Search Results (3,102)

Sound source localization based on microphone arrays has attracted extensive research interest in the fields of speech communication, detection and tracking. However, conventional near-field beamforming typically assumes free-field propagation and ignores coherent ground reflections, which bias phase estimates at floor-mounted arrays and degrade localization accuracy. To address this, the total Green’s function is reformulated by embedding the image-source reflected path directly into the beamforming propagation model. Unlike conventional approaches that assume free-field propagation, this formulation enables phase compensation to jointly account for the direct and ground-reflected wavefronts. The in-phase superposition of signals is then realized through frequency-domain phase compensation, and the sound source position is estimated via the maximum likelihood criterion. Subsequently, a dual-mode operation mechanism of automatic broadband scanning and manual single-frequency analysis is implemented, with frequency-weighted wideband spatial spectrum processing for noise and aliasing suppression. Finally, a real-time sound source localization system based on a 4 × 4 MEMS array is designed. Experimental results show that sound source localization in a broad frequency band can be achieved at standoff distances of 0.1 m–0.3 m from the array plane, with a localization accuracy of less than 0.015 m. The proposed method demonstrates strong robustness against ground-reflection interference and has potential applications in acoustic monitoring, industrial fault diagnosis and other related areas. Full article

Edge inference on resource-constrained embedded nodes demands accelerators that are energy-efficient and compact. This paper presents Versat-AI, an open-source compiler that accepts a standard Open Neural Network Exchange (ONNX) model and generates a complete, synthesisable RISC-V System-on-Chip (SoC) with an embedded CGRA accelerator. The key innovation is applying a known hardware merge strategy to collapse structurally compatible neural network operators into a physical CGRA instance. The Versat-AI compiler also derives memory-mapped interconnects, firmware drivers, and RISC-V application software co-generated by the Py2HWSW SoC framework, eliminating the manual hardware/software co-design effort that previously tied this accelerator’s own design lineage to a single target network. The next phase of the project is to extend this same automatic derivation from sizing the operator vocabulary to sizing per-operator parallel instancing and bandwidth, following the bandwidth-matched scaling principle already demonstrated, by hand, in this accelerator’s own design lineage. The current phase of the project has succeeded in creating a sound automation flow that produces an accelerator that maps each operator onto a single physical datapath instance and occupies 8763 LUTs, 9833 flip-flops, 4 DSPs, and 202 BRAMs on a Xilinx Kintex UltraScale field-programmable gate array (FPGA)—a footprint unchanged across all evaluated models regardless of size—and draws 0.65 W (1.96 W for the complete SoC including the DDR4 controller, by Vivado post-implementation power estimation), achieving $2.3\times$ to $9\times$ speedup over the software-only baseline produced by the same flow on four MLPerf Tiny benchmark tasks. The paper further examines the design choices that delimit this first phase—single-precision arithmetic, a single datapath instance per operator, and the block-RAM cost of the accelerator’s streaming buffers—and sets out the path to quantised integer support and parallel operator instancing. A condensed account of the two-decade lineage of reconfigurable accelerators and open-source SoC platforms that motivated Versat-AI’s design is also given. Full article

This paper presents a likelihood-consistent joint target-message receiver for a strictly constant-envelope continuous phase modulation (CPM) waveform in pulsed phased-array joint radar–communication (JRC). Station A performs monostatic detection with the transmitted message, while Station B performs bistatic detection and communication with an available, degraded, or absent target-independent reference path. The target-scattered message is included only under the target-present hypothesis. A log-domain 16-state recursion evaluates the exact finite-alphabet CPM message marginal over the complete 46+2-symbol, 92-bit frame and is verified against direct enumeration on a six-bit unit frame to floating-point precision. At a 10 dB reference-path SNR, marginalization increases detection probability relative to single-path max-log reconstruction by 4.67 percentage points (95% paired interval 1.33–8.00) and 8.33 percentage points (4.33–12.33) at target-path SNRs of 10 and 14 dB, respectively; the corresponding joint-success differences are zero. Across 2048 ordered error events, the directed conditional distance has a Spearman correlation of −0.970 with empirical pairwise error probability. The CPM parameterization guarantees a constant active-pulse envelope at every array element, whereas constrained common-phase selection provides only a secondary adjustment of message-dependent ambiguity sidelobes. System-level experiments in a coastal setting use independent 92-bit messages and matched transmission resources for the proposed CPM waveform and RRC-QPSK. Both waveforms recover all evaluated direct-path payloads, showing that the proposed constant-envelope waveform preserves communication reliability at the tested operating point. The same records demonstrate geometry-consistent monostatic and bistatic target recovery, while finite-scatterer tests define the boundary of the single-scattering-center model. Full article

