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Compliant physical human-robot interaction (pHRI), as well as the accuracy and robustness of trajectory tracking, are crucial for rehabilitation robots. In this paper, a new sitting/lying lower limb rehabilitation robot, SUT-SLLRR, has been designed for patients with lower extremity motor dysfunction. A dynamic movement primitives modulation-based compliance control strategy (DMPM-CCS) has been proposed for the SUT-SLLRR. The high-level trajectory planner consists of the trajectory generator based on dynamic movement primitives (DMPs), acceleration layer modulation generator, and velocity layer modulation generator, which can reshape the reference trajectory to generate desired trajectory within a constrained joint space through pHRI. Besides, the linear active disturbance rejection controller (LADRC) is adopted as the low-level position controller to ensure that each joint can accurately and robustness track the desired trajectory under internal and external disturbances. Simulation and experimental results indicate that the proposed strategy can provide the compliant pHRI within the constrained joint space and ensure the accuracy and robustness of trajectory tracking.

River silt deposited by water in coastal areas is unsuitable for engineering construction. Thus, the in situ stabilization treatment of river silt as the bearing layer has been an important research area in geotechnical engineering. The strength degradation behavior and mechanism of stabilized river silt reinforced with cement and alginate fibers (AFCS) in different engineering environments are crucial for engineering applications. Therefore, freeze–thaw (F–T) cycle tests, wetting-drying (W–D) cycle tests, water immersion tests and seawater erosion tests were conducted to explore the strength attenuation of stabilized river silt reinforced with the same cement content (9% by wet weight) and different fiber contents (0%, 0.3%, 0.6% and 0.9% by weight of wet soil) and fiber lengths (3 mm, 6 mm and 9 mm). The reinforcement and damage mechanism of AFCS was analyzed by scanning electron microscopy (SEM) imaging. The results indicate that the strength of AFCS was improved from 84% to 180% at 15 F–T cycle tests, and the strength of AFCS was improved by 26% and 40% at 30 W–D cycles, which showed better stability and excellent characteristics owing to the hygroscopic characteristics of alginate fiber arousing the release of calcium and magnesium ions within the alginate. Also, the strength attenuation of AFCS was reduced with the increase in the length and content of alginate fibers. Further, the strength of specimens in the freshwater environment was higher than that in the seawater environment at the same fiber content, and the softening coefficient of AFCS in the freshwater environment was above 0.85, indicating that the AFCS had good water stability. The optimal fiber content was found to be 0.6% based on the unconfined compressive strength (UCS) reduction in specimens cured in seawater and a freshwater environment. And the strength of AFCS was improved by about 10% compared with that of cement-stabilized soil (CS) in a seawater environment. A stable spatial network structure inside the soil was formed, in which the reinforcing effect of fibers was affected by mechanical connection, friction and interfacial bonding. However, noticeable cracks developed in the immersed and F–T specimens. These microscopic characteristics contributed to decreased mechanical properties for AFCS. The results of this research provide a reference for the engineering application of AFCS.

The suspension system is a crucial part of an electric vehicle, which directly affects its handling performance, driving comfort, and driving safety. The dynamics of the 8-DoF full-vehicle suspension with seat active control are established based on rigid-body dynamics, and the time-domain stochastic excitation model of four tires is constructed by the filtered white noise method. The suspension dynamics model and road surface model are constructed on the Matlab/Simulink simulation software platform, and the simulation study of the dynamic characteristics of active suspension based on the fractional-order PIλDμ control strategy is carried out. The three performance indicators of acceleration, suspension dynamic deflection, and tire dynamic displacement are selected to construct the fitness function of the genetic algorithm, and the structural parameters of the fractional-order PIλDμ controller are optimized using the genetic algorithm. The control effect of the optimized fractional-order PIλDμ controller based on the genetic algorithm is analyzed by comparing the integer-order PID control suspension and passive suspension. The simulation results show that for optimized fractional-order PID control suspension, compared with passive suspension, the average optimization of the root mean square (RMS) of acceleration under random road conditions reaches over 25%, the average optimization of suspension dynamic deflection exceeds 30%, and the average optimization of tire dynamic displacement is 5%. However, compared to the integer-order PID control suspension, the average optimization of the root mean square (RMS) of acceleration under random road conditions decreased by 5%, the average optimization of suspension dynamic deflection increased by 3%, and the average optimization of tire dynamic displacement increased by 2%.

