Multi-modal spectroscopic imaging with synchrotron light to study mechanisms of brain disease

NASA Astrophysics Data System (ADS)

Summers, Kelly L.; Fimognari, Nicholas; Hollings, Ashley; Kiernan, Mitchell; Lam, Virginie; Tidy, Rebecca J.; Takechi, Ryu; George, Graham N.; Pickering, Ingrid J.; Mamo, John C.; Harris, Hugh H.; Hackett, Mark J.

2017-04-01

The international health care costs associated with Alzheimer's disease (AD) and dementia have been predicted to reach $2 trillion USD by 2030. As such, there is urgent need to develop new treatments and diagnostic methods to stem an international health crisis. A major limitation to therapy and diagnostic development is the lack of complete understanding about the disease mechanisms. Spectroscopic methods at synchrotron light sources, such as FTIR, XRF, and XAS, offer a "multi-modal imaging platform" to reveal a wealth of important biochemical information in situ within ex vivo tissue sections, to increase our understanding of disease mechanisms.

Web accessibility and open source software.

PubMed

Obrenović, Zeljko

2009-07-01

A Web browser provides a uniform user interface to different types of information. Making this interface universally accessible and more interactive is a long-term goal still far from being achieved. Universally accessible browsers require novel interaction modalities and additional functionalities, for which existing browsers tend to provide only partial solutions. Although functionality for Web accessibility can be found as open source and free software components, their reuse and integration is complex because they were developed in diverse implementation environments, following standards and conventions incompatible with the Web. To address these problems, we have started several activities that aim at exploiting the potential of open-source software for Web accessibility. The first of these activities is the development of Adaptable Multi-Interface COmmunicator (AMICO):WEB, an infrastructure that facilitates efficient reuse and integration of open source software components into the Web environment. The main contribution of AMICO:WEB is in enabling the syntactic and semantic interoperability between Web extension mechanisms and a variety of integration mechanisms used by open source and free software components. Its design is based on our experiences in solving practical problems where we have used open source components to improve accessibility of rich media Web applications. The second of our activities involves improving education, where we have used our platform to teach students how to build advanced accessibility solutions from diverse open-source software. We are also partially involved in the recently started Eclipse projects called Accessibility Tools Framework (ACTF), the aim of which is development of extensible infrastructure, upon which developers can build a variety of utilities that help to evaluate and enhance the accessibility of applications and content for people with disabilities. In this article we briefly report on these activities.

MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

NASA Astrophysics Data System (ADS)

Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

2017-06-01

Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

PubMed

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

The Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes

PubMed Central

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit – a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/ PMID:21713110

Mashup Scheme Design of Map Tiles Using Lightweight Open Source Webgis Platform

NASA Astrophysics Data System (ADS)

Hu, T.; Fan, J.; He, H.; Qin, L.; Li, G.

2018-04-01

To address the difficulty involved when using existing commercial Geographic Information System platforms to integrate multi-source image data fusion, this research proposes the loading of multi-source local tile data based on CesiumJS and examines the tile data organization mechanisms and spatial reference differences of the CesiumJS platform, as well as various tile data sources, such as Google maps, Map World, and Bing maps. Two types of tile data loading schemes have been designed for the mashup of tiles, the single data source loading scheme and the multi-data source loading scheme. The multi-sources of digital map tiles used in this paper cover two different but mainstream spatial references, the WGS84 coordinate system and the Web Mercator coordinate system. According to the experimental results, the single data source loading scheme and the multi-data source loading scheme with the same spatial coordinate system showed favorable visualization effects; however, the multi-data source loading scheme was prone to lead to tile image deformation when loading multi-source tile data with different spatial references. The resulting method provides a low cost and highly flexible solution for small and medium-scale GIS programs and has a certain potential for practical application values. The problem of deformation during the transition of different spatial references is an important topic for further research.

Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

PubMed Central

Joshi, Alark; Scheinost, Dustin; Okuda, Hirohito; Belhachemi, Dominique; Murphy, Isabella; Staib, Lawrence H.; Papademetris, Xenophon

2011-01-01

Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software—BioImage Suite (bioimagesuite.org). PMID:21249532

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets

PubMed Central

2010-01-01

Background Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. Results We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. Conclusions The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics. PMID:20064262

A novel low-cost open-hardware platform for monitoring soil water content and multiple soil-air-vegetation parameters.

PubMed

Bitella, Giovanni; Rossi, Roberta; Bochicchio, Rocco; Perniola, Michele; Amato, Mariana

2014-10-21

Monitoring soil water content at high spatio-temporal resolution and coupled to other sensor data is crucial for applications oriented towards water sustainability in agriculture, such as precision irrigation or phenotyping root traits for drought tolerance. The cost of instrumentation, however, limits measurement frequency and number of sensors. The objective of this work was to design a low cost "open hardware" platform for multi-sensor measurements including water content at different depths, air and soil temperatures. The system is based on an open-source ARDUINO microcontroller-board, programmed in a simple integrated development environment (IDE). Low cost high-frequency dielectric probes were used in the platform and lab tested on three non-saline soils (ECe1: 2.5 < 0.1 mS/cm). Empirical calibration curves were subjected to cross-validation (leave-one-out method), and normalized root mean square error (NRMSE) were respectively 0.09 for the overall model, 0.09 for the sandy soil, 0.07 for the clay loam and 0.08 for the sandy loam. The overall model (pooled soil data) fitted the data very well (R2 = 0.89) showing a high stability, being able to generate very similar RMSEs during training and validation (RMSE(training) = 2.63; RMSE(validation) = 2.61). Data recorded on the card were automatically sent to a remote server allowing repeated field-data quality checks. This work provides a framework for the replication and upgrading of a customized low cost platform, consistent with the open source approach whereby sharing information on equipment design and software facilitates the adoption and continuous improvement of existing technologies.

A Novel Low-Cost Open-Hardware Platform for Monitoring Soil Water Content and Multiple Soil-Air-Vegetation Parameters

PubMed Central

Bitella, Giovanni; Rossi, Roberta; Bochicchio, Rocco; Perniola, Michele; Amato, Mariana

2014-01-01

Monitoring soil water content at high spatio-temporal resolution and coupled to other sensor data is crucial for applications oriented towards water sustainability in agriculture, such as precision irrigation or phenotyping root traits for drought tolerance. The cost of instrumentation, however, limits measurement frequency and number of sensors. The objective of this work was to design a low cost “open hardware” platform for multi-sensor measurements including water content at different depths, air and soil temperatures. The system is based on an open-source ARDUINO microcontroller-board, programmed in a simple integrated development environment (IDE). Low cost high-frequency dielectric probes were used in the platform and lab tested on three non-saline soils (ECe1: 2.5 < 0.1 mS/cm). Empirical calibration curves were subjected to cross-validation (leave-one-out method), and normalized root mean square error (NRMSE) were respectively 0.09 for the overall model, 0.09 for the sandy soil, 0.07 for the clay loam and 0.08 for the sandy loam. The overall model (pooled soil data) fitted the data very well (R2 = 0.89) showing a high stability, being able to generate very similar RMSEs during training and validation (RMSEtraining = 2.63; RMSEvalidation = 2.61). Data recorded on the card were automatically sent to a remote server allowing repeated field-data quality checks. This work provides a framework for the replication and upgrading of a customized low cost platform, consistent with the open source approach whereby sharing information on equipment design and software facilitates the adoption and continuous improvement of existing technologies. PMID:25337742

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

OpenSesame: an open-source, graphical experiment builder for the social sciences.

PubMed

Mathôt, Sebastiaan; Schreij, Daniel; Theeuwes, Jan

2012-06-01

In the present article, we introduce OpenSesame, a graphical experiment builder for the social sciences. OpenSesame is free, open-source, and cross-platform. It features a comprehensive and intuitive graphical user interface and supports Python scripting for complex tasks. Additional functionality, such as support for eyetrackers, input devices, and video playback, is available through plug-ins. OpenSesame can be used in combination with existing software for creating experiments.

