Search Results (344)

Stroke is a major cause of lower-limb paresis, and clinical practice has long shown that early, repetitive gait training can accelerate motor recovery. End-effector gait trainers mounted on a wheeled walker provide a portable and low-cost alternative to bulky treadmill-based exoskeletons. This paper presents a geared five-bar linkage as the trajectory-generating mechanism of a Walker Gait Trainer (WGT), a single-actuator rehabilitation device for over-ground use. The two cranks of the five-bar linkage are linked by a gear train made up of two identical spur gears and an intermediate idler. This arrangement reduces the dimensional synthesis problem from four defect constraints, Grashof, order, and two circuit constraints, to a single order constraint, because branch and circuit defects are removed by design when both cranks are compelled to rotate continuously. Dimensional synthesis is formulated as a path-generation problem based on seven precision points obtained from normative gait data, and the mechanism dimensions are found through a systematic design-by-analysis search carried out interactively in the GIM kinematic simulation environment, using the closed-form kinematic model developed in this study. The final mechanism is then reconstructed in GIM as a kinematic cross-check of the closed-form model. The geared five-bar linkage reproduces the typical teardrop ankle path of healthy gait with one fewer link than conventional six-bar designs, while also adding the gear ratio as an extra parameter for shaping the trajectory, which is not available in six-bar topologies. The paper also presents the full device integration, in which the input crank is powered by a single speed-controlled actuator mounted on the walker frame, together with a three-dimensional CAD assembly model. Full article

Non-covalent forces are the primary drivers of biomolecular interactions. They also represent a key factor in the unexpected tendency for proteins, peptides, and even individual amino acids to self-assemble into precise supramolecular assemblies, often characterized by a β-rich, amyloid-like structure. Studies carried out in the last few decades have shown that peptides/proteins self-assembly not only has structural consequences but also generates spectroscopic properties whose origin remains debated. Here, we investigated the spectroscopic properties of four peptides, GAIIGL, NNQQ, SSTSAA, and GNNQQNG (a derivative of the frequently studied GNNQQNY peptide), devoid of aromatic residues, whose crystallographic characterization has been seminal in elucidating the basis of the aggregation process. The spectroscopic behavior of these peptides was analyzed in two different media and in the solid state, highlighting the conditions that favor UV–visible fluorescence emission. These investigations have also prompted the use of this fluorescence as a potential diagnostic tool in nanomedicine. Importantly, the identification of intrinsic fluorescence signatures in these amyloid-like assemblies may support the development of label-free optical approaches for the early detection and monitoring of aggregation-related pathological processes. For all peptides, the emitted fluorescence spans a rather wide range of wavelengths. Although centered in the blue region, a significant signal is also observed in the green region, independent of their physical state. The structural analysis of the solid used to collect the spectroscopic data reveals features related to the packings in the crystal state. This observation suggests that their three-dimensional crystal structures may serve as reliable models for studies aimed at correlating structural and spectroscopic features. Full article

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, formin-associated assemblies, cofilin severing complexes, and Rho-family GTPase modules. Mapping interactors to the CORUM database revealed clustering within actin nucleation, polymerization, and severing complexes, indicating that US3 operates through organized cellular machines. Machine-learning classifiers trained on label-independent mass-spectrometry features were used to prioritize interactors resembling known actin regulators; under protein-group-aware cross-validation, logistic regression performed best (average precision 0.24; ROC-AUC 0.66), and the analysis was interpreted as prioritization rather than de novo discovery. Pharmacological inhibition of Arp2/3 and formin pathways significantly attenuated US3-dependent F-actin remodeling, supporting the functional involvement of these pathways. Together, these findings are consistent with an inferred hierarchical axis in which US3 modulates Rho GTPase signaling and cofilin activation to promote F-actin disassembly, coordinating cytoskeletal remodeling required for efficient viral egress and spread. Full article