E-commerce platforms are evolving rapidly, and consumers have adapted to shop online more effectively by utilizing product images on shopping websites. In the case of apparel, consumers pay attention not only to the information about practical attributes but also to the information about style attributes. In this study, to specifically analyze the respective style recognition capabilities of the depth feature extractor for studying different clothing styles, an empirical investigation was conducted on four commonly utilized networks: AlexNet, InceptionV3, ResNet50, and VGG16. To complete style classification, we propose the IMF model, which integrates shallow neural networks subsequent to feature engineering to incorporate the benefits of basic features and depth features. This process reinforces the basic features through secondary extraction and merges them with depth features to generate style features, ultimately accomplishing the objective of clothing style classification. Furthermore, a DeepCluster based unsupervised learning approach is used in this study as a comparison. Its classification outcomes are compared with those of the IMF model to authenticate the efficacy of IMF model in this study.

A high level of computation is required for edge detection in color images captured by unmanned aerial vehicles (UAVs) to address issues, such as noise, distortion, and information loss. Thus, an edge detection method for UAV-captured color images based on the improved whale optimization algorithm (WOA) is proposed in this study. In this method, the color image pixels are represented by quaternions, and the global random position variables and information exchange mechanism are introduced into the random walk foraging formula of the WOA. Further, a random disturbance factor is also introduced into the predator-prey formula of the spiral bubble net. The proposed improved WOA is then used to obtain the preliminary edge of the UAV-captured color image. An edge-point classification method using the radius of the shortest distance between the whale and the current global optimum in each iteration is presented to enhance a preliminary edge. The experimental results show that the proposed edge detection method has the advantages of strong denoising, fast speed, and good quality.

This article mainly focuses on DC voltage control loop of PMSG which affecting the subsynchronous oscillation (SSO) stability. Based on the established general dynamic interconnection model, the oscillation stability region of DC voltage control parameters is calculated by the eigenvalue method. It is found that a series of ’convex points’ appeared in the stability region are mainly due to strong dynamic interaction between DC voltage control of PMSG and other dynamics induced by modal coupling. Furthermore, by the proposed oscillation stability region, this article reviews the mechanism of the subsynchronous oscillation instability induced by the modal coupling, and the two types of parameters, system operating parameters and VSC control parameters, that affect the system SSO instability. In addition, effective measures to suppress SSO instability of the wind–thermal bundling system is proposed.

An effective method widely used in geotechnical engineering to solve the shrinkage and cracking issues in cement-stabilized soil (CS) is evenly mixing randomly distributed fibers into it. Dredger fills stabilized with cement and polypropylene fibers (PFCSs) are exposed to rainwater immersion and seawater erosion in coastal areas, influencing their mechanical performance and durability. In this study, direct shear and consolidation compression tests were conducted to investigate the influence of different curing environments on the mechanical properties and compressive behavior of PFCSs. Dominance and regression analyses were used to study the impact of each factor under different curing regimes. The reinforcement mechanism of different curing environments was also explored using scanning electron microscopy (SEM) imaging. The results show that the cohesion and elastic modulus of the specimens cured in seawater were reduced compared with those cured in freshwater and standard curing environments. The best fiber content for the strength and compressive modulus of PFCSs was determined to be 0.9% of the mass of dredged fill. The results of value-added contributions and the relative importance of each factor in different curing environments show that the overall average contribution of cement content in the seawater curing environment is reduced by 6.79% compared to the freshwater environment. Multiple linear regression models were developed, effectively describing the quantitative relationships of different properties under different curing conditions. Further, the shear strength was improved by the coupling effect of soil particles, a C-S-H gel, and polypropylene fibers in the PFCSs. However, the shear strength of the PFCSs was reduced due to the structural damage of the specimens in the freshwater and seawater curing environments.

The driving smoothness of vehicles is heavily influenced by their suspension system, and implementing active suspension control can effectively minimize the vibration movement of the vehicle and ensure a comfortable driving experience. An 8-DoF active suspension model of the full vehicle is established, and a fuzzy-PID controller is designed to autonomously regulate the parameters of the PID controller. Using the MATLAB/Simulink environment, a simulation model for suspension is created, and the vibration characteristics of passive, PID control, and fuzzy-PID control suspensions are compared with the help of the continuous crossing road hump model and C-level road model as road inputs. The results show that the utilization of fuzzy-PID control considerably diminishes the vertical, pitch, and roll oscillations of the suspension body and modifies the suspension dynamic deflection and tire dynamic load in contrast to the other two scenarios, thus enhancing ride comfort. Fuzzy-PID control led to a decrease of approximately 40% in acceleration, 25% in suspension workspace, and 30% in tire deflection compared to passive suspension. In addition, the reduction in acceleration is about 20%, the reduction in suspension workspace is approximately 10%, and the reduction in tire deflection is about 15% compared to the PID control suspension system.