Implementation of a near-real time cross-border web-mapping platform on airborne particulate matter (PM) concentration with open-source software

NASA Astrophysics Data System (ADS)

Knörchen, Achim; Ketzler, Gunnar; Schneider, Christoph

2015-01-01

Although Europe has been growing together for the past decades, cross-border information platforms on environmental issues are still scarce. With regard to the establishment of a web-mapping tool on airborne particulate matter (PM) concentration for the Euregio Meuse-Rhine located in the border region of Belgium, Germany and the Netherlands, this article describes the research on methodical and technical backgrounds implementing such a platform. An open-source solution was selected for presenting the data in a Web GIS (OpenLayers/GeoExt; both JavaScript-based), applying other free tools for data handling (Python), data management (PostgreSQL), geo-statistical modelling (Octave), geoprocessing (GRASS GIS/GDAL) and web mapping (MapServer). The multilingual, made-to-order online platform provides access to near-real time data on PM concentration as well as additional background information. In an open data section, commented configuration files for the Web GIS client are being made available for download. Furthermore, all geodata generated by the project is being published under public domain and can be retrieved in various formats or integrated into Desktop GIS as Web Map Services (WMS).

McIDAS-V: Data Analysis and Visualization for NPOESS and GOES-R

NASA Astrophysics Data System (ADS)

Rink, T.; Achtor, T. H.

2009-12-01

McIDAS-V, the next-generation McIDAS, is being built on top a modern, cross-platform software framework which supports development of 4-D, interactive displays and integration of wide-array of geophysical data. As the replacement of McIDAS, the development emphasis is on future satellite observation platforms such as NPOESS and GOES-R. Data interrogation, analysis and visualization capabilities have been developed for multi- and hyper-spectral instruments like MODIS, AIRS and IASI, and are being extended for application to VIIRS and CrIS. Compatibility with GOES-R ABI level1 and level2 product storage formats has been demonstrated. The abstract data model, which can internalize most any geophysical data, opens up new possibilities for data fusion techniques, for example, polar and geostationary, (LEO/GEO), synergy for research and validation. McIDAS-V follows an object-oriented design model, using the Java programming language, allowing specialized extensions for for new sources of data, and novel displays and interactive behavior. The reference application, what the user sees on startup, can be customized, and the system has a persistence mechanism allowing sharing of the application state across the internet. McIDAS-V is open-source, and free to the public.

MEA-Tools: an open source toolbox for the analysis of multi-electrode data with MATLAB.

PubMed

Egert, U; Knott, Th; Schwarz, C; Nawrot, M; Brandt, A; Rotter, S; Diesmann, M

2002-05-30

Recent advances in electrophysiological techniques have created new tools for the acquisition and storage of neuronal activity recorded simultaneously with numerous electrodes. These techniques support the analysis of the function as well as the structure of individual electrogenic cells in the context of surrounding neuronal or cardiac network. Commercially available tools for the analysis of such data, however, cannot be easily adapted to newly emerging requirements for data analysis and visualization, and cross compatibility between them is limited. In this report we introduce a free open source toolbox called microelectrode array tools (MEA-Tools) for the analysis of multi-electrode data based on the common data analysis environment MATLAB (version 5.3-6.1, The Mathworks, Natick, MA). The toolbox itself is platform independent. The file interface currently supports files recorded with MCRack (Multi Channel Systems, Reutlingen, Germany) under Microsoft Windows 95, 98, NT, and 2000, but can be adapted to other data acquisition systems. Functions are controlled via command line input and graphical user interfaces, and support common requirements for the analysis of local field potentials, extracellular spike activity, and continuous recordings, in addition to supplementary data acquired by additional instruments, e.g. intracellular amplifiers. Data may be processed as continuous recordings or time windows triggered to some event.

A multi-purpose open-source triggering platform for magnetic resonance

NASA Astrophysics Data System (ADS)

Ruytenberg, T.; Webb, A. G.; Beenakker, J. W. M.

2014-10-01

Many MR scans need to be synchronised with external events such as the cardiac or respiratory cycles. For common physiological functions commercial trigger equipment exists, but for more experimental inputs these are not available. This paper describes the design of a multi-purpose open-source trigger platform for MR systems. The heart of the system is an open-source Arduino Due microcontroller. This microcontroller samples an analogue input and digitally processes these data to determine the trigger. The output of the microcontroller is programmed to mimic a physiological signal which is fed into the electrocardiogram (ECG) or pulse oximeter port of MR scanner. The microcontroller is connected to a Bluetooth dongle that allows wireless monitoring and control outside the scanner room. This device can be programmed to generate a trigger based on various types of input. As one example, this paper describes how it can be used as an acoustic cardiac triggering unit. For this, a plastic stethoscope is connected to a microphone which is used as an input for the system. This test setup was used to acquire retrospectively-triggered cardiac scans in ten volunteers. Analysis showed that this platform produces a reliable trigger (>99% triggers are correct) with a small average 8 ms variation between the exact trigger points.

A multi-purpose open-source triggering platform for magnetic resonance.

PubMed

Ruytenberg, T; Webb, A G; Beenakker, J W M

2014-10-01

Many MR scans need to be synchronised with external events such as the cardiac or respiratory cycles. For common physiological functions commercial trigger equipment exists, but for more experimental inputs these are not available. This paper describes the design of a multi-purpose open-source trigger platform for MR systems. The heart of the system is an open-source Arduino Due microcontroller. This microcontroller samples an analogue input and digitally processes these data to determine the trigger. The output of the microcontroller is programmed to mimic a physiological signal which is fed into the electrocardiogram (ECG) or pulse oximeter port of MR scanner. The microcontroller is connected to a Bluetooth dongle that allows wireless monitoring and control outside the scanner room. This device can be programmed to generate a trigger based on various types of input. As one example, this paper describes how it can be used as an acoustic cardiac triggering unit. For this, a plastic stethoscope is connected to a microphone which is used as an input for the system. This test setup was used to acquire retrospectively-triggered cardiac scans in ten volunteers. Analysis showed that this platform produces a reliable trigger (>99% triggers are correct) with a small average 8 ms variation between the exact trigger points. Copyright © 2014 Elsevier Inc. All rights reserved.

GeolOkit 1.0: a new Open Source, Cross-Platform software for geological data visualization in Google Earth environment

NASA Astrophysics Data System (ADS)

Triantafyllou, Antoine; Bastin, Christophe; Watlet, Arnaud

2016-04-01

GIS software suites are today's essential tools to gather and visualise geological data, to apply spatial and temporal analysis and in fine, to create and share interactive maps for further geosciences' investigations. For these purposes, we developed GeolOkit: an open-source, freeware and lightweight software, written in Python, a high-level, cross-platform programming language. GeolOkit software is accessible through a graphical user interface, designed to run in parallel with Google Earth. It is a super user-friendly toolbox that allows 'geo-users' to import their raw data (e.g. GPS, sample locations, structural data, field pictures, maps), to use fast data analysis tools and to plot these one into Google Earth environment using KML code. This workflow requires no need of any third party software, except Google Earth itself. GeolOkit comes with large number of geosciences' labels, symbols, colours and placemarks and may process : (i) multi-points data, (ii) contours via several interpolations methods, (iii) discrete planar and linear structural data in 2D or 3D supporting large range of structures input format, (iv) clustered stereonets and rose diagram, (v) drawn cross-sections as vertical sections, (vi) georeferenced maps and vectors, (vii) field pictures using either geo-tracking metadata from a camera built-in GPS module, or the same-day track of an external GPS. We are looking for you to discover all the functionalities of GeolOkit software. As this project is under development, we are definitely looking to discussions regarding your proper needs, your ideas and contributions to GeolOkit project.

