Search Results (184)

Emerging power electronic devices like soft open points (SOPs) and electric springs (ESs) play a vital role in enhancing active distribution network (ADN) efficiency. SOPs enable flexible active/reactive power control, while ESs improve demand-side management and voltage regulation. This paper proposes a two-stage stochastic programming model to optimize ADN’s operation by coordinating these fast-response devices with legacy mechanical equipment. The first stage determines hourly setpoints for conventional devices, while the second stage adjusts SOPs and ESs for intra-hour control. To handle ES nonlinearities, a hybrid data–knowledge approach combines knowledge-based linear constraints with a data-driven multi-layer perceptron, later linearized for computational efficiency. The resulting mixed-integer second-order cone program is solved using commercial solvers. Simulation results show the proposed strategy effectively reduces power loss by 42.5%, avoids voltage unsafety with 22 time slots, and enhances 4.3% PV harvesting. The coordinated use of SOP and ESs significantly improves system efficiency, while the proposed solution methodology ensures both accuracy and over 60% computation time reduction. Full article

Surface-enhanced Raman scattering (SERS) has emerged as a powerful signal amplification strategy to address the inherent limitations of conventional flow-based diagnostic methods such as lateral flow analysis (LFA) and vertical flow analysis (VFA). By incorporating SERS-active nanostructures into these platforms, SERS-integrated LFA and VFA systems have significantly improved sensitivity, specificity, and multiplexing performance while maintaining the simplicity and portability of conventional approaches. In this review, we summarize recent advances in SERS-enhanced flow-based diagnostics with a focus on exogenous and endogenous disease detection. Exogenous targets include viral antigens, bacterial pathogens, and foodborne contaminants such as mycotoxins and antibiotic residues. Endogenous applications include therapeutic drug monitoring, inflammation profiling, cancer biomarker detection, and exosome-based molecular subtyping. We highlight the structural differences between LFA and VFA approaches and their impact on analytical performance, and explore the advantages of SERS-integrated platforms for rapid and multiplexed detection in complex biological matrices. Finally, we provide an overview of key technical challenges, such as signal reproducibility, matrix interference, and device integration, and discuss future directions for clinical implementation of SERS-based flow diagnostics in point-of-care settings. Full article

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

The rapid growth of Internet of Things (IoT) applications is reshaping countless sectors and, in the process, exposing the limitations of existing connectivity solutions—especially in rugged regions like South America’s Andean highlands, where conventional infrastructure networks are scarce. To address this gap, this research introduces an automated system that captures uplink and downlink data from LoRaWAN nodes in real time. The system continuously monitors essential indicators—RSSI, SNR, transmit power, spreading factor, bandwidth, device speed, and packet interval—and stores them for later analysis. Thanks to its modular design, the system adapts easily to urban, semi-urban, and challenging rural topographies. Field trials show that our tool gathers reliable performance data while cutting the time and manual effort typical of traditional measurement campaigns. These results streamline IoT roll-outs in demanding terrain and lay the foundation for scalable LoRaWAN deployments throughout the Andean region. Full article

Integrating two-dimensional transition-metal dichalcogenides with graphene is attractive for low-power memory and neuromorphic hardware, yet sequential wet transfer leaves polymer residues and high contact resistance. We demonstrate a complementary metal–oxide–semiconductor (CMOS)-compatible, transfer-free route in which an atomically thin amorphous MoS₂ precursor is RF-sputtered directly onto chemical vapor-deposited few-layer graphene and crystallized by confined-space sulfurization at 800 °C. Grazing-incidence X-ray reflectivity, Raman spectroscopy, and X-ray photoelectron spectroscopy confirm the formation of residue-free, three-to-four-layer 2H-MoS₂ (roughness: 0.8–0.9 nm) over 1.5 cm × 2 cm coupons. Lateral MoS₂/graphene devices exhibit reproducible non-volatile resistive switching with a set transition (SET) near +6 V and an analogue ON/OFF ≈2.1, attributable to vacancy-induced Schottky-barrier modulation. The single-furnace magnetron sputtering + sulfurization sequence avoids toxic H₂S, polymer transfer steps, and high-resistance contacts, offering a cost-effective pathway toward wafer-scale 2D memristors compatible with back-end CMOS temperatures. Full article