Reconfigurable intelligent surfaces (RISs) are emerging as a key enabling technology to engineer the wireless propagation environment in 5G/6G systems. This paper presents the design, characterization, and control of a high-resolution RIS targeting slowly time-varying scenarios, in which fine-grained and stable phase control is more valuable than fast reconfiguration. Starting from the OpenRIS unit-cell layout, the cell is re-optimized for single-polarization operation and continuous phase tuning through a single varactor diode, exploiting the full tuning range enabled by a high-resolution DAC infrastructure rather than multi-bit quantization. The unit cell is analyzed via full-wave 3D FEM simulation in COMSOL Multiphysics and optimized to maximize the reflection-phase excursion while limiting amplitude modulation across the 5G N78 band (3.60–3.78 GHz). The design is experimentally validated in a WR-284 waveguide fixture, exhibiting a phase excursion approaching the full ${360}^{\circ }$ near resonance, with an amplitude variation below 1 dB over the bias sweep at any given frequency, while the average reflection level decreases by about 2 dB from the center to the upper band edge. A fifth-order polynomial phase–voltage calibration feeds a lookup table driving a layered control system based on a Python HMI, a server, and STM32-driven 16-bit DACs. Experimental measurements confirm that the control chain delivers the commanded bias voltages to the addressed unit cells within measurement uncertainty; the array-level beamforming is assessed at simulation level under idealized (unit-magnitude) assumptions, while the experimental characterization of the assembled surface is left to future work. Full article

Distributed acoustic sensing (DAS) converts fiber cables into dense strain-rate sensor arrays, capturing direct, reflected and guided seismic phases with ultra-fine spatial sampling. However, DAS interrogators suffer far stronger random noise than traditional geophones, limiting its microseismic imaging capacity. This work adopts curvelet-transform denoising to suppress noise. Curvelets partition the frequency–wavenumber plane into multiscale directional sectors; coherent wave energy concentrates in limited angular wedges, while stochastic noise disperses evenly across all transform coefficients, enabling noise-signal separation via wedge-wise thresholding. We test four default threshold schemes on synthetic downhole DAS microseismic data. Parameter tuning proves all methods deliver comparable performance, so we compare their out-of-box reliability for shale reservoir monitoring. Three noise-statistic-based strategies perform stably: median-absolute-deviation (MAD), quiet-window and empirical-cumulative-distribution-Function (ECDF percentile) thresholding. By contrast, the default knee-point algorithm from mainstream DAS toolboxes fails, as its preset threshold falls within noise components and barely removes interference. We propose MAD as a robust default for the tested downhole DAS microseismic setting for it estimates thresholds directly from noisy traces without blank reference windows and offers superior operational stability. Applied to field DAS records from a southwest China shale-gas horizontal monitor well, the MAD curvelet workflow greatly enhances microseismic arrivals with negligible spurious events. Benchmarks against standard 2D Daubechies-4 wavelet and adaptive Goldstein FK filtering verify curvelet denoising as a physically interpretable, efficient tool for DAS wavefields. Full article