Electrophysiological signal analysis and visualization using Cloudwave for epilepsy clinical research.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Electrophysiological data recordings, such as electroencephalogram (EEG), are the gold standard for diagnosis and pre-surgical evaluation in epilepsy patients. The increasing trend towards multi-center clinical studies require signal visualization and analysis tools to support real time interaction with signal data in a collaborative environment, which cannot be supported by traditional desktop-based standalone applications. As part of the Prevention and Risk Identification of SUDEP Mortality (PRISM) project, we have developed a Web-based electrophysiology data visualization and analysis platform called Cloudwave using highly scalable open source cloud computing infrastructure. Cloudwave is integrated with the PRISM patient cohort identification tool called MEDCIS (Multi-modality Epilepsy Data Capture and Integration System). The Epilepsy and Seizure Ontology (EpSO) underpins both Cloudwave and MEDCIS to support query composition and result retrieval. Cloudwave is being used by clinicians and research staff at the University Hospital - Case Medical Center (UH-CMC) Epilepsy Monitoring Unit (EMU) and will be progressively deployed at four EMUs in the United States and the United Kingdomas part of the PRISM project.

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

XML-based scripting of multimodality image presentations in multidisciplinary clinical conferences

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Allada, Vivekanand; Dahlbom, Magdalena; Marcus, Phillip; Fine, Ian; Lapstra, Lorelle

2002-05-01

We developed a multi-modality image presentation software for display and analysis of images and related data from different imaging modalities. The software is part of a cardiac image review and presentation platform that supports integration of digital images and data from digital and analog media such as videotapes, analog x-ray films and 35 mm cine films. The software supports standard DICOM image files as well as AVI and PDF data formats. The system is integrated in a digital conferencing room that includes projections of digital and analog sources, remote videoconferencing capabilities, and an electronic whiteboard. The goal of this pilot project is to: 1) develop a new paradigm for image and data management for presentation in a clinically meaningful sequence adapted to case-specific scenarios, 2) design and implement a multi-modality review and conferencing workstation using component technology and customizable 'plug-in' architecture to support complex review and diagnostic tasks applicable to all cardiac imaging modalities and 3) develop an XML-based scripting model of image and data presentation for clinical review and decision making during routine clinical tasks and multidisciplinary clinical conferences.

Collaboration Modality, Cognitive Load, and Science Inquiry Learning in Virtual Inquiry Environments

ERIC Educational Resources Information Center

Erlandson, Benjamin E.; Nelson, Brian C.; Savenye, Wilhelmina C.

2010-01-01

Educational multi-user virtual environments (MUVEs) have been shown to be effective platforms for situated science inquiry curricula. While researchers find MUVEs to be supportive of collaborative scientific inquiry processes, the complex mix of multi-modal messages present in MUVEs can lead to cognitive overload, with learners unable to…

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

PR-PR: Cross-Platform Laboratory Automation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linshiz, G; Stawski, N; Goyal, G

To enable protocol standardization, sharing, and efficient implementation across laboratory automation platforms, we have further developed the PR-PR open-source high-level biology-friendly robot programming language as a cross-platform laboratory automation system. Beyond liquid-handling robotics, PR-PR now supports microfluidic and microscopy platforms, as well as protocol translation into human languages, such as English. While the same set of basic PR-PR commands and features are available for each supported platform, the underlying optimization and translation modules vary from platform to platform. Here, we describe these further developments to PR-PR, and demonstrate the experimental implementation and validation of PR-PR protocols for combinatorial modified Goldenmore » Gate DNA assembly across liquid-handling robotic, microfluidic, and manual platforms. To further test PR-PR cross-platform performance, we then implement and assess PR-PR protocols for Kunkel DNA mutagenesis and hierarchical Gibson DNA assembly for microfluidic and manual platforms.« less

PR-PR: cross-platform laboratory automation system.

PubMed

Linshiz, Gregory; Stawski, Nina; Goyal, Garima; Bi, Changhao; Poust, Sean; Sharma, Monica; Mutalik, Vivek; Keasling, Jay D; Hillson, Nathan J

2014-08-15

To enable protocol standardization, sharing, and efficient implementation across laboratory automation platforms, we have further developed the PR-PR open-source high-level biology-friendly robot programming language as a cross-platform laboratory automation system. Beyond liquid-handling robotics, PR-PR now supports microfluidic and microscopy platforms, as well as protocol translation into human languages, such as English. While the same set of basic PR-PR commands and features are available for each supported platform, the underlying optimization and translation modules vary from platform to platform. Here, we describe these further developments to PR-PR, and demonstrate the experimental implementation and validation of PR-PR protocols for combinatorial modified Golden Gate DNA assembly across liquid-handling robotic, microfluidic, and manual platforms. To further test PR-PR cross-platform performance, we then implement and assess PR-PR protocols for Kunkel DNA mutagenesis and hierarchical Gibson DNA assembly for microfluidic and manual platforms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apte, A; Veeraraghavan, H; Oh, J

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features andmore » (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.« less

OpenFLUID: an open-source software environment for modelling fluxes in landscapes

NASA Astrophysics Data System (ADS)

Fabre, Jean-Christophe; Rabotin, Michaël; Crevoisier, David; Libres, Aline; Dagès, Cécile; Moussa, Roger; Lagacherie, Philippe; Raclot, Damien; Voltz, Marc

2013-04-01

Integrative landscape functioning has become a common concept in environmental management. Landscapes are complex systems where many processes interact in time and space. In agro-ecosystems, these processes are mainly physical processes, including hydrological-processes, biological processes and human activities. Modelling such systems requires an interdisciplinary approach, coupling models coming from different disciplines, developed by different teams. In order to support collaborative works, involving many models coupled in time and space for integrative simulations, an open software modelling platform is a relevant answer. OpenFLUID is an open source software platform for modelling landscape functioning, mainly focused on spatial fluxes. It provides an advanced object-oriented architecture allowing to i) couple models developed de novo or from existing source code, and which are dynamically plugged to the platform, ii) represent landscapes as hierarchical graphs, taking into account multi-scale, spatial heterogeneities and landscape objects connectivity, iii) run and explore simulations in many ways : using the OpenFLUID software interfaces for users (command line interface, graphical user interface), or using external applications such as GNU R through the provided ROpenFLUID package. OpenFLUID is developed in C++ and relies on open source libraries only (Boost, libXML2, GLib/GTK, OGR/GDAL, …). For modelers and developers, OpenFLUID provides a dedicated environment for model development, which is based on an open source toolchain, including the Eclipse editor, the GCC compiler and the CMake build system. OpenFLUID is distributed under the GPLv3 open source license, with a special exception allowing to plug existing models licensed under any license. It is clearly in the spirit of sharing knowledge and favouring collaboration in a community of modelers. OpenFLUID has been involved in many research applications, such as modelling of hydrological network transfer, diagnosis and prediction of water quality taking into account human activities, study of the effect of spatial organization on hydrological fluxes, modelling of surface-subsurface water exchanges, … At LISAH research unit, OpenFLUID is the supporting development platform of the MHYDAS model, which is a distributed model for agrosystems (Moussa et al., 2002, Hydrological Processes, 16, 393-412). OpenFLUID web site : http://www.openfluid-project.org

Tools to Analyze Morphology and Spatially Mapped Molecular Data | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This project is to develop, deploy, and disseminate a suite of open source tools and integrated informatics platform that will facilitate multi-scale, correlative analyses of high resolution whole slide tissue image data, spatially mapped genetics and molecular data for cancer research. This platform will play an essential role in supporting studies of tumor initiation, development, heterogeneity, invasion, and metastasis.

Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

PubMed Central

2015-01-01

Efficiently and accurately analyzing big protein tandem mass spectrometry data sets requires robust software that incorporates state-of-the-art computational, machine learning, and statistical methods. The Crux mass spectrometry analysis software toolkit (http://cruxtoolkit.sourceforge.net) is an open source project that aims to provide users with a cross-platform suite of analysis tools for interpreting protein mass spectrometry data. PMID:25182276

Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

PubMed

Röst, Hannes L; Sachsenberg, Timo; Aiche, Stephan; Bielow, Chris; Weisser, Hendrik; Aicheler, Fabian; Andreotti, Sandro; Ehrlich, Hans-Christian; Gutenbrunner, Petra; Kenar, Erhan; Liang, Xiao; Nahnsen, Sven; Nilse, Lars; Pfeuffer, Julianus; Rosenberger, George; Rurik, Marc; Schmitt, Uwe; Veit, Johannes; Walzer, Mathias; Wojnar, David; Wolski, Witold E; Schilling, Oliver; Choudhary, Jyoti S; Malmström, Lars; Aebersold, Ruedi; Reinert, Knut; Kohlbacher, Oliver

2016-08-30

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.

