Search Results (3,242)

In arid and semi-arid agroecosystems, soil water availability is a critical regulator of coupled carbon–water (C–W) cycling, vegetation dynamics, and ecosystem resilience under environmental change. This research investigated the temporal evolution and spatial patterns of soil moisture across sand dune slopes within the Mu Us Sandy Land. Data were collected via a combination of continuous high-frequency in situ monitoring spanning 20 months and manual sampling campaigns. We analyzed moisture levels at various depths and slope positions (windward vs. leeward) to understand their distribution and reaction to precipitation. Statistical analysis of all rainfall events that triggered measurable soil moisture responses showed that precipitation was the primary determinant of soil moisture fluctuations. Specifically, shallow soil (10 cm) reacts rapidly to rainfall events > 4.6 mm, whereas intermediate layers (20–50 cm) require > 8.6 mm. Conversely, deep soil moisture (>100 cm) remains stable, responding only to substantial storm events (>50 mm). Topography exerts a strong control over spatial variance; notably, slope toes consistently exhibit higher moisture than upper sections, particularly during wet seasons, indicating strong topographic control on moisture redistribution and possibly reflecting lateral subsurface transfer. Additionally, a nonlinear correlation was observed between mean moisture content and its variability, peaking under intermediate moisture conditions. The results provide a mechanistic basis for understanding agroecosystem responses to climate variability and offer valuable insights for adaptive land management, vegetation restoration, and hydrological modeling in water-limited regions. Full article

The FOCUS mission is an integrative project developed at the Universidad Nacional de San Martín (UNSAM), Argentina, featuring a constellation of small satellites equipped with X-band Synthetic Aperture Radar (SAR) sensors. Designed with autonomous orbit control, the mission enables Interferometric SAR (InSAR) applications for critical infrastructure monitoring, providing scalable and cost-effective global observation capabilities. This paper presents the modeling, design, and numerical evaluation of the Attitude and Orbit Determination and Control System (AODCS) for the FOCUS mission. The analysis incorporates realistic constraints, including actuator saturation, sensor noise, underactuation effects, and hardware limitations—specifically regarding magnetorquer magnetic moments, reaction wheel capacities, and propulsion unit impulse bounds. Utilizing the NASA 42 attitude and orbit simulator, numerical simulations were conducted to assess stability, pointing accuracy, and agile maneuver tracking through specialized guidance laws. The results confirm that the proposed AODCS architecture achieves stable, responsive performance and supports continuous orbit maintenance, ensuring adequate target acquisition per orbit. Additionally, the selection of star trackers allows achieving a secondary objective through the detection of Resident Space Objects. Full article

In this study, a three-dimensional simulation of a walking-beam reheating furnace was developed to improve the steel slab reheating process and reduce surface oxidation kinetics using computational fluid dynamics (CFD). Combustion, heat transfer, fluid dynamics, and chemical reaction models were integrated into the numerical framework of this study. In addition, dynamic mesh remeshing was coupled through user-defined functions (UDFs), enabling the simultaneous simulation of slab movement and evolution of the involved transport phenomena. Turbulence was modeled with the realizable k-ε formulation, combustion with the Eddy Dissipation model, and radiation with the P-1 model coupled with WSGGM to include CO₂ and H₂O gas radiation. Scale formation was modeled using customized functions based on Arrhenius-type kinetics and Wagner’s oxidation model, evaluating its growth as a function of time, temperature, and furnace atmosphere. The predicted thermal evolution inside the furnace was validated using industrial data, yielding an average deviation of 5%. Furthermore, the proposed operating conditions led to an average slab temperature of 1289.77 °C at the exit of the homogenization zone, which was 16 °C higher than that under the current operation but still within the target range (1250 ± 50 °C). The reduction in combustion air decreased energy losses and improved product quality, lowering the molar oxygen content in the furnace atmosphere from 4.9 × 10² mol to 6.7 × 10¹ mol. Additionally, annual savings of 4,793,472 kg of natural gas and 13,884 tons of steel were estimated owing to reduced oxidation losses. The proposed air–fuel adjustment led to estimated annual energy savings (equivalent to 4,793,472 kg of natural gas) and a reduction in material loss due to oxidation from 4.5% to 3.75% (an absolute reduction of 0.75 percentage points; relative reduction ≈ 16.7%), which has a significant industrial impact on metal conservation and descaling cost reduction. Although there are CFD studies on plate overheating and scale growth separately, this work presents three main contributions: (1) the integration, within a single numerical framework, of combustion, radiation, species transport, oxidation kinetics, and actual plate movement using a dynamic mesh; (2) validation against continuous industrial records (16 thermocouples) and quantification of operational benefits such as fuel savings and reduced material loss; and (3) a comparative analysis between actual and optimized conditions, which standardize the air–methane ratio. Full article

