Search Results (939)

Climate concerns are driving the automotive industry to adopt advanced manufacturing technologies that aim to improve energy efficiency and reduce vehicle weight. In this context, lightweight structural materials such as aluminium alloys have gained significant attention due to their favorable strength-to-weight ratio. Laser welding plays a crucial role in assembling such materials, offering high flexibility and fast joining capabilities for thin aluminium sheets. However, welding these materials presents specific challenges, particularly in controlling heat input to minimize distortions and ensure consistent weld quality. As a result, numerical simulations based on the Finite Element Method (FEM) are essential for predicting weld-induced phenomena and optimizing process performance. This study investigates welding-induced distortions in laser butt welding of 1.5 mm-thick Al 6061 samples through FEM simulations performed in the SYSWELD 2024.0 environment. The methodology provided by the software is based on the Moving Heat Source (MHS) model, which simulates the physical movement of the heat source and typically requires extensive calibration through destructive metallographic testing. This transient approach enables the detailed prediction of thermal, metallurgical, and mechanical behavior, but it is computationally demanding. To improve efficiency, the Imposed Thermal Cycle (ITC) model is often used. In this technique, a thermal cycle, extracted from an MHS simulation or experimental data, is imposed on predefined subregions of the model, allowing only mechanical behavior to be simulated while reducing computation time. To avoid MHS-based calibration, this work proposes using thermal cycles acquired in-line during welding via infrared thermography as direct input for the ITC model. The method was validated experimentally and numerically, showing good agreement in the prediction of distortions and a significant reduction in workflow time. The distortion values from simulations differ from the real experiment by less than 0.3%. Our method exhibits a slight decrease in performance, resulting in an increase in estimation error of 0.03% compared to classic approaches, but more than 85% saving in computation time. The integration of real process data into the simulation enables a virtual representation of the process, supporting future developments toward Digital Twin applications. Full article

The integration of renewable energy sources (RESs) into power systems, particularly in microgrids, is becoming a prominent trend aimed at reducing dependence on traditional energy sources. Replacing conventional synchronous generators with grid-connected RESs through power electronic converters has significantly reduced the inertia of microgrids. This reduction negatively impacts the dynamics and operational performance of microgrids when confronted with uncertainties, posing challenges to frequency and voltage stability, especially in a standalone operating mode. To address this issue, this research proposes enhancing microgrid stability through frequency control based on virtual inertia (VI). Additionally, the Iterative Learning Control (ILC) method is employed, leveraging iterative learning strategies to improve the quality of output response control. Accordingly, the ILC-VI control method is introduced, integrating the iterative learning mechanism into the virtual inertia controller to simultaneously enhance the system’s inertia and damping coefficient, thereby improving frequency stability under varying operating conditions. The effectiveness of the ILC-VI method is evaluated in comparison with the conventional VI (C-VI) control method through simulations conducted on the MATLAB/Simulink platform. Simulation results demonstrate that the ILC-VI method significantly reduces the frequency nadir, the rate of change of frequency (RoCoF), and steady-state error across iterations, while also enhancing the system’s robustness against substantial variations from renewable energy sources. Furthermore, this study analyzes the effects of varying virtual inertia values, shedding light on their role in influencing response quality and convergence speed. This research underscores the potential of the ILC-VI control method in providing effective support for low-inertia microgrids. Full article

Background: People with post-stroke cognitive impairment (PSCI) are at increased risk of recurrent stroke, dementia, and accelerated cognitive decline. Objective: To examine the feasibility, safety, acceptability, and suitability of a virtually-delivered vascular risk reduction intervention that integrates tailored cognitive strategy training for people with executive function (EF) impairments post-stroke. Methods: This case series included eight participants who completed up to ten virtual sessions focused on vascular risk reduction and metacognitive strategy training. Sessions averaged 40 min over a 4–5-week period. Results: The intervention was found to be feasible, safe, and acceptable. The recruitment rate was 66.7%, and the retention rate was 87.5% (7 of 8 completed the training). No serious adverse events were reported. Most participants demonstrated improvements on the Canadian Occupational Performance Measure (COPM), with mean performance and satisfaction change scores of 1.22 ± 0.87 and 1.18 ± 0.83, respectively. Conclusions: This technology-enabled intervention was feasible and acceptable for individuals with post-stroke EF impairments. Virtual delivery was a key factor in its accessibility and success. The results are promising for improving self-management of vascular risk factors, warranting further study in larger trials. Full article

