Search Results (735)

Objective: This study aimed to improve the understanding of the lives of patients with chronic neuropathic pain planned for invasive motor cortex stimulation (iMCS) and assess their expectations towards this intervention and its impact. Methods: Semi-structured face-to-face interviews were conducted until saturation of data was reached. Patients were recruited from one university medical center in the Netherlands. All interviews were audio-recorded, transcribed verbatim, and subjected to thematic analysis using iterative and inductive coding by two researchers independently. Results: Fifteen patients were included (11 females; mean age 63 ± 9.4 yrs). Analysis of the coded interviews revealed seven themes: (1) the consequences of living with chronic neuropathic pain; (2) loss of autonomy and performing usual activities; (3) balancing energy and mood; (4) intimacy; (5) feeling understood and accepted; (6) meaning of life; and (7) the expectations of iMCS treatment. Conclusions: This is the first qualitative study that describes the suffering of patients with chronic neuropathic pain, and their expectations prior to invasive brain stimulation. Significant themes in the lives of patients with chronic pain have been brought to light. The findings strengthen communication between physicians, caregivers, and patients. Practice Implications: The insights gathered from the interviews create a structured framework for comprehending the values and expectations of patients living with central pain and reveal the impact of symptoms due to the central pain. This knowledge improves the communication between physicians and caregivers on one side and the patient on the other side. Furthermore, the framework enhances the capacity for shared decision-making, particularly in managing expectations related to iMCS. Full article

The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of a commercial motor–generator system in high-demand applications. A baseline model of a permanent magnet synchronous motor (PMSM) was developed using MotorCAD 2023^® software, which was supported by reverse engineering techniques to accurately replicate the motor’s physical and thermal characteristics. Subsequently, multiple cooling strategies were simulated under consistent operating conditions to assess their effectiveness. These strategies include conventional axial water jackets as well as advanced oil-based methods such as shaft cooling and direct oil spray to the windings. The integration of these systems in hybrid configurations was also explored to maximize thermal efficiency. Simulation results reveal that hybrid cooling significantly reduces the temperature of critical components such as stator windings and permanent magnets. This reduction in thermal stress improves current efficiency, power output, and torque capacity, enabling reliable motor operation across a broader range of speeds and under sustained high-load conditions. The findings highlight the effectiveness of hybrid cooling systems in optimizing both thermal management and operational performance of electric machines. Full article

Boda boda motorbike taxis are a primary mode of transport in Nairobi, Kenya, and a major source of urban air pollution. This study investigates the environmental and electrical grid impacts of electrifying Nairobi’s boda boda fleet. Using real-world tracking data from 118 motorbikes, we simulated the effects of a full-scale transition from internal combustion engine (ICE) vehicles to electric motorbikes. We analysed various scenarios, including different battery charging strategies (swapping and home charging), motor efficiencies, battery capacities, charging rates, and the potential for solar power offsetting. The results indicate that electrification could reduce daily ${\mathrm{CO}}_2$ emissions by approximately 85% and eliminate tailpipe particulate matter emissions. However, transitioning the entire country’s fleet would increase the national daily energy demand by up to 6.85 GWh and could introduce peak grid loads as high as 2.40 GW, depending on the charging approach and vehicle efficiency. Battery swapping was found to distribute the grid load more evenly and better complement solar power integration compared to home charging, which concentrates demand in the evening. This research provides a scalable, data-driven framework for policymakers to assess the impacts of transport electrification in similar urban contexts, highlighting the critical trade-offs between environmental benefits and grid infrastructure requirements. Full article

This study presents the development and validation of an AI-based system for detecting chainsaw sounds, integrated into a fixed-wing VTOL UAV. The system employs a convolutional neural network trained on log-mel spectrograms derived from four sound classes: chainsaw, music, electric drill, and human voices. Initial validation was performed through ground testing. Acoustic data acquisition is optimized during cruise flight, when wing-mounted motors are shut down and the rear motor operates at 40–60% capacity, significantly reducing noise interference. To address residual motor noise, a preprocessing module was developed using reference recordings obtained in an anechoic chamber. Two configurations were tested to capture the motor’s acoustic profile by changing the UAV’s orientation relative to the fixed microphone. The embedded system processes incoming audio in real time, enabling low-latency classification without data transmission. Field experiments confirmed the model’s high precision and robustness under varying flight and environmental conditions. Results validate the feasibility of real-time, onboard acoustic event detection using spectrogram-based deep learning on UAV platforms, and support its applicability for scalable aerial monitoring tasks. Full article

