Search Results (36,407)

Snow cover plays an important role in ecological stability and seasonal water regulation in the western Greater Khingan Mountains of Inner Mongolia, a cold-region transitional zone where climate warming may intensify environmental vulnerability and sustainability challenges. Using long-term remote sensing, meteorological, and topographic datasets, this study examined the spatiotemporal changes in snow cover and assessed the relative influences of climatic and geographic factors. The results showed pronounced spatial heterogeneity, with greater snow depth and longer snow cover duration occurring in the northeastern, high-altitude, gentle-slope, and north-facing areas. Snow depth showed a slight but marginally significant declining trend during 1982–2024 at a rate of 0.026 cm a⁻¹, while snow cover days decreased by 0.39 d a⁻¹ during 1982–2020. Snow cover onset exhibited a slight but significant delay, whereas snowmelt timing showed strong interannual variability. Compared with precipitation, temperature showed stronger and more persistent associations with snow cover variations, and climatic factors explained a larger proportion of snow-depth variability than geographic factors. Overall, the results suggest that regional warming has played a leading role in recent snow cover decline. These findings improve understanding of climate-sensitive snow dynamics and provide useful evidence for ecological conservation, seasonal water-resource adaptation, and sustainable regional management in cold-region landscapes of northern China. Full article

The application of multi-branch pinnate drilling has great prospects in gas control. Although there are many studies on the parameters of multi-branch plume drilling, the mathematical model used in the study is still not sufficient for the addition of the slippage effect and thermodynamic changes. In this paper, a thermal–fluid–solid coupling model is used to study the influence of branch angle and branch length on the extraction effect in high-gas and extra-thick coal seams. The reliability of the model is verified by simulating an onsite extraction environment to fit the onsite gas production rate. Under identical simulation conditions, the experiment investigated the gas extraction performance of boreholes with varying branch angles (30°, 40°, 50°, and 60°) and branch lengths (50 m, 75 m, 100 m, and 125 m). The results show that temperature affects the dynamic viscosity of gas, which in turn affects the flow rate. The slippage effect affects permeability. When the branch angle is less than 50°, the increase in the branch angle can expand the control range of drilling. By continuing to increase the angle, the improvement in the extraction effect is weakened. As the branch angle exceeds 50° and continues to increase, the branch borehole progressively approaches the edge of the coal seam. At this time, the overall control range of the borehole is greatly increased, and the gas extraction effect is improved. The increase in the branch length leads to a considerable improvement in the extraction effect. When the branch length is below 100 m, the improvement in extraction efficiency diminishes progressively with increasing branch length. This is because the effect of increasing the branch length on improving the overall control range of the borehole is weakened. When the branch length exceeds 100 m and continues to increase, the branch borehole approaches the edge of the coal seam. The overall control effect of drilling has been greatly improved. The extraction effect of boreholes has increased significantly compared with before. Full article

Rapid urbanisation is threatening agriculture in major cities worldwide. In the Greater Bandung Area (GBA), large-scale conversion of agricultural land into built-up areas has occurred over recent decades. Therefore, this study aimed to understand the rural–urban transition and its control in the agricultural context over the last 20 years. The methods adopted were multitemporal analysis of land cover change (2003–2023), calculation of the sub-district development index (SDI) (2005–2014–2021), spatial clustering analysis, and assessment of the level of agricultural land control. The results showed a transformation of GBA’s spatial structure from a monocentric growth pattern to a polycentric configuration, with the peri-urban zone within a 10–20 km radius evolving as a high-performance area. This shift has diminished the dominance of the traditional city centre and produced a pronounced “donut effect”. An integrated analysis of SDI and spatial clustering identified three interrelated functional zones, namely urban, peri-urban, and rural, forming a continuous spatial gradient. The peri-urban area functioned as a dynamic interface where agricultural activities coexisted and competed with urban expansion pressures. These results outlined the need for context-specific and differentiated planning methods, supported by selective spatial control to guide metropolitan transition toward balanced and sustainable development. Full article

