critical peak pricing periods. An energy management model for a VPP is developed by integrating DR, EV charging and discharging, and user loads. To solve this model and optimize economic benefits, this paper proposes an Improved Wolf Pack Search Algorithm (IWPSA). Based on the original Wolf Pack Search Algorithm (WPSA), the Improved Wolf Pack Search Algorithm (IWPSA) enhances the key behaviors of detection and encirclement. By reinforcing the attack strategy, the algorithm achieves better search performance and improved stability. IWPSA provides a parameter optimization mechanism with global search capability, enhancing searching efficiency and increasing the likelihood of finding optimal solutions. It is used to simulate and analyze the maximum profit of the VPP under various scenarios, such as different seasons, incentive prices, and DR periods. The verification analysis in this paper demonstrates that the proposed method can not only assist decision makers in improving the operation and scheduling of VPPs, but also serve as a valuable reference for system architecture planning and more effectively evaluating the performance of VPP operation management. Full article

As one of the world’s leading grain producers, Brazil stands out in soybean and corn production. Accurate estimation of key crop phenological stages is essential for agricultural decision-making, especially considering Brazil’s vast territory, climatic diversity, and increasing frequency of extreme weather events. This study investigated the applicability of the NDVI, EVI, WDRVI, and NDWI, derived from Harmonized Landsat Sentinel-2, to identify crop sowing and harvest dates at the field scale. We extracted the vegetative peak from each vegetation index time series and identified the left and right inflection points around the peak to delineate the crop season. A double-logistic function and a derivative approach were applied to identify the Start of Season, Peak of Season, and End of Season. For both soybeans and corn, the RMSE ranged from 5 to 8 days for sowing dates, while for harvest dates it ranged from 6 to 15 days for corn. Despite these differences, all vegetation indices exhibited robust performance, with Spearman correlation values between 0.56 and 0.84. Our findings indicate that the use of different indices does not have a significant impact on the results, as long as the adjustment of temporal parameters for the phenological metrics is appropriate for each index. Full article

Motivated by the rapid development of SERS technology, trace detection of various viruses in the sewage and body fluid environments and accurate positive and negative diagnosis of detection samples can be achieved. However, evaluating the environmental survival ability of viruses based on SERS technology remains an unexplored issue, but holds significant guiding significance for effective epidemic prevention and control as well as inactivation treatment. In this work, Au nanoarrays were fabricated on silicon substrates through a simple Ar ion sputtering route as ultra-sensitive SERS chips. With the synergistic contribution of the “lightning rod” effect and the enhanced coupling surface plasmon caused by the nanoarrays, the ultra-sensitive detection of SARS-CoV-2 S protein with a concentration of 1 pg/mL and SERS enhancement factor of 4.89 × 10⁹ can be achieved. Exploration of the environmental survival ability of the SARS-CoV-2 virus indicates that the Raman activity of SARS-CoV-2 S protein exhibited higher temperature tolerance from 0 °C to 60 °C than SARS-CoV S protein, suggesting that the SARS-CoV-2 virus has less temperature influence from increasing air temperature than the SARS-CoV virus to a certain extent, which explains the seasonal recurrence pattern and regional transmission pattern of the novel coronavirus that are different from the SARS virus. Full article

The thermal discharge from coastal power plants exchanges heat with the surrounding marine environment, potentially affecting the aquatic ecosystem. This study utilizes Landsat-series satellite data from 2008 to 2023 to extract the spatiotemporal distribution characteristics of thermal discharges from the Xiangshan Harbor Guohua Power Plant (GPP) and the Wushashan Power Plant (WPP). Additionally, the study investigates the impact of thermal discharge on local aquatic life by examining the spatiotemporal distribution of chlorophyll-a (Chl-a). The results indicate that (1) the overall area of thermal rise in GPP and WPP shows a decreasing trend. The interannual variation in low thermal rise zones (+1 °C, +2 °C) is substantial, with significant seasonal differences mainly influenced by seasonal sea–air temperature differences, the flow velocity of seawater at the discharge outlet, and water depth. (2) The diffusion of thermal discharge is significantly affected by tides. The area of thermal rise is larger during ebb tide compared to flood tide, and during neap tide compared to mid-tide and spring tide. During the ebb tide of the neap tide period, the total area of thermal rise in WPP is approximately three times that of GPP. (3) There is a significant positive correlation between thermal discharge and concentrations of Chl-a. Thermal discharge has complex impacts on aquatic life, primarily positive. The findings of this study provide important references for analyzing the ecological impacts of thermal discharge from coastal power plants. Full article