Search Results (891)

In complex low-altitude environments, unmanned aerial vehicles (UAVs) require reliable positioning, yet Global Navigation Satellite System (GNSS) signals are vulnerable to occlusion and interference. Pseudolite-augmented cooperative localization, which combines ground base-station signals with inter-UAV relative observations, can complement GNSS in such environments. However, two practical issues remain in real-world deployment: UAV-to-base-station (U-B) and UAV-to-UAV (U-U) observations have markedly different error statistics that a unified noise adjustment cannot handle, and the conservative covariance estimates produced by Covariance Intersection (CI) fusion bias the innovation-based adaptive noise estimation in distributed architectures. To address these issues, this paper proposes a Distributed Group Covariance Compensation Adaptive Kalman Filter (DGCC-AKF) for collaborative enhancement of UAV regional localization. DGCC-AKF establishes a group adaptive mechanism that independently adjusts the noise covariance matrices of U-B and U-U observations, enabling observation-type-level adaptive weighting that suppresses anomalous U-B or U-U measurements at the group level. In addition, a bounded covariance compensation factor is incorporated to alleviate the CI-induced conservatism in the adaptive noise estimation. The proposed method is evaluated on a 2800 km² semi-physical testbed based on the Ground-based High-precision Local Positioning System (GH-LPS) pseudolite network using measured U-B observations and high-dynamic (>300 km/h) flight trajectories collected from a fixed-wing platform across three independent flight sessions. Results demonstrate that under observation fault periods, the proposed method improves 3D positioning accuracy by up to about 75% over single-UAV extended Kalman filter (EKF). Compared with two advanced algorithms in this field, variational Bayesian adaptive Kalman filter (VBAKF) and maximum correntropy criterion Kalman filter (MCC-EKF), it is the only scheme that remains accurate and stable across all UAVs and fault types. The framework provides a practical step toward field deployment for resilient multi-UAV cooperative navigation in pseudolite-augmented GNSS-denied regions. Full article

Biological biogas upgrading using microalgae offers a sustainable route for simultaneous CO₂ removal and biomass production. This study sequentially evaluated liquid-to-gas ratios, L/G, of 0.6–4.0, photoperiods of 0:24–16:8 h, and light intensities of 150–400 µmol m⁻² s⁻¹ in a semi-continuous photobioreactor–absorption column (PBR-AC) with Chlorella vulgaris under moderate alkalinity conditions of 1053–1350 mg L⁻¹ CaCO₃. The system operated at D = 0.1 d⁻¹, a gas flow of 0.05 L min⁻¹, and GRT of 1.30 h. Increasing L/G from 0.6 to 4.0 improved CO₂-RE from 67.9% to 81.6% and CH₄ from 77.0% to 82.9%, showing that intensified recirculation partly compensated for the moderate carbonate-buffering capacity. Among illuminated photoperiods, 16:8 h performed best, reaching 81.4% CO₂-RE and 81.7% CH₄. At L/G = 4.0 and 16:8 h, increasing photosynthetic photon flux density (PPFD) from 200 to 300 µmol m⁻²·s⁻¹ further improved CO₂-RE from 81.4% to 82.86%, CH₄ from 81.7% to 84.4%, and biomass productivity from 0.230 to 0.250 g L⁻¹ d⁻¹. The dark control achieved 57.06% CO₂-RE, indicating substantial physicochemical CO₂ absorption, while illumination added up to 24.35 percentage points. Overall, the system showed strong upgrading potential under moderate alkalinity, although O₂ contamination, which was 1.5–2.5%, remains a key limitation. Full article

