Search Results (8,843)

Existing thermal sensation prediction models typically examine the relationship between skin temperature and thermal sensation during cooling or heating seasons. However, due to significant fluctuations in indoor thermal environments during shoulder seasons and considerable individual variation in clothing preferences, traditional thermal sensation prediction models demonstrate poor predictive performance during shoulder seasons. This study aims to investigate the relationship between facial skin temperature and clothing insulation versus thermal sensation under shoulder seasonal conditions and to establish a predictive model for human thermal sensation influenced by clothing insulation. First, facial temperature data under different clothing conditions are collected online using infrared thermal imaging equipment. Subjective thermal sensations are obtained through questionnaires, enabling analysis of the influence of relationships among clothing insulation, facial temperature, and thermal sensation. Subsequently, correlation analysis is used to identify the facial temperature zones closely related to human thermal sensation. Finally, a random forest algorithm is employed to establish a thermal sensation prediction model. Research findings indicate that during shoulder seasons, the left and right cheeks and lips exhibit a higher correlation with thermal sensation. Due to variations in clothing insulation, thermal sensation models based solely on facial temperature characteristics demonstrate lower predictive accuracy and struggle to overcome interference caused by individual clothing differences. After incorporating clothing insulation as a key input feature parameter, the model’s Root Mean Square Error decreased from 0.869 to 0.533, representing a 38.7% improvement in prediction accuracy. This demonstrates that the clothing insulation parameter plays a crucial role in enhancing the precision of human thermal sensation prediction models during shoulder seasons. Full article

The increasing popularity of macroalgae products highlights their potential as a safe source of essential macro and microelements for consumers. This study characterized wild and farmed macroalgae elemental composition and assessed the presence of biotoxins to identify potential health risks. Wild and farmed macroalgae samples were collected throughout 2024–2025, from three aquaculture production sites along the Portuguese coast (Ria de Aveiro, Matosinhos, and Olhão). Samples were freeze-dried, compressed and using a micro-XRF spectrometer, elemental composition was assessed. Macroalgae species factor was the strongest driver of elemental composition, explaining over 80% variation in macro and trace elements. Origin did not showcase statistical significance for elemental composition. Seasonal differences, though relatively small in extent, significantly impacted redox-sensitive elements in macroalgae, namely copper and manganese. All elements stayed below 30% of the recommended dietary recommendations, except iron (ranging from 0.5% to 111.8% of UL%) and Mn (ranging from 0.1% to 101% of UL%). All samples revealed the absence of regulated marine toxins. Only traces of the non-regulated cyclic-imine toxin SPX1 were detected in samples of Fucus vesiculosus. All quantified elements do not represent any risk for human health, strengthening the safety of macroalgae from the Portuguese coast. Full article

Positioning, navigation, and timing (PNT) services require stable time transfer, but satellite-based PNT signals are vulnerable to interference, attenuation, and limited availability in constrained environments. Very-low-frequency (VLF) signals propagate over long distances in the Earth–ionosphere waveguide and can serve as a terrestrial complement to satellite-based timing systems. Their timing performance, however, is affected by propagation-delay variation, especially the diurnal component associated with changes in the effective ionospheric reflection height. This study presents a propagation-delay correction method for VLF timing signals based on a phase-variation model. The total delay error is separated into primary path delay, secondary propagation delay, and residual random error. The primary delay is calculated from the transmitter–receiver path, while the periodic secondary delay is corrected using the predicted phase variation. Historical Alpha observations recorded at Chongqing and Guilin were used to evaluate the correction performance. The results show that the corrected standard deviation is reduced to 2.0054–2.2500 μs for the Chongqing paths and 2.7987–4.4792 μs for the Guilin paths. The corrected root mean square error (RMSE) ranges from 2.1316 μs to 4.5641 μs across the six Alpha propagation paths. These results indicate that the proposed method can suppress the main diurnal propagation-delay component in the selected historical Alpha datasets, although further validation with contemporary and multi-season VLF observations is still needed. Full article