ProteoCloud: a full-featured open source proteomics cloud computing pipeline.

PubMed

Muth, Thilo; Peters, Julian; Blackburn, Jonathan; Rapp, Erdmann; Martens, Lennart

2013-08-02

We here present the ProteoCloud pipeline, a freely available, full-featured cloud-based platform to perform computationally intensive, exhaustive searches in a cloud environment using five different peptide identification algorithms. ProteoCloud is entirely open source, and is built around an easy to use and cross-platform software client with a rich graphical user interface. This client allows full control of the number of cloud instances to initiate and of the spectra to assign for identification. It also enables the user to track progress, and to visualize and interpret the results in detail. Source code, binaries and documentation are all available at http://proteocloud.googlecode.com. Copyright © 2012 Elsevier B.V. All rights reserved.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

OpenCFU, a new free and open-source software to count cell colonies and other circular objects.

PubMed

Geissmann, Quentin

2013-01-01

Counting circular objects such as cell colonies is an important source of information for biologists. Although this task is often time-consuming and subjective, it is still predominantly performed manually. The aim of the present work is to provide a new tool to enumerate circular objects from digital pictures and video streams. Here, I demonstrate that the created program, OpenCFU, is very robust, accurate and fast. In addition, it provides control over the processing parameters and is implemented in an intuitive and modern interface. OpenCFU is a cross-platform and open-source software freely available at http://opencfu.sourceforge.net.

Performance Assessment of Network Intrusion-Alert Prediction

DTIC Science & Technology

2012-09-01

the threats. In this thesis, we use Snort to generate the intrusion detection alerts. 2. SNORT Snort is an open source network intrusion...standard for IPS. (Snort, 2012) We choose Snort because it is an open source product that is free to download and can be deployed cross-platform...Learning & prediction in relational time series: A survey. 21st Behavior Representation in Modeling & Simulation ( BRIMS ) Conference 2012, 93–100. Tan

SysSon: A Sonification Platform for Climate Data

NASA Astrophysics Data System (ADS)

Visda, Goudarzi; Hanns Holger, Rutz; Katharina, Vogt

2014-05-01

Climate data provide a challenging working basis for sonification. Both model data and measured data are assessed in collaboration with the Wegener Center for Climate and Global Change. The multi dimensionality and multi variety of climate data has a great potential for auditory displays. Furthermore, there is consensus on global climate change and the necessity of intensified climate research today in the scientific community and general public. Sonification provides a new means to communicate scientific results and inform a wider audience. SysSon is a user centered auditory platform for climate scientists to analyze data. It gives scientists broader insights by extracting hidden patterns and features from data that is not possible using a single modal visual interface. A variety of soundscapes to chose from lessens the fatigue that comes with repeated and sustained listening to long streams of data. Initial needs assessments and user tests made the work procedures and the terminology of climate scientists clear and informed the architecture of our system. Furthermore, experiments evaluated the sound design which led to a more advanced soundscape and improvement of the auditory display. We present a novel interactive sonification tool which combines a workspace for the scientists with a development environment for sonification models. The tool runs on different operating systems and is released as open source. In the standalone desktop application, multiple data sources can be imported, navigated and manipulated either via text or a graphical interface, including traditional plotting facilities. Sound models are built from unit generator graphs which are enhanced with matrix manipulation functions. They allow us to systematically experiment with elements known from the visual domain, such as range selections, scaling, thresholding, markers and labels. The models are organized in an extensible library, from which the user can choose and parametrize. Importance is given to the persistence of all configurations, in order to faithfully reproduce sonification instances. Finally, the platform is prepared to allow the composition of interactive sound installations, transitioning between the scientific lab and the gallery space.

Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

Development of a web application for water resources based on open source software

NASA Astrophysics Data System (ADS)

Delipetrev, Blagoj; Jonoski, Andreja; Solomatine, Dimitri P.

2014-01-01

This article presents research and development of a prototype web application for water resources using latest advancements in Information and Communication Technologies (ICT), open source software and web GIS. The web application has three web services for: (1) managing, presenting and storing of geospatial data, (2) support of water resources modeling and (3) water resources optimization. The web application is developed using several programming languages (PhP, Ajax, JavaScript, Java), libraries (OpenLayers, JQuery) and open source software components (GeoServer, PostgreSQL, PostGIS). The presented web application has several main advantages: it is available all the time, it is accessible from everywhere, it creates a real time multi-user collaboration platform, the programing languages code and components are interoperable and designed to work in a distributed computer environment, it is flexible for adding additional components and services and, it is scalable depending on the workload. The application was successfully tested on a case study with concurrent multi-users access.

PACS for Bhutan: a cost effective open source architecture for emerging countries.

PubMed

Ratib, Osman; Roduit, Nicolas; Nidup, Dechen; De Geer, Gerard; Rosset, Antoine; Geissbuhler, Antoine

2016-10-01

This paper reports the design and implementation of an innovative and cost-effective imaging management infrastructure suitable for radiology centres in emerging countries. It was implemented in the main referring hospital of Bhutan equipped with a CT, an MRI, digital radiology, and a suite of several ultrasound units. They lacked the necessary informatics infrastructure for image archiving and interpretation and needed a system for distribution of images to clinical wards. The solution developed for this project combines several open source software platforms in a robust and versatile archiving and communication system connected to analysis workstations equipped with a FDA-certified version of the highly popular Open-Source software. The whole system was implemented on standard off-the-shelf hardware. The system was installed in three days, and training of the radiologists as well as the technical and IT staff was provided onsite to ensure full ownership of the system by the local team. Radiologists were rapidly capable of reading and interpreting studies on the diagnostic workstations, which had a significant benefit on their workflow and ability to perform diagnostic tasks more efficiently. Furthermore, images were also made available to several clinical units on standard desktop computers through a web-based viewer. • Open source imaging informatics platforms can provide cost-effective alternatives for PACS • Robust and cost-effective open architecture can provide adequate solutions for emerging countries • Imaging informatics is often lacking in hospitals equipped with digital modalities.

A-Track: Detecting Moving Objects in FITS images

NASA Astrophysics Data System (ADS)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2017-04-01

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

Effect of perceptual load on semantic access by speech in children

PubMed Central

Jerger, Susan; Damian, Markus F.; Mills, Candice; Bartlett, James; Tye-Murray, Nancy; Abdi, Hervè

2013-01-01

Purpose To examine whether semantic access by speech requires attention in children. Method Children (N=200) named pictures and ignored distractors on a cross-modal (distractors: auditory-no face) or multi-modal (distractors: auditory-static face and audiovisual-dynamic face) picture word task. The cross-modal had a low load, and the multi-modal had a high load [i.e., respectively naming pictures displayed 1) on a blank screen vs 2) below the talker’s face on his T-shirt]. Semantic content of distractors was manipulated to be related vs unrelated to picture (e.g., picture dog with distractors bear vs cheese). Lavie's (2005) perceptual load model proposes that semantic access is independent of capacity limited attentional resources if irrelevant semantic-content manipulation influences naming times on both tasks despite variations in loads but dependent on attentional resources exhausted by higher load task if irrelevant content influences naming only on cross-modal (low load). Results Irrelevant semantic content affected performance for both tasks in 6- to 9-year-olds, but only on cross-modal in 4–5-year-olds. The addition of visual speech did not influence results on the multi-modal task. Conclusion Younger and older children differ in dependence on attentional resources for semantic access by speech. PMID:22896045

Using CamiTK for rapid prototyping of interactive computer assisted medical intervention applications.