Epilepsy remains a widespread neurological disorder, with approximately 30% of patients showing resistance to current antiepileptic therapies. To address this unmet need, a series of 2-(isoindolin-2-yl) esters derived from natural amino acids were designed and evaluated for their potential interaction with the GABA_A receptor. Sixteen derivatives were subjected to in silico assessments, including physicochemical and ADMET profiling, virtual screening–ensemble docking, and enhanced sampling molecular dynamics simulations (metadynamics calculations). Among these, compounds derived from the aromatic amino acids, phenylalanine, tyrosine, tryptophan, and histidine, exhibited superior predicted affinity, attributed to π–π stacking interactions at the benzodiazepine binding site of the GABA_A receptor. Based on computational performance, the tyrosine and tryptophan derivatives were synthesized and further assessed in vivo using the pentylenetetrazole-induced seizure model in zebrafish (Danio rerio). The tryptophan derivative produced comparable behavioral seizure reduction to the reference drug diazepam at the tested concentrations. The results implies that aromatic amino acid-derived isoindoline esters are promising anticonvulsant candidates and support the hypothesis that π–π interactions may play a critical role in modulating GABA_A receptor binding affinity. Full article

Background/Objectives: Dental anxiety in children is a common issue that can hinder the delivery of effective dental care. Traditional approaches to managing this are often insufficient or involve pharmacological interventions. This study shows the potential of virtual reality (VR) to aid in reducing anxiety in children undergoing simple dental procedures. By immersing children in relaxing VR environments (such as beaches, forests, mountains, or underwater scenes with calm music), the objective is to assess VR’s effectiveness in calming pediatrics patients during these procedures. Methods: Children scheduled for minor dental treatments wore a wearable device that monitored pulse, perspiration, and stress levels. Each child’s baseline data was collected without the VR headset, followed by data collection during VR exposure before and during dental procedures. VR scenarios ranged from soothing nature scenes to animated cartoons, designed to foster relaxation. Results: The data collected showed a reduction in physiological indicators of stress, such as lower heart rate and reduced perspiration, when the VR headset was used. Children appeared more relaxed, with a calmer response during the procedure itself, compared to baseline levels without VR. Conclusions: This study provides preliminary evidence supporting VR as an effective tool for reducing anxiety and stress in pediatric dental patients. By offering an engaging, immersive experience, VR can serve as an alternative or complementary approach to traditional anxiety management strategies in pediatric dentistry, potentially improving patient comfort and cooperation during dental procedures. Further research could determine if VR may serve as an alternative to local anesthesia for non-intrusive pediatric dental procedures. Full article

Blindness and low vision are increasing serious public health issues that affect a significant percentage of the population worldwide. Vision plays a crucial role in spatial navigation and daily activities. Its reduction or loss creates numerous challenges for an individual. Assistive technology can enhance mobility and navigation in outdoor environments. In the field of orientation and mobility training, technologies with haptic interaction can assist individuals with visual impairments in learning how to navigate safely and effectively using the sense of touch. This paper presents a virtual reality platform designed to support the development of navigation techniques within a safe yet realistic environment, expanding upon existing research in the field. Following extensive optimization, we present a visual representation that accurately simulates various 3D tile textures using graphics replicating real tactile surfaces. We conducted a user interaction study in a virtual environment consisting of 3D navigation tiles enhanced with tactile textures, placed appropriately for a real-world scenario, to assess user performance and experience. This study also assess the usability and user experience of the platform. We hope that the findings will contribute to the development of new universal navigation techniques for people with visual impairments. Full article

