Search Results (6,295)

Background: Cancer poses a significant health risk to humans, with prostate cancer (PCa) being the second most common and deadly form among men, following lung cancer. Each year, it affects over a million individuals and presents substantial diagnostic challenges due to variations in tissue appearance and imaging quality. In recent decades, various techniques utilizing Magnetic Resonance Imaging (MRI) have been developed for identifying and classifying PCa. Accurate classification in MRI typically requires the integration of complementary feature types, such as deep semantic representations from Convolutional Neural Networks (CNNs) and handcrafted descriptors like Histogram of Oriented Gradients (HOG). Therefore, a more robust and discriminative feature integration strategy is crucial for enhancing computer-aided diagnosis performance. Objectives: This study aims to develop a multi-stage hybrid learning model that combines deep and handcrafted features, investigates various feature reduction and classification techniques, and improves diagnostic accuracy for prostate cancer using magnetic resonance imaging. Methods: The proposed framework integrates deep features extracted from convolutional architectures with handcrafted texture descriptors to capture both semantic and structural information. Multiple dimensionality reduction methods, including singular value decomposition (SVD), were evaluated to optimize the fused feature space. Several machine learning (ML) classifiers were benchmarked to identify the most effective diagnostic configuration. The overall framework was validated using k-fold cross-validation to ensure reliability and minimize evaluation bias. Results: Experimental results on the Transverse Plane Prostate (TPP) dataset for binary classification tasks showed that the hybrid model significantly outperformed individual deep or handcrafted approaches, achieving superior accuracy of 99.74%, specificity of 99.87%, precision of 99.87%, sensitivity of 99.61%, and F1-score of 99.74%. Conclusions: By combining complementary feature extraction, dimensionality reduction, and optimized classification, the proposed model offers a reliable and generalizable solution for prostate cancer diagnosis and demonstrates strong potential for integration into intelligent clinical decision-support systems. Full article

The reservoir computing approach based on a semiconductor laser with optoelectronic time-delay feedback is distinguished by its simplicity, speed, and reliability. However, the response of the reservoir to the input signal in this configuration is a superposition of the laser relaxation oscillations, which has limited complexity, which may therefore reduce computational performance when solving problems requiring high nonlinearity. We experimentally demonstrate a combination of postprocessing techniques that overcome this limitation through upsampling and state space expansion using a nonlinear transformation of nodal functions, and show how this results in an order-of-magnitude reduction in prediction error for the Santa Fe task. Full article

The advancement of polymeric materials for orthopedic applications has enabled the development of lightweight, adaptable structures that support patient-specific solutions. This study focuses on the design, fabrication, and mechanical characterization of additively manufactured (AM) polymeric polylactic acid (PLA) components produced via Material Extrusion (MEX), commonly known as Fused Filament Fabrication (FFF). By optimizing geometric configurations and process parameters, these structures demonstrate enhanced flexibility, energy absorption, and load distribution, making them well-suited for orthopedic products and assistive devices. A comprehensive mechanical testing campaign was conducted to evaluate the elasticity, ductility, and strength of FFF-fabricated samples under tensile and three-point bending loads. Key process parameters, including nozzle diameter, layer thickness, and printing orientation, were systematically varied, and their influence on mechanical performance was recorded. The results reveal that these parameters affect mechanical properties in a complex, interdependent manner. To better understand these relationships, an automated routine was developed to calculate the experimental mechanical response, specifically, stiffness and strength. This methodology enables an automated evaluation of the output, considering parameter ranges for future applications. The outcome of the analysis of variance (ANOVA ) of the experimental investigation reveals that the printing orientation has a strong impact on the mechanical anisotropy in FFF, while layer thickness and nozzle diameter demonstrate moderate-to-weak importance. Thereafter, the experimental findings were applied on an innovative orthopedic wrist splint design to be fabricated by means of FFF. The most suitable mechanical properties were selected to test the mechanical response of the designed components under operational bending loading by means of linear elastic finite element (FE) analysis. The computational results indicated the importance of employing the actual mechanical properties derived from the applied printing process parameters compared to data sheet values. Hereby, an additional parameter to adjust the mechanical response is the product’s design topology. Finally, this framework lays the foundation for future training of neural networks to optimize specific mechanical responses, reducing reliance on conventional trial-and-error processes and improving the balance between orthopedic product quality and manufacturing efficiency. Full article