We formulate and analyze a 26-dimensional nonlinear dynamical system governing a doubly-fed induction generator (DFIG) wind energy conversion system coupled to an infinite bus through a dynamic transmission line. Seven interacting subsystems—aerodynamics, a two-mass drivetrain, a fourth-order machine, rotor- and grid-side converter controllers, a phase-locked loop, and a pitch regulator—are assembled into a single vector field $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x},\mathbf{u})$ on ${\mathbb{R}}^{26}$, derived in dimensionless coordinates. Strict positivity of the determinant $\mathrm{\Delta }=L_s{L}_r-L_m^2=\sigma L_s{L}_r$ for every physically admissible machine renders the flux–current map invertible, so the right-hand side is well defined; the nodal Kirchhoff constraint forms a semi-explicit differential-algebraic relation that we eliminate to obtain an explicit ordinary differential equation. The central contribution is a constructive scheme for the equilibria: the 26 stationarity conditions $\mathbf{f}({\mathbf{x}}^{\star },\mathbf{u})=\mathbf{0}$ are solved by an iterative voltage-matching procedure converging to a residual below ${10}^{-11}$ per unit—essentially machine precision—which removes the spurious start-up transients common in reported simulations. Analytically chosen feedback gains induce a hierarchy of well-separated time scales, placing the closed loop in the multiple-time-scale class; the separation is made quantitative through explicit small parameters ${\epsilon }_i$ formed from the ratios of subsystem time constants. Numerical integration of a GE $3.6$ MW configuration confirms the construction: under stationary forcing, the rotor speed stays within $1.32\times {10}^{-5}$ pu of the equilibrium, and under a large-amplitude wind program ($11\to 14\to 9$ m/s) spanning the full operating envelope, it is regulated to within $0.065\%$, while the DC-link voltage deviation remains below $2.4\times {10}^{-5}$ pu and the power balance closes with residual below ${10}^{-3}$ pu, the ≈2% mechanical–electrical gap being the modeled losses. Linearization about the computed equilibrium yields a Jacobian whose spectrum lies entirely in the open left half-plane, establishing local asymptotic stability and exposing the individual electromagnetic, torsional, and control modes. The model furnishes a rigorously initialized, analytically transparent basis for linearization, spectral stability analysis, and bifurcation study. Its practical value is that a consistent equilibrium and a certified spectrum remove the start-up transients and undocumented tuning that otherwise let initialization artifacts masquerade as genuine dynamics, so that the model can serve as a trustworthy building block for weak-grid and wind-farm stability studies. Full article

Sustainable hydroponic strawberry cultivation requires precise, real-time management of nutrient solutions to reduce waste and improve resource efficiency for home growers. This work presents an artificial neural network (ANN)-based system that estimates and approximates optimal nutrient formulations for strawberry hydroponics, with a primary focus on nutrient and water savings. The ANN-based system is implemented on hardware for real-time operation and was compared against a traditional PID controller to evaluate performance in nutrient solution management. The ANN receives temperature, humidity, water pH, nutrient concentrations, and lighting as inputs and outputs recommended nutrient solution parameters. Training used gradient descent and reached convergence after an average of 2500 epochs, achieving a mean error of 0.001 and an operating frequency of 84 MHz. Mechanical design was optimized for compact 3D-printable assembly to facilitate adoption by small-scale and domestic producers. The validation with 15 min sampling demonstrated the ability of the system to maintain target nutrient conditions, producing measurable increases in seedling and fruit weight and size while substantially reducing water and nutrient waste. These results indicate that ANN-driven, real-time nutrient estimation can make precision hydroponics more accessible and sustainable for home growers. In the comparative analysis, the ANN-based system demonstrated superior performance compared to the PID controller in maintaining precise nutrient concentrations and reducing resource waste, achieving more accurate tracking of target nutrient levels. Full article

