Search Results (5,708)

Estuaries support distinct spawning and nursery habitats for migratory fishes, yet the differential environmental response patterns between these two critical early life habitats remain poorly understood from a spatial non-stationarity perspective. Based on six ichthyoplankton surveys conducted during peak and late spawning seasons from 2018 to 2020 in the Yangtze Estuary, this study applied geographically weighted regression (GWR) models to quantify the spatially varying effects of sea surface temperature, sea surface salinity, chlorophyll-a, water depth and distance to coast on the distributions of Coilia mystus eggs and larvae. The results reveal clear divergence in both spatial pattern and environmental drivers between spawning and nursery habitats. Spawning grounds were persistently concentrated in the middle reaches of the South Branch, and shifted approximately 10 km upstream during the spring saltwater intrusion event in 2020. Nursery grounds, by contrast, formed a stable dual-core structure, with the northern core at the North Branch mouth consistently supporting higher larval densities than the southern core in the North and South Passages. Salinity was the primary limiting factor for spawning in spring, while temperature dominated in summer, and chlorophyll-a was never retained in optimal egg models. For larvae, chlorophyll-a emerged as a consistent key driver alongside salinity and temperature, and local regression coefficients spanned a wider range than those for eggs, indicating greater spatial heterogeneity in larval distribution–environment relationships. This study provides the first comparative analysis of spatially non-stationary environmental controls on spawning versus nursery habitats of C. mystus, and offers empirical support for stage-specific habitat conservation and fisheries management in the Yangtze Estuary. Full article

Open-channel hydraulic analysis often requires repeated solution of implicit nonlinear equations and numerical integration of gradually varied flow (GVF), which can become computationally demanding in inverse, optimization, and sensitivity applications. This study develops a hydraulically informed artificial neural network (ANN) surrogate framework comprising ten independently trained models for normal and critical depths, alternative and conjugate depths, GVF-related water-surface behavior, and profile-based discharge inference. Hydraulic information is introduced through physically meaningful, and where appropriate dimensionless, variables and reference solutions derived from established governing equations or numerical hydraulic models, while ANN optimization remains data driven. Equation-generated test sets quantified surrogate fidelity, whereas HEC-RAS comparisons were treated as numerical hydraulic cross-verification rather than independent physical validation. The forward surrogates reproduced their reference mappings with high accuracy within the represented domains. Benchmarking against Random Forest, support vector regression, and Gaussian Process Regression for Models 1, 5, and 7 showed no universal algorithmic superiority; however, ANN provided a favorable trade-off among accuracy, relative-error robustness, compactness, and repeated-inference efficiency. For Model 7, ANN inference was approximately 249 times faster than conventional GVF calculation, with development cost recovered after about 1.03 × 10⁵ evaluations. Model 9 inferred discharge with a 4.75% error in the profile-based test. Observation-based assessment using 16 historical Missouri River stage–discharge events showed that direct HEC-RAS inversion yielded a MAPE of 44.71%, whereas observation-only ANN and hybrid HEC-RAS-ANN discrepancy correction reduced MAPE to 10.25% and 9.83%, respectively. The framework is therefore a computational complement to established hydraulic equations and numerical models, with broader field validation and explicit uncertainty treatment required for general deployment. Full article

Fracture evolution of rock–backfill composites (RBCs) under complex loading–unloading and dynamic disturbances is critical for stope stability in deep backfill mining. Using PFC3D, this study constructs numerical models of RBCs to investigate this process, considering burial depths (500, 1000, 1500, 2000 m), interface angles (IA: 60°, 90°), and cement–tailings ratios (CTR—1:4, 1:8), while replicating true triaxial paths and blasting impacts. Systematic analysis of mesoscopic crack quantity, spatiotemporal distribution, and multiscale fracturing reveals that shear cracks dominate damage, with crack counts evolving in stages as strain increases. With greater depth, the number of propagation stages and growth rate inflection points shift systematically. During mining–filling disturbance, crack quantity negatively correlates with depth but turns positive during late static loading beyond 70% peak stress. Spatial crack distribution is synergistically controlled by IA, CTR, and depth. For IA 60°, shear crack angles spread broadly yet concentrate at 50–70°; for IA 90°, they are near-axial, concentrated at 80–90°. The synergistic process progresses through microscopic initiation, mesoscopic accumulation, and macroscopic instability. In terms of failure modes, IA 60° exhibits shear failure along the cemented interface plus tensile fracturing in rock, while IA 90° shows combined diagonal shear and axial tension. Higher CTR yields more extensive fracture networks in backfill, indicating superior synergistic bearing capacity. Full article