Banana harvesting relies heavily on manual labor, which is labor-intensive and prone to fruit damage due to insufficient control of contact forces. This paper presents a systematic methodology for the design and optimization of adaptive flexible end-effectors for banana bunch harvesting, focusing on contact behavior and mechanical constraints. By integrating response surface methodology (RSM) with multi-objective genetic algorithm (MOGA) optimization, the relationships between finger geometry parameters and key performance metrics—contact area, contact stress, and radial stiffness—were quantified, and Pareto-optimal structural configurations were identified. Experimental and simulation results demonstrate that the optimized flexible fingers effectively improve handling performance: contact area increased by 13–28%, contact stress reduced by 45–56%, and radial stiffness enhanced by 193%, while the maximum shear stress on the fruit stalk decreased by 90%, ensuring harvesting stability during dynamic loading. The optimization effectively distributes contact pressure, minimizes fruit damage, and enhances grasping reliability. The proposed contact-behavior-constrained design framework enables passive adaptation to fruit morphology without complex sensors, offering a generalizable solution for soft robotic handling of fragile and irregular agricultural products. This work bridges the gap between bio-inspired gripper design and practical agricultural application, providing both theoretical insights and engineering guidance for automated, low-damage fruit harvesting systems. Full article

In order to improve the seismic performance of traditional precast lightweight walls, a new precast concrete wall with beam connection and embedded steel support is proposed in this study. Six 2/3-scale specimens were designed for a quasi-static cyclic loading test, and a numerical study was carried out. Key variables include shear span ratio (0.8–1.6), wall thickness (120–200 mm), concrete strength (C25–C40), and concealed column configuration. The experimental results reveal three distinct failure modes, specifically, brace buckling, weld fracture at the lower joints, and bolt shear failure. The system shows excellent ductility (displacement ductility coefficient μ = 3.2–4.1) and energy dissipation capacity (equivalent viscous damping ratio ξ = 0.28–0.35), and its performance is 30–40% higher than that of traditional reinforced concrete walls and close to that of steel plate shear walls. The shear span ratio is reduced by 50%, the shear bearing capacity is increased by 16%, but the peak displacement is halved, and the peak load of concealed column is increased by 57%. The finite element analysis verified the experimental trends and emphasized that the shear capacity can be increased by 12–18% by widening the steel brace (relative to thickening) under the condition of constant steel volume. The results demonstrate that BIM-driven design is very important for solving connection conflicts and ensuring constructability. Parameter research shows that when the concrete strength is greater than C30, the yield load increases by 15–20%, but the influence on the ultimate bearing capacity is minimal. These findings provide an operational guide for the implementation of high-performance prefabricated walls in earthquake-resistant steel structures, and balance the details of constructability through support, connection, and BIM. Full article

