Search Results (12,663)

High-performance electrical contact materials are crucial for electric power systems, new energy vehicles, and rail transportation, as their properties directly impact the reliability and safety of electronic devices. Enhancing these materials not only improves energy efficiency but also offers notable environmental and economic advantages. However, traditional composite contact materials often suffer from poor dispersion of the reinforcing phase, which restricts further performance improvement. Graphene (G), with its unique two-dimensional structure and exceptional electrical, mechanical, and tribological properties, is considered an ideal reinforcement for metal matrix composites. Yet, its tendency to agglomerate poses a significant challenge to achieving uniform dispersion. To overcome this, the study introduces a dual approach: modulation of the zeta potential (ζ) in the silver-plated liquid to enhance G’s dispersion stability, and concurrent optimization of the composite electrodeposition process. Experimental results demonstrate that this synergistic strategy enables the uniform distribution of G within the silver matrix. The resulting silver–graphene (Ag-G) composite coatings exhibit outstanding overall performance at both micro and macro levels. This work offers a novel and effective pathway for the design of advanced electrical contact materials with promising application potential. Full article

Stroke is one of the leading causes of disability worldwide. Its sequelae require early, intensive, and repetitive rehabilitation, but is often ineffective due to a lack of patient motivation. Gamification has been incorporated in recent years as a response to this issue. The aim of incorporating games is to motivate patients to perform therapeutic exercises. This study presents PACTUS, a new version of a gamified device for stroke neurorehabilitation. Using a series of colored cards, a touchscreen station, and a sensorized handle with an RGB sensor, patients can interact with three games specifically programmed to work on different areas of neurorehabilitation. In addition to presenting the technical design (including energy consumption and sensor signal processing), the results of an observational study conducted with neurological patients, healthy older adults, and caregivers (who also completed the System Usability Scale) are also presented. This usability, safety, and satisfaction study provided an assessment of the device for future iterations. The inclusion of the experiences of the three groups (patients, caregivers, and older adults) provided a more comprehensive and integrated view of the device, enriching our understanding of its strengths and limitations. Although the results were preliminarily positive, areas for improvement were identified. Full article

In massive multiple-input and multiple-output (mMIMO) systems, superimposed channel state information (CSI) feedback is developed to improve the occupation of uplink bandwidth resources. Nevertheless, the interference from this superimposed mode degrades the recovery performance of both downlink CSI and uplink data sequences. Although machine learning (ML)-based methods effectively mitigate superimposed interference by leveraging the multi-domain features of downlink CSI, the complex interactions among network model parameters cause a significant burden on system resources. To address these issues, inspired by sensing-assisted communication, we propose a novel superimposed CSI feedback method assisted by inactive sensing information that previously existed but was not utilized at the base station (BS). To the best of our knowledge, this is the first time that inactive sensing information is utilized to enhance superimposed CSI feedback. In this method, a new type of modal data, different from communication data, is developed to aid in interference suppression without requiring additional hardware at the BS. Specifically, the proposed method utilizes location, speed, and path information extracted from sensing devices to derive prior information. Then, based on the derived prior information, denoising processing is applied to both the delay and Doppler dimensions of downlink CSI in the delay—Doppler (DD) domain, significantly enhancing the recovery accuracy. Simulation results demonstrate the performance improvement of downlink CSI and uplink data sequences when compared to both classic and novel superimposed CSI feedback methods. Moreover, against parameter variations, simulation results also validate the robustness of the proposed method. Full article

While synthetic biology has traditionally focused on creating biological systems often through genetic engineering, emerging technologies, for example, implantable pacemakers with integrated piezo-electric and tribo-electric materials are beginning to enlarge the classical domain into what we call symbiotic synthetic biology. These devices are permanently attached to a body, although non-living or genetically unaltered, and closely mimic biological behavior by harvesting biomechanical energy and providing functions, such as autonomous heart pacing. They form active interfaces with human tissues and operate as hybrid systems, similar to synthetic organs. In this context, the present paper first presents a short summary of previous in vivo studies on piezo-electric composites in relation to their deployment as battery-less pacemakers. This is then followed by a summary of a recent theoretical work using a damped harmonic resonance model, which is being extended to mimic the functioning of such devices. We then extend the theoretical study further to include new solutions and obtain a sum rule for the power output per cycle in such systems. In closing, we present our quantitative understanding to explore the modulation of the quantum vacuum energy (Casimir effect) by periodic body movements to power pacemakers. Taken together, the present work provides the scientific foundation of the next generation bio-integrated intelligent implementation. Full article

