High lithium storage of Co3O4 enabled by integrating hollow and porous carbon scaffolds

The Co₃O₄, as a potential anode of lithium-ion batteries, has gained considerable attention because of high theoretical capacity. However, the Co₃O₄ is suffering from serious structure deterioration and rapid capacity fading due to its bulky volume change during cyclic charge/discharge process. Herein, to stabilize the lithium storage performance of the Co₃O₄ nanoparticles, a characteristic carbon scaffold (HPC) integrating hollow and porous structures has been fabricated by a well-designed method for the first time. The ultrafine Co₃O₄ nanoparticles are cleverly anchored on the HPC (HPC@Co₃O₄) and hence achieve significantly improved electrochemical properties including high capacity, improved reaction kinetics and outstanding cycle stability, showing high capacity of 1084.7 mAh g^-1 after 200 cycles at 200 mA g^-1 as well as 681.4 mAh g^-1 after 300 cycles at 1000 mA g^-1. The HPC@Co₃O₄ therefore shows good promising for application in advanced lithium-ion battery anodes. The results of the systematically material and electrochemical characterizations indicate that the synergistic effects of ultrafine Co₃O₄ nanoparticles and well-designed HPC scaffolds are responsible for the outstand performance of the HPC@Co₃O₄ anode. Moreover, this work can enrich the understanding and development of stable and high-performance metal oxide-based lithium-ion battery anodes for advanced lithium storage.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

计算机网络办公自动化及安全策略探究

互联网通讯采取标准化模式主要以TCP/IP协议为载体,通讯的优越特性体现在同时具备便捷性与开放性,为办公提供很大的便利,但基于网络系统也会入侵病毒、也会给信息数据与办公体系安全性造成威胁,直接影响企业综合稳定发展。据此,为保障办公工作的顺利开展,本文对计算机网络办公自动化及安全策略进行详细分析。     

Field-Effect Chiral Anomaly Devices with Dirac Semimetal

Charge-based field-effect transistors (FETs) greatly suffer from unavoidable carrier scattering and heat dissipation. Analogous to valley degree of freedom in semiconductors, chiral anomaly current in Weyl/Dirac semimetals is theoretically predicted to be nearly nondissipative over long distances, but still lacks experimental ways to efficiently control its transport. Here, field-effect chirality devices are demonstrated with Dirac semimetal PtSe₂, in which its Fermi level is close to the Dirac point in the conduction band owing to intrinsic defects. The chiral anomaly is further corroborated by the planar Hall effect and nonlocal valley transport measurement, which can also be effectively modulated by external fields, showing robust nonlocal valley transport with micrometer diffusion length. Similar to charge-based FETs, the chiral conductivity in PtSe₂ devices can be modulated by electrostatic gating with an ON/OFF ratio of more than 10³. Basic logic functions in the devices are also demonstrated with electric and magnetic fields as input signals.     

Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time scheduling has become a problem to be solved. In this regard, automatic design for shop scheduling based on hyper-heuristics has been widely studied, and a number of reviews and scheduling algorithms have been presented. Few studies, however, have specifically discussed the technical points involved in algorithm development. This study, therefore, constructs a general framework for automatic design for shop scheduling strategies based on hyper-heuristics, and various state-of-the-art technical points in the development process are summarized. First, we summarize the existing types of shop scheduling strategies and classify them using a new classification method. Second, we summarize an automatic design algorithm for shop scheduling. Then, we investigate surrogate-assisted methods that are popular in the current algorithm field. Finally, current problems and challenges are discussed, and potential directions for future research are proposed.     

Anticancer activity of flavonoids accompanied by redox state modulation and the potential for a chemotherapeutic strategy

Since researchers began studying the mechanism of flavonoids’ anticancer activity, little attention has been focused on the modulation of redox state in cells as a potential chemotherapeutic strategy. However, recent studies have begun identifying that the anticancer effect of flavonoids occurs both in their antioxidative activity which scavenges ROS and their prooxidative activity which generates ROS. Against this backdrop, this study attempts to achieve a comprehensive analysis of the individual and separate study findings regarding flavonoids’ modulation of redox state in cancer cells. It focuses on the mechanism behind the anticancer effect, and mostly on the modulation of redox potential by flavonoids such as quercetin, hesperetin, apigenin, genistein, epigallocatechin-3-gallate (EGCG), luteolin and kaempferol in both in vitro and animal models. In addition, the clinical applications of and bioavailability of flavonoids were reviewed to help build a treatment strategy based on flavonoids’ prooxidative potential.     

Distributed two‐stage state estimation with event‐triggered strategy for multirate sensor networks

This paper investigates the state estimation issue for a class of wireless sensor networks (WSNs) with the consideration of limited energy resources. First, a multirate estimation model is established, and then, a new event‐triggered two‐stage information fusion algorithm is developed based on the optimal fusion criterion weighted by matrices. Compared with the existing methods, the presented fusion algorithm can significantly reduce the communication cost in WSNs and save energy resources of sensors efficiently. Furthermore, by presetting a desired containment probability over the interval [0,1] with the developed event‐triggered mechanism, one can obtain a suitable compromise between the communication cost and the estimation accuracy. Finally, a numerical simulation for the WSN tracking system is given to demonstrate the effectiveness of the proposed method.     

A fuzzy logic PI control with feedforward compensation for hydrogen pressure in vehicular fuel cell system

In a vehicular fuel cell system, alternative load and frequent purge action can lead to anode pressure varies with the hydrogen mass flow fluctuation. It's crucial to control the pressure difference between anode and cathode within a reasonable range to avoid adverse phenomena such as membrane failure, reactant starvation, or even water management fault. In this paper, an improved proportional integrative (PI) controller by the fuzzy logic technique that considers the engineer experience and knowledge on the hydrogen supply system behavior is proposed for hydrogen pressure control, in which the PI parameters are tuned by a fuzzy decision process. Furthermore, load current and purge action regarded as input disturbances are applied for feedforward compensation to reduce the pressure response hysteresis. A hydrogen supply subsystem based on the proportional valve is modeled, and corresponding parameters are determined by analyzing the response time and steady pressure fluctuation. The performance of the conventional PI controller, the fuzzy logic PI (FLPI) controller and fuzzy logic PI with feedforward (FLPIF) controller is validated. The presented results indicated that the FLPI controller significantly improves the dynamic response of hydrogen pressure compared to the PI controller, and the FLPIF controller can further reduce overshoot caused by disturbance. Finally, the proposed FLPIF controller is implemented on a rapid prototype platform of the hydrogen supply subsystem and an actual fuel cell system, exhibiting satisfactory performance.     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.     

Engineering Nanorobots for Tumor-Targeting Drug Delivery: From Dynamic Control to Stimuli-Responsive Strategy

Nanotechnology has been widely applied to the fabrication of drug delivery systems in the past decades. Recently, with the progress made in microfabrication approaches, nanorobots are steadily becoming a promising means for tumor-targeting drug delivery. In general, nanorobots can be divided into two categories: nanomotors and stimuli-responsive nanorobots. Nanomotors are nanoscale systems with the ability to convert surrounding energies into mechanical motion, whereas stimuli-responsive nanorobots are featured with activatable capacity in response to various endogenous and exogenous stimulations. In this minireview, the dynamic control of nanomotors and the rational design of stimuli-responsive nanorobots are overviewed, with particular emphasis on their contribution to tumor-targeting therapy. Moreover, challenges and perspectives associated with the future development of nanorobots are presented.