Winter-sport wearable technology spans motion and force sensing, physiological monitoring, thermal intervention, flexible bioelectronics, equipment-integrated systems, and safety technologies. This structured critical review synthesizes an evidence base of 80 unique scholarly records identified through a systematic Boolean search executed on 15 August 2026 in four standard academic databases (Scopus, Web of Science Core Collection, PubMed, and IEEE Xplore), which retrieved 1466 records (808 unique after cross-database deduplication), supplemented by backward/forward citation chasing for eligible records not indexed in these databases. The corpus comprises 32 direct winter-sport records, 15 cold-context translational records, 14 contextual validation records, and 19 secondary/background records. For empirical records containing sufficient information, validation maturity was additionally coded on a seven-stage ordinal scale; 54/80 records could be staged without inference, whereas 26/80 were retained as ‘not staged’. The corpus shows that translational maturity is strongly domain dependent. Motion and kinematic sensing frequently reaches real winter-sport training or field settings, whereas antifreezing hydrogels and flexible bioelectronics have advanced substantially in conductivity, adhesion, self-healing, conformability, and low-temperature operation but remain concentrated at material, integrated-device, and human-demonstration stages. The five recurring constraints—thermodynamic, interface, ecological, connectivity, and equity—are therefore reframed as non-equivalent, context-dependent dimensions rather than universal burdens. The revised architecture also distinguishes digitally mediated sense–decide–actuate loops from material-native stimulus–response and hybrid pathways, while continuous remote monitoring is treated as one option within an energy–communication trade-space. The resulting framework links evidence type, validation depth, system interface, and deployment context without equating commercial availability with scientific validation. Full article

Electric-shovel top sheave bearings with sensor-embedded slots operate under harsh service loads, making them prone to fatigue crack initiation and propagation. Accurate predictions of crack growth within the bearing body are therefore essential for intelligent bearing design and reliability assessments because the bearing integrity directly affects shovel service life and safety. This paper presents a sub-modeling-based method that embeds initial cracks while preserving actual roller-ring boundary conditions and ensuring computational efficiency via adaptive mesh refinement. A global model first identifies critical crack-prone zones, after which the sub-model systematically examines the effects of the initial crack angle and sensor-embedded slot depth on the propagation behavior. The results indicate that both factors significantly increased the stress intensity factor (SIF). Among the evaluated designs, the 15 mm -deep slot produced the highest SIFs and the shortest predicted crack-propagation life, indicating that slot depth was a key design parameter under the investigated conditions. The findings provide theoretical support for the structural design and fatigue evaluation of intelligent electric-shovel top sheave bearings. Full article

Climate change and variability pose serious threats to natural and human systems. The Mediterranean and North Africa (MNA) are among the world’s climate change hotspots. An in-depth understanding of the decadal climate variability in this region is critical to support planning and management, as well as adaptation in important sectors such as water resources. Therefore, in this study, fifth-generation ECMWF atmospheric reanalysis (ERA5) precipitation data and the outputs of the Coordinated Regional Downscaling Experiment-COmmon Regional Experiment (CORDEX-CORE) regional models were used to characterize the decadal precipitation variability in MNA and its sub-regions (Western North Africa: WNA, Sahara: SAH, southern Mediterranean: SMED, and northern Mediterranean: NMED). The models showed overestimation in most areas and underestimation in a few areas relative to the ERA5 data, with the magnitude varying by region and season. The positive biases obtained from the regional climate models (RCMs) were higher than the positive biases obtained from the general circulation models (GCMs). The wet biases were dominant during the annual, summer, and autumn seasons over MNA and its sub-regions. Negative biases were mostly associated with GCMs, mainly HadGEM2-ES and/or NorESM1-M; meanwhile, they were linked with RCMs such as CCLM5-0-15 and/or RegCM4_v7 and were mostly obtained in winter and spring. The multi-model mean (MME) was better at reproducing the decadal precipitation patterns over MNA, SMED, and NMED at all time scales, while REMO2015-NorESM1-M and the MME performed better than the remaining models at the annual time scale over WNA and SAH. These findings are useful for improving climate modeling, the water resources management and related sectors, and climate adaptation strategies in the region, especially in North Africa. The short-period coverage of the simulated data available for this study constitutes a limitation to the findings. Full article