Aiming at the problems of low thermal analysis efficiency and high computational cost of traditional computational fluid dynamics (CFD) methods for modular fault-tolerant permanent magnet synchronous motors (MFT-PMSMs) under complex working conditions, this paper proposes a fast modeling and calculation method of motor temperature field based on a high-efficiency and high-precision network algorithm. In this method, the physical structure of the motor is equivalent to a parameterized network model, and the computational efficiency is significantly improved by model partitioning and Fourth-order Runge Kutta method. The temperature change of the cooling medium is further considered, and the temperature rise change of the motor at different spatial positions is effectively considered. Based on the finite element method (FEM), the space loss distribution under rated, single-phase open circuit and overload conditions is obtained and mapped to the thermal network nodes. Through the transient thermal network solution, the rapid calculation of the temperature rise law of key components such as windings and permanent magnets is realized. The accuracy of the thermal network model was verified by using fluid-structure coupling simulation and prototype test for temperature analysis. This method provides an efficient tool for thermal safety assessment and optimization in the motor fault-tolerant design stage, especially for heat capacity check under extreme conditions and fault modes. Full article

Background/Objectives: Parkinson’s disease (PD) is a neurodegenerative disorder that impairs mobility. Treadmill training (TT) is a common rehabilitation strategy for improving gait parameters in individuals with PD. This systematic review evaluated the effectiveness of TT in improving motor function, walking ability, and overall functional mobility in PD patients. Methods: We compared TT to other forms of gait and motor rehabilitation, including conventional and robotic gait training. Trials that compared a treadmill training group with a non-intervention group were excluded from this review. We searched multiple databases for RCTs involving Parkinson’s patients until January 2025. The primary outcomes were motor function (UPDRS-III) and walking ability (6 MWT and TUG test). Results: We identified 285 articles; 199 were excluded after screening. We assessed the full text of 86 articles for eligibility, and 13 RCTs met the inclusion criteria. Some of them were included in the meta-analysis. The TT group showed a significant improvement in UPDRS-III scores [mean difference (MD): −1.36 (95% CI: −2.60 to −0.11)] and greater improvement in TUG performance [MD, −1.75 (95% CI: −2.69 to −0.81)]. No significant difference in walking capacity as assessed through the 6 MWT was observed [MD: 26.03 (95% CI: −6.72 to 58.77). Conclusions: The current study suggests that TT is effective in improving the motor symptoms and functional mobility associated with PD. Further studies are needed to develop protocols that consider the patients’ clinical characteristics, disease stage, exercise tolerance, and respiratory function. Full article

Background/Objectives: Motor creativity is a vital component of preschoolers’ growth and development. However, its underlying determinants remain largely underexplored. This study investigates the interrelationship among playful behavior, social profile, and motor creativity in preschool children, emphasizing its implications for holistic health and development. Methods: A total of 200 children and their kindergarten teachers from Greece participated in the study. The Children’s Playfulness Scale (CPS) was employed to assess the children’s playfulness, while a sociometric test was used to evaluate their social standing within peer groups. Motor creativity was measured through TCAM, a performance-based test focusing on fluency, imagination, and originality. Results: The findings revealed that the dimensions of playful behavior, particularly motor and social playfulness, significantly and positively influenced motor creativity, a core component of physical and mental health in early childhood. Conversely, certain aspects of social behavior had a negative association with imaginative capacities. Conclusions: The study underscores the critical role of movement-based playful activities in fostering children’s physical, emotional, cognitive, and social health. It highlights the need for educators to design developmentally appropriate motor play activities that cultivate creativity and social integration, promoting a balanced and health-oriented early education framework. The results contribute to educational policy and practice by reinforcing the importance of structured motor play in supporting preschoolers’ well-being and comprehensive development. Full article

Objective: The objective of the study was to investigate the relationship between the level of physical activity and body composition, and the levels of motor skills and strength in overweight and obese men. Methods: The research involved 64 men. Body composition, physical activity, motor control, Motor Control Test (MCT), and strength variables were evaluated. Body composition was assessed by DXA, and the participants were classified into two groups according to the percentage of total fat mass: greater and less than 27.65%. Physical activity was assessed using accelerometry, and motor control was measured with posturography, which provided a composite score of motor performance and postural control effectiveness. Strength was assessed using hand, leg, and back dynamometers. Results: The participants with a higher percentage of body fat had a lower DSI (Dynamic Strength Index) (p < 0.001) and significantly reduced PAL (physical activity level) and energy expenditure (p < 0.001). No significant differences were found in the muscle strength of the upper limbs (p = 0.06) and lower limbs (p = 0.419). With regard to MCT, there was a significant difference between groups in the backward direction (p = 0.041), with the group with the highest percentage of body fat showing lower values. Conclusions: Individuals with a higher percentage of body fat tend to have lower levels of strength, physical activity, and energy expenditure, which can lead to impaired balance. The findings highlight the need for targeted interventions to improve body composition and levels of strength and physical activity, with a positive impact on general health and quality of life. Emphasis should be placed on improving physical activity levels in male individuals with a higher percentage of fat mass to improve their body composition and dynamic strength levels, which are beneficial to life, particularly to help improve postural control. Full article

