Search Results (660)

A triboelectricity-enhanced piezoelectric nanogenerator (PENG) based on pressure-processed multi-electrospun polymeric layers is herein developed for efficient vibrational energy harvesting. The hybridization of piezoelectric and triboelectric mechanisms through electrospinning has been utilized to enhance electrical output by increasing contact areas and promoting alignment within piezoelectric materials. A multi-layer structure comprising alternating poly (vinylidene fluoride) (PVDF) and poly (hexamethylene adipamide) (PA 6/6) exhibits superior electrical performance. A lateral Janus configuration, providing distinct positive and negative triboelectric polarities, has further optimized device efficiency. This approach introduces a novel operational mechanism, enabling superior performance compared to conventional methods. The fiber-based architecture ensures exceptional flexibility, low weight, and a high surface-to-volume ratio, enabling enhanced energy harvesting. Experimentally, the PENG achieved an open-circuit voltage of 14.59 V, a short-circuit current of 205.7 nA, and a power density of 7.5 mW m⁻² at a resistance of 30 MΩ with a five-layer structure subjected to post-processing under pressure. A theoretical model has mathematically elucidated the output results. Long-term durability (over 345,600 cycles) has confirmed its robustness. Demonstrations of practical applications include monitoring human joint motion and respiratory activity. These results highlight the potential of the proposed triboelectricity-enhanced PENG for vibrational energy harvesting in flexible and wearable electronic systems. Full article

In recent years, the passenger flow volume of conventional transit in major cities has declined steadily. Ground public transit often suffers from congestion during rush hours caused by frequent stops (e.g., conventional fixed-route buses) or excessively high operating costs (e.g., demand-responsive transit). While rail transit offers reliable service with dedicated right-of-way, its high capital and operational costs pose challenges for integrated planning with other transit modes. The joint design of rail, conventional buses, and DRT remains underexplored. To bridge this gap, this paper proposes and analyses a new hybrid transit system that integrates conventional transit service with demand-adaptive transit (DAT) to feed urban rail transit (the system hence called hybrid microtransit system). The main task is to optimally design the hybrid microtransit system to allocate resources efficiently across different modes. Both the conventional transit and DAT connect passengers from their origin/destination to the rail transit stations. Travelers can choose one of the services to access urban rail transit, or directly walk. Accordingly, we divide the service area into three parts and compute the user costs to access rail transit by conventional transit and DAT. The optimal design problem is hence formulated as a mixed integer program by minimizing the total system cost, which includes both the user and agency (operating) costs. Numerical experiment results demonstrate that the hybrid microtransit system performs better than the system that only has conventional transit to feed under all demand levels, achieving up to a 7% reduction in total system cost. These may provide some evidence to resolve the “first-mile” challenges of rail transit in megacities by designing better conventional transit and DAT. Full article

Background: Temporomandibular joint (TMJ) injections and arthrocentesis are commonly used minimally invasive methods for treating temporomandibular disorders (TMDs). Although considered safe, they can cause neurological complications. The aim of this systematic review was to synthesize all identified evidence for neurological adverse events following intra-articular TMJ interventions. Methods: This review was based on a systematic search with BASE, DOAJ, PubMed, SciELO, and Semantic Scholar on 28 May 2025. It included primary studies involving patients diagnosed with TMDs who underwent intra-articular injections into the TMJ or were treated with arthrocentesis, and in whom neurological adverse effects associated with the intra-articular intervention were reported. Studies reporting non-specific symptoms or unrelated systemic conditions were excluded. The risk of bias was assessed using the Joanna Briggs Institute’s critical appraisal tools. Results were presented in summary tables. Results: The search yielded five eligible studies comprising 319 patients, of whom 320 neurological adverse events were reported. Included studies comprised a randomized controlled trial, two retrospective studies, and two case reports. Four studies had a low risk of bias, and one had a moderate risk of bias according to the Joanna Briggs Institute appraisal tools. The proportion of patients affected ranged from 14% to 65% depending on the study design and intervention type. The most common adverse event was transient facial nerve (cranial nerve VII) paralysis, mainly involving the temporal and zygomatic branches. Less commonly reported complications involved the trigeminal nerve branches (V1, V3). There is also a single case of epidural hematoma with palsy of the oculomotor nerve (III). Most symptoms resolved spontaneously within a few hours to a few days. The use of local anesthesia and large volumes of irrigation (60 mL) during arthrocentesis increases the risk of complications. Attempts to explain the mechanisms of complications include local anesthetic diffusion, compression neuropraxia due to lavage fluid leakage, and corticosteroid neurotoxicity. One of the limitations of the study is the scarcity of data. Conclusions: Although most adverse events are mild and reversible, these findings highlight that precise, real-time guided injection and careful control of lavage volumes can minimize extra-articular spread of anesthetics or fluids, thereby reducing the likelihood of neurological complications. This study received no funding. PROSPERO ID number: CRD420251088170. Full article