The assembly quality of scaffolding systems directly governs the safety of personnel on construction sites. According to construction safety statistics, scaffolding-related accidents account for approximately 30–40% of construction fatalities globally, with geometric assembly deviations being a contributing factor in over 60% of scaffold collapse incidents. Traditional scaffolding inspections rely heavily on manual measurements, which are inherently inefficient, hazardous, and difficult to scale comprehensively. This study presents an automated evaluation framework that integrates computer vision with structural mechanics simulations. First, an object detection model based on the SegFormer encoder architecture is developed to precisely identify scaffolding standards, ledgers, and couplers against complex site backgrounds. Its hierarchical Transformer encoder and global self-attention mechanism enable the model to capture long-range topological relationships, achieving a mean Average Precision (mAP@0.5) of 95.2% on a custom dataset with an inference speed of 45 FPS per 640 × 640 image patch. For complete high-resolution frame processing including tiling and geometric extraction, the end-to-end pipeline requires approximately 8–12 s per frame. Second, a simplified Hough transform with a restricted parameter domain is introduced. Integrated with a dual-track image processing workflow, this algorithm performs sub-pixel centerline fitting to automatically extract critical geometric parameters, including lift height and bay width, maintaining a relative measurement error within 3.5% compared to manual ground truth. Finally, a parameterized finite element model is established. An automated mapping middleware dynamically injects the extracted as-built parameters into the simulation environment. Comparative simulation analysis indicates that a 14.7% deviation in standard lift height, coupled with an initial tilt defect of 1/150, precipitates a 22.4% reduction in the predicted structural stability factor, illustrating the framework’s capability for assessing relative capacity degradation between design intent and as-built conditions. This framework establishes a robust, closed-loop pipeline spanning visual perception and structural safety assessment, indicating potential for automated construction site safety management. Full article

To address the pervasive engineering challenges of rigid interference and subpar machining efficiency encountered during the complex freeform surface polishing of P20 mold steel, this study proposes and fabricates a structurally designed, five-petal composite compliant polishing tool via fused granulation fabrication (FGF). The tool structurally integrates a passive thermoplastic polyurethane (TPU) compliant buffer layer with an active PA66/diamond micro-cutting functional layer, achieving monolithic precision assembly through dual-temperature-zone 3D printing. Tensile mechanical characterization (n = 6) reveals that the composite interface attains an average ultimate tensile strength (UTS) of 59.39 ± 15.41 MPa (with a peak of 78.90 MPa) and an average elongation at break of 27.42 ± 7.41%, demonstrating exceptional structural robustness and fracture toughness under heavy-load abrasive machining conditions. During adaptive polishing validations on complex convex topographies and deep concave mold cavities, the compliant tool effectively compensated for normal vector spatial errors intrinsic to three-axis CNC machining via passive geometric adaptation. Topographical evaluations suggest a ductile-regime, differential asperity planarization material removal paradigm, which is attributed to the macroscopic 3D elastic deformation of the tool synergized with the proposed compliance of the polymer matrix. Following high-intensity sequential polishing regimens, the original macroscopic milling striations were substantially reduced. Quantitative profilometric analysis reveals that the average surface roughness of the convex profiles decreased from an initial 13.33 µm to 7.42 µm, while that of the restrictive deep concave features was reduced from 10.84 µm to 4.11 µm. Ultimately, this technological framework circumvents the traditional reliance on capital-intensive, six-degree-of-freedom robotic platforms, providing a scalable automated polishing protocol compatible with standard CNC systems for the cost-effective surface planarization of precision molds. Full article

Recent advances in circular economy strategies have accelerated the development of low-cost electrochemical systems for energy harvesting, and resource reutilization in intelligent Wireless Sensor Networks (WSNs). This study proposes a zinc–copper (Zn–Cu) galvanic cell platform for copper reuse and evaluates the residual solution as a potential sustainable plant micronutrient source within a conceptual framework for edge-enabled precision agriculture. A five-cell Zn–Cu galvanic assembly was electrochemically characterized, producing a cumulative open-circuit voltage of 5.286 V (~1.10 V per cell), consistent with theoretical redox behavior. The system (180.6 g total mass) exhibited a specific power and specific energy of 0.0114 W kg⁻¹ and 0.0114 Wh kg⁻¹, respectively, indicating its potential as a low-power energy source for future WSN and edge-computing applications. The residual copper solution was diluted and applied to Rosmarinus officinalis at graded concentrations. Image-based phenotyping revealed a concentration-dependent response, with the 50 mg L⁻¹ treatment producing the strongest improvement in vegetation indices, including excess green index, vegetative index difference, normalized green-red difference index, triangular greenness index, and color index of vegetation extraction. Multivariate analysis confirmed clear treatment separation driven primarily by spectral traits. Overall, the results demonstrate that the residual copper-containing electrolyte solution left after galvanic cell operation might serve as a potential micronutrient source, while highlighting the prospective integration of galvanic energy harvesting into future intelligent WSN-based precision agriculture systems. Full article

