Using culturomics and social media data to characterize wildlife consumption

Wildlife provides food, medicine, clothing, and other necessities for humans, but overexploitation can disrupt the sustainability of wildlife resources and severely threaten global biodiversity. Understanding the characteristics of consumer behavior is helpful for wildlife managers and policy makers, but the traditional survey methods are laborious and time-consuming. In contrast, culturomics may more efficiently identify the features of wildlife consumption. As a case study of the culturomics approach, we examined tiger bone wine consumption in China based on social media and Baidu search engine data. Tiger bone wine is one of the most purchased tiger products; its consumption is closely related to tiger poaching, which greatly threatens wild tiger survival. We searched a popular social media website for the term “tiger bone wine” and focused on posts that were originally created from 1 January 2012 to 31 December 2018. We filtered and classified posts related to the purchase, sale, or consumption of tiger bone wine and extracted information on providers, consumption motivations, year of production, and place of origin of the tiger bone wines based on the texts and photos of these posts. We found 756 posts related to tiger bone wine consumption, 113 of which mentioned providers of tiger bone wine, including friends (53%), elder relatives (37%), peer relatives (7%), and others (3%). Out of the 756 posts, 266 indicated the motivations of tiger bone wine consumption. Tiger bone wines were consumed as a tonic (34%), medicine (23%), game product (30%), and a symbol of wealth (28%). Some posts indicated ≥2 consumption motivations. These findings were consistent with the search queries from Baidu index. Such information could help develop targeted strategies for tiger conservation. The culturomics approach illustrated by our study is a rapid and cost-efficient way to characterize wildlife consumption.     

基于空间适宜性评价和人口承载力的贵溪市中心城区城市开发边界的划定

城市开发边界的划定能够合理引导城市空间的有序发展,控制其无序蔓延。论文以典型的资源型城市贵溪市为研究区,从空间适宜性评价、人口承载力、城市规模以及城市总体规划和土地利用总体规划（简称“两规”）衔接等方面探索有效的城市开发边界划定方法。空间适宜性评价综合考虑自然、空间可达性和生态条件,运用聚类分析法确定区域内不宜作为开发建设的生态底线区域和适宜建设开发区域的高低等级,以此确定城市开发边界的发展方向。通过灰色预测GM(1,1)模型预测研究区2020年人口总量,并基于土地资源和水资源承载力验证当地所能容纳的最大人口总量,同时确定城市规模和划定城市开发边界。以空间适宜性评价、人口承载力、城市规模预测、两规衔接和空间形态控制等方法倒逼缩减建设用地,从而划定城市发展的刚性和弹性增长边界。     

用EXCEL进行精密度-偏性分析质控数据处理

利用EXCEL强大的数据处理功能，可以方便地对精密度—偏性分析质控数据进行处理，具有较高的推广价值。     

Nonstationary, long memory and anti-persistence in several climatological time series data

In this article we examine the stochastic behaviour of several daily datasets describing sun (total irradiance at the top of the atmosphere and sunspot numbers) and various climatological anomaly series by looking at their orders of integration. We use a testing procedure that permits us to consider fractional degrees of integration. The tests are valid under general forms of serial correlation and deterministic trends and do not require estimation of the fractional differencing parameter. Results show that the series are all nonstationary, with increments that might be stationary for those variables affecting sun, and anti-persistent for those affecting air temperatures.     

基于GIS的汉江水污染信息管理系统的结构设计

介绍了基于GIS开发的汉江流域水污染信息管理系统的结构设计 ,本系统可实现对汉江全流域的基础地理信息、用水信息、污染信息的输入、输出、查询 ,进而利用水文水质预测模型作出评价、预测 ,为有效控制汉江流域水污染 ,促进全流域的社会经济可持续发展提供一定的决策支持。     

地球化学数据去噪方法研究

在简要介绍移动平均、傅立叶交换和小波变换基本原理的基础上，比较了它们在地球化学数据处理过程中去除噪声效果的优劣，并应用于塔北雅克松-轮台地区的地球化学勘探实际。研究结果表明，小波变换是一种理想的数据处理方法。     

云南安宁工业区工业经济-水资源-水污染系统仿真模型及策略分析

水资源短缺和水污染是安宁工业区经济发展的重要限制因素。本文将该工业区分解为3个子区,应用系统动态学方法,建立多区相关的工业经济-水资源-水污染系统仿真模型,分别对各子区1985至2000年的工业产值、工业用水差距和水质进行多方案预测。在子区域综合的基础上,结合多级决策树法,筛选出安宁工业区协调工业经济、水资源和水质之间关系的最佳方案。     

浅议提高废水污染源监测数据代表性

对废水污染源监测中影响监测数据代表性的主要因素进行了分析,并对提高废水污染源监测数据代表性提出了可行性建议。     

生命周期评价数据库分析与建模

基于关系数据库和面向对象程序设计理论建立了生命周期评价数据库系统。通过综合分析生命周期评价数据，根据生命周期评价数据的数据类型，将数据分为产品评价数据、产品档案数据、基础材料数据和影响评价基础数据，相应的设计了4个数据库。运用关系数据库理论分别对4个数据库建立了物理结构模型。     

YEP与数据通讯网络

ＹＥＰ采用了先进的计算机管理技术与电子邮件网络系统，到目前为止，省项目办和英国ＤＲＡ咨询专家与世界银行和涉及ＹＥＰ的各有关单位之间及时准确地进行了大量的数据传输工作，保证了ＹＥＰ工作的顺利进行。