Insights into the timing of repeated testing after treatment for Chlamydia trachomatis: data and modelling study

The objective of this study was to determine the optimal time interval for a repeated Chlamydia trachomatis (chlamydia) test.

Studying the Roles of Nonprofits, Government, and Business in Providing Activities and Services to Youth in the Phoenix Metropolitan Area

The article addresses the questions, What do children in urban areas do on Saturdays? What types of organizational resources do they have access to? Does this vary by social class? Using diary data on children's activities on Saturdays in the Phoenix-Mesa-Scottsdale metropolitan area, the authors describe the different types of venues (households, businesses, public space, associations, charities, congregations, and government/tribal agencies) that served different types of children. They find that the likelihood of using a charity or business rather than a government or tribal provider increased with family income. Also, the likelihood of using a congregation or a government facility rather than a business, charity, or household increased with being Hispanic. The authors discuss the implications for the urban division of labor on Saturdays and offer research questions that need further investigation.

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.

Privacy Preserving Probabilistic Record Linkage (P3RL): a novel method for linking existing health-related data and maintaining participant confidentiality.

BACKGROUND Record linkage of existing individual health care data is an efficient way to answer important epidemiological research questions. Reuse of individual health-related data faces several problems: Either a unique personal identifier, like social security number, is not available or non-unique person identifiable information, like names, are privacy protected and cannot be accessed. A solution to protect privacy in probabilistic record linkages is to encrypt these sensitive information. Unfortunately, encrypted hash codes of two names differ completely if the plain names differ only by a single character. Therefore, standard encryption methods cannot be applied. To overcome these challenges, we developed the Privacy Preserving Probabilistic Record Linkage (P3RL) method. METHODS In this Privacy Preserving Probabilistic Record Linkage method we apply a three-party protocol, with two sites collecting individual data and an independent trusted linkage center as the third partner. Our method consists of three main steps: pre-processing, encryption and probabilistic record linkage. Data pre-processing and encryption are done at the sites by local personnel. To guarantee similar quality and format of variables and identical encryption procedure at each site, the linkage center generates semi-automated pre-processing and encryption templates. To retrieve information (i.e. data structure) for the creation of templates without ever accessing plain person identifiable information, we introduced a novel method of data masking. Sensitive string variables are encrypted using Bloom filters, which enables calculation of similarity coefficients. For date variables, we developed special encryption procedures to handle the most common date errors. The linkage center performs probabilistic record linkage with encrypted person identifiable information and plain non-sensitive variables. RESULTS In this paper we describe step by step how to link existing health-related data using encryption methods to preserve privacy of persons in the study. CONCLUSION Privacy Preserving Probabilistic Record linkage expands record linkage facilities in settings where a unique identifier is unavailable and/or regulations restrict access to the non-unique person identifiable information needed to link existing health-related data sets. Automated pre-processing and encryption fully protect sensitive information ensuring participant confidentiality. This method is suitable not just for epidemiological research but also for any setting with similar challenges.

Past and future evolution of Abies alba forests in Europe - comparison of a dynamic vegetation model with palaeo data and observations

Information on how species distributions and ecosystem services are impacted by anthropogenic climate change is important for adaptation planning. Palaeo data suggest that Abies alba formed forests under significantly warmer-than-present conditions in Europe and might be a native substitute for widespread drought-sensitive temperate and boreal tree species such as beech (Fagus sylvatica) and spruce (Picea abies) under future global warming conditions. Here, we combine pollen and macrofossil data, modern observations, and results from transient simulations with the LPX-Bern dynamic global vegetation model to assess past and future distributions of A. alba in Europe. LPX-Bern is forced with climate anomalies from a run over the past 21 000 years with the Community Earth System Model, modern climatology, and with 21st-century multimodel ensemble results for the high-emission RCP8.5 and the stringent mitigation RCP2.6 pathway. The simulated distribution for present climate encompasses the modern range of A. alba, with the model exceeding the present distribution in north-western and southern Europe. Mid-Holocene pollen data and model results agree for southern Europe, suggesting that at present, human impacts suppress the distribution in southern Europe. Pollen and model results both show range expansion starting during the Bølling–Allerød warm period, interrupted by the Younger Dryas cold, and resuming during the Holocene. The distribution of A. alba expands to the north-east in all future scenarios, whereas the potential (currently unrealized) range would be substantially reduced in southern Europe under RCP8.5. A. alba maintains its current range in central Europe despite competition by other thermophilous tree species. Our combined palaeoecological and model evidence suggest that A. alba may ensure important ecosystem services including stand and slope stability, infrastructure protection, and carbon sequestration under significantly warmer-than-present conditions in central Europe.

