Set Stabilization of Large-Scale Stochastic Boolean Networks:A Distributed Control Strategy

Dear Editor,This letter deals with the set stabilization of stochastic Boolean control networks(SBCNs)by the pinning control strategy,which is to realize the full control for systems by imposing control inputs on a fraction of agents.

Advances in isolation and detection of circulating tumor cells based on microfluidics

Circulating tumor cells(CTCs) are the cancer cells that circulate in the peripheral blood after escaping from the original or metastatic tumors. CTCs could be used as non-invasive source of clinical information in early diagnosis of cancer and evaluation of cancer development. In recent years, CTC research has become a hotspot field wherein many novel CTC detection technologies based on microfluidics have been developed. Great advances have been made that exhibit obvious technical advantages, but cannot yet satisfy the current clinical requirements. In this study, we review the main advances in isolation and detection methods of CTC based on microfluidics research over several years, propose five technical indicators for evaluating these methods, and explore the application prospects. We also discuss the concepts, issues, approaches, advantages, limitations, and challenges with an aim of stimulating a broader interest in developing microfluidics-based CTC detection technology.

Human natural killer cells for targeting delivery of gold nanostars and bimodal imaging directed photothermal/photodynamic therapy and immunotherapy

Objective:To construct a novel nanoplatform GNS@CaCO3/Ce6-NK by loading the CaCO3-coated gold nanostars(GNSs)with Chlorin e6 molecules(Ce6)into human peripheral blood mononuclear cells(PBMCs)-derived NK cells for tumor targeted therapy.Methods:GNS@CaCO3/Ce6 nanoparticles were prepared and characterized by TEM and UV-vis.The cell surface markers and cytokines secretion of NK cells before and after loading the GNS@CaCO3/Ce6 nanoparticles were detected by Flow Cytometry(FCM)and ELISA.Effects of the GNS@CaCO3/Ce6-NK cells on A549 cancer cells was determined by FCM and CCK-8.Intracellular fluorescent signals of GNS@CaCO3/Ce6-NK cells were detected via Confocal laser scanning microscopic(CLSM)and FCM at different time points.Intracellular ROS generation of GNS@CaCO3/Ce6-NK cells under laser irradiation were examined by FCM.The distribution of GNS@CaCO3/Ce6-NK in A549 tumor-bearing mice were observed by fluorescence imaging and PA imaging.The combination therapy of GNS@CaCO3/Ce6-NK under laser irradiation were investigated on tumor-bearing mice.Results:The coated CaC03 shell on the surface of GNSs exhibited prominent delivery and protection effect of Ce6 during the cellular uptake process.The as-prepared multifunctional GNS@CaCO3/Ce6-NK cells possessed bimodal functions of fluorescence imaging and photoacoustic imaging.The as-prepared multifunctional GNS@CaCO3/Ce6-NK cells could actively target tumor tissues with the enhanced photothermal/photodynamic therapy and immunotherapy.Conclusions:The GNS@CaCO3/Ce6-NK shows effective tumor-targeting ability and prominent therapeutic efficacy toward lung cancer A549 tumor-bearing mice.Through fully utilizing the features of GNSs and NK cells,this new nanoplatform provides a new synergistic strategy for enhanced photothermal/photodynamic therapy and immunotherapy in the field of anticancer development in the near future.

Bioinspired MXene-Based User-Interactive Electronic Skin for Digital and Visual Dual-Channel Sensing

User-interactive electronic skin(e-skin) that could convert mechanical stimuli into distinguishable outputs displays tremendous potential for wearable devices and health care applications. However, the existing devices have the disadvantages such as complex integration procedure and lack of the intuitive signal display function. Here, we present a bioinspired user-interactive e-skin, which is simple in structure and can synchronously achieve digital electrical response and optical visualization upon external mechanical stimulus. The e-skin comprises a conductive layer with a carbon nanotubes/cellulose nanofibers/MXene nanohybrid network featuring remarkable electromechanical behaviors, and a stretchable elastomer layer, which is composed of silicone rubber and thermochromic pigments. Furthermore, the conductive nanohybrid network with outstanding Joule heating performance can generate controllable thermal energy under voltage input and then achieve the dynamic coloration of silicone-based elastomer. Especially, such an innovative fusion strategy of digital data and visual images enables the e-skin to monitor human activities with evermore intuition and accuracy. The simple design philosophy and reliable operation of the demonstrated e-skin are expected to provide an ideal platform for next-generation flexible electronics.