Wi-Fi Channel State Information (CSI)-based indoor localization enables high-precision positioning, but its deployment across multiple environments faces two major challenges: privacy concerns from centralizing CSI data, and severe statistical heterogeneity (non-IID) arising from the strong environment-dependency of CSI. This heterogeneity creates a stability–plasticity trade-off in federated learning—maintaining precision in known environments (stability) while adapting to unseen domains (plasticity). To address this trade-off, we propose AdaFed-LDR, which combines server-side Confidence-Weighted Adaptive Aggregation with client-side Layerwise Dynamics Regularization (LDR). The aggregation recalibrates client contributions based on feature covariance changes, while LDR imposes depth-dependent constraints—stronger constraints on shallow layers to preserve environment-agnostic features and weaker constraints on deeper layers to allow environment-specific adaptation. Evaluated across 8 indoor environments using Leave-One-Out Cross-Validation and 5 random seeds, AdaFed-LDR achieved a mean localization error (MLE) of 0.41 cm in known environments, corresponding to an 88.2% reduction compared with FedAvg. In domain generalization to unseen environments, AdaFed-LDR achieved an MLE of $218.2\pm 2.8$ cm, demonstrating an improvement over FedPos ($257.6\pm 14.04$ cm). With one adaptation sample per reference point, MLE improved to 21 cm. Ablation experiments confirmed that combining the two proposed components achieved the highest improvement (83.9%) compared with applying them individually, supporting AdaFed-LDR as a reproducible approach to the stability–plasticity trade-off in federated CSI-based localization. Full article

Sustainable management of peatlands is one of the key global strategies for mitigating climate change. The balance between carbon (C) sequestration and emission in peatlands reflects environmental conditions over time and can provide insight into long-term ecosystem dynamics. However, current methods for estimating greenhouse gas (GHG) fluxes are often labor-intensive, costly, and site-specific. In this study, we propose a simplified and cost-efficient method to estimate long-term carbon balance in peatlands based on the inorganic (mineral) content of drill core samples. The approach uses exponential decay equations to approximate peat accumulation and decomposition processes over time. A conceptual model is applied that accounts for both anaerobic transformation of organic matter of varying molecular complexity and enhanced aerobic decomposition resulting from anthropogenic drainage during the last century. The model was applied to more than 100 drill cores from four peatland systems in Estonia. The resulting trends were compared qualitatively with known climatic fluctuations of the last millennium, including periods associated with the Little Ice Age. The results suggest that, in many cases, carbon losses from decomposition in deeper peat layers may exceed carbon accumulation in upper layers, even in peatlands that appear to be well preserved. The proposed method provides a rapid, low-cost, first-order approximation of peatland carbon dynamics and may serve as a complementary tool for large-scale assessments where detailed process-based models are not feasible. Full article

Soybean (Glycine max) is a vital food and oil crop in China, yet its yield and quality are severely threatened by piercing–sucking damage caused by Riptortus pedestris (Hemiptera: Alydidae) to soybean pods. Under global climate warming and expanded soybean cultivation, temperature has become a key environmental factor driving the spread of and aggravated damage caused by R. pedestris. We investigated the effects of temperature (32, 36, 40, 42, and 44 °C) and exposure duration (1–4 h) on the energy substances and antioxidant enzyme activities in adult R. pedestris. These two factors also had significant effects on the pest’s energy substances and antioxidant defense. Under short-term high-temperature stress, the water loss rate and fat, total sugar, and glycogen contents increased significantly, while protein content showed a fluctuating upward trend, with distinct sexual differences in these responses; the water loss and energy substance levels within the lethal high-temperature range, around 44 °C, were generally higher than those in the sublethal range (36–42 °C). R. pedestris showed physiological changes consistent with enhanced heat tolerance and adaptability, including water balance regulation, carbohydrate and lipid accumulation, and modulation of protein synthesis and degradation. In the sublethal high-temperature range, antioxidant enzyme activity patterns were altered, and SOD activity was increased; meanwhile, the MDA content also rose, and POD and CAT activities decreased. In the lethal high-temperature range, the overall antioxidant enzyme activities were lower than in the suitable temperature range, with the POD activities and MDA content still rising. These results suggest that the dynamic adjustment of antioxidant enzyme activities may contribute to alleviating oxidative damage and rapid adaptation to temperature-induced oxidative stress in R. pedestris. These findings indicate that R. pedestris possesses physiological plasticity to cope with sublethal heat stress through metabolic reallocation and antioxidant defense activation, but extreme temperatures cause severe physiological disruption. This study provides insights into the thermal biology and heat resistance mechanisms of this pest under climate warming scenarios. Full article

