Integrating open-source technologies to build low-cost information systems for improved access to public health data

Effective public health practice relies on the availability of public health data sources and assessment tools to convey information to investigators, practitioners, policy makers, and the general public. Emerging communication technologies on the Internet can deliver all components of the "who, what, when, and where" quartet more quickly than ever with a potentially higher level of quality and assurance, using new analysis and visualization tools. Open-source software provides the opportunity to build low-cost information systems allowing health departments with modest resources access to modern data analysis and visualization tools. In this paper, we integrate open-source technologies and public health data to create a web information system which is accessible to a wide audience through the Internet. Our web application, "EpiVue," was tested using two public health datasets from the Washington State Cancer Registry and Washington State Center for Health Statistics. A third dataset shows the extensibility and scalability of EpiVue in displaying gender-based longevity statistics over a twenty-year interval for 3,143 United States counties. In addition to providing an integrated visualization framework, EpiVue's highly interactive web environment empowers users by allowing them to upload their own geospatial public health data in either comma-separated text files or MS Excel™ spreadsheet files and visualize the geospatial datasets with Google Maps™

An architectural journey into RISC architectures for HPC workloads

The thesis evaluates the current state-of-the-art of RISC architectures in HPC. Studying the performance, power, and energy to solution in heterogeneous SoCs. For the evaluation 2 arm platforms (CPU+GPU, CPU+FPGA), 1 RISC-V platform and 1 Open Source RISC-V core running in an FPGA have been tested

The Ocean Observatories Initiative

Author Posting. © The Oceanography Society, 2018. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 31, no. 1 (2018): 16–35, doi:10.5670/oceanog.2018.105.The Ocean Observatories Initiative (OOI) is an integrated suite of instrumented platforms and discrete instruments that measure physical, chemical, geological, and biological properties from the seafloor to the sea surface. The OOI provides data to address large-scale scientific challenges such as coastal ocean dynamics, climate and ecosystem health, the global carbon cycle, and linkages among seafloor volcanism and life. The OOI Cyberinfrastructure currently serves over 250 terabytes of data from the arrays. These data are freely available to users worldwide, changing the way scientists and the broader community interact with the ocean, and permitting ocean research and inquiry at scales of centimeters to kilometers and seconds to decades.Funding for the OOI is provided by the National Science Foundation through a Cooperative Support Agreement with the Consortium for Ocean Leadership (OCE-1026342)

A Guide to the implementation of the National Electronic Disease Surveillance System (NEDSS) in state public health

''This document is targeted to program managers and surveillance staff in state health agencies who are involved in the implementation of the National Electronic Disease Surveillance System (NEDSS). The target audience includes epidemiologists and other professional staff with varying degrees of computer knowledge and skills. The goals of the document are: A. To present the basic principles of the NEDSS architecture and how they affect state-based surveillance systems; B. To assist state surveillance programs in deciding how to implement the NEDSS architecture; C. To discuss some current issues related to the NEDSS implementation'' - p. iiExecutive Summary -- Acknowledgments -- I. Objectives -- II. NEDSS and the NEDSS architecture -- III. NEDSS implementation options for state programs -- IV. Fitting NEDSS into a state plan: resources and other issues -- FAQs -- Glossary of Terms and list of Acronymsedited by Gianfranco Pezzino.Title from PDF t.p. (387 KB, 32 p).Handout at the 2nd National NEDSS Stateholders' Meeting, April 10-11, 2001, Atlanta, Georgia."This document was prepared by CSTE members and staff, with substantial input from CDC staff from the National Electronic Disease Surveillance System project. The primary target audience includes program managers and surveillance staff in state health agencies who are involved with collecting, processing, and analyzing information in electronic format and who need to learn more about the NEDSS concepts and implementation process. The target audience includes primarily epidemiologists and other professional staff with various degrees of computer knowledge and skills. Staff with more technical functions (e.g., computer specialists and programmers) may find the document helpful to understand the purpose of NEDSS, but this is not meant to be a comprehensive technical guidance document." - p. 1Mode of access: Internet.Includes bibliographical references

Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders

Chemical autoencoders are attractive models as they combine chemical space navigation with possibilities for de-novo molecule generation in areas of interest. This enables them to produce focused chemical libraries around a single lead compound for employment early in a drug discovery project. Here it is shown that the choice of chemical representation, such as SMILES strings, has a large influence on the properties of the latent space. It is further explored to what extent translating between different chemical representations influences the latent space similarity to the SMILES strings or circular fingerprints. By employing SMILES enumeration for either the encoder or decoder, it is found that the decoder has the largest influence on the properties of the latent space. Training a sequence to sequence heteroencoder based on recurrent neural networks(RNNs) with long short-term memory cells (LSTM) to predict different enumerated SMILES strings from the same canonical SMILES string gives the largest similarity between latent space distance and molecular similarity measured as circular fingerprints similarity. Using the output from the bottleneck in QSAR modelling of five molecular datasets shows that heteroencoder derived vectors markedly outperforms autoencoder derived vectors as well as models built using ECFP4 fingerprints, underlining the increased chemical relevance of the latent space. However, the use of enumeration during training of the decoder leads to a markedly increase in the rate of decoding to a different molecules than encoded, a tendency that can be counteracted with more complex network architectures

Architecture and the Built Environment:

This publication provides an overview of TU Delft’s most significant research achievements in the field of architecture and the built environment during the years 2010–2012. It is the first presentation of the joint research portfolio of the Faculty of Architecture and OTB Research Institute since their integration into the Faculty of Architecture and the Built Environment. As such the portfolio holds a strong promise for the future. In a time when the economy seems to be finally picking up and in which such societal issues as energy, climate and ageing are more prominent than ever before, there are plenty of fields for us to explore in the next three years