Structural Basis for the Function of the C-Terminal Proton Release Pathway in the Calcium Pump

The calcium pump (sarco/endoplasmic reticulum Ca²⁺-ATPase, SERCA) plays a major role in calcium homeostasis in muscle cells by clearing cytosolic Ca²⁺ during muscle relaxation. Active Ca²⁺ transport by SERCA involves the structural transition from a low-Ca²⁺ affinity E2 state toward a high-Ca²⁺ affinity E1 state of the pump. This structural transition is accompanied by the countertransport of protons to stabilize the negative charge and maintain the structural integrity of the transport sites and partially compensate for the positive charges of the two Ca²⁺ ions passing through the membrane. X-ray crystallography studies have suggested that a hydrated pore located at the C-terminal domain of SERCA serves as a conduit for proton countertransport, but the existence and function of this pathway have not yet been fully characterized. We used atomistic simulations to demonstrate that in the protonated E2 state and the absence of initially bound water molecules, the C-terminal pore becomes hydrated in the nanosecond timescale. Hydration of the C-terminal pore is accompanied by the formation of water wires that connect the transport sites with the cytosol. Water wires are known as ubiquitous proton-transport devices in biological systems, thus supporting the notion that the C-terminal domain serves as a conduit for proton release. Additional simulations showed that the release of a single proton from the transport sites induces bending of transmembrane helix M5 and the interaction between residues Arg762 and Ser915. These structural changes create a physical barrier against full hydration of the pore and prevent the formation of hydrogen-bonded water wires once proton transport has occurred through this pore. Together, these findings support the notion that the C-terminal proton release pathway is a functional element of SERCA and also provide a mechanistic model for its operation in the catalytic cycle of the pump.     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Evaluation of Scale and Corrosion Inhibition of Modified Polyaspartic Acid

Amino acid modified polyaspartic acids were evaluated as calcium-scale inhibitors. Feasibility of scale inhibition experiments was analyzed by molecular dynamics simulation and Gaussian optimization, and the scale inhibition mechanism was theoretically analyzed. Scale inhibition performance was studied by scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, static scale inhibition experiments, and electrochemical performance testing, which provided an experimental basis for the molecular dynamics simulation. The experimental results showed that Arg-SA-PASP has better scale inhibition and corrosion inhibition performance than His-SA-PASP. The scale inhibition effect increased with increasing concentration. Electrochemical tests indicated that Arg-SA-PASP is an excellent scale and corrosion inhibitor.     

Evaluation of hydrodynamic behavior of the perforated gas distributor of industrial gas phase polymerization reactor using CFD-PBM coupled model

A 2D computational fluid dynamics (Eulerian–Eulerian) multiphase flow model coupled with a population balance model (CFD-PBM) was implemented to investigate the fluidization structure in terms of entrance region in an industrial-scale gas phase fluidized bed reactor. The simulation results were compared with the industrial data, and good agreement was observed. Two cases including perforated distributor and complete sparger were applied to examine the flow structure through the bed. The parametric sensitivity analysis of time step, number of node, drag coefficient, and specularity coefficient was carried out. It was found that the results were more sensitive to the drag model. The results showed that the entrance configuration has significant effect on the flow structure. While the dead zones are created in both corners of the distributors, the perforated distributor generates more startup bubbles, heterogeneous flow field, and better gas–solid interaction above the entrance region due to jet formation.     

基于梯度提升决策树的车轮轮缘厚度磨耗预测

轮对在列车走行过程中起着导向、承受以及传递载荷的作用，其踏面及轮缘磨耗对地铁列车运行安全性和钢轨的寿命都将产生重要影响。根据地铁列车车轮磨耗机理，分析车轮尺寸数据特点，针对轮缘厚度这一型面参数，基于梯度提升决策树算法构建轮缘厚度磨耗预测模型。在该模型的基础上，任意选取某轮对数据进行验证分析，结果表明：基于梯度提升决策树的轮对磨耗预测模型具有较好的预测精度，可预测出1~6个月的轮缘厚度变化趋势范围，预测时间范围较长，可为地铁维保部门对轮对的维修方式由状态修转为预防修提供指导性建议。     

基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

ACE2, the Receptor that Enables Infection by SARS-CoV-2: Biochemistry,Structure, Allostery and Evaluation of the Potential Development of ACE2 Modulators

Angiotensin converting enzyme 2 (ACE2) is the human receptor that interacts with the spike protein of coronaviruses, including the one that produced the 2020 coronavirus pandemic (COVID-19). Thus, ACE2 is a potential target for drugs that disrupt the interaction of human cells with SARS-CoV-2 to abolish infection. There is also interest in drugs that inhibit or activate ACE2, that is, for cardiovascular disorders or colitis. Compounds binding at alternative sites could allosterically affect the interaction with the spike protein. Herein, we review biochemical, chemical biology, and structural information on ACE2, including the recent cryoEM structures of full-length ACE2. We conclude that ACE2 is very dynamic and that allosteric drugs could be developed to target ACE2. At the time of the 2020 pandemic, we suggest that available ACE2 inhibitors or activators in advanced development should be tested for their ability to allosterically displace the interaction between ACE2 and the spike protein.     

基于GFU和分层LSTM的组群行为识别研究方法

提出一种以"关键人物"为核心，使用门控融合单元（GFU，Gated Fusion Unit）进行特征融合的组群行为识别框架，旨在解决两个问题：①组群行为信息冗余，重点关注关键人物行为特征，忽略无关人员对组群行为的影响；②组群内部交互行为复杂，使用GFU有效融合以关键人物为核心的交互特征，再通过LSTM时序建模成为表征能力更强的组群特征.最终，通过softmax分类器进行组群行为类别分类.该算法在排球数据集上取得了86.7%的平均识别率.     

基于词法特征的恶意域名快速检测算法

针对互联网中恶意域名攻击事件频发，现有域名检测方法实时性不强的问题，提出一种基于词法特征的恶意域名快速检测算法。该算法根据恶意域名的特点，首先将所有待测域名按照长度进行正则化处理后赋予权值；然后利用聚类算法将待测域名划分成多个小组，并利用改进的堆排序算法按照组内权值总和计算各域名小组优先级，根据优先级降序依次计算各域名小组中每一域名与黑名单上域名之间的编辑距离；最后依据编辑距离值快速判定恶意域名。算法运行结果表明，基于词法特征的恶意域名快速检测算法与单一使用域名语义和单一使用域名词法的恶意域名检测算法相比，准确率分别提高1.7%与2.5%，检测速率分别提高13.9%与6.8%，具有更高的准确率和实时性。     

Long-run urban dynamics: understanding local housing market change in London

Abstract

Recently, a literature has emerged using empirical techniques to study the evolution of international cities over many centuries; however, few studies examine long-run change within cities. Conventional models and concepts are not always appropriate and data issues make long-run neighbourhood analysis particularly problematic. This paper addresses some of these points. First, it discusses why the analysis of long-run urban change is important for modern urban policy and considers the most important concepts. Second, it constructs a novel data set at the micro level, which allows consistent comparisons of London neighbourhoods in 1881 and 2001. Third, the paper models some of the key factors that affected long-run change, including the role of housing. There is evidence that the relative social positions of local urban areas persist over time but, nevertheless, at fine spatial scales, local areas still exhibit change, arising from aggregate population dynamics, from advances in technology, and also from the effects of shocks, such as wars. In general, where small areas are considered, long-run changes are likely to be greater, because individuals are more mobile over short than long distances. Finally, the paper considers the implications for policy.