The composition of honey is complex and can vary depending on its botanical and geographical origin. This study evaluated the phenolic acid profile (PAP), antioxidant activity, and antimicrobial properties of honey samples from different geographical origins, such as Romania (nine types: multiflower, thyme, manna, hawthorn, black locust, linden, rapeseed, mint, and pasture), Malaysia (Tualang), New Zealand (Manuka), and Spain (chestnut). Twelve different varieties of honey were analyzed, one sample for each type, and all analyses were performed in triplicate. Phenolic acids were extracted by solid-phase extraction (SPE) using C18 cartridges, followed by high-performance liquid chromatography with diode-array detection (HPLC-DAD) analysis at 310 nm. Antioxidant activity was assessed using the 2,2′-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays. Antimicrobial activity was evaluated by agar diffusion and broth microdilution to determine the minimum inhibitory concentration (MIC), while microbial anti-adherence activity was assessed using the crystal violet staining assay to determine the minimum anti-adherence inhibitory concentration (MAIC). The tested microorganisms included the reference strains Pseudomonas aeruginosa ATCC 27853, Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 25923, Enterococcus faecalis ATCC 29212, and Candida albicans ATCC 10231, as well as two C. albicans isolates (24114 and 5329). Several phenolic acids, including chlorogenic, caffeic, ferulic, trans-cinnamic, 3-O-methylgallic, p-coumaric, and syringic acids, were identified at varying concentrations across the analyzed honey samples. Rapeseed honey exhibited the highest overall concentration of phenolic acids. Among the honey samples analyzed, chestnut honey had the highest concentration of cinnamic acid, mint honey the highest concentration of ferulic acid, and multiflower honey the highest concentration of syringic acid. Tualang honey exhibited the highest antioxidant activity by both methods, reaching 2.103 mg TE/g honey for DPPH and 1.701 mg TE/g honey for ABTS. Tualang honey also exhibited the strongest antimicrobial activity against C. albicans and P. aeruginosa, whereas multifloral honey was the most active against E. faecalis. The analyzed honey extracts differed in their phenolic acid composition and biological activities, including antioxidant, antimicrobial, and anti-adherence effects of microorganisms on substrates. While associations were observed between selected phenolic acids and some of the evaluated biological activities, the overall biological properties of honey are more likely to arise from the combined contribution of multiple bioactive constituents than from individual compounds alone. The novelty of this study lies in the comparative assessment of the PAP obtained following SPE, and the biological activities of different types of honey from various botanical and geographical sources. Full article

A laboratory Hertz-like gravitational wave communication system (“gravity radio”) is proposed using coherent optical-stress sources in high-Q optical fiber ring-resonator arrays. Hyperentangled photon pairs and coincident tunneling events provide timing, phase, and correlations, while the gravitational source is the local, conserved field-plus-medium stress-energy tensor generated by phase-locked coherent optical fields. Because the electromagnetic stress tensor is quadratic in the fields, the source can contain both sum-frequency and difference-frequency components. The latter is emphasized because it relaxes the localization, phase-stability, and receiver-transduction requirements. The directed coherent transverse-traceless stress amplitude and receiver equivalent strain noise are derived for a meter-scale transfer test. Full article

Distributed multiple-input multiple-output (MIMO) is a promising architecture for future wireless systems because cooperation among geographically separated base stations (BSs) improves coverage, spectral efficiency, and link reliability. However, the large effective aperture formed by distributed BSs makes near-field effects non-negligible and complicates accurate channel state information acquisition. Existing near-field estimators often suffer from modeling errors caused by approximate angle–range decoupling or from the high storage and computational costs of dense two-dimensional sparse representations. This article proposes an off-grid variational Bayesian channel-estimation framework for the considered distributed near-field MIMO geometry, which comprises equally spaced, collinear BS reference points and aligned uniform linear arrays (ULAs) with common inter-element spacing. We establish a geometry-coupled model based on the exact geometric spherical-wave phase response and map the local direction–range parameters observed by different BSs into a common reference coordinate system, yielding a two-dimensional jointly sparse representation. An independent-vector variational Bayesian inference algorithm then decomposes the high-dimensional multiuser recovery problem into user-specific posterior subproblems. It operates directly on the received pilot matrices, avoiding pilot–matrix inversion and the resulting distortion of noise statistics. A two-dimensional skewed off-grid update is further embedded in an expectation-maximization procedure to jointly refine angle and range offsets, mitigating basis mismatch while permitting a coarser initial dictionary. Simulation results support the effectiveness of the proposed method in the evaluated scenarios. Full article