Under the background of “dual-carbon” strategy and global energy transition, the metallurgical industry, which accounts for 15–20% of industrial energy consumption, urgently needs to reduce the energy consumption and emission of DC power supply of electric furnaces. Aiming at the existing 400–800 V/≥3000 A industrial-frequency transformer-rectifier system with low efficiency, large volume, heat dissipation difficulties and other bottlenecks, this thesis proposes and realizes a high-frequency integrated DC power supply scheme for high-power electric furnaces: high-frequency transformer core and rectifier circuit are deeply integrated, which breaks through and reduces the volume of the system by more than 40%, and significantly reduces the iron consumption; multiple cores and three windings in parallel are used for the system. The topology of multiple cores and three windings in parallel enables several independent secondary stages to share the large current of 3000 A level uniformly, eliminating the local overheating and current imbalance; the combination of high-frequency rectification and phase-shift control strategy enhances the input power factor to more than 0.95 and cuts down the grid-side harmonics remarkably. The authors have completed the design of 100 kW prototype, magneto-electric joint simulation, thermal structure coupling analysis, control algorithm development and field comparison test, and the results show that the program compared with the traditional industrial-frequency system efficiency increased by 12–15%, the system temperature rise reduced by 20 K, electrode voltage increased by 10–15%, the input power of furnace increased by 12%, and the harmonic index meets the requirements of the traditional industrial-frequency system. The results show that the efficiency of this scheme is 12–15% higher than the traditional IF system, the temperature rise in the system is 20 K lower, the voltage at the electrode end is 10–15% higher, the input power of the furnace is increased by 12%, and the harmonic indexes meet the requirements of GB/T 14549, which verifies the value of the scheme for realizing high efficiency, miniaturization, and reliable DC power supply in metallurgy. Full article

Cranial cruciate ligament (CrCL) rupture is a common orthopedic disorder in dogs, leading to stifle joint instability and progressive osteoarthritis. This study aimed to develop and biomechanically evaluate a novel intra-articular reconstruction system designed to mimic the natural ligament and restore joint stability following CrCL excision. The system consisted of a 3D-printed thermoplastic polyurethane (TPU) graft, cerclage wire, and H-button fixation. Fourteen pelvic limbs from mature mixed-breed cadaveric dogs were used. The inclination angle, dimensions, volume, tensile strength, and elongation of the native CrCL were measured. Seven CrCL-deficient stifles were reconstructed using the proposed system and tested biomechanically. The native CrCL showed a significantly higher tensile strength than the TPU graft; however, the TPU demonstrated a greater flexibility. The reconstruction system successfully stabilized the joint and provided repeatable fixation. Significant correlations were found between CrCL volume and both age and body weight. These findings support the mechanical suitability of the proposed system for ex vivo stifle stabilization and highlight the potential of 3D-printed TPU in ligament reconstruction. Further in vivo studies are recommended to assess long-term performance, including implant integration, tissue remodeling, and clinical outcomes. Full article

The object of this study is welded joints of AISI 321 and Ti-6Al-4V, obtained by diffusion welding on developed conical surfaces. The problem of creating bimetallic joints of AISI 321 and Ti-6Al-4V with developed conical contact surfaces, using diffusion welding through an intermediate Electrolytic Tough Pitch Copper (Cu-ETP) copper layer, was solved. The joints were studied using micro-X-ray spectral analysis, microstructural analysis, and mechanical tests. High mutual diffusion of copper and titanium, along with increased concentrations of Cr and V in copper, was detected. The shear strength of the obtained welded joints is 250 MPa and 235 MPa at 30 min and 15 min, respectively, which is higher than the copper layer’s strength (180 MPa). The obtained results are explained by the dislocation diffusion mechanism in the volume of grains and beyond, due to thermal deformations during welding. Under operating conditions of internal pressure and cryogenic temperatures, the strength of the connection is ensured by the entire two-layer structure, and tightness is ensured by a vacuum-tight diffusion connection. The obtained strength of the connection (250 MPa) is sufficient under the specified operating conditions. Analysis of existing solutions in the literature review indicates that industrial application of technology for manufacturing bimetallic adapters from AISI 321 stainless steel and Ti-6Al-4V titanium alloy is limited to butt joints with small geometric dimensions. Studies of the transition zone structure and diffusion processes in bimetallic joints with developed conical contact surfaces enabled determination of factors affecting joint structure and diffusion coefficients. The obtained bimetallic adapters, made of Ti-6Al-4V titanium alloy and AISI 321 stainless steel, can be used to connect titanium high-pressure vessels with stainless steel pipelines. Full article