This paper provides a comprehensive review of the dynamic tensile behavior of concrete, focusing on its implications for seismic-resistant and impact-prone structures such as dams. The present work distinguishes itself in the following ways: providing the first comprehensive synthesis explicitly focused on large-aggregate dam concrete behavior across the seismic strain rate range (${10}^{-4}$ to ${10}^{-2}$ s${}^{-1}$), which is critical yet underrepresented in the existing literature; integrating recent experimental and numerical advances regarding moisture effects, load history, and cyclic loading—factors that are essential for dam safety assessments; and critically evaluating current design guidelines for concrete dams against state-of-the-art research to identify gaps between engineering practice and scientific evidence. Through the extensive synthesis of experimental data, numerical simulations, and existing guidelines, the study examines key factors influencing dynamic tensile strength, including strain rate effects, crack evolution, testing techniques, and material variables such as moisture content, load history, and aggregate size. Experimental results from spall tests, split Hopkinson pressure bar configurations, and cyclic loading protocols are analyzed, revealing dynamic increase factors ranging from 1.1 to over 12, depending on the strain rates, saturation levels, and preloading conditions. The roles of inertial effects, free water (via the Stefan effect), and microstructural heterogeneity in enhancing or diminishing tensile performance are critically evaluated. Numerical models, including finite element, discrete element, and peridynamic approaches, are discussed for their ability to simulate crack propagation, inertia-dominated responses, and moisture interactions. The review identifies and analyzes current design guidelines. Key conclusions emphasize the necessity of integrating moisture content, load history, and mesoscale heterogeneity into dynamic constitutive models, alongside standardized testing protocols to bridge gaps between laboratory data and real-world applications. The findings advocate for updated engineering guidelines that reflect recent advances in rate-dependent fracture mechanics and multi-scale modeling, ensuring safer and more resilient concrete infrastructure under extreme dynamic loads. Full article

Modeling elementary diffusion processes in nanostructured materials is essential for developing platforms capable of interacting with high-speed physical signals. In this work, the photothermal response of a nano-hydroxyapatite/carbon nanotube (nHAp/CNT) composite was experimentally characterized and modeled through a cellular automaton (CA) framework designed to capture the thermal propagation of the hybrid system. Synthesizing nHAp/CNT composites enables the combination of the biocompatible and piezoelectric nature of nHAp with the enhanced photothermal response introduced by CNTs. UV–Vis reflectance measurements confirmed that CNT incorporation increases the optical absorption of the ceramic matrix, resulting in more efficient photothermal conversion. The composite was irradiated with a nanosecond pulsed laser, and the resulting thermal transients were compared with CA simulations based on a D2Q9 lattice configuration. The model accurately reproduces experiments, achieving R² > 0.991 and NRMSE below 2.4% for all tested laser powers. This strong correspondence validates the CA approach for predicting spatiotemporal heat diffusion in heterogeneous nanostructured composites. Furthermore, the model revealed a sensitive thermal coupling when two heat sources were considered, indicating synergistic enhancement of local temperature fields. These findings demonstrate both the effective integration of CNTs within the nHAp matrix and the capability of CA-based modeling to describe their photothermal behavior. Overall, this study establishes a computational–experimental basis for designing controlled thermal-wave propagation and guiding future multi-frequency or multi-source photothermal mixing experiments. Full article

A decentralized DC power-exchange method is proposed to enable direct bidirectional power transfer among geographically distributed DC microgrids. Each microgrid is connected to a shared power-exchange grid via a bidirectional DC/DC converter, allowing for flexible participation regardless of location. The architecture supports dynamic scalability, permitting microgrids to join or leave the exchange network without disrupting overall operation. To evaluate the feasibility of the proposed method, a 2-to-2 power-exchange experiment was conducted using lithium-ion batteries configured to emulate microgrid baselines. The results demonstrated that arbitrary power ratios can be achieved through appropriate adjustment of converter parameters, and that transmission loss and efficiency varies depending on the power distribution ratio. In addition, the operational stability of the system was experimentally verified under sudden fluctuations in baseline voltage, such as those caused by abrupt changes in generation or load. Stable power exchange was maintained even under disturbances of several percent. These findings confirm the practicality and robustness of the converter-based architecture and highlight its applicability to scalable, distributed DC microgrid interconnection. Full article

