Search Results (773)

High-resolution range profile (HRRP) reconstruction is essential for extracting range-direction scattering characteristics in wideband radar remote sensing, particularly in synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) imaging. Coded interrupted sampling (CIS) can improve radar low probability of intercept (LPI) performance by controlling signal transmission with a binary sequence. However, the reduced number of valid echo samples may degrade HRRP reconstruction, especially under low-duty-ratio and low signal-to-noise ratio (SNR) conditions. Conventional orthogonal matching pursuit (OMP) processes each frame independently and ignores the inter-frame continuity of scattering-center positions, which may lead to false selections and missed detections. To address this problem, this paper proposes a candidate-interval-assisted orthogonal matching pursuit (CI-OMP) algorithm based on multi-frame sequential priors. Stable scattering-center positions are extracted from historical reconstruction results and expanded into candidate intervals to guide atom matching in the current frame. Simulation results show that CI-OMP outperforms standard OMP in terms of normalized mean squared error (NMSE), tolerant support recovery rate (Tol-SRR), and peak-to-sidelobe ratio (PSLR). At a duty ratio of 0.20, CI-OMP reduces the NMSE by 1.71 dB and improves the PSLR by 7.56 dB compared with OMP. In addition, the candidate-interval strategy reduces the atom-search range by approximately 54–75% under different duty ratios and by approximately 50–83% under different SNRs, demonstrating improved search efficiency. These results demonstrate that CI-OMP improves the accuracy, robustness, and search efficiency of HRRP reconstruction for CIS radar echoes, particularly under low-duty-ratio and low-to-medium-SNR conditions. Full article

Background and Objectives: Facial nerve palsy (FNP) remains a clinically relevant complication after vestibular schwannoma (VS) resection. Recovery trajectories vary according to the severity of neural injury and early postoperative facial function. This study aimed to characterize the temporal pattern of facial nerve recovery during the first postoperative year and to explore factors associated with favorable long-term function. Materials and Methods: We retrospectively analyzed 51 adult patients who developed FNP after VS surgery between 2020 and 2023. Facial nerve function was assessed using the House–Brackmann (HB) grading system and the Sunnybrook Facial Grading System (SBFGS) at discharge and at 1, 3, 6, and 12 months postoperatively. Longitudinal changes were analyzed using non-parametric repeated-measures methods with effect-size estimation. Favorable 12-month facial nerve function was defined as HB grade I–II. Given the limited number of unfavorable outcomes, associations with 12-month recovery were explored using parsimonious Firth-penalized logistic regression models. Results: At discharge, 45.1% of patients had HB II, 29.4% HB III–IV, and 25.5% HB V–VI. Facial function improved significantly during follow-up. Median SBFGS total score increased from 58.0 at discharge to 99.0 at 12 months (Friedman χ² = 118.78, df = 4, p < 0.001; Kendall’s W = 0.58), while HB grade also improved significantly (χ² = 107.48, df = 4, p < 0.001; W = 0.53). At 12 months, 37/51 patients (72.5%) achieved HB I–II and none remained in the HB V–VI category. Synkinesis, defined as an SBFGS synkinesis subscore > 0, was observed in 10/51 patients (19.6%) at 6 months and 19/51 (37.3%) at 12 months. HB grade and SBFGS score at discharge were strongly inversely correlated (Spearman ρ = −0.943, p < 0.001) and were therefore evaluated in separate models. After adjustment for age and tumor size, each one-grade increase in discharge HB was associated with lower odds of favorable 12-month function (OR 0.30, 95% CI 0.11–0.58; p < 0.001), whereas each 10-point increase in discharge SBFGS was associated with higher odds of favorable function (OR 1.90, 95% CI 1.32–3.53; p < 0.001). Conclusions: Facial nerve function showed substantial longitudinal improvement during the first year after VS surgery. Early postoperative facial function was independently associated with 12-month outcome in exploratory penalized regression analyses. Recovery may continue over several months, supporting prolonged functional surveillance, while the independent contribution of rehabilitation and the effect of nerve grafting require evaluation in larger prospective cohorts. Full article