Unsupervised feature selection aims to derive a compact set of features with desired generalization ability via removing the irrelevant and redundant features, yet challenging due to the unavailability of labels. Works about unsupervised feature selection always need to construct the similarity matrix, which makes the selected features highly depend on the accuracy of similarity measurement. However, existing works usually leverage a single fixed metric to build similarity matrix, which cannot fit various feature types very well and even damage the local manifold structure. To address this problem, we propose an adaptive multi-metric fusion by automatically integrating similarity across different metrics according to the specific data. Besides, to capture the global structure more precisely, a novel low-rank approximation method is proposed, which is relatively insensitive to the rank-norm parameter. Via the proposed novel low-rank approximation method, better tradeoff between the performance and robustness can be provided. Experimental results show that the accuracy performance of the proposed method can be boosted by $2\%-11\%$ , compared with previous methods.

Copper is the most common interconnecting material in the field of microelectronic packaging, which is widely used in advanced electronic packaging technologies. However, with the trend of the miniaturization of electronic devices, the dimensions of interconnectors have decreased from hundreds of microns to tens of or even several microns, which has brought serious reliability issues. As a result, nanotwinned copper (nt-Cu) has been proposed as a potential candidate material and is being certified progressively. Firstly, the physical properties of nt-Cu have been widely studied. Notably, the higher thermal stability and oxidation resistance of the (111) texture causes nt-Cu to maintain excellent physical properties under high-temperature serving conditions. Secondly, recent works on the electrolyte and electroplating processes of nt-Cu on wafer substrates are summarized, focusing on how to reduce the thickness of the transition layer, improve the twin density, and achieve complicated pattern filling. Thirdly, nt-Cu can effectively eliminate Kirkendall voids when it serves as UBM or a CuP. Additionally, the high (111) texture can control the preferred orientation of interfacial intermetallic compounds (IMCs) at the Cu–Sn interface, which should be helpful to improve the reliability of solder joints. nt-Cu has superior electromigration resistance and antithermal cycling ability compared to ordinary copper RDLs and TSVs. Above all, nt-Cu has attracted much attention in the field of microelectronic packaging in recent years. The preparation–performance–reliability interrelationship of nt-Cu is summarized and displayed in this paper, which provides a solid theoretical basis for its practical applications.

Rapid developments in wide-bandgap semiconductors have led to the demand for interconnection materials that can withstand harsh conditions. In this study, novel Ag composite pastes were developed with the assistance of metal organic decomposition (MOD) to significantly reduce the sintering temperature of commercial Ag pastes. The effects of the decomposition characteristics of different MODs on the microstructure, morphology, and the shear strength of the Ag-sintered joints were systematically investigated. Additionally, the low-temperature sintering mechanisms of the MOD-assisted Ag composite pastes were studied and proposed. Among all the MODs studied, the one consisting of propylamine complexed with silver oxalate demonstrated the best performance due to its ability to form Ag nanoclusters with the smallest size (~25 nm) and highest purity (~99.07 wt.%). Notably, the bonding temperature of the MOD-modified Ag pastes decreased from 250 °C to 175 °C, while the shear strength increased from 20 MPa to 40.6 MPa when compared to the commercial Ag pastes.

Motor planning can enable integration of sensory input to generate motor execution. However, how the brain analyses visual information and modulates its signals to the muscle have been not well studied in human. The aim of this study was to investigate the dimensionality effect of myoelectric-controlled interface (MCI) on motor planning and motor execution during elbow tracking movements. Twenty right-handed healthy subjects were recruited to complete tracking tasks by modulating their biceps and triceps activation within one-dimensional and two-dimensional MCI. The electromyography (EMG) signals of the biceps and triceps was recorded to calculate the normalized muscle activation, while the functional near infrared spectroscopy (fNIRS) signals of the prefrontal cortex (PFC) and bilateral motor cortex (MC) were also collected to gain the brain activation simultaneously. The results showed that the activation of antagonist muscle was significant lower within two-dimensional MCI than that within one-dimensional MCI at the muscle level. At the brain level, it was found an obvious higher activation in the PFC and the left MC within two-dimensional MCI than that within one-dimensional MCI. The current EMG-fNIRS study confirmed that visual feedback can influence motor planning and motor execution, and the PFC and bilateral MC are the likely targeted sites of the proactive inhibition of the antagonist muscle. This study adds a new perspective to possible visual regulation of neuromuscular control, which might be an effective rehabilitation method to improve abnormal muscle coordination in the clinic.

