Influence of metal-support interactions on reaction pathways over Ni/CeZrOx–Al2O3 catalysts for ethanol steam reforming

This work investigates selective Ni locations over Ni/CeZrO_x–Al₂O₃ catalysts at different Ni loading contents and their influences on reaction pathways in ethanol steam reforming (ESR). Depending on the Ni loading contents, the added Ni selectively interacts with CeZrO_x–Al₂O₃, resulting in the stepwise locations of Ni over CeZrO_x–Al₂O₃. This behavior induces a remarkable difference in hydrogen production and coke formation in ESR. The selective interaction between Ni and CeZrO_x for 10-wt.% Ni generates more oxygen vacancies in the CeZrO_x lattice. The Ni sites near the oxygen vacancies enhance reforming via steam activation, resulting in the highest hydrogen production rate of 1863.0 μmol/g_cat·min. In contrast, for 15 and 20-wt.% Ni, excessive Ni is additionally deposited on Al₂O₃ after the saturation of Ni–CeZrO_x interactions. These Ni sites on Al₂O₃ accelerate coking from the ethylene produced on the acidic sites, resulting in a high coke amount of 19.1 mg_c/g_cat·h (20Ni/CZ-Al).     

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%。     

SLM printing of cermet powders: Inhomogeneity from atomic scale to microstructure

It is very challenging for 3D printing based on the selective laser melting (SLM) technology to obtain cermet bulk materials with high density and homogeneous microstructures. In this work, the SLM process of the cermet powders was studied by both simulations and experiments using the WC-Co cemented carbides as an example. The results indicated that the evolution of the ceramic and metallic phases in the cermet particle during the heating, melting and solidification processes were all significantly inhomogeneous from atomic scale to mesoscale microstructures. As a consequence, the microstructural defects were caused intrinsically in the printed bulk material. The formation and growth of the bonding necks between the particles were mainly completed at the later stage of laser heating and the early stage of solidification. Both simulations and experiments demonstrated that thin amorphous layers formed at the ceramics/metal interfaces. This work disclosed the mechanisms for the evolution from the atomic scale to microstructure during the SLM printing of cermet powders, and discovered the origin of the defects in the printed cermet bulk materials.     

Green synthesis of zinc oxide nanoparticles using Amygdalus scoparia Spach stem bark extract and their applications as an alternative antimicrobial,anticancer, and anti-diabetic agent

For the first time in this study, Zinc oxide nanoparticles were biosynthesized by the eco-friendly and cost-effective procedure using Amygdalus scoparia stem bark extract then used as antibacterial, antifungal, anticancer, and anti-diabetic agents. The characterization techniques confirmed the biosynthesis, crystalline nature, structure, size, elemental composition of ZnO NPs and bioactive compounds that exist in A. scoparia extract accounting for Zn²⁺ ion reduction, capping and stabilization of ZnO NPs. The ZnO NPs displayed remarkable inhibitory activity against E. coli, E. aerigenes, S. aureus, P. oryzae, F. thapsinum, and F. semitectum compared to antibiotic standards. The ZnO NPs showed significant inhibitory effects on cancer cell lines, while it had no toxic effect on Vero normal cell line. The ZnO NPs (30 mg/kg)-treated diabetic rats showed significantly higher levels of insulin and lower AST, ALT and blood glucose compared with the STZ induced diabetic group and other treated groups (P < 0.05). The ZnO NPs- and extract-treated rats showed significantly higher levels of IR, GluT2, and GCK expression and lower TNFα expression compared with the STZ induced diabetic rats. Our findings showed that ZnO NPs represented an outstanding performance for biological applications.     

Theoretical investigation of solvent effects on the selective hydrogenation of furfural over Pt(111)

It was well known that solvent effect plays a very important role in the catalytic reaction. There are many theoretical studies on the solvent effect in homogeneous catalysis while there are few theoretical studies on the solvent effect in the heterogeneous catalytic reaction and there has been no work to investigate the solvent effect on furfural transformation in heterogeneous catalysis. In the present work, both the density functional calculations and the microkinetic analysis were performed to study the selective hydrogenation of furfural over Pt(111) in the presence of methanol as well as toluene and compared with that in the gas condition. The present results indicated that the methanol can enhance the adsorption strength of furfural and other oxygen-containing reaction species due to its relatively strong polarity properties and this can be a main reason for solvent-induced high activity and selectivity. Another reason is that reaction paths study showed that the presence of methanol solvent makes the dehydrogenation of furfural less thermochemical due to the fact that furfural is more stabilized than that of dehydrogenation species, and methanol also has an inhibition effect on the dehydrogenation of furfural in the kinetic aspect, and further energetic span theory proves highest activity and selectivity for hydrogenation in methanol solvent of vapor, methanol and toluene. Moreover, microkinetic model simulation demonstrated that the activity and selectivity of hydrogenation in methanol is both higher than that in vapor and toluene. The much higher activity in methanol is due to the stabilized adsorbed reactants in the surface, which leads to a higher surface coverage of furfural. It might be proposed based on the present work that a solvent with relatively strong polarity may be favorable for the high selective hydrogenation of furfural.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

