Search Results (731)

Accurate segmentation of clouds and cloud shadows in optical remote sensing imagery is an indispensable preprocessing step for downstream land-surface observation tasks. However, existing methods strike different trade-offs between local detail preservation and global context modeling, yet they still exhibit two major limitations: insufficient interaction during the dual-branch encoding stage, and decoder-side multi-scale fusion that applies uniform operations to all spatial locations, making it unable to distinguish boundary regions, such as thin cloud boundaries and cloud shadow contours, from homogeneous regions, such as thick cloud interiors. To address these issues, we propose SpecGateNet, a fusion network guided by spectral information from a frequency-domain perspective. The core idea is that the Fourier amplitude spectrum of deep features summarizes how much energy is carried by different spatial frequencies, where high-frequency components typically correspond to rapidly varying regions such as boundaries and textures, whereas low-frequency components are more closely associated with smooth regions. Building on this insight, we use an amplitude-derived, phase-free spectral energy cue constructed from the amplitude spectrum, and integrate it with a learnable gating generation network to produce spatially adaptive fusion modulation signals. SpecGateNet is built upon a CNN-Swin Transformer dual-branch encoder and consists of three key components: a Cross-Feature Fusion module (CFF) that enables stage-wise bidirectional interaction, a frequency-domain dynamic filtering bottleneck that enhances global context through input-adaptive frequency-domain filtering, and a Spectral-Guided Fusion decoder (SGF) that generates spatial gates from the amplitude spectrum to adaptively balance high-level semantics and low-level details. Together, the bottleneck filter and SGF constitute a spectral utilization framework that operates at both the encoder and decoder sides. Using only RGB inputs without relying on infrared auxiliary bands, SpecGateNet achieves the highest mIoU among the compared general-purpose baselines under a unified experimental protocol on three public datasets, namely CloudSEN-12, SPARCS-Val, and 38-Cloud, with mIoU scores of 77.80%, 76.75%, and 93.30%, respectively, outperforming the second-best method by 1.33, 5.26, and 1.44 percentage points. Ablation studies confirm that the spectral modules account for 70.1% of the total performance gain, with SGF contributing the largest single-step improvement among individual modules (+1.22%). Full article

In wheat threshing, reducing total grain loss and energy consumption is crucial for both economic and sustainable food security. This study investigates the effects of threshing drum type (straight and helical row), drum peripheral speed (36.73–48.98 m s⁻¹), and drum-concave clearance (35–50 mm) on total grain loss and specific fuel consumption in a stationary threshing machine using a full factorial design. The optimum machine settings (drum type, peripheral speed and drum–concave clearance) that simultaneously minimize these two outputs were then determined. We systematically compared three surrogate modelling approaches—Response Surface Model (RSM), Gaussian Process Regression (GPR), and Artificial Neural Network (ANN)—to identify the most effective method for small-dataset optimization in threshing machine design. The best model was selected through cross-validation, and optimization was performed using the NSGA-II multi-objective genetic algorithm. GPR yielded the highest prediction accuracy for both outputs (R² in prediction data: 0.99 for total grain loss and 0.91 for specific fuel consumption). Multi-objective optimization revealed a conflict between the two objectives; the best balance was achieved for the helical drum at a peripheral speed of approximately 41.5 m s⁻¹ and a drum–concave clearance of 50 mm (predicted total grain loss approximately 3.7%, specific fuel consumption approximately 2.98 mL kg⁻¹). Compared to the straight-row drum, the helical drum provided lower losses and fuel consumption, as well as approximately 3.5 times wider safe operating range. It should be noted that this optimum was predicted by the surrogate model and agreed closely with the best measured treatment; it was not confirmed by an independent validation experiment. The results demonstrated that combining a surrogate model with a genetic algorithm is an effective tool for optimizing threshing machine parameters. Full article

