高熵形状记忆合金的研究进展

高熵形状记忆合金是在等原子比NiTi合金的基础上,结合高熵合金的概念,逐渐发展起来的一种新型高温形状记忆合金。近年来,已开发出了综合性能优异的(TiZrHf)50(NiCoCu)50系和(TiZrHf)50(NiCuPd)50系高熵形状记忆合金,引起了广泛的关注和研究兴趣。本文从物相组成、微观组织、马氏体相变行为、形状记忆效应和超弹性等角度出发,综述了高熵形状记忆合金的研究进展,并对高熵形状记忆合金未来的研究重点进行了展望。     

The Function of Sialidase Revealed by Sialidase Activity Imaging Probe

Sialidase cleaves sialic acid residues from glycans such as glycoproteins and glycolipids. In the brain, desorption of the sialic acid by sialidase is essential for synaptic plasticity, learning and memory and synaptic transmission. BTP3-Neu5Ac has been developed for sensitive imaging of sialidase enzyme activity in mammalian tissues. Sialidase activity in the rat hippocampus detected with BTP3-Neu5Ac increases rapidly by neuronal depolarization. It is presumed that an increased sialidase activity in conjunction with neural excitation is involved in the formation of the neural circuit for memory. Since sialidase inhibits the exocytosis of the excitatory neurotransmitter glutamate, the increased sialidase activity by neural excitation might play a role in the negative feedback mechanism against the glutamate release. Mammalian tissues other than the brain have also been stained with BTP3-Neu5Ac. On the basis of information on the sialidase activity imaging in the pancreas, it was found that sialidase inhibitor can be used as an anti-diabetic drug that can avoid hypoglycemia, a serious side effect of insulin secretagogues. In this review, we discuss the role of sialidase in the brain as well as in the pancreas and skin, as revealed by using a sialidase activity imaging probe. We also present the detection of influenza virus with BTP3-Neu5Ac and modification of BTP3-Neu5Ac.     

SBS Thermoplastic Elastomer Based on Dynamic Metal-Ligand Bond: Structure,Mechanical Properties,and Shape Memory Behavior

A Cooper(II) (Cu²⁺)-nitrogen coordination-crosslinked network is designed in poly(styrene-co-butadiene-co-styrene) (SBS) to change commercial elastomers into advanced soft materials. Herein, ligand groups into SBS molecular chains by the 3,6-di(2-pyridyl)-1,2,4,5-tetrazine (DPT) click reaction are first introduced. The results from fourier transform infrared (FT-IR), 1H-nuclear magnetic resonance, and X-ray photoelectron spectroscopy (XPS) are verified the successful modification of SBS. The DPT-grafted SBS could then coordinate with copper sulfate (CuSO₄) to form a Cu²⁺-nitrogen bond, which is further characterized using FT-IR, XPS, atomic force microscope, scanning electron microscope, and geometric structure calculations. After modifying SBS to form an SBS-DPT/CuSO₄ composite (SBS-DPT2-Cu10), the tensile stress is improved from 11.43 to 23.25 MPa, while the elongation at break is remained almost unchanged, and the corresponding toughness is increased from 33.21 to 63.26 MJ m^–3. Moreover, the dynamic nature of the Cu²⁺-nitrogen coordination bonds enables the SBS-DPT/CuSO₄ composite to exhibit sustained thermoplastic performance and excellent shape memory behavior under an external thermal stimulus.     

Gyrotactic microorganisms bioconvection in combined convective magnetohydrodynamic Casson nanofluid flow over a vertically surfaced saturated porous media with variable viscosity

