Search Results (362)

As the requirements for structural functionality increase, designers frequently opt for inclined columns instead of traditional vertical columns. This choice enhances the spatial dynamics, esthetic appeal, and lighting effects of the structure. However, the research on the failure mechanism and seismic performance of inclined columns under cyclic loading is not systematic. To promote the application of inclined columns in earthquake-prone areas, quasi-static tests were conducted on steel-reinforced concrete inclined columns (SRCIC). The study analyzed the elastic and elastic-plastic development trend, failure mechanism, second-order effect, deformation and energy dissipation of the inclined columns. Traditional vertical columns often experience bending or shear failure, while SRCIC exhibited a new failure pattern characterized by bending failure on one side and compression failure on the other. Based on the experimental design, the nonlinear finite element analysis model of SRCIC is established. The finite element model was validated for horizontal peak load, ductility coefficient, and damage area at various inclination angles, providing a foundation for further parameter analysis. In the numerical analysis section, the effects of inclination angle, steel ratio, reinforcement ratio, and stirrup ratio on the skeleton curve and ductility coefficient were studied in detail, leading to the application of SRCIC. Full article

In order to solve the problem of inadequate confinement provided by traditional rectangular stirrups in concrete square columns under stringent seismic fortification requirements, a spiral stirrup with a better constraint effect was used in the square columns in this study. Through a comprehensive analysis of test results, numerical simulations, and theoretical derivations, the seismic performance and shear capacity calculation methods of concrete square columns confined with five-spiral composite stirrups were investigated. This study provides pertinent technical data to facilitate the engineering application of such columns. The existing low-cycle repeated loading tests of 13 concrete square columns confined with five-spiral composite stirrups were collected and analyzed; some of these specimens were selected for finite element numerical simulation, and the simulation results were compared with the test results. The results indicate that the hysteresis curves and skeleton curves obtained from the numerical simulation agree well with the experimental curves, which verifies the rationality of the numerical simulation model proposed in this paper; post-peak load behavior reveals a pronounced compound confinement effect attributable to the five-spiral stirrups; during mid-to-late loading stages, the tensile stress in small spiral stirrups at intersections with larger spirals escalates rapidly, resulting in maximum transverse confinement within these areas. Based on the validated numerical simulation approach, a comprehensive analysis was performed to investigate the effects of axial compression ratio, shear-span ratio, spacing of small spiral stirrups, and diameter ratio of large-to-small spiral stirrups on the seismic performance of the specimens. The results demonstrate that when the spacing of large and small spiral stirrups is kept consistent, the specimens yield optimal strength and ductility. With the diameter of the central large-spiral stirrup fixed, either an increase or a decrease in the diameter of small spiral stirrups will induce varying degrees of reduction in both strength and ductility of the specimens. Furthermore, the five-spiral reinforced columns achieve the best overall seismic performance when the diameter of the central large spiral stirrup reaches the maximum allowable value for the cross-section, and the diameter of small spiral stirrups is set to one-third that of the large spiral stirrup. Finally, the shear mechanism and influencing factors of the shear capacity of the concrete square columns confined with five-spiral composite stirrups were discussed, and a practical formula for calculating the shear capacity of such columns was proposed. Full article

To address the challenges of interdependent design parameters and reliance on empirical trial-and-error in ultrasonic cell levitation culture devices, this study proposes a top-down design framework integrating multi-physics modeling with complex network analysis. First, acoustic field simulations optimize transducer arrangement and define the cell manipulation field, establishing the Top-level Basic Structure (TBS). A skeleton model of the acoustofluidic coupled field is constructed based on the TBS. Core parameters are then determined by refining the TBS through multi-physics analysis. Second, a 24-node design change propagation network is constructed. Leveraging the TBS model coupled with multi-physics fields, a directed network model analyzes parameter interactions. The HITS algorithm is applied to prioritize the design sequence based on authority and hub scores, resolving parameter conflicts. Experimental validation demonstrates a device acoustic pressure of 1.3 × 10⁴ Pa, stable cell levitation within the focused acoustic field, and a 40% reduction in design cycle time compared to traditional methods. This framework systematically sequences parameters, effectively determines the design order, enhances design efficiency, and significantly reduces dependence on empirical trial-and-error. It provides a novel approach for developing high-throughput organoid culture equipment. Full article