Diet represents a key determinant of the body’s acid–base balance because foods are metabolized into non-volatile acids or bases. An increase in dietary acid load can elicit low-grade metabolic acidosis, which has been associated with systemic inflammation and the risk of adverse cardiometabolic conditions, including obesity. Potential renal acid load (PRAL) and Net Endogenous Acid Production (NEAP) represent the major markers of dietary acid load. The aim of this secondary analysis was to compare the acid load of four different diets and investigate its association with Body Mass Index (BMI) in a sample of the general population. In an online survey, the INVITA study, four dietary patterns (meat-eaters, fish-eaters, lacto-ovo-vegetarians, and vegans) were compared for their corresponding PRAL and NEAP values, and the associations of both parameters with BMI were evaluated. Multiple linear regression models were progressively adjusted for dietary pattern, energy intake, age, sex, physical activity, smoking status, and education level. The stepwise decrease in animal food consumption across the four dietary patterns was associated with a progressive reduction in dietary acid load, with vegan participants showing the lowest values. While PRAL did not prove consistently associated with BMI in this cohort, NEAP remained significantly associated with BMI even after full adjustment for lifestyle confounders (β = 0.032, p = 0.00013). However, because NEAP includes an anthropometric component based on body surface area, this association should be interpreted cautiously, as it may partly reflect mathematical coupling rather than a purely diet-derived effect. PRAL should be considered the more diet-specific marker, while NEAP represents a composite index combining dietary acid load and anthropometric scaling. Because PRAL and NEAP do not account for protein origin, future studies should assess whether diet-specific reference ranges could improve their comparisons for dietary patterns including mostly or exclusively plant protein. Full article

Background: Infrared (IR) radiation constitutes the dominant component of the energy reaching the Earth’s surface and plays a significant role in the photochemical and thermal processes occurring in the skin. The aim of this study was to evaluate the photoprotective potential of selected cosmetic ingredients—ferulic acid, citrus pectin, and dextran—against IR radiation using the directional hemispheric reflectance (DHR) method in an ex vivo model. Methods: Formulations based on an amphiphilic carrier (Lekobaza) containing various concentrations of the tested substances were developed, and their optical and thermal properties were evaluated. Results: The results showed that the application of all formulations led to a statistically significant reduction in reflectance in the near- and mid-infrared range, indicating an increase in the absorption of radiation energy within the formulation layer. The strongest absorption effect was observed for ferulic acid, which—in addition to its antioxidant properties—exhibits the ability to absorb IR energy and dissipate it as heat. Pectin and dextran formed a water-binding hydrocolloid matrix on the surface, acting as a selective “water filter” for long-wavelength radiation (IR-B and IR-C). At the same time, all the tested systems increased the surface’s thermal emissivity, which promotes more efficient dissipation of absorbed energy through radiative cooling and may support the skin’s natural thermoregulation. Conclusions: The obtained data indicate that protection against IR radiation should not be defined solely as the physical reflection of radiation, but as a complex process of managing the skin’s energy balance, encompassing surface absorption, heat dissipation, and the neutralization of biological effects. The results support the development of hybrid photoprotective systems combining antioxidant and thermoregulatory mechanisms to prevent thermal aging-related changes. Full article

Coral reefs are typical ecosystems of high diversity and productivity, but they are facing significant degradation in their structure and function due to the dual stresses of climate change and human activities. To uncover the trophic structure, energy flow, and environmental driving mechanisms of nearshore coral reefs in Hainan, this study constructed mass balance models for five regions, Sanya, Changjiang, Lingao, Wenchang, and Wanning, using Ecopath with Ecosim, and conducted quantitative analysis in conjunction with satellite environmental monitoring data. The results showed that the trophic levels of functional groups in different ecosystems ranged from 1.00 to 5.00, with Sanya and Changjiang having the highest trophic levels (4.505, 4.656), higher than Lingao, Wenchang, and Wanning (3.776–3.924). The system average trophic transfer efficiency ranged from 15.98% to 30.25%, generally higher than the classic Lindeman 10% rule, with Changjiang being the highest (30.25%) and Lingao the lowest (15.98%). In terms of material cycling, the energy utilization efficiency of primary trophic levels was low, with a large amount of energy retained as detritus at lower trophic levels; Sanya and Changjiang showed more complete detritus chain energy cycling, with Finn cycling indices reaching 7.69 and 2.53, respectively, indicating higher maturity. Keystone analysis identified zooplankton, corals, and medium carnivorous fish as key functional groups with a decisive impact on system stability. Environmental correlation analysis revealed that particulate inorganic carbon (Pic), light diffuse attenuation coefficient (Kd), chlorophyll-a concentration (Chl_a), and sea surface temperature (Sst) were the main regulating factors, among which Pic showed a significant peaked relationship with the total system throughput, total biomass, and total production, with an optimal range of 0.0050–0.0075 mol/m². Overall, the material cycling and energy flow states of the Sanya and Changjiang coral reef ecosystems were stronger than those of Lingao, Wenchang, and Wanning, with lower fishing pressure in the former contributing to a more complex food web and enhanced community structural stability. This study provides the first systematic quantitative assessment of food-web structures across five distinct nearshore coral reef regions in Hainan, introducing an early-warning threshold for particulate inorganic carbon that offers direct, actionable reference for regional ecosystem-based management. Full article

