Microstructures and properties of nickel-titanium carbide composites fabricated by laser cladding

In this work, Ni/TiC composites were synthesized by the laser cladding technique (LCT). A scanning electron microscope (SEM), X-ray diffractometer (XRD), microhardness meter, electrochemical workstation, and friction and wear tester examined the microstructure, surface morphology, phase structure, microhardness, wear, and corrosion resistances of the Ni/TiC composites. These results indicated the Ni/40TiC composite contained finer equiaxed crystals than the Ni and Ni/20TiC composites. In addition, numerous TiC particles in the Ni/40TiC composite impeded growth of the nickel crystals, which resulted in the fine microstructure of the Ni/40TiC composite. The Ni, Ni/20TiC, and Ni/40TiC composites exhibited face-centered cubic (f c c) lattices. The average microhardness values of the Ni/20TiC and Ni/40TiC composites were approximately 748 HV and 851 HV, respectively. The Ni/40TiC composite had the lowest friction coefficient (0.43) among all three coatings, and only some shallow scratches appeared on the surface of the Ni/40TiC composite. The corrosion potential (E) of Ni/40TiC exceeded the Ni/20TiC composite, and both were larger than the Ni composite, which indicated the Ni/40TiC composite had outstanding corrosion resistance and the Ni composite had poor corrosion resistance. The corrosion current densities (i) of Ni, Ni/20TiC, and Ni/40TiC composites were 5.912, 4.405, and 3.248 μA/cm², respectively.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

The production of Indo-Pacific monochrome drawn glass beads in the Sasanian Empire: Insights from Xinjiang,northwest China

Indo-Pacific glass beads are produced by the drawn technique, which originates from South Asia, and their chemical compositions are unique in South and Southeast Asia. However, a small number of Indo-Pacific beads with Sassanian glass compositions are excavated in Asia and Africa after the 3rd c. CE, and their production sites in South/Southeast Asia or in the Sassanian region remain controversial. In this study, 15 drawn glass beads with various colours from Astana necropolis (ca. the 4th-8th c. CE) in Xinjiang, northwest China were investigated by using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), Scanning Electron Microscope, Raman spectroscopy and visible to near-infrared spectroscopy to characterize the production technology and origins. The results show that most Astana glass beads share similar chemical compositions with the glassware from Veh Arda?īr, a famous Sasanian site. Furthermore, Sasanian glass compositions predominate in Indo-Pacific beads in Xinjiang during the 4th-8th c. CE, while popular glass recipes in contemporary South/Southeast Asia are infrequently found; thus, it is deduced that the drawn method should have been mastered by Sasanian craftsmen. Moreover, the cobalt materials in Sasanian glass were imported from further western regions and changed over time. The popular Sasanian glass across central Eurasia reflects the trade monopoly of Sasanian in West and Central Asia, and the land glass bead trade is distinct from the contemporary maritime trade in the Indian and Pacific Oceans.     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

The Function of Sialidase Revealed by Sialidase Activity Imaging Probe

Sialidase cleaves sialic acid residues from glycans such as glycoproteins and glycolipids. In the brain, desorption of the sialic acid by sialidase is essential for synaptic plasticity, learning and memory and synaptic transmission. BTP3-Neu5Ac has been developed for sensitive imaging of sialidase enzyme activity in mammalian tissues. Sialidase activity in the rat hippocampus detected with BTP3-Neu5Ac increases rapidly by neuronal depolarization. It is presumed that an increased sialidase activity in conjunction with neural excitation is involved in the formation of the neural circuit for memory. Since sialidase inhibits the exocytosis of the excitatory neurotransmitter glutamate, the increased sialidase activity by neural excitation might play a role in the negative feedback mechanism against the glutamate release. Mammalian tissues other than the brain have also been stained with BTP3-Neu5Ac. On the basis of information on the sialidase activity imaging in the pancreas, it was found that sialidase inhibitor can be used as an anti-diabetic drug that can avoid hypoglycemia, a serious side effect of insulin secretagogues. In this review, we discuss the role of sialidase in the brain as well as in the pancreas and skin, as revealed by using a sialidase activity imaging probe. We also present the detection of influenza virus with BTP3-Neu5Ac and modification of BTP3-Neu5Ac.     