This work presents a complete multi-serial adaptive bus interface system compatible with the most widely used industrial serial communications standards: RS-232, RS-485, RS-422, and CAN. The proposed system automatically detects the connected serial interface type through analog line sensors and dynamically redirects the bus to the appropriate transceiver using a logical multiplexer. This approach aims to simplify the configuration of heterogeneous serial devices in complex and modular integration scenarios, such as body builders in industrial or vehicular systems. The hardware is designed as a scalable PCIe card-based device, allowing multiple adaptive bus interfaces to be integrated within a rack-based modular architecture. In addition, a single 5-pin plug-and-play connector is proposed by unifying the different bus signals of the transceivers, thereby simplifying cabling and deployment. Complementary implemented capabilities include baud rate auto-detection and supervision, as well as automatic direction-control functionality for RS-485 communication. Experimental validation demonstrated that the proposed system successfully detected and redirected all supported interfaces, achieving reliable connection and disconnection within an average time of 2.5 s. Furthermore, the integrated baud rate auto-detection algorithm accurately identified transmission speeds up to 1 Mbps in under 80 ms, while the automatic direction-control capability operated reliably at speeds up to 576,000 bps. Full article

Enhancing the evaporator configuration of plate heat exchangers is essential for improving the overall efficiency of organic Rankine cycle (ORC) systems. To investigate the evaporator’s heat transfer characteristics, an experimental ORC test rig was developed. The experiments were conducted at saturation temperatures of 62.8–86.2 °C, mass fluxes of 5.0–16.6 kg/(m²·s), and heat fluxes of 3.1–9.2 kW/m², spanning subcooled boiling, saturated two-phase, and superheating regions. The heat flux showed minimal variation with heat source temperature, whereas higher mass fluxes resulted in substantial increases in generator power and thermal efficiency due to enhanced convection and vaporization. The overall and refrigerant heat transfer coefficients rise with heat source temperature and mass flux, peaking under moderate conditions and declining as the superheating region becomes constrained. Comparison with existing correlations reveals pronounced deviations, indicating their limited applicability under the present operating conditions. A nondimensional correlation was established using dimensional analysis and multivariate regression to predict heat transfer across the subcooled boiling, saturated two-phase, and superheating regions. The proposed correlation yielded a mean absolute percentage error of 15.9%, demonstrating good predictive accuracy and providing a reliable theoretical basis for performance evaluation and design optimization of plate evaporators in ORC systems. Full article

This paper presents an advanced signal processing framework for multi-channel forward-scatter radar (MC-FSR) systems based on the Multiple Signal Classification (MUSIC) algorithm. The proposed framework addresses the inherent limitations of FFT-based space-domain processing, such as limited angular resolution and the poor detectability of weak or closely spaced targets, which become particularly severe in low-cost FSR systems, which are typically operated with small antenna arrays. The MUSIC algorithm is adapted to operate on real-valued data obtained from the non-coherent, amplitude-based MC-FSR approach by reformulating the steering vectors and adjusting the degrees of freedom (DoFs). While compatible with arbitrary transmitting waveforms, particular emphasis is placed on Orthogonal Frequency Division Multiplexing (OFDM) signals, which are widely used in modern communication systems such as Wi-Fi and cellular networks. An analysis of the OFDM waveform’s autocorrelation properties is provided to assess their impact on target detection, including strategies to mitigate rapid target signature decay using a sub-band approach and to manage signal correlation through spatial smoothing. Simulation results, including multi-target scenarios under constrained array configurations, demonstrate that the proposed MUSIC-based approach significantly enhances angular resolution and enables reliable discrimination of closely spaced targets even with a limited number of receiving channels. Experimental validation using an S-band MC-FSR prototype implemented with software-defined radios (SDRs) and commercial Wi-Fi antennas, involving cooperative targets like people and drones, further confirms the effectiveness and practicality of the proposed method for real-world applications. Overall, the proposed MUSIC-based MC-FSR framework exhibits strong potential for implementation in low-cost, hardware-constrained environments and is particularly suited for emerging Integrated Sensing and Communication (ISAC) systems. Full article