Improving daylight performance in heritage hotels is essential for enhancing comfort, quality, and energy efficiency, especially in hot-desert climates where solar availability must be balanced with glare and overheating risks. However, façade preservation requirements limit conventional daylighting interventions, creating a need for climate-responsive and conservation-compatible solutions. This study investigates daylight optimization strategies for the Transatlantique Hotel in Biskra, Algeria, using Climate-Based Daylight Modelling (CBDM). The methodology combines three-dimensional modelling, in situ material characterization, and Radiance-based simulations with ClimateStudio version 2.3. Daylight performance was assessed using Spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), Useful Daylight Illuminance (UDI), and Daylight Factor (DF). Tested scenarios included improved glazing transmittance, increased surface reflectance, and tubular daylighting devices (TDDs). Results show that the existing configuration provides insufficient daylight in guest rooms, with average illuminance in poorly performing rooms ranging from 140 to 310 lux. Material-based optimization increased Room 210’s sDA from 3.9% to 62.3%, representing an approximately +1497% relative improvement, while UDI reached 58.6%. TDDs produced the strongest improvement: Room 110 sDA increased from 11.8% to 82.4% (+598%), while ASE decreased from 10.6% to 0.0%; Room 310 sDA increased from 31.2% to 100% (+221%), while ASE decreased from 16.9% to 0.0%. The novelty lies in integrating material-based and TDD strategies under strict façade-preservation constraints in a hot-desert heritage hotel. Full article

Efficient thermal management of high-power electronic components has become a critical engineering challenge as power densities grow and device geometries shrink. Conventional solutions based on passive heatsinks and mechanical fans are increasingly inadequate in applications where noise, reliability, and compactness are paramount. This paper presents a comprehensive Computational Fluid Dynamics (CFD) investigation of ionic wind—an Electro Hydro Dynamic (EHD) phenomenon in which a corona discharge between asymmetric electrodes generates a directed airflow without any moving part—as an energy-efficient alternative for cooling high-power electronics. A fully coupled 2D Multiphysics model is developed in COMSOL Multiphysics, integrating electrostatics, ion transport (Nernst–Planck), Navier–Stokes fluid dynamics, and convective heat transfer. The 2D formulation, while computationally efficient and consistent with prior EHD modeling studies, neglects lateral jet spreading inherent to a real three-dimensional needle configuration and is therefore expected to overestimate peak impingement velocities; quantitative comparisons with experimental temperatures are interpreted with this limitation in mind. The study focuses on a needle–collector configuration applied to a heated aluminum plate representative of a high-power electronic component such as a Light Emitting Diode (LED), a power transistor, or a microprocessor die. Simulation results are indirectly validated against experimental data obtained by Schlieren optics on a high-power (Chip-On-Board) COB LED system. The ionic wind reduces the maximum surface temperature by 8.1 K and substantially attenuates the central hotspot, redistributing heat laterally. A systematic parametric study reveals that applied voltage and needle height above the heat source are the dominant design parameters, while an energy balance shows that the EHD jet directly evacuates approximately 1.8% of the generated heat—acting primarily as a surface convection enhancer rather than a bulk heat extractor. These findings provide quantitative design guidelines applicable to any power electronic component cooled by an EHD system. Full article

