Search Results (2,647)

Multi-modal Magnetic Resonance Imaging (MRI) provides complementary information for clinical diagnosis, yet its large-scale storage, privacy sensitivity, and annotation cost pose significant challenges. Inspired by biological vision systems, which integrate multi-sensory inputs and compress experiences into compact memory representations, we propose a bio-inspired framework termed Contrast-Guided Multi-modal Dataset Distillation (CGMDD). In biological perception, different sensory channels observe the same environment from complementary perspectives, while hierarchical neural processing ensures perceptual consistency across modalities. Meanwhile, memory systems such as the associated medial temporal lobe structures consolidate redundant experiences into efficient representations for long-term storage. Motivated by these principles, CGMDD treats multi-modal MRI as multi-view perceptual signals and introduces a hierarchical cross-modal contrastive learning mechanism that enforces perceptual alignment across modalities, analogous to multi-level processing in the visual cortex. Furthermore, we design a dynamic dataset distillation strategy that mimics memory consolidation by compressing large-scale data into compact, informative synthetic representations through gradient-based optimization. The proposed framework jointly optimizes perceptual alignment and memory compression in an end-to-end manner, achieving a biologically plausible integration of perception and learning. Experimental results on two MRI datasets demonstrate that CGMDD can compress the original dataset to 5% of its size while maintaining competitive performance, even with only 30% of the labels. These findings highlight the effectiveness of bio-inspired mechanisms in building efficient, robust, and privacy-preserving computer vision systems. Full article

Recent advances in edge computing and Tiny Machine Learning (TinyML) have enabled the deployment of artificial intelligence models directly on microcontrollers with extremely limited computational and memory resources. In this context, this work presents the design, implementation, and validation of a real-time cardiac arrhythmia classification system based on a quantized one-dimensional convolutional neural network (1D-CNN), deployed on an 8-bit Arduino UNO microcontroller. The proposed system integrates end-to-end processing, including ECG signal acquisition using a low-cost AD8232 analog front-end, signal preprocessing, heartbeat segmentation, classification, and real-time visualization on an OLED display. The model was trained and evaluated using the MIT-BIH Arrhythmia Database, considering a reduced three-class problem (Normal, Ventricular, and Supraventricular) to meet the constraints of ultra-low-cost hardware deployment. Under benchmark conditions, the quantized model achieved an accuracy of 97.6%, with a memory footprint below 24 KB and an average inference time of 200 ms per heartbeat, enabling real-time operation on a resource-constrained microcontroller. Real-time experiments were conducted using signals acquired from healthy volunteers to validate system functionality, although no annotated ground truth was available for these recordings, and therefore no diagnostic performance was derived from them. The results demonstrate the feasibility of deploying lightweight deep learning models on ultra-constrained embedded systems using the TinyML paradigm, implemented using TensorFlow 2.15 and TensorFlow Lite. This work should be interpreted as a proof-of-concept platform that highlights the trade-off between classification performance and hardware limitations, providing a foundation for future development of low-cost cardiac monitoring technologies in resource-limited environments. Full article

Background/Objectives: The NETest is a blood-based, machine learning-enhanced multigene transcript assay designed to detect and monitor neuroendocrine tumors (NETs). This study evaluated the accuracy of the recently validated NETest2.0^® (2025) to (1) detect the presence of disease and (2) assess its utility as a clinically meaningful tool for monitoring NET status across diverse patient cohorts, including post-surgical surveillance, observation (“watch-and-wait”), and treatment settings. Methods: This registry study (NCT02270567) evaluated two objectives. For Objective 1, 1290 samples from 886 patients, of which 404 had paired follow-up samples, were analyzed for concordance between NETest2.0^® and imaging-detectable disease. For Objective 2, paired blood samples (n = 404; median interval 7 months [IQR 4–13.8]) from NET patients across specialized centers were assessed. NETest2.0^® scores were correlated with clinically adjudicated disease status using imaging as the comparator. Cohorts included post-surgical residual disease detection (n = 71), post-surgical recurrence monitoring (n = 44), observation (n = 72), and treatment monitoring (n = 217; somatostatin analogs, PRRT, and other therapies). Analyses were performed by cohort and in aggregate. Results: For Objective 1, NETest2.0^® (cut-off ≥ 50) demonstrated an AUC of 0.96, sensitivity of 91.9%, specificity of 94.9%, PPV of 98.4%, NPV of 77.1%, and overall accuracy of 92.5%. Performance was consistent across tumor grades and sites. For Objective 2, 286 patients (70.8%) were stable, and 118 (29.2%) had progression or recurrence. NETest2.0^® score changes correlated significantly with outcomes: scores decreased in stable patients (median −14.6%) and increased in progressive disease (median + 15.4%; p < 0.0001). Any increase (>0%) in score was associated with progression. Diagnostic performance for detecting progression reached a sensitivity of 78.0%, specificity of 98.3%, PPV of 91.1%, NPV of 90.2%, and accuracy of 83.9%. Conclusions: NETest2.0^® accurately detects disease and provides a clinically actionable tool for monitoring NETs. Its high specificity and predictive performance support risk-adapted surveillance, potentially reducing unnecessary imaging while identifying early progression across diverse clinical settings. Full article

