Search Results (1,445)

The crucial feature of seersucker woven fabrics is their surface geometry. In such kinds of woven fabrics, the puckered stripes appear in the warp direction, separated by stripes of smooth fabric. There are practically no methods to assess the seersucker effect and the reproducibility of this effect. In this work, an optical profilometer enabling non–contact assessment of surface geometry was used to measure the shape of the puckered stripes of example seersucker woven fabrics. Waviness amplitude parameters, such as the arithmetic mean height of individual points within the evaluation area, root mean square deviation of points’ height within the evaluated area, maximum waviness height, maximum peak height, maximum valley depth, skewness and kurtosis, were analyzed for the puckered stripes of the fabrics. Profiles along the puckered stripes were created to analyze their shape. The results showed that weft yarn type influences the waviness amplitude parameters and shape of the puckered stripes in a statistically significant way. To summarize the results, weft yarns with higher linear density provide the most intense seersucker effect, meaning a wave with the greatest peak height and greatest trough depth. Conversely, weft yarns with the lowest linear density provide less variation in peak height and valley depth but the highest wave frequency. However, the observed differences are associated with the weft yarn type, with linear density being only one of several possible explanatory factors. Full article

Driving-fatigue-induced attentional decline and response retardation are critical contributors to traffic accidents. However, stably and precisely identifying fatigue states from noisy electroencephalogram (EEG) signals remains a challenging issue in intelligent driving safety. To address the dual deficiencies of traditional methods in fatigue feature extraction precision and noise robustness, this paper innovatively constructs a collaborative recognition framework that integrates an Improved Strip Attention Mechanism (ISAM) with a Deep Residual Shrinkage Network (DRSN). The core innovations of this framework are twofold: ISAM achieves precise localization and focused enhancement of fatigue-related rhythmic bands in EEG signals via row–column separable adaptive pooling and channel-wise attention augmentation; concurrently, the DRSN module introduces an improved soft-thresholding function, which adaptively generates filtering thresholds through channel attention to effectively suppress noise and artifact interference in physiological signals. The deep fusion of these two modules forms a closed-loop optimization chain of “targeted feature reinforcement–adaptive noise suppression,” enabling the model to stably extract highly discriminative fatigue representations from complex non-stationary EEG signals. Validation on two public datasets, SEED-VIG and SADT, demonstrates that the proposed method achieves recognition accuracies of 98.86% and 97.38%, respectively, outperforming mainstream methods such as the convolutional spatial-frequency network and multi-scale convolutional neural network by 17.38% and 17.76%. These results confirm the significant advantages of the proposed dual-module collaborative architecture in precise fatigue characterization and anti-interference capability, offering a highly reliable technical solution for real-time driver mental fatigue monitoring in real-world road scenarios. Full article

Infrared stripe noise, mainly caused by detector nonuniformity and readout inconsistencies, is a common structured degradation in infrared imaging systems, exhibiting pronounced directional bias, strong column-wise persistence, and distinctive frequency-domain characteristics. These properties make generic restoration networks prone to a trade-off between stripe suppression and detail preservation: conventional two-dimensional attention often allocates modeling capacity to stripe-irrelevant spatial dependencies, early downsampling may entangle directional stripe components with scene structures, and skip connections in U-shaped architectures can reintroduce shallow residual stripe features into the decoder. Residual stripe artifacts and restoration-induced structural distortions can further impair downstream infrared image analysis, particularly small-target detection. To address these issues, we propose a Spatio-Frequency Synergistic Progressive Restoration Network (SFPRNet) for infrared image destriping. SFPRNet progressively exploits the column-wise statistical characteristics of stripe noise, directional frequency information during early scale transformation, and selective cross-level feature refinement to enhance stripe discrimination and suppression while preserving structural details. Extensive experiments on synthetic and real infrared images demonstrate that the proposed SFPRNet achieves superior or competitive performance across most datasets and degradation settings, providing a favorable balance between destriping quality and detail preservation. Furthermore, downstream evaluation with multiple infrared small-target detectors demonstrates that SFPRNet improves subsequent small-target detection performance. Full article

