Search Results (16)

Rapid detection of wilt-affected pine crowns in mountainous forests is hindered by occlusion, self-shadowing, and heterogeneous backgrounds in conventional nadir products. We evaluated whether oblique UAV RGB imagery improves crown-level detection relative to nadir imagery under matched site, season, sensor, and workflow conditions. The workflow was designed for rapid post-flight screening of geotagged UAV photographs. Paired nadir orthophotos and 45–70° oblique photographs were acquired over pine stands in Wenshan Prefecture, Yunnan, China, and organized into D1 (nadir), D2 (oblique), and D3 (simple mixed-view concatenation). Three YOLO11 detectors were trained for crown shoot damage ratio (SDR)-derived operational classes: early-stage (SDR < 50%), severely damaged (SDR ≥ 50%), and withered (needle-free dead crowns). A paired crown-level RGB subset (n = 20 crowns observed in both views) was analyzed as supporting evidence for view-dependent appearance differences. The oblique-image model (D2) achieved the highest validation performance, with precision of 0.994, recall of 0.991, F1-score of 0.989, mAP@0.5 of 0.995, and mAP@0.5:0.95 of 0.880. The paired subset showed a significant multivariate RGB profile difference between views (Hotelling’s T2 = 58.91, F = 3.10, p = 0.044), driven mainly by reduced Excess Green and greater dispersion of blue-related traits under oblique viewing. These results indicate that oblique UAV photographs retain additional crown-edge, lateral-structure, and chromatic context for detecting wilt-affected pine crowns. Oblique RGB imagery therefore provides a practical, low-cost input for rapid forest health surveillance and targeted field verification in rugged pine landscapes. Full article

Zero-shot goal navigation requires an agent to locate targets in unseen environments based on object categories, reference images, or text descriptions, placing high demands on scene understanding and reasoning. Existing methods mainly rely on online observations, modality similarity, or heuristic graph matching, and therefore still struggle with complex target search due to limited use of external knowledge and weak multi-step reasoning. We propose PriorNav, a prior-knowledge-enhanced framework for zero-shot goal navigation. PriorNav learns a unified retrievable knowledge space from semantic, instance, and relational knowledge, maintains a knowledge-enhanced scene graph by fusing retrieved priors with online observations, and performs progressive decision-making through multi-step iterative reasoning across exploration, verification, and approach stages. Experiments on Object-Goal, Image-Instance Goal, and Text-Goal navigation show that PriorNav improves the success rate over the baseline by 3.5%, 13.3%, and 3.5%, respectively, while also outperforming the strongest training-free baselines on all three tasks. Ablation studies further verify the effectiveness of multi-level prior knowledge, scene-graph enhancement, and iterative reasoning. These results show that combining prior knowledge with explicit reasoning is a promising direction for improving zero-shot goal navigation. Full article

Glyphosate is a highly polar herbicide, the reliable molecular recognition of which is complicated by co-occurring structural analogues, metabolites, and derivatives in real-world samples. Rather than reporting new aptamer discovery, this study establishes a standardized, solution-phase isothermal titration calorimetry (ITC) workflow to thermodynamically reassess two literature-reported glyphosate DNA aptamers, Seq03 and Seq05, under matched buffer composition and instrument settings. After verification of baseline stability and evaluation of heat-of-dilution contributions, ligand-to-aptamer titrations yielded apparent dissociation constants of approximately 8.14 μM for Seq03 and 40.2 μM for Seq05, enabling affinity-based prioritization of these reported candidates within the tested concentration window. To define an application-relevant selectivity boundary, we further constructed a counter-screen panel restricted to glyphosate-related chemicals, including structural analogues, metabolites, and derivatives, and evaluated all candidates using an identical ITC protocol with explicit background handling. None of the counter-screen compounds produced binding-consistent, saturable isotherms after integration and control-based interpretation; instead, their responses remained close to background heat and were therefore operationally classified as having no detectable binding under the tested conditions, including a reverse-titration format check with Glufosinate-N-acetyl. Collectively, these results position ITC as a label-free, platform-independent validation step for small-molecule aptamer benchmarking prior to analytical translation, while also highlighting that the present conclusions are bounded by the tested PBS-based conditions and the sensitivity window of the current ITC configuration. Full article

