Effect of a sweeping air stream and gas–phase aspect ratio of an isothermal Stefan diffusion column on the experimental estimation of binary gas diffusivities

The Stefan column consists of liquid A evaporating into an inert/stagnant gas B with a sweeping B stream at the top. It was designed to estimate binary gas diffusivities, D_AB’s, but “end effects” such as gas mixing at the top and interfacial curvature have been either ignored or uncorrelated to the operational settings. This study’s hypothesis is that gas mixing at the top and the gas–phase aspect ratio affect D_AB estimation in the acetone (A)-ambient air (B) system at 50?°C. The sweeping stream Reynolds number (Re) and the gas–phase aspect ratio (AR?=?initial gas phase height to column internal diameter) were the variables tested. Isothermal evaporation-diffusion experiments were conducted in which the temporal interfacial descent was tracked. The settings were 492 ≤ Re ≤ 5378 and AR between 5 and 15. A 1D transport model allowed determination of the experimental diffusivity, D_AB,exp, by nonlinear regression. For Re < 600, the D_AB,exp errors relative to D_AB,CE (predicted by the Chapman–Enskog kinetic theory for low-density gases) were small and unrelated to AR, while for Re > 600 the errors increased considerably with Re and were inversely proportional to AR. This study is the first to relate the column’s operational settings to the D_AB estimation errors. The column should be operated at low sweeping gas Re and large AR for accurate D_AB,exp’s. The low Re region deserves further study, while the present transport model may have to be replaced by computational fluid dynamics simulations to account for the multidimensional gas flow patterns.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Identification of Host Cellular Protein Substrates of SARS-COV-2 Main Protease

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.     

基于流数据聚类算法的电力大数据异常检测

针对电力大数据流的异常检测问题,该文将流数据聚类算法与电力大数据相结合,针对现有流数据聚类算法不易存储全部数据、断电数据易丢失等问题,以及流数据聚类算法对于离线阶段聚类算法实时应答的要求,从数据的完整性、安全性以及流数据聚类算法的低时间复杂度的角度出发,对CluStream流数据聚类算法进行改进,提出流式K-means聚类算法。对在线阶段,使用Redis集群进行流数据的缓冲,并设计节点时间衰减策略,增大心跳消息中有效消息所占比例;对离线阶段聚类算法进行优化,使用最佳距离法确定初始聚类中心,减少迭代次数;最后,使用所提出的流式K-means聚类算法进行用户用电异常行为检测,实验结果表明,该算法能够很好的发现用户用电异常行为。     

Malic acid production from renewables: a review

Malic acid derived from fossil resources is currently applied in the food and beverage industries with a medium global production capacity. However, in the transition from a fossil-based to a bio-based economy, biotechnologically produced l -malic acid may become an important platform chemical with many new applications, especially in the field of biopolymers. In this review, currently used petrochemical production routes to dl -malic acid are outlined and insights into possible bio-based alternatives for microbial l -malic acid production are provided. Besides ecological reasons, the possibility to produce enantiopure l -malic acid by microbial fermentation is the biggest advantage over chemical synthesis. State-of-the-art and open challenges concerning production host engineering, substrate choice and downstream processing are addressed. With regard to production hosts, a literature overview is given covering the leading natural production strains of Aspergillus, Ustilago and Aureobasidium, as well as Escherichia coli as the most important engineered recombinant host. The utilization of renewable substrates as an alternative to glucose is emphasized in particular as a key aspect for a competitive bio-based production. Out of the alternative substrates discussed in this review, the industrial side-streams crude glycerol and molasses seem to be most promising for large-scale l -malic acid production. © 2019 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