Point-of-interest (POI) data are widely used as urban big data to sense the functional organization of urban land and associated socioeconomic activities. Yet, POI-based studies often treat these records as temporally stable, even though different POI categories vary in turnover and responses to external shocks, affecting the comparability of urban sensing over time. Using POI datasets for Changzhou, China, from 2016, 2019, 2022, and 2025, this study examines category-specific changes before, during, and after the COVID-19 disruption. The results identify three patterns: government-driven POIs (government and residential) show high stability and retention; government–market hybrid POIs (financial and educational) exhibit moderate stability; and market-driven POIs (catering and shopping) have low stability. Across periods, change intensity is inversely related to stability. During the pandemic, turnover increased across all categories, retention declined markedly, and most replacements occurred within the same category, indicating functional continuity despite entity-level change. Although the overall spatial framework of urban functions remained broadly stable, new hotspots emerged during the pandemic and some persisted into the recovery period. These findings demonstrate that POI-based urban sensing is temporally contingent and that category-specific dynamics should be considered when interpreting urban land-use functions and supporting land-use planning under disruptive events. Full article

Low Earth orbit (LEO) satellite downlinks broadcast over wide ground footprints, exposing Earth-observation and remote-sensing sensor data to passive eavesdropping. Affine frequency division multiplexing (AFDM) is a candidate waveform for the doubly dispersive LEO channel and a natural integrated sensing and communication (ISAC) waveform whose delay–Doppler structure supports target parameter estimation; yet existing secure-AFDM schemes act only in the discrete affine Fourier transform (DAFT) parameter domain, leaving the transmitted waveform structurally recognizable. To address this gap, this paper applies time-domain waveform obfuscation to AFDM as physical layer encryption. Using a secret key, the transmitter permutes the inverse-DAFT samples and applies a phase rotation before chirp-periodic-prefix generation; the mask is unitary, so the peak-to-average power ratio is preserved exactly, and the key-holding receiver retains AFDM’s full delay–Doppler sensing capability, while a no-key receiver obtains a dense composite response that destroys target localization (sensing concentration drops from 0 dB to −16.6 dB). Secret pilot phases enable channel estimation at the legitimate receiver while blocking a naive composite-channel attack. Simulations at $N=64$ and 128 show that a wrong-key eavesdropper achieves uncoded BER within $0.01$ of $0.5$ across 0–20 dB and that blind Viterbi–Viterbi phase recovery is no more effective under QPSK (BER $0.46$–$0.48$), while the legitimate SNR penalty stays below $0.5$ dB. The mask also suppresses AFDM’s internal structure to the AWGN level under AFDM-aware processing. Time-domain obfuscation offers a complementary physical-layer security layer for confidential LEO remote-sensing data downlink and ISAC waveforms. Full article

Micromachined ultrasonic transducers (MUTs) represent a notable advance in miniaturized sensing, enabling compact, low-power, and complementary metal-oxide-semiconductor (CMOS)-integrated platforms that extend ultrasonic capabilities into wearable, implantable, and edge-computing domains. The integration of artificial intelligence (AI) has introduced new approaches for signal interpretation, adaptive control, and data-driven optimization, enhancing performance in specific areas such as compressed sensing, neural beamforming, and learned image enhancement that complement conventional signal processing. Meanwhile, sensor fusion strategies that combine ultrasonic data with complementary modalities have improved robustness, contextual awareness, and diagnostic accuracy across applications ranging from industrial monitoring to clinical diagnostics. This review provides a comprehensive analysis of this active research area, systematically covering transducer hardware platforms, design methodologies, and intelligent signal processing frameworks. While traditional bulk piezoelectric transducers remain the benchmark for high-power applications, capacitive and piezoelectric micromachined variants offer superior acoustic impedance matching and monolithic CMOS compatibility essential for portable systems. We examine the evolution from deterministic analytical and numerical modeling toward AI-powered inverse design, which enables the discovery of non-intuitive, high-performance geometries beyond human intuition. Furthermore, the integration of machine learning (ML) for signal recovery, image enhancement, and multi-modal sensor fusion is discussed as a pathway to compensate for hardware constraints such as limited aperture, sparse sampling, and low signal-to-noise ratio (SNR), while pointing out that AI technology cannot overcome fundamental physical limits including acoustic attenuation, thermal noise floors, and transduction efficiency boundaries. By synthesizing recent advancements, this review demonstrates how the convergence of classical acoustic physics and data-driven intelligence is guiding the development of of intelligent ultrasonic systems. Full article