Second-order derivative information, including mixed curvature, is central to Newton and trust-region optimization, uncertainty quantification, and simulation-based design. Classical finite differences (FD) remain popular but require delicate step-size tuning and can suffer from cancelation and noise amplification. Complex-step differentiation offers machine-precision gradients without subtractive cancelation, yet many second-derivative complex-step formulas reintroduce differencing. Hyper-dual numbers provide an algebraically principled alternative: by lifting real code to a four-component commutative nilpotent algebra, one obtains exact first and mixed second derivatives from a single evaluation, without finite differencing. This article gives a consolidated theoretical and experimental foundation for hyper-dual numbers. We formalize the algebra, prove exact Taylor truncation at second order, derive coefficient–extraction formulas for gradients and Hessians, and state assumptions for exactness, including limitations at non-smooth points and the need to branch on real parts. We present implementation patterns and language skeletons (C++, Python 3.11.5, MATLAB R2023b), and we provide fair numerical comparisons with FD, complex-step, and AD baselines. Stability tests under additive noise and ill-conditioning, together with runtime and memory profiling, demonstrate that hyper-dual coefficients are robust and reproducible in floating-point arithmetic, particularly for black-box codes where Hessian information is needed but differencing is fragile. Full article

For unmanned aerial vehicle (UAV) ground crew marshalling tasks, the accuracy of skeleton-based action recognition is often limited by the high similarity of motion patterns across action categories as well as variations in individual performance. To address this issue, we propose an adaptive refined graph convolutional network with enhanced features for action recognition. First, a multi-order and motion feature modeling module is constructed, which integrates joint positions, skeletal structures, and angular encodings for multi-granularity representation. Static-domain and dynamic-domain features are then fused to enhance the diversity and expressiveness of the input representations. Second, a data-driven adaptive graph convolution module is designed, where inter-joint interactions are dynamically modeled through a learnable topology. Furthermore, an adaptive refinement feature activation mechanism is introduced to optimize information flow between nodes, enabling fine-grained modeling of skeletal spatial information. Finally, a frame-index semantic temporal modeling module is incorporated, where joint-type semantics and frame-index semantics are introduced in the spatial and temporal dimensions, respectively, to capture the temporal evolution of actions and comprehensively exploit spatio-temporal semantic correlations. On the NTU-RGB+D 60 and NTU-RGB+D 120 benchmark datasets, the proposed method achieves accuracies of 89.4% and 94.2% under X-Sub and X-View settings, respectively, as well as 81.7% and 83.3% on the respective benchmarks. On the self-constructed UAV Airfield Ground Crew Dataset, the proposed method attains accuracies of 90.71% and 96.09% under X-Sub and HO settings, respectively. Environmental robustness experiments demonstrate that under complex environmental conditions including illumination variations, haze, rain, shadows, and occlusions, the adoption of the Test + Train strategy reduces the maximum performance degradation from 3.1 percentage points to within 1 percentage point. Real-time performance testing shows that the system achieves an end-to-end inference latency of 24.5 ms (40.8 FPS) on the edge device NVIDIA Jetson Xavier NX, meeting real-time processing requirements and validating the efficiency and practicality of the proposed method on edge computing platforms. Full article

Physical therapy is a critical component of medical rehabilitation, aiding recovery from conditions such as stroke, spinal cord injuries, and musculoskeletal disorders. Effective rehabilitation requires precise monitoring of patient performance to ensure exercises are executed correctly and progress is accurately assessed. This paper presents a novel automated system for controlling the rehabilitation process and evaluating physical therapy exercise quality using computer vision and a customized Human Skeleton-based Balanced Time Warping algorithm. The proposed method quantitatively assesses the similarity between a physiotherapist and patient performance by analyzing skeletal motion data extracted from RGB-D video sequences without requiring pre-alignment or sensor-specific calibration. A motion-dependent, weighted Euclidean distance between 3D skeletal models is used to compute pose dissimilarity, while a modified DTW approach aligns temporal sequences and evaluates dynamic consistency. The total dissimilarity measure is a balanced combination of posture (DP) and dynamics (DT) components. Evaluated on a custom dataset of 136 video recordings from 23 participants performing exercises in sitting and standing positions under varying performance accuracy levels (“good,” “intermediate,” and “bad”), the system demonstrates the strong clustering of accuracy levels. Proposed dissimilarity, together with a fixed reference element (physiotherapist), induces a natural non-strict order on the set of distances between patients and physiotherapists. A high value of Spearman’s rank correlation coefficient between computed dissimilarity and execution accuracy (0.977) indicates that this method is suitable for assessing exercise performance accuracy and for adequately evaluating the patient’s rehabilitation progress. The method enables objective, real-time feedback, reduces therapist workload, and supports remote monitoring, offering a scalable solution for personalized rehabilitation. Future work will involve clinical validation with post-stroke and cardiac patients. Full article