This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. The proposed platform features a dual-mode sensor array for early fire recognition, motorized ventilation units for rapid smoke extraction, and a 360° directional nozzle for targeted agent discharge using a residue-free clean extinguishing agent. Experimental trials demonstrated an average fire detection time of 5.8 s and complete flame suppression within 13.2 s, with 90% smoke clearance achieved in under 95 s. No false positives were recorded during non-fire simulations, and the system remained fully functional under simulated cloud communication failure, confirming its edge-resilient architecture. A probabilistic risk analysis based on ISO 31000 and NFPA 551 frameworks showed risk reductions of 75.6% in life safety, 58.0% in property damage, and 67.1% in business disruption. The system achieved a composite risk reduction of approximately 73%, shifting the operational risk level into the ALARP region. These findings demonstrate the system’s capacity to provide proactive, energy-efficient, and spatially targeted fire response suitable for high-value infrastructure. The modular design and SmartThings Edge integration further support scalable deployment and real-time system intelligence, establishing a strong foundation for future adaptive fire protection frameworks. Full article

Thermal control in rolling mills motors is gaining importance as more and more hard-to-deform steel grades are rolled. The capabilities of diagnostics monitoring also expand as digital IIoT-based technologies are adopted. Electrical drives in modern rolling mills are based on synchronous motors with frequency regulation. Such motors are expensive, while their reliability impacts the metallurgical plant output. Hence, developing the on-line temperature monitoring systems for such motors is extremely urgent. This paper presents a solution applying to synchronous motors of the upper and lower rolls in the horizontal roll stand of plate mill 5000. The installed capacity of each motor is 12 MW. According to the digitalization tendency, on-line monitoring systems should be based on digital shadows (coordinate observers) that are similar to digital twins, widely introduced at metallurgical plants. Modern reliability requirements set the continuous temperature monitoring for stator and rotor windings and iron core. This article is the first to describe a method for calculating thermal loads based on the data sets created during rolling. The authors have developed a thermal state observer based on four-mass model of motor heating built using the Simscape Thermal Models library domains that is part of the MATLAB Simulink. Virtual adjustment of the observer and of the thermal model was performed using hardware-in-the-loop (HIL) simulation. The authors have validated the results by comparing the observer’s values with the actual values measured at control points. The discrete masses heating was studied during the rolling cycle. The stator and rotor winding temperature was analysed at different periods. The authors have concluded that the motors of the upper and lower rolls are in a satisfactory condition. The results of the study conducted generally develop the idea of using object-oriented digital shadows for the industrial electrical equipment. The authors have introduced technologies that improve the reliability of the rolling mills electrical drives which accounts for the innovative development in metallurgy. The authors have also provided recommendations on expanded industrial applications of the research results. Full article

Background: Motor performance in childhood predicts physical fitness, cognitive capacity, socio-emotional development, and academic success. Parenting styles are especially important to such performance in the preschool period, as children’s gross motor abilities are shaped in part by their interactions with parents. Young children’s physical activity is also declining as they spend more time on screens. Methods: This quantitative survey-based study examined the relationships among 252 preschoolers’ gross motor skills, their tendency to become addicted to digital games, and their parents’ parenting styles. Results: The sampled preschoolers’ gross motor skill development and game addiction tendencies were both low, while the participating parents reported high levels of democratic and overprotective parenting attitudes, low levels of authoritarian ones, and moderate levels of permissive ones. Motor skills were not associated with children’s addiction tendency or parents’ democratic (also known as authoritative), authoritarian, or permissive styles. However, overprotective parenting was positively and significantly associated with gross motor skill scores. While no significant relationship was found between children’s digital game addiction tendencies and their parents’ adoption of a democratic parenting style, such tendencies were positively and statistically correlated with the authoritarian and permissive parenting styles. One dimension of such tendencies, constant gameplay, was also positively and significantly correlated with overprotective parenting. Conclusions: Although the participating children’s digital game addiction tendencies were low, the findings indicate that parents and carers should guide children to reduce their screen time and promote increased interaction with their surroundings and other people to mitigate screen time’s known negative effects on gross motor coordination. Full article