Edible Natural Deep Eutectic Solvents (NADES) offer a route to ready-to-use extracts without solvent removal. This study examined how rational formulation design influences physicochemical properties, extraction performance, energy efficiency, thermal behavior, and cytocompatibility during bioactive recovery from Nigella sativa seeds. Twelve formulations spanning malic acid–polyol, citric acid–polyol, binary polyol, and ternary acid–polyol families were evaluated under standardized ultrasound-assisted conditions and compared with ethanolic ultrasound-assisted extraction, Soxhlet extraction, and cold-pressed oils. Selected NADES formulations outperformed the conventional systems. E1 (malic acid:glycerol:water) achieved the highest total phenolic content and lowest specific energy consumption (40.00 kJ mg⁻¹ GAE), below the Soxhlet benchmark (55.17 kJ mg⁻¹ GAE), whereas E9 (glycerol:xylitol:water) exhibited the greatest ABTS activity. Neat-NADES apparent pH and viscosity were inversely associated with total phenolic content, while viscosity and density were inversely associated with ABTS activity. ATR-FTIR showed stable, solvent-dominated fingerprints over 15 days, whereas DSC better differentiated neat NADES from their extracts. Most systems remained cytocompatible at 10,000× dilution, while acid–polyol formulations reduced viability at 500×; partial neutralization of N5/E5 restored viability. NADES performance was formulation- and application-dependent, requiring joint optimization of composition, acidity, viscosity, energy efficiency, and biologically compatible concentration. Full article

Ultra-wideband (UWB) inter-node ranging provides relative-distance constraints for cooperative localization in GNSS-denied UAV swarms, but dense candidate networks can exceed the available ranging slots, communication bandwidth, computation, and energy. This paper proposes a Fisher-information-based cooperative sensor node pre-selection method under heterogeneous ranging noise. All mobile nodes remain in the localization state, while the selected nodes induce the active ranging-link set. Selected-node, induced-link, ranging-slot, and normalized general-resource budgets are represented separately. Using predicted geometry and estimated link-quality weights, a gauge-free normalized Fisher information matrix combines link geometry, link-quality-dependent weights, and topology-induced coupling. A trace-based generalized GDOP (G-GDOP) criterion is optimized by a two-stage greedy heuristic with recursive matrix updates. The experiments show that G-GDOP is a local observability and information-quality metric rather than a direct predictor of topology-level nonlinear recovery error. Within the same topology, normalized local RMSE increased from 0.698 [0.673, 0.752] in the Low G-GDOP group to 1.014 [0.999, 1.068] and 1.980 [1.806, 2.180] in the Medium and High groups. Increasing the selected-node budget from K = 6 to K = 20 reduced median RMSE from 0.550 to 0.148 m while increasing the median induced-link number from 109 to 214. Additional tests covered Gaussian and heterogeneous ranging noise, deterministic NLOS bias, online link-weight errors, and predicted-position uncertainty. Direct Inversion and Woodbury Updating were numerically equivalent within a predefined tolerance in all 24 size–regime combinations, and a Woodbury runtime advantage was supported in 20 conditions. The proposed framework therefore provides an interpretable resource-aware pre-selection module without implying an unconditional real-time guarantee. Full article