Exhaled breath (EB) contains numerous volatile organic compounds (VOCs) that can reflect pathological metabolic processes, making breath analysis a promising non-invasive diagnostic approach. In particular, volatile aldehydes and ketones have been identified as disease biomarkers in EB. Gas sensors are expected to play a crucial role in the diagnosis of numerous diseases at an early stage. Among the various available approaches, sensors stand out as especially attractive tools for diagnosing diseases such as lung cancer (LC) and diabetes, due to their affordability and operational simplicity. There is an urgent need in the field of disease detection for the development of affordable, non-invasive, and user-friendly sensors capable of detecting various biomarkers. Devices of the new generation should also demonstrate high repeatability of measurements and extended operational stability of the employed sensors. Due to these demands, the past few years have seen significant advancements in the development and implementation of electronic noses (ENs), which are composed of an array of sensors for the determination of VOCs present in EB. To meet these requirements, the development and integration of advanced receptor coatings on sensor transducers is essential. These coatings include nanostructured materials, molecularly imprinted polymers, and bioreceptors, which collectively enhance selectivity, sensitivity, and operational stability. However, reliable biomarker detection in point-of-care (PoC) mode remains a significant challenge, constrained by several factors. This review provides a comprehensive and critical evaluation of recent studies demonstrating that the detection of VOCs using gas sensor platforms enables disease detection and can be implemented in PoC mode. Full article

Swarm Robotics (SR) is a relatively new field, inspired by the collective intelligence of social insects. It involves using local rules to control and coordinate large groups (swarms) of relatively simple physical robots. Important tasks that robot swarms can handle include demining, search, rescue, and cleaning up toxic spills. Over the past decade, the research effort in the field of Swarm Robotics has intensified significantly in terms of hardware, software, and systems integrated developments, yet significant challenges remain, particularly regarding standardization, scalability, and cost-effective deployment. To contextualize the state of Swarm Robotics technologies, this paper provides a systematic literature review (SLR) of Swarm Robotic technologies published from 2014 to 2024, with an emphasis on how hardware and software subsystems have co-evolved. This work provides an overview of 40 studies in peer-reviewed journals along with a well-defined and replicable systematic review protocol. The protocol describes criteria for including and excluding studies and outlines a data extraction approach. We explored trends in sensor hardware, actuation methods, communication devices, and energy systems, as well as an examination of software platforms to produce swarm behavior, covering meta-heuristic algorithms and generic middleware platforms such as ROS. Our results demonstrate how dependent hardware and software are to achieve Swarm Intelligence, the lack of uniform standards for their design, and the pragmatic limits which hinder scalability and deployment. We conclude by noting ongoing challenges and proposing future directions for developing interoperable, energy-efficient Swarm Robotics (SR) systems incorporating machine learning (ML). Full article

Hydrogels are hydrophilic, soft polymer networks with high water content and mechanical properties that are tunable; they are also biocompatible. Therefore, as biomaterials, they are of interest to modern medicine. In this review, the main applications of hydrogels in essential clinical applications are discussed. Chemical, physical, or hybrid crosslinking of either synthetic or natural polymers allow for the precise control of hydrogels’ physicochemical properties and their specific characteristics for certain applications, such as stimuli-responsiveness, drug retention and release, and biodegradability. Hydrogels are employed in gynecology to regenerate the endometrium, treat infections, and prevent pregnancy. They show promise in cardiology in myocardial infarction therapy through injectable scaffolds, patches in the heart, and medication delivery. In rheumatoid arthritis, hydrogels act as drug delivery systems, lubricants, scaffolds, and immunomodulators, ensuring effective local treatment. They are being developed, among other applications, as antimicrobial coatings for stents and radiotherapy barriers for urology. Ophthalmology benefits from the use of hydrogels in contact lenses, corneal bandages, and vitreous implants. They are used as materials for chemoembolization, tumor models, and drug delivery devices in cancer therapy, with wafers of Gliadel presently used in clinics. Applications in abdominal surgery include hydrogel-coated meshes for hernia repair or Janus-type hydrogels to prevent adhesions and aid tissue repair. Results from clinical and preclinical studies illustrate hydrogels’ diversity, though problems remain with mechanical stability, long-term safety, and mass production. Hydrogels are, in general, next-generation biomaterials for regenerative medicine, individualized treatment, and new treatment protocols. Full article