Background/Objectives: Berberis species are recognized for their ethnomedicinal importance and phytochemical richness associated with antidiabetic activity. Although B. crataegina is widely distributed in the Turkish flora and has a history of traditional use, its phytochemical properties and biological activities remain less extensively investigated than those of other Berberis species. This study aimed to comparatively evaluate the phytochemical profiles, in vitro antidiabetic potential, and cytoprotective effects of extracts prepared from different parts of B. crataegina in a high-glucose-induced SH-SY5Y cell-based model of diabetic neuropathy. Methods: Crude hydroethanolic extracts (70% ethanol) were prepared from the leaves, flowers, shoots, roots, and fresh fruits of B. crataegina collected from Kızılcahamam, Ankara, Türkiye. The total phenolic and flavonoid contents, antioxidant capacities and α-glucosidase inhibitory activities of leaf, flower, shoot, root, and fruit extracts were determined. The cytoprotective effects of the crude extracts were evaluated in a high-glucose-induced SH-SY5Y cell model. The metabolomic profiles of the extracts were comparatively analyzed using liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). The most active fruit extract was fractionated by reversed-phase vacuum liquid chromatography (RP-VLC), and the phytochemical contents and α-glucosidase inhibitory activities of the fractions were evaluated. The major phenolic compounds in the most active fruit extract were quantitatively determined using high-performance liquid chromatography–diode array detection (HPLC-DAD). The relationships between metabolites and biological activities were investigated through correlation analysis. Results: The fruit extract was distinguished by its α-glucosidase inhibitory activity, total phenolic content, antioxidant capacity, and cytoprotective effect in the high-glucose-induced SH-SY5Y cell model. It showed no marked cytotoxicity at concentrations ranging from 25 to 400 µg/mL and, at 25 µg/mL, attenuated the high-glucose-induced reduction in cell viability, restoring viability to a level close to that of the normal control. Untargeted metabolomic analysis identified 191 metabolites detected in at least two crude extracts, while the metabolites detected exclusively in the fruit extract were predominantly flavonoids and flavonoid glycosides. Fractionation showed that α-glucosidase inhibitory activity was mainly concentrated in the medium-polarity fractions; however, none of the fractions reached the activity level of the crude extract. Chlorogenic acid, rutin, caffeic acid, protocatechuic acid, quercetin, and quercetin-3-O-glucoside were detected and quantified in the fruit extract by HPLC-DAD. Correlation analysis indicated that the observed biological activities may be associated with phenolic acids, flavonoids, and other polyphenolic metabolites. Conclusions: The fruit extract of B. crataegina showed promising α-glucosidase inhibitory activity and cytoprotective effects in the high-glucose-induced SH-SY5Y cell model. The findings suggest that these effects may arise from the combined contribution of multiple constituents within a polyphenolic matrix rather than from a single compound; however, synergistic interactions were not experimentally demonstrated. These results support further evaluation of the fruit extract through mechanistic, in vivo, and standardization studies. Full article

