Search Results (30,649)

Layered cloud cover (LCC) describes the vertical distribution of cloud occurrence and is a key variable for assessing the radiation budget of the Earth-atmosphere system. However, ground-based radars have limited spatial coverage, while existing satellite cloud-cover products rarely provide both spatiotemporal continuity and high accuracy. Because nighttime satellite observations lack visible-channel information, conventional passive satellite remote sensing remains limited in providing day-night continuous LCC retrievals. In this study, we propose an infrared-based framework for retrieving large-scale day-night LCC from geostationary satellite observations. The framework first resolves cloud vertical structure using a hybrid machine learning and physical algorithm for day-night cloud-base height (CBH) retrieval, and then derives cloud cover in different vertical layers. Validation against active measurements from spaceborne and ground-based cloud radar demonstrates that the satellite-retrieved LCC captures cloud vertical distributions and their diurnal variations. The cloud-layer identification accuracies reach 76.3% and 77.9% for daytime and nighttime, respectively, with corresponding Cohen’s kappa coefficients of 0.66 and 0.68. The primary source of algorithmic uncertainty is the low precision of low-cloud identification, which is constrained by objective factors and physical characteristics. The retrieved annual mean LCC fields reproduce major climatological features, including enhanced high and deep convective clouds over the tropical western Pacific and dominant low-cloud occurrence over the mid-latitude oceans. A case study of Typhoon Doksuri further shows that the 10 min LCC retrievals capture the vertical evolution of the typhoon cloud system during intensification, eyewall structural adjustment, landfall, and post-landfall decay. These results indicate that the proposed infrared-based retrieval framework provides a promising basis for constructing large-scale day-night LCC datasets and can support cloud-radiation studies, climate-model evaluation, and weather monitoring. Full article

Greek mussel farming produces ~15,000 tons annually, though it faces severe threats from biotoxins (DSP, ASP, PSP). Weekly monitoring protects public health through harvest bans, which lasted up to 200 days near the Axios Delta between 2018 and 2023. These restrictions, alongside COVID-19 and rising sea temperatures (>27 °C) causing mass mortality, have reduced production volume and value. Although wholesale prices rose to €0.7/kg, they remain below historical peaks. While essential for safety, prolonged toxin presence and climate change impose a heavy socio-economic burden on producers, necessitating more efficient monitoring to sustain the sector. Full article

Background: Renal cell carcinoma accounts for nearly 15,000 deaths annually in the US, and approximately 30–40% of patients present with metastatic disease (mRCC). The advent of immune checkpoint inhibitors (IO) and tyrosine kinase inhibitors (TKI) has revolutionized the treatment paradigm of patients with mRCC. However, the role of cytoreductive nephrectomy (CN) in the IO-TKI era, particularly for rare and understudied histologies such as non-clear-cell RCC, remains poorly understood. Methods: We conducted a retrospective cohort study of patients with metastatic non-clear-cell RCC. Patients were stratified by receipt of CN. Baseline demographic, clinical, histologic, and metastatic site variables were collected. Overall survival was analyzed using Kaplan–Meier methods and compared with the log-rank test. Cox proportional hazards regression was performed to identify independent predictors of survival, including CN, systemic therapy, year of diagnosis, histology, and metastatic sites. Results: Among 2753 patients with metastatic nccRCC, 1654 (60.1%) underwent CN and 1099 (39.9%) did not undergo CN. The 2-year and 5-year OS rates were 35.52% and 19.22% in the CN group versus 18.53% and 7.47% in the non-CN group (p < 0.001). In the doubly robust IPTW-weighted multivariable Cox regression analysis, CN was associated with improved overall survival, corresponding to a 40% lower risk of death compared with no CN (HR 0.60, 95% CI 0.54–0.66; p < 0.001). Additionally, more recent treatment eras were associated with progressively improved overall survival, with patients diagnosed between 2015 and 2017 and 2018 onward demonstrating significantly improved OS compared with those diagnosed between 2004 and 2014. Conclusions: Our study demonstrates that CN was associated with improved OS in patients with non-clear-cell mRCC by reducing the risk of death by 40% after adjusting for baseline characteristics. These findings emphasize the role of CN even in the IO-TKI era for the management of patients with non-clear-cell mRCC. However, these findings should be interpreted in the context of the retrospective study design, potential selection bias, and lack of granular systemic therapy data within the NCDB. Full article