This study presents a comprehensive analysis of the modeling and optimization of sensor installation nodes for weight measurement in the hoppers of a charging car utilized in coke production. The research highlights the critical role of precise load monitoring in preventing technological disruptions, minimizing equipment degradation, and optimizing energy consumption. Conventional sensor technologies, including capacitive, ultrasonic, and laser-based systems, are evaluated, with weight sensors mounted on hopper supports identified as the most robust solution for real-time mass determination under industrial conditions characterized by high dust levels, temperature fluctuations, and mechanical vibrations. A finite element analysis (FEA) was conducted to assess the structural behavior of sensor installation nodes under three distinct loading scenarios, corresponding to different operational conditions of the charging car. The four-point support structure of the hopper experienced the highest loads and non-uniformities. A stress–strain analysis of the sensor mounting assembly, performed using the Ansys software package, confirmed that both the sensor and its support structure maintain a sufficient safety margin (version 2024 R1, Ansys Inc., Canonsburg, PA, USA, the academic license provided to Wrocław University of Science and Technology). The findings validate the structural integrity and operational reliability of the proposed sensor configuration, contributing to the advancement of automated monitoring and control systems in coke production. Full article

Shared bikes are frequently parked in disorder, resulting in low efficiency of manual collection and transfer and heavy workload for maintenance staff. Random parking across various areas forces shared bikes to occupy sidewalks and fire exits, damaging urban landscapes and disrupting traffic order. To tackle these industrial pain points, this paper develops an integrated intelligent robot system equipped with functions of multi-pose grasping, automatic transfer and fixed-point delivery of shared bikes, which can effectively address the drawbacks of low efficiency and high labor costs in traditional manual maintenance. This paper focuses on the completion of the robot’s overall mechanical structure design, stiffness–precision collaborative optimization model construction, finite-element static simulation verification, 1:7 scaled prototype development and performance testing. Firstly, the overall layout design of the multi-posture adaptive floating clamping mechanism, transfer-bearing frame, and Mecanum wheel omnidirectional mobile chassis is completed, and the structural parameters and assembly benchmarks of the core components are clarified. Secondly, a stiffness–precision coupling optimization model is established, and the static analysis under extreme load conditions is carried out through Abaqus finite-element software, which verifies the rationality of 45# carbon steel material selection and the safety of structural strength. Subsequently, a 1:7 scaled principle prototype is developed, and repetitive grabbing and transfer tests are carried out to verify the system operation feasibility, stability and grabbing accuracy. Finally, the statistical analysis of the test data and the horizontal comparison of similar schemes are completed. The test and simulation results show that the maximum stress of the system under extreme working conditions is 131.21 MPa, which is far lower than the allowable stress of 355 MPa of 45# steel, and the safety factor reaches 2.71. The maximum total deformation is 4.0552 mm, which is concentrated at the end of the front-end clamping mechanism, and is within the allowable stiffness deviation range of the transfer system. The average value of the single clamping positioning error of the scaled prototype is 0.476 mm, with a 95% confidence interval of 0.457–0.495 mm, which is converted to a positioning error of ≤3.4 mm for the full-scale prototype, which is far better than similar industry solutions. The average time of a single complete grabbing and transfer operation is 12.38 s, which is more than 45% higher than the traditional manual mode. The structural design, grabbing accuracy and operation stability of the robot designed in this paper all meet the requirements of actual working conditions of urban sidewalks, which can effectively reduce the intensity of manual labor and improve the operation and maintenance efficiency of shared bicycles. It has strong engineering application value and can provide reference for the design and manufacturing of intelligent collection and transfer systems for shared two-wheelers. Full article