Terminal forensics in large mobile networks is a vital activity for identifying compromised devices and analyzing malicious actions. In contrast, the study described here begins with the domain of terminal forensics as the primary focus, rather than the threat itself. This paper proposes a new multi-criteria decision-making (MCDM) model that integrates complex picture fuzzy sets (CPFS) with the combinative distance-based assessment (CODAS), referred to throughout as complex picture fuzzy CODAS (CPF-CODAS). The aim is to assist in forensic analysis for detecting mobile botnet command and control (C&C) systems. The CPF-CODAS model accounts for the uncertainty, hesitation, and complex numerical values involved in expert decision-making, using degrees of membership as positive, neutral, and negative values. An illustrative forensic case study is constructed where three mobile devices are evaluated by three cybersecurity professionals based on six key parameters related to botnet activity. The results demonstrate that the model can effectively distinguish suspicious devices and support the use of the CPF-CODAS approach in terminal forensics of mobile networks. The robustness, symmetry, and advantages of this model over existing MCDM methods are confirmed through sensitivity and comparison analyses. In conclusion, this paper introduces a novel probabilistic decision-support tool that digital forensic specialists can incorporate into their workflow to proactively identify and prevent actions of mobile botnet C&C servers. Full article

Objective: The objective of this study was to evaluate the influence of heated CO₂ and forced-air warming on perioperative temperature in a rabbit model of prolonged pneumoperitoneum. Methods: Thirty-seven New Zealand rabbits, weighing an average of 3.85 kg, were divided into four experimental groups with different warming methods: the control group (CT) underwent unheated pneumoperitoneum (22 °C); another group (HP) underwent pneumoperitoneum with heated CO (36 °C); a third group (FA) underwent unheated pneumoperitoneum but with the use of a forced-air warming device (43 °C) positioned between the animal and the surgical table; and the fourth group of animals (HP + FA) underwent heated pneumoperitoneum with the use of a forced-air warming device. For all animals, the pneumoperitoneum was maintained for 120 min. The animals’ temperature was measured immediately before sedation (I0), at the beginning of insufflation (I1, which was mandatory 60 min after I0), every 15 min during pneumoperitoneum (I2–I9), and 15 min after desufflation (I10). The data were analyzed and compared by Student’s t-test, ANOVA, Pearson’s correlation and linear regression, considering p < 0.05 as significant. Results: There was no difference between the groups regarding weight, temperature at I0, temperature at I1, volume of CO used, or Δt (I0–I1). In all groups, there was a decrease in temperature when comparing the final instants (I9 or I10) with the initial instants (I0 or I1) of the study (p < 0.05). However, the groups that used the forced-air warming (FA and HP + FA) had a smaller decrease in temperature and a higher final temperature, with no difference between these groups. Furthermore, these groups recovered their temperature better after deflation (from I9 to I10). For all groups, a correlation between time and temperature was observed, but in the groups that used a heated mattress, the slope of the linear regression line was smaller. Conclusions: The use of a forced-air warming system (combined or not with the use of heated CO) reduced the heat loss during prolonged pneumoperitoneum in a small animal model. This warming method is recommended for preventing hypothermia in laparoscopic surgeries with expected prolonged surgical time. Full article

In order to solve the problem encountered by traditional potato–stem separation devices, that is, they cannot meet the requirements when installed in small-scale harvesters, a new type of vertical differential roller potato–stem separation device was developed. The device features a compact structure and simultaneously possesses both separating and conveying functions. Through the analysis of the separation force between potato and stem, the structure and parameters of the separation device were determined. The simulation and the field test of the potato–stem separation process were carried out with the vertical differential roller speed, the vertical differential roller gap width and the conveyor chain speed as the influencing factors. The simulation test analysed the influence law of different working parameters on the performance of potato–stem separation. The field test revealed the order of the effects of various factors on the impurity rate and skin-breaking rate, concluding that the optimal combination of operational parameters was a vertical differential roller rotational speed of 6 s⁻¹, a vertical differential roller gap width of 7 mm, and a conveyor chain speed of 1.4 m·s⁻¹. This experiment fills the research gap in the study of potato–stem separation devices suitable for small-scale potato harvesters and promotes the development of compact potato harvesters. Full article

Over the last century, improvements in computational power resulting from the exponential growth of microelectronics have been the driving force of outstanding global economic growth as well as of deep changes in society and ethical values. Manufacturing of silicon-based memory cells has, as a matter of fact, become an industry of strategic importance also from a geopolitical perspective. Despite such advancements, a lot of concern has recently aroused as physical limitations such as tunnel-effect phenomena, current leakage, and high power consumption are increasingly hindering further improvements in dynamic random-access memory. Spintronic technologies are promising alternatives to overcome such issues, being considered no longer merely an academic subject of interest, but increasingly becoming an industrial reality. In this review work, the history and the physical principles of spintronic devices are presented, focussing on new, groundbreaking materials. Concepts are exposed step by step and in an easy-to-understand manner, allowing even researchers who are not specialized in the fields of spintronics, microelectronics, and hardware engineering to understand the fundamentals and gain initial insight into the topic. Special attention is paid to half-metallic ferromagnets and Heusler alloys, which are considered among the most promising materials for the future of spintronics. Full article