PubMed

Promayon, Emmanuel; Fouard, Céline; Bailet, Mathieu; Deram, Aurélien; Fiard, Gaëlle; Hungr, Nikolai; Luboz, Vincent; Payan, Yohan; Sarrazin, Johan; Saubat, Nicolas; Selmi, Sonia Yuki; Voros, Sandrine; Cinquin, Philippe; Troccaz, Jocelyne

2013-01-01

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc. CamiTK is a modular framework that helps researchers and clinicians to collaborate together in order to prototype CAMI applications by regrouping the knowledge and expertise from each discipline. It is an open-source, cross-platform generic and modular tool written in C++ which can handle medical images, surgical navigation, biomedicals simulations and robot control. This paper presents the Computer Assisted Medical Intervention ToolKit (CamiTK) and how it is used in various applications in our research team.

DCO-VIVO: A Collaborative Data Platform for the Deep Carbon Science Communities

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.; West, P.; Erickson, J. S.; Ma, X.; Fox, P. A.

2014-12-01

Deep Carbon Observatory (DCO) is a decade-long scientific endeavor to understand carbon in the complex deep Earth system. Thousands of DCO scientists from institutions across the globe are organized into communities representing four domains of exploration: Extreme Physics and Chemistry, Reservoirs and Fluxes, Deep Energy, and Deep Life. Cross-community and cross-disciplinary collaboration is one of the most distinctive features in DCO's flexible research framework. VIVO is an open-source Semantic Web platform that facilitates cross-institutional researcher and research discovery. it includes a number of standard ontologies that interconnect people, organizations, publications, activities, locations, and other entities of research interest to enable browsing, searching, visualizing, and generating Linked Open (research) Data. The DCO-VIVO solution expedites research collaboration between DCO scientists and communities. Based on DCO's specific requirements, the DCO Data Science team developed a series of extensions to the VIVO platform including extending the VIVO information model, extended query over the semantic information within VIVO, integration with other open source collaborative environments and data management systems, using single sign-on, assigning of unique Handles to DCO objects, and publication and dataset ingesting extensions using existing publication systems. We present here the iterative development of these requirements that are now in daily use by the DCO community of scientists for research reporting, information sharing, and resource discovery in support of research activities and program management.

An Extensible Sensing and Control Platform for Building Energy Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rowe, Anthony; Berges, Mario; Martin, Christopher

2016-04-03

The goal of this project is to develop Mortar.io, an open-source BAS platform designed to simplify data collection, archiving, event scheduling and coordination of cross-system interactions. Mortar.io is optimized for (1) robustness to network outages, (2) ease of installation using plug-and-play and (3) scalable support for small to large buildings and campuses.

OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects

PubMed Central

Geissmann, Quentin

2013-01-01

Counting circular objects such as cell colonies is an important source of information for biologists. Although this task is often time-consuming and subjective, it is still predominantly performed manually. The aim of the present work is to provide a new tool to enumerate circular objects from digital pictures and video streams. Here, I demonstrate that the created program, OpenCFU, is very robust, accurate and fast. In addition, it provides control over the processing parameters and is implemented in an intuitive and modern interface. OpenCFU is a cross-platform and open-source software freely available at http://opencfu.sourceforge.net. PMID:23457446

Open Source Next Generation Visualization Software for Interplanetary Missions

NASA Technical Reports Server (NTRS)

Trimble, Jay; Rinker, George

2016-01-01

Mission control is evolving quickly, driven by the requirements of new missions, and enabled by modern computing capabilities. Distributed operations, access to data anywhere, data visualization for spacecraft analysis that spans multiple data sources, flexible reconfiguration to support multiple missions, and operator use cases, are driving the need for new capabilities. NASA's Advanced Multi-Mission Operations System (AMMOS), Ames Research Center (ARC) and the Jet Propulsion Laboratory (JPL) are collaborating to build a new generation of mission operations software for visualization, to enable mission control anywhere, on the desktop, tablet and phone. The software is built on an open source platform that is open for contributions (http://nasa.github.io/openmct).

Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

PubMed Central

Joshi, Bishnu P.; Wang, Thomas D.

2010-01-01

Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research. PMID:22180839

BEARS: a multi-mission anomaly response system

NASA Astrophysics Data System (ADS)

Roberts, Bryce A.

2009-05-01

The Mission Operations Group at UC Berkeley's Space Sciences Laboratory operates a highly automated ground station and presently a fleet of seven satellites, each with its own associated command and control console. However, the requirement for prompt anomaly detection and resolution is shared commonly between the ground segment and all spacecraft. The efficient, low-cost operation and "lights-out" staffing of the Mission Operations Group requires that controllers and engineers be notified of spacecraft and ground system problems around the clock. The Berkeley Emergency Anomaly and Response System (BEARS) is an in-house developed web- and paging-based software system that meets this need. BEARS was developed as a replacement for an existing emergency reporting software system that was too closedsource, platform-specific, expensive, and antiquated to expand or maintain. To avoid these limitations, the new system design leverages cross-platform, open-source software products such as MySQL, PHP, and Qt. Anomaly notifications and responses make use of the two-way paging capabilities of modern smart phones.

A low-power multi-modal body sensor network with application to epileptic seizure monitoring.

PubMed

Altini, Marco; Del Din, Silvia; Patel, Shyamal; Schachter, Steven; Penders, Julien; Bonato, Paolo

2011-01-01

Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable sensor platform, and its characteristics with respect to power consumption. Second we present the preliminary results of the comparison between our sensors and a reference system, on healthy subjects, to test the reliability of the detected physiological (electrocardiogram and respiration) and electromyography signals.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

PubMed

Georgiadis, Vassilis; Stephanou, Anastasis; Townsend, Paul A; Jackson, Thomas R

2015-01-01

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

Cross contrast multi-channel image registration using image synthesis for MR brain images.

PubMed

Chen, Min; Carass, Aaron; Jog, Amod; Lee, Junghoon; Roy, Snehashis; Prince, Jerry L

2017-02-01

Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information. Copyright © 2016 Elsevier B.V. All rights reserved.

What Can OpenEI Do For You?

ScienceCinema

None

2018-02-06

Open Energy Information (OpenEI) is an open source web platform—similar to the one used by Wikipedia—developed by the US Department of Energy (DOE) and the National Renewable Energy Laboratory (NREL) to make the large amounts of energy-related data and information more easily searched, accessed, and used both by people and automated machine processes. Built utilizing the standards and practices of the Linked Open Data community, the OpenEI platform is much more robust and powerful than typical web sites and databases. As an open platform, all users can search, edit, add, and access data in OpenEI for free. The user community contributes the content and ensures its accuracy and relevance; as the community expands, so does the content's comprehensiveness and quality. The data are structured and tagged with descriptors to enable cross-linking among related data sets, advanced search functionality, and consistent, usable formatting. Data input protocols and quality standards help ensure the content is structured and described properly and derived from a credible source. Although DOE/NREL is developing OpenEI and seeding it with initial data, it is designed to become a true community model with millions of users, a large core of active contributors, and numerous sponsors.

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

NASA Technical Reports Server (NTRS)

Hart, Andrew F.; Verma, Rishi; Mattmann, Chris A.; Crichton, Daniel J.; Kelly, Sean; Kincaid, Heather; Hughes, Steven; Ramirez, Paul; Goodale, Cameron; Anton, Kristen;

Implementing Open Source Platform for Education Quality Enhancement in Primary Education: Indonesia Experience

ERIC Educational Resources Information Center

Kisworo, Marsudi Wahyu

2016-01-01

Information and Communication Technology (ICT)-supported learning using free and open source platform draws little attention as open source initiatives were focused in secondary or tertiary educations. This study investigates possibilities of ICT-supported learning using open source platform for primary educations. The data of this study is taken…

Big data sharing and analysis to advance research in post-traumatic epilepsy.

PubMed

Duncan, Dominique; Vespa, Paul; Pitkanen, Asla; Braimah, Adebayo; Lapinlampi, Nina; Toga, Arthur W

2018-06-01

We describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time. Copyright © 2017. Published by Elsevier Inc.

Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Yonggang

In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integratedmore » analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.« less

System Architecture Development for Energy and Water Infrastructure Data Management and Geovisual Analytics

NASA Astrophysics Data System (ADS)

Berres, A.; Karthik, R.; Nugent, P.; Sorokine, A.; Myers, A.; Pang, H.