Rehabilitation robots play an increasingly important role in the recovery of motor function for stroke. To ensure a natural physical human-robot interaction (pHRI) and enhance the active participation of subjects, it is necessary for the robots to understand the human intention and cooperate actively with humanlike characteristics. This study proposed a hybrid active control algorithm with human motion intention detection. The motion intention was defined as the desired position and velocity, which were continuously estimated according to the human upper-limb model and minimum jerk model, respectively. The motion intention was then fed into a hybrid force and position controller of an upper-limb cable driven rehabilitation robot (CDRR). And a three-dimensional reaching task without predefined trajectory was employed to validate the effectiveness of the proposed control algorithm. Experimental results showed that the control algorithm could continuously recognize the human motion intention and enabled the robot better movement performance indicated as smaller offset error, smoother trajectory, and lower impact. The proposed method could guarantee a natural pHRI and improve the engagement of the subjects, which has great potential in clinical applications.

Intelligent regulation for human exercise behaviors becomes significantly necessary for exercise medicine after the COVID-19 epidemic. The key issue of exercise regulation and its potential development for intelligent exercise is to describe human exercise physiological behaviors in a more accurate and sufficient manner. Here, a non-parametric modeling method with kernel-based regularization is presented to estimate cardiorespiratory biomarkers (i.e., oxygen uptake (V̇O2) and carbon dioxide output (V̇O2) by merely non-invasively monitoring the indicator of exercise intensity (e.g., walking speed). Using the kernel-based non-parametric modeling, we show that V̇O2 and V̇O2 behaviors in response to continuous and diversified exercise intensity stimulations can be quantitatively described. Furthermore, the dataset from the stairs experiment with a proper protocol is applied in the kernel parameter selection, and this selection approach is compared with the numerical simulation approach. The comparison results illustrate an improvement of 4.18% for oxygen uptake and 7.63% for carbon dioxide output in a half period, and 11.00% for oxygen uptake and 12.60% for carbon dioxide output in one period when using the kernel parameter selected from the stairs exercise. Moreover, the advantages of using the non-parametric model, the necessity of sufficient stimulation for identification and the importance of the kernel regularization term are also addressed in this paper. This method provides fundamental work for the practice of intelligent exercise.

Piggybacking codes are a class of distributed storage codes adopted in distributed storage systems, which received much attention in recent years. Two novel piggybacking constructions based on the double-layered piggybacking framework are proposed. They can reduce the repair bandwidth of both the systematic nodes and the parity nodes efficiently. The average repair bandwidth ratio for the two constructions approaches to zero asymptotically as the number of systematic nodes and parity nodes tends to infinity. Compared with other piggybacking codes, the two proposed double-layered piggybacking codes, especially the second one, not only require less design constraints, but also obtain the optimal comprehensive repair efficiency, which further save the amount of data read and downloaded.

In traditional hybrid energy storage system (HESS), separated bidirectional dc/dc converter is usually used to interface energy storage system with dc bus. Though it has an advantage in flexibility of control system design using separated power converters, it results in more switches, auxiliary components, and cost for the whole system development. Particularly, since the energy storage system (ESS) designed for high dynamic compensation (e.g., supercapacitor) is mainly used to provide high-dynamic compensation in transient state process, the utilization rate of the corresponding interface dc/dc converter is relatively low. On the other hand, the dc bus voltage compensation performance will be discounted due to the inherent time delay for the current reference signal production of HESS with outer loop voltage control. In this paper, to address these two issues, an integrated topology of the hybrid energy storage system is proposed, and an improved control method that has the ability to enhance the control performance of HESS to compensate the dc bus voltage is developed too. The experimental test results are provided to validate the correctness and effectiveness of the proposed methods.

