Search Results (18,482)

The background modification of ecosystems affected by fire can cause black or dark colours in animals to become adaptive, providing better protection against visually oriented predators. We surveyed fire-prone Mediterranean woodlands to describe the behaviour, position and background characteristics of the black cicada Tibicina quadrisignata Hagen, 1855 found in recently burnt and unburnt trees. A human detectability test, using cicada pictures in natural backgrounds taken during the fieldwork, was used to assess detection risk. Most cicadas found were solitary males uttering courtship song. Many cicadas flew when approached, with 82% of flight initiation distances being less than 3 m and half of the flights being less than 30 m. Cicadas favoured sunny locations in early morning, and shady sites as the temperature increased. Fire altered fine-scale microhabitat use by cicadas, since cicadas were found in 71% thicker stems and at 14% lower height on the tree, in burnt trees, in relation to unburnt trees. Generalised Linear Mixed Models (GLMMs) revealed a negative fire effect on cicada detection by human test participants. The probability of detection fell from 0.62 in unburnt backgrounds to 0.48 in burnt backgrounds, while the time needed for detection did not change between burnt and unburnt sites. Overall, these results show that T. quadrisignata cicadas adjust their substrate use after fire and are less detectable on burnt backgrounds. Real predation risk, however, also depends on thermoregulation-associated exposure, courtship song activity and predator densities. Full article

Accurate prediction of thermo-mechanical behavior in Fused Deposition Modeling (FDM) is often limited by mismatches between idealized Computer-Aided Design (CAD) geometry and path-dependent material deposition. This paper presents a G-code-driven, filament-level modeling and process-simulation workflow for complex geometries and infill strategies, especially toolpaths with in-plane inclinations. Extrusion segments are parsed from slicing G-code to obtain endpoints and process parameters, and each filament is reconstructed as a path-aligned rectangular bead using a dedicated local coordinate system. Progressive deposition is simulated in ANSYS Parametric Design Language (APDL) via an element birth–death method, enhanced by a centroid-based element selection strategy that reduces dependence on strictly aligned hexahedral partitions and improves robustness for complex meshes. A nonlinear transient thermal analysis is performed, and temperatures are mapped to the structural model through an indirect thermo-mechanical coupling scheme to predict warpage and residual stresses. Case studies on square plates with triangular and hexagonal infills (with/without sidewalls and a bottom base) show that the high-temperature zone follows newly deposited paths with peak temperatures near 220 °C, while displacement and von Mises stress accumulate and are strongly affected by infill topology and boundary conditions. Full article

2219 aluminum alloy is widely used in aerospace components because of its high specific strength, excellent fracture toughness, and resistance to stress corrosion cracking. Accurate characterization of its hot deformation behavior is important for the numerical simulation and process design of ring rolling. In this study, isothermal compression tests were carried out on a thermal–mechanical simulator at temperatures of 380–460 °C and strain rates of 0.01–10 s⁻¹ to investigate the hot deformation behavior of 2219 aluminum alloy. The effects of deformation temperature and strain rate on flow stress evolution were analyzed based on the experimental results. A strain-compensated Arrhenius-type constitutive model was developed to describe the flow stress behavior over a wide strain range. The material constants, including the stress exponent, stress level parameter, activation energy for hot deformation, and structure factor, were determined by regression analysis, and their strain dependence was expressed as polynomial functions of true strain. The model was evaluated by comparing predicted and experimental flow stress values, giving an average absolute error of 4.78%. The results indicate that the developed model can describe the combined effects of temperature, strain rate, and strain with good accuracy, and can be used for numerical simulation and process optimization in hot ring rolling. Full article

