Human pathogenic streptococcal proteomics and vaccine development

Gram-positive streptococci are non-motile, chain-forming bacteria commonly found in the normal oral and bowel flora of warm-blooded animals. Over the past decade, a proteomic approach combining 2-DE and MS has been used to systematically map the cellular, surface-associated and secreted proteins of human pathogenic streptococcal species. The public availability of complete streptococcal genomic sequences and the amalgamation of proteomic, genomic and bioinformatic technologies have recently facilitated the identification of novel streptococcal vaccine candidate antigens and therapeutic agents. The objective of this review is to examine the constituents of the streptococcal cell wall and secreted proteome, the mechanisms of transport of surface and secreted proteins, and describe the current methodologies employed for the identification of novel surface-displayed proteins and potential vaccine antigens.     

The cell probe complexity of succinct data structures

We consider time-space tradeoffs for static data structure problems in the cell probe model with word size 1 (the bit probe model). In this model, the goal is to represent n$n$-bit data with s=n+r$s=n+r$ bits such that queries (of a certain type) about the data can be answered by reading at most t$t$ bits of the representation. Ideally, we would like to keep both s$s$ and t$t$ small, but there are tradeoffs between the values of s$s$ and t$t$ that limit the possibilities of keeping both parameters small.     

Segmentation of microscope images of living cells

This paper describes a segmentation method combining a texture based technique with a contour based method. The technique is designed to enable the study of cell behaviour over time by segmenting brightfield microscope image sequences. The technique was tested on artificial images, based on images of living cells and on real sequences acquired from microscope observations of neutrophils and lymphocytes as well as on a sequence of MRI images. The results of the segmentation are compared with the results of the watershed and snake segmentation methods. The results show that the method is both effective and practical.

From Water Poverty to Water Prosperity—A More Participatory Approach to Studying Local Water Resources Management

The Water Poverty Index (WPI), a tool designed for integrated analysis of water issues, was set-up in a community in Madhya Pradesh, India through a transparent and participatory process. Though the aim of the WPI is to primarily use existing statistical data, quantitative information from census and local records was combined with qualitative data from community interviews and participatory exercises. The inclusion of community chosen indicators and the adjustment of values so that higher numbers represent water prosperity rather than water poverty, led to the Water Prosperity Index (WPI⁺). The WPI?⁺?score was contrasted with the WPI at community level. It was also calculated for two community areas with different caste and socio-economic characteristics and weighted separately according to water issues prioritized by men and women. The WPI?⁺?revealed a great difference in water access between the two areas and in prioritized issues between men and women illustrating the importance of appropriate spatial representation and gender sensitive assessments for revealing important disparities. Results also showed that highly aggregated data hide these differences making it more difficult to target the most vulnerable groups when planning measures to increase equitable water allocation. While quantitative data reveal an important perspective of the water situation, qualitative data about adequacy of resources, services or institutions, improve understanding of which issues to prioritize. A valid and useful community water index must be based on representative participation, transparency and local influence on the methodology and subsequent results.     

Information systems for enhancing social experience in a conference context: A sensor based approach

We combine Auto Identification and Web technologies in an extensible on-site event support system for enhancing experience of conference organizers as well as participants. Our system enables users to authenticate themselves using RFID badges and to access interactive, Web-based services via a touchscreen PC. The developed services aim at supporting social interactions of participants, and thus validate the promising usage directions of the combination of offline social networks and the online social Web. The main hypothesis of our work is that: ??A sensor based information system can truly enhance social conference experience.?? Technically, we have investigated employment of Web 2.0 technologies in social, sensor and mobile technologies enabled systems at conferences and events. This article gives an overview of the overall system and its evaluation via a user survey and usage log data collected during the Extended Semantic Web Conference (ESWC) 2010 and similar international conferences, altogether with several hundred participants.     

Modeling broad-scale patterns of avian species richness across the Midwestern United States with measures of satellite image texture

Avian biodiversity is threatened, and in order to prioritize limited conservation resources and conduct effective conservation planning a better understanding of avian species richness patterns is needed. The use of image texture measures, as a proxy for the spatial structure of land cover and vegetation, has proven useful in explaining patterns of avian abundance and species richness. However, prior studies that modeled habitat with texture measures were conducted over small geographical extents and typically focused on a single habitat type. Our goal was to evaluate the performance of texture measures over broad spatial extents and across multiple habitat types with varying levels of vertical habitat structure. We calculated a suite of texture measures from 114 Landsat images over a study area of 1,498,000 km² in the Midwestern United States, which included habitats ranging from grassland to forest. Avian species richness was modeled for several functional guilds as a function of image texture. We subsequently compared the explanatory power of texture-only models with models fitted using landscape composition metrics derived from the National Land Cover Dataset, as well as models fitted using both texture and composition metrics. Measures of image texture were effective in modeling spatial patterns of avian species richness in multiple habitat types, explaining up to 51% of the variability in species richness of permanent resident birds. In comparison, landscape composition metrics explained up to 56% of the variability in permanent resident species richness. In the most heavily forested ecoregion, texture-measures outperformed landscape metrics, and the two types of measurements were complementary in multivariate models. However, in two out of three ecoregions examined, landscape composition metrics consistently performed slightly better than texture measures, and the variance explained by the two types of measures overlapped considerably. These results show that image texture measures derived from satellite imagery can be an important tool for modeling patterns of avian species richness at broad spatial extents, and thus assist in conservation planning. However, texture measures were slightly inferior to landscape composition metrics in about three-fourths of our models. Therefore texture measures are best considered in conjunction with landscape metrics (if available) and are best used when they show explanatory ability that is complementarity to landscape metrics.     

面向调度主站一体化的数据网格设计与实现

高性能电力应用致力于搭建用于调度数据的统一管理、集中处理平台。数据网格易于海量数据共享的特点使其适用于实现调度主站一体化。构建了调度主站数据网格的基本架构,利用网格软件Globus Toolkit建立网格环境,在此基础上配置数据库访问中间件OGSA-DAI来建立面向调度主站一体化的数据网格实验平台。     

Destruction of trichloroethylene (TCE) and trichloromethane (TCM) in the presence of selected VOCs over Pt-Pd-based catalyst

Catalytic oxidation of trichloroethylene (TCE) and trichloromethane (TCM) oxidized alone and in two-component mixtures with selected volatile organic compounds (VOCs) such as toluene, n-hexane, ethanol or acetone was investigated over a Pt-Pd-based catalyst on a monolithic, metallic, γ-Al₂O₃-washcoated support. TCE and TCM were more difficult to oxidize than VOCs and temperatures of their 50% conversion (T_50%) amouted to 420 and 330 °C, respectively. All the VOCs added were found to enhance the conversion of the two chlorinated compounds, drecreasing T_50% by 20 °C, at the most, for TCM in the presence of toluene and by 50 °C for TCE in the presence of acetone. Both the chlorinated compounds lowered the conversion of the VOCs added (except that of toluene), and this lowering was particularly distinct with n-heptane; they also raised the concentration of acetaldehyde formed during the oxidation of oxyderivative compounds.