Passive solar shading must balance energy saving, daylight availability, glare control, and thermal comfort under contrasting climates. This study develops and validates a lightweight, interpretable light-thermal-energy coupling framework for early-stage shading optimization in building retrofits and new construction. It addresses two questions: how shading geometry, envelope performance, and thermal inertia should adapt to hot low-latitude and cold high-latitude regions, and how their coupled performance can be quantified. The framework combines solar geometry, the Perez radiation model, surface irradiance calculation, indoor ray tracing/voxel illuminance simulation, daylight glare probability (DGP) assessment, and a 6R3C (6-Resistance, 3-Capacitance) transient thermal network. A full-factorial matrix of 120 design combinations was evaluated using shading scale, glazing performance, envelope thermal resistance, and thermal mass as variables, with energy use, thermal response, daylight availability, and DGP as objectives. Results show climate-dependent thermal inertia: it stabilizes indoor temperature in cold regions but increases heat accumulation in hot regions. The optimal schemes satisfy visual comfort (DGP < 0.40) and achieve energy savings up to 44.2% for retrofits and 50.0% for new buildings in hot regions, and 14.6% in cold regions. The framework provides transparent decision support for climate-adaptive, low-carbon building design and complements EnergyPlus, TRNSYS, and Radiance. By supporting energy-efficient retrofits and climate-responsive new construction, the proposed approach contributes to sustainability by reducing dependence on mechanical heating and cooling, improving operational resource efficiency, and maintaining indoor thermal and visual comfort. Full article

Pumped-storage hydropower (PSH) remains the main grid-scale energy storage technology in Europe, yet much of the fleet is ageing and requires periodic verification against current geotechnical standards. The Dychów plant (88 MW, western Poland), in service since the 1930s and classified as national critical energy infrastructure, has a documented history of surface mass movements, including a 1997 landslide on the frontal dam. To reassess its condition, two earthen sections were analysed: lateral section of the frontal dam of the upper reservoir and the embankment of the derivation channel. Electrical resistivity tomography (ERT) profiles, measured using a gradient array in 2023 and further detailed in 2024 along the same GNSS-fixed lines, imaged the internal structure of both sections. The resistivity cross-sections, verified against shallow control boreholes and archival geological data, supplied the geometry of the finite-element (FEM) models in ZSoil: the confirmed layer boundaries became the material zones, and piezometric observations set the groundwater boundary conditions. The safety factor SF was then computed with the shear-strength reduction technique for four calculation variants and two groundwater scenarios per section. The resulting SF equals 1.75 for the side section of the frontal dam area and ranges from 1.80 to 2.10 for the channel embankment. A parametric reduction in the friction angle of saturated medium sand gives limit values of φ = 12.3° (dam) and φ = 20.3° (embankment), which are clearly below realistic in situ values. Overall, both structures meet the SF ≥ 1.50 requirement for Class I hydraulic structures. The ERT-to-FEM workflow offers a non-invasive and repeatable tool for the periodic reassessment of ageing PSH infrastructure, which continues to balance variable renewable generation. Full article

The lubrication performance of high-speed transmission systems directly affects mechanical power consumption and operational reliability. During high-speed oil-stirring lubrication, strong gas–liquid interfacial shear, liquid-film deformation, droplet splashing, and oil-mist transport generate an unsteady multiphase turbulent flow field. Conventional continuum-based numerical methods often face difficulties in resolving interface breakup and transient turbulent dissipation under high-speed rotational excitation. To address this problem, this study develops a coupled Lattice Boltzmann–Large Eddy Simulation (LBM–LES) method for oil–air two-phase flow in a high-speed oil-stirring lubrication system. The D3Q27 discrete velocity model, cumulant collision operator, WALE subgrid-scale model, free-surface tracking, and local grid refinement are integrated to analyze free-surface deformation, oil-mist evolution, and power-loss characteristics. Taking a notched toothless oil-stirring disk as the reference configuration, the effects of oil immersion depth and disk topology on gas–liquid phase distribution, oil-mist coverage, power consumption, and vortex-induced energy dissipation are investigated. The results indicate that oil immersion depth has a nonlinear influence on lubrication performance and power loss. Among the investigated cases, an immersion depth of 20 mm provides a favorable balance between upper-region oil-mist coverage and lower-region oil-pool stability. At this depth, the notched disk exhibits directional oil delivery and relatively low power consumption, whereas the double-rhombus structure expands the oil-mist coverage but increases the average power consumption to approximately 175 W. These findings provide numerical support for balancing oil-mist coverage, mechanical power consumption, and disk topology design in high-speed transmission lubrication systems. Full article