The rapid development of new energy has caused a sharp increase in the stochasticity on the source side of the new power system (NPS), and extreme weather along with climate variability have also led to increased stochasticity in power demand on the load side; thus, how to achieve source-load matching and enable the load to track the source under the new situation is the key to the efficient operation of the power system. Aiming at the problem that existing load regulation potential evaluation mainly focuses on physical capacity, making it difficult to reflect users’ subjective willingness to participate as well as the dynamic changes in regulation capability under different operating scenarios, this paper proposes a two-stage dynamic profiling classification method for multi-type power user loads considering regulation willingness. First, an evaluation index system is constructed from three dimensions, physical reliability, execution reliability, and behavioral willingness, to achieve the unified characterization of the regulation capabilities of heterogeneous resources such as industrial loads and electric vehicle (EV) aggregators. Second, the DBSCAN algorithm is adopted to identify typical annual operating scenarios. Finally, the Dynamic Time Warping (DTW) distance is introduced to improve the K-Means++ algorithm, achieving the profiling classification of user regulation potential. This paper takes a certain NPS demonstration park as an example for verification, and the results show that the annual operating scenarios can be divided into 4 types of typical days; the proposed DTW-K-Means++ method has better classification performance compared with traditional Euclidean distance clustering, can effectively identify the differences and dynamic migration characteristics of user regulation potential under different operating scenarios, and stably classifies users into three types of profiles: deep regulation type, agile response type, and rigid constraint type. The research results aim to provide reliable data support for the refined dispatch of the power grid by effectively quantifying the dynamic migration patterns of heterogeneous resources under variable scenarios. Full article

Natural gas pressure-reduction stations dissipate a significant portion of the gas pressure energy during conventional throttling. The recovery of this energy at small-capacity stations remains challenging due to low gas flow rates and variable operating conditions. This study investigates the application of a volumetric expander–generator regulator based on a vane-type positive-displacement expander as a combined pressure control and energy recovery device for small natural gas pressure-reduction stations. A mathematical model of gas-dynamic processes in the expander–generator regulator was developed and verified using experimental data obtained from a laboratory-scale compressed-air test facility. Experimental investigations were carried out within four pressure-drop ranges of 25–65, 45–105, 75–175, and 125–285 kPa under both rotor-speed stabilization and outlet-pressure stabilization modes. Based on the experimental results, second-order regression models were developed to describe the dependence of rotor speed on operating pressures and were subsequently used to estimate annual energy recovery. The results indicate that outlet-pressure stabilization provides higher energy recovery than rotor-speed stabilization across the investigated operating ranges. Depending on operating conditions, the estimated annual recovered energy ranged from 83 to 2265 kWh, which is sufficient to cover the auxiliary power demand of cabinet-type pressure-reduction stations and cathodic protection systems. The experimental validation presented in this study was performed using compressed air as the working medium. Therefore, the obtained quantitative results should be regarded as a laboratory-scale assessment of the feasibility of the proposed approach rather than a direct validation of a natural-gas expander–generator system. The results suggest the potential applicability of volumetric expander–generator regulators for energy recovery at small-scale gas pressure-reduction stations operating under variable flow conditions. Full article

Trillium camschatcense, a plant renowned for its ecological and medicinal value, is predominantly found in the temperate forests of East Asia. However, its habitat is increasingly threatened from climate change, habitat fragmentation, and intensified human activities. In this study, the Maxent (Maximum Entropy) model was used to assess the current ecological suitability of T. camschatcense based on historical climate data (1970–2000), and further simulate its potential distribution shifts under multiple future climate change scenarios to predict long-term habitat variation trends across northeast China.All modeling and spatial mapping analyses were performed using MaxEnt and ArcGIS 10.8.1 software. Drawing upon 93 known distribution points and 26 pertinent environmental variables covering climate, soil, and elevation, we built species distribution models for both present and future periods to pinpoint the crucial environmental factors influencing its distribution. Our findings revealed that elevation, soil nitrogen content, seasonal temperatures, annual precipitation, mean temperature during the coldest quarter, and mean diurnal temperature range were the primary factors influencing the distribution of T. camschatcense. Notably, highly suitable habitats were predominantly concentrated in Baishan City and the southwestern region of Yanbian Korean Autonomous Prefecture in Jilin Province. This insight offers valuable scientific guidance for the conservation planning, sustainable utilization, and potential introduction and cultivation of T. camschatcense. Furthermore, targeted conservation strategies can help identify climate refugia and protect climatically stable habitats for the long-term persistence and resilience of the species under continuous global warming. Full article