Using surface observations, ADTD lightning data, and radar reflectivity from April-September 2022–2024 in the Xi’an terminal area, this study classified severe convective events into four categories: ordinary thunderstorms, short-duration heavy precipitation, convective wind gust, and hail events. Their temporal variability, spatial distribution, life cycle characteristics, and propagation pathways were systematically analyzed. The results reveal significant differences among convective event types across multiple temporal and spatial scales. Convective wind gust events exhibited the strongest interannual variability, with a decrease of 44% from 2023 to 2024. Hail events occurred relatively infrequently, totaling only 16 cases from 2022 to 2024. Seasonally, convective wind gusts were concentrated in April-May, while ordinary thunderstorms and short-duration heavy precipitation events mainly occurred in July–August. Most events initiated during the afternoon and intensified toward evening, with short-duration heavy precipitation events showing a bimodal diurnal variation. Ordinary thunderstorms were dominated by short-lived events lasting 30–60 min, whereas heavy precipitation, convective wind gust, and hail events were primarily associated with long-lived convective systems exceeding 180 min. Spatially, severe convective weather generally initiated in the western part of the terminal area and propagated eastward. Lightning activity was more concentrated in the southeastern sector, indicating greater impacts on the SHX waypoint. Propagation paths were predominantly oriented toward the east-northeast. Full article

The atmospheric boundary layer (ABL) has strong diurnal variability, but routine radiosonde launches at 00:00 and 12:00 UTC cannot fully resolve its daily evolution. This study develops and evaluates a 13-year (2007–2019) hourly ABL profile dataset using Aircraft Meteorological Data Relay (AMDAR) observations from 42 selected European airports, and applies it to characterize airport-scale diurnal, seasonal, and regional variations in ABL structure. AMDAR-derived temperature and wind profiles were validated against collocated radiosonde observations by season, pressure layer, and airport–radiosonde distance. Errors decrease for shorter separation distances and lower-tropospheric layers. For separations < 50 km and pressures > 850 hPa, spring, summer, autumn, and winter RMSEs are 0.9/1.0/1.4/1.2 K for temperature, 1.7/2.0/1.9/1.9 m/s for zonal wind, and 1.4/1.6/1.9/1.6 m/s for meridional wind. Hourly AMDAR profiles reveal distinct diurnal ABL evolution at airport scale. Seasonal ABL height (ABLH) composites are mainly 250–900 m, with available nighttime and early-morning values of about 300–450 m and spring–summer afternoon maxima of 800–900 m at far-inland airports. Coastal airports show weaker daytime growth, mostly below 600–650 m. These results demonstrate AMDAR’s value as a supplementary profile dataset for characterizing European airport-scale ABL structure and diurnal variability. Full article

Landslides are a recurrent geohazard in Andean urban environments, where weak soils, intense seasonal rainfall, and unplanned urban expansion combine to increase slope vulnerability. In such settings, sustainable hillside management requires stabilization strategies that are both technically effective and environmentally compatible. This study evaluates the effect of root reinforcement by vetiver grass (Chrysopogon zizanioides) on slope stability in two representative soils from Loja, Ecuador: sandy silt (SM) and sandy clay (SC). A reduced-scale physical model with 30 days of root development was established, and consolidated–drained direct shear tests (ASTM D3080/D3080M-23) were performed to determine the shear strength parameters under bare and vetiver-reinforced conditions. These parameters were then incorporated into numerical slope stability analyses using Slide and PLAXIS 2D, considering three slope angles (30°, 45°, and 50°), six root-positioning configurations, and hydraulic conditions with and without a water table. Vetiver increased effective cohesion by 22.7% in sandy silt and 19.0% in sandy clay, while the internal friction angle increased by 21.8% and 12.2%, respectively. Across all modeled scenarios, vetiver produced a consistent improvement in the factor of safety. The most critical case, corresponding to sandy silt at 45° with a water table, increased from FS = 0.841 in the control condition to FS = 1.309 under the full-coverage configuration. Parametric sensitivity analysis yielded coefficients of variation between 4.97% and 7.03%, indicating a stable model response under controlled parameter perturbations. These findings support vetiver as an experimentally grounded and environmentally sustainable Nature-based Solution for slope stabilization and provide relevant evidence for sustainable management of hazard-prone urban hillsides in vulnerable Andean settings. Full article

Accurate evapotranspiration (ET) estimation is critical for sustainable water management in arid environments. This study estimates actual ET over the Al-Hofuf region, Al-Ahsa Oasis, Saudi Arabia, during 2024 using a cloud-based remote sensing approach. Landsat 9 Level-2 imagery was combined with ERA5-Land meteorological data to quantify spatial and temporal ET variations across a 25 km buffer. Vegetation dynamics were characterized using the Normalized Difference Vegetation Index (NDVI) to derive crop coefficients (Kc) within a Kc–ET₀ framework, where reference ET (ET₀) was obtained from ERA5-Land potential evaporation. All processing utilized Python (Version 3.14) on Google Colab and Google Earth Engine for scalable computation. Eighty-eight cloud-free Landsat 9 scenes were processed following cloud and shadow masking. Mean NDVI, Kc, and daily ET values were compiled into a comprehensive time-series dataset. Model performance was evaluated through cross-validation with MODIS MOD16A2 and internal consistency checks, demonstrating strong statistical agreement (R² = 0.82, NSE = 0.71, PBIAS = +8.3%). Results revealed pronounced seasonal variability closely linked to vegetation activity and atmospheric demand, with peak ET occurring during summer months (June–July: 7.2–7.5 mm day⁻¹) and minima in winter (January–February: 2.0–2.6 mm day⁻¹). Findings demonstrate that cloud-based techniques provide reliable, cost-effective ET monitoring in data-scarce, groundwater-dependent regions. Validation confirms Kc-ET₀ estimates reliably capture spatial and temporal patterns, supporting practical irrigation management applications. This approach aids precision irrigation and long-term water sustainability planning in Al-Hofuf, contributing significantly to national water conservation objectives under Saudi Arabia’s Vision 2030 and National Water Strategy. Full article