Multiple string matching is a fundamental operation in real-time analytics, cybersecurity, bioinformatics, and large-scale information retrieval. Nevertheless, existing approaches continue to face inherent trade-offs among preprocessing efficiency, verification overhead, and support for dynamic pattern updates, particularly in large and continuously evolving environments. This paper presents MMIVL, a high-performance algorithm founded on the multi-character inverted list (m-CIVL), a unified and inherently dynamic indexing framework for pattern management. By integrating positional information, termination semantics, and pattern associations within a single structure, m-CIVL enables direct matching without requiring a separate verification stage. MMIVL achieves a preprocessing complexity of O(|P|/s), a search complexity of O(|T| + n_occ), and an update complexity of O(|p|/s), where s denotes the segment length. Extensive experiments on synthetic and real-world datasets demonstrate that MMIVL consistently outperforms representative baselines, with especially strong gains in large-scale scenarios, while maintaining stable performance and favorable memory efficiency. Overall, these results establish m-CIVL as an effective, scalable, and practically viable solution that unifies efficient preprocessing, high-throughput searching, and dynamic update capability for modern multiple string-matching applications. Full article

To tackle the drawbacks of small effective area and limited incident angle in conventional Fabry–Pérot (F-P) etalons, this paper presents a high-utilization laser frequency-selective ultra-narrow band F-P filter module, along with systematic investigations into its operating principle, simulation, design, and verification. A simulation model with a central wavelength of 532.20 nm (±0.1 nm) and a free spectral range of 300 pm is developed, and a prototype filter is fabricated accordingly. The prototype exhibits a transmission peak linewidth better than 0.037 nm and a peak transmittance over 68%, matching well with the simulation. Simulations also reveal symmetric high-transmittance peaks at ±2.9° with stable frequency selection performance. On this basis, an integrated module is proposed using field-of-view angle conversion and optical path multiplexing. Under combined incidence at 0° and ±2.9°, the module achieves 1.67 times the energy of single-angle incidence while satisfying wavelength and bandwidth requirements. The proposed structure breaks through the conventional normal-incidence restriction and offers a novel approach for high-efficiency, multi-angle multiplexing applications of F-P etalons in precision optical systems. Full article

Time delays are inherent in modern motion-control and electric-drive loops due to sensing, filtering, sampling and computation, communication, and actuation scheduling. When such delays are only partially known, they can markedly reduce stability margins and narrow the admissible range of state-feedback gains, especially in high-bandwidth servo applications. This paper develops a design-oriented state-feedback framework for delay-affected plants based on the Manabe polynomial concept and the Coefficient Diagram Method (CDM). The plant is represented as a chain of integrators of order two to four with an effective input gain, and the feedback gain is synthesized for the nominal delay-free model by matching a standard Manabe/CDM characteristic polynomial using the classical CDM stability-index pattern. When an unmodeled input delay is present, the closed loop is governed by a delay-dependent characteristic equation. By introducing a normalized representation, the analysis yields explicit delay-stability limits that directly translate into a lower bound on the equivalent time constant used for tuning. The degradation of the phase margin and gain margin with increasing normalized delay is quantified as design charts, and a simple phase-margin-based inequality is proposed for selecting the tuning time constant, with gain-margin checks recommended as a verification step. Full article

