Elemental analysis of particulate matter in a metal workshop and of biological samples from exposed workers

During metal welding and cutting, large amounts of particulate matter (PM) are produced that might represent a significant health risk for the exposed workers. In the present pilot study, we performed an elemental analysis of fine PM collected in a metal workshop. Also, elemental analysis of the hair and nail samples collected from workers exposed to the workshop dust and control group was done. Concentrations of 15 elements in PM were measured with X‐Ray Fluorescence (XRF) and Particle Induced X‐ray Emission (PIXE), whereas inductively coupled plasma mass spectrometry (ICP‐MS) was used to determine 12 elements in hair and nail samples. Mean 8‐hr concentrations of PM_2.5, Fe, and Mn in the vicinity of welders were up to 1803, 860, and 30 μg/m³, respectively, whereas in the nearby city, daily PM_2.5 concentrations are on average 11 μg/m³. We found that several elements, especially Fe and Mn, had substantially higher concentrations in hair and nail samples of exposed workers than in the control group, which indicates the accumulation of metals in workers' tissues, although limit values were not exceeded.     

Lower Bounds for the Robustness of Multilevel Coherence

International Journal of Theoretical Physics - Quantum coherence, coming from quantum superposition, occupies a significant position in the field of physics. We put forward a lower bound of the...     

Tantalum Nitride Nanosheets for Photoacoustic Imaging-Guided Photothermal Cancer Therapy

In this study, the synthesis of TaN nanosheets and their application in theranostic agents is reported. After coating polyethylene glycol (PEG) on the TaN nanosheets, the as-synthesized PEG-modified TaN nanosheets (TaN-PEG) show good stability and biocompatibility. Because of their high absorbance in the near-IR region, TaN-PEG can be utilized as photoacoustic imaging contrast agents for tumor imaging. Moreover, TaN-PEG has significant photothermal conversion performance, exhibiting effective laser-induced tumor ablation capability. The TaN-PEG possessing excellent photoacoustic contrast effect and photothermal properties thus have great promise in theranostic applications, especially imaging-guided cancer treatment.     

硅和锗纳米线的原子排布和电荷分布的密度泛函紧束缚方法研究

低维硅锗材料是制备纳米电子器件的重要候选材料，是研发高效率、低能耗和超高速新一代纳米电子器件的基础材料之一，有着潜在的应用价值。采用密度泛函紧束缚方法分别对厚度相同、宽度在0.272 nm~0.554 nm之间的硅纳米线和宽度在0.283 nm~0.567 nm之间的锗纳米线的原子排布和电荷分布进行了计算研究。硅、锗纳米线宽度的改变使原子排布，纳米线的原子间键长和键角发生明显改变。纳米线表层结构的改变对各层内的电荷分布产生重要影响。纳米线中各原子的电荷转移量与该原子在表层内的位置相关。纳米线的尺寸和表层内原子排列结构对体系的稳定性产生重要影响。     

Model and nonlinear dynamic analysis of linear guideway subjected to external periodic excitation in five directions

Nonlinear Dynamics - Investigation of the dynamic characteristics of linear guideway is essential for enhancing structural performance of machine tools. However, few mechanical models are...     

A visual uncertainty analytics approach for weather forecast similarity measurement based on fuzzy clustering

Journal of Visualization - Forecast calibration methods based on historical similar atmospheric state are effective means weather forecast accuracy. Conventional approaches search similar forecasts...     

Exponential Stability for Time-changed Stochastic Differential Equations

Acta Mathematicae Applicatae Sinica, English Series - So far there have been few results presented on the exponential stability for time-changed stochastic differential equations. The main aim of...     

多元统计分析中一类矩阵迹函数最小化问题的有效算法

研究来源于多元统计分析中的一类矩阵迹函数最小化问题$\min c+ tr(AX)+\sum\limits_{j=1}^{m}tr(B_j X C_jX^{T}),\ \ {\rm s. t.} \ X^TX=I_p,$其中$c$为常数, $A\in R^{p\times n}\ (n\geq p)$, $B_j\in R^{n\times n}, C_j\in R^{p\times p}$为给定系数矩阵. 数值实验表明已有的Majorization算法虽可行, 但收敛速度缓慢且精度不高. 本文从黎曼流形的角度重新研究该问题, 基于Stiefel流形的几何性质, 构造一类黎曼非单调共轭梯度迭代求解算法, 并给出算法收敛性分析.数值实验和数值比较验证所提出的算法对于问题模型是高效可行的.     

基于电子病历的乳腺癌群组与治疗方案可视分析

乳腺癌是当前最常见的恶性肿瘤之一，其电子病历数据可用于挖掘隐含规律，对治疗与预后分析有重要意义。通过与乳腺科医生合作，选择合适的预测模型和可视化方法，搭建了一个基于电子病历的乳腺癌群组和治疗方案可视分析系统。首先，对具有高维属性的病人进行降维和聚类处理，形成病人群组，并采用南丁格尔图、词云和时间轴可视化方法，直观展示病人群组间特征的差异；然后，用支持向量机（support vector machine，SVM）模型预测治疗方案，用平行坐标、矩阵热力图和分类图分别展示属性相关性、训练后的特征权重和预测结果；最后，用真实案例验证了系统在群组分析、治疗方案及病人属性关联分析中的有效性，从而较好地帮助医生选择合适的治疗方案。