Parkinson’s disease (PD) is associated with progressive gait deterioration; however, widely used clinical scales such as the Hoehn & Yahr (H&Y) stage are limited in capturing continuous severity changes due to subjectivity and discrete grading. This study proposes a two-stage explainable AI framework using vertical ground reaction force (VGRF) signals to achieve reproducible PD detection and continuous severity estimation. In the first stage, three deep learning models, temporal convolutional network (TCN), BiGRU with attention, and FCNN-Transformer, were trained using windowed VGRF signals under repeated subject-wise data segmentation. All models achieved high discrimination performance (AUC ≥ 0.93), with FCNN-Transformer showing the highest mean AUC (0.940) and statistically superior performance (paired Wilcoxon test, p < 0.05). Stability-based explainable AI using Integrated Gradients consistently identified variability-related VGRF features as the most informative, which were also significantly different between groups at the data level (p < 0.001, FDR-corrected). In the second stage, XGBoost regression was applied to PD subjects to predict continuous H&Y severity, achieving strong correlation with clinical grades (Spearman ρ = 0.921, p < 0.001), low error (MAE = 0.158, RMSE = 0.241), and high determination (R² = 0.953). This shows that gait-based features are a sensitive enough signal to continuously quantify disease progression. In addition, in the TREND prospective longitudinal cohort (n = 696), wearable walking indicators differed significantly from those of non-patients prior to diagnosis, and a decline in walking pace was observed approximately four years before Parkinson’s disease diagnosis, providing the basis for early screening and monitoring using gait-based digital biomarkers. These results demonstrate that gait-based digital biomarkers can objectively quantify both PD presence and disease progression. The proposed framework provides a reproducible, explainable, and clinically interpretable AI-based decision support approach for PD assessment. Full article

To overcome the limitations imposed by the intermittent nature of sunlight in photocatalytic applications, this research constructs a round-the-clock purification system. We integrated an optimized S-scheme CoFe₂O₄/BiVO₄ (CFO/BV) heterojunction (synthesized via ultrasonic self-assembly at a 0.5:0.5 ratio) with a thermal energy storage (TES) unit consisting of SiO₂-encapsulated Na₂SO₄·10H₂O phase change materials (PCMs). Comprehensive characterization techniques, including XRD, HRTEM, UV-Vis DRS, EPR, and DSC, confirmed the successful formation of the interface, a broadened visible-light response (λ > 650 nm), efficient radical production, and a high latent heat storage capacity (>200 J/g). Under simulated solar irradiation, the composite exhibited superior performance, degrading 98% of the Rhodamine B within 6 h (k = 0.00994 min⁻¹), significantly surpassing single-component counterparts. More importantly, during the subsequent 12 h dark period, the heat released from the PCM maintained the reaction temperature above 35 °C, driving a 64% degradation efficiency via a thermocatalytic pathway. The system demonstrated robust stability (>90% efficiency after five cycles), excellent magnetic recoverability (98%), and high tolerance to saline textile wastewater (<10% activity loss). Furthermore, Life Cycle Assessment (LCA) indicated a 40% reduction in energy consumption compared to conventional UV/TiO₂ processes, highlighting a sustainable strategy for continuous wastewater remediation through synergistic photocatalysis and thermocatalysis. Full article

Background: The need for autonomous aerial surveillance originates from weaknesses in manual monitoring, such as late response, low scalability and rigid patrol plans. AI and GPS-driven smart aerial monitoring present an attractive solution for continuous adaptive wide-area surveillance. Objective: In this paper, we aim at designing and validating experimentally a low-cost drone-based unmanned autonomous mission patrolling system with waypoint navigation, real-time video backhauling, AI-based human/object detection and GPS path re-planning when an event occurs to ensure the safety of patrol missions under battery constraints. Methods: The proposed architecture combines autonomous navigation and embedded flight-control with online analog video streaming and ground-station-based computer vision processing. Object detection based on deep learning for live aerial video is used, and the proposed system’s performance is tested at different altitudes, lighting states and GPS patrol plans. Results: Experimental results show that the proposed method can obtain stable waypoint tracking with a clear real-time video downlink in patrol missions. The system is able to adaptively modify paths as a reaction to detected events and commence safe return-to-home functionality during low-battery conditions. The proposed detection model obtains a mean average precision of 87.4%, with an F1-score of 0.89 and real-time inference latency (20–25 ms per frame) that enables fast service without any interruption in practice during surveillance deployment. Conclusions: Experimental results show that the proposed method can obtain stable waypoint tracking with a clear real-time video downlink in patrol missions. The system can adaptively modify paths as a reaction to detected events and commence safe return-to-home functionality during low-battery conditions. The proposed detection model obtains a mean average precision of 87.4%, with an F1-score of 0.89 and real-time inference latency (20–25 ms per frame) that enables fast service without any interruption in practice during surveillance deployment. Full article