Background: Drought tolerance in wheat is a complex trait controlled by multiple regulatory networks, among which calcium-dependent protein kinases (CDPKs) act as important components linking stress perception with downstream cellular responses. However, the functional contribution of individual CDPK members to drought adaptation in wheat remains largely unclear. This study aimed to identify and functionally characterize drought-responsive CDPK genes associated with differential drought responses in wheat. Methods: Two wheat lines derived from the same breeding background exhibiting contrasting drought adaption, 23B1 and 23B39, were subjected to PEG6000-induced osmotic stress. Growth traits, osmotic adjustment-related metabolites, membrane damage indicators, and antioxidant enzyme activity were evaluated. Transcriptomic analysis was performed at early drought-response stages, followed by differential expression analysis, functional enrichment, CDPK family screening, and qRT-PCR validation. The role of TaCDPK22-5A was further investigated using barley stripe mosaic virus (BSMV)-mediated virus-induced gene silencing (VIGS). Results: The drought-responsive line 23B1 maintained stronger growth, accumulated higher levels of proline and soluble sugars, exhibited enhanced peroxidase activity, and showed reduced membrane lipid peroxidation compared with 23B39. Transcriptome analysis revealed extensive transcriptional reprogramming under drought stress, with differentially expressed genes mainly associated with metabolic adjustment, transport regulation, secondary metabolism, and stress-responsive pathways. Among the identified CDPK members, TaCDPK22-5A showed a strong drought-responsive expression pattern in the line exhibiting stronger drought tolerance (23B1). Virus-induced gene silencing of TaCDPK22-5A significantly impaired drought tolerance, resulting in reduced growth, biomass accumulation, and chlorophyll retention under drought conditions. Conclusions: These findings demonstrate that TaCDPK22-5A contributes positively to drought adaptation in wheat and highlight CDPK-mediated calcium signaling as an important regulatory component of drought responses. The identified gene provides a potential target for improving drought resilience in wheat breeding. Full article

Synthetic Aperture Radar (SAR) enables high-resolution sea-surface wind speed retrieval. However, the enhanced spatial resolution of SAR imagery introduces substantial challenges, from small-scale contamination sources that significantly degrade retrieval accuracy. Particularly in coastal regions, non-wind-related backscatter signals, such as ships and oil slicks, can severely bias wind speed estimates at sub-kilometer scales. In this study, the first-order moment (average, m₁) and second-order moment (variance, m₂) are computed from the normalized radar cross-section (NRCS) within sub-images of Sentinel-1 SAR data acquired in Interferometric Wide (IW) mode. Analysis reveals that clean-sea-surface signals in both VV and VH polarizations cluster around an approximately linear empirical trend, m₂ = 2m₁ + b, in the m₁-m₂ statistical feature space, whereas the examined contamination types deviate from this trend and occupy separable regions. Based on this characteristic, a quality-control framework is proposed for the systematic separation of clean sea surface from image noise (border noise and inter-swath stripe noise) and non-ocean targets (land contamination, bright targets, and dark spots). Validation using independent SAR data from the Taiwan Strait was conducted separately for native 10 m and height-adjusted 3 m buoy observations. For the native 10 m observations, the RMSE and MBE were essentially unchanged at 1.5 m/s and −0.3 m/s, respectively. For the height-adjusted nearshore observations, the RMSE decreased from 3.2 m/s to 2.1 m/s and the MBE changed from −1.5 m/s to −1.1 m/s. Full article

Optical Camera Communication (OCC) enables data reception using common CMOS cameras and commercial webcams. However, applying multi-level modulation with rolling-shutter sensors is constrained by temporal acquisition parameters that may be undocumented or not directly accessible, making it challenging since many existing solutions rely on specialized hardware or require high processing complexity. This paper demonstrates that reliable multi-level OCC can be achieved using only unmodified commercial hardware and straightforward signal processing by experimentally characterizing and validating a 4-level pulse width modulation (4-PWM) link. Data are encoded in the duty cycle of the transmitted signal and recoveblack from the width of the captublack rolling-shutter stripes. Two internal timing parameters are estimated directly from the captublack images without access to the internal camera timing: the row readout period (34.38 $\mathsf{\mu }$s), obtained from the spatial periodicity of the stripes, and the effective integration time (490 $\mathsf{\mu }$s), inferblack from the deformation of the received constellation with carrier frequency. A single-parameter model is derived to describe this deformation and is validated at two carrier frequencies differing by a factor of four, pblackicting constellation compression, a fixed point at a duty cycle of 0.5, and constellation collapse (followed by inversion) when the exposure-to-carrier-period ratio reaches 0.5. We evaluate system performance under different exposure settings, showing that automatic camera control strongly degrades multi-level detection (BER of 0.290, with mean image level variation constrained to $0.14\%$ compablack to $61\%$ under fixed exposure). Under optimal fixed-exposure operating conditions, a prospective 15 min transmission achieved zero bit errors over 35,878 bits at 40 bps, corresponding to a $95\%$ upper confidence bound on the BER of $8.4\times {10}^{-5}$. These results reveal a practical balance between cost, complexity, and performance, demonstrating that 4-PWM rolling-shutter OCC is a viable solution for Internet of Things (IoT) signaling and low-rate data transmission using commercially available devices. Full article

