三种风险预测模型预测钢铁工人颈动脉粥样硬化的效能比较

背景颈动脉粥样硬化(CAS)不仅影响钢铁工人的工作效率,而且是引发缺血性脑血管疾病最重要的危险因素。近年来,越来越多的学者利用机器学习并通过易获得的因素对疾病进行风险预测,但目前,关于CAS风险预测模型的研究依然缺乏。目的运用支持向量机(SVM)、BP神经网络(BPNN)与随机森林(RF)模型构建钢铁工人CAS发生风险预测模型,并比较其预测效能。方法选取2017年3—6月在唐山市弘慈医院进行体检和健康监测的4568例钢铁工人为研究对象,按照本团队编写的《健康评估检查表》进行调查,调查内容:人口学特征(性别、年龄、体质指数、文化程度、婚姻状况)、个人的行为生活习惯与方式(吸烟、饮酒)、个人病史(高血压、糖尿病、CAS家族史)、职业史(倒班、高温作业、噪声作业)。收集研究对象的实验室检查指标,如胆固醇、三酰甘油、同型半胱氨酸、尿酸。结合非条件多因素Logistic回归分析结果以及查阅相关文献,确定变量构建SVM、BPNN和RF模型并进行比较。结果训练集显示SVM、BPNN和RF模型预测钢铁工人发生CAS的准确率分别为83.81%、79.27%、86.60%,灵敏度分别为80.10%、66.19%、73.62%,特异度分别为87.32%、91.62%、98.90%,受试者工作特征曲线下面积(AUC)分别为0.84、0.79、0.86。SVM模型的灵敏度最高,RF模型在准确率、特异度和AUC方面高于其余两种模型,差异有统计学意义(P<0.05)。测试集显示SVM、BPNN和RF模型预测钢铁工人发生CAS的准确率分别为85.70%、75.46%、73.37%,灵敏度分别为81.63%、64.65%、60.00%,特异度分别为90.29%、87.66%、88.45%,AUC分别为0.86、0.76、0.74。SVM模型在灵敏度、准确率和AUC方面高于其余两种模型比较,差异有统计学意义(P<0.05)。结论运用SVM模型预测钢铁工人CAS发生风险的效果优于BPNN和RF模型。

广西某金属冶炼厂工人镉暴露与认知相关基因甲基化的关联

[背景]多项研究表明镉暴露与认知功能受损相关,但是关于职业镉暴露与多个认知相关基因甲基化水平的关联性研究有限。[目的]观察工人重金属镉职业暴露后机体认知相关的klotho(KL)、脑源性神经营养因子(BDNF)、淀粉样蛋白前体(APP)基因的甲基化水平变化,探讨镉与3个基因甲基化的关联。[方法]选择广西某金属冶炼厂参与2017年职业体检的职业工人作为研究对象,完成问卷调查及血样、尿样的采集。采用原子吸收光谱法测定尿镉(UCd)浓度,并经尿肌酐调整校正。根据调整后的UCd(<P_(25),P_(25)~P_(75),>P_(75))将研究对象分为低、中、高暴露组,将各暴露组工人按年龄、性别进行分层,采用频数匹配法从各暴露组随机抽取150例样本,应用多重PCR结合的MethylTarget技术检测APP、BDNF、KL基因甲基化水平。通过方差分析和Mann-Whitney U检验探索各组之间三个基因甲基化水平和CpG位点的差异,限制性立方样条分析用于探索UCd水平与基因甲基化率之间的暴露-效应关系。[结果]共纳入了450名研究对象,其中男性377名(83.78%),年龄为(38.88±6.87)岁,UCd水平为2.73(1.04,5.75)μg·g^(-1)。APP、BDNF、KL基因平均甲基化率分别为(1.52±0.34)%、(4.55±1.08)%、(2.34±0.39)%。APP基因04片段、KL基因及其02片段的甲基化率在各暴露组间存在差异(P<0.05);中暴露组APP基因04片段甲基化率低于低暴露组(P<0.05),而中、高暴露组的KL基因及其02片段平均甲基化率均低于低暴露组(P<0.05)。限制性立方样条分析的结果显示,UCd水平(lg转换)与KL基因甲基化率呈线性负相关关系(P=0.035),即随着UCd水平升高,KL基因甲基化率降低。[结论]镉暴露可能与KL、APP基因低甲基化率有关,KL基因甲基化水平与尿镉水平呈负相关。