Background/Objectives: the assessment and prevention of fall risk is an essential component of healthcare, particularly for vulnerable populations such as older adults with or without diabetes. The use of objective and validated tools to assess balance, gait, and other risk factors enables healthcare professionals to make informed clinical decisions and design personalized prevention programs. An observational cross-sectional study was conducted with a probabilistic sample of older patients, with and without diabetes, attending a podiatric clinic (Valencia, Spain). Methods: fall risk was assessed using the Tinetti Scale and the FallSkip^® device, which measures posture (i.e., medial-lateral and anterior-posterior displacements), gait (vertical and medial-lateral ranges), turn-to-sit (time) and sit-to-stand (power) tests, total time and gait reaction time. Results: the results showed a significant association between the values obtained with FallSkip^® and the Tinetti Scale (p < 0.001), identifying the older individuals at high risk of falls. The “reaction time” parameter measured by FallSkip^® showed a significant difference between diabetic and non-diabetic patients (p < 0.05), as well as the balance score assessed by the Tinetti Scale (p < 0.05). Having experienced falls in the previous year had a strong (p < 0.001) significant influence on the results evaluated using both the Tinetti Scale and FallSkip^®. Among the FallSkip^® parameters in the multivariate analysis, the ‘Total Time (%)’ parameter significantly (p < 0.01, Exp(B) = 0.974 (CI 95%: 0.961–0.988) discriminates individuals with or without falls in the previous year. Conclusions: this study supports the usefulness of the FallSkip^® device as an objective, efficient, and easy-to-use tool for fall risk assessment in primary care settings. Full article

The increase in the number of wildfires in recent years in different parts of the world has caused growing concern among the population, since the consequences of these fires go beyond the destruction of the ecosystem. With the growing relevance of the Internet of Things (IoT) industry, developing solutions for the early detection of fires is of critical importance. This paper proposes a low-cost network based on Long-Range (LoRa) technology to autonomously assess the level of fire risk and the presence of a fire in rural areas. The system consists of several LoRa nodes with sensors to measure environmental variables such as temperature, humidity, carbon monoxide, air quality, and wind speed. The data collected is sent to a central gateway, where it is stored, processed, and later sent to a website for graphical visualization of the results. In this paper, a survey of the requirements of the devices and sensors that compose the system was made. After this survey, a market study of the available sensors was carried out, ending with a comparison between the sensors to determine which ones met the objectives. Using the chosen sensors, a study was made of possible power solutions for this prototype, considering the expected conditions of use. The system was tested in a real environment, and the results demonstrate that it is possible to cover a circular area with a radius of 2 km using a single gateway. Our system is prepared to trigger fire hazard alarms when, for example, the signals for relative humidity, ambient temperature, and wind speed are below or equal to 30%, above or equal to 30 °C, and above or equal to 30 m/s, respectively (commonly known as the 30-30-30 rule). Full article

In recent years, various devices utilizing surface acoustic waves (SAW) have emerged as powerful tools for manipulating particles and fluids in microchannels. Although they demonstrate a wide range of functionalities across diverse applications, existing devices still face limitations in flexibility, manipulation efficiency, and spatial resolution. In this study, we developed a dual-sided standing surface acoustic wave (SSAW) device that simultaneously excites acoustic waves through two piezoelectric substrates positioned at the top and bottom of a microchannel. By fully exploiting the degrees of freedom offered by two pairs of interdigital transducers (IDTs) on each substrate, the system enables highly flexible control of microparticles. To explore its capability on particle aggregation, we developed a two-dimensional numerical model to investigate the influence of the SAW phase modulation on the established acoustic fields within the microchannel. Single-particle motion was first examined under the influence of the phase-modulated acoustic fields to form a reference for identifying effective phase modulation strategies. Key parameters, such as the phase changes and the duration of each phase modulation step, were determined to maximize the lateral motion while minimizing undesired vertical motion of the particle. Our dual-sided SSAW configuration, combined with novel dynamic phase modulation strategy, leads to rapid and precise aggregation of microparticles towards a single focal point. This study sheds new light on the design of acoustofluidic devices for efficient spatiotemporal particle concentration. Full article