In this work, we theoretically investigate the valley-dependent electron transport properties of graphene modulated by two strained regions and a single ferromagnetic stripe based on the Dirac equation and the transfer-matrix method. By constructing a multi-region model, the conductances of the K and K’ valleys as well as the corresponding valley polarization are systematically calculated. The effects of the magnetic vector-potential, the strain-induced gauge potentials, the widths of the strained regions, and the competition parameter $\lambda$ on the valley-resolved transport behavior are analyzed in detail. The results show that both the conductance and the valley polarization are highly sensitive to the external modulation parameters and the geometric structural parameters. By properly tuning the relative strength and spatial distribution of the magnetic vector-potential and strain, an effective control of valley polarization can be achieved. This work deepens the understanding of valley-dependent transport mechanisms in graphene and provides theoretical guidance for tunable valley filtering in graphene-based systems. Full article

Indirect observation systems, such as hyperspectral remote sensing and passive geophysical measurements, retrieve useful information from redundant observations of the same scene. However, the resulting data are often contaminated by structured coherent artifacts caused by sensor nonuniformity, calibration residuals, or incomplete illumination. These artifacts are difficult to suppress because they are spatially organized components with directional continuity and non-negligible correlation. Their signal-like coherence allows them to mimic image textures or physical events, making conventional denoising methods prone to residual artifacts or signal leakage. To address this problem, we propose a consistency-guided collaborative filtering framework for suppressing structured coherent artifacts while preserving useful signals. The proposed framework extends paired-observation similarity analysis into a consistency-guided strategy for redundant observations. Paired observations of the same target are constructed to distinguish useful signals from physically inconsistent artifacts. This consistency contrast is incorporated into collaborative filtering to guide block matching and aggregation, while a coherent noise power spectral density model characterizes the directional and spatial correlation of the artifacts for targeted noise shrinkage. The proposed framework is evaluated primarily on hyperspectral remote-sensing images contaminated by simulated stripe artifacts, with additional validation on synthetic and field geophysical paired-observation data containing nonphysical coherent events. The results demonstrate that the proposed method can suppress structured coherent artifacts while preserving useful signals and maintaining high signal fidelity. This work provides a unified way to exploit observational redundancy for enhancing imaging reliability. Full article

To further improve the impact toughness of aged 6082 aluminum alloy, electromagnetic shocking treatment (EST) was applied to IHC (solution treatment + unidirectional compression + peak aging) samples. The mechanical properties and impact toughness of the IHC and EST samples were evaluated through room-temperature tensile tests and Charpy impact tests, respectively. The results indicate that, compared to the IHC samples, the EST samples exhibit higher tensile strength (an increase of approximately 9.4%), greater elongation, and significantly higher impact energy (an increase of approximately 26.5%). Microstructural characterization reveals that, compared to the IHC samples, the EST samples possess a lower dislocation density, a larger grain size, and shorter precipitates. Striped grain boundaries were observed in both IHC and EST samples, but they were considerably more pronounced in the EST samples. This indicates that more distinct interface wetting occurred in the EST samples, which promoted grain growth to some extent, a reduction in dislocation density, precipitate dissolution, and the occurrence of interface bridging. This paper primarily investigates the microstructural evolution within the alloy under EST and discusses how these microstructural changes influence the alloy’s performance, thereby providing a novel approach to enhancing the impact toughness of aluminum alloys. Full article

We study a reaction–diffusion model for population–toxin interactions on a two-dimensional torus, where avoidance is driven by a nonlocal average of toxin-related memory. The variables represent population density, toxin concentration, and a phenomenological information field generated by population–toxin encounters. This information diffuses, decays, and enters the taxis term through convolution with a perceptual kernel. We prove local well-posedness, global existence and uniform boundedness, and give sufficient conditions for exponential convergence to either the positive equilibrium or the toxin-only equilibrium. Numerical simulations with two perceptual radii yield stripe and spot patterns, illustrating that the sensing scale can alter spatial organization. These simulations do not establish an effect on population persistence and should be viewed as hypotheses for empirical study. Full article

