A hand-held in-situ nucleic acid detection device based on dual-function GHz acoustofluidic resonator.

Microfluidic-based nucleic acid testing (NAT) has been proven as an alternative approach for in-situ and rapid NA detection. However, these on-chip methods still require complex peripherals, which contradict the purpose of point-of-care (POC) applications. One of the major challenges is the integration of NA purification and amplification in a miniaturized setup with high mass and heat transfer efficiency.

An Implantable Self-Driven Diaphragm Pacing System Based on a Microvibration Triboelectric Nanogenerator for Phrenic Nerve Stimulation.

Spinal cord injury poses considerable challenges, particularly in diaphragm paralysis. To address limitations in existing diaphragm pacing technologies, we report an implantable, self-driven diaphragm pacing system based on a microvibration triboelectric nanogenerator (MV-TENG). Leveraging the efficient MV-TENG, the system harvests micromechanical energy and converts this energy into pulses for phrenic nerve stimulation.

Broad Learning System under Label Noise: A Novel Reweighting Framework with Logarithm Kernel and Mixture Autoencoder.

The Broad Learning System (BLS) has demonstrated strong performance across a variety of problems. However, BLS based on the Minimum Mean Square Error (MMSE) criterion is highly sensitive to label noise. To enhance the robustness of BLS in environments with label noise, a function called Logarithm Kernel (LK) is designed to reweight the samples for outputting weights during the training of BLS in order to construct a Logarithm Kernel-based BLS (L-BLS) in this paper.

The impact study of variable diameter stabilizer on drilling fluid and cuttings transport.

Through numerical simulation, this study investigates the flow field characteristics of the variable diameter stabilizer in drilling tools under various conditions. It analyzes the influence of different flow rates and speeds on axial velocity and pressure distribution. The results indicate that more significant flow rates correspond to higher average axial velocities across sections, facilitating the transport of drilling fluid and cuttings.

Alternating current stimulation promotes neurite outgrowth and plasticity in neurons through activation of the PI3K/AKT signaling pathway.

As a commonly used physical intervention, electrical stimulation (ES) has been demonstrated to be effective in the treatment of central nervous system disorders. Currently, researchers are studying the effects of electrical stimulation on individual neurons and neural networks, which are dependent on factors such as stimulation intensity, duration, location, and neuronal properties. However, the exact mechanism of action of electrical stimulation remains unclear.

Brain development mediates the relationship between self-reported poor parental monitoring and adolescent anxiety.

Adolescence is the peak period for the onset of generalized anxiety disorder (GAD). Brain networks of cognitive and affective control in adolescents are not well developed when their exposure to external stimuli suddenly increases.Reasonable parental monitoring is especially important during this period.

Spectrum-Weighted Fusion Cooperative Detection Algorithm Based on Double Thresholds for Underwater Acoustic Networks.

Spectrum-sensing technology is crucial for the development of underwater acoustic communication networks and plays a key role in detecting spectrum holes and channel occupancy. Energy detection technology, as the fundamental spectrum sensing technology in cognitive radio, has reached a mature level of development. Its application in hydroacoustic communications can significantly enhance the utilization of the hydroacoustic spectrum.

Analysis of Comfort during Transfer by a Dual-Arm Care Robot Based on Human Body Pressure and Surface Electromyographic Signals.

In-home elderly care faces a crucial challenge regarding mobility among essential assistive devices, for which dual-arm care robots present a viable solution. However, ensuring human comfort in human-robot interactions necessitate quantifiable standards. Currently, the field lacks accurate biomechanical model solutions and objective comfort evaluation.

Defect detection and identification for aircraft cable insulation layer based on deep forest.

Due to the special internal environment of aircraft, cable damage is inevitable, which usually starts from insulation layer defects and may cause major economic losses, and even seriously threaten the life of people on board. According to the above issue, a defect detection system for aircraft cable insulation layer based on ultrasonic guided waves (UGWs) is built in this paper. In order to ensure the complete coupling between the sensor and the insulation layer of the aircraft cable, the macro fiber composite (MFC) flexible sensor is employed in the system.

Investigation of the Degradation Mechanism of SiC MOSFET Subjected to Multiple Stresses.

The performance requirements for power devices in airborne equipment are increasingly demanding, while environmental and working stresses are becoming more diverse. The degradation mechanisms of devices subjected to multiple stresses become more complex. Most proposed degradation mechanisms and models in current research only consider a single stress, making it difficult to describe the correlation between multiple stresses and the correlation of failures.

Controllable Skyrmionic Phase Transition between Néel Skyrmions and Bloch Skyrmionic Bubbles in van der Waals Ferromagnet Fe GeTe.

The van der Waals (vdW) ferromagnet Fe GeTe has garnered significant research interest as a platform for skyrmionic spin configurations, that is, skyrmions and skyrmionic bubbles. However, despite extensive efforts, the origin of the Dzyaloshinskii-Moriya interaction (DMI) in Fe GeTe remains elusive, making it challenging to acquire these skyrmionic phases in a controlled manner. In this study, it is demonstrated that the Fe content in Fe GeTe has a profound effect on the crystal structure, DMI, and skyrmionic phase.

Multi-objective pathfinder algorithm for multi-objective optimal power flow problem with random renewable energy sources: wind, photovoltaic and tidal.

In this paper, the multi-objective optimal power flow (MOOPF) problem optimization objectives focus on four optimization objectives: generation cost, emission, real power loss and voltage deviation (VD). Three renewable energy sources with successful industrial applications, including wind energy, solar energy, and tidal energy are introduced. Renewable energy supply is uncertain, so Weibull distribution probability, lognormal probability and Gumbel probability are used to calculate the instability and intermittency of wind energy, solar energy and tidal energy, respectively.