This work presents a design technique for a type of recursive 2D filter, specifically anisotropic filters, with a frequency response depending on orientation. This design method is based on a 1D analog low-pass prototype filter of a specified approximation type (for instance, elliptical) and imposed order and selectivity. Next, a special frequency transformation is applied to this prototype, leading to a 2D oriented filter in the analog version. Next, applying the well-known bilinear transformation on the two frequency axes, we finally derive the frequency response of the desired 2D directional filter, with a given orientation angle in the frequency plane. The obtained 2D filter is of low complexity, its matrices being of size 5 × 5, and therefore can be efficiently implemented. Moreover, the filter is parametric (tunable), its selectivity and orientation angle being adjustable through independent parameters, which appear explicitly in the filter matrices. Several design examples using the proposed method are given for specified values of parameters (selectivity and orientation angle). The main application of this type of filter is enhancing and extracting straight lines or various oriented features and details from an image, as shown in the provided simulation results. A very efficient system-level implementation is also developed, using the block filtering approach, which ensures a higher degree of parallelism and a lower arithmetic complexity. Full article

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major cause of morbidity and mortality worldwide, particularly due to the emergence of drug-resistant strains. Membrane-active antimicrobial peptides (AMPs) represent attractive therapeutic candidates because they target bacterial envelope integrity and disrupt essential cellular processes. We evaluated two rationally designed LL-37-derived peptides: a truncated C-terminally amidated analog (LL37-1) and a modified variant incorporating N-terminal acetylation and a single D-amino acid substitution (D-LL37). Dose–response analysis demonstrated that D-LL37 exhibited greater antimycobacterial potency, with lower inhibitory concentrations of 90% (IC₉₀) and 50% (IC₅₀) values (18.40 ± 0.39 μM and 10.11 ± 0.60 μM, respectively) compared with LL37-1 (25.44 ± 0.36 μM and 15.45 ± 1.40 μM). Fluorescence-based permeability assays revealed partial membrane disruption (36% and 44% at IC₉₀ for LL37-1 and D-LL37, respectively), which was supported by ultrastructural alterations observed by scanning electron microscopy, including bacillary shortening, rough surface formation, cell clusters, and the presence of cellular debris, all of which are consistent with membrane damage. RT-qPCR analysis demonstrated significant upregulation of the P-type ATPase genes ctpF, ctpA, and ctpH following D-LL37 exposure. Collectively, these findings indicate that optimized LL-37-derived peptides exert antitubercular activity associated with envelope perturbation and coordinated activation of ion transport-related stress responses. Full article

Morphing aircraft, which are capable of adaptively changing their configurations in response to mission requirements and flight environments to achieve improved aerodynamic performance, have become an important direction in aircraft design. Since the unsteady aerodynamic characteristics during continuous wing morphing differ from those in corresponding quasi-steady states, evaluating dynamic aerodynamic effects during morphing is important. In this study, a surface-based dynamic mesh approach was developed based on a spring-analogy method to simulate continuous wing morphing processes. The method employed a surface-driven mesh motion strategy, in which prescribed analytical motion of surface nodes was propagated into the volume mesh without relying on global interpolation procedures. By coupling this approach with a CFD solver, unsteady simulations of a continuously stretching wing were performed. Numerical examples showed consistent results between moving-mesh and fixed-mesh simulations. Further simulations under subsonic, transonic, and supersonic conditions allowed analysis of aerodynamic responses during continuous morphing. The proposed approach provides a numerical framework for unsteady aerodynamic simulations involving continuous surface deformation. Full article