Background: Celiac disease (CD) is a multisystem immune-mediated disorder increasingly recognized to affect sleep and neurobehavioral functioning. Pediatric data remain limited, and no prior study has examined especially for sleep microstructure in this population. This study evaluates the prevalence and patterns of sleep disturbances in children with CD using the Sleep Disturbance Scale for Children (SDSC) and explores potential electrophysiological correlates through N2 sleep spindle analysis. Methods: Children with biopsy-confirmed CD (n = 31) and age-matched controls (n = 25) completed the SDSC. A subgroup of CD patients with SDSC ≥ 35 and healthy controls underwent quantitative sleep spindle analysis (C3, C4, O1, O2) using automated and visual verification methods combined. Results: Clinically significant sleep disturbances were substantially more prevalent in CD than in controls (77.4% vs. 12%). Excessive somnolence, sleep–wake transition disorders, and sleep hyperhidrosis were the most affected domains. Moreover, among children with CD, those noncompliant with a gluten-free diet exhibited higher rates of excessive somnolence and sleep–wake transition disorders. While spindle parameters did not differ between groups, higher SDSC scores (≥35)—particularly in the somnolence and sleep–wake transition disorder domains—are associated with reduced spindle amplitude and density, suggesting that spindle alterations are linked to sleep disturbance severity rather than disease status per se. Conclusions: Sleep disturbances are common in pediatric CD and worsen with poor dietary adherence. Although sleep microarchitecture is largely preserved, reduced spindle activity is evident in children with higher subjective sleep burden, suggesting that spindle metrics may serve as potential objective markers for sleep disturbance. Longitudinal studies are required for validation. Full article

Accurate group target association is essential for multi-sensor multi-target tracking, particularly in heterogeneous radar systems where systematic biases, asynchronous observations, and dense formations frequently cause ambiguous or incorrect associations. Existing approaches often rely on strict spatial assumptions or pre-trained models, limiting their robustness when measurement distortions and sensor-specific deviations are present. To address these challenges, this work proposes a robust association framework that integrates deep feature embedding, density-adaptive clustering, and global graph-theoretic matching. The method first applies an autoencoder–HDBSCAN clustering scheme to extract stable latent representations and obtain adaptive group structures under nonlinear distortions and non-uniform target densities. A weighted bipartite graph is then constructed, and a global optimal matching strategy is employed to compensate for heterogeneous systematic errors while preserving inter-group structural consistency. A mutual-support verification mechanism further enhances robustness against random disturbances. Monte Carlo experiments show that the proposed method maintains over 90% association accuracy even in dense scenarios with a target spacing of 1.4 km. Under various systematic bias conditions, it outperforms representative baselines such as Deep Association and JPDA by more than 20%. These results demonstrate the method’s robustness, adaptability, and suitability for practical multi-radar applications. The framework is training-free and easily deployable, offering a reliable solution for group target association in real-world multi-sensor fusion systems. Full article

Ensuring the integrity of medical images is essential to securing clinical workflows, telemedicine platforms, and healthcare IoT environments. Existing watermarking and reversible data-hiding approaches often modify pixel intensities, reducing diagnostic fidelity, introducing embedding constraints, or causing instability under compression and format conversion. This work proposes a distortion-free, non-embedding authentication framework that leverages the inherent stability of the most significant bit (MSB) patterns in the Non-Region of Interest (NROI) to construct a secure and tamper-sensitive reference for the diagnostic Region of Interest (ROI). The ROI is partitioned into fixed blocks, each producing a 256-bit SHA-256 signature. Instead of embedding this signature, each hash bit is mapped to an NROI pixel whose MSB matches the corresponding bit value, and only the encrypted coordinates of these pixels are stored externally in a secure database. During verification, hashes are recomputed and compared bit-by-bit with the MSB sequence extracted from the referenced NROI coordinates, enabling precise block-level tamper localization without modifying the image. Extensive experiments conducted on MRI (OASIS), X-ray (ChestX-ray14), and CT (CT-ORG) datasets demonstrate the following: (i) perfect zero-distortion fidelity; (ii) stable and deterministic MSB-class mapping with abundant coordinate diversity; (iii) 100% detection of intentional ROI tampering with no false positives across the six clinically relevant manipulation types; and (iv) robustness to common benign Non-ROI operations. The results show that the proposed scheme offers a practical, secure, and computationally lightweight solution for medical image integrity verification in PACS systems, cloud-based archives, and healthcare IoT applications, while avoiding the limitations of embedding-based methods. Full article