In 2018, over half of the world’s population lived in urban areas, and this figure is expected to continue to increase over the next 25 years. Water security in growing urban areas is becoming increasingly important. Current global warming can pose additional challenges for sustainable water resource management. In this study, the city of Krakow (Poland) and its water supply system were considered. The MK and Spearman tests were used to detect trends in the studied data and the residuals from the Ensemble Empirical Mode Decomposition (EEMD) method. The analyses indicate that for 1971–2020, significant increasing trends (p < 0.05) in annual air temperature (0.36–0.46 °C/decade) were accompanied by significant trends in annual precipitation, with differences in direction and intensity (approx. −8 and 30 mm/decade). Similarly, significant trends in annual river flow for the two main sources of drinking water for Krakow (the Raba and Rudawa rivers) differed in both direction and intensity (0.51 m∙s⁻¹ and −0.05 m∙s⁻¹, respectively). The study also examined trends for individual months of the year, which largely explained the observed annual trends. Furthermore, the results of cross-correlation and autocorrelation analyses suggest that the identified decreasing trend in the Rudawa flow may be partly related to the significantly reduced underground recharge in the Rudawa catchment. The information obtained in this work can be used for more realistic and sustainable water resource management and urban-water-security planning. Full article

The increasing penetration of renewable generation and flexible loads has made modern power systems operate under highly variable and diverse conditions. For power-system planning studies, static power-system analysis plays an important role in characterizing the security and stability behavior of these operating conditions. In such planning tasks, annual or long-term hourly datasets are often needed to capture temporal variations in renewable generation, load, and power-flow patterns, but performing power-flow-based static analysis for every operating condition can be computationally expensive, especially for targets that require repeated power-flow-based calculations. Therefore, an effective operating-condition reduction framework is needed to select a compact yet representative subset and reconstruct the overall static-analysis profile required for variation trends and distribution analysis. To address this problem, this paper proposes a problem-driven scenario reduction framework based on batch-attention-based self-supervision feature selection (A-SFS) for simplifying large-scale power-flow-based static analysis. Instead of clustering operating conditions only according to their geometric similarity in the original feature space, the proposed framework incorporates the downstream static-analysis target into the reduction process. Target values are first computed for only a small portion of the operating-condition dataset, and A-SFS is then used to learn target-relevant features and their importance weights. Based on the learned weighted feature space, all operating conditions are clustered using weighted K-means++, and the actual operating condition closest to each cluster centroid is selected as the representative scenario. The downstream target evaluation is then performed only on these representative scenarios, and their target values are assigned to the operating conditions within the same clusters to reconstruct the overall target-value profile of the full dataset. The proposed framework is validated on a yearly RTS-GMLC operating-condition dataset using two representative static-analysis targets, namely load margin and the minimum singular value of the power-flow Jacobian, ${\sigma }_{min}$. The results show that the proposed target-aware clustering framework can effectively reconstruct the overall static-analysis profile of the full operating-condition dataset while preserving the relative ranking of different operating conditions. In the best-M comparison, the proposed method achieves MAPEs of 19.56% for load margin and 12.85% for ${\sigma }_{min}$, with corresponding Spearman coefficients of 0.8380 and 0.8755, respectively. Full article

Dew condensation on passive collectors can supplement water availability across different climates, but its prediction remains uncertain because condensation depends on both atmospheric conditions and collector properties. This study evaluated a physically based model of dew condensation potential (horizontal condenser surface) using field observations from four sites: Helsinki (Finland), Maktau (Kenya), Ajaccio (Corsica, France), and Bordeaux (France). Simulations were primarily driven by ERA5 reanalysis data, while on-site weather station data were used for sensitivity analysis where available. Near-future dew behavior at the European sites was further examined using EURO-CORDEX climate data. The model reproduced the general timing and cumulative progression of condensation, but predicted yields were generally greater than observed yields, especially at Helsinki and Maktau. The best agreement was obtained by Bordeaux, where the experimental setup closely matched the model assumptions. On-site weather stations data improved agreement, highlighting the importance of site-specific nocturnal conditions. CORDEX simulations showed clear site differences, with Bordeaux having the highest and most stable projected condensation potential, Ajaccio frequent but low-intensity condensation, and Helsinki lower annual totals but comparable yield per dew night. The results show that the model was useful for comparing relative condensation potential across climates and identifying dew seasons, but accurately estimating the harvestable dew requires better representation of collector properties such as geometry and surface. Full article