The current article focuses on mass and thermal transfer analysis of a two-dimensional immovable combined convective nanofluid flow including motile microorganisms with temperature-dependent viscosity on top of a vertical plate through a porous medium, and a model has been developed to visualize the velocity slip impacts on a nonlinear partial symbiotic flow. The governed equations include all of the above physical conditions, and suitable nondimensional transfigurations are utilized to transfer the governed conservative equations to a nonlinear system of differential equations and obtain numerical solutions by using the Shooting method. Numerical studies have been focusing on the effects of intricate dimensionless parameters, namely, the Casson fluid parameter, Brownian motion parameter, thermophoresis parameter, Peclet number, bioconvection parameter, and Rayleigh number, which have all been studied on various profiles such as momentum, thermal, concentration, and density of microorganisms. The concentration boundary layer thickness and density of microorganisms increased as the Casson fluid parameter, Brownian and thermophoresis parameters increased, whereas the bioconvection parameter, Peclet number, and Rayleigh number increased. The thermal boundary layer thickness, concentration boundary layer thickness, and density of microorganisms all decreased. The velocity distribution decreases as the Peclet number, bioconvection, and thermophoresis parameters rise but rises as the Rayleigh number, Brownian motion parameter, and Casson fluid parameter rise. These are graphed via plots along with divergent fluid parameters.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

建筑结构控制爆破拆除的力学分析与应用

应用运动学、动力学理论建立建(构)筑物控爆坍落过程的力学模型,进而研究在非定常约束条件下坍落结构的力学特征。首次提出了采用延时起爆技术时,非自由质点系及其广义坐标应是建立在每一段位上的瞬间虚位移。在此基础上,分析求解运动过程中时控单元的质点自由度,为精确选定爆破部位及时序提供了设计理论和计算依据。同时,结合振动理论,将控爆时差、结构载荷分布调制为振动系统,形成坍落结构梁板单元的强迫振动,充分实现在运动中进一步解体、破碎其自身结构,并形成具有明显缓冲效果的下落过程。应用实践结果证明力学分析是正确的,为工程结构爆破拆除计算机辅助设计及动态模拟技术的有效应用奠定了基础。     

Squeezed MHD tangent hyperbolic fluid flow across a sensor surface

In the present numerical study, the combined effect of temperature-dependent thermal conductivity, linear thermal radiation, and magnetic effect on shear-thinning tangent hyperbolic fluid past a sensor surface has been studied. After converting the modelled partial differential equations into ordinary differential equations by using similarity transformation, the system of equations is tackled with the aid of the shooting method. The influence of important parameters on the fluid motion and energy distribution is displayed graphically and analyzed in detail. The presented simulations depict that a significant rise in fluid velocity is noticed for an enhancement in the magnetic parameter while an opposite trend is observed for the temperature distribution. Moreover, the skin friction coefficient decreases as the squeezed flow index is increased.     

A novel pre-dilution,swirling jet diffuser to enhance effluent mixing: Hydrodynamics and dilution performance

Diffusers are widely-used to quickly dilute effluents in receiving water bodies. This study proposed a novel diffuser that pre-mixes effluent with ambient water before discharging and that uses the swirling jet to further enhance near-field dilution. The nozzle of the diffuser was examined in two ambient flow conditions: co-flow and counter-flow that are commonly-met in the environment such as oceans due to tidal effect. Physical experiments were first conducted in co-flow on its dilution performance and hydrodynamics, using heated water as the effluent. A 3-D CFD model was developed and calibrated the co-flow scenarios, and then used to investigate the diffuser in counter-flow. The results showed that the nozzle can effectively reduce the maximum temperature rise of the effluent by about 50 % before discharging. The swirling jet from the outlet has a larger shear area, half-width and entrainment rate, enabling the effluent to be rapidly diluted to a minimum of around 10 times at x/D = 6 in co-flow, whereas the dilution for conventional nozzles is about 1 because of the potential core. The flow amplification ratio (α) decreases gradually with increasing velocity ratio in co-flow but increases with increasing velocity ratio in counter-flow. The counter-flow reduces the water drawn into the device; however, the pre-dilution effect at the outlet remains stable. The near-field dilution in counter-flow was significantly enhanced than that in co-flow. Environmental regulations at outfalls and mixing zones can be more easily met using this novel diffuser.     

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%。     

以新发展理念引领高校专业基础课教学改革

以“创新、协调、绿色、开放、共享”为内核的新发展理念，是对马克思主义发展理念的继承和发扬，极具时代精神，富含问题意识，为高校思想政治教育发展、教育教学改革实践提供了强大的理论支撑。本文以“通信原理”为例，阐述了新发展理念在课程改革中的思路和方法，实现了思想政治教育与专业基础课程有机融合，为深化高校教学改革、创新人才培养模式提供了思路。