Background/Objectives: In glioma patients, acute neurologic deterioration may reflect nonconvulsive status epilepticus (NCSE), peri-ictal pseudoprogression, treatment-related change, or true progression. As these entities share imaging features, misdiagnosis can delay therapy. This review synthesizes evidence relevant to a proposed electroclinical-imaging framework for distinguishing seizure-related deterioration from treatment-related change and true progression. Methods: This narrative review synthesized English-language literature on tumor-related epilepsy, NCSE, peri-ictal imaging abnormalities, pseudoprogression, radiation necrosis, Response Assessment in Neuro-Oncology (RANO) criteria, and advanced imaging in adult diffuse glioma. Results: Seizure recurrence after glioma treatment may indicate tumor activity, but it may also reflect radiation injury, postoperative gliosis, edema, metabolic disturbance, medication effects, or transient peri-ictal change. NCSE is particularly important because it may present with aphasia, confusion, impaired consciousness, behavioral change, or deficits without convulsions, making electroencephalography central for unexplained deterioration. Seizure activity can also produce transient magnetic resonance imaging (MRI) or positron emission tomography (PET) abnormalities, including enhancement, fluid-attenuated inversion recovery (FLAIR) hyperintensity, diffusion restriction, and perfusion changes that mimic recurrence. Conclusions: This review proposes a structured electroclinical-imaging framework incorporating early EEG, seizure history, treatment timing, corticosteroid and antiseizure response, multimodal imaging, and longitudinal reassessment for prospective evaluation in treated glioma patients with new neurologic decline. Full article

High-mobility dual-functional radar–communication systems require a common waveform that combines delay–Doppler information organization, sensing resolution, and power-efficient transmission. We present a cyclically closed constant-envelope orthogonal time frequency space–continuous phase modulation–linear frequency modulation (OTFS–CPM–LFM) waveform and matched transceiver architecture. Hermitian delay–Doppler mapping and direct-current (DC) row nulling create a real, zero-sum drive with a reversible frame-level phase representation. The communication receiver combines a Tikhonov-regularized waveform inverse with reference-aided unwrapping and tail-biting phase regression, while the radar receiver reconstructs the data-dependent current-frame reference. Numerical results verify the structural waveform properties and characterize communication, radar, and computational tradeoffs. They also quantify degradation under controlled complex-gain channel-state-information mismatch and show that phase regression is less reliable at a low signal-to-noise ratio (SNR). The constant-envelope claim applies only to ideal discrete complex-baseband samples and does not include pulse shaping or radio-frequency hardware. The framework therefore provides a self-consistent waveform interface while exposing tradeoffs among payload, recovery reliability, sensing sidelobes, and implementation cost. Full article

This paper investigates inverse spectral problems for a class of discrete Sturm–Liouville operators with multiple transmission interfaces. The presence of several interfaces generates a coupled spectral structure in which the reconstruction of the operator coefficients is determined by a common generalized spectral function. A generalized spectral framework adapted to the multi-interface setting is introduced, and explicit reconstruction formulas for the associated tridiagonal coefficient matrix are derived. Using the corresponding Hankel moment determinants, it is shown that the interface coefficients are spectrally linked through the same moment sequence, producing a globally coupled reconstruction mechanism. In contrast to the single-interface case, the reconstruction cannot be decomposed into independent local procedures. A constructive recovery algorithm for the operator coefficients is obtained, and the role of the transmission parameters in the spectral representation is analyzed. An example illustrating the reconstruction process for multiple interfaces is also presented. Full article

