Data from: Fine-scale tracking of ambient temperature and movement reveals shuttling behavior of elephants to water|大象行为数据集|环境温度影响数据集
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Population and Housing Census of 2007 - Ethiopia
Geographic coverage --------------------------- National coverage Analysis unit --------------------------- Household Person Housing unit Universe --------------------------- The census has counted people on dejure and defacto basis. The dejure population comprises all the persons who belong to a given area at a given time by virtue of usual residence, while under defacto approach people were counted as the residents of the place where they found. In the census, a person is said to be a usual resident of a household (and hence an area) if he/she has been residing in the household continuously for at least six months before the census day or intends to reside in the household for six months or longer. Thus, visitors are not included with the usual (dejure) population. Homeless persons were enumerated in the place where they spent the night on the enumeration day. The 2007 census counted foreign nationals who were residing in the city administration. On the other hand all Ethiopians living abroad were not counted. Kind of data --------------------------- Census/enumeration data [cen] Mode of data collection --------------------------- Face-to-face [f2f] Research instrument --------------------------- Two type sof questionnaires were used to collect census data: i) Short questionnaire ii) Long questionnaire Unlike the previous censuses, the contents of the short and long questionnaires were similar both for the urban and rural areas as well as for the entire city. But the short and the long questionnaires differ by the number of variables they contained. That is, the short questionnaire was used to collect basic data on population characteristics, such as population size, sex, age, language, ethnic group, religion, orphanhood and disability. Whereas the long questionnaire includes information on marital status, education, economic activity, migration, fertility, mortality, as well as housing stocks and conditions in addition to those questions contained in a short questionnaire.
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Materials Project 在线材料数据库
Materials Project 是一个由伯克利加州大学和劳伦斯伯克利国家实验室于 2011 年共同发起的大型开放式在线材料数据库。这个项目的目标是利用高通量第一性原理计算,为超过百万种无机材料提供全面的性能数据、结构信息和计算模拟结果,以此加速新材料的发现和创新过程。数据库中的数据不仅包括晶体结构和能量特性,还涵盖了电子结构和热力学性质等详尽信息,为研究人员提供了丰富的材料数据资源。相关论文成果为「Commentary: The Materials Project: A materials genome approach to accelerating materials innovation」。
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全国 1∶200 000 数字地质图(公开版)空间数据库
As the only one of its kind, China National Digital Geological Map (Public Version at 1∶200 000 scale) Spatial Database (CNDGM-PVSD) is based on China' s former nationwide measured results of regional geological survey at 1∶200 000 scale, and is also one of the nationwide basic geosciences spatial databases jointly accomplished by multiple organizations of China. Spatially, it embraces 1 163 geological map-sheets (at scale 1: 200 000) in both formats of MapGIS and ArcGIS, covering 72% of China's whole territory with a total data volume of 90 GB. Its main sources is from 1∶200 000 regional geological survey reports, geological maps, and mineral resources maps with an original time span from mid-1950s to early 1990s. Approved by the State's related agencies, it meets all the related technical qualification requirements and standards issued by China Geological Survey in data integrity, logic consistency, location acc racy, attribution fineness, and collation precision, and is hence of excellent and reliable quality. The CNDGM-PVSD is an important component of China' s national spatial database categories, serving as a spatial digital platform for the information construction of the State's national economy, and providing informationbackbones to the national and provincial economic planning, geohazard monitoring, geological survey, mineral resources exploration as well as macro decision-making.
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Multi-Text CIR (MTCIR)
MTCIR是一个大规模的合成数据集,包含340万图像对和1770万修改文本。该数据集由亚马逊公司收集,旨在解决组合图像检索领域数据不足的问题,通过多模态大型语言模型生成图像对的修改文本,并提供了多个简短的修改文本,以覆盖各种属性,更好地反映人类查询构建方式,为CIR模型提供更真实、全面的训练基础。
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