A rapid reversed-phase ultra-high-performance liquid chromatography method with diode-array detection (RP-UHPLC-DAD) was developed and validated for the simultaneous determination of major bioactive phenolic compounds (hydroxytyrosol, tyrosol, and oleuropein) and triterpenic acids (maslinic and oleanolic acids) in table olives from major Greek cultivars. Existing chromatographic methods for table olives typically target either the phenolic compounds or the triterpenic acids, requiring separate protocols. The proposed method determines both classes simultaneously, resolving all five analytes (resolution, R_s ≥ 5) within a 20 min separation (25 min total run) using a single methanolic co-extraction, thereby reducing analysis time and increasing throughput relative to sequential approaches. This protocol was selected among four evaluated extraction procedures, based on simplicity and efficient analyte extraction. The method showed excellent linearity (R² > 0.999), along with satisfactory sensitivity, selectivity, accuracy, and precision across the tested ranges. Recoveries of 70.8–108.9% were obtained in three different matrices (Chalkidiki, Kalamata, and Throumba Thassou olives), indicating satisfactory applicability to complex foods. The samples differed in their analyte profiles, with hydroxytyrosol predominating in the Chalkidiki and Kalamata samples, whereas oleuropein was detected only in Throumba Thassou olives. Sustainability assessment using the Complementary Green Analytical Procedure Index (ComplexGAPI) indicated moderate greenness, while a Blue Applicability Grade Index score of 72.5 denoted good practical applicability. Full article

High-speed airborne platforms impose stringent aerodynamic constraints that restrict traditional planar antenna designs. Concurrently, multi-component echoes from extended targets and complex propagation environments induce strong signal coherence, severely degrading spatial angle estimation. To address these dual challenges, this paper proposes a straight-curved hybrid L-shaped asymmetric conformal array hardware topology tailored for cylindrical radomes. Building upon this, a millimeter-wave radar 3D point cloud imaging framework is developed for coherent targets. An orthogonal virtual manifold transformation is first devised to effectively compensate for the non-linear phase distortion induced by the conformal topology. Subsequently, a cascaded Forward-Backward Spatial Smoothing (FBSS) and Root-MUSIC framework is used for efficient signal decoherence. To resolve angle mismatches, a global cost function based on the cross-covariance Frobenius norm is formulated, which pairs independent angles and significantly suppresses spatial ghost targets. Systematic evaluations using 3D computer vision metrics demonstrate that the proposed method achieves accurate geometric restoration of aircraft targets with coherent signals. In the representative simulation, the method obtains a median point-wise localization error of 0.3986 m, a Chamfer Distance (CD) of 0.9695 m², an Earth Mover’s Distance (EMD) of 1.9504 m, and a spatial angular resolution of 1.0° under the stated test conditions. Under the stated simulation assumptions, boundary analyses indicate stable reconstruction around a post-pulse-compression SNR of −8.0 dB and a conformal curvature of 12.50 m⁻¹ ($r=0.08$ m), providing simulation-based design references for conformal radar 3D imaging. Full article

To address the slow response, low pointing accuracy, and degraded stability caused by the coexistence of fractional-order dynamics, dual-axis coupling, and system delay in liquid crystal optical phased array (LCOPA) beam control, a fractional-order composite control method is proposed. First, the LCOPA is modeled as a two-input two-output system, and a fractional-order time-delay dynamic model is established. A composite control architecture integrating a fractional-order controller, a diagonal decoupling compensator, and a Smith predictor is then designed to improve dynamic response, suppress cross-axis coupling, and mitigate delay-induced performance degradation. A multi-strategy improved sparrow search algorithm is used to optimize the dual-channel fractional-order controller parameters, and closed-loop stability is verified using characteristic roots and the Matignon criterion. Simulation results show that the settling times of both axes are 11.50 ms, reduced by 62.54%/62.30%, 57.09%/56.11%, and 51.68%/48.89% compared with the results for PID, FOPID, and ADRC, respectively. The maximum cross-axis deviations are reduced to 0.0036° and 0.0030°, respsectively. Experiments further show that the mean absolute pointing errors of the X- and Y-axes decrease from 0.0466° and 0.0362° to 0.0057° and 0.0045°, while the RMSEs under external disturbances are 0.0060° and 0.0044°, respectively. These results demonstrate improved response speed, pointing accuracy, decoupling performance, and disturbance rejection. Full article