Satellite remote sensing increasingly supports water quality monitoring, yet the temporal transferability of machine learning (ML) models remains insufficiently tested, particularly in coastal shallow lakes subject to hydrological variability. This study evaluates the predictive robustness of satellite-based ML models for electrical conductivity (EC), turbidity (TUR), water temperature (WT), and dissolved oxygen (DO) in Vrana Lake, Croatia. A total of 409 in situ measurements collected during 2023–2024 and 2025 were paired with Sentinel-2 and Landsat 8–9 imagery. Pearson, Spearman, and Kendall correlation analyses were applied for parameter-specific band selection using original, inverse, quadratic, and logarithmic feature transformations. Seventeen regression algorithms were evaluated under six training–testing split strategies, including strict temporal projection. WT exhibited high robustness (R² ≈ 0.90 under temporal projection) due to its strong dependence on thermal bands, while DO achieved moderate temporal stability (R² = 0.51) using log-transformed predictors. EC and TUR demonstrated substantial performance degradation under temporal separation (R² = 0.14 and −4.62, respectively), reflecting sensitivity to distribution shifts. For parameters showing sufficient stability, interpretable band-based retrieval equations were derived using the most strongly correlated spectral predictors. These findings highlight the importance of temporally structured validation and demonstrate that model complexity does not guarantee operational robustness in shallow, dynamically evolving lake systems. Full article

Olive cultivation is widespread throughout the Mediterranean basin, where the world’s main producing countries are located. Regions such as Extremadura are considered to be at high risk from the effects of climate change in the near future. In particular, olive cultivation is highly sensitive to climate change and can suffer profound effects on phenology and yield. This crop depends directly on variables such as maximum and minimum temperatures and rainfall. In this study, we have analysed how olive cultivation could be affected by calculating two bioclimatic indices, the Dryness Index (DI) and the Cool Night Index (CI), for three future periods. The methodology used projected ten combinations of climate models in two scenarios, RCP 4.5 and RCP 8.5. The results showed significant variations in the bioclimatic indices over the periods, which were used to calculate the water stress and extreme temperatures that these crops could suffer. They indicate that most of Extremadura will continue to be suitable for cultivation in the near future (2006–2035), while by the middle of the century (2036–2065) 67% of the area will remain temperate, where 72% of the olive groves are located, with a Dryness Index of 18% in the very dry category. By the end of the century (2066–2095), the zone will be 60–34% warm and very dry, with a Dryness Index of 72%. These results show that it will probably be necessary to create new areas suitable for olive cultivation and new varieties. Full article

Silicon carbide (SiC) MOSFETs are critical for next-generation power electronics, yet their reliability is challenged by alternating-current Bias Temperature Instability (AC BTI). While charge trapping and Recombination-Enhanced Defect Reaction (REDR) are known degradation pathways, the specific role of gate oxide thickness in determining the dominant mechanism remains unclear. This study investigates the degradation behaviors of SiC MOSFETs with varying oxide thicknesses under 150 kHz Dynamic Gate Stress. By maintaining a constant electric field, we decouple the effects of oxide thickness using high-frequency C-V, quasi-static gate current (I_GS) characteristics, and transconductance analysis. Results reveal that thin-oxide devices exhibit parallel C-V shifts and stable transconductance, indicating degradation driven by deep-level charge trapping. Conversely, thick-oxide devices display significant C-V stretch-out, negligible I_GS peak shifts, and severe transconductance degradation, accompanied by irreversible threshold voltage drift. We conclude that despite identical electric fields, the higher driving voltages in thick-oxide devices trigger severe interface state generation consistent with the REDR model, whereas thin-oxide devices are dominated by bulk oxide trapping. These findings highlight the necessity of thickness-dependent optimization strategies for SiC power devices. Full article