The foot-terrain interaction mechanics of human is important in understanding the biped locomotion mechanism. This paper aims to investigate the effect of walking speed and the hardness of the terrain on foot-terrain interaction mechanics. In the experiments, mobile portable plantar mechanical measuring insoles with 107 sensor elements were used to gauge the plantar force and contact area in real-time. Seven subjects with healthy feet have participated in typical experiments. The statistical methods including correlation analysis, univariance analysis, and systematic identification are primarily used to obtain several main results. Bimodal functions in describing the total pressure-time relations were performed at slow and regular speeds but only one hump is left if walking at fast paces; they can be unified and summed by three subsections' unimodal functions. The forefoot produces a large peak impact force in slow and regular quasi-static walking on both hard ground and deformable terrains, while the heel absorbs more dynamic impact shocks in fast walking on hard ground. The torques generated by the ankle joints are calculated based on plantar force or its derived information such as zero moment point. Some implications are drawn, for example, the dynamically changed positions of zero moment point (ZMP) for humans are similar to that generated by reptiles wiggling through the flowable terrains; increasing the stride length on the hard ground produces more impact vibrations than quickening paces but more effective in accelerating walks on deformable terrains.

This paper aims to examine how the trajectory dimension influences sensorimotor control during arm tracking. We designed three trajectories with different dimensions in a three-dimensional (3D) immersive virtual reality environment and instructed the subjects to control a virtual hand to follow a cubic target that moved along the designed trajectories. The position of the virtual hand was determined by the position of the actual hand captured with a high-resolution 3D motion capture system in real time. Five kinematic measures were calculated: the root mean square error (RMSE), the standard deviation of the speed (speedsd), the magnitude of the jerk (Jerkm), the integral of the speed power spectrum (IVPS), and the 3D fuzzy approximate entropy (fApEn3D). All the kinematic measures increased significantly with increasing trajectory dimensions, except for the IVPS between the 1D and 2D conditions and the fApEn3D between the 2D and 3D conditions. The increase in time-domain parameters (i.e., RMSE, speedsd, and Jerkm) showed degradation in accuracy, energy efficiency, and multijoint coordination, respectively, in the higher dimensions. An increase in the frequency-domain measure (i.e., IVPS) in higher dimensional condition reflected an increase of visual feedback-related intermittency in manual control when increasing the trajectory dimension. The larger nonlinear fApEn3D values in the 2D and 3D conditions might have been due to the higher level neuromotor noise and increased sensory inputs. The selected parameters could provide a comprehensive method for evaluating motor performance from different perspectives. The findings in this paper shed light on the underlying sensorimotor control that is caused by the trajectory dimension in arm tracking tasks.

Although psychological distress is associated with heart rate variability (HRV) and can be improved by interventions, few studies compared the effects of different interventions on cardiac regulation and the changes of the complexity of HRV in pre-, during-, and post-intervention phases. In this paper, 18 healthy young participants were recruited to investigate the effects of deep breathing, meditation, and video-watching tasks. The respiration (RSP) and electrocardiogram (ECG) signals were simultaneously recorded. Fuzzy entropy (FuzzyEn) was applied to quantify the complexity of HRV in pre-, during-, and post-task phases. The results showed that the FuzzyEn value of HRV in the during-task phase was significantly lower than that in the pre-task phase in deep breathing, video-watching, and meditation tasks, which might result from the effect of cardiorespiratory coupling (CRC), brain-heart coupling (BHC), and the combined effect of CRC and BHC, respectively. There were also significant increases of the FuzzyEn value in the post-task phase than the during-task phase in the deep breathing and meditation tasks, while the lower FuzzyEn value in the post-task phase than during-task phase only occurred in the video-watching task, which might result from that watching video had a more lasting impact on HRV than the other two tasks due to the brain memory. The method and indicator provide the evidence of cardiac rhythm changes after different interventions, and further research was needed to promote the clinical application.

Helixes and chiralities are ubiquitous in nature and closely related to the origin of life, but the spontaneous assembly of such patterns has rarely been realized in low-temperature plasma jets which have numerous applications in biomedical engineering and materials processing. Recently chiral plasma plumes have been generated in the absence of any asymmetric factor. Under the condition of specific pulse DC discharge parameters, the discharge channels that originally propagated along a straight line turn into three dimensional helical plasma discharge channels spontaneously. And the pitch of the helixes can be guided by the external coils outside dielectric tubes in experiments. In this paper, we apply the finite element analysis method to simulate the electrostatic field of the chiral plasma guided by external coils. The effects of initial electric field and surface charges for the formation of the chiral plasma plumes are discussed respectively. These results have important implications for the production of chiral pharmaceuticals and nano-materials.