This paper evaluates a dense, total-variation-based optical flow method for retrieving wildfire smoke plume motion vectors from geostationary, deep-space, and airborne remote sensing imagery. Using multiple major fire events, we assess the robustness of the approach across a range of spatial resolutions and time intervals. The test cases include Geostationary Operational Environmental Satellite (GOES) observations of the 2025 Los Angeles Fires and the 2024 Park Fire, imagery from NASA’s Enhanced MODIS Airborne Simulator (eMAS) for the 2019 Sheridan and Williams Flats Fires, and a complementary Park Fire image pair from the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR). Optical flow is computed directly on radiance fields, and smoke plumes are isolated using smoke masks derived from the Segmentation, Instance Tracking, and data Fusion Using multi-SEnsor imagery (SIT-FUSE) framework where available. Performance is evaluated by comparing the root mean square error (RMSE) between original image pairs and between the first image and the second image after warping with the retrieved motion field. RMSE is computed both globally and over smoke-only regions. Across GOES and eMAS cases, optical flow systematically reduces RMSE, often by more than a factor of two within smoke regions, indicating substantially improved frame-to-frame alignment of plume structures after motion correction. The DSCOVR/EPIC case, despite its coarser spatial resolution and longer temporal separation, also shows a marked reduction in global RMSE, demonstrating that the method remains informative under a broader range of observational conditions. For a selected subset of 10 consecutive GOES Park Fire pairs, we additionally compare the retrieved smoke motion vectors with collocated winds from the High-Resolution Rapid Refresh (HRRR) model and find the closest agreement in a broad lower-tropospheric layer centered near 875 hPa. These results show that dense optical flow can capture fine-scale plume evolution in high-temporal-resolution datasets while also providing useful motion estimates in coarser, global-view imagery. RMSE reduction is interpreted here as evidence of improved motion-compensated alignment, while the HRRR comparison provides initial physical context rather than independent validation. The resulting smoke motion vector fields provide a foundation for future comparison with model winds and for applications in plume analysis, fire hazard monitoring, and air quality studies. Full article

The aim of this study was to determine the efficiency of timber harvesting using Logset harvesters with hybrid and standard drives. The research was conducted in stands where thinning and final felling had been performed. Operating time and fuel consumption were determined in terms of productive machine hours (PMH). Data from the harvester’s operating system was used. Standard fixed and unit costs were included in the cost calculations. The hybrid harvester achieved better productivity, approximately 17% higher than the conventional machine (23.64 m³·h⁻¹ and 19.59 m³·h⁻¹, respectively). Differences in productivity between the machines were observed in both selective cutting and clear-cut areas. Average fuel consumption was 17.15 L·h⁻¹ (0.98 L·m⁻³) for the standard harvester and 20.33 L·h⁻¹ (1.44 L·m⁻³) for the hybrid-powered machine. Similar unit costs were recorded in clear-cut stands—on average from 4.2 EUR·m⁻³ for an 8 h shift to 2.90 EUR·m⁻³ for a 16 h shift. The average unit cost of timber harvesting with the hybrid harvester was approximately 20% lower compared to the standard machine (approx. 0.80 EUR·m⁻³). Despite the higher operating costs of the hybrid harvester, its use may be economically justified in situations where high productivity compensates for higher energy and investment costs. Full article

This study investigates the influence of isomorphous substitution of Aluminum by V, Zr, La, and Ni in Beta zeolite frameworks used as supports for Ni-based dry reforming of methane catalysts. The research focuses on how the nature of the incorporated metal affects catalytic activity and long-term stability. Catalysts were synthesized using both co-impregnation and sequential impregnation strategies. Physicochemical characterization—including gas adsorption, X-ray diffraction, transmission electron microscopy, and H₂ temperature-programmed reduction—revealed distinct structural roles for each metal. Results indicate that V primarily occupies T-vacancy sites within the dealuminated Beta framework, whereas Ni resides as charge-compensating extra-framework species or highly dispersed NiO clusters. Zr and La tend to form highly dispersed oxide species or occupy enlarged silanol nests. Notably, the addition of La₂O₃ was found to significantly enhance the long-term stability of the catalysts during the dry reforming of methane process. V-modified catalysts exhibited the highest activity but suffered from low stability; conversely, Zr incorporation offered the best overall performance, balancing high activity with enhanced stability, achieving 85% CO₂ and 75% CH₄ conversion, with no detectable carbon deposition after 98 h on stream. Full article