With the rapid development of global maritime trade, high-precision ship heading estimation has become crucial for maritime traffic safety and intelligent shipping. To address the challenge of heading estimation from horizontal-view optical images, this study proposes a novel framework integrating DeepLabV3+ image segmentation with contrastive-learning-optimized multi-scale similarity matching. First, a cascaded image preprocessing method is developed, incorporating linear transformation, bilateral filtering, and the Multi-Scale Retinex with Color Restoration (MSRCR) algorithm to mitigate noise and haze interference and enhance image quality with improved target edge clarity. Subsequently, the DeepLabV3+ network is employed for the precise segmentation of ship targets, generating binarized contour maps for subsequent heading analysis. Based on actual ship dimensional parameters, 3D models are constructed and multi-angle rendered to establish a heading template library. The framework introduces the Multi-Scale Structural Similarity (MS-SSIM) algorithm enhanced by a triplet contrastive learning mechanism that dynamically optimizes feature weights across scales, thereby improving robustness against image degradation and partial occlusion. Experimental results demonstrate that under noise-free, noise-interfered, and mist-occluded conditions, the proposed method achieves mean heading estimation errors of 0.41°, 0.65°, and 0.88°, respectively, significantly outperforming the single-scale SSIM and fixed-weight MS-SSIM approaches. This verification confirms the method’s effectiveness and robustness, offering a novel technical solution for ship heading estimation in maritime surveillance and intelligent navigation systems. Full article

Researchers frequently utilize the method of optical initial structure (MOIS) of Czerny–Turner (C–T) spectrometers for aberration-correction studies based on the coma-free equation. While effective, this method has limitations: small numerical apertures at slits (0.05–0.07) hinder weak signal detection; V or W-shaped variations in Airy disk across wavelengths; optical resolution depends on the radius of the collimating lens may not match detector resolution; and sequence patterns based on the spot diagrams cannot simulate the full width at half maximum (FWHM) under discrete sampling. To address these issues, using ray tracing and imaging equations, three criteria are proposed: luminous flux and aberration balance (LFAB), Airy disk variation at imaging points (ADVI), and optical-detector resolution matching (ORDR). A verification system with a 500–750 nm wavelength range and 0.4 nm resolution was designed. Results show that designing spectrometers based on these criteria increases the slit’s numerical aperture to 0.11 while controlling aberrations. After optimization, the tangential Airy disk size decreased by 28% with variations within 3 μm. Discrete sampling indicates FWHM pixel errors remain within 1/2 pixel of the theoretical value, and FWHM is at least 2.5 pixels, satisfying stricter sampling requirements beyond Nyquist. Optimization only involves adjusting the image plane by 0.017 mm axially, 0.879 mm off-axis, and 0.48° eccentricity. This research strengthens spectrometer design theory and improves practical applications. Full article

Consistent standards regarding whether postoperative adjuvant chemotherapy is required in the treatment of adenoid cystic carcinoma of the breast (ACCB) are currently lacking. Using clinical data from the Surveillance, Epidemiology, and End Results (SEER) database (1988–2015), and the National Cancer Center of China (2004–2020), we retrospectively analyzed patients with ACCB who received radical treatment. A total of 661 patients were eligible. The median age at diagnosis was 61 years; 99.5% of patients were initially diagnosed with stage I and II breast cancer, and 76.7% had triple-negative breast cancer. Only 12.4% of patients received adjuvant chemotherapy. Multivariate analysis showed that patients with lymph node metastasis and non-radiotherapy had worse overall survival (OS) (p < 0.05). Patients with lymph node metastasis, stage IIB and III, histological grade ≥ 2, and non-radiotherapy had worse breast cancer-specific survival (BCSS) (p < 0.05). Adjuvant chemotherapy did not improve the OS or BCSS. Patients treated with adjuvant chemotherapy also had no better survival outcomes after propensity score matching. External data verification confirmed that chemotherapy did not improve disease-free survival or OS. Adjuvant chemotherapy cannot improve the clinical outcomes of ACCB, even in subgroups with a high risk of recurrence and metastasis. Full article