Facial expression recognition (FER) is a critical research direction in artificial intelligence, which is widely used in intelligent interaction, medical diagnosis, security monitoring, and other domains. These applications highlight its considerable practical value and social significance. Face expression recognition models often need to run efficiently on mobile devices or edge devices, so the research on lightweight face expression recognition is particularly important. However, feature extraction and classification methods of lightweight convolutional neural network expression recognition algorithms mostly used at present are not specifically and fully optimized for the characteristics of facial expression images, yet fail to make full use of the feature information in face expression images. To address the lack of facial expression recognition models that are both lightweight and effectively optimized for expression-specific feature extraction, this study proposes a novel network design tailored to the characteristics of facial expressions. In this paper, we refer to the backbone architecture of MobileNet V2 network, and redesign LightExNet, a lightweight convolutional neural network based on the fusion of deep and shallow layers, attention mechanism, and joint loss function, according to the characteristics of the facial expression features. In the network architecture of LightExNet, firstly, deep and shallow features are fused in order to fully extract the shallow features in the original image, reduce the loss of information, alleviate the problem of gradient disappearance when the number of convolutional layers increases, and achieve the effect of multi-scale feature fusion. The MobileNet V2 architecture has also been streamlined to seamlessly integrate deep and shallow networks. Secondly, by combining the own characteristics of face expression features, a new channel and spatial attention mechanism is proposed to obtain the feature information of different expression regions as much as possible for encoding. Thus improve the accuracy of expression recognition effectively. Finally, the improved center loss function is superimposed to further improve the accuracy of face expression classification results, and corresponding measures are taken to significantly reduce the computational volume of the joint loss function. In this paper, LightExNet is tested on the three mainstream face expression datasets: Fer2013, CK+ and RAF-DB, respectively, and the experimental results show that LightExNet has 3.27 M Parameters and 298.27 M Flops, and the accuracy on the three datasets is 69.17%, 97.37%, and 85.97%, respectively. The comprehensive performance of LightExNet is better than the current mainstream lightweight expression recognition algorithms such as MobileNet V2, IE-DBN, Self-Cure Net, Improved MobileViT, MFN, Ada-CM, Parallel CNN(Convolutional Neural Network), etc. Experimental results confirm that LightExNet effectively improves recognition accuracy and computational efficiency while reducing energy consumption and enhancing deployment flexibility. These advantages underscore its strong potential for real-world applications in lightweight facial expression recognition. Full article

Driven by the rapid development of e-commerce and intelligent logistics, the volume of express delivery services has surged, making the efficient and accurate identification of shipping information a core requirement for automatic sorting systems. However, traditional Optical Character Recognition (OCR) technology struggles to meet the accuracy and real-time demands of complex logistics scenarios due to challenges such as image distortion, uneven illumination, and field overlap. This paper proposes a three-level collaborative recognition method based on deep learning that facilitates structured information extraction through regional normalization, dual-path parallel extraction, and a dynamic matching mechanism. First, the geometric distortion associated with contour detection and the lightweight direction classification model has been improved. Second, by integrating the enhanced YOLOv5s for key area localization with the upgraded PaddleOCR for full-text character extraction, a dual-path parallel architecture for positioning and recognition has been constructed. Finally, a dynamic space–semantic joint matching module has been designed that incorporates anti-offset IoU metrics and hierarchical semantic regularization constraints, thereby enhancing matching robustness through density-adaptive weight adjustment. Experimental results indicate that the accuracy of this method on a self-constructed dataset is 89.5%, with an F1 score of 90.1%, representing a 24.2% improvement over traditional OCR methods. The dynamic matching mechanism elevates the average accuracy of YOLOv5s from 78.5% to 89.7%, surpassing the Faster R-CNN benchmark model while maintaining a real-time processing efficiency of 76 FPS. This study offers a lightweight and highly robust solution for the efficient extraction of order information in complex logistics scenarios, significantly advancing the intelligent upgrading of sorting systems. Full article

