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%。     

A stiffness parameter and truncation error criterion for adaptive path following in structural mechanics

We explore a truncation error criterion to steer adaptive step length refinement and coarsening in incremental-iterative path following procedures, applied to problems in large-deformation structural mechanics. Elaborating on ideas proposed by Bergan and collaborators in the 1970s, we first describe an easily computable scalar stiffness parameter whose sign and rate of change provide reliable information on the local behavior and complexity of the equilibrium path. We then derive a simple scaling law that adaptively adjusts the length of the next step based on the rate of change of the stiffness parameter at previous points on the path. We show that this scaling is equivalent to keeping a local truncation error constant in each step. We demonstrate with numerical examples that our adaptive method follows a path with a significantly reduced number of points compared to an analysis with uniform step length of the same fidelity level. A comparison with Abaqus illustrates that the truncation error criterion effectively concentrates points around the smallest-scale features of the path, which is generally not possible with automatic incrementation solely based on local convergence properties.     

Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience

Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration.     

粉土界面恒刚度循环剪切试验研究

竖向循环荷载作用下桩土界面的作用机理是研究桩土摩擦疲劳的关键。针对循环荷载作用下桩-粉土界面的剪切性能,使用改进的剪切试验装置在恒刚度条件下进行循环剪切试验,研究循环次数、累积位移和法向刚度对其摩擦疲劳性能、循环后单调剪切性能的影响。试验结果表明,粉土在循环剪切过程中,法向应力和剪应力在初始10个循环内随循环数增加快速衰减,随着循环进行,逐渐趋于稳定;单次循环内在剪切位移方向变化时,土体呈现表现出剪缩-剪胀-剪缩交替现象,总体变形呈现剪缩的趋势;循环荷载作用下,粉土界面的法向应力和剪应力随法向刚度增大衰减速率增大,达到稳定的累积循环位移越小;粉土循环后的单调剪切、法向应力恢复的单调剪切的剪应力比小于首次单调剪切试验值,且法向应力恢复的循环后剪切试验的剪胀程度较小,表明循环剪切过程中界面处粉土颗粒棱角破碎,颗粒变得光滑。在对试验数据分析的基础上,提出了与累积位移、法向刚度和初始应力相关的无量纲累积位移,建立了法向应力和界面摩擦角随累积位移的衰减方程。     

Deformation-Strength Relationships in Short-Term Tension of Heat-Resistant Materials

The analysis of 124 curves obtained in short-term tensile tests demonstrate that they can be described by varying strain hardening and softening characteristics. Different stress–strain curves can be produced at invariable yield strength and ultimate strength and interrelated proportional variations of the above characteristics. To determine some specific stress–strain curve, it is necessary to take account of yield strength and ultimate strength as well as strain corresponding to the latter. The relations between yield strength, ultimate strength and hardening and their practically complete absence between these parameters and softening were statistically established.     

底部两层框架-抗震墙砖房抗震能力的分析方法与设计控制

提出了底部两层框架 -抗震墙砖房框剪层和砖混层的极限受剪承载力、侧移刚度、极限剪力系数计算公式 ,并基于设置不同数量抗震墙的底部两层框架 -抗震墙砖房的实例计算和弹塑性时程分析 ,给出了结构砖混过渡层与相邻框剪层的极限剪力系数比和侧移刚度比的合理取值及薄弱楼层位置判别和破坏状态评定的方法和原则。     

A continuum-based modeling of MEMS devices for estimating their resonant frequencies

A continuum-based modeling of coupled electrostatics-structure interactions is presented for the frequency computations of MEMS devices. The present general formulation of electrostatics accounting for free space is validated first by specializing it to one-dimensional uniform motion of conducting surfaces and comparing the resulting electrostatics to conventional lumped models. The general coupled electrostatics-structure interactions are then applied for the prediction of resonant frequencies of MEMS devices due to bias-voltage changes and temperature variations. Comparisons of predicted resonant frequencies obtained by the present coupled electrostatics-structure interaction models with experimental results available in the literature demonstrate that the proposed continuum-based interaction modeling yields high-confidence predictions of resonant frequencies of MEMS devices.     

A direct stiffness analysis of a composite beam with partial interaction

The use of the conventional semi-analytical stiffness method in finite element analysis, in which interpolation polynomials are used to develop the stiffness relationships, leads to problems of curvature locking when beam-type elements are developed for composite members with partial interaction between the materials of which it is comprised. The curvature locking phenomenon that occurs for composite steel–concrete members is quite well reported, and the general approach to minimizing the undesirable ramifications of curvature locking has been to use higher-order polynomials with increasing numbers of internal nodes. This paper presents an alternate formulation based on a direct stiffness approach rather than starting from pre-defined interpolation polynomials, and which does not possess the undesirable locking characteristics. The formulation is based on a more general approach for a bi-material composite flexural member, whose constituent materials are joined by elastic shear connection so as to provide partial interaction. The stiffness relationships are derived, and these are applied to a simply supported and a continuous steel–concrete composite beam to demonstrate the efficacy of the method, and in particular its ability to model accurately both very flexible and very stiff shear connection that causes difficulties when implemented in competitive semi-analytical algorithms. Copyright © 2004 John Wiley & Sons, Ltd.     

Treatment of depressive symptoms during short-term rehabilitation: An attempted replication of the DOUR project.

Objective: To replicate and extend P. A. Lichtenberg and colleagues' (1996) cross-disciplinary intervention to improve physical and mental health among older adults. Participants: 14 depressed older adults (6 treatment, 8 control). Setting: The short-term rehabilitation unit of an urban nursing home. Intervention: Occupational therapists were trained to treat depression using pleasant events and cognitive-behavioral therapies. Outcome Measures: Geriatric Depression Scale, the Short Form-12, and the Multi-Level Assessment Instrument: Activities of Daily Living. Results: No significant group differences were found in physical or mental health. However, more control group members (75%) than treatment group members (33%) were depressed at study completion. Conclusions: The treatment of depressive symptoms can be integrated with a nonmental health treatment modality. (PsycINFO Database Record (c) 2011 APA, all rights reserved)