Wheat stripe rust (yellow rust), a devastating disease caused by the phytopathogen Puccinia striiformis f. sp. tritici (Pst), poses a major threat to global wheat (Triticum aestivum L.) production. Under ongoing climate warming, the highly virulent Pst race CYR34 has become predominant in China and exhibits increased tolerance to elevated temperatures. Although temperature is known to influence Pst urediniospore germination, the molecular mechanisms underlying temperature sensitivity during this process remain poorly understood. In this study, we combined histological examinations with transcriptome sequencing across multiple temperature regimes to identify temperature-responsive genes and characterize the predicted protein association networks in Pst. Urediniospore germination of three Pst races was tested; stronger heat tolerance was observed in CYR34-8 with 67.40–77.40% germination at 9–16 °C. RNA-Seq analysis identified 89 differentially expressed genes (DEGs) associated with temperature sensitivity, and their expression patterns were validated by qRT-PCR. The DEGs were significantly enriched in ubiquinone and other terpenoid-quinone biosynthesis, glycan degradation, and longevity-regulating pathways. Among these DEGs, genes annotated as encoding an ABC transporter, malate dehydrogenase, Hsp70, and a class 3 lipase were identified as putative hub genes in the predicted protein association network and may be associated with the coordination of temperature responses and metabolic processes. Full article

To address the difficulty in stably detecting weld seam keypoints under complex industrial interferences, such as intense arc light, spatter, reflection, and partial occlusion, this paper proposes a lightweight weld seam keypoint detection model named StripePoint-YOLO. The proposed method formulates five typical types of weld seams as a unified detection-based keypoint localization task. Built upon YOLO11n, the model introduces a P2 detection head to enhance shallow high-resolution feature representation for keypoints and adopts SPDConv to reduce the loss of local details caused by early-stage downsampling. Meanwhile, the P5 detection output layer is removed, while its deep semantic features are retained for top-down feature fusion. This design reduces the negative influence of redundant coarse-scale predictions on the center localization of tiny keypoints. For optimization and training, WIoU v3 and NWDLoss are adopted as a joint regression loss to improve the stability of small-scale keypoint bounding box regression. In addition, an online physics-driven data augmentation strategy, OPDDA, is designed to simulate welding disturbances such as arc light, spatter, and dynamic occlusion. Experimental results show that StripePoint-YOLO achieves an mAP@50-95 of 80.46%, a Mean Center Error (MCE) of only 2.33 px, a parameter count of 1.86 M, and a computational cost of 19.42 GFLOPs, while reaching an inference speed of 159.80 FPS under the reported hardware configuration. Further MCE visualization and localization error analysis demonstrate that the proposed method maintains stable keypoint center localization across multiple weld seam types and complex noisy scenarios, verifying the effectiveness of StripePoint-YOLO for accurate and efficient weld seam keypoint detection in industrial welding images. Full article

Cutin matrices in the cuticle cover plant epidermis, facilitating plant adaptation to stressful environments. Although cutin biosynthesis is extensively explored in the model plant Arabidopsis thaliana, the molecular mechanism governing cutin biosynthesis in the agriculturally important crop bread wheat (Triticum aestivum L.) remains largely unknown. The aim of the study is the characterization of the function and transcriptional regulation of a wheat gene involved in cutin biosynthesis. Long-chain acyl-CoA synthetase TaLACS2 was identified as an essential component of the wheat cutin biosynthetic machinery. Silencing of the wheat TaLACS2 gene by barley stripe mosaic virus-induced gene silencing assay resulted in remarkably reduced cutin accumulation and increased cuticle permeability. Furthermore, wheat GT-1-like transcription factor TaGT-3b was identified as a positive regulator of cutin biosynthesis. Silencing of the wheat TaGT-3b gene led to significantly decreased cutin accumulation and enhanced cuticle permeability. Importantly, we found that TaGT-3b could occupy the promoter regions of the TaLACS2 gene and that it functions as a transcriptional activator to activate TaLACS2 gene transcription. Collectively, these results elucidated that wheat GT-1-like transcription factor TaGT-3b boosts cutin biosynthesis, probably by activating TaLACS2 gene transcription, contributing to genetically improving cutin-associated traits in bread wheat. Full article