Background/Objectives: To evaluate the short-term clinical and radiological outcomes of using custom-designed additive-manufactured acetabular components (CDAMACs) in revision total hip arthroplasty for patients with Paprosky type IIIA-IIIB acetabular defects. Materials and Methods: A retrospective single-center case series was conducted. Between 2020 and 2025, 19 patients with massive Paprosky type IIIA-IIIB acetabular defects underwent revision hip arthroplasty with CDAMACs. Preoperative planning was based on multislice computed tomography data, followed by 3D modeling and implant design. Perioperative parameters, functional outcomes (Harris Hip Score [HHS], WOMAC, Visual Analog Scale [VAS] for pain), and radiographic parameters (restoration of the center of rotation, component stability) were assessed. Minimum follow-up was 12 mo. Results: The mean operative time was 155 ± 24 min, and the mean blood loss was 718 ± 288 mL. At 12 mo, significant functional improvements were observed: the mean HHS increased from 37.5 ± 5.2 to 74.5 ± 8.6 points, WOMAC decreased from 74.5 ± 9.2 to 40.3 ± 7.6 points, and VAS decreased from 7.6 ± 1.0 to 2.8 ± 0.7 points (p < 0.001 for all). Restoration of the hip center of rotation was determined. Minimum follow-up was 12 mo. No component migration or progressive radiolucent lines were observed. Complications occurred in two patients (10.5%), with only one case directly related to the acetabular component. Conclusions: The use of CDAMACs in revision hip arthroplasty for severe Paprosky type IIIA-IIIB acetabular defects is associated with satisfactory short-term clinical, functional, and radiological outcomes. This technique enables restoration of the center of rotation and provides stable component fixation in complex anatomical conditions. Full article

Background: The impact that various methods of calcaneal fracture treatment have on functional outcomes is not thoroughly understood. The purpose of this study was to analyze the impact of calcaneal fractures on the level of physical activity and foot and ankle mobility following various fixation methods. Methods: In our two-center retrospective analysis, we compared treatment outcomes of intra-articular calcaneal fractures in 50 patients treated with the Ilizarov method and 49 patients who underwent internal plate fixation. The following parameters were analyzed: range of motion of the foot and ankle joint; the UCLA Activity Scale, the Saltin–Grimby scale, and the Visual Analog Scale (VAS) of Activity. No multivariable adjustment was performed. Accordingly, between-group comparisons are unadjusted, except where stratified analyses are indicated. Results: Postoperatively, a significant improvement was noted in terms of UCLA Activity parameters and the Saltin–Grimby score in the Ilizarov group. A comparison of post-treatment physical activity levels in the two groups revealed significantly better scores in the Grimby scale and VAS activity in the Ilizarov group than in the internal fixation group. The ranges of motion in the Ilizarov group showed significantly worse mobility in the operated limb than in the intact limb. The ranges of dorsiflexion, foot inversion, and foot eversion in the ORIF group were comparable for the treated and intact limb. A comparison of ranges of motion in the study groups showed significantly lower ranges of motion in the Ilizarov group than in the ORIF group. Conclusions: Calcaneal fracture treatment with the Ilizarov method may be associated with better physical activity levels than internal plate fixation. Foot and ankle mobility following calcaneal fracture treatment is better in patients treated with internal plate fixation. The results should be taken with caution due to the lack of randomization, two-center design and the retrospective nature of the study. Full article

The Axial Flux Permanent Magnet Synchronous Motor (AFPMSM) has gained significant attention as a core power source for next-generation industrial sectors, including electric vehicles, wind turbines, robot joints, and drone propulsion motors, due to its high power density from a short axial length and large radial dimensions. Despite these structural advantages, cogging torque caused by magnetic interaction between the stator teeth and permanent magnets remains a critical drawback, inducing noise and vibration. While conventional Soft Magnetic Composite (SMC) core methods facilitate 3D flux paths, they suffer from low magnetic permeability, insufficient mechanical strength, and manufacturing complexity. To address these issues, this study proposes a stepped structure model utilizing electrical steel sheets to effectively reduce cogging torque. This structure features radial stacking of identical electrical steel sheets with varying widths, where each layer's center is incrementally shifted in the rotational direction. This configuration achieves an effect analogous to continuous skewing without specialized 3D machining. To validate the proposed design, 3D Finite Element Analysis (FEA) was conducted. Results demonstrate that the peak-to-peak cogging torque was reduced to approximately 86% of the conventional model’s value, while maintaining the back-EMF reduction rate within 5%. By presenting a novel skewing technique, this research provides a practical alternative for high-precision and high-power AFPMSM. Full article