Purpose—The flexspline of a harmonic drive constitutes a thin-walled structure with discontinuous gear rim and cylinder configuration, where cyclic stresses induce stress concentration, followed by crack initiation, propagation, and ultimately fatigue failure. This paper reviews advancements in understanding its mechanical properties and fatigue failure mechanisms, aiming to establish a foundation for enhancing operational longevity and guiding future research. Design/Methodology/Approach—The study integrates meshing theory, tooth shape parameters, cylinder stress influencers, and assembly/meshing stress considerations. Theoretical analysis, finite element simulations, and experimental methods are employed to examine stress patterns and fatigue dynamics. Structural parameters and tooth profiles are systematically analyzed for their impact on stress distribution and fatigue life. Findings—Flexspline fatigue failure arises from tooth root stress concentration and cylinder bending stress accumulation. The double-circular-arc tooth profile boosts load capacity by 35% relative to the involute profile, yet demands high-precision machining to preserve meshing performance. Increasing cylinder length mitigates stress concentration but reduces torsional stiffness, while optimized root fillet radii can lower the stress concentration coefficient by 28%. Assembly interference and meshing contact stress accelerate crack initiation, as validated by transient dynamics simulations. Surface strengthening processes (e.g., shot peening) enhance fatigue life by up to 66% through residual compressive stress regulation. Originality/Value—This paper synthesizes multi-scale research on flexspline design, structural optimization, and fatigue mechanisms, proposing novel approaches such as “manufacturability-oriented optimization” and digital twin-driven monitoring. By linking dynamic loads, material properties, and geometric parameters, it bridges theoretical gaps and provides actionable insights for high-precision harmonic drives in robotics and aerospace, advancing reliability in precision transmission systems. Full article

Designers, engineers, and building officials face increasing pressure to accelerate and improve the accuracy of design review for buildings and infrastructure. Roof assemblies and rooftop structures are particularly challenging due to the complexity and fragmentation of regulatory requirements, especially in jurisdictions such as Florida, where compliance must be verified across both the residential and commercial volumes of the Florida Building Code (FBC). The resulting review process is technically demanding and time-intensive, imposing significant cognitive and operational burdens on practitioners and under-resourced public agencies. To address these challenges, this study proposes and evaluates an agentic artificial intelligence (AI) framework for automated code compliance checking of roof assemblies and rooftop structures. The framework employs a multi-agent architecture in which specialized AI agents collaboratively interpret regulatory provisions and evaluate roof design parameters across four core modules: data preprocessing and code ingestion, rule-based and semantic analysis, results visualization, and iterative validation. YOLO11m-seg and Mask R-CNN were used for element detection and segmentation, and the system was developed using 150 design projects, including roof plans, section details, and specifications. Four large language models from two families (Mistral and GPT) were comparatively evaluated on standardized compliance tasks. The framework was then tested on a held-out portfolio of 15 distinct roof-design projects comprising 60 code-compliance decisions derived from the FBC 2023, with performance measured by precision, recall, F1-score, and accuracy. GPT-5.4 achieved the highest overall performance (F1 = 0.97; accuracy = 97%). Because the reasoning and vision components were evaluated separately rather than as an integrated end-to-end pipeline, and the scope was limited to one jurisdiction and two drawing types, broader code coverage and production-setting validation are needed before claims of generality. Nonetheless, the results suggest that agentic AI can meaningfully support compliance review and reduce reviewer burden in roof-design permitting. Full article