Aerial radiation surveys produce sparse trajectories that must be reconstructed into contamination maps. Conventional aerial interpolators—inverse distance weighting (IDW) and ordinary kriging—treat observations as local ground samples, ignoring that each measurement integrates radiation over an extended footprint A(x, y) = (C * K)(x, y). The resulting double-blurring imposes a second smoothing on already-convolved values, causing systematic underprediction regardless of measurement density. We cast reconstruction as inverse deconvolution. A physics-aware encoder–decoder receives five channels (sparse measurements, IDW baseline, land–water scalar prior, measurement mask, water mask) and learns to invert K under a forward-consistency loss. The network is pretrained on synthetic data and deployed without fine-tuning. At a 50% random within-system holdout over the 2213-point Ukedo benchmark trajectory, 25 runs achieve a mean root-mean-square error (RMSE) of 705.4 ± 102.8 counts per second (CPS) versus 916.8 ± 34.2 (IDW) and 832.4 ± 31.3 (Kriging), with directional improvement over IDW in 25/25 runs. In a three-model ensemble diagnostic, among held-out points exceeding T = 6000 CPS (n = 64 at split seed 10, near the IDW ceiling), the U-Net recovers approximately 80% while IDW and kriging both fall to approximately 0%. The operational value lies in high-intensity hotspot recovery. These gains apply to dense-trajectory, within-coverage reconstruction; under large-gap extrapolation beyond the observed trajectory, the advantage over conventional interpolation is drastically reduced, and spatially independent validation remains an open challenge. Full article

Women with endometriosis experience chronic cyclic pelvic pain (CCPP) or chronic persistent pelvic pain (CPPP), both of which may be incapacitating even after treatment. Emotional dysregulation in endometriosis impedes patient recovery. This study evaluated the relationships among emotional state, pain perception, and inflammatory biomarkers (IL-1β, IL-6, and TNF-α) in women with endometriosis presenting with CCPP or CPPP. An exploratory, observational, descriptive, cross-sectional, comparative with repeated sampling study was conducted with 52 women diagnosed with endometriosis and experiencing either CPPP or CCPP. Participants completed a psychometric battery including the State-Trait Anxiety Inventory (STAI), Beck Depression Inventory (BDI-II), Goldberg General Health Questionnaire (GHQ-30), Hospital Anxiety and Depression Scale (HADS), and Mini-Mental State Examination (MMSE). Pain perception was assessed using the Wong–Baker Pain Rating Scale (FACES). Saliva samples were collected at baseline, during stressor and recovery phases, and concentrations of IL-1β, IL-6, and TNF-α were determined by ELISA. Fifty-two women with endometriosis were included (CPPP: n = 33; CCPP: n = 19). No significant between group differences were observed in emotional state (HADS: p = 0.682; BDI: p = 0.842), anxiety (STAI-State: p = 0.086; STAI-Trait: p = 0.615), general distress (GHQ-30: p = 0.730), or pain intensity (FACES: p = 0.705). The prevalence of depressive symptoms did not differ between groups (CPPP: 69.7% vs. CCPP: 73.7%; χ² = 0.093, p = 0.760). Salivary cytokine levels (IL-1β, IL-6, TNF-α) were comparable between groups across all measurement conditions. Spearman correlations revealed uncorrected significance between TNF-α and emotional distress: basal TNF-α correlated inversely with HADS (ρ = −0.292, p = 0.031) and BDI (ρ = −0.278, p = 0.041); TNF-α under stress correlated with HADS (ρ = −0.329, p = 0.014) and GHQ-30 (ρ = −0.271, p = 0.046); and TNF-α during recovery correlated with GHQ-30 (ρ = −0.363, p = 0.006). These findings indicate that CPPP and CCPP were not associated with statistically significant differences in emotional states or salivary cytokine profiles at the group level. Exploratory pos hoc analyses suggested that pain pattern may moderate the association between TNF-α and psychological burden, particularly in the CCPP subgroup; however, these findings require confirmation in larger studies with prespecified analyses. Exploratory analyses suggested patterns between salivary inflammation and psychological burden; however, these findings should be interpreted cautiously because of the small subgroup size, multiple comparisons, and lack of a matched healthy control group. Full article