Environmental vibrations may affect the functional use of engineering structures and even lead to disastrous consequences. Vibration suppression and energy harvesting based on Nonlinear Energy Sink (NES) and the piezoelectric effect have gained significant attention in recent years. The harvested electrical energy can supply power to the structural health monitoring sensor device. In this work, the electromechanical-coupled governing equations of the primary structure coupled with the series-connected 2-degree-of-freedom NES (2-DOF NES) integrated by a piezoelectric energy harvester are derived. The absorption and dissipation performances of the system under varying transient excitation intensities are investigated. Additionally, the targeted energy transfer mechanism between the primary structure and the two NESs oscillators is investigated using the wavelet analysis. The reduced slow flow of the dynamical system is explored through the complex-variable averaging method, and the primary factors for triggering the target energy transfer phenomenon are revealed. Furthermore, a comparison is made between the vibration suppression performance of the single-degree-of-freedom NES (S-DOF NES) system and the 2-DOF NES system as a function of external excitation velocity. The results indicate that the vibration suppression performance of the first-level NES (NES1) oscillator is first stimulated. As the external excitation intensity gradually increases, the vibration suppression performance of the second-level NES (NES2) oscillator is also triggered. The 1:1:1, high-frequency, and low-frequency transient resonance captures are observed between the primary structure and NES1 and NES2 oscillators over a wide frequency range. The 2-DOF NES demonstrates superior efficiency in suppressing vibrations of the primary structure and exhibits enhanced robustness to varying external excitation intensities. This provides a new strategy for structural vibration suppression and online power supply for health monitoring devices. Full article

The rapid growth of AI-enabled medical wearables and home-based diagnostic devices has opened new pathways for preventive care, chronic disease management and user-driven health insights. Despite significant technological progress, many solutions face adoption hurdles, often due to usability challenges, episodic measurements and poor alignment with daily life. This review surveys the current landscape of at-home healthcare technologies, including wearable vital sign monitors, digital diagnostics and body composition assessment tools. We synthesize insights from the existing literature for this narrative review, highlighting strengths and limitations in sensing accuracy, user experience and integration into daily health routines. Special attention is given to the role of AI in enabling real-time insights, adaptive feedback and predictive monitoring across these devices. To examine persistent adoption challenges from a user-centered perspective, we reflect on the Pi-CON methodology, a conceptual framework previously introduced to stimulate discussion around passive, non-contact, and continuous data acquisition. While Pi-CON is highlighted as a representative methodology, recent external studies in multimodal sensing, RFID-based monitoring, and wearable–ambient integration confirm the broader feasibility of unobtrusive, passive, and continuous health monitoring in real-world environments. We conclude with strategic recommendations to guide the development of more accessible, intelligent and user-aligned smart healthcare solutions. Full article

This research is based on the acoustic package design of new energy vehicles, investigating the application of the hybrid Finite Element–Statistical Energy Analysis (FE-SEA) model in predicting the high-frequency dynamic response of automotive structures, with a focus on the modeling and correction methods for hybrid point connections. New energy vehicles face unique acoustic challenges due to the special nature of their power systems and operating conditions, such as high-frequency noise from electric motors and electronic devices, wind noise, and road noise at low speeds, which directly affect the vehicle’s ride comfort. Therefore, optimizing the acoustic package design of new energy vehicles to reduce in-cabin noise and improve acoustic quality is an important issue in automotive engineering. In this context, this study proposes an improved point connection correction factor by optimizing the division range of the decision circle. The factor corrects the dynamic stiffness of point connections based on wave characteristics, aiming to improve the analysis accuracy of the hybrid FE-SEA model and enhance its ability to model boundary effects. Simulation results show that the proposed method can effectively improve the model’s analysis accuracy, reduce the degrees of freedom in analysis, and increase efficiency, providing important theoretical support and reference for the acoustic package design and NVH performance optimization of new energy vehicles. Full article

Polymeric optical waveguides represent an essential component in photonic technology thanks to their ability to guide light through controlled structures, enabling applications in telecommunications, sensors, and integrated devices. With the development of new materials and increasingly versatile manufacturing methods, these structures are being integrated into various systems at a rapid pace, while their dimensions are constantly being reduced. This article explores the main fabrication methods for polymeric optical waveguides, such as traditional and maskless photolithography, laser ablation, hot embossing, nanoimprint lithography, the Mosquito method, inkjet printing, aerosol jet printing, and electrohydrodynamic (EHD) printing. The operating principle of each method, the equipment and materials used, and their advantages, limitations, and practical applications are evaluated, in addition to the propagation losses and characterization of the waveguides obtained with each method. Full article