A Dynamic Anomaly Detection Approach Based on Permutation Entropy for Predicting Aging-Related Failures

Software aging is a phenomenon referring to the performance degradation of a long-running software system. This phenomenon is an accumulative process during execution, which will gradually lead the system from a normal state to a failure-prone state. It is a crucial challenge for system reliability to predict the Aging-Related Failures (ARFs) accurately. In this paper, permutation entropy (PE) is modified to Multidimensional Multi-scale Permutation Entropy (MMPE) as a novel aging indicator to detect performance anomalies, since MMPE is sensitive to dynamic state changes. An experiment is set on the distributed database system Voldemort, and MMPE is calculated based on the collected performance metrics during execution. Finally, based on MMPE, a failure prediction model using the machine learning method to reveal the anomalies is presented, which can predict failures with high accuracy.     

Chemists around the World,Take Your Part in the Circular Economy!

Based on recent examples and initiatives reported in the literature, this concept article discusses how chemistry can contribute to the circular economy approach in order to improve our current and future economical, societal, and environmental system. Through five proposed levels of contribution, chemists can take a significant part in this global approach via the consideration of green chemistry principles, the simplification of syntheses, the limitation of complex products preparation, the efficient utilization of resources but also the novel ways of waste valorization. A more systematic and generalized environmental and economic assessment from the lab-scale is also recommended. At last, chemists have to work even more collaboratively and in a multidisciplinary way, within chemistry and beyond.     

Fatigue Behavior of Composite Sandwich Panels Under Three Point Bending Load

In this paper, the bending fatigue tests of honeycomb sandwich panels are carried out by using an improved three-point bending test fixture, and the S-N curves at different stress ratios are obtained. Through the records of fatigue damage in the experiment, the failure mode of the honeycomb sandwich panels and the source of fatigue damage are determined. At the same time, through the calculation of the shear stress distribution on the honeycomb wall, the reasons for the difference in the failure morphology of the L-direction and W-direction sandwich panels are clarified. Besides, a life prediction method is proposed and its effectiveness in predicting the fatigue life of sandwich panels has been verified.     

基于SVM的固化土无侧限抗压强度模型

为实现较少试验次数下固化土无侧限抗压强度(qu)的准确预测, 提出了基于支持向量机(SVM)的固化土qu的预测模型. 以固化剂各组分掺入比、龄期、初始含水量、固化剂掺量等因素为输入量, 固化土的qu作为输出量, 以径向基为核函数, 采用网格搜索法和交叉验证法进行参数优化, 建立了基于SVM的固化土qu的预测模型. 算例分析表明: 该模型适用于任意条件下固化土qu的精确预测, 且在较小试验成本下实现与响应面法相当的预测精度.     

一种轿车车轮应力状态测量与分析方法

基于台架应变测试试验方法,研究轿车车轮在疲劳试验中的应力状态。结果表明:车轮的径向疲劳试验时,轮胎会对车轮的载荷产生较大的影响,轮胎与转鼓的挤压变形以及正反转动都会对车轮的应力状态产生影响;车轮径向疲劳试验时,最大应变出现在轮辋与轮胎接触位置沿车轮圆周方向,而在靠近轮心位置的应变较小;车轮弯曲疲劳试验时,最大应变出现在轮辐靠近轮心的位置,最大应变出现在轮辐的长度方向;不同的载荷对车轮应变的变化规律并没有影响,但是会对最大和最小峰值产生影响。     

Characteristic material parameters of CIGS solar cell related with device performance

CIGS solar cells with power conversion efficiency (PCE) in the range of 1.82%–12.30% were obtained by using two-step process, and were further analyzed through various measurement techniques. Material parameters showed diverse values and some trends depending on the device performance. The lower performance device showed small integrated PL intensity, short minority life time, larger defect density and lower activation energy, whereas the higher performance device showed opposite values. We investigated relationship between material parameters and PCE of solar cells, and found that some physical parameters such as integrated PL intensity, minority life time, defect density, and difference between band gap and activation energy (E_g-E_a), which all reflect defect states in bulk and at pn interface, are strongly related with PCE and would be used as a good indicator to evaluate device performance quickly.     

New Opportunities for the Utilization of the Sulfoximine Group in Medicinal Chemistry from the Drug Designer's Perspective**

Extension of the medicinal chemistry toolbox is in the vital interest of drug designers. However, the diffusion of an innovation can be a lengthy process. Along these lines, it took almost 70 years before the use of the sulfoximine group reached a critical mass in medicinal chemistry. Even though interest in this versatile functional group has increased exponentially in recent years, there is ample room for further innovative applications. This Review highlights emerging trends and opportunities for drug designers for the utilization of the sulfoximine group in medicinal chemistry, such as in the construction of complex molecules, proteolysis targeting chimeras (PROTACs), antibody-drug conjugates (ADCs) and novel warheads for covalent inhibition.     

一种经验型疲劳小裂纹扩展模型

金属材料疲劳寿命由裂纹萌生和裂纹扩展寿命两部分组成，其中对于萌生寿命中的小裂纹分析是精确描述裂纹萌生寿命的关键．而小裂纹在扩展过程中由于尺寸相对较小，导致传统线弹性断裂力学预测方法失效，需要对其进行改进，考虑裂纹尖端塑性区引起的残余压应力对小裂纹扩展速度的影响．本文针对此问题进行了初步分析，通过对塑性区引起的残余应力的量化，结合小裂纹门槛值特性，提出了一种经验型修正的小裂纹扩展模型，用于定量预测裂纹的萌生寿命．使用铝合金6082-T6缺口试样进行了疲劳实验，并与理论结果进行了对比，验证了所提模型的有效性．     

An interview with Sam C. Saunders

Sam C. Saunders, the son of Elizabeth Cundiff and Winston E. Saunders, was born in Richland, OR, on February 24, 1931. The family moved to La Grande, OR, in 1944, where Sam completed high school and two years at Eastern Oregon College. He then received the BSc degree in Mathematics from the University of Oregon, Eugene, OR, in 1952, and he attended the University of Washington, Seattle, WA, receiving a PhD degree under Z. W. Birnbaum. After graduating, he accepted employment at the Boeing Company in its Mathematical Services Unit and, in 1972, a position as a Full Professor at Washington State University, Pullman, WA, from which he retired in 1996.     

Reducing the computational cost of NMR crystallography of organic powders at natural isotopic abundance with the help of 13C-13C dipolar couplings

Structure determination of functional organic compounds remains a formidable challenge when the sample exists as a powder. Nuclear magnetic resonance crystallography approaches based on the comparison of experimental and Density Functional Theory (DFT)-computed ¹H chemical shifts have already demonstrated great potential for structure determination of organic powders, but limitations still persist. In this study, we discuss the possibility of using ¹³C-¹³C dipolar couplings quantified on powdered theophylline at natural isotopic abundance with the help of dynamic nuclear polarization, to realize a DFT-free, rapid screening of a pool of structures predicted by ab initio random structure search. We show that although ¹³C-¹³C dipolar couplings can identify structures possessing long range structural motifs and unit cell parameters close to those of the true structure, it must be complemented with other data to recover information about the presence and the chemical nature of the supramolecular interactions.