Effects of upholstery materials on the burning behavior of real‐scale residential upholstered furniture mock‐ups

Fire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF.     

基于改进残差特征蒸馏的轻量级超分辨率网络

基于深度学习的图像超分辨率算法通常采用递归的方式或参数共享的策略来减少网络参数，这将增加网络的深度，使得运行网络花费大量的时间，从而很难将模型部署到现实生活中。为了解决上述问题，本文设计一种轻量级超分辨率网络，对中间特征的关联性及重要性进行学习，且在重建部分结合高分辨率图像的特征信息。首先，引入层间注意力模块，通过考虑层与层之间的相关性，自适应地分配重要层次特征的权重。其次，使用增强重建模块提取高分辨率图像中更精细的特征信息，以此得到更加清晰的重建图片。通过大量的对比实验表明，本文设计的网络与其他轻量级模型相比，有更小的网络参数量，并且在重建精度和视觉效果上都有一定的提升。     

Nido-Hydroborate-Based Electrolytes for All-Solid-State Lithium Batteries

Hydroborate-based solid electrolytes have recently been successfully employed in high voltage, room temperature all-solid-state sodium batteries. The transfer to analogous lithium systems has failed up to now due to the lower conductivity of the corresponding lithium compounds and their high cost. Here LiB₁₁H₁₄ nido-hydroborate as a cost-effective building block and its high-purity synthesis is introduced. The crystal structures of anhydrous LiB₁₁H₁₄ as well as of LiB₁₁H₁₄-based mixed-anion solid electrolytes are solved and high ionic conductivities of 1.1 × 10⁻⁴ S cm⁻¹ for Li₂(B₁₁H₁₄)(CB₁₁H₁₂) and 1.1 × 10⁻³ S cm⁻¹ for Li₃(B₁₁H₁₄)(CB₉H₁₀)₂ are obtained, respectively. LiB₁₁H₁₄ exhibits an oxidative stability limit of 2.6 V versus Li⁺/Li and the proposed decomposition products are discussed based on density functional theory calculations. Strategies are discussed to improve the stability of these compounds by modifying the chemical structure of the nido-hydroborate cage. Galvanostatic cycling in symmetric cells with two lithium metal electrodes shows a small overpotential increase from 22.5 to 30 mV after 620 h (up to 0.5 mAh cm⁻²), demonstrating that the electrolyte is compatible with metallic anodes. Finally, the Li₂(B₁₁H₁₄)(CB₁₁H₁₂)  electrolyte is employed in a proof-of-concept half cell with a TiS₂ cathode with a capacity retention of 82% after 150 cycles at C/5.     

Association of TaD14-4D,a Gene Involved in Strigolactone Signaling,with Yield Contributing Traits in Wheat

Tillering is a crucial agronomic trait of wheat; it determines yield and plant architecture. Strigolactones (SLs) have been reported to inhibit plant branching. D14, a receptor of SLs, has been described to affect tillering in rice, yet it has seldomly been studied in wheat. In this study, three TaD14 homoeologous genes, TaD14-4A, TaD14-4B, and TaD14-4D, were identified. TaD14-4A, TaD14-4B, and TaD14-4D were constitutively expressed, and TaD14-4D had a higher expression level in most tissues. TaD14 proteins were localized in both cytoplasm and nucleus. An SNP and a 22 bp insertion/deletion (Indel) at the exon regions of TaD14-4D were detected, forming three haplotypes, namely 4D-HapI, 4D-HapII, and 4D-HapIII. Due to the frameshift mutation in the coding region of 4D-HapII, the interaction of 4D-HapII with TaMAX2 and TaD53 was blocked, which led to the blocking of SL signal transduction. Based on the two variation sites, two molecular markers, namely dCAPS-250 and Indel-747, were developed. Association analysis suggested that haplotypes of TaD14-4D were associated with effective tillering number (ETN) and thousand kernel weight (TKW) simultaneously in four environments. The favorable haplotype 4D-HapIII underwent positive selection in global wheat breeding. This study provides insights into understanding the function of natural variations of TaD14-4D and develops two useful molecular markers for wheat breeding.     

Benchmark experiment of large-angle scattering reaction cross section of iron at 14 MeV using two shadow bars – Comparison of experimental results with ENDF/B-VIII –

ABSTRACT

It is important to perform neutron transport simulations with accurate nuclear data in the neutronics design of a fusion reactor. However, absolute values of large-angle scattering cross sections vary among nuclear data libraries even for well-examined nuclide of iron. Benchmark experiments focusing on large-angle scattering cross sections were thus performed to confirm the correctness of nuclear data libraries. The series benchmark experiments were performed at a DT neutron source facility, OKTAVIAN of Osaka University, Japan, by the unique experimental system established by the authors’ group, which can extract only the contribution of large-angle scattering reactions. This system consists of two shadow bars, target plate (iron), and neutron detector (niobium). Two types of shadow bars were used and four irradiations were conducted for one experiment, so that contribution of room-return neutrons was effectively removed and only large-angle scattering neutrons were extracted from the measured four Nb reaction rates. The obtained experimental results were compared with calculations for five nuclear data libraries including JENDL-4.0, JEFF.-3.3, FENDL-3.1, ENDF/B- VII, and recently released ENDF/B-VIII. It was found from the comparison that ENDF/B-VIII showed the best result, though ENDF/B-VII showed overestimation and others are in large underestimation at 14 MeV.     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

我国中空吹塑行业发展现状及“十四五”期间重点产品、工艺和设备发展方向

从原料、中空成型机和吹塑工艺等方面介绍了我国中空吹塑行业发展现状，并对电子化学品专用超洁净桶、高压储氢四型瓶、全电动中空成型机、微发泡中空成型技术和挤吹聚对苯二甲酸乙二醇酯（PET）容器等在“十四五”期间的重点产品、工艺和设备发展方向进行了展望。     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

Design of energy‐efficient train speed profiles considering fixed‐block signaling system

In dense traffic railway networks, trains may often slow down or stop between stations owing to previous train delays. If preceding train trajectory can be predicted, energy‐efficient driving can be achieved by suppressing unnecessary speed changes. In this paper, we propose an algorithm to find energy‐efficient driving considering fixed‐block signaling (FBS) system by using dynamic programming (DP). DP is suitable for use because it can optimize the control inputs with discrete and state constraints. In this paper, we discuss energy‐efficient driving by considering a FBS system using some case studies of simulation. In the simulation, we examine a technique to drive an express train in an energy‐efficient way when the preceding local train is running toward the station with passing loops. The results show that the proposed method can derive complex speed profiles for energy‐efficient driving and the train can be operated with a maximum reduced energy consumption of 8.3%.     

BHDDF350型联轴器失效分析及改进设计

联轴器在旋转过程中连续传递扭矩且具备一定缓冲和减振的保护作用,而又不改变初始旋转方向和扭矩大小,BHDDF350型联轴器是某型矿用减速机与电机之间的扭矩传动部件。从该型联轴器的运行工况、结构分布、损坏形式等方面查找并分析了其失效原因,依据其受力分析提出了改进型设计方案,以供业内参考。改进设计后的联轴器,弹性块受力均匀,且最大受力降比30%以上,可有效延长联轴器的整体使用寿命,减少了煤矿井下日常的维护工作量。