Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.     

基于三相幅度测量的相控阵天线快速校准方法

提出了一种基于三相幅度测量的相控阵天线快速校准方法。该方法将天线阵列进行分组,利用每种分组在三种配相下的阵面合成场幅度测量值,可解算出各个天线单元的初始幅相值。该方法仅需幅度测量,避免了相位测量误差影响单元幅相值的计算精度,而且所需幅度测量次数仅为(2N+1)次,可显著提高校准时效性。另外,利用分组思想,同时改变多个单元相位,使总辐射场的幅度变化显著,提升校准准确性。仿真结果表明:校准后相位均方根误差为2.2°,幅度均方根误差为0.2 dB。     

调节性B细胞在自身免疫性溶血性贫血患者外周血中的表达及临床意义

目的: 探讨自身免疫性溶血性贫血（AIHA）患者外周血中调节性B细胞（Bregs）的表达及其在该病发病中的意义。方法:选择16例自身免疫性溶血性贫血患者和14例健康志愿者为研究对象，用流式细胞术分析外周血CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞的表达；ELISA方法检测培养上清液中IL-10的水平。结果:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞、CD19+CD24hiCD27+调节性B细胞的表达分别为（1.27±0.39）％、（9.85±2.18）％，健康志愿者组分别为（2.92±0.71）％、（26.47±4.31）％，两组比较差异有统计学意义（P<0.05）；自身免疫性溶血性贫血患者细胞培养上清中IL-10的水平低于健康志愿者组（P<0.05）。结论:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞比例降低，提示调节性B细胞可能参与自身免疫性溶血性贫血的发病过程。     

丙烷脱沥青装置调合前沥青的综合利用

在丙烷脱沥青装置加热炉试烧装置自产调合前沥青,通过观察油枪雾化沥青的能力、火嘴的燃烧情况以及燃烧后的烟尘状况,筛选出适合沥青燃烧的油枪,最终实现调合前沥青直接做加热炉燃料、减少重油出厂量的目的。     

Evaluation model of green supply chain cooperation credit based on BP neural network

Neural Computing and Applications - More and more enterprises hope to achieve cooperation and win–win. However, many companies often have problems such as insufficient partner credit, which...     

Predicting visual similarity between colour palettes

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour-difference formulae. The best performance (r² = 0.86 and STRESS = 16.9) was obtained using the minimum colour-difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.     

水文序列相依变异识别的RIC定阶准则——以自回归模型为例

水文过程相依性是水文变异的主要表现形式之一,应用自回归模型对其进行拟合时合理确定模型阶数是一个难点问题。本文在分析AIC和BIC准则的基础上,提出了一种以原序列与其相依成分的相关系数作为拟合度指标,同时借用信息熵形式的函数式,作为模型不确定性度量指标的自回归模型定阶准则(简称RIC准则)。以AR(1)、AR(2)、AR(3)和AR(4)模型为例进行统计试验,将不同序列长度下该准则的定阶准确率与其他定阶准则进行比较,试验结果表明,RIC准则对于上述模型均具有较好的适应性,且定阶准确率远高于AIC准则,其中对于前三阶模型RIC准则优于BIC准则,但四阶模型略低于BIC准则。RIC准则的优势是可以同时满足模型定阶、相依程度分级与模型检验的需求,将其应用于实测水文序列分析,结果显示,该准则能较准确地识别自回归模型的阶数,且符合提出的"相依有变异而残差无变异的最小阶数"的检验标准。