Alkaline water electrolysis (ALK) is essential for renewable energy integration, yet traditional models using a fixed minimum operating power often overestimate low-load flexibility by neglecting state-dependent safety boundaries. This study develops an electro-thermal-mass multiphysics dynamic model that treats the transient hydrogen content in oxygen (H₂-in-O₂) concentration as a first-principles state variable. Based on a quasi-steady-state safety balance, a dynamic minimum operating power constraint is derived to replace empirical static limits. A key feature of this model is the explicit coupling of Arrhenius thermal diffusion and pressure-differential-driven permeation during load transients, allowing the safety threshold to respond to real-time system states. Year-round simulations of a 30 MW industrial system under a wind–solar time series reveal that thermal inertia, with a time constant of approximately 4.2 h, induces a sustained mismatch between low-power operation and high system temperature. Under high-temperature and rapid-ramp conditions, the dynamic safety lower bound reaches 28.2% of the rated capacity, exceeding the conventional 20% static threshold by 8.2 percentage points. This deviation results in 378.3 MWh of implicit curtailment and 60.5 h of additional downtime annually, leading to a green hydrogen production deficit of approximately 42.2 t/year. This research provides a theoretical foundation and technical reference for the optimal control and flexibility assessment of industrial-scale green hydrogen systems under fluctuating power supply conditions. Full article

Newhall navel orange, a major citrus variety in China, shows considerable variation in fruit quality across production regions. To investigate the key factors driving the geographical variation, this study systematically compared the quality of Newhall navel oranges from 13 production areas and analyzed the relationships between volatile metabolites and climate variables. Our results revealed pronounced regional differences in both fruit physicochemical properties and volatile profiles. Total soluble solids, titratable acid content, and peel color parameters (L*, a*, b*) were identified as the core physicochemical indicators most strongly associated with quality variation. Using headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS), 106 volatile organic compounds (VOCs) were identified, of which 56 were selected as potential differential markers via partial least squares discriminant analysis (PLS-DA). Correlation analysis and partial least squares regression (PLSR) revealed that annual mean wind speed (AMWS), mean diurnal temperature variation at the expansion stage (MDTV-ES), and mean wind speed, total sunshine duration, mean diurnal temperature variation at the degreening stage (MWS-DS, TSD-DS, MDTV-DS) were important meteorological factors related to volatile metabolism. The study clarified the geographical variations in physicochemical characteristics and volatile profiles of Newhall navel oranges, as well as the key climatic factors linked to volatile metabolism, providing a crucial theoretical basis for site-specific cultivation planning, demarcation of high-quality production areas, and targeted quality regulation of citrus varieties. Full article

Influenza B virus (IBV) represents a significant global health threat, contributing 20–30% of annual influenza cases and causing substantial morbidity and mortality across all age groups. Current seasonal vaccines demonstrate variable effectiveness, highlighting the urgent need for next-generation approaches that provide enhanced and sustained protection against both IBV lineages. Moreover, continuous antigenic drift of circulating viruses progressively reduces the match between vaccine-induced antibodies and contemporary strains, necessitating broad-spectrum protection strategies. This review discusses influenza B virus control strategies, encompassing both conventional approaches and emerging vaccine technologies. While antiviral therapy, epidemiological surveillance, diagnostics, and non-pharmaceutical public-health measures are integral components of influenza B control, the present review focuses specifically on vaccine-based strategies. By critically appraising the available evidence, this review evaluates the extent to which these strategies may improve the effectiveness of IBV vaccines and, in the longer term, inform the prospect of reducing the burden of—or potentially eliminating—influenza B virus, a goal that remains hypothetical and requires clinical validation. Full article