Variable-speed reciprocating compressors (VSRCs) have been increasingly used in domestic refrigeration due to their ability to modulate cooling capacity and reduce energy consumption. A detailed understanding of performance-limiting factors such as volumetric and exergetic inefficiencies is essential for optimizing their operation. An experimentally validated simulation model was developed using GT-SUITE to analyze a VSRC operating with R-600a across speeds from 1800 to 6300 rpm. Volumetric inefficiencies were quantified using a stratification methodology, while an exergy-based approach was adopted to assess the main sources of thermodynamic inefficiency in the compressor. Unlike traditional energy analysis, exergy analysis reveals where and why irreversibilities occur, linking them directly to power consumption and providing a framework for optimizing design. Results reveal that neither volumetric nor exergy efficiency varies monotonically with compressor speed. At low speeds, exergetic losses are dominated by the electrical motor (up to 19% of input power) and heat transfer (up to 13.5%). Conversely, at high speeds, irreversibilities from fluid dynamics become critical, with losses from discharge valve throttling reaching 5.8% and bearing friction increasing to 6.5%. Additionally, key volumetric inefficiencies arise from piston–cylinder leakage, which causes up to a 4.5% loss at low speeds, and discharge valve backflow, causing over a 5% loss at certain resonant speeds. The results reveal complex speed-dependent interactions between dynamic and thermodynamic loss mechanisms in VSRCs. The integrated modeling approach offers a robust framework for diagnosing inefficiencies and supports the development of more energy-efficient compressor designs. Full article

Urban mobility resilience plays a central role in sustainable urban planning discussions, especially considering the challenges of extreme events, climate change, and the increasing scarcity of fossil fuels. This study evaluates urban mobility resilience in Petrópolis (RJ), incorporating socio-spatial heterogeneity and energy vulnerability. This research fills methodological gaps in the literature by proposing a composite resilience index that integrates technical, socioeconomic, and fossil fuel dependency variables within a robust multicriteria framework. We selected eleven variables relevant to urban mobility and organized them into inference blocks. We normalized the variables using Gaussian functions, respecting their maximization or minimization characteristics. We applied the Analytic Hierarchy Process (AHP) to assign weights to the criteria and then aggregated and ranked the results using multicriteria analysis. The final index represents the adaptive capacity of urban territories facing the energy crisis, and we applied it spatially to the neighborhoods of Petrópolis. The analysis identified a significant concentration of neighborhoods with low resilience, particularly in quadrants, combining deficiencies in public transportation, high dependence on fossil fuels, and socioeconomic constraints. Factors such as limited pedestrian access, insufficient motorized public transport coverage, and a high proportion of elderly residents emerged as significant constraints on urban resilience. Intervention strategies that promote active mobility, improve accessibility, and diversify transportation modes proved essential for strengthening local resilience. The results emphasize the urgent need for public policies to reduce energy vulnerability, foster active mobility, and promote equity in access to transportation infrastructure. Full article

Robotic arms are used in a wide range of industrial and medical applications. However, for research and education, users often face a trade-off between costly commercial solutions with no adaptability and open-source alternatives that lack usability and functionality. In education, this problem is exacerbated by the prohibitive cost of commercial systems or simplifications that distort learning. Thus, we present HELENE, an open-source robot with six degrees of freedom, closed-loop position control, and robot operating system (ROS) integration. The modular design of the robot, printed on a commercial 3D printer, and its integrated custom electronics allow for easy customization for research purposes. The joints are driven by standard stepper motors with closed-loop position control using absolute encoders. The ROS integration guarantees widespread control options and integration into existing environments. Our prototype, tested in accordance with ISO 9283, has a small positional accuracy error of 8.4 mm and a repeatability error of only 0.87 mm with a load capacity of 500 g at a reach of 432 mm. Ten prototypes were built and used in various research and education applications, demonstrating the versatile applicability of this open-source robot, closing the gap between reliable commercial systems and flexible open-source solutions. Full article

This paper presents the design and development of a new modular wall-climbing robot—Modular Wall Climbing-1 (MC-1)—for solving the problem of autonomous wall switching observed in wall-climbing robots. Each modular robot is capable of independently adhering to vertical surfaces and maneuvering, making it a fully autonomous robotic system. Multiple modules of MC-1 are connected by an electromagnet-based magnetic attachment method, and wall transitions are achieved using a servo motor mechanism. Moreover, an ultrasonic sensor is employed to measure the unknown wall-inclination angle. Mechanical analysis is conducted for MC-1 at rest individually and in combination to determine the required suction force. Experimental investigations are performed to assess the robot’s crawling ability, loading capacity, and wall-transition performance. The results demonstrate that the MC-1 robot is capable of multi-angle wall transitions for executing multiple tasks. It provides a new approach for wall-climbing robots to collaborate during wall transitions through a quick attachment-and-disassembly device and an efficient wall detection method. Full article