Single chamber Solid Oxide Fuel Cells selective electrodes: A real chance with brownmillerite-based nanocomposites

In this contribution brownmillerite-based nanocomposite cathode for Single-Chamber Solid Oxide Fuel Cells is developed. These cells can be very attractive especially for small and cheap devices because of the absence of seals. The efficiency of SC-SOFCs is strictly connected to the selectivity of anode and cathode, the bottleneck for this technology. The development of a cathode inert in fuel oxidation is particularly challenging. Our strategy is to start from a catalytically un-active support (CFA = Ca₂FeAl_0.95Mg_0.05O₅) and induce the formation of iron oxide based nanoparticles, expected to activate oxygen. Symmetric (CFA + FeO_x/CGO/CFA + FeO_x) and complete cells (CFA + FeO_x/CGO/Ni-CGO) are studied in air and methane/oxygen 2:1 mixture. The Area Specific Resistance of CFA + FeO_x is less than 1/3 that of CFA. The high selectivity allows to reach an efficiency of 25%; power still needs to be increased but we demonstrated the possibility to develop selective low cost electrodes. The effect of air, methane/oxygen exposure and the heat treatments were carefully investigated.     

Optimization of Selective Epitaxial Growth of Silicon in LPCVD

Selective epitaxial growth (SEG) of silicon has attracted considerable attention for its good electrical properties and advantages in building microstructures in high‐density devices. However, SEG problems, such as an unclear process window, selectivity loss, and nonuniformity have often made application difficult. In our study, we derived processing diagrams for SEG from thermodynamics on gas‐phase reactions so that we could predict the SEG process zone for low pressure chemical vapor deposition. In addition, with the help of both the concept of the effective supersaturation ratio and three kinds of E‐beam patterns, we evaluated and controlled selectivity loss and nonuniformity in SEG, which is affected by the loading effect. To optimize the SEG process, we propose two practical methods: One deals with cleaning the wafer, and the other involves inserting dummy active patterns into the wide insulator to prevent the silicon from nucleating.     

Context-Processing Deficits in Schizotypal Personality Disorder.

Research suggests that schizotypal personality disorder (SPD) is a part of the spectrum of schizophrenia-related illnesses. This article hypothesizes that a deficit in the representation and maintenance of context is a core cognitive disturbance in schizophrenia and that SPD individuals should demonstrate context-processing deficits. To test this hypothesis, the authors administered 3 versions of their AX-CPT task, designed to assess context processing, to 35 healthy controls and 26 individuals with DSM-IV SPD. They also administered working memory and selective attention tasks. SPD individuals displayed context representation deficits similar to those found in schizophrenia but did not show the same additional deficits in context maintenance. Context processing was strongly associated with working memory and selective attention performance in the SPD individuals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimized species growth in epoxy polymerization with real-coded NSGA-II

Satisfaction of twin objectives of maximization of M_n along with minimization of PDI do not necessarily guarantee the maximization of concentration of desired species in a semibatch epoxy polymerization process. As the final product consists of a number of polymer species, a need is felt to perform an advanced optimization study to come up with such process conditions for which the selective growth of a particular polymer species is maximized in minimum possible processing time and the population of other species should be at their lowest values. These above-mentioned conflicting objectives frame the platform for a multi-objective optimization problem, which is solved here using a real-coded non-dominated sorting genetic algorithm or NSGA II and Pareto optimal solutions are obtained. The decision variables are discrete addition rates of various ingredients, e.g. the amount of addition of bisphenol-A (a monomer), sodium hydroxide and epichlorohydrin at different time steps. All species balance equations, bounds on M_n, PDI and addition amounts are treated as constraints. Results are very promising in terms of optimized operations for selective enhancement of desired polymer species for the epoxy polymerization process. Total additions are kept very close to available experimental conditions to minimize probable extrapolation errors. It has been observed that preferential oligomer production is extremely difficult for epoxy polymerization. Lower chain polymers are the only choice for a good quality, stable polymer product.