贝叶斯网参数学习中连续变量离散化方法研究

连续变量离散化是贝叶斯网络参数学习中面临的一个重要问题,它的好坏将直接影响到贝叶斯网络的推理效果。目前缺少一种有效的手段用于评价连续变量离散化的好坏,通过研究,提出了推理信息量的概念,并采用作为衡量连续变量离散化好坏的标准。在连续变量离散化的过程中,采用遗传算法通过迭代的方式寻求最优解,其中,推理信息量作为衡量个体适应度的标准。实例分析证明,推理信息量大的推理效果好要优于推理信息量小的推理效果。     

一种求解Shubert函数优化问题的演化算法

综合国内外演化计算研究现状,基于热力学中的自由能极小化原理, 设计了一个全新的热力学演化算法,并通过对于Shubert函数优化问题求解的数值试验,测试了热力学演化算法的优良性能,实验结果表明了热力学演化算法求出的解比一般演化算法求出的解更加接近于全局最优。     

常用的基于控制流的测试充分性准则

本文介绍了几种在软件测试中常用的基于控制流的测试充分性评价准则。这些测试充分性准则适用于用过程式语言、面向对象语言编写的程序。测试人员可用这些准则判断究竟测试了多少代码,还有多少代码未测试到。     

Weak signal detection and adaptive synchronous stability of a novel fifth-order memristive circuit system

This paper is devoted to introduce a novel complex fifth-order memristive circuit system and its applications in synchronous stability and weak signal detection. Firstly, the typical dynamical behaviors of the memristive system are discussed by chaotic phase portrait, complexity analysis, one-parameter bifurcation and Lyapunov exponent spectrum. Secondly, the adaptive control method is applied to realize the synchronization between the drive memristive system (DMS) and the response memristive system (RMS). The results indicate that the synchronization method has strong robustness and anti-interference ability. Thirdly, the weak signal detection of the novel five-dimensional memristive system is realized by using the extreme sensitivity of chaotic system to initial values. Finally, the fifth-order memristive circuit is designed by using basic electronic elements and simulated by Multisim software. And the anti-interference ability and sensitivity of the fifth-order memristive circuit are further verified by adding different weak disturbance signals at different positions of the circuit.     

Multi-objective routing algorithms for low-earth orbit satellite network

The low-earth orbit (LEO) satellite network, composed of a large number of satellite nodes, is a hot research topic at present. Due to the characteristics of the large-scale LEO satellite network, such as many satellite nodes, short orbit period, large dynamic change of topology, and unstable link-state, its communication quality of service (QoS) requirements are difficult to meet. Aiming at this problem, various factors that may affect data transmission are first analyzed. The network link selection problem is modeled as a multi-constraint optimization decision problem, a routing mathematical model based on linear programming (LP) is designed, and its solution is solved. Aiming at the problem of limited onboard computing resources, a multi-object optimization Dijkstra algorithm (MOODA) is designed. The MOODA finds the optimal path according to the comprehensive performance of the link. It solves the problems of poor comprehensive QoS performance and the low degree of load balancing of the paths found by the Dijkstra algorithm. The simulation results show that the paths found by the two algorithms have good QoS, robustness, and load balancing performance.     

2D MoN1.2-rGO Stacked Heterostructures Enabled Water State Modification for Highly Efficient Interfacial Solar Evaporation

Improving interfacial solar evaporation performance is crucial for the practical application of this technology in solar-driven seawater desalination. Lowering evaporation enthalpy is one of the most promising and effective strategies to significantly improve solar evaporation rate. In this study, a new pathway to lower vaporization enthalpy by introducing heterogeneous interactions between hydrophilic hybrid materials and water molecules is developed. 2D MoN_1.2 nanosheets are synthesized and integrated with rGO nanosheets to form stacked MoN_1.2-rGO heterostructures with massive junction interfaces for interfacial solar evaporation. Molecular dynamics simulation confirms that atomic thick 2D MoN_1.2 and rGO in the MoN_1.2-rGO heterostructures simultaneously interact with water molecules, while the interactions are remarkably different. These heterogeneous interactions cause an imbalanced water state, which easily breaks the hydrogen bonds between water molecules, leading to dramatically lowered vaporization enthalpy and improved solar evaporation rate (2.6 kg m⁻² h⁻¹). This study provides a promising strategy for designing 2D-2D heterostructures to regulate evaporation enthalpy to improve solar evaporate rate for clean water production.     