This paper presents the mathematical modeling, numerical implementation, and experimental validation of a decoupling control algorithm for a five-port multiport modular active bridge (MMAB) converter in DC microgrid applications. Based on an analytically derived generalized state-space framework of the MMAB topology, a matrix-based method for suppressing non-linear mutual cross-couplings among individual ports is proposed. The study addresses parametric uncertainties within the system matrix caused by parasitic bus inductances; by formulating a linear system of equations solved via the numerical least-squares method, the equivalent parameter identification error was reduced from over 18% to a valid threshold. The decoupling performance and dynamic responsiveness of the closed-loop system were experimentally verified on a dual-core TMS320F28379D digital signal processor. The experimental results demonstrate that the proposed algorithm effectively isolates transient step-load perturbations, maintaining voltage stability on adjacent undisturbed ports within a strict deviation of less than $+0.51\%$ and achieving a recovery time below 5 ms. Furthermore, the real-time execution of the online Jacobian matrix inversion via the Newton–Raphson method confirms the computational feasibility and convergence of the iterative approach under tight sampling periods. The obtained results provide a robust, experimentally validated foundation for advanced algebraic and numerical control strategies in high-stability multiport power conversion systems. Full article

Monitoring physical performance during the pre-season may help coaches and practitioners interpret short-term changes in young soccer players, although group-level analyses may mask individual variability. This observational longitudinal study analyzed short-term changes, individual variability, and associations between baseline performance and change magnitude in 50 under-17 male outfield soccer players during a 47-day pre-season. Physical performance was assessed before and after the pre-season using the squat jump (SJ), countermovement jump (CMJ), 20 m linear sprint (Sprint-20m), 20 m change-of-direction test (COD-20m), and Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IRL1). Significant improvements were observed in SJ (+1.43 cm, p < 0.001), CMJ (+1.37 cm, p < 0.001), and COD-20m (+0.31 km·h⁻¹, p < 0.001), whereas no statistically significant changes were detected in Sprint-20m (−0.14 km·h⁻¹, p = 0.121) or Yo-Yo IRL1 (−26.20 m, p = 0.721). Individual changes were heterogeneous, with 68.0% improving in SJ and COD-20m, 64.0% in CMJ, 40.0% in Sprint-20m, and 54.0% in Yo-Yo IRL1. Exploratory inverse associations were observed between baseline performance and change scores for SJ (ρ = −0.35, p = 0.014), CMJ (ρ = −0.40, p = 0.004), and COD-20m (ρ = −0.30, p = 0.033), whereas no statistically significant associations were detected for Sprint-20m or Yo-Yo IRL1. These findings support integrating group-level changes, individual variability, and baseline-performance context when interpreting short-term physical performance monitoring in youth soccer. Full article

Two-objective optimization requires both reliable front approximation and explainable non-dominated extraction. This study develops a theoretical and computational method that maps sampled objective vectors to rasterized objective-space images and processes their Pareto structure through supervised neural approximation, a deterministic convolutional extractor, and exploratory reinforcement search. Network I reconstructs a high-density sampled occupancy image from sparse samples, whereas Network II approximates the sampled Pareto-front boundary. The principal algorithmic contribution is a fixed cross-correlation kernel derived from the two-objective dominance quadrant and coupled with a cell archive that preserves original vectors and resolves raster collisions through exact dominance checks. Under the stated coordinate convention, central inversion relates the dominating and dominated displacement quadrants, translation-equivariant cross-correlation applies the same local relation across the grid, and minimization selects only the improvement-directed boundary. Experiments on SCH, FON, POL, KUR, and ZDT synthetic benchmarks assess front-geometry recovery and deterministic extraction on grids from 127 × 127 to 2048 × 2048; the reinforcement-learning results on SCH are interpreted as exploratory feasibility evidence. The present evidence is therefore confined to synthetic benchmarks. The method provides a benchmark-based methodological foundation for future multi-criterion model-selection and calibration research, including option-pricing model research in financial mathematics and quantitative economic analysis. Full article