Regenerative vibrations are a major hindrance to flexible cantilever structures during milling, resulting in a reduced tool life and diminished surface finish. In this research, two actively controlled methods are directly compared: a genetic algorithm (GA)-optimized classical proportional-integral-derivative (PID) controller and a GA-optimized fractional-order PID (FOPID) controller for a milling-dependent regenerative force on a flexible cantilever beam via numerical modeling, using piezoelectric actuator/sensor patches. The original aspect lies in synergistically combining fractional-order control with genetic algorithm-based optimization to actively reduce chatter and increase the machining stability of flexible milling systems. The simulation results from the GA-FOPID controller exhibited a reduction in vibration of approximately 92.70% compared with the open-loop system by reducing the RMS value from 1.5058 × 10⁻⁴ m to 1.0996 × 10⁻⁵ m. By reducing the vibration level and enlarging the predicted stable machining region, these improvements could potentially contribute to longer tool life, improved surface finish, and reduced post-processing requirements, although these technological benefits were not directly modeled in the present study. The main innovation of this work involves a unique combination of fractional-order control, PZT actuation, and genetic algorithm optimization in a regenerative milling delay architecture. To the best of the authors’ knowledge, based on the literature surveyed in this work, this combination of techniques has not previously been reported for active chatter suppression. The stability lobe diagram (SLD) analysis, conducted under the single-mode approximation that serves as the reference framework for the like-for-like comparison of the five investigated configurations, shows that the critical axial depth of cut at the representative spindle speed increases from a_p,crit(1500) = 0.061 mm for the uncontrolled system to 0.52 mm under GA-FOPID control. This enlargement of the predicted stable machining region was further confirmed, at a comparable order of magnitude, when the structural model was extended to include the two next bending modes, indicating that the trend is not an artifact of the single-mode simplification. Therefore, although the results were obtained exclusively from numerical simulation and have not yet been experimentally validated, they support the use of optimization-based methods to implement FOPID strategies as a means to increase both reliability and performance of flexible milling configurations. Full article

The pursuit of self-evolving AI raises a critical question: when is autonomous self-improvement sustainable rather than degenerative? Drawing an analogy to von Neumann’s complexity threshold for self-reproducing automata, we argue that sustainable recursive self-improvement in large language models (LLMs) requires a functional analogue: introspection—the system’s capacity to simulate its own operations and target modifications. Grounded in Kleene’s Second Recursion Theorem, we construct such introspective self-improvement programs and prove their key properties: completeness of self-modification, necessity of the reflective architecture, undecidability of improvement in general, and equivalence with Schmidhuber’s Gödel machine under a rewrite-equivalence notion, which transfers the global optimality guarantee. An empirical review, organized around these functional criteria, suggests that current LLMs exhibit only quasi-introspection.The available evidence does not establish complete introspection in the formal sense developed here, while pointing to several candidate structural bottlenecks, including incomplete self-access, feedforward processing, and limited computational depth. We outline architectural paths toward the threshold and discuss the safety implications of crossing it. Full article

Tajikistan is highly vulnerable to climate change and depends heavily on agriculture, making soil moisture dynamics critical for water and food security. This study provides a comprehensive assessment of soil moisture variability across four depth layers (0–10 cm, 10–40 cm, 40–100 cm, and 100–200 cm) from 2000 to 2021 using NASA’s GLDAS-2 model and remote sensing data for land-air temperature, precipitation, and vegetation to identify key nexus of soil moisture change. Moisture data were converted to volumetric water content (m³/m³) to enable valid cross-layer comparisons. Our findings show that volumetric soil moisture increases with depth, from 0.219 m³/m³ at the surface to 0.293 m³/m³ in the deepest layer. Eastern Tajikistan exhibits higher moisture levels than the west, likely due to differing precipitation patterns. Seasonally, spring replenishes the soil with the highest moisture (0.270 m³/m³ at 0–10 cm), while summer strips it away (0.194 m³/m³ at 0–10 cm), potentially reflecting evapotranspiration losses. A significant warming trend is evident, with mean annual temperature peaking at 4.32 °C in 2016. Precipitation strongly influences upper-layer moisture (correlation: 0.49 at 0–10 cm; 0.44 at 10–40 cm). While annual averages remain stable, seasonal trends reveal significant winter wetting (+0.00043 m³/m³ per year, p < 0.001) and summer drying in the deepest layer, indicating intensifying seasonal contrasts. Vegetation follows a parallel pattern, declining from 2000 to 2010 and recovering thereafter. Greening is observed in 16.74% of the area, concentrated in the western mountains and northern highlands, while only 2.98% shows decline, mostly in small, fragmented patches. These findings highlight the substantial connection between climate, soil moisture, and vegetation in Tajikistan. They also suggest the need for depth-specific and seasonally aware water management strategies in this climate-sensitive region. Managing water here means looking beyond surface averages and thinking in layers, seasons, and geography. Full article