The exponential growth of AI-driven data traffic necessitates the evolution of Data Center Networks toward high bandwidths and sub-microsecond latency. While co-packaged optics (CPO) offer a pathway to reduced energy consumption and increased capacity, they introduce significant challenges in optical chip coupling and packaging complexity. This study explores monolithically integrated metasurfaces as an alternative for optical interfaces, potentially reducing the need for bulky external microlens arrays or extremely precise mechanical alignment. We design an amorphous silicon (a-Si) metasurface on a Silicon-On-Insulator (SOI) platform operating at 1310 nm. By spatially mapping nanopillar radii to satisfy a spherical phase profile, we achieved near-vertical beam emission with an emission angle of 0.88° focused at a focal length of 98.99 μm. Broadband characterization across a 20 nm band confirms stable focusing and a confined spot size with moderate roll-off toward the band edges. The sensitivity of the emission profile of the device to fabrication imperfections in pillar radius, height, and sidewall taper is quantified. The coupling to a polymer-based optical redistribution layer (ORDL) is also studied, and the corresponding modal analysis demonstrates a maximum coupling efficiency of 68.2% into an SU-8 polymer waveguide. Tolerance analysis results reveal deterioration of 0.9 dB and 0.4 dB for $\pm 0.6 \mathsf{\mu }\mathrm{m}$ horizontal and $\pm 1.5 \mathsf{\mu }\mathrm{m}$ vertical misalignment respectively, making the interface compatible with relaxed alignment assembly assumptions, although experimental packaging validation remains required. The methodology is further validated at 1550 nm, demonstrating its applicability across telecom bands. These results suggest that integrated metasurfaces may simplify the packaging stack and enhance density for next-generation CPO links by providing precise, on-chip wavefront manipulation. Full article

Knowledge of the biology of the genus Vitis has undergone a profound transformation, evolving from the morphological descriptions of classical ampelography to the high-resolution analyses enabled by modern phylogenomics. This review explores the “Paradox of the Vine”—the remarkable phenotypic plasticity that historically complicated botanical nomenclature—and examines how genomic tools have helped resolve many of these long-standing taxonomic challenges. We trace the development of grapevine genomics from the first near-homozygous reference genome (PN40024) to the current era of telomere-to-telomere (T2T) assemblies and phased diploid genomes. Attention is given to the genomic “dark matter” represented by transposable elements and structural variation, which contribute substantially to varietal identity and species-specific adaptation to changing environmental conditions. Advances in bioinformatic methodologies, including pangenome graph construction and machine learning-based variant detection, now enable clonal discrimination and complex parentage analysis with unprecedented precision. The definition of genuine wild grapevines (Vitis vinifera subsp. sylvestris) remains a critical issue in studies of grapevine evolution, domestication, and genome structure. The traditional concept of wild populations free from introgression by cultivated grapevines has been increasingly challenged by ecological observations and molecular evidence. Distinguishing truly wild populations from feral lineages is therefore essential for reconstructing the history of grapevine domestication and understanding patterns of gene flow between cultivated and wild compartments. Future progress in Vitis systematics will depend on the integration of genomic, ecological, and morphometric approaches. We propose that the next generation of grapevine taxonomy will combine the historical insights of ampelography with high-throughput phenotyping and comprehensive pangenomic resources, leading to a predictive and evolutionarily informed framework for the classification of Vitis species and cultivars. Full article

The increasing adoption of virtual reality for industrial tasks such as virtual assembly, inspection, and operator training necessitates a standardized approach for evaluating and selecting appropriate hardware. This paper addresses this need by introducing a comprehensive methodology to assess the usability of commercially widespread virtual reality headsets specifically for industrial applications with hand-held controllers. We conducted a large-scale comparative study involving five leading headsets (HTC VIVE Pro 1 and 2, HTC VIVE XR Elite, Meta Quest Pro, and Meta Quest 3) and 60 demographically balanced participants. The evaluation was based on a protocol of 15 distinct tasks designed to measure performance in near and far-field object manipulation, interaction fidelity, visual clarity, ergonomics, and long-term comfort. By combining quantitative Key Performance Indicators with subjective user feedback and rigorous inferential statistical analysis, our findings reveal significant performance disparities among the devices. The results demonstrate that, while certain headsets excel in high-precision tracking for assembly tasks, others offer superior comfort, visual quality, and ease of use for inspection and prolonged sessions. Ultimately, this study concludes that no single headset is universally superior; the optimal choice is highly task-dependent. The proposed methodology provides a robust, evidence-based framework to guide industries in making informed virtual reality hardware selections tailored to their specific needs. Full article