In the leveling process of ultra-high-strength steel plates, sample scarcity—driven by high prototyping costs and small-batch production—coupled with a narrow and unevenly distributed feasible region due to high yield-to-tensile ratios and limited ductility, impedes the balanced optimization of plate shape quality and energy consumption. To address this issue, this paper develops an optimization framework for the balanced trade-off between these two objectives. First, a high-precision response surface model based on Box–Behnken experimental design and finite element simulation was constructed using initial wave height, entry roll reduction, exit roll reduction, and leveling speed as key process parameters; peak residual stress difference (characterizing potential sheet quality) and leveling energy consumption as co-optimization objectives; and post-leveling flatness as a constraint. Next, by introducing the NSGA-II multi-objective genetic algorithm, the Pareto optimal solution set for the quality and energy efficiency objectives was obtained, clearly revealing the trade-off relationship between the two; furthermore, the TOPSIS decision-making method was employed to select the comprehensive optimal process scheme that achieves a balance between quality and energy efficiency from the Pareto solution set. An adaptive recommendation curve for the leveling process parameters of MS1500 ultra-high-strength steel plates was established, covering an initial wave height range of 10.5–14.6 mm, thereby enabling intelligent parameter matching based on different incoming material conditions. Finally, industrial validation demonstrated that this optimized scheme significantly reduced leveling energy consumption while ensuring that post-leveling flatness meets the high-quality requirement of less than 3.5 mm·m⁻¹. This achieves a balanced optimization of quality and energy efficiency. This study provides a reliable theoretical basis and practical engineering solution for the efficient and environmentally friendly leveling production of ultra-high-strength steel. Full article

This paper presents an optimization-based framework for active vibration control of rotor bearing systems using external surface-bonded piezoelectric patches. The rotor bearing system is modelled using the Finite Element Method (FEM), enabling the coupling between the shaft and the flexible piezoelectric actuators. A Linear Quadratic Regulator (LQR) is adopted to achieve optimal feedback control considering the balance between vibration reduction and control effort. The central contribution of this work is a comprehensive actuator placement optimization of the axial and angular position of the piezoelectric patches along the shaft. Firstly, axial positions are selected by maximizing a multimodal weighted Modal Strain Energy (MSE) criterion over a selected number of bending modes. In the second stage, which constitutes the main novelty of this work, the angular position of each pair of bonded piezoelectric patches is optimized. Each piezoelectric pair generates control moments at each extremity of the patch. The influence of the angular separation between independent piezoelectric pairs bonded at different axial locations is investigated through an iterative optimization framework. The optimized actuator placements are subsequently employed within an LQR-based active vibration control framework. The parameters of the controller are selected using a Genetic Algorithm (GA). Numerical simulations are performed on a bi-disk flexible rotor bearing system. The results of the numerical simulations demonstrate that the combined axial-circumferential optimization significantly enhances the controllability of the rotor system and improves the multimodal vibration suppression capability, achieving an improvement of approximately 93%. The proposed methodology offers a physically meaningful and computationally efficient framework, guaranteeing symmetric and effective vibration control. Full article

Steam injection is an energy-intensive enhanced-oil-recovery method for high-viscosity reservoirs, and its performance is controlled by coupled heat delivery, steam condensation, temperature-dependent viscosity reduction, mobility change and reservoir filtration response. This study develops an experimentally validated physics-motivated residual-learning framework for forecasting oil production and selecting thermally rational steam-supply regimes. The model combines a physics-motivated semi-empirical baseline describing useful steam-related heat input, calibrated viscosity transformation, mobility growth, steam–oil ratio and a thermal-energy efficiency index with a residual-learning block fitted to measured regime-level records. The supervised forecasting task was performed at the regime level using 200 operating-regime records treated as the effective modelling units, with nested logs aggregated within regimes and within-group dependence examined through campaign-, reservoir-state- and well-availability-based checks. The 4800 steam-injection log entries and 4800 production-response log entries were treated as nested time-resolved measurements used only for regime-level aggregation, feature construction and quality-control checks; they were not counted as independent training samples. Blind-test validation produced R² values of 0.974 for oil rate, 0.988 for cumulative oil production, 0.731 for steam–oil ratio and 0.828 for the thermal-energy efficiency index; the corresponding MAPE values were 4.56%, 3.86%, 4.48% and 3.29%, respectively. The error structure shows higher uncertainty for composite indicators than for direct production responses, which is consistent with the measurement chain. Response-surface and Pareto analyses identify bounded steam-supply operating regions where production gain remains balanced against specific steam consumption and the thermal-energy efficiency index. Full article

