云南扶桑绵粉蚧的发生及防治

扶桑绵粉蚧是一种全球恶性入侵害虫,2008年传入我国,目前已有13个省区报道其为害,2009年在云南省被发现,截至2013年3月,云南省共8个州(市) 10个县(市)已有分布。扶桑绵粉蚧寄主范围广,危害性大,适应性强。同时,云南省花卉、蔬菜调运及进出口贸易频繁,加之气候类型丰富、水热条件优越、自然地理环境复杂多样、动植物资源丰富等优势,有利于扶桑绵粉蚧的入侵、定殖与扩散,易造成较大的经济损失。目前,关于云南省扶桑绵粉蚧的研究仍然缺乏,现就扶桑绵粉蚧在云南的发生现状、潜在风险和防治措施等方面进行概述,以期为该虫的有效防范提供参考。     

广州市城市生态环境问题与防治对策

本文分析了广州市城市生态环境的大气、水、噪声、固体废物,园林绿化等问题,提出了做好城市生态规划,加强城市生态环境管理,扩大城市园林绿化,以森林包围城市,运用政策法令调控城市生态环境等防治对策。     

Choosing the number of principal coordinates when using CAP,the canonical analysis of principal coordinates

This study explores various options available for choosing the number of principal coordinates m in the canonical analysis of principal coordinates ‘CAP’, a useful procedure that has wide‐ranging application wherever multivariate data sets are collected or generated. Choosing too few coordinates (small m) in this constrained (i.e. hypothesis‐based) ordination procedure may lead to inadequate separation of the groups (when used as a canonical discriminant analysis) or to inadequate correlation between explanatory and response variables (when used as a canonical correlations analysis), whereas choosing too many (large m) may lead to overparameterization, resulting in overfitting of the data and spurious relationships. It is shown here that the optimum number of principal coordinates is simply the one that results in the smallest P value in the canonical analysis carried out using permutations. For data in which more than one m value results in the same minimum P value, m should be chosen from that set to be the number of principal coordinates that minimizes the leave‐one‐out residual sum of squares. This choice of m provides suitable solutions for each of the 17 case studies investigated here (which yielded 17 canonical discriminant analyses and 7 canonical correlation analyses).     

Assessment of a method for cultivar selection based on regional trial data

Summary In this study a method for analyzing regional trial data is investigated for its effectiveness in cultivar selection. The method is a synthesis of three procedures: (1) regression analysis for genotype × environment (GE) interaction, and subsequent cluster analysis for grouping cultivars for similarity of response; (2) superiority measure analysis of cultivar performance based on the distance mean square between the test cultivar and the maximum response; (3) type 4 stability analysis for three-way classification data (cultivar × location × year), to measure a cultivar's stability. Each of these three procedures is aimed at different aspects of the selection problem: the first obtains an overview of the types of cultivar response; the second measures a cultivar's general adaptability within the region; the third assesses a cultivar's ability to withstand unpredictable variation, namely that caused by year effects. Four sets of published data, each originally analyzed by a univariate or a multivariate approach, were used as examples. The results suggest that the present method provides direct and useful information for selection purposes. The superiority measure, which is the core of the method, can be used even if the data do not fit the linear model for GE interaction. Plotting the data with a fixed standard represented by the maximum response provides a simple visual tool for identifying environments where a cultivar performs well.Contribution No. C-035 from Research Program Service, Research Branch, Agriculture Canada, Ottawa, Ontario, K1A 0C6     

Markowitz模型与局势决策

本文论证了局势决策乃是随机优势原则下的Markowitz模型的一种特殊情况和局势决策所具有的优良性质,证实了局势决策的可行性,从而获得了一种简便易行的实用决策方法。     

Farmers’ preferences for result-based schemes for grassland conservation in Slovenia

Government-funded payments for ecosystem services (PES) have increasingly been used to facilitate transactions between users of environmental services and their providers. In order to improve the link between payments and the service provided, some countries in the EU have promoted result-based schemes (RBS), which remunerate farmers for ecological results, as part of their agricultural policy. Since PES programs are voluntary, it is important to understand farmers’ responses before more large-scale implementations of RBS are initiated. Using a choice experiment and a mixed logit model, we elicited the preferences of farmers in two Natura 2000 sites in Slovenia for different design elements of a hypothetical scheme for dry grassland conservation. We found that the majority of farmers preferred the result-based approach over the management-based scheme both in terms of payment conditions and monitoring; one group of farmers preferred the RBS very strongly (average WTA of more than 500 EUR/ha/yr) and another group less strongly (average WTA about 200 EUR/ha/yr). Farmers also showed a higher preference for on-farm advise and training in small groups than for lectures, which would be offered to a larger audience. A collective bonus, which would incentivise coordination and could potentially increase participation rates in the scheme, significantly influenced the farmers’ willingness to adopt the scheme. However, the estimated average WTA was comparable or lower than the 40 EUR/ha annual bonus payment. Older farmers and those who managed small and semi-subsistent farms were significantly more likely to be highly resistant to scheme adoption no matter its design.     

天可力氨糖胶囊中氨基葡萄糖硫酸钾测定方法比较

目的:选择一种能准确测定天可力氨糖胶囊中氨基葡萄糖硫酸钾含量的方法。方法:参照GB/T 20365-2006硫酸软骨素和盐酸氨基葡萄糖含量的方法进行液相色谱法测定以及利用盐酸氨基葡萄糖Fdson—Morgan反应后在525 nm左右波长处有吸收峰,测定其吸收值与标准品比较进行比色定量。结果:液相色谱法测定时胶囊中的其它中药成分干扰很大,数据偏差太大;而比色法测定时,氨基葡萄糖盐酸盐含量在175μg/mL浓度范围内,呈良好线性关系:Y(μg/mL)=0.196X-O.004,R=0.997,平均回收率102.09%。结论:该比色法测定方法灵敏、准确、简便,可供天可力氨糖胶囊中氨基葡萄糖硫酸钾含量测定。     

Creating robust, reliable, clinically relevant classifiers from spectroscopic data

I describe in detail the intimately connected feature extraction and classifier development stages of the data-driven Statistical Classification Strategy (SCS) and compare them with current practice used in MR spectroscopy. We initially created the SCS for the analysis of MR and IR spectra of biofluids and tissues, and subsequently extended it to analyze biomedical data in general. I focus on explaining how to extract discriminatory spectral features and create robust classifiers that can reliably discriminate diseases and disease states. I discuss our approach to identifying features that retain spectral identity and provisionally relate these features, averaged subregions of the spectra, to specific chemical entities (“metabolites”). Particular emphasis is placed on describing the steps required to help create classifiers whose accuracy doesn’t deteriorate significantly when presented with new, unknown samples. A simple but powerful extension of the discovered features to detect metabolite-metabolite (feature-feature) interactions is also sketched. I contrast the advantages and disadvantages of using either spectral signatures or explicit metabolite concentrations derived from the spectra as sets of discriminatory features. At present, no clear-cut preference is obvious and more objective comparisons will be needed. Finally, I argue that clinical requirements and exigencies strongly suggest adopting a two-phase approach to diagnosis/prognosis. In the first phase the emphasis ought to be on providing as accurate a diagnosis as possible, without any attempt to identify “biomarkers.” That should be the goal of the second, research phase, with a view of providing prognosis on disease progression.