Given the depletion of conventional oil and gas resources, oil shale represents a promising alternative source of hydrocarbons that can be recovered through pyrolysis. This study examines the thermal decomposition of raw oil shale from the Tarfaya deposit and its decarbonized concentrate, studied by thermogravimetric analysis at different heating rates (5, 10, 20 and 40 °C/min). Pretreatment with acetic acid enabled the selective removal of calcite, confirmed by elemental, XRF, and XRD analyses, which revealed a relative enrichment in silica and dolomite in the oil shale concentrate. Pyrolysis of the raw shale occurs primarily between 300 and 500 °C, with a conversion rate of approximately 30%. In contrast, for the oil shale concentrate, the pyrolysis process begins at a relatively low temperature, within a wider temperature range (260–520 °C). Kinetic analysis based on Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) methods shows that at a conversion rate of 60%, the activation energy achieves 14.09 kJ/mol and 10.78 kJ/mol, respectively. The results indicate that the selective removal of calcite by acetic acid treatment facilitates kerogen pyrolysis by reducing mineral–organic interactions. Indeed, calcite dilutes the reactive organic fraction and can act as a physical barrier limiting heat and mass transfer within the oil shale. Its removal improves, on the one hand, the accessibility of kerogen to thermal cracking and promotes its decomposition, and on the other hand, reduces the amount of residue after pyrolysis. In addition, the kinetic analysis based on Criado master curves reveals changes in the reaction mechanism after decarbonation treatment depending on the heating rate (β). A shift from a two-dimensional Avrami–Erofeev model (A2) to a three-dimensional model (A3) was observed at a low heating rate (β = 5 °C/min), suggesting a change in nucleation and growth dynamics during kerogen decomposition. At high heating rates (10, 20 and 40 °C/min), the thermal decomposition of kerogen combines several reaction mechanisms depending on the temperature range considered. Full article

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), biofluid interfaces (sweat, interstitial fluid, and saliva), and materials engineering strategies enabling flexible, high-performance devices. Emphasis is placed on biofluid transport dynamics, analytical performance across sampling matrices, and system-level integration with wireless communication and digital health platforms. Key challenges limiting clinical translation, including biofouling, enzymatic instability, and variability in biofluid composition, are examined—alongside emerging solutions such as antifouling interfaces, synthetic recognition elements, and multimodal sensing architectures. Finally, regulatory pathways and the role of artificial intelligence in digital nephrology are discussed. This review highlights the potential of wearable biosensors to transform CKD management through continuous monitoring, early detection, and personalized therapeutic intervention. Full article

Wireless Power Transfer (WPT) systems often face performance limitations due to the right-half-plane zero (RHPz) in conventional constant-current-fed Buck converters, which can lead to negative undershoot and a slow dynamic response. In this paper, we propose a Buck converter topology with an additional active switch in series with the input capacitor. This mechanism-level modification effectively mitigates the RHPz. The operating modes, steady-state behavior, and small-signal characteristics of the converter are systematically analyzed. A tailored control strategy enables independent regulation of input and output capacitor charging times, supporting improved voltage regulation. Experimental results indicate that the proposed converter reduces settling time by approximately 83%, substantially suppresses negative undershoot, and maintains stable voltage regulation under reference step changes and load transients. The converter maintains high efficiency while demonstrating improved dynamic performance and stability relative to conventional topologies, providing a practical approach for advanced WPT applications. Full article

Underwater Wireless Sensor Networks (UWSNs) play a vital role in ocean monitoring and exploration. However, harsh underwater conditions and frequent topology changes caused by node and sink mobility pose significant challenges for reliable routing. Conventional routing protocols that depend on global route reconstruction and static paths generate excessive control overhead and degrade performance in large-scale underwater environments. In this paper, we propose an energy-efficient virtual cell-based mobile-sink adaptive routing (VC-MAR) protocol for UWSNs. The sensing field is logically partitioned into a three-dimensional grid of virtual cells, where a cell-gateway is elected in each cell to construct a low-overhead routing backbone. To support sink mobility, VC-MAR introduces a localized route-adjustment mechanism that updates only the affected backbone segments rather than reconstructing the entire routing structure. By confining routing updates to neighboring cells influenced by sink movement, the proposed protocol significantly reduces control packet exchanges while ensuring stable and reliable data delivery. Simulation results show that the proposed VC-MAR improves the packet delivery ratio by up to 20% and reduces routing control overhead by about 34% compared with traditional grid-based routing methods. These results confirm the suitability of VC-MAR for dynamic and realistic underwater sensing scenarios. Full article