Fluid Flow Modeling of Arc Plasma and Bath Circulation in DC Electric Arc Furnace

A mathematical model describing the flow field, heat transfer and the electromagnetic phenomenon in a DC electric arc furnace has been developed. First the governing equations in the arc plasma region are solved and the calculated results of heat transfer, current density and shear stresses on the anode surface are used as boundary conditions in a model of molten bath. Then a two-dimensional time-dependent model is used to describe the flow field and electromagnetic phenomenon in the molten bath. Moreover, the effect of bottom electrode diameter on the circulation of molten bath is studied.

Composites of Graphene and LiFePO_4 as Cathode Materials for Lithium-Ion Battery:A Mini-review

This mini-review highlights selectively the recent research progress in the composites of Li Fe PO4 and graphene. In particularly, the different fabrication protocols, and the electrochemical performance of the composites are summarized in detail. The structural and morphology characters of graphene sheets that may affect the property of the composites are discussed briefly. The possible ongoing researches in area are speculated upon.

Boosting of reversible capacity delivered at a low voltage below 0.5 V in mildly expanded graphitized needle coke anode for a high-energy lithium ion battery

The rate performance and cycle stability of graphitized needle coke(GNC)as anode are still limited by the sluggish kinetics and volume expansion during the Li ions intercalation and de-intercalation process.Especially,the output of energy density for lithium ion batteries(LIBs)is directly affected by the delithiation capacity below 0.5 V.Here,the mildly expanded graphitized needle coke(MEGNC)with the enlarged interlayer spacing from 0.346 to 0.352 nm is obtained by the two-step mild oxidation intercalation modification.The voltage plateau of MEGNC anode below 0.5 V is obviously broadened as compared to the initial GNC anode,contributing to the enhancement of Li storage below the low voltage plateau.Moreover,the coin full cell and pouch full cell configured with MEGNC anode exhibit much enhanced Li storage ability,energy density and better cycling stability than those full cells configured with GNC and commercial graphite anodes,demonstrating the practical application value of MEGNC.The superior anode behaviors of MEGNC including the increased effective capacity at low voltage and superior cyclic stability are mainly benefited from the enlarged interlayer spacing,which not only accelerates the Li ions diffusion rate,but also effectively alleviates the volume expansion and fragmentation during the Li ions intercalation process.In addition,the above result is further confirmed by the density functional theory simulation.This work provides an effective modification strategy for the NC-based graphite to enhance the delithiation capacity at a low voltage plateau,dedicated to improving the energy density and durability of LIBs.

Controllable Biosynthesis and Properties of Gold Nanoplates Using Yeast Extract

Biosynthesis of gold nanostructures has drawn increasing concerns because of its green and sustainable synthetic process. However, biosynthesis of gold nanoplates is still a challenge because of the expensive source and difficulties of controllable formation of morphology and size. Herein, one-pot biosynthesis of gold nanoplates is proposed, in which cheap yeast was extracted as a green precursor. The morphologies and sizes of the gold nanostructures can be controlled via varying the pH value of the biomedium. In acid condition, gold nanoplates with side length from 1300 ± 200 to 300 ± 100 nm and height from 18 to 15 nm were obtained by increasing the pH value. Whereas, in neutral or basic condition, only gold nanoflowers and nanoparticles were obtained. It was determined that organic molecules, such as succinic acid, lactic acid, malic acid, and glutathione, which are generated in metabolism process, played important role in the reduction of gold ions. Besides, it was found that the gold nanoplates exhibited plasmonic property with prominent dipole infrared resonance in near-infrared region, indicating their potential in surface plasmon-enhanced applications, such as bioimaging and photothermal therapy.

Analysis of basic conditions of the power grid interconnection among Xinjiang, Pakistan, and five Central Asian countries

Inter-regional and transnational grid interconnection is necessary for energy development. Xinjiang, which is rich in renewable energy resources, is adjacent to countries in Central Asia and has great potential for interconnection with its neighbors. This paper outlines China's relevant policies for transnational power interconnection, and introduces the energy structure, load demand endowments, and power supply status of Xinjiang, Pakistan, and five Central Asian countries. Further, it analyzes the advantages of the multinational power interconnection from the aspects of power supply and load complementation. Finally, from the perspective of technical support and practical basis, the feasibility of interconnection between Xinjiang, Pakistan, and five Central Asian countries have been analyzed. This paper provides a theoretical basis for promoting and implementing China's "Belt and Road" power transnational interconnected development strategy.