Testbeds are widely used in experiential learning, providing practical assessments and bridging classroom material with real-world applications. However, manually managing and provisioning student lab environments consumes significant preparation time for instructors. The growing demand for advanced technical skills, such as network administration and cybersecurity, is leading to larger class sizes. This stresses testbed resources and necessitates continuous design updates. To address these challenges, we designed an efficient Environment Management Platform (EMP). The EMP is composed of a set of 4 Command Line Interface scripts and a Web Interface for secure administration and bulk user operations. Based on our testing, the EMP significantly reduces setup time for student virtualized lab environments. Through a cybersecurity learning environment case study, we found that setup is completed in 15 s for each student, a 12.8-fold reduction compared to manual provisioning. When considering a class of 20 students, the EMP realizes a substantial saving of 62 min in system configuration time. Additionally, the software-based management and provisioning process ensures the accurate realization of lab environments, eliminating the errors commonly associated with manual configuration. This platform is applicable to many educational domains that rely on virtual machines for experiential learning. Full article

Partially guided implant surgery has emerged as a technique that enhances the precision of implant placement while maintaining surgical flexibility. This in vitro experimental study evaluated the influence of the milling cutter drill on the angular and linear deviations of implant placement in synthetic polyurethane bone models using a partially guided surgical protocol. Additionally, the effects of bone density and implant macrogeometry were assessed. A total of 120 Straumann^® implants (BL, BLT, and BLX) were placed in polyurethane blocks simulating four bone densities (D1–D4). Implant positions were virtually planned with coDiagnostiX^® (version 10.9) software and executed with or without the use of the milling cutter drill. Deviations between planned and final implant positions were measured at the neck and apex using the software’s “Treatment Evaluation” tool. The use of the milling cutter drill significantly reduced angular deviation (p = 0.007), while linear deviations showed no statistically significant differences. Bone density and implant macrogeometry did not significantly affect angular deviation but influenced linear and 3D deviations. Given that angular deviation may compromise prosthetic fit and biomechanical function, the observed reduction is of potential clinical relevance. These findings indicate that the milling cutter drill enhances angular accuracy in partially guided implant surgery and may improve outcomes in anatomically challenging cases. However, the results should be interpreted within the limitations of this in vitro model, including the absence of soft tissue simulation, intraoral constraints, and inter-operator variability. Full article

The architecture of contemporary museums often emphasizes visual aesthetics, such as large volumes, open-plan layouts, and highly reflective finishes, resulting in acoustic challenges, such as excessive reverberation, poor speech intelligibility, elevated background noise, and reduced privacy. This study quantified the impact of surface—specific absorption treatments on acoustic metrics across eight gallery spaces. Room impulse responses calibrated virtual models, which simulated nine absorption scenarios (low, medium, and high on ceilings, floors, and walls) and evaluated reverberation time (T₂₀), speech transmission index (STI), clarity (C₅₀), distraction distance (r_D), Spatial Decay Rate of Speech (D_2,S), and Speech Level at 4 m (L_p,A,S,4m). The results indicate that going from concrete to a wooden floor yields the most rapid T₂₀ reductions (up to −1.75 s), ceiling treatments deliver the greatest STI and C₅₀ gains (e.g., STI increases of +0.16), and high-absorption walls maximize privacy metrics (D_2,S and L_p,A,S,4m). A linear regression model further predicted the STI from T₂₀, total absorption (Sabins), and room volume, with an 84.9% conditional R², enabling ±0.03 accuracy without specialized testing. These findings provide empirically derived, surface-specific “first-move” guidelines for architects and acousticians, underscoring the necessity of integrating acoustics early in museum design to balance auditory and visual objectives and enhance the visitor experience. Full article

Exercise plays a key role in managing type 1 diabetes mellitus (T1DM), and virtual reality (VR)-based exercise offers an innovative solution to increase motivation and deliver meaningful health benefits to patients who are often hesitant to engage in physical activity. The purpose of this study was to assess the acceptability, usability, intention for future use, and preference of a VR-based cycling application, as well as to investigate the effects of VR-based exercise on the physiological, biochemical, and psychological parameters of individuals with T1DM compared to conventional exercise. This study represents a preliminary investigation with a small sample size of 11 patients with T1DM. Each participant underwent two 20 min low-intensity exercise trials. One session involved conventional cycling on a stationary ergometer, while the other used a VR-based cycling application. The two exercise conditions were conducted 48 h apart, without a formal washout period. According to the results, high scores were observed for preference, acceptance, and usability of the VR-based cycling application, and statistically significant improvements in mood and enjoyment were observed following the VR-based cycling compared to conventional cycling. Additionally, while no statistically significant differences were found in physiological parameters (blood glucose, blood pressure, and heart rate) between the two conditions, the VR-based session showed a trend toward greater reductions. In conclusion, the use of VR technology in the field of cycling exercise has great significance in improving the mood and engagement of T1DM patients in exercise programs, providing a user-friendly and well-accepted VR cycling application; subsequently, it has also shown preliminary potential for the regulation of biological parameters. Healthcare professionals could easily expand exercise protocols with the strengths of the VR technologies along with other health-related programs. Full article