Evapotranspiration (ET) estimation in desert-oasis ecotones remains challenging due to sparse meteorological observations and the coarse spatial resolution of satellite remote sensing, which limit the ability to resolve highly heterogeneous surface conditions. To address this issue, this study develops a high-resolution ET estimation framework by integrating unmanned aerial vehicle (UAV)-based thermal infrared remote sensing with a three-temperature (3T) model in the Hexi Corridor. UAV-derived land surface temperature (LST) at meter-scale resolution, together with meteorological and vegetation data, was used to drive the model and generate high-resolution ET maps. The model’s performance was validated spatially against the Surface Energy Balance Algorithm for Land (SEBAL) model and at the point-scale against a two-source model. The results show that: (1) The 3T model effectively captured the spatial gradient of decreasing ET from cropland (3–10.69 mm d⁻¹), through shelterbelts (3–6 mm d⁻¹), to desert areas (<3 mm d⁻¹). (2) Spatial validation against the SEBAL model was conducted using stratified pixel-wise comparisons across four land-cover types over 14 UAV transects, showing strong agreement (R² = 0.90–0.95; RMSE = 0.22–0.43 mm d⁻¹). The model achieved highest accuracy in cropland (R² = 0.92; RMSE = 0.24 mm d⁻¹), with slight overestimation in shelterbelts. (3) Point-scale validation against the two-source model yielded an MAE of 0.38 mm d⁻¹. This study demonstrates the effectiveness of combining UAV thermal infrared data with the 3T model for high-resolution ET simulation in complex ecological transition zones, offering a promising technical approach for ecohydrological monitoring and water resource assessment in arid regions. Full article

Hydrophobic silica aerogels are widely used as thermal-insulation materials, but the thermal decomposition of their organic surface groups may affect their stability and safety during high-temperature service. In this study, ambient-pressure-dried silica aerogels modified with trimethylsilyl, dimethylsilyl, and methylsilyl groups were prepared and denoted as TSA, DSA, and MSA, respectively, to clarify how the degree of methyl substitution in the surface modifier controls the pyrolysis behavior of hydrophobic silica aerogels. Thermogravimetric analysis at different heating rates was combined with TG-FTIR, a model-free kinetic analysis, a model-fitting analysis and thermodynamic calculation. With decreasing methyl substitution from TSA to MSA, the aerogel framework became denser, the specific surface area decreased, and the contribution of solid-phase heat transfer increased slightly. The main pyrolysis process occurred at 250–800 °C and involved multiple overlapping reactions. The average activation energies of TSA, DSA, and MSA were 241.4, 246.6, and 285.5 kJ/mol according to the Kissinger–Akahira–Sunose (KAS) method and 243.0, 248.2, and 289.0 kJ/mol according to the Flynn–Wall–Ozawa (FWO) method, respectively. The higher activation energy of MSA indicates that the more condensed silica-rich framework and lower organic methyl content improves its resistance to the main degradation process. The model-fitting analysis further suggested an A1/2 mechanism for TSA and A2/5 mechanisms for DSA and MSA. TG-FTIR further confirmed the evolution of CO₂, H₂O, CH₄, and C₂H₄ and revealed distinct gas-release behaviors among the three samples. These results demonstrate that the surface methyl-substitution structure governs the balance between hydrophobic modification, pore-structure preservation, pyrolysis resistance, and volatile-product release, providing a basis for selecting surface modifiers for thermally stable silica-aerogel insulation materials under oxygen-limited high-temperature conditions. Full article