Fault location of distribution networks based on multi-source information

In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance.

Design and modulation principles of molybdenum carbide-based materials for green hydrogen evolution

The green production of hydrogen from electrocatalytic water splitting is an important base and promising direction for the future of the large-scale application of hydrogen energy.The key of green hydrogen evolution depends on the development of low-cost and highly active electrocatalysts.Molybdenum carbides(MoxC),as a typical of earth-abundant transition-metal material,have accumulated great attention due to their low cost,earth abundance,electrical conductivity,similar d-band state to Pt,and regulated morphology/electronic structures.In this paper,recent researches focusing on MoxC for efficient HER in a wide pH range are summarized from respects of modulation of unique morphology,electronic structure,and electrode interface step by step.Briefly,modulation of morphology influence the apparent activity of catalyst,modulation of electronic structure of active sites by heteroatom doping and designing heterointerface boost intrinsic HER kinetics,and modulation of electrode interface via hybridization of MoxC structures with carbon materials can ensure the fast electron transfer and boost the activity.Besides the above methods discussed,perspective and challenges of designing MoxC as the substitute of Pt-based electrocatalyst for practical hydrogen generation in a wide pH range are pointed out.

Outstanding Humidity Chemiresistors Based on Imine-Linked Covalent Organic Framework Films for Human Respiration Monitoring

Human metabolite moisture detection is important in health monitoring and non-invasive diagnosis.However,ultra-sensitive quantitative extraction of respiration information in real-time remains a great challenge.Herein,chemiresistors based on imine-linked covalent organic framework(COF)films with dual-active sites are fabricated to address this issue,which demonstrates an amplified humidity-sensing signal performance.By regulation of monomers and functional groups,these COF films can be pre-engineered to achieve high response,wide detection range,fast response,and recovery time.Under the condition of relative humidity ranging from 13 to 98%,the COFTAPB-DHTA film-based humidity sensor exhibits outstanding humidity sensing perfor-mance with an expanded response value of 390 times.Furthermore,the response values of the COF film-based sensor are highly linear to the relative humidity in the range below 60%,reflecting a quantitative sensing mechanism at the molecular level.Based on the dual-site adsorption of the(-C=N-)and(C-N)stretching vibrations,the revers-ible tautomerism induced by hydrogen bonding with water molecules is demonstrated to be the main intrinsic mechanism for this effective humidity detection.In addition,the synthesized COF films can be further exploited to effectively detect human nasal and oral breathing as well as fabric permeability,which will inspire novel designs for effective humidity-detection devices.

Improving the energy efficiency of surface dielectric barrier discharge devices for plasma nitric oxide conversion utilizing active flow control

Improving energy efficiency in plasma NO removal is a critical issue.When the surface dielectric barrier discharge(SDBD)device is considered as a combination of multiple plasma actuators,the induced plasma aerodynamic effect cannot be ignored,which can affect the mass transfer,then affect the chemical reactions.Five SDBD devices with different electrode arrangements are studied for NO conversion.They correspond to different flow patterns.We find that the energy efficiency in an SDBD device with a common structure(Type 1)is 28%lower than that in SDBD devices with a special arrangement(Types 2–5).Two reasons may explain the results.First,fewer active species are produced in Type 1 because the development of discharge is hindered by the mutually exclusive electric field forces caused by the symmetrically distributed charged particles.Second,the plasma wind induced by the plasma actuator can enhance the mass and heat transfer.The mixing of reactants and products is better in Types 2–5 than Type 1 due to higher turbulence kinetic energy.