In ultra-high-temperature and high-pressure gas well drilling, the use of high-density drilling fluid inevitably invades the reservoir, and perforation operations require penetrating this invasion zone to further connect the reservoir. This paper first conducts core drilling fluid invasion experiments, introducing two parameters—filter cake loss and core slice permeability—to derive the long-term invasion depth pattern of drilling fluid. Then, through three types of perforation target experiments (steel target, cement ring target, and sandstone target), the penetration performance of this type of perforating charge is evaluated. The results indicate that the total volume of drilling fluid invasion depends on the pore permeability characteristics of the core, with a fitted final invasion depth of 7.24 cm after 30 days of actual operation. The edge effect of the perforating gun causes significant differences in penetration depth and hole diameter at different phases, where the near-edge penetration depth and hole diameter are 1.86 times and 1.75 times larger than the far-edge, respectively. When the temperature resistance exceeds 200 °C/100 h, penetration depth and hole diameter decrease significantly with increasing temperature and time, and under 250 °C/170 h conditions, the firing rate markedly decreases. Using sandstone targets with identical strength and pore permeability conditions as a South China Sea ultra-high-temperature and high-pressure well block, the average penetration depth is 197 mm, far exceeding the thickness of the drilling fluid invasion zone. These experimental results provide theoretical support for perforation operations in a South China Sea ultra-high-temperature and high-pressure well block. Full article

As one of the three fundamental modes of heat transfer, thermal radiation has long attracted interest due to its independence from a medium and its strong temperature dependence. In extreme environments such as deep space exploration and cryogenic engineering, thermal radiation often becomes the dominant heat transfer mechanism. Consequently, the radiative properties of materials are crucial for achieving precise thermal control, directly influencing the thermal stability and overall performance of advanced systems, including space probes, cryogenic devices, and superconducting components operating under high-vacuum and low-temperature conditions. This paper provides a systematic review of the physical mechanisms, key factors affecting emissivity, major measurement methods, and technological developments related to material radiative properties at cryogenic temperatures. Particular attention is given to experimental methods and techniques describing material radiative behavior, along with a comparative analysis of the suitability of different measurement techniques for cryogenic applications. Finally, the study highlights the significant practical value of this research for fields such as aerospace, precision electronics, and cryogenic instrumentation, aiming to offer insights for optimizing cryogenic thermal management and guiding the design of novel functional materials. Full article

Vegetation in desert ecosystems is strongly affected by seasonal climatic fluctuations and soil physical and chemical properties. Rawdat Nourah is a natural watershed depression within the King Abdulaziz Royal Reserve in Saudi Arabia. It is colonized by grasses, herbs, and shrubs. Climatic variability and soil heterogeneity are influencing the vegetation dynamics and regeneration patterns in this ecosystem. Based on the literature review, no previous study analyzed and determined either the vegetation composition or the soil seed-bank of Rawdat Nourah. So, the general objective of this study is to examine the vegetation composition and its relationships with soil physicochemical properties and soil seed-bank composition across Rawdat Nourah across different seasons. Floristic analyses, vegetation composition, soil properties, and soil seed-bank were performed within two seasons (winter–spring and summer–fall seasons) of 2023–2024. The obtained data were analyzed using multivariate and statistical approaches. Six plant associations were identified: winter–spring (WVG I: Zilla spinosa–Malva parviflora; WVG II: Rhazya stricta–Zilla spinosa; WVG III: Cynodon dactylon–Convolvulus pilosellifolius) and summer–fall (SVG I: Calotropis procera–Pulicaria undulata; SVG II: Cynodon dactylon–Zilla spinosa; SVG III: Rhazya stricta–Schismus arabicus). Species richness was higher in winter–spring (2.4 species stand⁻¹) than in summer–fall (1.66 species stand⁻¹), while the seed-bank densities were 633.9 and 575.1 seeds m⁻², respectively. Vegetation responded strongly to marked seasonal contrasts in temperature and moisture (~15 °C, 11 mm vs. ~36 °C, 3 mm). Moderate human activity enhanced vegetation cover, whereas prolonged grazing exclusion reduced diversity through the dominance of a few species. The response of vegetation structure and species richness to climatic factors varies greatly depending on the increase in water availability, and moisture content during the mild weather Winter–Spring season (mean temperature is 15 °C and rainfall is 11 mm), compared to the Summer–Autumn season (mean temperature is 36 °C and rainfall is 3 mm). The richness and cover of the plants were generally affected by human activity, where long-term grazing will reduce species richness and increase competition between species, making one or two species dominant. Although above-ground vegetation exhibited clear seasonal and spatial shifts in species composition and abundance, these changes were not reflected in the soil seed-bank. This relation suggests that above-ground communities and seed-banks are regulated by different ecological processes under arid conditions. The data of the present study showed low correlation between the current vegetation and the soil seed bank, which reflects a degradation in this region. Therefore, these findings suggest that sustained protection of the King Abdulaziz Royal Reserve is essential for enhancing seed-bank persistence, vegetation recovery, and ecosystem resilience under arid conditions. Full article

