胃脘痛证候的聚类分析及因子分析研究

目的 采用聚类分析及因子分析的数据挖掘方法,对胃脘痛的中医临床证候及四诊信息进行研究。方法 收集640例755诊次胃脘痛病例,记录症状、舌象和脉象等临床资料,对临床资料进行聚类分析及因子分析。结果 胃脘痛临床证候可分为六类:脾胃虚寒、肝气犯胃、湿热中阻、脾胃气虚、痰湿内蕴、瘀血停胃,每一类证候对应贡献率不同的特异的四诊信息。结论 胃脘痛有特异的证候分类及四诊信息,通过数据挖掘方法深入研究,对胃脘痛的规范化诊断提供了有效的数据支持,能提高辨证准确性。     

江苏环境库兹涅兹曲线形状研究——基于面板数据模型

该文分析了江苏省1999年至2009年各市GDP数据与各市环境污染三废数据的关系,提出江苏省环境污染情况并不完全符合环境库兹涅兹曲线。该文采用面板模型对苏南、苏中、苏北的三废污染数据与经济增长水平的数据的关系曲线进行分析描绘,结果发现在江苏三大区域九种经济与三废污染的关系曲线形状中,有的呈现“N”型,有的呈现“-”型,有的呈现“S”型,总体并无特定规律。研究结果表明,江苏省经济发展情况与三废污染之间有其自身的特点,因此,在经济发展过程中要采取切合实际的措施,在推动经济发展的同时注意保护环境。     

Does social capital increase public support for economic globalisation?

The dominant explanation of public attitudes vis‐à‐vis economic globalisation focuses on re‐distributional implications, with an emphasis on factor endowments and government‐sponsored safety nets (the compensation hypothesis). The empirical implication of these theoretical arguments is that in advanced economies, on which this article focuses, individuals endowed with less human and financial capital will be more likely to experience income losses. Hence they will oppose economic openness unless they are compensated by the government. It is argued here that including social capital in the analysis can fill two gaps in explanations relying on factor endowments and the compensation hypothesis. First, generalised trust – one key aspect of social capital – constitutes a personal endowment alongside human and financial capital. Second, structural social capital – another key aspect of social capital – can be regarded as a nongovernmental social safety net that can compensate for endowment‐related disadvantages of individuals. Both aspects of social capital are expected to contribute, for distinct reasons, to more positive views on economic openness. The empirical testing relies on survey data for two countries: Switzerland and the United States. For both countries, the results indicate that generalised trust has a strong, positive effect on public opinion of economic globalisation, whereas structural social capital has no effect.     

高校数据云存储的实践

随着"数字校园"建设的深入,许多学校都已经建立或正在筹建自己的校园信息系统。但是,仅仅拥有一流的硬件设备和先进的管理软件肯定是不够的,还需要大量的教育信息资源。这就需要大容量的存储设备。而随着"云计算"所带来的信息化革命,高校将逐步建立各自的"私有云",在学校内部实现"云存储"。     

Comparing Self-Report to Official Measures of Inmate Misconduct

Studies have revealed systematic measurement errors in self-report data on crime and deviance resulting from poor recall and/or underreporting by certain groups of respondents. Official crime data have also been criticized, but for different reasons (e.g. gross underestimations of less serious offenses). Very similar observations have been made in studies of inmate crime (misconduct committed by prison inmates). Despite these criticisms, official data on inmate misconduct continue to be the most frequently used data in related studies. This study compared self-report and official data on inmate assaults, property thefts, and drug offenses for samples of inmates from 46 correctional institutions for adults in Ohio and Kentucky. Findings revealed that officially recorded misconduct underestimates the total volume of inmate crime. Analyses designed to uncover sources of the divergence between self-reported misconduct and officially recorded misconduct revealed far more consistencies than differences in the magnitude of inmate and facility effects on the different types of offenses. A few important differences did emerge in the magnitude of effects such as amount of time served (at the individual level) and facility population size (at the aggregate level).     

An Assessment of the Quality of Homicide Data in the Supplementary Homicide Reports: A Research Note

The Federal Bureau of Investigation (FBI)’s Supplementary Homicide Reports (SHR) is a national-level incident-based data clearinghouse for homicide events in the USA used in countless research studies to track homicide trends, test theory, and analyze policy. Despite its wide use, the SHR has well-known limitations. This research note examines the accuracy of the information in the SHR by comparing homicide cases in Newark, New Jersey with their respective data to determine the level of disagreement between the data sources, which variables exhibit the greatest disagreement, and the case-related variables related to the disagreement. Uniquely, we do this for cases where offenders are known in the SHR. Our findings suggest that variables such as victim-offender relationship and circumstance have high disagreement even when the SHR reports an offender, and that the most important covariate of this is time to close the homicide investigation with an arrest. Research implications of the results are discussed.     

隐私权视野下的网上公开裁判文书之限

裁判文书的上网是落实审判公开的一项有力措施,但其对隐私权的威胁亦不容忽视。裁判文书的全文上网原则上应预先获得当事人的同意,当然,若裁判文书涉及公共利益,则隐私权也应受到限制。但因公共利益的需要而将裁判文书上网时,仍应对具有可识别性的个人信息和其他重要信息予以保密。被害人、证人、未成年人的隐私权应予特殊保护。调解书原则上不应通过网络公开。     

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.     

广域组织RCEP下我国货物贸易流量的影响因素——基于静态面板数据的贸易引力模型

在广域一体化组织RCEP的区域范围内,运用基于静态面板数据的贸易引力模型分析方法,对我国货物贸易流量影响因素的问题进行了研究。首先探讨了什么是RCEP及其发展历程,其次对我国与其他RCEP成员国间的货物贸易流量进行描述性统计,接着对货物出口流量与GDP等诸多影响因素间的关系进行实证研究,再通过对描述性统计和计量研究进行总结,认为我国与其他RCEP成员国间的货物贸易增长较快但增长率并不稳定,GDP和距离因素是影响相互间贸易的主要因素,人口数量、TPP及FTA是次要因素。