Polymer adhesive materials have been utilized across a wide range of applications, including adhesion to wood, metals, and biomaterial substrates. To meet increasing performance demands, the development of high-performance adhesive materials continues to be actively pursued by introducing advanced functions and capabilities into polymer networks. By incorporating dynamic covalent bonds into the polymer network, these materials gain self-healing and reprocessing abilities. While these materials exhibit high mechanical robustness and stability under service conditions, the bonding/rebonding reactions of dynamic covalent bonds allow the polymers to detach from target surfaces when needed. Additionally, noncovalent interactions within the network and between the polymer and the target surface significantly contribute to overall adhesive strength. Although dynamic covalent bonds and noncovalent interactions operate through different mechanisms, both contribute significantly to adhesive performance. This review manuscript presents studies on polymer networks containing dynamic covalent bonds and non-covalent interactions. Based on these studies, the respective contributions of each type of bond to the superior adhesive strength of the materials are discussed, and potential target substrates for adhesion, including wood, metal, and biomaterials, are proposed. Full article

Mining at the Red Dog Mine generated a 60 million-tonne waste rock stockpile that produces acid rock drainage with pH values typically below 3. The drainage chemistry is controlled by the competing kinetics of acid-generating iron sulfide weathering and acid-neutralizing carbonate and phosphate dissolution. To evaluate the interaction of these reactions, waste rock was collected from the stockpile by drilling a borehole from the surface to a depth of 52 m, terminating at the shale bedrock. A temporal paste pH test was conducted to extend the utility of the static paste pH test to a continuous (30 min) measurement of pH and ORP over a 24-h period. The 24-h paste pH results revealed multiple acid-generating and acid-neutralizing reactions: pH values ranged from 3.31 to 6.96. Mineralogical analysis indicated initial acidic conditions in 12 of the depth intervals (upper and lower zones) were due to the release of stored acidity from soluble iron sulfate minerals. Subsequent pH increases were driven by calcite dissolution and likely phosphate and clay mineral acid-neutralizing reactions. Conversely, late-stage pH decreases in the lower middle zone indicated the presence of highly reactive/available iron sulfide surfaces, which allowed for earlier acid generation compared to less reactive/available iron sulfide minerals in other zones. The utility of this temporal paste pH test and associated mineral analysis is to understand the mineralogical controls on early temporal acid generation to guide batch reactor testing of remaining acid potential under saturated conditions. This sequential approach provides critical information for predicting long-term acid generation and information management of the stockpile for mine site remediation and closure. Full article

Building lighting has a significant impact on occupant health and well-being, energy efficiency, spatial perception, and visual comfort. Many current building lighting systems, however, continue to be insufficiently responsive to changing environmental conditions and human-centric demands, leading to ineffective energy use, poor visual quality, and disruption of the circadian rhythm. This disparity highlights the need for modern buildings to incorporate integrated, intelligent, and sustainable lighting design strategies. This review offers a methodical examination of current, emerging and future developments in building lighting research in six related fields within an architectural scope of building design and performance. To assess lighting effectiveness, it first examines both qualitative and quantitative performance metrics, including illuminance, luminance distribution, glare, color quality, and user comfort. Second, it examines lighting control systems that use tunable light sources that can dynamically change the spectral composition and intensity in response to task demands, occupancy patterns, and daylight availability. Third, the study examines circadian-centric lighting strategies, focusing on digital modeling and simulation approaches that capture real-world lighting conditions and biological reactions. Fourth, the function of virtual reality and sophisticated visualization tools is examined, emphasizing their role in design decision-making and pre-implementation assessment. Fifth, a critical evaluation is conducted of the expanding use of machine learning and data-driven techniques in adaptive lighting control, prediction, and optimization. Limited real-time adaptability, inadequate personalization, disjointed simulation frameworks, and poor integration of human-centric metrics with intelligent control systems are some of the major research gaps. Sustainable Development Goal (SDG) 7, SDG 11, and SDG 3 are in line with the review, which ends with a summary of future paths toward intelligent, energy-efficient, and human-centered building lighting systems. Full article