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

FIWARE Lab: managing resources and services in a cloud federation supporting future internet applications

Real-world experimentation facilities accelerate the development of Future Internet technologies and services, advance the market for smart infrastructures, and increase the effectiveness of business processes through the Internet. The federation of facilities fosters the experimentation and innovation with larger and more powerful environment, increases the number and variety of the offered services and brings forth possibilities for new experimentation scenarios. This paper introduces a management solution for cloud federation that automates service provisioning to the largest possible extent, relieves the developers from time-consuming configuration settings, and caters for real-time information of all information related to the whole lifecycle of the provisioned services. This is achieved by proposing solutions to achieve the seamless deployment of services across the federation and ability of services to span across different infrastructures of the federation, as well as monitoring of the resources and data which can be aggregated with a common structure, offered as an open ecosystem for innovation at the developers' disposal. This solution consists of several federation management tools and components that are part of the work on Cloud Federation conducted within XIFI project to build the federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab). We present the design and implementation of the solution-concerned FIWARE Lab management tools and components that are deployed within a federation of 17 cloud infrastructures distributed across Europe.

Mutual Recognition: economic and regulatory logic in goods and services. Bruges European Economic Research (BEER) Papers 24/June 2012

Mutual recognition is one of the most appreciated innovations of the EU. The idea is that one can pursue market integration, indeed "deep' market integration, while respecting 'diversity' amongst the participating countries. Put differently, in pursuing 'free movement' for goods, mutual recognition facilitates free movement by disciplining the nature and scope of 'regulatory barriers', whilst allowing some degree of regulatory discretion for EU Member States. This BEER paper attempts to explain the rationale and logic of mutual recognition in the EU internal goods market, its working in actual practice for about three decades now, culminating in a qualitative cost/benefit analysis and its recent improvement in terms of 'governance' in the so-called New Legislative Framework (first denoted as the 2008 Goods package) thereby ameliorating the benefits/costs ratio. For new (in contrast to existing) national regulation, the intrusive EU procedure to impose mutual recognition is presented as well, with basic data so as to show its critical importance to keep the internal goods market free. All this is complemented by a short summary of the scant economic literature on mutual recognition. Subsequently, the analysis is extended to the internal market for services. This is done in two steps, first by reminding the debate on the origin principle (which goes further than mutual recognition EU-style) and how mutual recognition works under the horizontal services directive. This is followed by a short section on how mutual recognition works in vertical (i.e. sectoral) services markets.

Exploring complementarities between goods and services trade in trade agreements

More than three decades of research on trade costs and goods trade have unveiled fundamental insights into the determinants, the nature and the consequences of goods trade agreements. A cottage literature has also evolved studying similar issues from a services trade perspective, but the two-way interaction between goods and services trade has not been explored formally. We bridge this gap by providing a formal treatment of the inter-linkages between goods and services trade. The model provides insights into how trade agreements impact goods and services trade. We also explore the impact of the complementarities of goods and services agreements on goods and services trade empirically using bilateral goods and services trade data for OECD and BRICS trading partners over 1995-2010.

A Competitive assessment of the United States data processing services industry.

Item 231-B-1

Transportation statistical data and information. Final report.

Transportation Department, Office of Transportation Systems Analysis and Information, Washington, D.C.

Hidden treasures! : Census Bureau data and where to find it!

Mode of access: Internet.