Urban water–vegetation systems play an important role in mitigating surface heat, yet the spatial decay structure of shoreline-mediated cooling remains insufficiently quantified in high-density urban environments. Focusing on seven urban water bodies within the heritage buffer zone of the Beijing Central Axis, this study combines 120 m shoreline segmentation with 0–600 m ring-buffer analysis to examine seasonal shoreline cooling patterns using Landsat-derived land surface temperature (LST) and Sentinel-2 vegetation information. The results show that shoreline cooling followed a layered spatial decay structure rather than a single fixed-distance effect. The most rapid LST increase generally occurred within the first 200 m from the shoreline, forming a nearshore rapid-gradient zone, while cooling distance (CD) represented a broader outward reach of detectable cooling. Cooling intensity (CI) was strongest in summer, whereas the seasonal differentiation of CD was weaker than that of CI. Vegetation greenness was generally negatively associated with LST, especially in the near and middle shoreline zones, and this relationship was supported by the same-date Landsat NDVI robustness test. After controlling for built-up intensity and waterbody-specific differences, shoreline distance, vegetation greenness, and built-up intensity mainly operated as additive spatial predictors of LST, while the NDVI × Distance interaction provided limited additional explanatory power. These findings suggest that shoreline cooling in high-density heritage urban areas should be understood as a spatially differentiated interface process, and that planning should prioritize the nearshore rapid-gradient zone while managing the broader shoreline transition area according to local vegetation and built-up conditions. Full article

Biological invasions are among the main threats to freshwater biodiversity, yet ecological patterns associated with assemblage structure and high relative abundances of non-native fishes in spring ecosystems remain insufficiently documented. We evaluated seasonal variation in community composition, reproductive traits, and trophic interactions in La Zarcita springs, part of the Natural Protected Area Laguna de Zacapu, central Mexico. Bimonthly sampling was conducted, including stomach content analysis and reproductive trait assessment. A total of 14 fish taxa were recorded (seven native and seven non-native), with the assemblage numerically dominated by Oreochromis niloticus (30%), Pseudoxiphophorus bimaculatus (24%), and Xiphophorus hellerii (14%). Overall diet composition did not differ significantly between taxa classified as native and non-native (PERMANOVA, p > 0.05), consistent with overlap in resource use within the assemblage. Exploratory assemblage-level analyses detected differences in omnivory index values among taxa grouped according to species origin (LMM, p < 0.05). Reproductive analyses detected variation in fertility values (GLMM, p < 0.05), reproductive activity (Wilcoxon test, p < 0.05), gonadosomatic index values, and Fulton’s condition factor values (LMM, p < 0.01) among taxa within the assemblage. Physicochemical variables varied seasonally but were not significantly associated with trophic composition, condition factor values, or reproductive traits in the statistical analyses performed. Overall, the results document variation in reproductive characteristics and trophic patterns among taxa within this urbanized spring system and highlight the value of assemblage-level ecological studies for understanding fish community structure in small freshwater habitats. Full article

Tropical estuaries are highly productive yet increasingly threatened by natural and anthropogenic pressures, necessitating robust ecological assessments for sustainable management. This study assesses the spatio-seasonal distribution of macrobenthic assemblages and evaluates the ecological health of the Sangu River estuary based on their bioindicator potential. Sediment samples for macrobenthos analysis were collected during three seasons (pre-monsoon, monsoon, and post-monsoon) from nine stations across three estuarine zones influenced by sedimentation, aquaculture, and terrestrial runoff. We employed microbenthic diversity indices, multivariate analyses, the AZTI’s Marine Biotic Index (AMBI), and multivariate-AMBI (M-AMBI) to evaluate the ecological health status of the study area. Our study recorded 13 taxa, dominated by Nereididae (40.90%), Mysidae (14.29%), and Capitellidae (10.20%). Macrobenthos diversity (Shannon diversity) ranged from 0.80 to 1.22, and abundance showed negative correlations with salinity (r = −0.29) and silt (r = −0.22), and a positive correlation with dissolved oxygen (r = 0.29). Analysis of Similarities (ANOSIM) indicated that seasonal variation was the primary driver of community structure (p < 0.001). AMBI classified most stations as having good to moderate ecological status, while M-AMBI indicated moderate disturbance across seasons, with elevated proportions of opportunistic taxa (EG V: 14.4–32%) reflecting persistent anthropogenic stress. This study provides the first empirical ecological baseline for the Sangu River estuary and highlights the applicability of family-level AMBI assessments in data-limited tropical estuarine systems. Full article