The deformation and failure mechanism of deep mudstone under high temperature and high pressure (HTHP) is a critical issue constraining deep-drilling efficiency. Taking an HTHP mudstone formation in the western South China Sea as the research object, this study integrates X-ray diffraction, scanning electron microscopy, nanoindentation, HTHP triaxial compression tests, and FDEM numerical modeling incorporating mineral heterogeneity and Weibull strength distribution. The mudstone is predominantly composed of clay minerals (44.67%) and quartz (32.37%), with low hardness (1.42–2.96 GPa) and moderate elastic modulus (43.9–58.2 GPa). Under ambient conditions, uniaxial compressive strength is approximately 19.5 MPa with axial splitting failure; at 40 MPa confining pressure, strength increases to 121.8 MPa with shear failure; at 150 °C and 40 MPa, peak strength slightly decreases, yield point is delayed, and post-peak decline accelerates. The FDEM model, calibrated against experimental data, reasonably reproduces crack evolution and failure modes. However, due to limited tests (one per condition) and variations in specimen depth, statistical robustness is constrained; thus, this study does not yet establish a generalizable quantitative cross-scale correlation, and the findings are primarily applicable to the specific formation investigated. Full article

Membrane separation technology is extensively used in water treatment. However, during long-term operation, biofouling caused by bacteria and other microorganisms significantly limits the service life of membranes. Introducing antibacterial nanomaterials onto the membrane surface or into the internal structure is an effective way to combat biofouling. This review systematically summarizes recent progress in antibacterial membranes modified with different nanomaterials. First, we classify antibacterial nanomaterials by dimensionality and highlight their physicochemical properties and effects on overall membrane performance. Furthermore, we summarize the advantages, disadvantages, and applicability of three antibacterial nanomaterial modification strategies for membranes, including surface coating, grafting, and blending. Subsequently, we analyze in depth the main antibacterial mechanisms that enhance membrane performance, including metal ion release, reactive oxygen species oxidation, physical contact disruption, and anti-adhesion, as well as their synergistic effects. Finally, we critically evaluate the remaining challenges, such as interfacial compatibility between nanomaterials and polymers, controlled release of metal ions, and environmental safety. This review provides a reference for the rational design of high-performance antibacterial membranes. Full article

High-frequency induction hardening enhances the surface wear resistance and contact fatigue life of high-speed linear guides, but simultaneously produces an inhomogeneous, layered cross-sectional structure comprising a high-strength, low-ductility outer hardened layer and a low-strength, high-ductility inner core. This structural heterogeneity renders conventional straightening stroke prediction models—predicated on homogeneous material assumptions—fundamentally inadequate. Moreover, the iterative trial-bending operations ubiquitous in industrial practice progressively accumulate plastic strain, causing guide rails to exhibit erratic positive-to-negative deflection reversal during sequential straightening passes. To address these critical challenges, this study proposes a novel two-stage hybrid straightening strategy based on inverse finite element analysis (FEA) and closed-loop experimental feedback. An equivalent hardened layer depth (HD₀) is introduced as a parametric descriptor to construct a layered elastoplastic finite element model, and an inverse simulation strategy is developed to generate a comprehensive three-dimensional stroke–residual deflection prediction dataset encompassing both vertical and lateral straightening conditions across multiple support spans. Displacement-controlled three-point bending experiments validate the layered model and elucidate the mechanism by which cumulative plasticity progressively amplifies cross-sectional plastic sensitivity under repeated loading. Grounded in this physical insight, a hybrid straightening algorithm is formulated, combining dataset-driven initial stroke prediction for rapid large-deformation elimination with an upper-bound constraint and a measurement-feedback-driven sequential reduction compensation scheme for fine-tuning. Comparative experiments demonstrate that the proposed strategy effectively suppresses the oscillatory over-straightening characteristic of conventional empirical trial-and-error approaches, consistently reducing residual deflection below 0.05 mm within two to three loading cycles. This work bridges the gap between theoretical simulation and the complex physical state of actual machining, substantially improving both the efficiency and precision of straightening for guide rails with induction-hardened layers. Full article

