Search Results (1,076)

Direct Torque Control (DTC) for induction motors (IMs) is an advanced method derived from Field-Oriented Control (FOC). In DTC, a voltage source inverter (VSI) is employed to directly regulate the stator flux linkage and electromagnetic torque through space vector modulation (VSM), where the optimal switching vector is selected for the VSI. Similarly to FOC, the stator flux and electromagnetic torque are independently controlled to deliver enhanced dynamic performance. However, DTC still suffers from certain drawbacks, such as slow transient response, limited dynamic performance, and high ripples in torque and flux. In this paper, an improved DTC method is proposed for a three-phase squirrel-cage induction motor. Specifically, a Type-2 fuzzy logic controller is employed to regulate both the stator flux and electromagnetic torque (T2FLC). The proposed method (FLCDTC) combines a three-level VSI with dual-band hysteresis (DBHW) switching to generate the gating signals for the insulated gate bipolar transistors (IGBTs). This approach effectively reduces the total harmonic distortion (THD) in torque and stator current, lowers the common-mode voltage (CMV), and enhances the overall motor performance. Simulation results under random noise distribution demonstrate the robustness of the proposed controller, even at low operating speeds. Finally, the effectiveness of the algorithm is validated in real-time through hardware-in-the-loop (HIL) implementation. Full article

New-energy plants and battery energy-storage stations increasingly depend on software-defined supervision, remote maintenance, and event-driven control, which makes cyber protection inseparable from operational responsiveness. This study presents a calibrated context-aware Security-as-a-Service orchestration framework, denoted SECaaS-CARO, for station-oriented adaptive risk control. The framework separates field assets, control services, security services, and an adaptive decision layer, and it uses a monotone nine-indicator risk score whose weights are calibrated from the training split rather than fixed heuristically. A validation-based threshold search maps that score to low-, medium-, and high-intensity service chains so that protection strength changes with session context instead of remaining static. A reproducible semi-synthetic dataset containing 17,000 station sessions was used to emulate operator login, remote maintenance, gateway misuse, and malicious command scenarios. Across 10 independently resampled 5000-session test streams, SECaaS-CARO achieved an F1 score of 0.973, a blocking success of 0.965, and the highest deployment utility of 1.173 while reducing mean latency to 21.28 ms compared with 27.06 ms for Logistic-Fixed and 28.15 ms for RandomForest-Fixed. The results indicate that an interpretable calibrated service-orchestration policy can preserve near-supervised detection quality while materially improving deployment-oriented efficiency for new-energy and energy-storage stations. Full article

Reliable front-end pressure-pulse generation is critical to mud-pulse telemetry because waveform distortion introduced at the rotary valve propagates through the telemetry chain and reduces downstream recoverability. This paper targets accurate and computationally tractable control of an intelligent drill-bit rotary valve under actuator limits, parameter drift, and downhole-like disturbances. A control-oriented electromechanical–hydraulic grey-box model is established, and a real-time lexicographic model predictive control (MPC) framework with candidate pre-screening, move blocking, and online correction/compensation is developed and compared with proportional–integral–derivative (PID) control and conventional MPC. Under a sampling period of $T_s=20\mathrm{ms}$, the proposed controller reduces the step-tracking rise time from $2.18\mathrm{s}$ to $1.76\mathrm{s}$ and the steady-state pressure error from $0.1208\mathrm{MPa}$ to $0.0292\mathrm{MPa}$ relative to conventional MPC. In the pulse-output and mismatch–disturbance scenarios, it further maintains lower steady-state pressure error while reducing the cumulative input variation from $51.0$ to $11.5$ and from $121.5$ to $19.5$, respectively. The observed 99th-percentile and worst-case MATLAB workstation execution times remain below one sampling period, while supplementary mismatch–disturbance sensitivity maps indicate a favorable accuracy–timing compromise within the tested numerical envelope. These results support the proposed method as a simulation-validated candidate for low-complexity rotary-valve control and motivate subsequent bench/hardware-in-the-loop (HIL) validation rather than field-qualified deployment claims. Full article