Energy-dissipating braces are novel structural components as they not only accommodate the seismic energy demand but also enhance both the flexibility and overall earthquake resistance of the structure, preventing brittle or non-ductile behavior. The novel brace proposed in this study was developed to achieve two primary objectives: first, to restrict relative displacements at its ends by dissipating energy through U-shaped flexural plates (UFPs), and second, to provide a self-centering mechanism through the use of post-tension (PT) to ensure structural re-centering after cyclic loading. The novelty of this research lies in the experimental findings showing that post-tensioned (PT) braces exhibit a flag-shaped self-centering hysteretic response, improved initial stiffness, and reduced residual displacements by 72%, while non-PT braces behave as conventional metallic dissipators with larger residual displacements. Increasing UFP thickness from 6 to 8 mm enhances strength by 22%. Stainless steel UFPs offer superior plastic recovery, whereas regular steel UFPs dissipate ~%10 more energy through greater plasticity. Energy dissipation of the brace increases with increasing PT forces and displacement due to the PT force pulling the force–displacement curve towards high force levels. This study highlights the importance of PT force and UFP parameters in a brace configuration with self-centering and metallic dissipators such as U-shaped flexural plates. Full article

This paper presents an experimental and analytical investigation into the dominant noise generation mechanisms of unmanned Fixed-wing Vertical Take-Off and Landing (VTOL) propeller–wing configurations during takeoff. This paper reports the velocity measurements made in the close vicinity of a scale-model propeller adjacent to a flat plate or wing, aimed at understanding and characterising its dominant noise generation mechanisms. This paper identifies two main interaction mechanisms. The first is a purely acoustical phenomenon whereby the wing acts as an image source causing strong interference between the direct and image noise sources due to the propeller. The second is a significant noise increase resulting from the unsteady blade loading that occurs when the blade passes over the wing at lower vertical separation distances. Other, more minor noise sources from the propeller and the wing are also discussed in this paper. Full article

Bamboo has evolved a highly optimized structural system in its culms, which this study transfers into lightweight fiber composite trusses fabricated by coreless filament winding. Focusing on the structural segmentation involving diaphragms of the biological role model, this design principle was integrated into the additive manufacturing process using a multi-stage winding, a tiling approach, and a water-soluble winding fixture. Through a FE-assisted analytical abstraction procedure, the transition to a carbon fiber material system was considered by determining a geometrical configuration optimized for structural mass, bending deflection, and radial buckling. Samples were fabricated from CFRP and experimentally tested in four-point bending. In mass-specific terms, integrating diaphragms into wound fiber composite samples improved failure load by 36%, ultimate load by 62%, and energy absorption by a factor of 7, at a reduction of only 14% in stiffness. Benchmarking against steel and PVC demonstrated superior mass-specific performance, although mōsō bamboo still outperformed all technical solutions, except in energy absorption. Full article

Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with a single-mode DFOS cable incorporating internal anchors at 2 m intervals and bonded externally with structural epoxy. Brillouin time-domain analysis (BOTDA) provided distributed strain measurements at approximately 0.5 m spatial resolution, with all cables calibrated to ±15,000 µε. Under stepwise monotonic loading, the system captured smooth, repeatable strain baselines and clearly resolved localized tensile peaks associated with crack initiation and propagation. Long-gauge averages exhibited a near-linear load–strain response (R² ≈ 0.99) consistent with discrete foil and vibrating-wire strain gauges. Even after cracking, the DFOS signal remained continuous, while some discrete sensors showed saturation or scatter. Temperature compensation via a parallel fiber ensured thermally stable interpretation during load holds. The fixed-point configuration mitigated local debonding effects and yielded unbiased long-gauge strain data suitable for assessing serviceability and differential settlement. Overall, the results confirm the suitability of fixed-point DFOS as a durable, SHM-ready sensing approach for RC foundation elements and as a dense data source for emerging digital-twin frameworks. Full article