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%。     

From modification to mechanism: Supercritical hydrothermal synthesis of nano-zirconia

Nano-zirconia has been widely applied due to its excellent physical and chemical properties (e.g., high strength, corrosion resistance, oxygen ion conductivity). Existing preparation methods of nano-zirconia tend to require long reaction time, and the sizes of final particles are large with uneven distributions. Sub-/supercritical hydrothermal synthesis of nanoparticles is favored by researchers owing to controllable reaction process, uniform particle size distribution, good reproducibility, short reaction time, high conversion rate and harmlessness to environment. In this paper, the characteristics and mechanisms of dissolution, crystallization and growth of nano-zirconia during sub-/supercritical hydrothermal synthesis are systematically reviewed. The influences of process and material parameters on the size and purity of particles are analyzed. Then, the reaction mechanism and product phase transition mechanism during hydrothermal synthesis of zirconia are summarized to provide a theoretical reference for the oriented preparation. Finally, the improvement and commercialization of sub-/supercritical hydrothermal synthesis technology are evaluated, and the future research topics are proposed.     

Hydrogen production by supercritical water gasification of lignin over CuO–ZnO catalyst synthesized with different methods

In this study, lignin was gasified in supercritical water with catalysis of CuO–ZnO synthesized by deposition precipitation, co-precipitation and sol-gel methods. Sol-gel synthesized CuO–ZnO showed the highest catalytic performance, and the gasification efficiency was increased by 37.92% with it. The XRD, SEM-EDS and N₂ adsorption/desorption analysis showed that the priority of the sol-gel catalyst was the smallest crystallite size, largest specific surface area and high dispersion. For sol-gel synthesized CuO–ZnO, the increase of CuO/ZnO ratio improved the gasification efficiency but reduced H₂ selectivity. And the catalytic activity was reduced with the calcination temperature above 600 °C due to enlarged crystallites and reduced pores. During sol-gel preparation, both the addition of ethanol and PEG in the solvent reduced the agglomeration and improved the catalytic activity. With CuO–ZnO prepared with 1 g PEG + water as the solvent, the highest H₂ yield of 6.86 mol/kg was obtained, which was over 1.5 times of that without catalyst.     

Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process

Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.     

面部运动单元检测研究综述

面部运动单元检测旨在让计算机从给定的人脸图像或视频中自动检测需要关注的运动单元目标。经过二十多年的研究，尤其是近年来越来越多的面部运动单元数据库的建立和深度学习的兴起，面部运动单元检测技术发展迅速。首先，阐述了面部运动单元的基本概念，介绍了已有的常用面部运动单元检测数据库，概括了包括预处理、特征提取、分类器学习等步骤在内的传统检测方法；然后针对区域学习、面部运动单元关联学习、弱监督学习等几个关键研究方向进行了系统性的回顾梳理与分析；最后讨论了目前面部运动单元检测研究存在的不足以及未来潜在的发展方向。     

基于双离合变速器电控单元的Volcano CAN开发

Volcano 是集汽车电子网络设计、实现和测试于一体的完整工具链。它包括整车网络规划及优化设计工具VNA,网络节点(TCU等)实现工具VTP以及网络测试工具Tellus。本文着重介绍了基于TCU的VTP。     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Catalytic supercritical water oxidation of tri-n-butyl phosphate: Process optimization by response surface methodology and cytotoxicity assessment

Catalytic supercritical water oxidation (SCWO) of an organophosphate flame retardant, namely tri-n-butyl phosphate (TNBP) was studied. Firstly, copper oxide nanoparticles (NPs) were synthesized in SCW and their properties were characterized by various analyses. Afterwards, their catalytic performance was investigated under different conditions including reaction temperature (400–500 °C), TNBP volume percentage in the feed (1–4%), oxidant ratio (0–2) and reaction time (50–150 min) based on response surface methodology (RSM). The synthesized CuO NPs had an average particle size of 30 nm with a narrow distribution. According to RSM analysis, the reaction temperature and time are the most significant factors; whereas, the impact of the other factors, especially TNBP volume percentage in the feed, was found to be negligible. Overall, excellent performance was achieved under optimal conditions found by the RSM, which was reaction temperature of 500 °C, TNBP volume percentage of 4%, oxidant ratio of 1.5, and reaction time of 90 min. The TOC removal efficiency as an indicator of TNBP degradation was about 99%. Finally, in vitro cell viability assays for the cytotoxicity evaluation of fresh and SCW-treated solution were applied. The results of MTT showed that SCWO converts TNBP into by-product that did not induce any cytotoxicity.     

Benchmark value determination of energy efficiency indexes for coal-fired power units based on data mining methods

The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values.     

Towards Diastereomeric Pure Salts with Antisolvent Methods

Chiral molecules, especially enantiomers and diastereomers of purity > 99 %, present a significant market share within the chemical, pharmaceutical, and flavor industries. Antisolvent precipitations, both batch and semicontinuous operations to serve the current trends in flow chemistry were demonstrated to be environmentally benign and efficient tools in achieving high optical purities. Although salts are known to be insoluble in supercritical CO₂, instabilities of the nascent salts were detected and applied for increasing efficiency. Diastereomeric excess values of the crystalline products exceeded 99 % in maximum of three consecutive steps both by repeated resolution with half molar equivalent of the amine to the acid and by direct recrystallization of the salts.