Porcine rotavirus (PoRV) has emerged as a primary pathogen causing viral diarrhea in pigs, resulting in significant economic losses. This study was conducted to systematically characterize the epidemiology and genotypic characteristics of PoRV in Guangxi, China. A total of 870 diarrheic pig samples were collected from Guangxi during 2020–2025. The qRT-PCR results indicated an overall PoRV-positive rate of 41.38% (360/870), and the annual positivity rate showed an overall upward trend. The genetic evolutionary analysis of the VP4, VP6, and VP7 genes indicated that PoRV predominantly belonged to the A group and the predominant P genotype observed was P[13] (76.83%), while the G genotypes were G5 (36.56%) and G9 (33.33%). The most prevalent genotype combinations were G9P[13]I5 and G5P[13]I5. CH-GXGL-PoRV-3151-2021, a PoRV strain isolated from positive samples, was identified via RT-PCR, qRT-PCR, whole-genome sequencing, and IFA. This strain was assigned the 11-segment genotype constellation G9-P[23]-I5-R1-C1-M1-A8-N1-T1-E1-H1 based on whole-genome sequencing. NSP1 and NSP2 showed high similarity to human rotavirus strains, whereas VP1–VP4, VP6, VP7, and NSP3–NSP5 showed high similarity to porcine rotavirus strains. This study indicates the widespread circulation of PoRV in Guangxi, with multiple G genotypes, including G9, G5, G4, G3, G2, and G26, being detected. The isolated G9P[23]I5 strain exhibits the same genotype as the strains that have become increasingly prevalent in recent years. This strain may represent a possible reassortant between porcine and human rotaviruses. This study offers significant insights into the epidemiology of PoRV and the prevalent genotypes in Guangxi, thereby supporting the development of targeted prevention strategies and novel vaccines. Full article

Research in quantitative paleohydrology shows that a phase of very high river discharge on the northern Eurasian plains in the late Pleniglacial (about 18–14 ka BP) was followed by a much less studied phase of reduced discharge and small-channel formation. To characterize this morphohydrological metamorphosis, we investigated the morphometry of small meandering paleochannels on floodplains at 132 river-valley sites in the Volga basin. On average, the widths and meander wavelengths of these paleochannels are approximately half those of modern channels. The ages of the paleochannels range from 10 to 4 ka BP. The hydrological regime of small mid-Holocene meandering rivers was reconstructed using morphometric relationships, principally the power-law relationship between bankfull channel width and mean maximum flood discharge and the relationship between maximum discharge and contributing basin area. The mean reconstructed daily maximum runoff depth for small catchments in the Volga basin during the snowmelt period in the mid-Holocene was about 5 mm/day, approximately half the modern value. The ratios between mean annual and mean maximum runoff depths in the mid-Holocene were estimated from modern regional analogues of the ancient climate, using climate models for the 6 ka BP time slice. Annual river runoff depths in the Volga basin in the mid-Holocene were then calculated from these analogue ratios and the daily maximum runoff depths. The mean annual runoff depth in small catchments was about 100 mm, almost half the current runoff in the Volga River basin. The annual Volga River runoff volume in the mid-Holocene was approximately 132 km³, compared with the current value of 250 km³. This decline in river runoff in the Volga basin resulted in a low stand of the Caspian Sea in the early–middle Holocene, with a calculated potential sea level of −65 to −79 m abs. Full article

In warm and humid tropical regions, balancing thermal comfort and energy efficiency presents a significant challenge due to high cooling demands. Strategies to reduce energy use and integrate renewable energy into buildings have increasingly focused on achieving self-sufficiency. Aligning with the United Nations Sustainable Development Goals 7 and 13, which call for access to sustainable energy and climate change mitigation, this study assessed the potential of facade-mounted solar photovoltaic (PV) systems to offset the cooling energy demand of buildings in the urban area of Quezon City, Philippines. A geospatial-computational workflow was developed utilizing QGIS 3.28 and Python 3.9 for LiDAR-derived 3D building model generation and hourly solar ray tracing. This workflow was used to estimate direct PV electricity generation and passive cooling effects from facade shading based on the ASHRAE radiant time series method. Results showed that east and west facades achieved the highest annual yields of up to 86 kWh/m² and cooling load reduction by up to 7.3% due to the shading effect. Techno-economic analysis found several setups commercially viable, particularly installations on east–west walls with minimal self-shading and limited obstruction, focusing capital on the most productive surfaces. These findings support vertical solar PV as a complementary solution in dense tropical environments. Full article