Gel polymer electrolytes (GPEs) typically suffer from sluggish kinetics and interfacial instability at elevated temperatures and high voltages. Herein, 3-(trifluoromethyl)-1H-1,2,4-triazole (TTA) is employed to construct an ultrathin (~25 μm), robust, and homogeneous GPE. TTA acts as a molecular bridge, significantly improving compatibility between the PVDF-HFP (Poly(vinylidene fluoride-co-hexafluoropropylene)) matrix and LLZTO (Li_6.4La₃Zr_1.4Ta_0.6O₁₂) fillers to create continuous ion-conducting pathways. Consequently, the TTA-GPEs exhibits high ionic conductivity (0.267 mS cm⁻¹ at room temperature), low activation energy (0.181 eV), and an increased lithium-ion transference number (0.425). Advanced surface analysis reveals that TTA preferentially reacts to form a dense, gradient hierarchical interphase (solid electrolyte interphase/cathode electrolyte interphase, SEI/CEI) enriched with inorganic species (LiF, Li₃N, and Li₂S) on the inner side. This architecture suppresses parasitic reactions and lithium dendrite growth. Accordingly, NCM811(LiNi_0.8Co_0.1Mn_0.1O₂)//Li batteries with TTA-GPEs demonstrate stable cycling at 80 °C and 1C, retaining 57.68% capacity after 125 cycles—significantly outperforming benchmarks. This study offers a molecular engineering strategy to simultaneously optimize bulk transport and interfacial stability for high-energy-density solid-state batteries. Full article

This study presents AgroNova—a hybrid IoT architecture for autonomous monitoring and management of microclimate in greenhouse environments. The system combines a capillary wireless sensor network, gateway-level rule-based agents, a server agent, cloud services and an advisory component based on a large language model (LLM) that supports local decision-making by incorporating external contextual information from meteorological services. The proposed architecture was validated through a seven-month deployment in an unheated tomato greenhouse, during which more than 380,000 environmental measurements were collected from five sensor nodes. The system operated continuously under real agricultural conditions, including during temporary internet connectivity interruptions, due to the autonomous gateway-level control and deterministic fallback mechanisms. The analysis of the collected data includes 3110 environmental threshold exceedance events, in which recovery dynamics, reaction latency, and actuator activation frequency were evaluated. The results show that the architecture supports stable autonomous operation under limited actuation conditions, with an average local reaction latency of less than 1 s, while physical actuator operations occur in approximately 2.3% of all control decisions. This behavior reflects a conservative control strategy that limits unnecessary mechanical operations and contributes to stable system operation. The experimental integration of a consultative LLM module within the server-side agent demonstrates the potential for context-enriched decision support using external meteorological data, while final control decisions remain under the authority of the gateway-based deterministic control mechanism. The main contribution of this study is the demonstration of a hybrid IoT architecture that combines edge-level autonomy with context-assisted reasoning, validated through deployment in a real greenhouse environment. Full article

In situ stope leaching is an economically and environmentally friendly metal recovery method suitable for low-grade copper ores, with the internal temperature of the deposit typically ranging from 30 to 45 °C. The fragmented ore with a specific particle size distribution formed after blasting constitutes a complex pore structure, which provides channels for acid solution infiltration and chemical reactions, directly affecting leaching efficiency. To reveal the spatiotemporal heterogeneity of pore structure evolution during leaching at the microscopic level and its fundamental impact on macroscopic permeability and leaching rate, leaching experiments were conducted using acid leaching methods based on ore particle models with different size distributions. Computed Tomography (CT) scanning technology and Avizo 2023 software were employed to scan and reconstruct three-dimensional physical models, enabling quantitative calculation and analysis of the evolutionary patterns of pore structure parameters. These results were then correlated with the measured leaching rate evolution. The findings indicate that both the connectivity and overall volumetric porosity of the stope models for Sample 1 (2–20 mm, uniformly graded) and Sample 2 (0–20 mm, high fine particle content) continuously decreased during leaching, with a more pronounced decline in the lower regions, particularly for Sample 2. The pore-throat sizes of both models increased with leaching time, and after 45 days of leaching, the average pore radius of the two granular ore samples increased by 16.75% and 9.21%, respectively. The leaching rate showed a high correlation with the effective reaction area (R² = 0.93). During the 0–15-day period, a sharp decline in the effective reaction area led to a rapid decrease in leaching efficiency. Sample 1 exhibited a longer effective leaching duration, achieving a leaching rate of 61%, significantly higher than that of Sample 2. Full article

