Experimental study and model predictions on helium release in an enclosure with single or multiple vents

This paper presents experiments performed at Canadian Nuclear Laboratories (CNL) to examine the dispersion behaviour of helium in a polycarbonate enclosure that was representative of a residential parking garage. The purpose was to gain a better understanding of the effect of buoyancy- or wind-driven natural ventilation on hydrogen dispersion behaviour. Although hydrogen dispersion studies have been reported extensively in the literature, gaps still exist in predictive methods for hazard analysis. Helium, a simulant for hydrogen, was injected near the centre of the floor with a flow rate ranging from 5 to 75 standard litres per minute through an upward-facing nozzle, resulting in an injection Richardson number ranging between 10^?1 and 10². The location of the nozzle varied from the bottom of the enclosure to near the ceiling to examine the impact of the nozzle elevation on the development of a stratified layer in the upper region of the enclosure. When the injection nozzle was placed at a sufficiently low elevation, the vertical helium profile always consisted of a homogenous layer at the top overlaying a stratified layer at the bottom. To simulate outdoor environmental conditions, a fan was placed in front of each vent to examine the effect of opposing or assisting wind on the dispersion. The helium transients in the uniform layer predicted with analytical models were in good agreement with the measured transients for most tests. Model improvements are required for adequately predicting transients with primarily stratified profiles or strong opposing wind.     

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%。     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

学生参与电气人才创新能力培养的探索

基于“以学生为本”的OBE教育理念，本文对电气人才创新能力培养进行了探索。整个过程将专业课程体系契合学业规划以明确学生学习目标；学生参与理论、实践教学和平台搭建，在夯实其理论知识的同时丰富教学资源；在创新考核中采用“螺旋递进式”的师生互动模式，全程培养学生自主的创新能力。多年实践探索表明学生在课程实践、学科竞赛、论文发表和申报专利等方面的创新能力得到显著提升。     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Influence of accelerated curing on the compressive strength of polymer-modified concrete

In recent building practice, rapid construction is one of the principal requisites. Furthermore, in designing concrete structures, compressive strength is the most significant of all parameters. While 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strength is paramount. An effort has been made in this study to develop mathematical models for predicting compressive strength of concrete incorporating ethylene vinyl acetate (EVA) at the later phases. Kolmogorov-Smirnov (KS) goodness-of-fit test was used to examine distribution of the data. The compressive strength of EVA-modified concrete was studied by incorporating various concentrations of EVA as an admixture and by testing at ages of 28, 56, 90, 120, 210, and 365 d. An accelerated compressive strength at 3.5 hours was considered as a reference strength on the basis of which all the specified strengths were predicted by means of linear regression fit. Based on the results of KS goodness-of-fit test, it was concluded that KS test statistics value (D) in each case was lower than the critical value 0.521 for a significance level of 0.05, which demonstrated that the data was normally distributed. Based on the results of compressive strength test, it was concluded that the strength of EVA-modified specimens increased at all ages and the optimum dosage of EVA was achieved at 16% concentration. Furthermore, it was concluded that predicted compressive strength values lies within a 6% difference from the actual strength values for all the mixes, which indicates the practicability of the regression equations. This research work may help in understanding the role of EVA as a viable material in polymer-based cement composites.     

基于改进SOA-VMD的磁声发射信号去噪算法

磁声发射（MAE）是铁磁性材料磁化过程中产生的声发射信号，在构件应力检测和微观损伤检测中有着广泛的应用。针对MAE信号非稳态、复杂性、衰减性等特点，提出海鸥算法结合变分模态分解（SOA-VMD）的去噪方法，为克服海鸥算法求解过程中易陷入局部最优解问题，利用柯西变异算子产生随机迭代过程，使改进算法即柯西变异海欧算法（CVSOA）跳出早熟收敛。采用以幅值谱熵为适应度函数，优化VMD算法中分解模态个数K和二次惩戒因子α两个参数，将含噪声的MAE信号进行VMD分解重构。经仿真信号和实际检测信号分析表明，改进后的CVSOA-VMD算法全局寻优能力和去噪性能优于传统的SOA-VMD算法，降噪后的MAE信号特征值对于不同应力下均方根、偏斜度特征值的重复性更好，可靠性更高。     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.