The electromechanical transmission (EMT) systems of hybrid special vehicles are highly susceptible to severe transient torsional resonance under frequent start-stop operating conditions. Traditional entire-frequency domain H_∞ active vibration reduction strategies are often limited by insufficient gain, failing to achieve ultimate suppression within the core resonance frequency band. To address this issue, this paper proposes a finite-frequency H_∞ active torsional vibration suppression strategy based on a motor dual-loop control architecture. This strategy achieves a profound physical decoupling between torsional vibration suppression and steady-state driving tasks. Furthermore, by introducing the Generalized Kalman–Yakubovich–Popov (GKYP) lemma and Linear Matrix Inequalities (LMIs) into the secondary loop, the control degrees of freedom are precisely concentrated on the 8–30 Hz frequency band, where the transient resonance energy is highly localized. This thoroughly eliminates the conservatism inherent in entire-frequency designs. To mitigate the instability risks caused by unmeasurable states and actuator response lags in practical engineering applications, a robust controller integrating input time-delay compensation and dynamic output feedback is subsequently constructed. Numerical case studies and hardware-in-the-loop (HIL) test results based on a specific EMT configuration demonstrate that the proposed strategy effectively overcomes the instability induced by system delays. It achieves an outstanding resonance peak attenuation of up to 93% and strictly constrains output shaft torque fluctuations within a safe threshold of 50 N·m. Ultimately, this study provides an efficient and robust closed-loop engineering solution for the transient vibration management of high-power electromechanical transmission systems and the enhancement of overall vehicle NVH performance. Full article

Resource-constrained edge processors deployed on unmanned aerial vehicles and wearable platforms require compact, drift-robust gas classification models for a range of environmental and security monitoring applications, including CBRN-motivated scenarios. Existing approaches rely on server-grade architectures incompatible with edge-board-scale deployment, or on classifiers that chemically degrade severely under long-term sensor drift. Each UCI gas class was mapped to a CBRN behavioral category based on physicochemical analogy (molecular functional group, vapor pressure, and metal-oxide semiconductor (MOS) cross-sensitivity pattern), following established precedent. Analyzed were Ammonia (NH₃), Acetaldehyde (CH₃CHO), Acetone ((CH₃)₂CO), Ethylene (C₂H₄), Ethanol (C₂H₅OH), Toluene (C₆H₅CH₃). We propose herein an end-to-end pipeline integrating a novel 1-D convolutional neural network with depth-wise separable convolutions (LiteSensor-Net), INT8 post-training quantization, structured magnitude pruning, and a knowledge-distillation domain-adaptation module (KD–DM) for sensor drift compensation. Using the UCI Gas Sensor Array Drift Dataset (13,910 measurements; 16 metal-oxide sensors; six analyte gases; a 36-month work span). LiteSensor-Net achieved accuracy = 92.63 ± 2.02%, macro-F1 = 0.898, model size = 5.99 kB INT8 pruned, inference latency = 6.3 ms, RAM footprint = 31.7 kB, and energy per inference = 0.04 mJ (all metrics on Raspberry Pi 4B, ARM Cortex-A72). Under chronological forward-chaining evaluation, KD–DM–20 achieved 47.91 ± 18.79% mean accuracy over Batches 2–10, representing a +9.25 pp improvement over uncompensated NC (38.66%). A six-metric benchmark framework—accuracy, macro-F1, model size, inference latency, RAM footprint, and energy per inference—is introduced to standardize edge-AI gas classifier evaluation. The proposed pipeline provides an open-source, deployable foundation for edge-class gas classification systems, with CBRN detection as a motivating application. Full operational validation on certified chemical simulants remains as future work. Full article

Large-scale electric vehicle (EV) integration provides considerable flexibility for integrated energy systems (IESs), but stronger incentives do not always yield proportional demand response benefits under physical operating limits. This paper proposes a techno-economic dispatch optimization framework for an IES incorporating a Kalina Cycle (KC), power-to-gas (P2G) technology, and hydrogen storage. A 24 h mixed-integer linear programming (MILP) model is developed to evaluate the interaction among the incentive intensity, multi-energy load response, and operating cost under different integrated demand response (IDR) scenarios. The results show a saturation-like response pattern: as the incentive intensity increases, the total operating cost rises monotonically, while the total demand response does not increase proportionally. In the studied case, the low-incentive strategy achieves the best economic performance because the additional compensation paid under high-incentive scenarios outweighs the marginal operating-cost savings. Load response analysis further indicates that EV-dominated electrical loads provide the main flexibility, whereas thermal and gas loads are strongly constrained by physical balance and equipment limits. The ablation results show that the saturation trajectory is affected by physical flexibility resources, especially the hydrogen subsystem. These findings suggest that incentive design should be coordinated with system physical constraints to avoid over-incentivization. Full article