Conventional two-dimensional (2D) electrocatalytic ozonation faces challenges such as low mass transfer efficiency, limited hydroxyl radical (•OH) yield, and insufficient pollutant degradation rates. To address these limitations, this study developed a novel three-dimensional electrocatalytic ozonation system using a 316 stainless-steel skeleton as the cathode. By systematically comparing the ozone decay kinetics, •OH yield, imidacloprid degradation efficiency, and ozone mass transfer characteristics among the 3D electrocatalytic ozonation system, 2D electrocatalytic ozonation system, and conventional ozonation system, combined with electrode interface reaction analysis and structural simulation, the core mechanism by which the 3D structure enhances the electrocatalytic ozonation reaction was revealed. The results showed that the 3D electrocatalytic ozonation technology primarily promotes ozone decay and •OH generation through a reaction pathway dominated by the reduction of ozone at the cathode, while simultaneously enhancing pollutant removal efficiency. The pseudo-first-order kinetic constant for ozone decay in the 3D system reached 1.0 min⁻¹, which was five times that of the 2D system (0.2 min⁻¹). The •OH yield increased to 38%, significantly higher than that of the 2D system (15%) and conventional ozonation (10%). The complete degradation of imidacloprid was achieved within 5 min, and the degradation rate (2.14 min⁻¹) was 10 times that of the 2D system. The high specific surface area (75 cm²/g, 30–90 times that of the 2D flat electrode) and 70% porosity of the 3D framework overcame the mass transfer limitation of the 2D structure, exhibiting excellent reaction activity. The ozone mass transfer amount was approximately 1.5 times that of the 2D electrode and 2 times that of conventional ozonation. This study provides theoretical support and technical basis for the engineering application of 3D electrocatalytic ozonation technology in the field of micro-pollutant control. Full article

Background/Objectives: This proof-of-concept study evaluated whether optical coherence tomography angiography (OCTA) can non-invasively capture micro-vascular alterations in non-melanoma skin cancer (NMSC) lesions during and after superficial orthovoltage radiotherapy (RT) using radiomics and vascular features analysis. Methods: Eight patients (13 NMSC lesions) received 36–50 Gy in 6–20 fractions. High-resolution swept-source OCTA volumes (1.1 × 10 × 10 mm³) were acquired from each lesion at three time points: pre-RT, immediately post-RT, and three months post-RT. Additionally, healthy skin baseline was scanned. After artifact suppression and region-of-interest cropping, (i) first-order and texture radiomics and (ii) skeleton-based vascular features were extracted. Selected features after LASSO (least absolute shrinkage and selection operator) were explored with principal-component analysis. An XGBoost model was trained to classify time points with 100 bootstrap out-of-bag validations. Kruskal–Wallis tests with Benjamini–Hochberg correction assessed longitudinal changes in the 20 most influential features. Results: Sixty-one OCTA volumes were analyzable. LASSO retained 47 of 103 features. The first two principal components explained 63% of the variance, revealing a visible drift of lesions from pre- to three-month post-RT clusters. XGBoost achieved a macro-averaged AUC of 0.68 ± 0.07. Six features (3 texture, 2 first order, 1 vascular) changed significantly across time points (adjusted p < 0.05), indicating dose-dependent reductions in signal heterogeneity and micro-vascular complexity as early as treatment completion, which deepened by three months. Conclusions: OCTA-derived radiomic and vascular signatures tracked RT-induced micro-vascular remodeling in NMSC. The approach is entirely non-invasive, label-free, and feasible at the point of care. As an exploratory proof-of-concept, this study helps to refine scanning and analysis protocols and generates knowledge to support future integration of OCTA into adaptive skin-cancer radiotherapy workflows. Full article