Lentils constitute a strategically important crop within sustainable agricultural systems, particularly in the context of rising global demand for plant-based protein sources. In Switzerland, approximately 95% of lentil seeds are imported, underscoring the untapped potential for domestic production. This study systematically evaluated the performance of multiple lentil genotypes, alongside optimal seeding densities and growing seasons, through a series of field experiments conducted over five years. In addition, a sensory evaluation was performed on 12 selected genotypes to assess consumer-relevant quality traits. The findings revealed substantial variability in yield among genotypes, ranging from 0.9 to 1.6 t/ha; however, interannual variation exerted a more pronounced influence, with yields fluctuating between 0.1 and 2.0 t/ha. Notably, autumn-sown lentils achieved yields of up to 2.7 t/ha in three out of four growing seasons, even among genotypes lacking full winter-hardiness, indicating significant production potential under appropriate management conditions. Optimal plant densities were identified within the range of 180–240 plants/m². From an economic standpoint, higher seeding densities appear justifiable, as the increased seed costs are offset by corresponding gains in yield. Since intercropping of lentils with oats did not negatively affect grain yield nor the thousand kernel weight, the benefits of this cropping system are highlighted. Sensory analysis demonstrated statistically significant differences in attributes such as mealiness and juiciness, leading to the classification of genotypes into three distinct sensory clusters. Despite these differences, overall sensory variation was relatively limited, suggesting that genotype selection may be guided primarily by agronomic performance, climatic adaptability, and winter-hardiness, as well as by market preferences for seed colour and size. Collectively, these results highlight the potential of autumn sowing as a viable strategy to enhance lentil production and reduce the risk of crop failure in Swiss agricultural systems. Full article

Against the backdrop of the global advancement of carbon neutrality goals and the energy transition in the building sector, zero-carbon buildings have emerged as pivotal enablers for achieving carbon neutrality in the construction industry. The rule-based scheduling of energy storage systems (ESS) is critical to enhancing energy efficiency and economic performance of buildings. This study takes the Jinan Zero-Carbon Operation Center Project in Shandong Province as the research object, developing a comprehensive technical framework covering the entire process from design to operation, and investigates the rule-based design and ESS scheduling strategies in response to Shandong’s newly implemented seasonal time-of-use (TOU) electricity pricing policy. First, core performance indicators are defined in accordance with national evaluation standards for zero-carbon buildings. Hourly building energy loads and photovoltaic (PV) generation profiles are simulated over a full year, which serves as the basis for determining the optimal PV installed capacity and ESS sizing. Second, an ESS scheduling strategy integrating PV generation forecasting and the seasonal TOU electricity price structure is formulated, with clear charging and discharging logic defined. Finally, the operational and economic performance of different scheduling modes are evaluated and compared through case studies. The results show that the annual PV generation ratio reaches 101.38%, with a self-consumption rate of 73% and a self-sufficiency rate of 72%, all meeting the core requirements for zero-carbon buildings. Compared with the conventional real-time scheduling mode (Mode 1), the proposed optimized mode (Mode 2) that incorporates TOU pricing and PV forecasting achieves an annual operational cost saving of 367,349 CNY, corresponding to a reduction of 47.02%. Distinct seasonal variations in core indicators are also observed: the PV generation ratio is lower in summer and winter but the self-consumption rate is higher, with the opposite trend in spring and autumn. The proposed technical framework and scheduling strategy provide practical guidance for the design and operational optimization of zero-carbon buildings and offer decision-making support for ESS operation under TOU electricity pricing policies. Full article