This paper presents a mathematical modeling and advanced control strategy for the beer fermentation process, which is characterized by nonlinear biochemical kinetics and time-dependent dynamics. A biokinetic model was developed to describe the relationship between yeast growth, sugar consumption, and ethanol formation. The system was represented as a cascade of several continuous stirred-tank reactors (CSTRs), and experimental data confirmed a fermentation cycle of approximately 10 days. During this period, biomass concentration reached 6.8 g/L and ethanol levels exceeded 42 mmol/L. Substrate concentration (S) declined from 120 to 5 g/L, demonstrating effective conversion. The model was linearized around an operating point and reformulated into a 12-state-space system with input variables: temperature (set at 20–22 °C) and pH (maintained within 4.2–4.5). These inputs were controlled using fuzzy logic control (FLC) and model predictive control (MPC). Simulation results indicated that the FLC reduced temperature deviation to ±0.3 °C and minimized pH fluctuation below ±0.05. The MPC strategy improved substrate consumption efficiency by 8.5% and decreased fermentation time by 12 h under optimized input profiles. The combined FLC–MPC scheme demonstrated superior robustness, smooth trajectory tracking, and adaptability to biological variability compared to traditional methods. The developed framework supports intelligent brewery automation and provides a scalable foundation for further integration of digital fermentation technologies. Full article

Here, the resistive switching characteristics in a Cu/a-SiC/P+-Si sandwiched structure are systematically investigated for multilevel nonvolatile memory applications. The formation of Cu conducting filaments is believed to be the switching mechanism through temperature-dependent testing. Four distinguished resistance states can be achieved in the Cu/a-SiC/P+-Si memory device through the modulation of suitable compliance current, which could be attributed to the formation of more conductive filaments when applying a higher compliance current during the Set process. In addition, these different resistance values can be easily distinguished and show reliable retention (~105 s), with the temperature even reaching 85 °C, which offers considerable potential for high-density RRAM applications. Full article

Hydrogen-induced crack growth initiation, in metallic structures, is studied under constant temperature and chemical equilibrium, by employing Chemical Equilibrium Fracture Mechanics (CEFM). The conditions of small-scale, contained and large-scale hydrogen embrittlement are introduced and the areas of material deterioration, together with the distributions of stress and hydrogen concentration, including hydride volume fraction, are derived analytically. It is shown that the shape of the material deterioration zone is identical for embrittlement caused either by hydrogen in solid solution or by hydride precipitation; the size depends on the strength of the asymptotic crack-tip field, which develops by the mechanical loading in the hydrogen-free structure, as well as on the average hydrogen content absorbed by the structure. It is also shown that a linear relation exists between a power of the threshold of crack-growth initiation and the logarithm of hydrogen content, depending on the extent of hydrogen embrittlement and material elastic-plastic deformation. These linearity trends, which are derived by the present analysis, are confirmed by published experimental fracture mechanics measurements on several non-hydride- and hydride-forming alloys, including α/β hydride-forming alloys. The present study promotes structural integrity assessments, without reliance on complicated coupled numerical analysis of material deformation, hydrogen diffusion and hydride precipitation. Full article