2017-12-01

Building an integrated data infrastructure that can meet the needs of a sustainable energy-water resource management requires a robust data management and geovisual analytics platform, capable of cross-domain scientific discovery and knowledge generation. Such a platform can facilitate the investigation of diverse complex research and policy questions for emerging priorities in Energy-Water Nexus (EWN) science areas. Using advanced data analytics, machine learning techniques, multi-dimensional statistical tools, and interactive geovisualization components, such a multi-layered federated platform is being developed, the Energy-Water Nexus Knowledge Discovery Framework (EWN-KDF). This platform utilizes several enterprise-grade software design concepts and standards such as extensible service-oriented architecture, open standard protocols, event-driven programming model, enterprise service bus, and adaptive user interfaces to provide a strategic value to the integrative computational and data infrastructure. EWN-KDF is built on the Compute and Data Environment for Science (CADES) environment in Oak Ridge National Laboratory (ORNL).

The Image Data Resource: A Bioimage Data Integration and Publication Platform.

PubMed

Williams, Eleanor; Moore, Josh; Li, Simon W; Rustici, Gabriella; Tarkowska, Aleksandra; Chessel, Anatole; Leo, Simone; Antal, Bálint; Ferguson, Richard K; Sarkans, Ugis; Brazma, Alvis; Salas, Rafael E Carazo; Swedlow, Jason R

2017-08-01

Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links data from several imaging modalities, including high-content screening, super-resolution and time-lapse microscopy, digital pathology, public genetic or chemical databases, and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.

pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data.

PubMed

Duvvuri, Hiranmayi; Wheeler, Lucas C; Harms, Michael J

2018-05-08

Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc .

Neuroimaging Data Sharing on the Neuroinformatics Database Platform

PubMed Central

Book, Gregory A; Stevens, Michael; Assaf, Michal; Glahn, David; Pearlson, Godfrey D

2015-01-01

We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data. PMID:25888923

Global review of open access risk assessment software packages valid for global or continental scale analysis

NASA Astrophysics Data System (ADS)

Daniell, James; Simpson, Alanna; Gunasekara, Rashmin; Baca, Abigail; Schaefer, Andreas; Ishizawa, Oscar; Murnane, Rick; Tijssen, Annegien; Deparday, Vivien; Forni, Marc; Himmelfarb, Anne; Leder, Jan

2015-04-01

Over the past few decades, a plethora of open access software packages for the calculation of earthquake, volcanic, tsunami, storm surge, wind and flood have been produced globally. As part of the World Bank GFDRR Review released at the Understanding Risk 2014 Conference, over 80 such open access risk assessment software packages were examined. Commercial software was not considered in the evaluation. A preliminary analysis was used to determine whether the 80 models were currently supported and if they were open access. This process was used to select a subset of 31 models that include 8 earthquake models, 4 cyclone models, 11 flood models, and 8 storm surge/tsunami models for more detailed analysis. By using multi-criteria analysis (MCDA) and simple descriptions of the software uses, the review allows users to select a few relevant software packages for their own testing and development. The detailed analysis evaluated the models on the basis of over 100 criteria and provides a synopsis of available open access natural hazard risk modelling tools. In addition, volcano software packages have since been added making the compendium of risk software tools in excess of 100. There has been a huge increase in the quality and availability of open access/source software over the past few years. For example, private entities such as Deltares now have an open source policy regarding some flood models (NGHS). In addition, leaders in developing risk models in the public sector, such as Geoscience Australia (EQRM, TCRM, TsuDAT, AnuGA) or CAPRA (ERN-Flood, Hurricane, CRISIS2007 etc.), are launching and/or helping many other initiatives. As we achieve greater interoperability between modelling tools, we will also achieve a future wherein different open source and open access modelling tools will be increasingly connected and adapted towards unified multi-risk model platforms and highly customised solutions. It was seen that many software tools could be improved by enabling user-defined exposure and vulnerability. Without this function, many tools can only be used regionally and not at global or continental scale. It is becoming increasingly easy to use multiple packages for a single region and/or hazard to characterize the uncertainty in the risk, or use as checks for the sensitivities in the analysis. There is a potential for valuable synergy between existing software. A number of open source software packages could be combined to generate a multi-risk model with multiple views of a hazard. This extensive review has simply attempted to provide a platform for dialogue between all open source and open access software packages and to hopefully inspire collaboration between developers, given the great work done by all open access and open source developers.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

PubMed

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

ProteoWizard: open source software for rapid proteomics tools development.

PubMed

Kessner, Darren; Chambers, Matt; Burke, Robert; Agus, David; Mallick, Parag

2008-11-01

The ProteoWizard software project provides a modular and extensible set of open-source, cross-platform tools and libraries. The tools perform proteomics data analyses; the libraries enable rapid tool creation by providing a robust, pluggable development framework that simplifies and unifies data file access, and performs standard proteomics and LCMS dataset computations. The library contains readers and writers of the mzML data format, which has been written using modern C++ techniques and design principles and supports a variety of platforms with native compilers. The software has been specifically released under the Apache v2 license to ensure it can be used in both academic and commercial projects. In addition to the library, we also introduce a rapidly growing set of companion tools whose implementation helps to illustrate the simplicity of developing applications on top of the ProteoWizard library. Cross-platform software that compiles using native compilers (i.e. GCC on Linux, MSVC on Windows and XCode on OSX) is available for download free of charge, at http://proteowizard.sourceforge.net. This website also provides code examples, and documentation. It is our hope the ProteoWizard project will become a standard platform for proteomics development; consequently, code use, contribution and further development are strongly encouraged.

Utilizing Multi-Modal Literacies in Middle Grades Science

ERIC Educational Resources Information Center

Saurino, Dan; Ogletree, Tamra; Saurino, Penelope

2010-01-01

The nature of literacy is changing. Increased student use of computer-mediated, digital, and visual communication spans our understanding of adolescent multi-modal capabilities that reach beyond the traditional conventions of linear speech and written text in the science curriculum. Advancing technology opens doors to learning that involve…

ImTK: an open source multi-center information management toolkit

NASA Astrophysics Data System (ADS)

Alaoui, Adil; Ingeholm, Mary Lou; Padh, Shilpa; Dorobantu, Mihai; Desai, Mihir; Cleary, Kevin; Mun, Seong K.

2008-03-01

The Information Management Toolkit (ImTK) Consortium is an open source initiative to develop robust, freely available tools related to the information management needs of basic, clinical, and translational research. An open source framework and agile programming methodology can enable distributed software development while an open architecture will encourage interoperability across different environments. The ISIS Center has conceptualized a prototype data sharing network that simulates a multi-center environment based on a federated data access model. This model includes the development of software tools to enable efficient exchange, sharing, management, and analysis of multimedia medical information such as clinical information, images, and bioinformatics data from multiple data sources. The envisioned ImTK data environment will include an open architecture and data model implementation that complies with existing standards such as Digital Imaging and Communications (DICOM), Health Level 7 (HL7), and the technical framework and workflow defined by the Integrating the Healthcare Enterprise (IHE) Information Technology Infrastructure initiative, mainly the Cross Enterprise Document Sharing (XDS) specifications.

The Prodiguer Messaging Platform

NASA Astrophysics Data System (ADS)

Greenslade, Mark; Denvil, Sebastien; Raciazek, Jerome; Carenton, Nicolas; Levavasseur, Guillame

2014-05-01

CONVERGENCE is a French multi-partner national project designed to gather HPC and informatics expertise to innovate in the context of running French climate models with differing grids and at differing resolutions. Efficient and reliable execution of these models and the management and dissemination of model output (data and meta-data) are just some of the complexities that CONVERGENCE aims to resolve. The Institut Pierre Simon Laplace (IPSL) is responsible for running climate simulations upon a set of heterogenous HPC environments within France. With heterogeneity comes added complexity in terms of simulation instrumentation and control. Obtaining a global perspective upon the state of all simulations running upon all HPC environments has hitherto been problematic. In this presentation we detail how, within the context of CONVERGENCE, the implementation of the Prodiguer messaging platform resolves complexity and permits the development of real-time applications such as: 1. a simulation monitoring dashboard; 2. a simulation metrics visualizer; 3. an automated simulation runtime notifier; 4. an automated output data & meta-data publishing pipeline; The Prodiguer messaging platform leverages a widely used open source message broker software called RabbitMQ. RabbitMQ itself implements the Advanced Message Queue Protocol (AMPQ). Hence it will be demonstrated that the Prodiguer messaging platform is built upon both open source and open standards.