Image classification of hyperspectral remote sensing using semi-supervised learning algorithm.

Hyperspectral images contain abundant spectral and spatial information of the surface of the earth, but there are more difficulties in processing, analyzing, and sample-labeling these hyperspectral images. In this paper, local binary pattern (LBP), sparse representation and mixed logistic regression model are introduced to propose a sample labeling method based on neighborhood information and priority classifier discrimination. A new hyperspectral remote sensing image classification method based on texture features and semi-supervised learning is implemented.

A COVID-19 medical image classification algorithm based on Transformer.

Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. This paper proposes a novel deep learning network based on ResNet-50 merged transformer named RMT-Net. On the backbone of ResNet-50, it uses Transformer to capture long-distance feature information, adopts convolutional neural networks and depth-wise convolution to obtain local features, reduce the computational cost and acceleration the detection process.

Flexible Electrodes as a Measuring System of Electrical Impedance Imaging.

Electrical Impedance Tomography (EIT) is a detection imaging technology developed 30 years ago. When the conventional EIT measurement system is used, the electrode and the excitation measurement terminal are connected with a long wire, which is easily affected by external interference, and the measurement result is unstable. In this paper, we developed a flexible electrode device based on flexible electronics technology, which can be softly attached to the skin surface for real-time physiological monitoring.

DOIDS: An Intrusion Detection Scheme Based on DBSCAN for Opportunistic Routing in Underwater Wireless Sensor Networks.

In Underwater Wireless Sensor Networks (UWSNs), data should be transmitted to data centers reliably and efficiently. However, due to the harsh channel conditions, reliable data transmission is a challenge for large-scale UWSNs. Thus, opportunistic routing (OR) protocols with high reliability, strong robustness, low end-to-end delay, and high energy efficiency are widely applied.

Current-Induced Reversible Split of Elliptically Distorted Skyrmions in Geometrically Confined Fe Sn Nanotrack.

Skyrmions are swirling spin textures with topological characters promising for future spintronic applications. Skyrmionic devices typically rely on the electrical manipulation of skyrmions with a circular shape. However, manipulating elliptically distorted skyrmions can lead to numerous exotic magneto-electrical functions distinct from those of conventional circular skyrmions, significantly broadening the capability to design innovative spintronic devices.

Quantum-Inspired Moth-Flame Optimizer With Enhanced Local Search Strategy for Cluster Analysis.

Clustering is an unsupervised learning technique widely used in the field of data mining and analysis. Clustering encompasses many specific methods, among which the K-means algorithm maintains the predominance of popularity with respect to its simplicity and efficiency. However, its efficiency is significantly influenced by the initial solution and it is susceptible to being stuck in a local optimum.

An Optical Fiber Sensing Method for Measuring the Surface Flatness of an Object.

Sensing of data or object is a mature research domain where intelligent devices, may possibly be embedded with the artificial intelligence-based techniques, are placed in the closed vicinity of the object or phenomenon. This sensing activity becomes more complex if it is related to the measurements of an object which is required to be accurate and precise. In this paper, the reflection interference spectrum method is used to measure the flatness of the surface of the object.

Damage detection of carbon fiber reinforced polymer composite materials based on one-dimensional multi-scale residual convolution neural network.

Carbon fiber reinforced polymers (CFRPs) have been widely applied in the aerospace industry, and the health conditions of CFRPs largely affect aerospace safety. Due to the limitations of traditional detection methods, electrical impedance tomography (EIT) has been gradually applied in the damage detection of CFRP composite materials. Aiming at the problems of poor imaging quality and low identification rate in the traditional EIT reconstruction algorithm, an EIT algorithm based on the one-dimensional multi-scale residual convolution neural network (1D-MSK-ResNet) is proposed in this paper.

Bioinspired Bare Bones Mayfly Algorithm for Large-Scale Spherical Minimum Spanning Tree.

Mayfly algorithm (MA) is a bioinspired algorithm based on population proposed in recent years and has been applied to many engineering problems successfully. However, it has too many parameters, which makes it difficult to set and adjust a set of appropriate parameters for different problems. In order to avoid adjusting parameters, a bioinspired bare bones mayfly algorithm (BBMA) is proposed.

Commutation Torque Ripple Reduction Strategy of Brushless DC Motor Drives Based on Boosting Voltage of DC-Link Small Capacitor.

Based on the brushless DC motor system with DC-link small capacitance powered by a single-phase AC power source, a boosting DC-link voltage strategy to reduce the commutation torque ripple of brushless DC motors is proposed in this paper. The control strategy utilizes the special topology of the motor system to boost the DC-link capacitor voltage in a specific zone during the non-commutation period. During the commutation period, the high voltage of the DC-link capacitor is released to meet the voltage requirement of the brushless DC motor during commutation.

Broken-Edge Decision-Making Strategy for COVID-19 over Air Railway Composite Network.

In order to control the spread of the COVID-19 virus, this study proposes an ARCN-SUTS (air railway composite network susceptible-untested-tested-susceptible) model based on the correlation characteristics of the air railway composite network in mainland China. Furthermore, this study also puts forward a broken-edge decision-making strategy for the purpose of making decision about the edge efficiently broken and avoiding the second outbreak of the virus spread to minimize the economic losses for railway and civil aviation companies. Finally, simulation results demonstrate that the proposed strategy can effectively control the spread of the virus with minimal economic losses.