Deep Learning Accelerates the Discovery of Two- Dimensional Catalysts for Hydrogen Evolution Reaction

Two-dimensional materials with active sites are expected to replace platinum as large-scale hydrogen production catalysts.However,the rapid discovery of excellent two-dimensional hydrogen evolution reaction catalysts is seriously hindered due to the long experiment cycle and the huge cost of high-throughput calculations of adsorption energies.Considering that the traditional regression models cannot consider all the potential sites on the surface of catalysts,we use a deep learning method with crystal graph convolutional neural networks to accelerate the discovery of high-performance two-dimensional hydrogen evolution reaction catalysts from two-dimensional materials database,with the prediction accuracy as high as 95.2%.The proposed method considers all active sites,screens out 38 high performance catalysts from 6,531 two-dimensional materials,predicts their adsorption energies at different active sites,and determines the potential strongest adsorption sites.The prediction accuracy of the two-dimensional hydrogen evolution reaction catalysts screening strategy proposed in this work is at the density-functional-theory level,but the prediction speed is 10.19 years ahead of the high-throughput screening,demonstrating the capability of crystal graph convolutional neural networks-deep learning method for efficiently discovering high-performance new structures over a wide catalytic materials space.

Novel Criteria on Finite-Time Stability of Impulsive Stochastic Nonlinear Systems

Dear Editor,This letter considers the finite-time stability(FTS)problem of generalized impulsive stochastic nonlinear systems(ISNS).By employing the stochastic Lyapunov and impulsive control approach,some novel criteria on FTS are presented,where both situations of stabilizing and destabilizing impulses are considered.Furthermore,new impulse-dependent estimation strategies of stochastic settling time(SST)are proposed.

Joint Optimization of Communications and Computing Resources Allocation for Deterministic Transmission in Wireless Edge Networks

Motivated by 5th generation wireless systems(5G),a large number of emerging applications appear,which put forward higher requirements for the task’s transmission determinacy,which refers to the delay and jitter.To satisfy the deterministic requirement,mobile edge computing(MEC)is envisioned as a promising technique for reducing the end-to-end delay significantly.In this paper,we consider delaysensitive task and jitter-sensitive task,and then formulate the joint communications and computing optimization problem under the latency,the total bandwidth,the total transmission power of base station(BS)and the computing ability of the MEC server constraints to minimize the delay and jitter in a multiuser MEC system.Because of the problems are nonconvex,we decouple them into some subproblems and propose the corresponding algorithms to obtain a suboptimal solution.Finally,numerical results show that the proposed algorithms have a significant performance gain over the traditional solution in terms of the delay and the jitter.

Investigation of stimulated Raman scattering in longitudinal magnetized plasma by theory and kinetic simulation

Stimulated Raman scattering(SRS)in a longitudinal magnetized plasma is studied by theoretical analysis and kinetic simulation.The linear growth rate derived via one-dimensional fluid theory shows the dependence on the plasma density,electron temperature,and magnetic field intensity.One-dimensional particle-in-cell simulations are carried out to examine the kinetic evolution of SRS under low magnetic intensity of w_c/w_0<0.01.There are two density regions distinguished in which the absolute growth of enveloped electrostatic waves and spectrum present quite different characteristics.In a relatively low-density plasma(ne~0.20 nc),the plasma wave presents typical absolute growth and the magnetic field alleviates linear SRS.While in the plasma whose density is near the cut-off point(ne~0.23 nc),the magnetic field induces a spectral splitting of the backscattering and forward-scattering waves.It has been observed in simulations and verified by theoretical analysis.Due to this effect,the onset of reflectivity delays,and the plasma waves form high-frequency oscillation and periodic envelope structure.The split wavenumber Dk/k0 is proportional to the magnetic field intensity and plasma density.These studies provide novel insight into the kinetic behavior of SRS in magnetized plasmas.

An efficient approach of EEG feature extraction and classification for brain computer interface

In the study of brain-computer interfaces,a method of feature extraction and classification used fortwo kinds of imaginations is proposed.It considers Euclidean distance between mean traces recorded fromthe channels with two kinds of imaginations as a feature,and determines imagination classes using thresh-old value.It analyzed the background of experiment and theoretical foundation referring to the data sets ofBCI 2003,and compared the classification precision with the best result of the competition.The resultshows that the method has a high precision and is advantageous for being applied to practical systems.

Application of Kernel GDA to Performance Monitoring and Fault Diagnosis for Rotating Machinery

Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on kernel generalized discriminant analysis(kernel GDA,KGDA)was proposed.Through KGDA,the data were mapped from the original space to the high-dimensional feature space.Then the statistic distance between normal data and test data was constructed to detect whether a fault was occurring.If a fault had occurred,similar analysis was used to identify the type of faults.The effectiveness of the proposed method was evaluated by simulation results of vibration signal fault dataset in the rotating machinery,which was scalable to different rotating machinery.