盘县火腿自然发酵过程中理化和风味特征

分析盘县火腿自然发酵过程中理化特性和风味特征的变化，并结合香气活度值（odor activity value，OAV）和偏最小二乘回归（partial least squares regression，PLSR）分析确定盘县火腿主体香气成分。结果表明：盘县火腿理化特性在发酵过程中发生显著变化（P＜0.05），pH值和NaCl含量显著上升，而水分活度、水分含量和肌内脂肪含量显著下降，亮度值和黄度值呈持续下降趋势，而红度值先降低后升高；随着发酵的进行，盘县火腿中风味物质的种类从25 种增加至40 种，含量从（218.50±22.14） μg/kg上升至（1 044.49±51.47） μg/kg，其中醛类物质的种类和含量最丰富；OAV分析筛选出16 种主体香气物质，PLSR模型显示3-甲基丁醛、十二醛、十六醛、(Z)-9-十八烯醛和十八醛对盘县火腿肉香、清香和油脂香有显著贡献。     

汽车涂装废水处理技术的研究进展

汽车涂装中产生大量的工业废水，主要包括脱脂废水、磷化废水、电泳废水和喷漆废水等,其典型污染物为重金属离子、表面活性剂、油漆颗粒、磷酸盐等，是一类复杂及难处理的高浓度工业废水。依据废水中所含污染物的不同，对涂装各工序废水进行分质预处理可有效地去除磷酸盐、重金属离子、悬浮固体、油类物质等污染物，有利于减轻后续生物或高级处理单元的负荷，提高整个处理系统的效率。本文综述近年来汽车涂装废水处理方面的研究成果或实践，旨在总结预处理工艺及主体处理工艺的优点及存在的不足，希望为汽车涂装废水处理达标排放及循环回用提供一些借鉴。     

撞击流反应器撞击面稳定性研究进展

撞击流技术因其良好的混合特性近些年用于强化制备超细粉体反应中的混合过程。撞击面的稳定影响反应器内的混合效果，所以本文对撞击面稳定性的研究进行了综述。撞击流反应器不同结构形式包括平面撞击流、轴对称撞击流和微型撞击流等。文中简述了撞击流稳定性的实验研究手段，分析轴对称撞击流反应器的径向偏转振荡的起止条件和不同喷嘴间距下的轴向偏移振荡规律，并且分析平面撞击流反应器的撞击面偏转周期以及偏转振荡的起止条件。得出轴对称撞击流与平面撞击流撞击面驻点的振荡对混合都有促进作用，并且偏移振荡周期不定，轴对称撞击面偏移振幅与喷嘴间距和雷诺数相关。平面撞击流的偏转振荡周期与进口流速成反比，反应器结构参数是撞击流稳定性的影响因素之一。根据轴对称撞击流偏移振荡对混合的促进作用，本文提出一种新型的预设流量波形双组撞击流反应器。新型撞击流反应器的独特结构克服了物料反应通道单一缺点，通过预设波形控制其进口流量，增大其撞击面偏移振幅，消除撞击面无序振荡，使流动轨迹扩展，扩大混合区域，并设计实验装置与方法讨论动态流量撞击流反应器撞击面稳定性对混合效果的影响。最后，本文对轴对称撞击流反应器的混合性能研究前景进行展望。     

重庆主城区城市空间结构演变与优化——基于公共服务功能组织视角

城市空间结构与城市公共服务功能组织密切相关。重庆主城区作为典型的"多中心、组团式"城市,在城市公共服务功能的就近组织、公共服务需求的均衡化方面具有先天的优势。本文梳理重庆主城区空间结构的演进历程以及与公共服务需求变化的互动关系,辨识随着城市功能由生产向消费转型,空间面临的结构问题及其内在动因,借鉴马斯洛理论,提出顺应当前及未来公共服务需求层次的分异,城市空间结构应从"多中心、组团式"进一步向"分层多中心、组团式"优化,引导形成相对集中、功能综合的基层"小、微中心"体系,以有序组织公共服务功能,最大限度地减少非必要交通出行,降低居民出行的时耗,提升城市效率,并借鉴恩格尔系数构建衡量城市效率的评价框架,为破解山地城市空间结构问题,推动城市空间转型提供新的思考视角。