Gold-enriched silica-listvenite rock from the Kaymaz Gold Deposit (KGD) was investigated to determine the effect of regional tectonism and Eocene granite intrusion on gold mineralization. The questions “is granite a heat–fluid source or a lithologic barrier?” and “how does regional tectonism affect gold mineralization?” remain unclear. This study aims to clarify these questions via field studies, core sample observations, petrography, ore microscopy, scanning electron microscopy (SEM), XRD, and fluid inclusion analyses; these methods were applied to samples collected from four different sites within the KGD (1—Damdamca, 2—Karakaya, 3—Mermerlik, and 4—Kızılağıl). The highest-grade gold mineralization is present in the listvenite rock in the fault-controlled contact zone between serpentinite and granite, whereas granite hosts minor gold and silver enrichments near the contact. The orientations of contacts are compatible with the NW-SE-trending Eskişehir fault zone in Karakaya and the NE-SW-trending tear faults in Damdamca. Listvenite is silica-rich and has high iron oxy-hydroxide content, while granite is argilized and silicified along the contact with listvenite. Native gold grains were found between the quartz minerals of listvenite and granite. The adsorption of gold by goethite ± lepidocrocite has been observed in the listvenite samples of Mermerlik. Chromite, Ni-sulfide minerals, pyrite, arsenopyrite, galena, native silver, acanthite, iodargyrite, and goethite ± lepidocrocite are the other detected ore minerals. Secondary Cr-Fe-Mn oxide minerals were detected in a granite sample via SEM analyses. The data indicates that listvenitization-causing fluid partially remobilized these metals along with Au and reprecipitated them in the granite during mineralization. The homogenization temperatures (Th) (°C) of fluid inclusions vary between 116 and 393 °C, and the Th (°C) distribution indicates multi-phase mineralization. The Th (°C) values of listvenite and silicified granite are quite similar, which indicates that the same hydrothermal fluid circulated in both lithologies. The low salinity values (1.2–5.4%) indicate that the hydrothermal fluid was derived predominantly from meteoric water. The liquid–vapor ratios of inclusions and quartz textures indicate non-boiling conditions. Gold enrichment in the KGD developed in relation to the circulation of hydrothermal fluids along the faults. The KGD shows typical fluid inclusions, alteration properties, and mineral paragenesis of low-sulfidation-type epithermal deposits. Our study data indicates that meteoric water-rich hydrothermal fluid circulated along the fault zones, dissolved Au and other related elements from the serpentinite, and reprecipitated in the listvenite-altered granite. Granite acts as an impermeable barrier, leading to the circulation of hydrothermal fluids through the contact. Supergene activities affect the mineralization in both Mermerlik and Kızılağıl. No evidence indicating the magmatic origin of gold mineralization was observed. Full article

Crop attribute detection, as a key component of intelligent agricultural harvesting machinery, plays a crucial role in harvesting efficiency, loss reduction, and autonomous operation control. Compared with existing reviews on artificial intelligence and sensing technologies in agriculture, this review focuses on crop attribute detection scenarios oriented toward the intelligent decision-making and control requirements of agricultural harvesting machinery. It mainly analyzes crop attributes that affect harvesting operations, as well as the sensors and algorithms involved in detecting these attributes, and further clarifies the relationship between detection methods and control decisions in agricultural harvesting machinery. For grain crops, the key attributes relevant to harvesting operations include plant height, plant density, spike number, crop lodging, canopy structure, and crop position. For fruit and vegetable crops, the key attributes relevant to harvesting operations include maturity, position, and quality. From the perspectives of multi-source data acquisition, data analysis, and attribute detection algorithms, the key technologies in the field of crop attribute detection are systematically summarized and analyzed, including sensors used in crop attribute detection, such as RGB, spectral, near-infrared, and LiDAR sensors, as well as data analysis and recognition approaches, such as image classification, object detection, and point cloud analysis. The complexity of field environments and the dynamics of machine operation are analyzed, highlighting the technical bottlenecks of current detection systems in environmental adaptability, real-time responsiveness, and resistance to interference. To address these challenges, feasible optimization directions were proposed, including multi-sensor fusion, weakly supervised learning, and few-shot learning. This review aims to provide systematic references and theoretical support for the coordinated development of crop detection and control decision-making in intelligent agricultural harvesting systems. Full article