Climate change poses an increasing threat to the functionality of forest transportation infrastructure, particularly in northern regions where seasonal access and ground conditions are critical for wood mobilization. The objective of this study was to assess how projected changes in temperature and precipitation may compromise accessibility to forest resources. In addition, it aimed to develop targeted adaptation recommendations to support resilient transportation systems. These actions are essential to ensure the continuity of wood supply under future climatic conditions. Climate projections were extracted from the climatedata.ca platform based on the CMIP6 (CanDCS-M6) model under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Using a GIS-based workflow, projected temperature and precipitation data were spatially matched to the selected Forest Management Units (FMUs) in Quebec, Canada, and the study area was divided into three latitudinal subregions to capture spatial temperature variation. Classified road network maps were then overlaid with projected climate data for 2020, 2040, 2060, and 2080 to evaluate winter road usability, precipitation-related exposure of road classes, and changes in effective winter road density. Results showed a consistent shortening of the winter road operational period under all scenarios, with the most severe reductions under SSP5-8.5. In highly affected areas, the winter road usability window may decrease from 90 days in 2020 to only 21 days by 2080. Increased precipitation is also expected to affect numerous road segments, raising risks of erosion, sedimentation, and loss of accessibility. A reduction of approximately 7% in effective winter road density is projected across the study area under the high-emission scenario (SSP5-8.5), reflecting the most severe impact of future temperature increases. Based on these findings, targeted road upgrades, climate-informed infrastructure design, and alternative access planning are proposed to help sustain wood flow and support year-round forest operations under future climatic conditions. Full article

Tomato yellow leaf curl virus (TYLCV) is one of the most destructive viral diseases causing severe yield losses in tomato production worldwide. This study investigated the effects of TYLCV infection on plant growth, photosynthetic physiological responses, and yield formation in greenhouse-grown tomatoes and evaluated the applicability of physiological trait-based yield prediction models. Two large-fruited tomato cultivars widely cultivated in Korean protected horticulture systems, ‘Daphnis’ and ‘Pink Star’, were inoculated with TYLCV under greenhouse conditions, and their growth, physiological responses, and yield characteristics were compared under high- and low-temperature growing seasons. TYLCV infection significantly reduced leaf length, leaf width, and leaf area index (LAI), and decreased both flowering truss number and fruit-setting truss number, resulting in reduced total yield. Physiological analyses showed that infected plants exhibited decreases in the OJIP fluorescence rise curve and Fv/Fm values, indicating a reduced photochemical efficiency in photosystem II. In addition, A–Ci response curve analysis revealed a reduction in net photosynthetic rate, suggesting limited carbon assimilation capacity. Total yield showed significant positive correlations with maximum net photosynthetic rate (Amax), Fv/Fm, and Ci300. GGE and GT biplot analyses further indicated that yield was closely associated with photosynthetic performance and canopy development traits. A multiple regression model based on physiological traits and virus infection status explained a significant proportion of the variation in tomato yield (R² = 0.367), indicating that TYLCV infection acts as a key limiting factor for yield reduction. These findings demonstrate that TYLCV infection restricts tomato productivity through reduced photosynthetic efficiency and altered canopy structure. Moreover, physiological trait-based yield prediction approaches may provide a useful framework for evaluating productivity under viral infection conditions and for developing data-driven crop management strategies in greenhouse tomato production systems. Full article

The progressive degradation of natural habitats, driven by anthropogenic pressures and climate change, constitutes one of the most serious threats to biodiversity. Peatland ecosystems, along with the valuable plant species associated with them, are particularly vulnerable to these processes. Salix lapponum, a glacial relict species, is undergoing a drastic decline in both its range and population size across Poland and Europe. This emphasizes the need for the implementation of conservation measures, including species translocation, as well as the development of effective methods for monitoring plant condition following introduction. The aim of this study was to evaluate the usefulness of selected physiological indicators for the rapid and reliable assessment of plant condition in active conservation efforts. The experimental material consisted of S. lapponum plantlets derived from tissue culture, which were introduced into five experimental sites in eastern Poland, differing in habitat conditions. Over two growing seasons, chlorophyll fluorescence parameters (F₀, F_m, F_v/F_m), the content of photosynthetic pigments and anthocyanins, relative water content, guaiacol peroxidase activity, and the presence of reactive oxygen species were analyzed. The results revealed clear seasonal variability in most of the studied physiological parameters, as well as their differentiation across habitat conditions. The highest sensitivity to environmental changes was observed for indicators related to photosynthetic performance (F_v/F_m), tissue hydration status (RWC), and enzymatic activity. Declines in photosystem II efficiency at the beginning of the growing season, reflected in F_v/F_m values decreasing to 0.47–0.49 indicate transient stress conditions in plants. Simultaneously, variation in relative water content (52–90%) and peroxidase activity reflects differences in water availability and the intensity of environmental stress across habitats. The findings confirm that selected physiological indicators can serve as effective tools for the early monitoring of plant condition and for assessing the success of S. lapponum translocation. Full article