Self-assembling β-sheet-forming peptides are attractive building blocks for drug delivery nanomaterials. However, their strong intermolecular interactions often lead to high structural stability, which can hinder intracellular dissociation and limit cargo availability. Here, we propose a charge-compensated ampholytic design strategy for β-sheet peptide nanofibers that undergo destabilization and disassembly under reducing conditions. Six ampholytic peptides comprising an anionic main-chain peptide (β-sheet-forming motif, model antigenic cargo, and oligoglutamic acid segment) and a disulfide-linked cationic segment were designed and synthesized to vary the lengths and charges of the anionic and cationic segments, as well as the cationic insertion position. Four peptides formed nanofibers in 4×phosphate buffered saline (4×PBS) and the resulting nanofibers remained stable after dilution to 1×PBS, retaining β-sheet-rich secondary structures and fibrillar morphologies for at least 24 h. Under reducing conditions, the four preformed nanofibers exhibited distinct behaviors, including reduction-insensitive persistence, disassembly, and transient destabilization followed by re-stabilization, depending on peptide charge design. Redox-triggered disassembly was favored when the main-chain peptide had sufficient anionic character and the cationic segment was of moderate length and charge. This study therefore provides a molecular design strategy for controlling the destabilization of β-sheet peptide nanofibers under reducing conditions through disulfide-cleavage-induced disruption of charge compensation. Full article

Mass concrete is prone to cracking induced by high early-age temperature rise and significant shrinkage stress, which severely compromises structural durability and safety. Aiming to achieve “low temperature rise and high crack resistance,” this study systematically optimized raw material selection and conducted experimental investigations on mix proportioning and the influence of critical parameters. The proposed design was subsequently validated through a field application. The results indicate that a fly ash content of 35% effectively improves workability, mitigates early-age shrinkage and reduces the heat of hydration. The incorporation of a high-performance expansive agent not only retards the hydration process and delays the temperature peak but also generates compensatory expansion at early ages, significantly reducing shrinkage during the cooling phase. Additionally, a polypropylene fiber dosage of 1.2 kg/m³ was found to optimally balance workability with crack resistance enhancement, resulting in less than 5% reduction in early-age strength. Field applications demonstrate that the concrete with the optimized mix proportion exhibits excellent workability and rapid early strength development. Specifically, the expansive agent delayed the temperature peak to 78 h and generated significant chemical expansion, effectively compensating for shrinkage caused by cooling. The findings provide critical insights into the construction-stage behavior of mass concrete, enabling improved safety control through better prediction and mitigation of early-age thermal and shrinkage effects. This study offers theoretical and technical support for the design of mass concrete characterized by low temperature rise and high crack resistance. Full article

This paper investigates harmonic compensation for an LCL-filtered cascaded H-bridge (CHB) STATCOM operating in medium-voltage distribution networks under grid-frequency deviations and nonlinear loads. A hybrid current control strategy is proposed by combining a deadbeat (DB) inner-current loop with a Thiran all-pass filter-based frequency-adaptive repetitive controller (FARC). Weighted average inductor current (WAIC) feedback is adopted to reduce the third-order LCL filter to an equivalent first-order plant, thereby simplifying the current loop design while retaining the dominant low-frequency dynamics. The Thiran all-pass fractional delay filter is then embedded in the repetitive controller to realize a noninteger-period internal model at a fixed sampling frequency. This enables the controller to maintain harmonic compensation accuracy when the grid frequency deviates from its nominal value. A 10 kV LCL-filtered CHB STATCOM model is developed in MATLAB/Simulink, and the proposed method is compared with a conventional repetitive controller (CRC) under nominal frequency, frequency drift, nonlinear loading, harmonic load-switching conditions and grid impedance variation. Simulation results show that the proposed controller reduces the grid-current THD from 4.35% to 3.88% at 50 Hz, from 5.20% to 2.37% at 49.6 Hz, and from 6.51% to 3.56% at 50.4 Hz. In the tested frequency range of 49.5–50.5 Hz, the proposed method also maintains the power factor close to unity. These quantitative results demonstrate improved frequency robustness, harmonic suppression, and current-tracking performance compared with the CRC scheme, indicating that the proposed method can enhance STATCOM-based power quality compensation and support more reliable and efficient operation of medium-voltage distribution networks. Full article