2.3–21 GHz broadband and high linearity distributed low noise amplifier

This paper focuses on the design of a 2.3–21 GHz Distributed Low Noise Amplifier (LNA) with low noise figure (NF), high gain (S₂₁), and high linearity (IIP3) for broadband applications. This distributed amplifier (DA) includes S/C/X/Ku/K-band, which makes it very suitable for heterodyne receivers. The proposed DA uses a 0.18 μm GaAs pHEMT process (OMMIC ED02AH) in cascade architecture with lines adaptation and equalization of phase velocity techniques, to absorb their parasitic capacitances into the gate and drain transmission lines in order to achieve wide bandwidth and to enhance gain and linearity. The proposed broadband DA achieved an excellent gain in the flatness of 13.5 ± 0.2 dB, a low noise figure of 3.44 ± 1.12 dB, and a small group delay variation of ±19.721 ps over the range of 2.3–21 GHz. The input and output reflection coefficients S₁₁ and S₂₂ are less than −10 dB. The input compression point (P_1dB) and input third-order intercept point (IIP3) are −1.5 dBm and 11.5 dBm, respectively at 13 GHz. The dissipated power is 282 mW and the core layout size is 2.2 × 0.8 mm².     

基于PBFT区块链技术的电网企业仓储系统

提出了一种基于实用拜占庭容错(PBFT)算法的区块链技术,首先对传统的实用拜占庭容错算法原理进行了阐述,该传统算法包含前期、需求、预准备、准备、确认、答复6个阶段,但传统算法具有实时性差、缺乏惩罚机制、带宽高的缺点。针对出现的这些问题,又对传统算法进行了改进,具体涉及记账节点、共识过程以及视图切换过程。通过测试进一步证明了该改进算法的实用性,并将该算法应用于电网企业中,构建的虚拟仓库实现了联储联备,降低了库存资金的耗费,并且提高了电网企业库存管理的效率。     

Effect of apple cider vinegar agent on the microstructure,phase evolution,and magnetic properties of CoFe2O4 magnetic nanoparticles

In the present study, spinel structure CoFe₂O₄ nanoparticles were successfully synthesized by the sol-gel auto-combustion technique. The effect of apple cider vinegar (ACV) addition as an organic biocompatible agent on the size, morphology, and magnetic properties of CoFe₂O₄ nanoparticles was investigated in detail. The phase evolution, particle size, and lattice parameter changes of the synthesized phase have been estimated by using Rietveld structure refinement analysis of X-ray powder diffraction data. Also, Fourier transform infrared spectra (FT-IR) of the samples verified the presence of two expected bands correspond to tetrahedral and octahedral metal-oxygen complexes within the spinel structure. Furthermore, microstructural observations revealed that ultrafine particles have a semi-spherical morphology. It was shown that the particles size decreased from ~45 to ~17 nm with an increase in the amount of ACV. Magnetic properties were carried out by vibrating sample magnetometer (VSM) at room temperature. Both the saturation magnetization (M_s) and coercivity (H_c) were found to be significantly dependent on the crystallite size and the amount of ACV.     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

Cognitive abilities,digital games and arithmetic performance enhancement: A study comparing the effects of a math game and paper exercises

Besides entertainment, games have shown to have the potential to impact a broader variety of cognitive abilities. Research has consistently shown that several aspects in cognition such as visual short-memory, multitasking and spatial skills can be enhanced by game play. In a previous study, it was found that playing Monkey Tales, a game aimed at training arithmetic skills, helped second grade pupils to increase their accuracy in mental calculation as compared to paper exercises. In this follow up study we explore whether traditional methods and game training differ in terms of the cognitive processes that both are able to impact. We incorporated standardized measures of working memory and visuo-motor skills. Additionally, the mathematics game was modified and its contents extracted to allow precise comparison between the gaming and paper exercises condition. Thus each single math exercise, type of question (e.g., multiple choice), quantity and order was perfectly matched in the game training and the traditional training conditions. Gains in arithmetical performance, and self-reported measures of enjoyment were also investigated. We found some evidence suggesting that arithmetic performance enhancement induced by game play and paper exercises differ not only in terms of enjoyment but also of working memory capacity improvements.