Lenstronomy: Multi-purpose gravitational lens modeling software package

NASA Astrophysics Data System (ADS)

Birrer, Simon; Amara, Adam

2018-04-01

Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

Specifications and implementation of the RT MHD control system for the EC launcher of FTU

NASA Astrophysics Data System (ADS)

Galperti, C.; Alessi, E.; Boncagni, L.; Bruschi, A.; Granucci, G.; Grosso, A.; Iannone, F.; Marchetto, C.; Nowak, S.; Panella, M.; Sozzi, C.; Tilia, B.

2012-09-01

To perform real time plasma control experiments using EC heating waves by using the new fast launcher installed on FTU a dedicated data acquisition and elaboration system has been designed recently. A prototypical version of the acquisition/control system has been recently developed and will be tested on FTU machine in its next experimental campaign. The open-source framework MARTe (Multi-threaded Application Real-Time executor) on Linux/RTAI real-time operating system has been chosen as software platform to realize the control system. Standard open-architecture industrial PCs, based either on VME bus and CompactPCI bus equipped with standard input/output cards are the chosen hardware platform.

Joint Intelligence Operations Center (JIOC) Baseline Business Process Model & Capabilities Evaluation Methodology

DTIC Science & Technology

2012-03-01

Targeting Review Board OPLAN Operations Plan OPORD Operations Order OPSIT Operational Situation OSINT Open Source Intelligence OV...Analysis Evaluate FLTREPs MISREPs Unit Assign Assets Feedback Asset Shortfalls Multi-Int Collection Political & Embasy Law Enforcement HUMINT OSINT ...Embassy Information OSINT Manage Theater HUMINT Law Enforcement Collection Sort Requests Platform Information Agency Information M-I Collect

Psynteract: A flexible, cross-platform, open framework for interactive experiments.

PubMed

Henninger, Felix; Kieslich, Pascal J; Hilbig, Benjamin E

2017-10-01

We introduce a novel platform for interactive studies, that is, any form of study in which participants' experiences depend not only on their own responses, but also on those of other participants who complete the same study in parallel, for example a prisoner's dilemma or an ultimatum game. The software thus especially serves the rapidly growing field of strategic interaction research within psychology and behavioral economics. In contrast to all available software packages, our platform does not handle stimulus display and response collection itself. Instead, we provide a mechanism to extend existing experimental software to incorporate interactive functionality. This approach allows us to draw upon the capabilities already available, such as accuracy of temporal measurement, integration with auxiliary hardware such as eye-trackers or (neuro-)physiological apparatus, and recent advances in experimental software, for example capturing response dynamics through mouse-tracking. Through integration with OpenSesame, an open-source graphical experiment builder, studies can be assembled via a drag-and-drop interface requiring little or no further programming skills. In addition, by using the same communication mechanism across software packages, we also enable interoperability between systems. Our source code, which provides support for all major operating systems and several popular experimental packages, can be freely used and distributed under an open source license. The communication protocols underlying its functionality are also well documented and easily adapted to further platforms. Code and documentation are available at https://github.com/psynteract/ .

Missing Modality Transfer Learning via Latent Low-Rank Constraint.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2015-11-01

Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.

A Video Game Platform for Exploring Satellite and In-Situ Data Streams

NASA Astrophysics Data System (ADS)

Cai, Y.

2014-12-01

Exploring spatiotemporal patterns of moving objects are essential to Earth Observation missions, such as tracking, modeling and predicting movement of clouds, dust, plumes and harmful algal blooms. Those missions involve high-volume, multi-source, and multi-modal imagery data analysis. Analytical models intend to reveal inner structure, dynamics, and relationship of things. However, they are not necessarily intuitive to humans. Conventional scientific visualization methods are intuitive but limited by manual operations, such as area marking, measurement and alignment of multi-source data, which are expensive and time-consuming. A new development of video analytics platform has been in progress, which integrates the video game engine with satellite and in-situ data streams. The system converts Earth Observation data into articulated objects that are mapped from a high-dimensional space to a 3D space. The object tracking and augmented reality algorithms highlight the objects' features in colors, shapes and trajectories, creating visual cues for observing dynamic patterns. The head and gesture tracker enable users to navigate the data space interactively. To validate our design, we have used NASA SeaWiFS satellite images of oceanographic remote sensing data and NOAA's in-situ cell count data. Our study demonstrates that the video game system can reduce the size and cost of traditional CAVE systems in two to three orders of magnitude. This system can also be used for satellite mission planning and public outreaching.

Neurite guidance and three-dimensional confinement via compliant semiconductor scaffolds.

PubMed

Cavallo, Francesca; Huang, Yu; Dent, Erik W; Williams, Justin C; Lagally, Max G

2014-12-23

Neurons are often cultured in vitro on a flat, open, and rigid substrate, a platform that does not reflect well the native microenvironment of the brain. To address this concern, we have developed a culturing platform containing arrays of microchannels, formed in a crystalline-silicon nanomembrane (NM) resting on polydimethylsiloxane; this platform will additionally enable active sensing and stimulation at the local scale, via devices fabricated in the silicon. The mechanical properties of the composite Si/compliant substrate nanomaterial approximate those of neural tissue. The microchannels, created in the NM by strain engineering, demonstrate strong guidance of neurite outgrowth. Using plasma techniques, we developed a means to coat just the inside surface of these channels with an adhesion promoter (poly-d-lysine). For NM channels with openings larger than the cross-sectional area of a single axon, strong physical confinement and guidance of axons through the channels are observed. Imaging of axons that grow in channels with openings that approximate the size of an axon suggests that a tight seal exists between the cell membrane and the inner surface of the channel, mimicking a myelin sheath. Such a tight seal of the cell membrane with the channel surface would make this platform an attractive candidate for future neuronal repair. Results of measurements of impedance and photoluminescence of bare NM channels are comparable to those on a flat NM, demonstrating electrical and optical modalities of our platform and suggesting that this scaffold can be expanded for active sensing and monitoring of neuron cellular processes in conditions in which they exist naturally.

Visualization of Vgi Data Through the New NASA Web World Wind Virtual Globe

NASA Astrophysics Data System (ADS)

Brovelli, M. A.; Kilsedar, C. E.; Zamboni, G.

2016-06-01

GeoWeb 2.0, laying the foundations of Volunteered Geographic Information (VGI) systems, has led to platforms where users can contribute to the geographic knowledge that is open to access. Moreover, as a result of the advancements in 3D visualization, virtual globes able to visualize geographic data even on browsers emerged. However the integration of VGI systems and virtual globes has not been fully realized. The study presented aims to visualize volunteered data in 3D, considering also the ease of use aspects for general public, using Free and Open Source Software (FOSS). The new Application Programming Interface (API) of NASA, Web World Wind, written in JavaScript and based on Web Graphics Library (WebGL) is cross-platform and cross-browser, so that the virtual globe created using this API can be accessible through any WebGL supported browser on different operating systems and devices, as a result not requiring any installation or configuration on the client-side, making the collected data more usable to users, which is not the case with the World Wind for Java as installation and configuration of the Java Virtual Machine (JVM) is required. Furthermore, the data collected through various VGI platforms might be in different formats, stored in a traditional relational database or in a NoSQL database. The project developed aims to visualize and query data collected through Open Data Kit (ODK) platform and a cross-platform application, where data is stored in a relational PostgreSQL and NoSQL CouchDB databases respectively.

Analyzing huge pathology images with open source software.