This paper provides a perspective on the use of RGB-D cameras and non-invasive brain–computer interfaces (BCIs) for human activity recognition (HAR). Then, it explores the potential of integrating both the technologies for active and assisted living. RGB-D cameras can offer monitoring of users in their living environments, preserving their privacy in human activity recognition through depth images and skeleton tracking. Concurrently, non-invasive BCIs can provide access to intent and control of users by decoding neural signals. The synergy between these technologies may allow holistic understanding of both physical context and cognitive state of users, to enhance personalized assistance inside smart homes. The successful deployment in integrating the two technologies needs addressing critical technical hurdles, including computational demands for real-time multi-modal data processing, and user acceptance challenges related to data privacy, security, and BCI illiteracy. Continued interdisciplinary research is essential to realize the full potential of RGB-D cameras and BCIs as AAL solutions, in order to improve the quality of life for independent or impaired people. Full article

Sign language is a visual language articulated through body movements. Existing approaches predominantly leverage RGB inputs, incurring substantial computational overhead and remaining susceptible to interference from foreground and background noise. A second fundamental challenge lies in accurately modeling the nonlinear temporal dynamics and inherent asynchrony across body parts that characterize sign language sequences. To address these challenges, we propose a novel part-wise graph Fourier learning method for skeleton-based continuous sign language recognition (PGF-SLR), which uniformly models the spatiotemporal relations of multiple body parts in a globally ordered yet locally unordered manner. Specifically, different parts within different time steps are treated as nodes, while the frequency domain attention between parts is treated as edges to construct a part-level Fourier fully connected graph. This enables the graph Fourier learning module to jointly capture spatiotemporal dependencies in the frequency domain, while our adaptive frequency enhancement method further amplifies discriminative action features in a lightweight and robust fashion. Finally, a dual-branch action learning module featuring an auxiliary action prediction branch to assist the recognition branch is designed to enhance the understanding of sign language. Our experimental results show that the proposed PGF-SLR achieved relative improvements of 3.31%/3.70% and 2.81%/7.33% compared to SOTA methods on the dev/test sets of the PHOENIX14 and PHOENIX14-T datasets. It also demonstrated highly competitive recognition performance on the CSL-Daily dataset, showcasing strong generalization while reducing computational costs in both offline and online settings. Full article

Inspired by naturally occurring bis-isochromans such as penicisteckins, we envisaged the first synthesis of biaryl-type bis-1-arylisochromans containing a stereogenic ortho-trisubstituted biaryl axis. We achieved the stereoselective synthesis of 5,5′-linked heterodimeric bis-isochromans containing both central and axial chirality elements by performing diastereoselective Suzuki–Miyaura biaryl coupling reactions on two optically active 1-arylpropan-2-ol derivatives, followed by two oxa-Pictet–Spengler cyclizations with aryl aldehydes or methoxymethyl chloride. We studied the diastereoselectivity of the cyclization step, separated the stereoisomeric products with chiral preparative HPLC and determined the absolute configuration through a combination of vibrational circular dichroism (VCD), NMR and single-crystal X-ray diffraction analysis. We demonstrated that different aryl groups could be introduced into the two isochroman subunits, since the dimethoxyaryl subunit reacted faster, enabling the two oxa-Pictet–Spengler cyclizations to be performed separately with different aryl aldehydes. We also explored the acid-catalyzed isomerization and oxidation to axially chiral ortho-quinones in order to produce stereoisomeric and oxidized analogs, respectively. We identified the antibacterial activity of our target bis-isochromans against Bacillus subtilis and Enterococcus faecalis with minimum inhibitory concentrations down to 4.0 and 0.5 μg/mL, respectively, which depend on the stereochemistry and substitution pattern of the bis-isochroman skeleton. Full article