Accurate measurement of spool displacement is essential for achieving high-performance closed-loop control and condition monitoring in hydraulic systems. However, conventional inductive displacement transducers typically rely on sinusoidal excitation and complex analog signal conditioning circuits, resulting in higher hardware cost and limited system integration. To address these issues, this paper proposes a software-based demodulation method for a differential inductive displacement transducer under symmetric complementary square-wave excitation. First, the structure and operating principle of the transducer are analyzed, and an electromagnetic model describing the nonlinear relationship between coil inductance and the position of the inductive core is established, along with its electrical characteristics. Then, a simplified signal acquisition circuit is designed to enable digital extraction of inductance variations using a microprocessor. Compared with conventional approaches, the proposed scheme significantly reduces hardware complexity and cost while being more suitable for embedded system integration. A simulation model is developed to analyze the inductance variation and to validate the proposed hardware circuit. In addition, a test platform is built to conduct static calibration and dynamic response experiments. The experimental results show that the proposed method achieves a linearity of 2.36% and a sensitivity of 155.6 mV/mm and exhibits strong robustness against switching noise. Finally, application tests in a hydraulic valve system demonstrate that the proposed transducer and demodulation method enable accurate and stable spool position measurement, providing a low-cost and easily integrated solution for embedded hydraulic control systems. Full article

In the Industry 4.0 era, the Architecture, Engineering, Construction, and Operation (AECO) sector faces a strategic challenge in integrating Mechanical, Electrical, and Plumbing (MEP) systems during early design stages, where a lack of “Design for Maintainability” contributes to building defect rates of up to 28%. These failures not only incur significant resource waste but also undermine long-term building sustainability. This study evaluates a digital innovation framework synthesizing Serious Games and Cooperative Problem-Based Learning (CPBL) via Minecraft to foster systemic thinking and spatial reservation logic at Level of Development (LOD) 100–150 as a catalyst for digital transformation. Utilizing a mixed-methods design (n = 25), the curriculum employed a “Mirror Mapping” mechanism, translating game physics into real-world electrical and plumbing logic. While results showed 93% management competency, a significant 13% “Symbolic Transformation Gap (STG)” (80% in system analogy) persisted, indicating that symbolic fluency does not automatically yield professional engineering reasoning. These findings validate the framework’s potential for spatial externalization and emphasize the necessity of “bridging activities” and Digital Twin linkages to optimize building lifecycle performance and reduce carbon footprints, ultimately achieving sustainable building goals. Full article

Memristors, as transformative electronic devices designed to transcend the von Neumann architecture, enable the physical unification of information storage and computation, thereby offering a foundational hardware pathway toward energy-efficient, brain-inspired computing. Their intrinsic analog resistive switching, non-volatility, and history-dependent learning capabilities allow them to natively implement in-memory computing and emulate synaptic plasticity, addressing the critical bottlenecks of energy and speed in conventional systems. Notably, the evolution from electrically controlled memristors to optoelectronic memristors marks a paradigm shift from pure computing to integrated sensing-processing, opening new dimensions for high-speed, parallel, and adaptive signal processing. In recent years, significant progress has been made in the development of memristor-based neuromorphic vision and tactile systems, on-chip signal processors, and dynamic trajectory trackers, demonstrating their potential in edge intelligence, adaptive robotics, and real-time perceptual tasks. This review systematically summarizes the latest advances in memristor technology, providing a comprehensive analysis of their operating mechanisms, material and structural innovations, and cutting-edge applications in neuromorphic perception and computing. Furthermore, it discusses the key challenges and future directions for the development and integration of memristor-based systems in the post-von Neumann era. Full article