This paper presents the first hybrid supply modulator (HSM) designed for envelope tracking power amplifiers (ET-PAs) in base station applications. The focus is on a rail-to-rail Class-AB linear amplifier (LA) optimized for high-voltage and wide-bandwidth operation. The LA is designed using 130 nm BCD technology, utilizing Laterally Diffused Metal-Oxide Semiconductor (LDMOS) transistors for high-voltage operation and incorporating shielding MOSFETs to protect the low-voltage devices. The circuit utilizes dual power supply domains (5 V and 30 V) to improve power efficiency. The proposed LA achieves a bandwidth of 100 MHz and a slew rate of +1003/−852 V/$\mathsf{\mu }\mathrm{s}$, with a quiescent power consumption of 0.89 W. Transient simulations using a 50 MHz bandwidth 5G NR envelope input demonstrate that the proposed HSM achieves a power efficiency of 83%. Consequently, the proposed HSM supports high-output (100 W) wideband 5G NR transmission with enhanced efficiency. Full article

Clouds appear as a cross-culturally useful literary device in Greco-Roman, Jewish, and Christian sources. This paper argues that the cloud travel in the apocryphal Acts of Andrew and Matthias functions in three ways: as a transformative callback to Jesus’s ascension and coming return, as a demonstration of Andrew’s power over natural elements, and as a secure form of transportation away from the difficulties of other travel methods. The author of the text combines the divine protection found in clouds in Greco-Roman literature with the theophanies found in the Septuagint and the New Testament to create this cloud-travel motif that later reappears in the apocryphal sequel Acts of Peter and Andrew. Full article

The output energy of Laser Active Optical Systems (LAOSs), in which image brightness is amplified within the laser-active medium, is always higher than the input energy. This contrasts with conventional optical systems (OSs). As a result, a LAOS enables the creation of laser beams with tailored energy distribution across the aperture, making them ideal for material processing applications. This concept was first successfully implemented using metal vapor lasers as the gain medium. In these systems, material processing was achieved by using a laser beam that either carried the required energy profile or the image of the object itself. Later, other laser media were utilized for LAOSs, including barium vapor, strontium vapor, excimer XeCl lasers, and solid-state media. Additionally, during the development of these systems, several modifications were introduced. For example, Space-Time Light Modulators (STLMs) and CCD cameras were incorporated, along with the use of multipass amplifiers, disk-shaped or thin-disk (TD) solid-state laser amplifiers, and other advancements. These techniques have significantly expanded the range of power, energy, pulse durations, and operating wavelengths. Currently, TD laser amplifiers and STLMs based on Digital Light Processor (DLP) technology or Digital Micromirror Devices (DMDs) enhance the potential to develop LAOS devices for Subtractive and Additive Technologies (ST, AT), applicable in both macromachining (cutting, welding, drilling) and micro-nano processing. This review presents comparable characteristics and requirements for these various LAOS applications. Full article

On-chip optical accelerometers can be a promising alternative to capacitive, piezo-resistive, and piezo-electric accelerometers in some applications due to their immunity to electromagnetic interference and high sensitivity, which allow for robust operation in electromagnetically noisy environments. This paper focuses on the characterization of an easy-to-fabricate tri-axial fiber-free optical MEMS accelerometer, which employs a simple assembly consisting of a light emitting diode (LED), a quadrant photodetector (QPD), and a suspended proof mass, measuring acceleration through light power modulation. This configuration enables simple readout circuitry without the need for complex digital signal processing (DSP). Performance modeling was conducted to simulate the LED’s irradiance profile and its interaction with the proof mass and QPD. Additionally, experimental tests were performed to measure the device’s mechanical sensitivity and validate the mechanical model. Lateral mechanical sensitivity is obtained with acceptable discrepancy from that obtained from FEA simulations. This work consolidates the performance of the design adapted and demonstrates the accelerometer’s feasibility for practical applications. Full article