Background: Adhesive capsulitis (AC) causes a global limitation of both active and passive range of motion (ROM) in the shoulder, with or without pain, and no specific radiographic findings. Its course is self-limiting and progresses through three or four stages. The diagnosis is primarily clinical, since imaging tests are nonspecific. Treatment options include physical therapy (PT), intra-articular corticosteroid injections, suprascapular nerve block (SSNB), and hydrodilatation (HD). The latter is useful for expanding and reducing inflammation of the joint capsule through the insufflation of saline solution, anesthetics, and corticosteroids. Objectives: To compare whether patients with AC, stratified by phase 1 and 2, who receive high-volume HD as treatment achieve better outcomes in terms of shoulder pain and function compared to patients who receive low-volume HD. To compare whether there are differences in PT times and to determine mean axillary recess (AR) values. Methods: A randomized, parallel-block, triple-blind clinical trial will be conducted in 64 patients with AC in phases 1 and 2, aged 30 to 70 years, with limited active and passive ROM in two planes, and shoulder pain lasting more than 3 months. HD will be administered with volumes of 20 mL or 40 mL, followed by a conventional rehabilitation program. Outcomes will be reviewed at the 1st, 3rd, and 6th months of HD. Variables collected will include Shoulder Pain and Disability Index (SPADI), Visual Analog Scale (VAS), Range of motion (ROM), Lattinen index (LI), AR size, and time to completion of PT. Results: HD has been gaining clinical relevance in interventional rehabilitation as a treatment for AC, although its medium- and long-term efficacy remains a matter of debate. The variability in the volumes used for capsular expansion, with studies ranging from 18 mL to 47 mL, is compounded by the fact that most of these studies do not differentiate between AC stages. This could influence treatment effectiveness. Furthermore, diagnosis remains a challenge since valid and specific diagnostic parameters are lacking. Conclusions: Understanding the differences between HD techniques, considering the influence of certain factors such as the volume used or the stages of AC, as well as improving diagnosis and the coordination of scientific work. This could facilitate the development of protocols for the use of HD in AC. Full article

The design of steel connections presents considerable complexity due to their inherently nonlinear behavior, cost constraints, and the necessity to comply with structural design codes. These factors highlight the need for advanced computational algorithms to identify optimal solutions. In this study, a comprehensive computational framework is presented in which the finite element method (FEM) is integrated with a genetic algorithm (GA) to optimize material usage in bolted steel end-plate joints, while structural safety is ensured based on multiple performance criteria. By incorporating both material and geometric nonlinearities, the mechanical response of the connections is accurately captured. The proposed approach is applied to a representative beam-to-column assembly, with numerical results verified against experimental data. By employing the framework, an optimized layout is obtained, yielding a $10.4\%$ improvement in the overall performance objective compared to the best-performing validated model and a $39.3\%$ reduction in material volume relative to the most efficient feasible alternative. Furthermore, a $53.6\%$ decrease in equivalent plastic strain is achieved compared to the configuration exhibiting the highest level of inelastic deformation. These findings demonstrate that the developed method is capable of enhancing design efficiency and precision, underscoring the potential of advanced computational tools in structural engineering applications. Full article

An ultra-high-strength press-hardening steel (PHS) and a high-strength dual-phase steel (DP) were butt-joined by the gas metal arc welding (GMAW) process, aiming to assess the effects of a high heat input welding process on the structure-property relationship and residual stress. The post-weld microstructure, the microhardness profile, the tensile behavior, and the experimentally obtained residual stresses (by x-ray diffraction) of the steels in dissimilar (PHS-DP) and similar (PHS-PHS, DP-DP) pair combinations have been analyzed. Results indicated that the ultimate tensile strength (UTS) of the dissimilar pair PHS-DP achieves a similar strength to the DP-DP joint, whereas the elongation was similar to that of the PHS-PHS weldment. The failure location of the tensile specimens was expected and systematically observed at the tempered and softer sub-critical heat-affected zone (SC-HAZ) in all welded conditions. Compressive residual stresses were consistently observed along the weldments in all specimens; the more accentuated negative RS were measured in the PHS joint attributed to the higher volume fraction of martensite; furthermore, the negative RS measured in the fusion zone (FZ) could be well correlated to weld restraint due to the sheet anchoring during the welding procedure, despite the presence of predominant ferrite and pearlite microstructures. Full article

This paper deals with an important issue, which is the influence of failure caused by the quality of matrix post-curing on the strength of complex and difficult materials of the “new generation” such as fibre composites, particularly with a polymer matrix. In recent years, significant advances in the field of adhesive materials chemistry have led to the constant development of bonding technology. The effectiveness of bonding depends, to a large extent, on the suitable selection of the adhesive and the use of appropriate surface treatment technology. It is difficult to imagine virtually any modern industry without adhesive joints, be it the aircraft, aerospace or automotive industries, which simultaneously highlights the great importance of adhesives and adhesive materials for the present-day economy. In modern technology, it is extremely important to obtain the right combination of modern construction materials. The statistical analysis of the components showed the complexity of the layered composite structure. The proposed model of the weakest micro-volume developed in this study indirectly reflects the experimentally based curing variables that affect the stresses of the components in the composite (laminate) structure. The strength of fibrous composite structures based on the Markov chain theory considers technological aspects during hardening. The model proposed in the paper was validated on the basis of examples from the literature and experimental data obtained in the research project. The numerical results are in good agreement with the literature database and measurement data. The presented model could be a novel method, which allows better insight into the curing process of epoxy resins. Full article