Application of BPANN in spinning deformation of thin-walled tubular parts with longitudinal inner ribs

Back-propagation artificial neural network (BPANN) is used in ball backward spinning in order to form thin-walled tubular parts with longitudinal inner ribs. By selecting the process parameters which have a great influence on the height of inner ribs as well as fish scale on the surface of the spun part, a BPANN of 3-8-1 structure is established for predicting the height of inner rib and recognizing the fish scale defect. Experiments data have proved that the average relative error between the measured value and the predicted value of the height of inner rib is not more than 5%. It is evident that BPANN can not only predict the height of inner ribs of the spun part accurately, but recognize and prevent the occurrence of the quality defect of fish scale successfully, and combining BPANN with the ball backward spinning is essential to obtain the desired spun part.

Computer Simulation on Metallic Card Clothing Garnett Wire Teeth's Temperature Field & Structure Field in the Process of Quenching Treatment

The quenching process of garnett wire teeth of metallic card clothing heated by flame was researched by use of 3-D finite element method and the equation of boundary condition was established by making use of a model of artificial neural network. The transient temperature field, phase transformation in the heating process, the quenching microstructures and the hardness distribution on quenched garnett wire teeth of metallic card clothing were simulated. The result shows that the maximum error of the hardness between the simulative value and the actual measuring value is 8.0% on only one testing point and errors are all less than 3.0% on other testing points.

Cr （Ⅲ） Removal from Synthetic Waste Water by Using Water Pond Mud

The pollution of aquatic ecosystem by heavy metals has assumed serious proportions due to their toxicity and accumulative behavior. The toxicity metal is dependent on its chemical form and therefore removal of metal is more meaningful than the estimation of its concentrations. In this study, the batch experiments were carried out under 30℃ to study the effect of pH, initial Cr concentration, adsorbent dose and contact time on the removal of Cr （lII）. The maximum adsorption efficiency （99%） was observed when 1.5 g of pond mud was used for removal ofCr （Ⅲ） from test solution containing 150 mg·Cr / 100 ml. The optimal pH and contact time recorded during the study were 6 and 10.0, respectively.

Protection strategy for improved catalytic stability of silicon photoanodes for water oxidation

Silicon-based electrodes have attracted great attention in the artificial photosynthetic systems that mimic natural photosynthesis and directly convert the solar energy into chemical energy. Despite significant efforts to date,catalytic stability of the silicon photoelectrodes is limited by their poor electrochemical stability. The formation of passivation or protective layers provides a feasible strategy to improve the photocatalytic stability of silicon photoelectrodes. Many candidates including metals, metal oxides, metal silicides and polymers have been explored as the protection layers for silicon photoelectrodes. The present review gives a concise overview of the protected silicon photoanodes for water oxidation with a focus on the relationship between the structural architecture of silicon photoanodes and their photocatalytic activity and stability.

Recent advances on crystalline materials-based flexible memristors for data storage and neuromorphic applications

Memristors have recently emerged as promising contenders for in-memory computing and artificial neural networks,attributed to their analogies to biological synapses and neurons in structural and electrical behaviors.From the diversity level,a variety of materials have been demonstrated to have great potential for memristor applications.Herein,we focus on one class of crystalline materials(CMs)-based flexible memristors with state-of-the-art experimental demonstrations.Firstly,the typical device structure and switching mechanisms are introduced.Secondly,the recent advances on CMs-based flexible memristors,including 2 D materials,metal-organic frameworks,covalent organic frameworks,and perovskites,as well as their applications for data storage and neuromorphic devices are comprehensively summarized.Finally,the future challenges and perspectives of CMs-based flexible memristors are presented.

Atmospheric corrosion mapping of copper surfaces from diffuse light scattering measurements by an optoelectronic sensor system

A novel light scattering technique for mapping metal surface corrosion is presented and its results on copper exposed to atmosphere are reported. The front end of the instrument is made up of a sensor module comprising a thin beam light emitting diode (LED) illuminating a small spot on the metal surface, and a matched pair of photodetectors, one for capturing the reflected light and the other for sampling the scattered light. The analog photocurrent signals are digitized and processed online by a personal computer (PC) to determine the corrosion factor defined in terms of the two current values. By scanning the sample surface using the light beam and by computing the corrosion factor values simultaneously, a three dimensional graph and a two dimensional contour map are generated in the PC using Matlab tools. The values of the corrosion factor measured in different durations of exposure to atmosphere, which obey a bilogarithmic law, testify to the validity of our mathematical model.