BiOF has emerged as a promising functional material for photocatalysis, electrochemical energy storage, and ion adsorption due to its unique layered structure, excellent chemical stability, and tunable electronic properties. Density functional theory (DFT) calculations provide in-depth theoretical insights into the crystal structure, intrinsic defects, doping modification, and heterostructure construction of BiOF. This review systematically summarizes the recent DFT research progress of BiOF systems. Computational results reveal the lattice characteristics, bandgap features, built-in electric field distribution and facet anisotropy of BiOF, and highlight the critical influence of Bi semicore states on structural relaxation and electronic modulation. Defect engineering of bismuth and oxygen vacancies can effectively optimize band structure, accelerate carrier separation and improve catalytic performance. Cation and anion doping introduce impurity energy levels to narrow the bandgap and broaden the visible-light response range. Various BiOF-based heterostructures with different band alignment modes are analyzed, and the interfacial built-in electric field dominates charge separation, while excessive formation energy and unfavorable charge transfer still restrict material optimization. This work provides a systematic theoretical reference for the rational design and performance improvement of high-efficiency BiOF-based materials. Full article

Soil erosion is a critical global challenge and presents particularly alarming characteristics in the Amazon–Cerrado transition in Mato Grosso, a leading agricultural state in Brazil. Therefore, soil and water losses were evaluated under three soil cover conditions for corn and pasture cultivation (with vegetation cover, without vegetation cover, and without vegetation cover with soil scarified to a depth of 0.10 m) and four precipitation patterns (Advanced, Intermediate, Delayed, and Constant). The results showed that both soil cover and rainfall patterns directly influence the erosion processes. Soil loss increased up to sixfold under the Intermediate compared to the Constant rainfall, highlighting the strong influence of rainfall temporal distribution on erosion dynamics. The highest maximum runoff rates (MRR) and soil losses (SL) were recorded in tilled plots under maize cultivation, reaching 98.57 mm h⁻¹ and 5.90 g m⁻², respectively, under the intermediate pattern. In pasture areas, SL followed a similar pattern to the maize area, with maximum values of 6.96 g m⁻², but the MRR was recorded under the advanced pattern and in plots with cover (89.71 mm h⁻¹). This may be attributed to soil management conditions in pasture areas. Advanced and Intermediate patterns resulted in greater soil losses (3.78 and 2.04 g m², respectively), highlighting the impact of peak intensity timing on soil erosion. Greater soil losses were observed at the pasture experimental site than at the maize experimental site. Because the experiments were conducted at different locations with contrasting soil and management conditions, these differences should not be interpreted as being caused exclusively by crop type. The current study reinforces the need for erosion control and management strategies that account for natural variations in rainfall and soil cover to mitigate the negative impacts of land degradation on agricultural production and environmental sustainability. Full article

Urban informality in amphibious territories represents a critical yet understudied dimension of contemporary urbanisation in the Global South. This article analyses the interrelations between spatial transformation, social equity, and environmental change in Las Flores, an informal settlement located between the Mallorquín Lagoon and the Magdalena River in Barranquilla, Colombia. Drawing on a mixed-methods approach combining GIS interpretation, participatory mapping, and in-depth interviews, the study examines how processes of informal territorialisation have reshaped both the physical landscape and the social fabric of this amphibious environment. Results indicate that the settlement has expanded progressively over the past two decades, occupying areas of the wetland previously covered by mangroves and natural vegetation. This expansion has been accompanied by environmental degradation, soil infilling, and declining water quality. Residents face persistent infrastructural deficits, limited access to education and healthcare, and increasing social fragmentation between the formal and informal sectors. Yet, the community also exhibits strong organisational capacity, adaptive livelihoods, and a deep sense of place that sustains local identity and resilience. These dynamics exemplify the paradox of amphibious life: coexistence with water as both a resource and a source of vulnerability. Building on these findings, the study develops an urban socio-ecological conceptualisation of Amphibious Justice, a framework for interpreting equity, recognition, and governance in hybrid territories where urbanisation and land–water dynamics intersect. The article proposes a framework of equitable amphibious urbanism that integrates environmental restoration, social inclusion, and participatory governance. The findings suggest that sustainability in such territories cannot be achieved through technocratic restoration or forced resettlement, but through co-produced strategies that recognise local knowledge, tenure security, and ecological stewardship. Ultimately, the case of Las Flores offers insights into how cities in the Global South can pursue just and adaptive coexistence with water amid growing climate and urban pressures. Full article