How to Create an Innovation Accelerator

Too many policy failures are fundamentally failures of knowledge. This has become particularly apparent during the recent financial and economic crisis, which is questioning the validity of mainstream scholarly paradigms. We propose to pursue a multi-disciplinary approach and to establish new institutional settings which remove or reduce obstacles impeding efficient knowledge creation. We provided suggestions on (i) how to modernize and improve the academic publication system, and (ii) how to support scientific coordination, communication, and co-creation in large-scale multi-disciplinary projects. Both constitute important elements of what we envision to be a novel ICT infrastructure called "Innovation Accelerator" or "Knowledge Accelerator".Comment: 32 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Medical Informatics

Information technology has been revolutionizing the everyday life of the common man, while medical science has been making rapid strides in understanding disease mechanisms, developing diagnostic techniques and effecting successful treatment regimen, even for those cases which would have been classified as a poor prognosis a decade earlier. The confluence of information technology and biomedicine has brought into its ambit additional dimensions of computerized databases for patient conditions, revolutionizing the way health care and patient information is recorded, processed, interpreted and utilized for improving the quality of life. This book consists of seven chapters dealing with the three primary issues of medical information acquisition from a patient's and health care professional's perspective, translational approaches from a researcher's point of view, and finally the application potential as required by the clinicians/physician. The book covers modern issues in Information Technology, Bioinformatics Methods and Clinical Applications. The chapters describe the basic process of acquisition of information in a health system, recent technological developments in biomedicine and the realistic evaluation of medical informatics

Development and application of the dynamic system doctor to nuclear reactor probabilistic risk assessments.

This LDRD project has produced a tool that makes probabilistic risk assessments (PRAs) of nuclear reactors - analyses which are very resource intensive - more efficient. PRAs of nuclear reactors are being increasingly relied on by the United States Nuclear Regulatory Commission (U.S.N.R.C.) for licensing decisions for current and advanced reactors. Yet, PRAs are produced much as they were 20 years ago. The work here applied a modern systems analysis technique to the accident progression analysis portion of the PRA; the technique was a system-independent multi-task computer driver routine. Initially, the objective of the work was to fuse the accident progression event tree (APET) portion of a PRA to the dynamic system doctor (DSD) created by Ohio State University. Instead, during the initial efforts, it was found that the DSD could be linked directly to a detailed accident progression phenomenological simulation code - the type on which APET construction and analysis relies, albeit indirectly - and thereby directly create and analyze the APET. The expanded DSD computational architecture and infrastructure that was created during this effort is called ADAPT (Analysis of Dynamic Accident Progression Trees). ADAPT is a system software infrastructure that supports execution and analysis of multiple dynamic event-tree simulations on distributed environments. A simulator abstraction layer was developed, and a generic driver was implemented for executing simulators on a distributed environment. As a demonstration of the use of the methodological tool, ADAPT was applied to quantify the likelihood of competing accident progression pathways occurring for a particular accident scenario in a particular reactor type using MELCOR, an integrated severe accident analysis code developed at Sandia. (ADAPT was intentionally created with flexibility, however, and is not limited to interacting with only one code. With minor coding changes to input files, ADAPT can be linked to other such codes.) The results of this demonstration indicate that the approach can significantly reduce the resources required for Level 2 PRAs. From the phenomenological viewpoint, ADAPT can also treat the associated epistemic and aleatory uncertainties. This methodology can also be used for analyses of other complex systems. Any complex system can be analyzed using ADAPT if the workings of that system can be displayed as an event tree, there is a computer code that simulates how those events could progress, and that simulator code has switches to turn on and off system events, phenomena, etc. Using and applying ADAPT to particular problems is not human independent. While the human resources for the creation and analysis of the accident progression are significantly decreased, knowledgeable analysts are still necessary for a given project to apply ADAPT successfully. This research and development effort has met its original goals and then exceeded them

Updates in metabolomics tools and resources: 2014-2015

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources—in the form of tools, software, and databases—is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

2018 Annual Research Symposium Abstract Book

2018 annual volume of abstracts for science research projects conducted by students at Trinity College

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project) and from the European Unions Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1)

How to create an innovation accelerator

Abstract.: The purpose of this White Paper of the EU Support Action "Visioneer” (see www.visioneer.ethz.ch) is to address the following goals: 1. Identify new ways of publishing, evaluating, and reporting scientific progress. 2. Promote ICT solutions to increase the awareness of new emerging trends. 3. Invent tools to enhance Europe's innovation potential. 4. Develop new strategies to support a sustainable technological development. 5. Lay the foundations for new ways to reach societal benefits and respond to industrial needs using IC