In the rapidly advancing digital era, the demand for miniaturized and high-performance electronic devices is increasing, particularly in applications such as wireless communication, unmanned aerial vehicles, and healthcare devices. Radio-frequency microelectromechanical systems (RF MEMS), particularly RF MEMS switches, play a crucial role in enhancing RF performance by providing low-loss, high-isolation switching and precise signal path control in reconfigurable RF front-end systems. Among different configurations, electrothermally actuated bistable lateral RF MEMS switches are preferred for their energy efficiency, requiring power only during transitions. This paper presents a novel approach to improve the RF performance of such a switch through structural modifications and machine learning (ML)-driven optimization. To enable efficient high-frequency operation, the H-clamp structure was re-engineered into various lateral configurations, among which the I-clamp exhibited superior RF characteristics. The proposed I-clamp switch was optimized using an eXtreme Gradient Boost (XGBoost) ML model to predict optimal design parameters while significantly reducing the computational overhead of conventional EM simulations. Activation functions were employed within the ML model to improve the accuracy of predicting optimal design parameters by capturing complex nonlinear relationships. The proposed methodology reduced design time by 87.7%, with the optimized I-clamp switch achieving −0.8 dB insertion loss and −70 dB isolation at 10 GHz. Full article

The rapid evolution and deployment of 5G networks have introduced complex security challenges due to their reliance on dynamic network slicing, ultra-low latency communication, decentralized architectures, and highly diverse use cases. Traditional perimeter-based security models are no longer sufficient in these highly fluid and distributed environments. In response to these limitations, this study introduces SecureChain-ZT, a novel Adaptive Zero Trust Policy Framework (AZTPF) that addresses emerging threats by integrating intelligent access control, real-time monitoring, and decentralized authentication mechanisms. SecureChain-ZT advances conventional Zero Trust Architecture (ZTA) by leveraging machine learning, reinforcement learning, and blockchain technologies to achieve autonomous policy enforcement and threat mitigation. Unlike static ZT models that depend on predefined rule sets, AZTPF continuously evaluates user and device behavior in real time, detects anomalies through AI-powered traffic analysis, and dynamically updates access policies based on contextual risk assessments. Comprehensive simulations and experiments demonstrate the robustness of the framework. SecureChain-ZT achieves an authentication accuracy of 97.8% and reduces unauthorized access attempts from 17.5% to just 2.2%. Its advanced detection capabilities achieve a threat detection accuracy of 99.3% and block 95.6% of attempted cyber intrusions. The implementation of blockchain-based identity verification reduces spoofing incidents by 97%, while microsegmentation limits lateral movement attacks by 75%. The proposed SecureChain-ZT model achieved an authentication accuracy of 98.6%, reduced false acceptance and rejection rates to 1.2% and 0.2% respectively, and improved policy update time to 180 ms. Compared to traditional models, the overall latency was reduced by 62.6%, and threat detection accuracy increased to 99.3%. These results highlight the model’s effectiveness in both cybersecurity enhancement and real-time service responsiveness. This research contributes to the advancement of Zero Trust security models by presenting a scalable, resilient, and adaptive policy enforcement framework that aligns with the demands of next-generation 5G infrastructures. The proposed SecureChain-ZT model not only enhances cybersecurity but also ensures service reliability and responsiveness in complex and mission-critical environments. Full article

Deterministic lateral displacement (DLD) has emerged as a powerful microfluidic technique for label-free particle separation with high resolution. Although recent innovations in pillar geometry have broadened its biomedical applications, the fundamental mechanisms dictating flow behavior and separation efficiency remain not fully understood. In this study, we conducted dissipative particle dynamics simulations to systematically investigate the separation of rigid spherical particles and red blood cells (RBCs) in DLD arrays with inverse L-shaped pillars. The simulations established a predictive formula for the critical separation size in such devices and demonstrated that inverse L-shaped pillars enabled a reduced critical separation size compared with conventional circular pillars. Additionally, we revealed that the inverse L-shaped pillars could act as deformability sensors, promoting localized RBC deformation near their protrusions and inducing stiffness-dependent bifurcation in cell trajectories, which enables effective sorting based on cell deformability. These findings advance the mechanistic understanding of inverse L-shaped DLD arrays and provide valuable design principles for their potential applications. Full article