The Contribution of Small Vessel Disease to Neurodegeneration: Focus on Alzheimer’s Disease,Parkinson’s Disease and Multiple Sclerosis

Brain small vessel disease (SVD) refers to a variety of structural and functional changes affecting small arteries and micro vessels, and manifesting as white matter changes, microbleeds and lacunar infarcts. Growing evidence indicates that SVD might play a significant role in the neurobiology of central nervous system (CNS) neurodegenerative disorders, namely Alzheimer’s disease (AD) and Parkinson’s disease (PD), and neuroinflammatory diseases, such as multiple sclerosis (MS). These disorders share different pathophysiological pathways and molecular mechanisms (i.e., protein misfolding, derangement of cellular clearance systems, mitochondrial impairment and immune system activation) having neurodegeneration as biological outcome. In these diseases, the actual contribution of SVD to the clinical picture, and its impact on response to pharmacological treatments, is not known yet. Due to the high frequency of SVD in adult-aged patients, it is important to address this issue. In this review, we report preclinical and clinical data on the impact of SVD in AD, PD and MS, with the main aim of clarifying the predictability of SVD on clinical manifestations and treatment response.     

基于改进DaNN的综合能源系统多能负荷预测

随着能源革命的推进及双碳目标的提出,综合能源系统越发受到广大研究者的重视,对综合能源系统进行高效的规划和控制离不开精准的多能负荷预测。基于上述需求,引入迁移学习理论,提出一种改进领域自适应神经网络（DaNN）负荷预测模型对综合能源系统中的冷、热、电负荷进行统一建模与预测。首先,通过历史数据分别构筑冷、热、电负荷特征图,随后输入改进DaNN的参数共享卷积层和全连接层;其次,基于冷、热、电负荷联合预测的特点改进传统神经网络的损失函数,加入最大均值差异指标,并优化训练模型;最后,通过3个各自独立的全连接层分别输出冷、热、电负荷的预测值。通过采用实际算例验证并与基准模型对比可知,所提改进DaNN模型能够有效提高综合能源多能负荷预测精度。     

Microstructure and properties of WC-8Co cemented carbides prepared by multiple spark plasma sintering

In this study, WC-8Co cemented carbides were prepared by spark plasma sintering. When the samples sintered at 1300℃ were cooled to room temperature, the samples were sintered multiple times at 1250℃. The changes in microstructure and mechanical properties of WC-8Co cemented carbides prepared by multiple spark plasma sintering were studied. The hardness of cemented carbides increased in the first two sintering, reaching 16.5 GPa. However, the hardness decreased seriously in the last two sintering. The attenuation rates of hardness were 6.2% and 2.5% due to the abnormal coarse grains. Furthermore, the crack path along the grain boundary was almost straight, causing a decrease in the indentation fracture toughness of cemented carbides. Additionally, the grains of cemented carbides were abnormally coarsened, and the morphologies of grains became unstable due to multiple sintering.     

高压粉末制样-X射线荧光光谱法测定海洋沉积物中28种组分

常规粉末压片制样是一种简单、高效的绿色环保制样技术,但是应用于某些沉积物样品制备存在样片表面粗糙和粉末容易脱落的问题。实验采用高于常规的压力进行样品制备,建立了X射线荧光光谱法(XRF)分析海洋沉积物样品中包括硫、氧化钠、氧化镁、三氧化二铝、二氧化硅、五氧化二磷、氧化钾、氧化钙、二氧化钛、氧化锰、三氧化二铁、钴、镍、铜、锌、钒、铬、镓、铌、锆、钇、锶、铷、铅、钡、镧、钕和铪在内的28种主、微量组分的方法。探讨了压力为300 kN和1 600 kN时的制样效果,并尝试引入BP神经网络模型利用其非线性拟合能力校正主量组分的基体效应。结果表明,采用1 600 kN压力制备的样片,表面致密、光滑、不龟裂和不掉粉,制样重复性和测试精密度也有较大提高。以55个有证标准物质中17种组分的数据集为训练样本,建立了海洋沉积物样品中主、微量组分的遗传算法-BP神经网络预测模型。按照实验方法对各组分含量相对较低的实际样品连续测试12次,计算得方法的检出限在 0.63～634 μg/g之间;精密度试验结果表明,各组分测定值的相对标准偏差(RSD, n=7)为0.16%～25.1%。方法用于海洋沉积物实际样品分析,其分析结果与国标法的测定结果吻合,能够满足海洋沉积物样品中多种组分准确分析的要求。     

影响中小企业球铁质量稳定的因素

分析了影响中小企业球铁生产稳定性的关键因素,指出在一定的原材料条件下,目前中小型企业生产球铁存在的问题是温度偏低,孕育方法不当。     

类金刚石膜的制备及其影响因素

概述了近年来制类金刚石膜的新技术如双射频辉光放电（RF－RF）法，射频－直流辉光放电（RF－DC）法和微波－射频（MW－RF）法等，并且对影响类金刚石膜制备及性能的因素如基体材料，制备类金刚石膜时在膜中添加元素，类金刚石膜与基材之间的中间层等进行了较全面的分析。     

Unique microstructure and property of a 2024 aluminum alloy subjected to upsetting extrusion multiple processing

The microstructure and hardness of a 2024 aluminum alloy subjected to multi-pass upsetting extrusion at ambient temperature were studied. Experimental results indicated that with the number of upsetting extrusion passes increasing, the grains of the alloy are gradually refined and the hardness increases correspondingly. After ten passes of upsetting extrusion processing, the grain size decreases to less than 200 nm in diameter and the sample maintains its original shape, while the hardness is double owing to equal-axial ultrafine grains and work hardening effect caused by large plastic deformation.     

锡磷青铜合金水平连铸工艺参数的优化

铸造锡磷青铜合金组织中存在显微缩松、枝晶偏析和反偏析是冷加工报废的主要原因.通过连铸工艺参数的正交实验,建立了轧制成材率与主要工艺参数之间的神经网络描述,网络模型与遗传算法结合对工艺参数的组合进行了优化,改善了铸坯的组织,提高了轧制带材成材率.     

U形件弯曲影响回弹因素模拟分析

板材在弯曲过程中存在的最突出的问题是弯曲回弹难以精确控制.弯曲卸载后产生的回弹,使弯曲件的形状和尺寸与模具工作部分的形状和尺寸不符.弯曲件的最后形状与整个变形过程有关,模具几何参数、材料性能参数等都会对回弹产生很大影响.在板材弯曲成形智能化控制系统中,准确确定实时识别和预测模型的输入、输出参数是弯曲智能化控制的成功与否以及回弹控制精度高低的关键.本文采用Ls-dyna软件,对U形件弯曲影响回弹的因素进行了分析,得出了影响回弹规律的主要因素.为U形件弯曲智能化控制神经网络参数识别及预测模型输入、输出参数的选择提供依据.