Wheeled inverted-pendulum robots with movable upper structures and variable payloads exhibit configuration-dependent equilibrium drift and payload-dependent dynamic variation, which complicate balancing control. This paper proposes a gain-scheduled controller–observer framework for payload-adaptive balancing of such a robot. First, the multi-body system is reduced to a control-oriented equivalent inverted-pendulum model through center-of-mass lumping, from which a parameter-varying linearized model is established. On this basis, an H∞ state-feedback controller with input constraints is synthesized in a linear matrix inequality (LMI) framework, and an augmented-state observer is designed to estimate the residual equilibrium offset induced by payload variation. To improve robustness over the operating range, the frozen-point design is extended to a sampled-model multi-model synthesis framework, and gain scheduling is implemented with respect to the measurable arm angle. Nonlinear Simscape simulations show that the proposed method can recover balance at representative fixed operating points, compensate effectively for load-induced equilibrium drifts, and preserve stable balancing performance under slow arm-angle variation. Quantitative comparisons with an LQR baseline further support the effectiveness of the proposed framework for payload-adaptive balancing control. Full article

Wafer-level testing of Photonic Integrated Circuits (PICs) represents a critical throughput bottleneck in silicon photonics manufacturing, particularly as co-packaged optics demand testing of thousands of optical I/O per wafer. This work introduces optimized alignment algorithms for the Technoprobe Eclipse Dynamic probe card system, which integrates electrical probes and a piezoelectrically actuated fiber array unit within a single probe head, eliminating external positioning equipment. We systematically evaluate seven alignment algorithms: Reference Coarse Scan, Reference Coarse+Fine Scan, Cross Scan, Local and Global Bayesian Optimization, Variable and Fixed Gradient Ascent. The evaluation is made across 72 simulated test cases derived from eight experimental datasets through systematic spatial windowing, combined with experimental validation. Performance is assessed under four operating regimes—high-speed (HS) and low-speed (LS) operation, each with or without hysteresis compensation (H/NH). Experimental validation across eight die positions confirms 100% success rate for both Local Bayesian (98.24% accuracy in 99.87 arbitrary units (a.u.)) and Fixed Gradient (99.18% accuracy in 154.01 a.u.) baseline algorithms. Comprehensive simulation results with improved algorithms across all four scenarios reveal distinct performance characteristics. Fixed Gradient achieves the highest reliability (95.8%) with 99.4% average accuracy across all operating conditions. Variable Gradient provides the fastest alignment (1.18 a.u. in HS-NH) with 90.3% reliability. Local Bayesian demonstrates 94.4% reliability with intermediate performance. Global Bayesian Optimization achieves the best sample efficiency (average 24 steps) but exhibits scenario-dependent reliability ranging from 88.9% (HS-H, LS-H) to 93.1% (LS-NH). For the ideal production scenario, high speed with effective hysteresis compensation (HS-NH), Fixed Gradient emerges as the optimal choice, delivering 95.8% reliability with 1.44 a.u. alignment time, resulting in the best success rate while being nearly as fast as the fastest method. Variable Gradient achieves the absolute fastest alignment (1.18 a.u.) but with 5.5% lower reliability (90.3%), making it suitable only for applications tolerating higher failure rates. Under realistic production conditions with uncompensated hysteresis (HS-H), Fixed Gradient maintains its advantage (95.8% reliability, 3.32 a.u.), while Global Bayesian degrades significantly (88.9% reliability, 4.29 a.u.). Statistical analysis using data profiles validates these methods for high-volume PIC manufacturing, with the Eclipse Dynamic system demonstrating per-die optical alignments in sub-second timescales using open-loop control hardware. Full article