This study aimed to evaluate how wearable hip exoskeleton assistance affects phase-dependent gait stability in healthy adults using a novel visualization technique known as gait tube analysis. Hip exoskeletons offer significant potential to enhance human locomotion through joint torque augmentation, yet their effects on gait stability across the gait cycle remain underexplored. This study introduces gait tube analysis, a novel method for visualizing center of mass velocity trajectories in three-dimensional state space, to quantify phase-dependent gait stability under hip exoskeleton assistance. We analyzed data from ten healthy adults walking under twelve conditions (ten powered with varying torque magnitude and timing, one passive, and one unassisted), assessing variability via covariance-based ellipsoid volumes. Powered conditions, notably HighLater and HighLatest, significantly increased vertical variability (VT) during early-to-mid stance (10–50% of the gait cycle), with HighLater showing the highest mean ellipsoid volume (99,937 mm³/s³; z = 2.3). Conversely, the passive PowerOff condition exhibited the lowest variability (47,285 mm³/s³; z = –1.7) but higher metabolic cost, highlighting a stability-efficiency trade-off. VT was elevated in 11 of 12 conditions (p ≤ 0.0059), and strong correlations (r ≥ 0.65) between ellipsoid volume and total variability validated the method’s robustness. These findings reveal phase-specific stability challenges and metabolic cost variations induced by exoskeleton assistance, providing a foundation for designing adaptive controllers to balance stability and efficiency in rehabilitation and performance enhancement contexts. Full article

Background: Magnetic resonance imaging (MRI) plays a crucial role in staging and preoperative evaluation in osteosarcoma patient. Fewer studies have focused on 2-year survival, which reflects tumour aggressiveness and early disease progression. This study examines the association between MRI characteristics and 2-year survival outcomes in osteosarcoma to better understand the imaging characteristic of high-risk patients. Methods: A retrospective case–control study was conducted at a tertiary university hospital. Patients diagnosed with osteosarcoma between 2010 and 2022 were included if they had a pre-treatment MRI and at least 2 years of follow-up. MRI scans were reviewed by two blinded radiologists to assess tumour location, volume, growth pattern, presence of fluid–fluid levels (FFL), pathological fractures, skip metastases, neurovascular bundle involvement, regional lymphadenopathy, and physeal or joint involvement. Statistical analyses, including Fisher’s exact test, Chi-square test, and Mann–Whitney U test, were performed to determine associations between MRI features and survival outcomes. Results: Twenty-eight patients (n = 28) met the inclusion criteria. Larger tumour volume (>300 mls) was significantly associated with poorer 2-year survival (p = 0.008). The presence of skip metastases also correlated with worse outcomes (p = 0.041). While presence of FFL, concentric growth pattern, regional lymphadenopathy, and physeal involvement showed trends toward poorer prognosis, these associations were not statistically significant. Conclusions: MRI characteristics, particularly tumour volume and skip metastases, are significant prognostic indicators of 2-year survival in osteosarcoma. These findings highlight the potential role of MRI in risk stratification and treatment planning, aiding in the identification of high-risk patients that can help with management. Full article

The water–energy nexus (WEN) is of great significance due to the strong interdependence between the energy and water sectors. Nevertheless, water leakage in water distribution networks (WDNs), which is often ignored in existing WEN operation models, causes notable water and energy losses. In this research, a cooperative operation model for WEN considering WDN water leakage is put forward. A hybrid stochastic–information gap decision theory (IGDT) method was tailored in this study to properly manage the probabilistic uncertainties associated with renewable generation, electrical and water demand in the WEN, and water leakage with limited information to enhance the robustness of the operation strategies of the WEN under complex operational conditions. The proposed model and method were validated on a modified IEEE 33-bus system integrated with a 15-node commercial WDN. The co-optimization model reduced the operational cost by 23.01% compared to the independent operation model. When considering water leakage, the joint optimization resolved the water supply shortage issue caused by ignoring leakage and reduced the water purchase volume by 94.44 cubic meters through coordinated optimization. These quantitative results strongly demonstrate the effectiveness of the proposed framework. Full article