A Novel SE-CNN Attention Architecture for sEMG-Based Hand Gesture Recognition

In this article,to reduce the complexity and improve the generalization ability of current gesture recognition systems,we propose a novel SE-CNN attention architecture for sEMG-based hand gesture recognition.The proposed algorithm introduces a temporal squeeze-and-excite block into a simple CNN architecture and then utilizes it to recalibrate the weights of the feature outputs from the convolutional layer.By enhancing important features while suppressing useless ones,the model realizes gesture recognition efficiently.The last procedure of the proposed algorithm is utilizing a simple attention mechanism to enhance the learned representations of sEMG signals to performmulti-channel sEMG-based gesture recognition tasks.To evaluate the effectiveness and accuracy of the proposed algorithm,we conduct experiments involving multi-gesture datasets Ninapro DB4 and Ninapro DB5 for both inter-session validation and subject-wise cross-validation.After a series of comparisons with the previous models,the proposed algorithm effectively increases the robustness with improved gesture recognition performance and generalization ability.

Dengue virus infection:A review of advances in the emerging rapid detection methods

Dengue virus infections are increasing worldwide generally and in Asia,Central and South America and Africa,particularly.It poses a serious threat to the children population.The rapid and accurate diagnostic systems are essentially required due to lack of effective vaccine against dengue virus and the progressive spread of the dengue virus infection.The recent progress in developing micro-and nano-fabrication techniques has led to low cost and scale down the biomedical point-of-care devices.Starting from the conventional and modern available methods for the diagnosis of dengue infection,this review examines several emerging rapid and point-of-care diagnostic devices that hold significant potential for the progress in smart diagnosis tools.The given review revealed that an effective vaccine is required urgently against all the dengue virus serotypes.However,the rapid detection methods of dengue virus help in early treatment and significantly reduce the dengue virus outbreak.

Rapid and label-free classification of pathogens based on light scattering,reduced power spectral features and support vector machine

The rapid identification of pathogens is crucial in controlling the food quality and safety.The proposed system for the rapid and label-free identification of pathogens is based on the principle of laser scattering from the bacterial microbes.The clinical prototype consists of three parts:the laser beam,photodetectors,and the data acquisition system.The bacterial testing sample was mixed with 10 mL distilled water and placed inside the machine chamber.When the bacterial microbes pass by the laser beam,the scattering of light occurs due to variation in size,shape,and morphology.Due to this reason,different types of pathogens show their unique light scattering patterns.The photo-detectors were arranged at the surroundings of the sample at different angles to collect the scattered light.The photodetectors convert the scattered light intensity into a voltage waveform.The waveform features were acquired by using the power spectral characteristics,and the dimensionality of extracted features was reduced by applying minimal-redundancy-maximal-relevance criterion(mRMR).A support vector machine(SVM)classifier was developed by training the selected power spectral features for the classification of three different bacterial microbes.The resulting average identification accuracies of E.faecalis,E.coli and S.aureus were 99%,87%,and 94%,respectively.The ove rall experimental results yield a higher accuracy of 93.6%,indicating that the proposed device has the potential for label-free identification of pathogens with simplicity,rapidity,and cost-effectiveness.

Cooperative Chemical Coupling and Physical Lubrication Effects Construct Highly Dynamic Ionic Covalent Adaptable Network for High-Performance Wearable Electronics

Covalent adaptable networks(CANs),which combine the benefits of traditional thermosets and thermoplastics,have attracted considerable attention.The dynamics of reversible covalent bonds and mobility of polymer chains in CANs determine the topological rearrangement of the polymeric network,which is critical to their superior features,such as self-healing and reprocessing.Herein,we introduce an ionic liquid to dimethylglyoximeurethane(DOU)-based CANs to regulate both reversible bond dynamics and polymer chain mobility by cooperative chemical coupling and physical lubrication.Small-molecule model experiments demonstrated that ionic liquids can catalyze dynamic DOU bond exchange.Ionic liquid also breaks the hydrogen bonds between polymeric chains,thereby increasing their mobility.As a combined result,the activation energy of the dissociation of the dynamic network decreased from 110 to 85 kJ mol^(−1).Furthermore,as a functional moiety,the ionic liquid imparts new properties to CANs and will greatly expand their applications.For example,the consequent conductivity of resultant ionic CAN(iCAN)has demonstrated a great power to build high-performance multifunctional wearable electronics responsive to multiple stimulations including temperature,strain,and humidity.This study provides a new design principle that simultaneously uses the chemical and physical effects of two structural components to regulate material properties enabling novel applications.

旋转磁场调控组装圆盘状微结构磁性水凝胶(英文)

具有可控微结构的复合生物材料在组织工程和再生医学中发挥着越来越重要的作用.本文报道了在旋转磁场作用下,通过组装氧化铁纳米颗粒制备具有盘状微结构的磁性水凝胶复合材料.组装用的磁性纳米材料是按照合成Ferumoxytol的方法制备而得,也是唯一的被FDA批准应用于临床的铁氧化物纳米颗粒.磁性纳米颗粒的微观结构在水凝胶内部排列为三维有序.其形成机理是由于磁性纳米颗粒的排列链受到旋转磁场作用扭曲从而形成了微观结构系统能量的最低态.通过改变组装参数,可以将微结构尺寸从几微米调整到几十微米.随着组装结构体的增大,其磁各向异性也得到相应的增强.这种情况也证明了即使是微米级的纳米粒子聚集体,也可以通过旋转磁场组装诱导产生各向异性.旋转磁场辅助技术制备有序微纳米结构水凝胶具有成本低、操作简单、灵活等优点.我们相信利用这种方法将有利于构建一些快速、绿色和智能制造的复合材料.