Low-cost IoT-based air quality sensors enable dense monitoring networks but suffer from significant measurement noise and instability particularly in dynamic environments. Conventional fixed-window smoothing reduces noise but introduces a trade-off between signal stability and temporal responsiveness, often attenuating short-term pollution events. This paper proposes an adaptive filtering algorithm that dynamically adjusts the averaging window size based on short-term signal variability. The method relies on real-time variance estimation to balance noise suppression and sensitivity to rapid changes without increasing computational complexity. The approach is implemented within an IoT-based monitoring framework and evaluated using parallel measurements with a certified reference device. Comparative analysis against a certified reference device demonstrates strong agreement, with Pearson correlation coefficients reaching r = 0.88 for PM_2.5 and r = 0.86 for PM₁₀, and low error levels (RMSE ≈ 2.1–2.2 µg/m³). The proposed adaptive filtering approach preserves temporal dynamics while improving signal stability and robustness compared to raw and fixed-window filtering. In addition, this method improves event detection stability, achieving low false alarm rates and near real-time response (latency < 1 sampling interval), supporting RPA-based workflow triggering. The results show that the proposed adaptive filtering provides an efficient and lightweight solution for real-time signal processing on resource-constrained devices, making it suitable for large-scale deployment in environmental monitoring systems. Full article

Many of life’s biggest dilemmas can be summed up as a tension between holding on and letting go. The very language evokes a notion of intentionality which, for the most part, has evaded scientific understanding. How might we even get a window into it? Important insights have come from a seemingly simple task: wiggling one’s fingers to and fro to the beat of a metronome. As the metronome pace increases to some critical frequency, one coordinative pattern becomes unstable and switches spontaneously to another. Such transitions are typically preceded by critical fluctuations, a predicted feature of self-organization in complex, dynamical systems. Here we address the nature and source of these fluctuations, usually assumed to be: (1) random; (2) of external origin; and (3) of fixed magnitude. We performed an experiment in which participants were instructed to oscillate their fingers in either an in-phase or anti-phase pattern in time with a metronome and instructed them to either “hold-on” or “let-go” should they feel the pattern begin to change, yielding a 2 by 2 within-subjects design. We observed that as the metronome frequency was increased from 1.00 to 3.00 Hz, fluctuations in the relative phase between the fingers were significantly altered both by the starting coordinative pattern as well as the participant’s intention to “hold it on” or “let it go”. Specifically, the intention to hold on to the anti-phase pattern delayed the spontaneous transition to in-phase, an effect that was paired with increased fluctuations beyond the critical frequency. These observations were analyzed under the extended Haken–Kelso–Bunz (HKB) model which describes the non-linear stochastic dynamics of the order parameter (relative phase) as a gradient descent on a certain potential. Our analysis, in line with experimental results, suggests that intention transforms the HKB potential not only by stabilizing unstable coordination states but also (paradoxically) by increasing fluctuations around them. Such findings may offer new interpretative light on the relation between intention and fluctuations in the coordination dynamics of living things. Full article