With the popularity of cloud computing technology, the healthcare cloud system is becoming increasingly perfect, which reduces the time of disease diagnosis and brings great convenience to people’s lives. But meanwhile, the healthcare cloud system usually involves users’ privacy information, and there is still a challenge on how to ensure that the sensitive information of users is not disclosed. Attribute-based signature (ABS) is a very useful technique for the privacy protection of users and is very suitable for anonymous authentication and privacy access control. However, general ABS schemes usually contain heavy computation overhead in signing and verification phases, which is not conducive for resource-limited devices to access healthcare cloud system. To address the above issues, we propose a lightweight and privacy-preserving medical services access scheme based on multi-authority ABS for healthcare cloud, named LPP-MSA. By using online/offline signing and server-aided verification mechanisms, the proposed scheme can greatly reduce the calculation overhead. In addition, LPP-MSA achieves unforgeability and anonymity and can resist collision attack. The comparisons of computational cost and storage overhead between LPP-MSA and the other existing schemes show that LPP-MSA is more efficient in both signing and verification phases. Therefore, it could be well applied to the scenarios where users access the healthcare cloud system for large scale remote medical services via resource-constrained mobile devices.

It is a great challenge to find an optimal one-wafer cyclic schedule for a single-arm multicluster tool that is widely adopted in semiconductor fabrication. Aiming to tackle this significant problem, an optimal scheduling strategy is determined first for each individual tool under the condition that the bottleneck individual tool is transport-bound. Then, by developing a Petri net model with robot waiting being explicitly described to reveal the properties of the entire system, this paper shows that to schedule such a tool optimally is to allocate the robot waiting time properly. Then, this paper presents the necessary and sufficient conditions for the existence of an optimal one-wafer cyclic schedule. Thereafter, an efficient algorithm is developed to check the given conditions and find such a schedule efficiently if existing. Finally, two industrial examples are used to verify that the proposed method is applicable and effective.

With the emergence of mobile communication technologies, we are entering the fifth generation (5G) mobile communication system era. Various application scenarios will arise in the 5G era to meet the different service requirements. Different 5G network slicings may deploy different public key cryptosystems. The security issues among the heterogeneous systems should be considered. In order to ensure the secure communications between 5G network slicings, in different public cryptosystems, we propose two heterogeneous signcryption schemes which can achieve mutual communications between the public key infrastructure and the certificateless public key cryptography environment. We prove that our schemes have the indistinguishability against adaptive chosen ciphertext attack under the computational Diffie-Hellman problem and the existential unforgeability against adaptive chosen message attack under the discrete logarithm problem in the random oracle model. We also set up two heterogeneous cryptosystems on Raspberry Pi to simulate the interprocess communication between different public key environments. Furthermore, we quantify and analyze the performance of each scheme. Compared with the existing schemes, our schemes achieve greater efficiency and security.

Along with the development of vehicular sensors and wireless communication technology, Internet of Vehicles (IoV) is emerging that can improve traffic efficiency and provide a comfortable driving environment. However, there is still a challenge how to ensure the survivability of IoV. Fortunately, this goal can be achieved by quickly verifying real-time monitoring data to avoid network failure. Aggregate signature is an efficient approach to realize quick data verification. In this paper, we propose a monitoring data batch verification scheme based on an improved certificateless aggregate signature for IoV, named MDBV. The size of aggregated verification message is remaining roughly constant even as the increasing number of vehicles in MDBV. Additionally, MDBV is proved to be secure in the random oracle model assuming the intractability of the computational Diffie-Hellman problem. In consideration of the network survivability and performance, the proposed MDBV can decrease the computation overhead and is more suitable for IoV.

