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.     

基于网络数据的乡村旅游热点识别及成因分析——以江苏省为例

基于旅游网站数据,提出一种乡村旅游热点识别方法,以江苏省为例,运用趋势面、核密度、热点分析等方法探寻乡村旅游冷热格局及演变特征,并借助地理探测器揭示其时空演化的影响因素。结果表明：（1）江苏省乡村旅游热度的时间演化规律明显,年际变化呈“S”型演变轨迹;季节变化呈“三峰四谷”特征。（2）江苏省乡村旅游热度的空间结构在2009—2017年间经历了“单核—双核—三核”的演化过程,但其空间异质性依然显著,整体表现为“南高北低,东高西低”的差异特征。（3）影响因素在不同时段的影响强度各异,交通条件、服务能力一直是主导因素,经济水平对乡村旅游发展早期的热度提升有显著影响,资源禀赋的显著性趋于下降,生态环境和政府导向的影响力逐渐增强。基于网络数据的乡村旅游热点识别为乡村旅游定量研究提供了新的研究视角,对乡村旅游资源开发与区域合作具有重要的指导意义。     

唐钢2×150t转炉煤气回收系统设计及运行实践

在此较详细地介绍了唐钢一炼钢厂 2× 15 0t转炉煤气回收湿法除尘工艺和系统的技术特点。该系统设计吸收了国内外大型转炉煤气回收的经验。经近 18个月的生产实践 ;认为效果良好 ,煤气回收率近 80 % ,热值近 80 0 0kJ Nm3,放散排放浓度小于 80mg m     

跌水曝气——改进型填料(滤料)排水系统处理屠宰废水的设计

对屠宰厂原有的排水管道系统进行改造和革新 ,使之成为沉淀、厌氧好氧生物接触氧化与过滤的新型排水系统 ,用于屠宰废水处理 ,实现了达标排放     

新型伞形罩烟气洗涤器的性能研究

针对中小型燃煤锅炉的粉尘和二氧化硫等有害气体的污染问题,开发出一种新型伞形罩烟气洗涤器。以粉煤灰、空气和水为物系,测试了伞形罩烟气洗涤器的压降(ΔP)、除尘效率和动力消耗。实验的入口气速为10～18m/s,含尘浓度为2～22g/m3,液气比(L/G)0～0.8L/m3。结果表明:伞形罩洗涤器的ΔP较小,在250～750Pa范围内;当L/G为0.2L/m3时,除尘效率达98.8%以上,动力消耗约0.06×10-3kW.h/m3(气体约216Pa),实现节能高效的目的。     

长江上游森林植被变化对削洪减灾功能的影响

长江上游具有形成暴雨洪水的地形与气候条件，森林植被削洪减灾功能的提高必须着眼于森林植被—土壤生态系统结构的改善，削洪减灾功能的提高是通过林冠层、枯枝落叶层和土壤层对雨水的截留拦蓄作用实现的。研究区森林植被—土壤生态系统区域差异明显，不同地区该系统林冠层、枯枝落叶层和土壤层的最大截持水量不同，该系统削洪减灾功能的大小不仅与降雨特点有关，而且与系统各水文层前期持水量有关。在连续长时间暴雨情况下，森林植被—土壤生态系统除对第一次洪峰有削减作用外，对后续暴雨洪水的削减作用不明显，甚至会使洪峰增高。根据宜昌站30d洪水量的地区组成和森林植被—土壤生态系统截留持水功能的特点，提出了长江上游森林植被恢复、重建与保护的宏观调控对策。     

特大型煤和瓦斯突出的地质条件及其成因

特大型煤和瓦斯突出危害极大，具有独特的发生条件，应专门研究。在全国９９ 次特大型煤和瓦斯突出详细研究的基础上，总结了特大型突出的一般特征及发生的地质和采矿条件，并给出了南桐矿区的几个临界值。对特大型突出地质条件的成因进行了较深入的探讨，提出了防止特大型突出的几点建议     

Review of the remediation strategies for soil water repellency

Many regions of the world are predicted to experience water scarcity due to more frequent and more severe droughts and increased water demands. Water use efficiency by plants can be negatively affected by soil water repellency (SWR). It is timely to review existing techniques to remedy SWR. Ideally remediation addresses the origins of a problem. However, the fundamental mechanisms of how and why SWR develops are still poorly understood. In this review it was hypothesized that SWR occurs where the balance of input-decomposition of organic matter is impaired, due to either increased input or decreased decomposition rates of hydrophobic substances. Direct and indirect strategies to remedy SWR were distinguished. While direct remediation aims at abolishing the causes of SWR, indirect strategies seek to manage sites with SWR by treating its symptoms. The 12 reviewed strategies include applying surfactants, clay, slow-release fertilizers, lime, and fungicides, bioremediation of SWR through stimulating earthworms, choosing adapted vegetation, irrigation, cultivation, soil aeration and compaction. Some of the techniques have been applied successfully only in laboratory experiments. Our review highlights that it is not straightforward to cure SWR based on easily measurable and site-specific soil and vegetation properties, and that long-term, large-scale field experiments are required to improve the understanding of the evolution of SWR as cornerstone to develop cost-effective and efficient remediation strategies. We also identified current research gaps around the diagnosis and prevention of SWR.     

Determination of Nitrobenzene in Wastewater Using a Hanging Mercury Drop Electrode

The determination of trace amount nitrobenzene in wastewater on a hanging mercury drop electrode was studied. The determination conditions of pH, supporting electrolyte, accumulation potential, accumulation time, and voltammetric response were optimized. The sharp peak of the nitrobenzene was appeared at 0.05 V. The peak electric current was proportional to the concentration of nitrobenzene in the range of 1.47 × 10⁻⁵ ∼ 1.0 × 10⁻³ mol/l with relative standard deviations of 3.99 ∼ 8.94%. The detection limit of the nitrobenzene in water was 5 × 10⁻⁶ mol/l. The proposed method offered low limit of determination, easy operation, the use of simple instrumentation, high sensitivity and good reproducibility. It was applied to the determination of nitrobenzene in wastewater with an average recovery of 94.0% ∼ 105%. The proposed method provided fast, sensitive and sometimes real time detection of nitrobenzene.     

基于大数据挖掘技术的地震舆情感知研究

对地震舆情信息的深入感知和有效管理,能够保障社会和谐发展.提出一个基于大数据技术和深度学习的地震舆情感知平台,基于Hadoop和MongoDB大数据技术实现对海量实时地震舆情数据的处理和存储.基于Word2vec和LSTM的融合模型能够有效实现震后网民的情感识别,为舆情预警提供支持.以台湾5.8级地震舆情数据为例,对该...