The widespread emergence of resistant pathogenic microorganisms are diminishing the effectiveness of existing antimicrobial drugs, posing an enormous threat to global public health. This phenomenon, known as antimicrobial resistance (AMR), is primarily driven by the misuse and overuse of antimicrobial drugs. Natural product researchers around the globe, in response to antibiotics resistance, are searching for new antimicrobial lead compounds from unexplored or underexplored ecological niches such as the marine environment. In order to isolate new antimicrobial lead compounds, two Streptomyces spp. were isolated from marine sediment samples by a serial dilution technique and subsequently cultured in modified Bennett’s broth medium. Repeated chromatographic steps of ethyl acetate (EtOAc) extracts obtained from the culture broth led to the isolation of a new compound with an unusual chemical skeleton, streptopiperithiazol (1), and a synthetically known (2) compound. These compounds were characterized by the extensive analysis of 1D and 2D spectroscopic as well as HRMS data. The absolute configuration of 1 was unresolved due to limited yield and lack of proper facilities for taking CD and ECD spectra. In vitro activity study of compounds 1 and 2 revealed that these compounds had better activity against Gram-positive bacteria than Gram-negative bacteria and yeast. Full article

Background: Positive identification is at the forefront of tasks for forensic practitioners when a set of remains is discovered. Standard means of identification include fingerprints, dental, and DNA analyses; however, additional methods are utilized by forensic practitioners to identify remains when these primary methods of identification are not applicable. Comparative radiography has become a frequently employed approach for positive identification, specifically focused on individualizing characteristics evident in human skeletal variation. Regions that display wide ranges of morphological variation within the human skeleton include the cranium as well as the thorax. With regard to the cranium specifically, paranasal sinuses have been recognized as unique features and are valuable for identification purposes. Objectives: This paper explores the basic information of the anatomy and development, range of variation, and the importance of paranasal sinuses in forensic contexts. Results: This article discusses how practitioners can best use the morphological information contained in the paranasal sinuses and how to compare the antemortem and postmortem datasets involving different imaging modalities for positive identification purposes, in order to provide practical concepts that may assist in cases where paranasal sinuses may be used for forensic human identification. Conclusions: Understanding the development of paranasal sinuses, the imaging techniques applied for their visualization, as well as the principles of identification, is key to conducting proper antemortem vs. postmortem comparisons and effectively utilizing paranasal sinuses in forensic identification contexts. Full article

Melamine sponges have demonstrated significant application potential in the field of adsorption materials due to their unique three-dimensional porous network structure, excellent chemical/mechanical stability, and abundant amino active sites on the surface. However, the development of modified melamine sponges with efficient Congo red dye removal capabilities remains a substantial challenge. In this study, a stable linear polymer network structure was constructed on the surface of melamine sponges via an in situ polymerization strategy based on the Schiff base reaction mechanism. Characterization analyses reveal that the modified sponge not only retained the original porous skeleton structure but also significantly enhanced the density of surface active sites. Experimental data demonstrate that the modified sponge exhibited excellent adsorption performance for Congo red dye, with the adsorption process conforming to the pseudo-second-order kinetic model and achieving a practical maximum adsorption capacity of 380.4 mg/g. Notably, the material also displayed favorable cyclic stability. This study provides an efficient adsorbent for Congo red dye-contaminated wastewater treatment through the development of a novel surface-functionalized sponge material while also offering new solutions for advancing the practical applications of melamine-based porous materials and environmental remediation technologies. Full article

Coprolites from the Oligocene Menilite Formation of the Outer Carpathians in southeastern Poland were investigated to reveal the diversity of prey fishes consumed by coprolite producers. The material comprises 186 coprolites from seven localities. The coprolites are either sub-spherical, or elongate, and although classified into eight shape categories, display a morphological continuum. The phosphatic matrix is preserved in 28% of the specimens. Fish remains, including bones and scales, are preserved in 94% of the coprolite specimens. In 31% of specimens, these remains belong to the orders Perciformes, Gadiformes, Clupeiformes, and Aulopiformes. Prey sizes were estimated and compared to the sizes of fishes preserved as articulated skeletons from the same formation, that inhabited the Carpathian Basin of the Paratethys. The results demonstrate that coprolite analysis provides a significant paleontological data, which can be applied to infer fish diversity in other regions of the Paratethys, as well as in other sedimentary basins. Full article