Salt-bearing foreland fold–thrust belts represent a critical tectonic system for ultra-deep hydrocarbon exploration. In the Kalasu structural belt of the Kuqa Depression—characterized by the “four extremes” of ultra-high temperature, pressure, salinity, and stress—conventional single-detachment models fail to adequately resolve the complex subsalt structures. To address this challenge, this study integrates high-resolution 3D seismic data, field outcrop observations, well logs, balanced cross-sections, and particle image velocimetry (PIV)-monitored physical modeling to propose a ramp–flat multi-detachment model. Our results demonstrate that deformation is governed by four regional detachment horizons: gypsum-salt layers, thick mudstones, coal-bearing strata, and the basement, which vertically partition the basin into six tectonic units: supra-salt, salt, subsalt, supra-coal, coal, and sub-coal basement. The structural architecture is controlled by five key factors: (1) paleo-uplift geometry, (2) distance from the South Tianshan orogenic front, (3) orientation of basin-bounding faults, (4) regional stress regime (pure compression versus transpression), and (5) rheological contrasts among detachment layers. The kinematic evolution follows a progressive sequence: basement-involved thrusting → multi-level ramp–flat detachment folding → cover detachment. Three primary trap levels are identified—subsalt, supra-coal, and sub-coal—hosting six distinct trap styles: pop-up anticlines, imbricate faulted anticlines, structural triangle zones, fault-bend fold anticlines, supra-coal anticlines, and inter-coal/sub-coal anticlines. Notably, under transpressional stress, oblique paleo-uplifts control the formation of enigmatic “fish-scale” arcuate trap belts composed of fault-bend fold anticlines. Full article

Hybrid hydrogen energy storage systems are increasingly considered for renewable integration in rural and weak-grid contexts, yet much of the literature remains simulation-based, site-specific, or insufficiently explicit about control and operational performance. This paper examines a hybrid hydro–PV–battery–hydrogen system operated at the Agkistron Living Lab in Northern Greece and assesses the role of layered storage in renewable surplus valorization and resilience-oriented operation. This study combines a system architecture description, a supervisory energy management strategy based on Hybrid Automata, and analysis of field data under both grid-connected and intentional off-grid conditions. The installation integrates hydropower, photovoltaics, battery storage, alkaline electrolysis, hydrogen storage, and PEMFCs. The results show that during on-grid operation, the EMS prioritizes battery charging and then hydrogen production, enabling high renewable utilization and low curtailment while preparing reserves for outages. During a 48 h intentional islanding event, the battery and hydrogen pathway operated sequentially, achieving an autonomy index of 82%, compared with 36% for the battery-only benchmark. Although the hydrogen pathway showed lower round-trip efficiency than battery-only storage, it substantially extended off-grid autonomy and continuity of supply. The findings support hybrid battery–hydrogen storage as a transferable operating concept for rural systems where renewable surplus and resilience requirements coexist. Full article

To address the large variability in existing pavement distress in expressway reconstruction and expansion projects in Zhejiang Province, China, a differentiated overlay design and decision-making method based on multi-index evaluation was proposed using the Ningbo section of the Yongtaiwen Expressway as a case study. Based on 3D ground-penetrating radar (GPR), falling weight deflectometer (FWD), and field coring tests, the existing pavement was classified into five conditions: intact pavement, slight and severe surface-layer distress, and slight and severe base-layer distress. For pavements with surface-layer distress, two alternative overlay schemes were designed. Scheme I was defined as a performance-oriented scheme using high-performance SMA/Superpave asphalt layers and an ATB-25 transition layer where necessary to improve fatigue resistance and coordinated structural performance. Scheme II was defined as an economy-oriented scheme using conventional AC layers and crack-resistant or bonding measures to reduce construction cost while maintaining adequate structural capacity. An ABAQUS-based temperature–load coupled finite element model considering the temperature-sensitive viscoelastic characteristics of asphalt layers was established to analyze the mechanical responses and service lives of the overlay schemes, and the entropy weight–TOPSIS method was used for multi-objective comprehensive decision-making. The results showed that temperature–load coupling markedly increased the tensile strain at the bottom of the asphalt overlay and was a key controlling factor in design. All schemes satisfied the 15-year design requirement, while the base-layer fatigue life of the performance-oriented scheme (Scheme I) was generally no lower than that of the cost-oriented scheme (Scheme II), indicating better long-term service reliability. In addition, the relative closeness coefficients of Scheme I under slight and severe surface-layer distress were 0.586 and 0.546, respectively, both higher than those of the cost-oriented scheme. The proposed method can effectively balance technical performance and life-cycle cost and provides a useful reference for differentiated overlay design in similar expressway reconstruction and expansion projects in hot–humid regions. Full article