The purpose of this study is to improve the overall cognitive function of patients with dementia in Yunlin County, Taiwan, by designing an indoor gardening flower combination game suitable for home and maintenance institutions. This paper uses qualitative research (participatory interviews, case studies, and contextual observation methods in the demand exploration phase) and quantitative research (experimental methods and the Mini-Mental State Examination (MMSE) and Barthel Index questionnaires in the product verification phase). This study adopted a four-stage service design: demand exploration, demand definition, design implementation, and product verification. In the stage of demand exploration, 14 elderly people with mild or moderate dementia were interviewed, and two cases were selected for two in-depth observations of horticultural treatment activities. Common obstacles and potential demand points were listed after integration: (1) The safety of elderly patients with dementia can be improved by employing horticultural treatment activities transferred from outdoors to indoors; (2) the objects and facilities used in horticultural activities should be improved to reduce the attention burden of elderly patients with dementia; (3) the elements of reminiscence or familiarity of the mentally handicapped elderly should be increased; (4) the process of gardening and planting can be used by two or four people to improve social and language skills. According to this study, an indoor gardening planting table game was developed. This game includes a group of flower combination prompt cards (including five flower groups: camellia, cherry blossom, chrysanthemum, kapok, and lotus), a group of color and number prompt rings, and a flower base, which provides planting of up to 25 flowers and is matched with the number prompt color rings; then, the combined flowers are planted into the base. In the final experience experiment, 7 participants with free movement of the upper limbs and mild or moderate dementia were selected by the MMSE and Barthel Index to participate in a 5-week experiment. After using a combination of progressive low-level, medium-level, and high-level flower combination tasks, the results showed that the overall performance of the elderly patients with mild or moderate dementia in the MMSE test was improved by the indoor gardening planting table game. However, the treatment effect-size presented a low effect magnitude. Full article

The low-cost, indoor-feasibility, and non-intrusive characteristic of passive infrared sensors (PIR sensors) makes it widely used in human motion detection, but the limitation of its object identification ability makes it difficult to further analyze in the field of Geographic Information System (GIS). We present a template matching approach based on geometric algebra (GA) that can recover the semantics of different human motion patterns through the binary activation data of PIR sensor networks. A 5-neighborhood model was first designed to represent the azimuth of the sensor network and establish the motion template generation method based on GA coding. Full sets of 36 human motion templates were generated and then classified into eight categories. According to human behavior characteristics, we combined the sub-sequences of activation data to generate all possible semantic sequences by using a matrix-free searching strategy with a spatiotemporal constraint window. The sub-sequences were used to perform the matching operation with the generation-templates. Experiments were conducted using Mitsubishi Electric Research Laboratories (MERL) motion datasets. The results suggest that the sequences of human motion patterns could be efficiently extracted in different observation periods. The extracted sequences of human motion patterns agreed well with the event logs under various circumstances. The verification based on the environment and architectural space shows that the accuracy of the result of our method was up to 96.75%. Full article

The intent of this paper is to provide an overview of basic concepts, types, techniques, and experimental studies of the current state-of-the-art Frequency Selective Surfaces (FSSs). FSS is a periodic surface with identical two-dimensional arrays of elements arranged on a dielectric substrate. An incoming plane wave will either be transmitted (passband) or reflected back (stopband), completely or partially, depending on the nature of array element. This occurs when the frequency of electromagnetic (EM) wave matches with the resonant frequency of the FSS elements. Therefore, an FSS is capable of passing or blocking the EM waves of certain range of frequencies in the free space; consequently, identified as spatial filters. Nowadays, FSSs have been studied comprehensively and huge growth is perceived in the field of its designing and implementation for different practical applications at frequency ranges of microwave to optical. In this review article, we illustrate the recent researches on different categories of FSSs based on structure design, array element used, and applications. We also focus on theoretical breakthroughs with fabrication techniques, experimental verifications of design examples as well as prospects and challenges, especially in the microwave regime. We emphasize their significant performance parameters, particularly focusing on how advancement in this field could facilitate innovation in advanced electromagnetics. Full article