Hydrochars (HCs) were produced from pine needles (urban waste), brewer’s spent grain, and grape pomace via hydrothermal carbonization (HTC) at 230 °C, and were comparatively assessed as unmodified, low-dose amendments (1 wt%) in an alkaline soil slurry. Fixed-contact-time (4 h) batch tests were conducted using a Taguchi L9 array to screen the effects of feedstock type, HTC residence time, initial metal concentration, and test temperature on the aqueous-phase removal of for Zn, Pb, and Cd at this fixed endpoint. In the ternary test containing 20 mg/L of each metal, the soil-only control removed 94% Zn, 99% Pb, and 96% Cd, whereas the soil amended with 1 wt% pine-needle HC removed 98% Zn and 99% Pb, while Cd in the recovered liquid was below the instrumental detection limit. Operational distribution coefficients (K_d) and separation factors (SF) calculated at the 4 h endpoint indicated preferential Cd partitioning within the amended soil system. These findings support further evaluation of minimally processed, low-dose hydrochars for metal-contaminated soils, while providing a potential valorization route for residual biomass within a circular economy framework. Full article

Background/Objectives: Cutaneous T-cell lymphomas (CTCL), most commonly mycosis fungoides and Sézary syndrome, are rare non-Hodgkin lymphomas. Advanced disease responds poorly to current treatments, highlighting the need for new molecularly targeted therapies. WEE1 is a central regulator of the G2/M checkpoint and S-phase progression and has emerged as a therapeutic target in several malignancies, yet it has not been systematically explored in CTCL. Methods: We screened a library of more than 2200 kinase inhibitors in CTCL cell lines and selected adavosertib for further study. Its effects were tested in four CTCL lines; primary keratinocytes and fibroblasts; patient-derived malignant CD4⁺ T cells and healthy donor CD4⁺ T cells; and a MyLa xenograft model, using viability, apoptosis, cell-cycle, Western blot, and phospho-protein array assays. Results: Adavosertib reduced viability at submicromolar IC₅₀ values (0.26–0.56 µM) across all four CTCL lines while largely sparing primary skin cells and was more active in malignant than in healthy donor CD4⁺ T cells. It induced apoptosis and cell-line-specific S-phase and/or G2/M accumulation, lowered WEE1 and phospho-CDK1 (Tyr15), and increased phospho-H2A.X. A phospho-protein array showed activation of checkpoint and stress signalling. In a preliminary xenograft experiment, adavosertib slowed MyLa tumour growth. Conclusions: These preclinical data identify WEE1 as a therapeutic target in CTCL and support further preclinical and early-phase clinical evaluation of adavosertib in this disease. Full article

As offshore wind turbines continue to grow in capacity, reducing the structural weight of substructures has become a key factor in securing project economics, and the package installation method has attracted attention as a promising technology for reducing installation costs. This study presents an integrated design procedure for the package installation substructure of a 10 MW fixed offshore wind turbine, ranging from the establishment of classification rule-based design load conditions to surrogate model-based approximate optimization and verification of the optimum designs. Design load conditions for the installation, operation, and survival phases were defined in accordance with DNV classification rules and IEC 61400-3-1, and the structural safety of the initial design was evaluated via finite element analysis. Response data for 243 design matrices were generated using an orthogonal array design in which the thicknesses of nine primary structural members were defined as three-level design variables. Kriging, response surface methodology (RSM), and radial basis function neural network (RBFN) surrogate models were compared using multiple statistical metrics, and the RBFN, exhibiting the highest average coefficient of determination of 0.942 together with the lowest error levels for the stress responses, was selected for the approximate optimization. Discrete and continuous design variable optimizations were carried out in parallel by coupling the RBFN surrogate model with the adaptive simulated annealing (ASA) algorithm. The discrete optimum design reduced the structural weight by 2.5% while satisfying the allowable stress criteria for all load conditions, converged with approximately 94% fewer design evaluations than the continuous approach, and is defined directly in manufacturable plate thicknesses; it was therefore adopted as the final design. Full article