Changes in motor behavior during aging might be induced by complexity fluctuations in the neuromuscular system. Most previous studies have been performed based on single-scale entropies. In this paper, multiscale fuzzy entropy (MSFuzzyEn) was applied to characterize the changes in the complexity of simulated electromyogram (EMG) signals with the increasing motor unit number and signal-to-noise ratio. Age-related differences in multiscale complexity during handgrip control were also investigated. Ten young and 10 older adults were instructed to produce constant forces at 25%, 50%, and 75% of their maximal grip force with their dominant hands. The grip force and EMG signals of four forearm muscles were recorded simultaneously and analyzed using MSFuzzyEn. The simulation tests revealed that, as the time scale increased, the interference of noise in the EMG signals decreased. At time scale 1, the complexities of the force and EMG signals exhibited opposite changes with aging. When the time scale increased, we observed a loss in complexity with aging in both the force and EMG signals. These results confirmed the merits of MSFuzzyEn in noise abatement, and implied that entropy at relatively larger time scales might better characterize EMG signals. Further studies should extend the application of multiscale entropy in pathologies.

As modern electronics are developed towards miniaturisation, high-degree integration and intelligentisation, a large amount of heat will be generated during the operation of devices. How to efficiently remove needless heat is becoming more and more crucial for the lifetime and performance of electronic devices. Many efforts have been made to improve the thermal conductivity of polymer composites, which is an important component of electronics. Herein, the authors report on preparation of boron nitride micosphere/epoxy composites. The cross-plane thermal conductivity of the resultant composites is up to 1.03 Wm^‒1K^‒1. This is attributed to the thermally conductive network formed by the peeled hexagonal boron nitride flakes. Thanks to the superior thermal stability of boron nitride micosphere, the boron nitride micosphere/epoxy composite shows a decreased coefficient of thermal expansion (53.47 ppm/K) and an increased glass transition temperature (147.2°C) compared with the pure epoxy resin. In addition, the boron nitride micosphere/epoxy composite exhibits a lower dielectric constant compared with that of the hexagonal boron nitride/epoxy composite. This strategy can potentially pave the way for the design and fabrication of materials with high cross-plane thermal conductivity and lower dielectric properties.

In this study, 2-[2-(2-methoxyethoxy)ethoxy]acetic acid (MEEAA) was used to modify the surface of barium titanate nanoparticles (BT NPs) to enhance the compatibility and dispersion of the BT ceramic fillers in polymer matrix. A uniform coating layer with a thickness about 2 nm was formed on the surface of BT after modification. The poly(vinylidene fluoride)-hexafluoropropene [P(VDF-HFP)] composites filled with MEEAA-modified BT NPs achieved higher permittivity(∼13 at 3.0 vol% filler) and discharged energy density than that of the untreated BT filled composite. The maximum discharge energy density of 7.8 J/cm^3 was obtained in the nanocomposites with 3 vol% MEEAA-modified BT NPs at electric field of 425 kV/mm, which is 77% higher than that of 4.4 J/cm^3 of pure P(VDF-HFP) film at electric field of 420 kV/mm.

A Ku-band wideband conformal array antenna with 13×19 elements is presented in the paper. The array has a spherical structure, and its element is a proximity-coupled stacked patches antenna with a cavity-backed ground plane. The stacked patches and the cavity produce multiple coupled resonances, which enhance the bandwidth of the element extremely. A simulated model with the reasonable dimensions is framed with the coupling analyses, and the effective simulated results and good computing efficiency are obtained simultaneously. The measured results of the center embedded element in the whole array show a bandwidth exceeding 40% VSWR

Pristine Ag3PO4 microspheres were synthesized by a co-precipitation method, followed by being calcined at different temperatures to obtain a series of calcined Ag3PO4 photocatalysts. This work aims to investigate the origin of activity and stability enhancement for Ag3PO4 photocatalyst after calcination based on the systematical analyses of the structures, morphologies, chemical states of elements, oxygen defects, optical absorption properties, separation and transfer of photogenerated electron-hole pairs, and active species. The results indicate that oxygen vacancies (VO˙˙) are created and metallic silver nanoparticles (Ag NPs) are formed by the reaction of partial Ag+ in Ag3PO4 semiconductor with the thermally excited electrons from Ag3PO4 and then deposited on the surface of Ag3PO4 microspheres during the calcination process. Among the calcined Ag3PO4 samples, the Ag3PO4-200 sample exhibits the best photocatalytic activity and greatly enhanced photocatalytic stability for photodegradation of methylene blue (MB) solution under visible light irradiation. Oxygen vacancies play a significantly positive role in the enhancement of photocatalytic activity, while metallic Ag has a very important effect on improving the photocatalytic stability. Overall, the present work provides some powerful evidences and a deep understanding on the origin of activity and stability enhancement for the Ag3PO4 photocatalyst after calcination.