To address the corrosion protection issues for hot components of high-end equipment in extreme service environments, the C276 alloy coating was deposited on the surface of 304 stainless steel via high-velocity air fuel (HVAF) spraying. The extreme conditions of 1000 °C temperature, an atmosphere containing 6% HCl, and a flow rate of 30 m/s were simulated in the study using a high-temperature airflow corrosion erosion device. The C276 coating and the 304 stainless steel substrates were subjected to a corrosion test for 25 min. The surface phase composition, element distribution, corrosion product characteristics, and cross-section structure of the samples before and after corrosion were systematically analyzed by means of a scanning electron microscope, an energy dispersive spectrometer, and an X-ray diffractometer. The mechanism of high-temperature chlorination corrosion was deduced through thermodynamic and kinetic analysis. The results show that compared with 304 stainless steel, the C276 alloy coating exhibits better corrosion resistance in an extremely high-temperature environment containing HCl, and the average weight gain and growth rate of the corrosion layer were lower. The main corrosion products on the C276 coating surface are Fe₂O₃, FeO, FeCl₂, NiO, and Cr₂O₃, among which the oxides of Ni and Cr form a continuous and dense protective oxide layer that effectively inhibits the intrusion of corrosive media. The high-temperature HCl corrosion follows the ‘chlorination–oxidation’ cycle mechanism, and Cl₂ plays a catalytic role in the reaction and accelerates the corrosion process. Full article

The performance of flux-cored Zn-Al filler metal is susceptible to corrosion-induced degradation, thereby impairing its brazability. In this study, flux-cored Zn-2Al filler metals are prepared, and the salt spray test is subsequently carried out on the prepared filler metals. Scanning transmission electron microscope is used to identify the phases in filler metals. An electrochemical workstation was employed to test the electrochemical performance of the filler metals. The corrosion pathways and evolution patterns of filler metals are analyzed. The findings demonstrate that the corrosion type of the filler metals is electrochemical corrosion, characterized primarily by the corrosion modes of pitting corrosion and intergranular corrosion. The cathode is the α-Al phase, which undergoes an oxygen-absorption corrosion reaction, while the anode is the η-Zn phase, which experiences corrosion and subsequent dissolution. The continuously distributed α-Al phase bands and discontinuously distributed large-sized rod-like α-Al phases accelerate the corrosion rate, and the corrosion propagation rate along the extrusion direction is higher than that in the radially inward direction. After 15 days of salt spray corrosion, the tensile strength of filler metals decreases by 16.2%, and the elongation rate decreases to 3.73%. Full article

Zirconium hydride is susceptible to dehydrogenation at elevated temperatures. In this study, zirconium hydride was oxidized by in situ oxidation in a CO₂ atmosphere at temperatures ranging from 550 to 700 °C for 10 h. The morphology, elemental distribution, phase structure, and hydrogen barrier performance of the resulting oxide films were systematically characterized using SEM, EDS, XRD, film adhesion and microhardness tests, and dehydrogenation experiments. At 550–600 °C, the formed oxide films are thin and non-uniform, containing numerous micropores and cracks, which results in limited hydrogen barrier performance. When the oxidation temperature is increased to 650 °C, a better balance between the oxidation reaction and diffusion processes is achieved. This leads to the formation of a dense, continuous, and uniform ZrO₂ film with strong adhesion to the substrate. As a result, the initial dehydrogenation temperature increases to 660 °C, while both the dehydrogenation rate and cumulative hydrogen release are significantly reduced, indicating the best overall hydrogen resistance. However, further increasing the oxidation temperature to 700 °C causes an excessively high oxidation rate, which introduces large growth and thermal stresses. These stresses promote the formation of microcracks in the oxide film, weaken the interfacial bonding strength, and consequently reduce the hydrogen barrier performance. The results demonstrate that the hydrogen permeation resistance of the oxide film is mainly governed by film compactness, defect evolution, and interfacial integrity. Based on these findings, 650 °C is identified as the optimal processing temperature for producing a high-quality hydrogen-resistant ZrO₂ film on zirconium hydride under a CO₂ atmosphere. Full article