In early-warning scenarios for thermal runaway in energy storage batteries, carbon monoxide (CO) may interfere with hydrogen detection and reduce the reliability of signal interpretation. To mitigate CO cross-interference under representative mixed-gas conditions and improve sensing stability, a fiber-optic microelectromechanical systems (MEMS) hydrogen sensor based on a Pd–Cu alloy-sensitive layer was developed. The sensor employs a single-cantilever structure and a reflective Fabry–Pérot (F–P) interferometer for optical readout. Comparative experiments were carried out using sensors coated with pure Pd and Pd–Cu-sensitive layers under pure H₂, CO background interference, and temperature-fluctuation conditions. The Pd–Cu sensor exhibited a good linear response over 0–500 ppm H₂, with a sensitivity of 0.0845 nm/ppm. Under a mixed atmosphere of 200 ppm H₂ and 500 ppm CO, the Pd–Cu sensor measured 198 ppm, whereas the pure Pd sensor measured 176 ppm, corresponding to relative errors of approximately 1% and 12%, respectively. In addition, the Pd–Cu sensor showed faster response/recovery behavior and better output stability after temperature compensation. These results indicate that, under the investigated conditions, the selected Pd–Cu-sensitive layer can effectively reduce CO-induced interference and improve the accuracy and stability of fiber-optic MEMS hydrogen sensing, supporting its feasibility for representative early-warning-related monitoring scenarios in energy storage batteries. Full article

Background: The majority of Class II malocclusions stem from mandibular deficiency, leading to chin retrusion. In growing patients, the ideal correction—aiming for a skeletal mandibular response—should avoid common pitfalls such as “Point B” dropping postero-inferiorly, excessive labial proclination of mandibular incisors, or the lingual tipping and extrusion of maxillary incisors. When planning mandibular advancement (MA) using clear aligners with integrated advancement features, biomechanical forces are not the only consideration; precise management of the lower incisor position is critical for success. Current literature highlights not a good control in digital planning software: these platforms are primarily dentoalveolar-based and lack integrated cephalometric analysis. Consequently, mandibular advancement is often defined by standard linear parameters (typically 2 mm per step), while incisor position is managed through virtual alignment without correlation to cephalometric landmarks like the Pogonion, NB line, or IMPA. The software cannot monitor real-time sagittal or vertical skeletal relationships, the software will elaborate the treatment planning after doctor’s prescription, the clinician must manually adjust incisor positioning based on external cephalometric analysis to prevent dental compensation or excessive proclination. Aim: This clinical case demonstrates a specific arch preparation protocol designed to optimize mandibular advancement in a growing patient with mandibular retrusion. Methods: A 12-year-old female presented with a skeletal and dental Class II malocclusion, characterized by increased overjet and a normal overbite. Treatment was conducted using Invisalign^® clear aligners (22 h/day wear, weekly changes). The treatment objectives were: transverse: Correct upper dentoalveolar contraction and coordinate arch form while restoring midline alignment; sagittal: establish Class I molar and canine relationships by correcting the overjet and reducing the labial inclination of the lower incisors; vertical: level the curve of Spee. A key clinical condition of our protocol was the pre-advancement phase: the lower arch was reshaped by reducing the buccolingual inclination (retroclination) and intruding the lower incisors. This was specifically intended to increase the available overjet space, creating the necessary room for subsequent mandibular advancement. Results Treatment was completed in 24 months with high patient compliance. Objectives were successfully met, including the correction of skeletal and dental discrepancies, the establishment of harmonious arch forms, and precise overjet reduction through enhanced control of the mandibular incisors. Conclusions: This case report outlines an optimized clinical strategy for Class II correction. Cephalometric Integration: Perform an initial analysis outside the digital planning software to define the ideal IMPA and NB angles. Anatomic Verification: Utilize radiographic overlays to ensure tooth movement remains within alveolar bone limits. Pre-MA Optimization: Prioritize a “pre-advancement” phase to maximize the sagittal inter-arch space (overjet). A larger overjet allows for a more significant orthopedic effect from the MA features. Stepwise Advancement: Implement mandibular advancement in increments (≥2 mm) with periodic clinical reassessment to facilitate the adaptation of the muscular sling and functional occlusion. Full article