A thorough understanding of the resistivity response characteristics of ethanol-contaminated soil is of great significance for the development of non-destructive geophysical detection techniques and for supporting contaminated site investigation and assessment. This experimental study aims to systematically investigate the resistivity behavior of ethanol-contaminated sandy soils, with a focus on the coupled mechanisms of multiple factors, including water content, ethanol concentration, particle size distribution, and contamination time. It is hypothesized that water content serves as the dominant factor controlling resistivity, whereas ethanol concentration and contamination time regulate resistivity by altering the physicochemical properties of the pore fluid. Under laboratory conditions, silt, fine sand, and medium sand were selected as the test materials. Resistivity was systematically measured using a Miller Soil Box with increasing water content, Wenner array configuration across varying water contents (3–24%), ethanol concentrations (40–98%), and contamination durations (0–144 h). The experimental results indicate the following: (1) Regardless of the presence of ethanol contamination, the resistivity of sandy soil decreases with increasing water content following a power-law relationship. The decrease is most pronounced at low water contents (3–9%), and gradually stabilizes at higher water contents. The results show that, at a constant water content, resistivity systematically and consistently follows the order: silt > medium sand > fine sand. (2) The influence of ethanol concentration on resistivity is constrained by water content levels, and the overall increase in resistivity is primarily attributed to ion dilution and the obstruction of conductive pathways. (3) Over time, resistivity exhibits a two-stage increasing trend, associated with ethanol volatilization and water loss. Resistivity changes in fine sand samples contaminated with ethanol at concentrations ranging from 75% to 95% follow a two-stage pattern. The initial phase of growth is characterized by a gradual increase over a period of 0–48 h, followed by a more rapid increase during the subsequent phase, which extends from 48 to 144 h. The results show that higher initial ethanol concentrations enhance the sensitivity of resistivity to temporal changes. Comprehensive analysis indicates that the resistivity variation mechanism under multi-factor coupling conditions can be summarized as follows: the water content is the dominant factor in the regulation of the conductive pathways; the particle size distribution determines pore structure and the characteristics of the particle interface; ethanol concentration and contamination time dynamically alter pore fluid properties, collectively regulating the resistivity response. Although the experiments were conducted under controlled laboratory conditions and the results have certain limitations, they provide a preliminary reference for interpreting resistivity responses in relatively homogeneous sandy contaminated sites and offer theoretical support for the application of resistivity methods in contamination identification and dynamic monitoring. Full article

Rising temperatures, driven by global climate change, are profoundly altering high-latitude ecosystems, influencing vegetation phenology and productivity. However, understanding the long-term, nuanced responses of these ecosystems remains a critical challenge. Soil warming experiments have served as useful tools for understanding these shifts. However, many of these studies have relied on a single measure, predominantly the Normalized Difference Vegetation (NDVI), measured at a single level of warming. This approach often fails to separate structural greening from underlying physiological responses. To address these gaps, this study provided a comprehensive snapshot assessment of growing season vegetation dynamics in a subarctic grassland ecosystem in Iceland that had been exposed to continuous geothermal soil warming for over 60 years. Using high-resolution multispectral drone imagery, twelve different vegetation indices (VIs) were derived to assess not only greenness but also physiological stress and photosynthetic efficiency across a range of mean annual soil temperatures (MATs). Using linear regression and redundancy analysis (RDA), the responses of these indices to warming and their relationships with other environmental drivers, such as standing biomass and plant nutrient concentrations (nitrogen and phosphorus), were analyzed. The results revealed significant positive linear relationships between most of the indices and MATs across the 5 to 11 °C range. This indicated that higher MATs led to increased biomass and structural growth, without revealing any significant thresholds or tipping points in vegetation response within the observed warming range. However, the Photochemical Reflectance (PRI) showed a significant negative relationship with warming, suggesting a decoupling between structural greening and photosynthetic light-use efficiency. Furthermore, RDA results indicated that, while most of the VIs were primarily driven by biomass, the decline in PRI was likely a compounding effect of physical canopy self-shading and plant phosphorus constraints. Ultimately, this study demonstrated that, while these subarctic grasslands exhibited local evidence of “Arctic greening” under further warming, multispectral drone remote sensing could detect underlying physiological adjustments and nutrient constraints that traditional greenness indices might overlook, providing a more nuanced understanding of ecosystem response. Full article

This study investigates the tide-dominated hydrodynamic response of Pulandian Bay to shoreline changes by comparing numerical simulations under shoreline conditions in 2004 and 2020 using the FVCOM. The results indicate that shoreline changes exert significant spatially heterogeneous effects on tidal dynamics. Channel narrowing caused by aquaculture enclosures and saltpan construction increased flow velocity near Boji Island. Meanwhile, tidal prism decreased during both spring and neap tides due to the loss of intertidal areas from northern reclamation, thereby weakening water exchange capacity. The outer bay, directly connected to the open sea, exhibits stronger water exchange than the relatively enclosed inner bay. However, the removal of seawalls in the inner bay enhanced flow in the central deep trough, resulting in improved water exchange capacity in 2020 compared to 2004. Shoreline changes also intensified tidal residual currents, with high-value Eulerian residuals mainly distributed in the northern and central parts of the bay. In addition, the restoration of tidal channels in the inner bay slightly increased residual current velocity. Overall, shoreline modification plays a critical role in regulating tidal hydrodynamic processes, providing important implications for coastal engineering and aquaculture management. Full article