Background: Chronic musculoskeletal disorders (CMDs) represent a leading cause of global disability and diminished quality of life, and they are often resistant to conventional physiotherapy. Emerging technologies such as virtual reality (VR), augmented reality (AR), and exergaming are increasingly used to enhance rehabilitation outcomes, yet their comparative effectiveness remains unclear. Objective: To systematically evaluate the effectiveness of VR, AR, and exergaming interventions in improving pain, function, balance, and psychological outcomes among adults with CMDs. Methods: This systematic review and exploratory meta-analysis followed PRISMA 2020 guidelines and was prospectively registered (PROSPERO: CRD42024589007). A structured search was conducted in PubMed, Cochrane CENTRAL, Scopus, and PEDro (up to 1 May 2025). Eligible studies were randomized controlled trials (RCTs) involving adults (≥18 years) with CMDs receiving VR, AR, or exergaming-based rehabilitation. Risk of bias was assessed using the PEDro scale and the Downs and Black checklist. Where feasible, standardized mean differences (SMDs) for pain outcomes were pooled using a random-effects model. Results: Thirteen RCTs (n = 881 participants) met the inclusion criteria. Interventions spanned immersive VR, AR overlays, exergaming platforms (e.g., Kinect, Wii), and motion-tracking systems. Pain, function, and quality of life improved in most studies. An exploratory meta-analysis of eight RCTs (n = 610) yielded a significant pooled effect favoring VR/AR interventions for pain reduction (SMD = −1.14; 95% CI: −1.63 to −0.75; I² = 0%). Exergaming showed consistent improvements in physical performance, while immersive VR was more effective for kinesiophobia and psychological outcomes. AR was underrepresented, with only one study. Risk of bias was generally low; however, publication bias could not be excluded due to limited funnel plot power (n < 10). Conclusions: VR, AR, and exergaming are effective adjuncts to conventional rehabilitation for CMDs, improving pain and function with high patient adherence. Nevertheless, gaps in long-term data, economic evaluation, and modality comparison persist. Future RCTs should address these limitations through standardized, inclusive, and longitudinal design. Full article

With the increasing prominence of the energy crisis and environmental problems, microgrid technology has received widespread attention as an important technical means to improve the stability and reliability of new energy access. Focusing on the latest development of microgrid operation control technology, this paper combs and summarizes the related research at home and abroad, including the key technologies of microgrid optimization operation, power prediction and virtual synchronous active support control technology, and points out their advantages and limitations. First, this review describes the concept and structure of microgrids, including components such as distributed power sources, energy storage devices, energy conversion devices and loads. Then, the microgrid optimization operation technologies are analyzed in detail, including energy management optimization algorithms for efficient use of energy and cost reduction. Focusing on microgrid power forecasting techniques, including wind energy and PV power forecasting and load forecasting, the contributions and impacts of different power forecasting methods are summarized. Furthermore, the inverter control strategies and the stability mechanism of the virtual synchronous generator (VSG) active support control technology are investigated. Finally, synthesizing domestic and international microgrid development experience, this review summarizes the current state-of-the-art technologies, analyzes the advantages and limitations of these key technologies (including optimization scheduling, power prediction and VSG-based active support control) and highlights the necessity of their continuous improvement to provide a solid foundation for promoting the widespread application and sustainable development of microgrid technology. Full article

