山东西南部南四湖流域环境地质综合调查

本文论述了水体污染、矿山环境地质灾害、地下水环境异常、南四湖淤积、地球化学环境与地方病等环境地质问题，探讨了煤炭开采对南四湖湖容演变的积极影响。湖体及主要人湖河流污染严重；流域内煤炭资源开发引起的矿山环境地质灾害比较严重，地面塌陷面积达112．395km^2；各种固体废弃物积存总量6412．68万t；矿井排水对矿区地下水资源造成严重破坏。地方病以地氟病和克山病为主。在对流域内环境地质问题综合分析的基础上，提出了对流域环境地质问题的治理措施。     

Emerging and vector-borne diseases: Role of high spatial resolution and hyperspectral images in analyses and forecasts

 Many infectious diseases that are emerging or transmitted by arthropod vectors have a strong link to landscape features. Depending on the source of infection or ecology of the transmitting vector, micro-habitat characteristics at the spatial scale of square meters or less may be important. Recently, satellite images have been used to classify habitats in an attempt to understand associations with infectious diseases. Whether high spatial resolution and hyperspectral (HSRH) images can be useful in studies of such infectious diseases is addressed. The nature of questions that such studies address and the desired accuracy and precision of answers will determine the utility of HSRH data. Need for such data should be based on the goals of the effort. Examples of kinds of questions and applications are discussed. The research implications and public health applications may depend on available analytic tools as well as epidemiological observations. Received: 30 July 2001 / Accepted: 14 October 2001     

云南省金沙江流域作物病虫灾害区划研究

选取5个指标,运用模糊聚类方法进行了云南金沙江流域作物病虫灾害区划,将该流域划分为3个病虫灾害 区、8个病虫灾害亚区,揭示了该流域病虫灾害的地域差异性,为因地制宜地制定病虫灾害防治规划及减灾防灾措施 提供了科学依据。     

基于数据挖掘分析《类证治裁》治疗脾胃病的用药规律

目的：基于数据挖掘分析林珮琴《类证治裁》治疗脾胃病的用药规律,为中医药治疗脾胃病及新方研发提供参考。方法：运用中医传承计算平台构建《类证治裁》治疗脾胃病的方剂数据库,并对其进行用药频次、性味、归经、功效、高频组合与核心组合的分析。结果：共纳入方剂123首,涉及药物142味。用药频次≥20次的共8味,其中甘草应用频次最多。四气以温、寒、平为主,五味以甘、苦、辛为主,归经以脾、肺、胃为主。药物功效以补虚类为主。通过关联规则分析得到药物高频组合16组,通过聚类分析得到药物核心组合3组。结论：林珮琴治疗脾胃病始终秉持“以补益脾胃为本”的理念,补行并重,补清兼顾,为现代中医学诊治脾胃病提供了一定的理论依据。     

《卫生宝鉴》中治疗脾胃病方剂用药规律

目的：基于数据挖掘分析《卫生宝鉴》中治疗脾胃病方剂的用药规律。方法：运用中医传承辅助平台（TCMISS）V2.5,采用频次统计、关联规则和聚类分析等数据挖掘方法,对《卫生宝鉴》中所载脾胃病的用药规律进行分析。结果：共收集处方151首,中药168味。频次≥17次的中药有21味,排前5位的依次是陈皮、白术、炙甘草、木香、干姜;温性中药使用频次最高,其次是寒性、平性中药;辛味药出现最多,其次是苦味、甘味药;排前5位的中药归经依次是脾、胃、肺、大肠、心经;频次≥14次的中药组合24个,对药物组合进行关联规则分析得到中药组合17个;聚类分析得到新方聚类的中药组合5组,对应新方组合5组。结论：通过中医传承辅助平台分析得出,《卫生宝鉴》中所载治疗脾胃病的处方注重甘辛温补、健脾消滞,慎用苦寒药,该研究结果可为临床治疗脾胃病开发新药物提供一定的参考     

对虾与鱼、贝类封闭式综合养殖的实验研究

于1995－1999年采用陆基实验围隔法系统地研究了对虾与鱼、贝类封闭式综合养殖的基础问题，所选取的材料为中国对虾、台湾红罗非鱼、缢蛏与海湾扇贝，研究出了4种优化结构养殖模式。结果表明，4种模式的组成及各成分间生物量（收获前）的比值分别为：对虾的养殖效果都比同样条件下的对虾单养模式显著优越；其中最好的虾、鱼、贝三元综合养殖模式将产量提高了28％，投入氮的利用率提高了85％。同时采取封闭式的养殖方法，向浅海输出的氮只占养殖输入氮的6％－8％，从而显著降低了对浅海的污染。     

西安市大降水环流特征分析

病虫害是农业气象灾害衍生灾害，是危害农业生产的重要自然灾害，往往使农作物生长和发育受到抑制和损害，造成农作物产量减少或品质下降。通过对农业病虫害的发生特点及相关农业气象条件进行分析，对农业增产增收、可持续发展具有重要意义。     

Use of earth observation data for applications in public health

The Earth Observation (EO) data with their advantages in spectral, spatial and temporal resolutions have demonstrated their great value in providing information about many of the components that comprise environmental systems and ecosystems for decades that are crucial to the understating of public health issues. This literature review shows that in conjunction with in situ data collection, EO data have been used to observe, monitor, measure and model many environmental variables that are associated with disease vectors. Furthermore, satellite derived aerosol optical depth has been increasingly employed to estimate ground-level PM_2.5 concentrations, which have been found to associate with various health outcomes such as cardiovascular and respiratory diseases. It is suggested that Landsat-like imagery data may provide important data sources to analyse and understand contagious and infectious diseases at the local and regional scales, which are tied to urbanisation and associated impacts on the environment. There is also a great need of data products from coarse resolution imagery, such as those from moderate resolution imaging spectrometer, multiangle imaging spectroradiometer and geostationary operational environmental satellite , to model and characterise infectious diseases at the continental and global scales. The infectious diseases at greater geographical scales have become unprecedentedly significant as global climate change and the process of globalisation intensify. The relationship between infectious diseases and environmental characteristic have been explored by using statistical, geostatistical and physical models, with recent emphasis on the use of machine-learning techniques such as artificial neural networks. Lastly, we suggest that the planned HyspIRI mission is crucial for observing, measuring and modelling environmental variables impacting various diseases as it will improve both spectral resolution and revisit time, thus contributing to better prediction of occurrence of infectious diseases, target intervention and tracking of epidemic events.