Monitoring center-of-mass is crucial for assessing postural control, but field measurements are often impractical or cost-prohibitive. This study investigates the feasibility of predicting center-of-mass kinematics from the motion of an unstable base—the Sensopro Luna—using deep learning, eliminating the need for wearable sensors. We conducted a cross-sectional study in which 64 participants were recorded performing three coordination exercises (Single-Leg Stance, Stepping, and Waves). Marker-based motion capture and auxiliary inertial sensors were used to record reference and tape kinematics. The model inputs consisted of IMU- and motion-capture-derived tape segment orientations, IMU accelerations and angular velocities, and algorithmic estimates of the lowest tape positions. Nine axis-specific exercise models were developed using a hybrid Encoder–LSTM–Decoder architecture and compared against linear regression baselines. Our results indicate that the deep learning models successfully predicted horizontal center-of-mass displacements (DNN Mean Absolute Errors of 16.1–23.7 mm for X-axis and 4.4–31.3 mm for Y-axis) and exhibited descriptively lower errors than linear models in mean absolute error and signal morphology. However, vertical predictions were less reliable, likely due to the physical constraints inherent to the kinematics of the unstable base. Error analysis revealed that prediction accuracy was highest within common postural ranges, but decreased for extreme displacements. These findings provide a proof-of-concept for wearable-free postural monitoring, particularly for movement along the mediolateral and sagittal axes. Such a system could facilitate automated, cost-effective postural feedback and performance tracking in rehabilitation and fitness environments, supporting autonomous coordination training without the practical constraints of traditional measurement systems. Full article

High-Andean grasslands in the Central Andes of Peru are severely degraded by Lepidium meyenii (maca) cultivation, compromising pasture structure and forage availability for sustainable livestock production. A factorial field experiment evaluated restoration timing and pasture-oriented seed mixtures by manipulating resting time after abandonment (0, 1, 2, and 3 years) and restoration treatment (control; Festuca dolichophylla monoculture; full mixture of Dactylis glomerata + Lolium spp. + Trifolium repens + F. dolichophylla; and mixture without F. dolichophylla) across 64 plots. Vegetation was assessed eight months after seeding, and responses were analysed with ordination, PERMANOVA with restricted permutations, PERMDISP, and generalised linear models and mixed-effects models for diversity metrics. Community composition differed significantly among resting times and seed treatments, with resting time explaining the largest proportion of variance (R² = 0.353), followed by treatment (R² = 0.236), while the interaction was significant but smaller (R² = 0.102, p = 0.002). PERMDISP detected significant differences in multivariate dispersion for both Resting Time and Treatment, indicating that compositional differences may reflect both centroid shifts and heterogeneity among groups. Passive recovery and Festuca-only plots showed slower, more variable compositional change, whereas productive mixtures produced clearer, treatment-specific trajectories over time, suggesting possible divergence in community development patterns, rather than providing formal evidence of distinct alternative stable states. Establishment was consistently high for D. glomerata and Lolium spp., supporting rapid ground cover, which may be associated with short-term forage potential, while F. dolichophylla showed chronically low establishment consistent with limited germination performance. The invasive Pennisetum clandestinum was most pronounced under passive recovery and was reduced under seeded mixtures, suggesting a potential competitive suppression effect. Overall, early seeding with productive mixtures appeared to influence community assembly trajectories, while resting time remained the dominant driver of compositional variation, suggesting potential implications for restoration management in maca-degraded landscapes, although outcomes related to sustainable grazing systems were not directly evaluated. Full article

This study investigates three-dimensional magnetohydrodynamic convection in a cubic cavity with a symmetrical ellipsoidal obstacle in two different scenarios, under the combined effect of internal heat source and magnetic field strength. The significance of this research is based on understanding the interlinking of geometric orientation, buoyancy, and magnetic damping on the dynamics of the flow and thermal transfer phenomena. The approach taken is based on finite element simulations using COMSOL Multiphysics (version 6.3), coupled with a surrogate model of XGBoost to predict the Nusselt numbers for each of the configurations. The results show that the increase of the heat source parameter promotes the circulation driven by buoyancy and heat transport, while the increase of the Hartmann number suppresses fluid motion by the Lorentz force, leading to the reduction of heat transport. The orientation of the symmetrical ellipsoid has a major influence on the asymmetry of the flow and the properties of mixing. The extraordinary agreement between the numerical results and the predicted results is a validation of the accuracy of the proposed analytical framework. These insights have important implications for practical applications in energy systems, electronic cooling, and magnetically controlled heat processes. Full article