Cloud computing is a virtualized and distributed computing model that provides resources and services based on demand and self-service. Resource failure is one of the major challenges in cloud computing, and there is a need for fault tolerance mechanisms. This paper addresses the issue by proposing a multi-objective radial kernelized federated learning-based fault-tolerant scheduling (MRKFL-FTS) technique for allocating multiple IoT requests or user tasks to virtual machines in cloud IoT-based environments. The MRKFL-FTS technique includes Cloud RAN (C-RAN) and Virtual RAN (V-RAN). The proposed MRKFL-FTS technique comprises four entities, namely, IoT devices, cloud servers, task assigners, and virtual machines. Each IoT device generates several service requests and sends them to the control server. At first, radial kernelized support vector regression is applied in the local training model to identify resource-efficient virtual machines. After that, locally trained models are combined, and the resulting model is fed into the global aggregation model. Finally, using a weighted round-robin method, the task assigner allocates incoming IoT service requests to virtual machines. This approach improves resource awareness and fault tolerance in scheduling. The quantitatively analyzed results show that the MRKFL-FTS technique achieved an 8% improvement in task scheduling efficiency and fault prediction accuracy, a 36% improvement in throughput, and a 14% reduction in makespan and time complexity. In addition, the MRKFL-FTS technique resulted in a 13% reduction in response time. The energy consumption of the MRKFL-FTS technique is reduced by 17% and increases the scalability by 8% compared to conventional scheduling techniques. Full article

This research explores how artificial intelligence (AI) can be leveraged to optimize packaging design, reduce operational costs, and enhance sustainability in e-commerce. As packaging waste and shipping inefficiencies grow alongside global online retail demand, traditional methods for determining box size, material use, and logistics planning have become economically and environmentally inadequate. Using a three-phase framework, this study integrates data-driven diagnostics, AI modeling, and real-world validation. In the first phase, a systematic analysis of current packaging inefficiencies was conducted through secondary data, benchmarking, and cost modeling. Findings revealed significant waste caused by over-packaging, suboptimal box-sizing, and poor alignment between product characteristics and logistics strategy. In the second phase, a random forest (RF) machine learning model was developed to predict optimal packaging configurations using key product features: weight, volume, and fragility. This model was supported by AI simulation tools that enabled virtual testing of material performance, space efficiency, and damage risk. Results demonstrated measurable improvements in packaging optimization, cost reduction, and emission mitigation. The third phase validated the AI framework using practical case studies—ranging from a college textbook to a fragile kitchen dish set and a high-volume children’s bicycle. The model successfully recommended right-sized packaging for each product, resulting in reduced material usage, improved shipping density, and enhanced protection. Simulated cost-saving scenarios further confirmed that smart packaging and AI-generated configurations can drive efficiency. The research concludes that AI-based packaging systems offer substantial strategic value, including cost savings, environmental benefits, and alignment with regulatory and consumer expectations—providing scalable, data-driven solutions for e-commerce enterprises such as Amazon and others. Full article

The behavior of the cast-in-place continuously reinforced concrete (CRC) bus pad applied to bus stop pavement in a central bus-only lane was experimentally analyzed under environmental and moving vehicle loads, and the early-age performance of the CRC bus pad was evaluated using experimental data and finite element analysis results. Using various measurement sensors, the concrete slab strain, longitudinal steel bar strains, horizontal and vertical displacements, and crack behavior of the CRC bus pad due to environmental loads were measured, and the dynamic responses of the concrete slab and steel bars due to moving vehicle loads were also measured. Additionally, a method for converting strain gauge measurements of a cracked concrete slab to the strain of an uncracked concrete slab was also proposed. Under environmental loads, the range of stresses acting on the steel bars and the bond between concrete and steel bars were analyzed to be appropriate for ensuring excellent performance of the CRC bus pad. The crack widths and vertical and longitudinal displacements of the CRC bus pad were found to have no effect on the pavement performance. Within the vehicle velocity range used in this experiment, the strains of the slab and steel bars as the vehicle passed through the CRC bus pad were virtually independent of the vehicle velocity and were within a range that did not cause any reduction in pavement performance. This study confirmed that the CRC bus pad has excellent performance and can replace asphalt concrete bus stop pavement or jointed concrete bus pad. Full article