Background: Thumb pain frequently arises from multiple conditions—de Quervain’s tenosynovitis, carpometacarpal (CMC) osteoarthritis, carpal tunnel syndrome, intersection syndrome, and myofascial pain syndrome—that often coexist yet are traditionally managed as separate entities. Fascial abnormalities, including hyaluronic acid-related densification and impaired interlayer gliding, have been proposed to constitute a shared pathological substrate underlying these conditions. Ultrasound-guided fascia hydrorelease (US-FHR) targeting fascial pathology has been used clinically for thumb–wrist pain; however, the anatomical targets and treatment regions have not been systematically described. Aim: This article presents a fifteen-point US-FHR clinical protocol for five converging thumb pain conditions, based on shared fascial abnormalities—densification and impaired interlayer gliding—that these conditions may have in common. It further provides a shared practical framework for pain physicians, orthopedic specialists, hand therapists, and acupuncturists. Methods: The protocol was organized based on a focused literature review on fascial biology, thumb–wrist anatomy, and the five converging conditions, combined with long-term clinical experience at Kimura Pain Clinic. For each POINT, the anatomical rationale, associated pain pattern, procedural concept, and major safety considerations were summarized. A four-direction screening test (thumb flexion, extension, abduction, and adduction) assessed in three modes (active contraction, resistance loading, and passive stretch), combined with nine established clinical tests, was integrated to identify the affected fascial structures. A diagnostic ultrasound finding characterized by multi-layered hyperechoic bands with reduced interlayer gliding—the sonographic appearance termed “stacking fascia” (a hyperechoic, stripe-shaped lesion), a previously described morphological sign that may reflect fascial densification—is described. Results: The protocol comprises 15 POINTs distributed across two approaches: nine POINTs via a dorsal approach and six POINTs via a palmar approach. The dorsal approach (9 POINTs) covers the first and third extensor compartments, their intersections (1st–2nd and 2nd–3rd), the two radial-artery crossing points (Points 5 and 6, where the radial artery passes deep to the first-compartment and EPL/ECRB–ECRL tendons, respectively), Gokoku (Hegu), the adductor pollicis, and the deep palmar arch. The palmar approach (6 POINTs) covers the thenar muscles, transverse carpal ligament, paraneural sheath and interfascicular epineurium of the median nerve, the median-nerve/FPL/FCR interface, the median nerve within the carpal tunnel, and the deeper palmar ligamentous structures adjacent to the median nerve. Periarterial release around the radial artery is proposed as a hypothesis-generating approach to CMC osteoarthritis, in which fascial constriction of periarterial tissue may contribute to subchondral vascular compromise. For each POINT, the anatomical rationale, associated pain patterns, procedural concept, and safety considerations are integrated and described. Conclusions: The proposed fifteen-point protocol represents an expanded, structured, and clinical-experience-based framework for US-FHR in five converging thumb pain conditions sharing common fascial abnormalities. It may serve as a practical basis for the standardization, education, and broader dissemination of US-FHR in this population. Prospective observational studies, randomized controlled trials, and imaging validation studies are needed to evaluate its clinical effectiveness and to test the underlying mechanistic hypotheses, including potential periarterial vascular contributions to CMC osteoarthritis. Full article

Platform jitter in stereo mapping satellites introduces periodic stripe artifacts into digital surface models (DSMs), degrading geometric quality, while existing detection methods usually depend on disparity maps or high-frequency attitude data. This study proposes a DSM-based frequency-domain framework for detecting and removing jitter-induced stripes in GF-7 DSMs. First, 2D Fourier narrow-band notch analysis of detrended high-pass DSMs estimates stripe orientation and dominant period from directional and radial spectral peak prominence, and a Gaussian narrow-band stop filter is constructed for global suppression. Then, under these spectral priors, a profile-template method uses 1D median profiles, IIR notch filtering, and a global stripe template with a slowly varying amplitude field to model and remove the stripe component in the spatial domain. Multi-temporal co-registered DSM differencing provides reference stripe characteristics for evaluation. Experiments on three GF-7 DSMs show a stripe normal direction aligned with the subsatellite ground track, a stable dominant stripe period of about 90 m, period errors not exceeding 0.34 m, and consistency above 99.7% between the two methods. The spectral notch filtering suppresses more than 92% of stripe-band energy while preserving the overall spectral shape. The proposed framework therefore enables accurate jitter characterization and effective destriping without attitude or disparity information. Full article