In this paper, we provide new insight into the Quaternary tectonics of the Floridia Graben (southeastern Sicily) and develop 3D geologic and ground-flow models of its subsurface. The Floridia Graben is a structural depression bounded by NW–SE trending normal faults and represents the main water reservoir that supplies the city of Siracusa (southeastern Sicily) and its countryside. The knowledge of the subsurface geology and neo-tectonic evolution of the Floridia Graben, as well as the spatial distribution of groundwater volumes is crucial for the management and protection of water resources. Within the government project of the new Italian geological cartography (ISPRA-CARG, Sheet N. 646 Siracusa), field and well data (both publicly available and newly acquired) have been collected and reinterpreted. NW–SE and NE–SW buried tectonic–structural features, inferred in the sub-surface of the graben, are consistent with the orientations of Quaternary faults diffusely observed inside and outside the investigated area. The Quaternary tectonic activity of bounding and buried faults has had a strong influence on the control of the morpho-structural pattern and, consequently, the groundwater flow of the Floridia Graben. The study allowed for the redefinition of the timing of these structures as well as their tectonic–structural control on the graben’s architecture and related water flow. The study represents a valuable tool for the better prediction of the spatial distribution of geologic and hydrogeologic volumes, thus enhancing the efficiency in the management and protection of natural resources. Full article

Thyroxine (T4) is a key hormone regulating metabolic, cardiovascular, and neurodevelopmental processes, yet its clinical quantification still relies on centralized immunoassays that limit rapid or point-of-care monitoring. Here, we present a label-free biosensing platform based on silicon nanowire field-effect transistors (SiNW-FETs) functionalized with a T4-selective DNA aptamer via a 3-Triethoxysilyl propylsuccinic Anhydride (TESPSA)-mediated silanization approach, enabling a streamlined two-step modification for oriented immobilization. The biosensor achieves robust real-time detection of T4 across the physiological concentration range (5–30 pM), with a limit of detection of ~5 pM and a strong linear correlation between drain current and analyte concentration (R² = 0.9931). Specificity is confirmed using non-functionalized devices and estradiol as a non-target control. All measurements were performed in undiluted phosphate-buffered saline, representing a physiologically relevant ionic environment and demonstrating stable sensor performance under realistic buffer conditions. The dose–response behavior follows a Hill model, allowing extraction of binding parameters and confirming that the electrical signal originates from specific aptamer–target interactions. These results demonstrate that aptamer-functionalized SiNW-FETs provide a highly sensitive, selective, and miniaturizable platform for quantitative thyroid hormone monitoring, with strong potential for future point-of-care applications. Full article

Daylighting in shopping-mall atriums affects both perceived visual quality and the availability of daylight for reducing electric-light use under daylight-responsive control. However, early-stage atrium design still lacks a reproducible workflow that connects field-based user-response evidence with parametric daylight simulation in retail settings. This study develops a weighted-sum design-search workflow for shopping-mall atrium morphology by combining a luminance-based visual satisfaction proxy with spatial daylight autonomy (sDA_300/50%) as an annual daylight-sufficiency indicator. Morphological parameter ranges were derived from a survey of 150 atriums in 26 shopping malls in China, and three prevalent atrium types were retained for simulation-based testing. ClimateStudio/Radiance simulations were used to calculate scene mean luminance and sDA_300/50%, and particle swarm optimization was used as a practical search algorithm under a fixed baseline weighting scenario. The reported high-scoring solutions reached sDA saturation, indicating that the final score differences were mainly governed by the luminance-based satisfaction term within the high-daylight-sufficiency region. This study contributes a retail-oriented, reproducible design-search workflow for early-stage atrium morphology decisions, while the results should be interpreted as scenario-based preferred solutions rather than statistically confirmed global optima or a complete visual-risk/energy-performance assessment. Full article

Cooperative motion control is a fundamental requirement for unmanned underwater vehicle (UUV) swarms operating in complex marine environments. Conventional swarm motion-control algorithms may suffer from limited convergence efficiency and redundant obstacle-avoidance maneuvers when the swarm is required to move toward multiple task-related regions. To address these issues, this study proposes a Vicsek-based distributed motion-control framework with static summoning points and threat-selective obstacle avoidance. First, static summoning points are introduced as predefined task-attraction locations, and a movement-cost-based assignment rule is used to divide the initially mixed swarm into task-oriented subclusters. Under a limited field-of-view constraint, a summoning factor is incorporated into the heading-update rule to balance local neighbor alignment and directional guidance toward the assigned summoning point. Then, an obstacle-avoidance strategy is developed by considering both the relative position of obstacles and the velocity direction of individuals. The detected obstacles are classified as current obstacles or potentially threatening obstacles, and avoidance maneuvers are triggered only when a current obstacle lies within the prescribed safety distance. Simulation results demonstrate that the proposed VSSPAO framework can improve convergence consistency, reduce convergence time, and decrease redundant obstacle-avoidance routes compared with the reference algorithms. The proposed method provides an interpretable and computationally simple distributed coordination mechanism for UUV swarm segmentation, task-oriented aggregation, and obstacle avoidance. Full article