Corrosion resistance of steel wires can be achieved through several approaches, one of the most established being hot-dip galvanizing. The effectiveness of anticorrosive protection of a galvanized wire is considered to depend not only on the galvanizing process itself, namely bath composition, temperature, and immersion duration—but also on the post-galvanizing wiping method, which ultimately determines the final thickness and uniformity of the zinc coating. This study describes and quantifies the resulting parameters of the Zn layer, systematically comparing two technical variants. Four parameters were analyzed to characterize the coating: the effective thickness of the constituent layers, their morphology (examined by SEM), their compositional profile (EDX mapping), and their microhardness. To comprehensively assess the influence of the wiping method on the anticorrosion performance of the galvanized wire, the final corrosion tests, fifth in the sequence, will be conducted in a salt fog environment using an Erichsen chamber, in accordance with standardized procedures. Full article

Precise regulation of the postharvest storage environment is critical for reducing losses and maintaining potato quality. Semi-underground storage facilities are widely used in major potato-producing regions of northern China; however, pronounced spatiotemporal heterogeneity in the internal temperature field often leads to localized quality deterioration. To enable accurate sensing and proactive prediction of temperature dynamics in such facilities, this study investigated a typical semi-underground potato storage cellar in Wuchuan County, Inner Mongolia. A high-density sensor network was deployed to collect temperature data, and the spatiotemporal variation patterns of the internal temperature field were systematically analyzed. The results indicate that, at the same vertical height, spatial temperature gradually increases from the entrance toward the interior of the cellar. Both the maximum and minimum temperatures in the entrance zone are lower than those in other regions, while the highest temperatures are observed near the rear wall. Based on the collected data, hierarchical clustering was employed to partition the internal temperature field into three spatiotemporal pattern clusters with significant differences. Key representative monitoring locations were then identified using the Spearman correlation coefficient. An AdaBoost-based prediction model was subsequently developed to estimate the temperatures at other test locations within each cluster using measurements from the representative points. The results demonstrate that the proposed model maintains high prediction accuracy while substantially reducing dependence on a dense sensor network. The overall MAE ranges from 0.075 to 0.373 °C, and the sensor reduction ratio reaches 87%. This approach provides a paradigm for low-cost intelligent monitoring and offers theoretical support and decision-making guidance for the smart regulation of potato storage environments. By optimizing the monitoring of potato storage environments, this study can reduce monitoring system costs and resource consumption, providing technical support for building a sustainable potato supply chain and delivering significant economic benefits in promoting the development of a resource-conserving potato industry. Full article

Artificial neural networks (ANNs) are widely used to approximate nonlinear mappings, yet their ability to capture thermodynamic behaviour in dynamic physical systems remains insufficiently characterised. This study investigates how representational capacity influences surrogate modelling accuracy for a crank-angle-resolved internal combustion engine (ICE) simulation with a maximum dynamic state dimension of six. Two feedforward ANN configurations are evaluated: a low-capacity 5–5 architecture containing 84 trainable parameters and a high-capacity 25–25–25 architecture containing 1554 parameters (18.5× larger). Both networks approximate the nonlinear mapping from five embedded operating parameters to four peak thermodynamic outputs (maximum pressure, pressure phasing, maximum temperature, and temperature phasing). Evaluation across 53,178 operating points demonstrates that the high-capacity configuration reduces root mean squared error by factors of 30–50× relative to the low-capacity network, decreasing peak temperature error from 17.68 K to 0.36 K and peak pressure error from 0.116 MPa to 0.0025 MPa. Although both models achieve coefficients of determination exceeding 0.99, the low-capacity network exhibits heavy-tailed residual distributions and regime-dependent error amplification, whereas the high-capacity model reduces both central dispersion and extreme-case error. These results demonstrate that high correlation alone does not guarantee engineering reliability in nonlinear thermodynamic systems. Distribution-level analysis, including percentile and extreme-case characterisation, is required to evaluate engineering robustness. The findings provide a quantitative framework linking ANN capacity, nonlinear dynamic system representation, and predictive robustness. Full article