The work uses a comprehensive approach based on the information and communication concept of construction management templates to minimize information asymmetry between construction stakeholders when implementing innovative technologies. An analysis of the regulatory framework and patent research of existing analogs of wall structures was conducted. It was theoretically substantiated that the use of removable reusable formwork for monolithic walls made of expanded polystyrene concrete allows significant reduction in cost and logistics costs. A technology for erecting heat-insulating walls made of expanded polystyrene concrete (EPC) has been developed, which involves preliminary preparation of the insulation with the application of a protective reinforced layer. This allows avoiding performing labor-intensive and dangerous operations at height. A design of a noise-proof wall with sound-absorbing hollow-forming elements has been proposed, improving acoustic characteristics while saving materials. Thermophysical tests of fragments of walls made of expanded polystyrene concrete with a density of D250 (thickness of 260 mm) confirmed the need for additional insulation for heat transfer resistance for regulatory compliance. Acoustic studies have proven the effectiveness of using hollow-forming elements to increase the airborne noise insulation index and to reduce material consumption. All this helped to develop and patent the polystyrene concrete wall technology. For the first time, the concept of implementing the technological process of expanded polystyrene concreting of monolithic walls into construction management and production using construction management templates was proposed. This allowed the transformation of technological operations into a flow of objective data to minimize information asymmetry between project participants. It was theoretically proven that the objectification of production indicators through construction management templates is a base for measuring the commercial value and investment attractiveness of the technology being implemented. Full article

High-intensity or repetitive exercise induces metabolic stress and neuromuscular fatigue in skeletal muscle. Using a within-subjects repeated-measures crossover design, eight male amateur swimmers completed five experimental sessions at one-week intervals. Following an isokinetic fatigue protocol, five recovery interventions were applied in a randomized order: control (NT), foam roller (FR), vibration foam roller (VFR), and whole-body vibration at 12 Hz (WBV-12) and 20 Hz (WBV-20). The isokinetic fatigue protocol produced a significant reduction in bilateral extensor peak torque (229.2 ± 37.8%BW to 189.8 ± 27.5%BW; t(7) = 4.19, p = 0.004, d = 1.48), confirming successful fatigue induction. Outcome measures included visual analog scale (VAS) scores, blood lactate concentration, and knee extensor/flexor peak torque (%BW) assessed at three time points. A two-way repeated-measures ANOVA (intervention × time) revealed significant main effects of recovery methods at the post-recovery time point for VAS scores (F(4,28) = 5.98, p = 0.001, η²g = 0.248), blood lactate (F(4,28) = 5.12, p = 0.003, η²g = 0.226), and isokinetic peak torque (F(4,28) = 10.75, p < 0.001, η²g = 0.226). Post hoc Bonferroni analysis indicated that VFR and WBV-20 produced significantly higher lactate recovery rates than NT. Active recovery interventions produced lower perceived fatigue scores and greater lactate reductions than passive rest; however, individual Bonferroni pairwise comparisons for VAS and blood lactate did not reach adjusted significance, and these findings should be considered preliminary. WBV-20 demonstrated statistically confirmed superiority in isokinetic muscle function recovery (Bonferroni p < 0.05 vs. NT, FR, and VFR), suggesting its potential as an effective post-exercise recovery strategy for neuromuscular restoration. Full article

Background and Objectives: Functional neurosurgery encompasses surgical interventions aimed at modulating the function of the central and peripheral nervous systems. Spinal cord stimulation (SCS), as a form of neuromodulation, is an established treatment for chronic pain and is increasingly utilized by both anesthesiologists and neurosurgeons. The aim of this study was to evaluate the effectiveness of SCS in patients with chronic neuropathic spinal pain. Materials and Methods: This prospective study included 42 patients who demonstrated a positive response to trial stimulation. Only patients achieving a clinically meaningful response (≥50% pain reduction) during the trial phase were included in the final analysis. Pain intensity and functional disability were assessed using the Visual Analog Scale (VAS) and the Oswestry Disability Index (ODI). All patients underwent a two-stage percutaneous implantation procedure using burst stimulation. A follow-up assessment was performed 3–6 months after implantation. Results: A statistically significant reduction in pain intensity was observed (p < 0.0001), with median VAS scores decreasing from 8 to 3, corresponding to a 62.5% reduction in pain intensity and exceeding the minimal clinically important difference (MCID) for VAS. Functional status improved significantly, with ODI scores decreasing from 74% to 38%, markedly surpassing the established MCID threshold. A clinically meaningful reduction in pain (≥50%) was achieved in the majority of patients. All patients requiring opioid analgesics at baseline discontinued their use following SCS implantation, and a reduction in overall analgesic consumption was observed across the cohort. Conclusions: These findings suggest that burst SCS may be an effective treatment option for carefully selected patients with chronic neuropathic spinal pain who are not candidates for conventional spine surgery. However, the results should be interpreted with caution due to the enriched study design and limited follow-up period. Full article