Nano-Engineered Carbon Fibre-Based Piezoelectric Smart Composites for Energy Harvesting and Self-Powered Sensing

The integration of piezoelectric materials onto carbon fiber (CF) can add energy harvesting and self-power sensing capabilities enabling great potential for “Internet of Things” (IoT) applications in motion tracking, environmental sensing, and personal portable electronics. Herein, a CF-based smart composite is developed by integrating piezoelectric poly(3,4-ethylenedioxythiophene) (PEDOT)/CuSCN-coated ZnO nanorods onto the CF surfaces with no detrimental effect on the mechanical properties of the composite, forming composites using two different polymer matrices: highly flexible polydimethylsiloxane (PDMS) and more rigid epoxy. The PDMS-coated piezoelectric smart composite can serve as an energy harvester and a self-powered sensor for detecting variations in impact acceleration with increasing output voltage from 1.4 to 7.6 V under impact acceleration from 0.1 to 0.4 m s⁻². Using epoxy as the matrix for a CF-reinforced plastic (CFRP) device with sensing and detection functions produces a voltage varying from 0.27 to 3.53 V when impacted at acceleration from 0.1 to 0.4 m s⁻², with a lower output compared to the PDMS-coated device attributed to the greater stiffness of the matrix. Finally, spatially sensitive detection is demonstrated by positioning two piezoelectric structures at different locations, which can identify the location as well as the level of the impacting force from the fabricated device.     

Tough Transient Ionic Junctions Printed with Ionic Microgels

Emerging soft ionotronics better match the human body mechanically and electrically compared to conventional rigid electronics. They hold great potential for human-machine interfaces, wearable and implantable devices, and soft machines. Among various ionotronic devices, ionic junctions play critical roles in rectifying currents as electrical p–n junctions. Existing ionic junctions, however, are limited in electrical and mechanical performance, and are difficult to fabricate and degrade. Herein, the design, fabrication, and characterization of tough transient ionic junctions fabricated via 3D ionic microgel printing is reported. The 3D printing method demonstrates excellent printability and allows one to fabricate ionic junctions of various configurations with high fidelity. By combining ionic microgels, degradable networks, and highly charged biopolymers, the ionic junctions feature high stretchability (stretch limit 27), high fracture energy (>1000 Jm⁻²), excellent electrical performance (current rectification ratio >100), and transient stability (degrade in 1 week). A variety of ionotronic devices, including ionic diodes, ionic bipolar junction transistors, ionic full-wave rectifiers, and ionic touchpads are further demonstrated. This study merges ionotronics, 3D printing, and degradable hydrogels, and will motivate the future development of high-performance transient ionotronics.     

Surface Oxygen Coordination of Hydrogen Bond Chemistry for Aqueous Ammonium Ion Hybrid Supercapacitor

Aqueous ammonium ion hybrid supercapacitor (A-HSC) combines the charge storage mechanisms of surface adsorption and bulk intercalation, making it a low-cost, safe, and sustainable energy storage candidate. However, its development is hindered by the low capacity and unclear charge storage fundamentals. Here, the strategy of phosphate ion-assisted surface functionalization is used to increase the ammonium ion storage capacity of an α-MoO₃ electrode. Moreover, the understanding of charge storage mechanisms via structural characterization, electrochemical analysis, and theoretical calculation is advanced. It is shown that NH₄⁺ intercalation into layered α-MoO₃ is not dominant in the A-HSC system; rather, the charge storage mainly depends on the adsorption energy of surface “O” to NH₄⁺. It is further revealed that the hydrogen bond chemistry of the coordination between “O” of surface phosphate ion and NH₄⁺ is the reason for the capacity increase of MoO₃. This study not only advances the basic understanding of rechargeable aqueous A-HSC but also demonstrates the promising future of surface engineering strategies for energy storage devices.     

Highly Conductive MXene/PEDOT:PSS-Integrated Poly(N-Isopropylacrylamide) Hydrogels for Bioinspired Somatosensory Soft Actuators

Sophisticated sensing and actuation capabilities of many living organisms in nature have inspired scientists to develop biomimetic somatosensory soft robots. Herein, the design and fabrication of homogeneous and highly conductive hydrogels for bioinspired somatosensory soft actuators are reported. The conductive hydrogels are synthesized by in situ copolymerization of conductive surface-functionalized MXene/Poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) ink with thermoresponsive poly(N-isopropylacrylamide) hydrogels. The resulting hydrogels are found to exhibit high conductivity (11.76 S m⁻¹), strain sensitivity (GF of 9.93), broad working strain range (≈560% strain), and high stability after over 300 loading–unloading cycles at 100% strain. Importantly, shape-programmable somatosensory hydrogel actuators with rapid response, light-driven remote control, and self-sensing capability are developed by chemically integrating the conductive hydrogels with a structurally colored polymer. As the proof-of-concept illustration, structurally colored hydrogel actuators are applied for devising light-driven programmable shape-morphing of an artificial octopus, an artificial fish, and a soft gripper that can simultaneously monitor their own motions via real-time resistance variation. This work is expected to offer new insights into the design of advanced somatosensory materials with self-sensing and actuation capabilities, and pave an avenue for the development of soft-matter-based self-regulatory intelligence via built-in feedback control that is of paramount significance for intelligent soft robotics and automated machines.