PubMed

Deroulers, Christophe; Ameisen, David; Badoual, Mathilde; Gerin, Chloé; Granier, Alexandre; Lartaud, Marc

2013-06-06

Digital pathology images are increasingly used both for diagnosis and research, because slide scanners are nowadays broadly available and because the quantitative study of these images yields new insights in systems biology. However, such virtual slides build up a technical challenge since the images occupy often several gigabytes and cannot be fully opened in a computer's memory. Moreover, there is no standard format. Therefore, most common open source tools such as ImageJ fail at treating them, and the others require expensive hardware while still being prohibitively slow. We have developed several cross-platform open source software tools to overcome these limitations. The NDPITools provide a way to transform microscopy images initially in the loosely supported NDPI format into one or several standard TIFF files, and to create mosaics (division of huge images into small ones, with or without overlap) in various TIFF and JPEG formats. They can be driven through ImageJ plugins. The LargeTIFFTools achieve similar functionality for huge TIFF images which do not fit into RAM. We test the performance of these tools on several digital slides and compare them, when applicable, to standard software. A statistical study of the cells in a tissue sample from an oligodendroglioma was performed on an average laptop computer to demonstrate the efficiency of the tools. Our open source software enables dealing with huge images with standard software on average computers. They are cross-platform, independent of proprietary libraries and very modular, allowing them to be used in other open source projects. They have excellent performance in terms of execution speed and RAM requirements. They open promising perspectives both to the clinician who wants to study a single slide and to the research team or data centre who do image analysis of many slides on a computer cluster. The virtual slide(s) for this article can be found here:http://www.diagnosticpathology.diagnomx.eu/vs/5955513929846272.

Analyzing huge pathology images with open source software

PubMed Central

2013-01-01

Background Digital pathology images are increasingly used both for diagnosis and research, because slide scanners are nowadays broadly available and because the quantitative study of these images yields new insights in systems biology. However, such virtual slides build up a technical challenge since the images occupy often several gigabytes and cannot be fully opened in a computer’s memory. Moreover, there is no standard format. Therefore, most common open source tools such as ImageJ fail at treating them, and the others require expensive hardware while still being prohibitively slow. Results We have developed several cross-platform open source software tools to overcome these limitations. The NDPITools provide a way to transform microscopy images initially in the loosely supported NDPI format into one or several standard TIFF files, and to create mosaics (division of huge images into small ones, with or without overlap) in various TIFF and JPEG formats. They can be driven through ImageJ plugins. The LargeTIFFTools achieve similar functionality for huge TIFF images which do not fit into RAM. We test the performance of these tools on several digital slides and compare them, when applicable, to standard software. A statistical study of the cells in a tissue sample from an oligodendroglioma was performed on an average laptop computer to demonstrate the efficiency of the tools. Conclusions Our open source software enables dealing with huge images with standard software on average computers. They are cross-platform, independent of proprietary libraries and very modular, allowing them to be used in other open source projects. They have excellent performance in terms of execution speed and RAM requirements. They open promising perspectives both to the clinician who wants to study a single slide and to the research team or data centre who do image analysis of many slides on a computer cluster. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5955513929846272 PMID:23829479

3-D interactive visualisation tools for Hi spectral line imaging

NASA Astrophysics Data System (ADS)

van der Hulst, J. M.; Punzo, D.; Roerdink, J. B. T. M.

2017-06-01

Upcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we present SlicerAstro, an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.

Unified, Cross-Platform, Open-Source Library Package for High-Performance Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kozacik, Stephen

Compute power is continually increasing, but this increased performance is largely found in sophisticated computing devices and supercomputer resources that are difficult to use, resulting in under-utilization. We developed a unified set of programming tools that will allow users to take full advantage of the new technology by allowing them to work at a level abstracted away from the platform specifics, encouraging the use of modern computing systems, including government-funded supercomputer facilities.

Multi-modal automatic montaging of adaptive optics retinal images

PubMed Central

Chen, Min; Cooper, Robert F.; Han, Grace K.; Gee, James; Brainard, David H.; Morgan, Jessica I. W.

2016-01-01

We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download. PMID:28018714

Associative learning changes cross-modal representations in the gustatory cortex

PubMed Central

Vincis, Roberto; Fontanini, Alfredo

2016-01-01

A growing body of literature has demonstrated that primary sensory cortices are not exclusively unimodal, but can respond to stimuli of different sensory modalities. However, several questions concerning the neural representation of cross-modal stimuli remain open. Indeed, it is poorly understood if cross-modal stimuli evoke unique or overlapping representations in a primary sensory cortex and whether learning can modulate these representations. Here we recorded single unit responses to auditory, visual, somatosensory, and olfactory stimuli in the gustatory cortex (GC) of alert rats before and after associative learning. We found that, in untrained rats, the majority of GC neurons were modulated by a single modality. Upon learning, both prevalence of cross-modal responsive neurons and their breadth of tuning increased, leading to a greater overlap of representations. Altogether, our results show that the gustatory cortex represents cross-modal stimuli according to their sensory identity, and that learning changes the overlap of cross-modal representations. DOI: http://dx.doi.org/10.7554/eLife.16420.001 PMID:27572258

On modal cross-coupling in the asymptotic modal limit

NASA Astrophysics Data System (ADS)

Culver, Dean; Dowell, Earl

2018-03-01

The conditions under which significant modal cross-coupling occurs in dynamical systems responding to high-frequency, broadband forcing that excites many modes is studied. The modal overlap factor plays a key role in the analysis of these systems as the modal density (the ratio of number of modes to the frequency bandwidth) becomes large. The modal overlap factor is effectively the ratio of the width of a resonant peak (the damping ratio times the resonant frequency) to the average frequency interval between resonant peaks (or rather, the inverse of the modal density). It is shown that this parameter largely determines whether substantial modal cross-coupling occurs in a given system's response. Here, two prototypical systems are considered. The first is a simple rectangular plate whose significant modal cross-coupling is the exception rather than the norm. The second is a pair of rectangular plates attached at a point where significant modal cross-coupling is more likely to occur. We show that, for certain cases of modal density and damping, non-negligible cross coupling occurs in both systems. Under similar circumstances, the constraint force between the two plates in the latter system becomes broadband. The implications of this for using Asymptotic Modal Analysis (AMA) in multi-component systems are discussed.

Technical Note: PLASTIMATCH MABS, an open source tool for automatic image segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zaffino, Paolo; Spadea, Maria Francesca

Purpose: Multiatlas based segmentation is largely used in many clinical and research applications. Due to its good performances, it has recently been included in some commercial platforms for radiotherapy planning and surgery guidance. Anyway, to date, a software with no restrictions about the anatomical district and image modality is still missing. In this paper we introduce PLASTIMATCH MABS, an open source software that can be used with any image modality for automatic segmentation. Methods: PLASTIMATCH MABS workflow consists of two main parts: (1) an offline phase, where optimal registration and voting parameters are tuned and (2) an online phase, wheremore » a new patient is labeled from scratch by using the same parameters as identified in the former phase. Several registration strategies, as well as different voting criteria can be selected. A flexible atlas selection scheme is also available. To prove the effectiveness of the proposed software across anatomical districts and image modalities, it was tested on two very different scenarios: head and neck (H&N) CT segmentation for radiotherapy application, and magnetic resonance image brain labeling for neuroscience investigation. Results: For the neurological study, minimum dice was equal to 0.76 (investigated structures: left and right caudate, putamen, thalamus, and hippocampus). For head and neck case, minimum dice was 0.42 for the most challenging structures (optic nerves and submandibular glands) and 0.62 for the other ones (mandible, brainstem, and parotid glands). Time required to obtain the labels was compatible with a real clinical workflow (35 and 120 min). Conclusions: The proposed software fills a gap in the multiatlas based segmentation field, since all currently available tools (both for commercial and for research purposes) are restricted to a well specified application. Furthermore, it can be adopted as a platform for exploring MABS parameters and as a reference implementation for comparing against other segmentation algorithms.« less

Use of Open Standards and Technologies at the Lunar Mapping and Modeling Project

NASA Astrophysics Data System (ADS)

Law, E.; Malhotra, S.; Bui, B.; Chang, G.; Goodale, C. E.; Ramirez, P.; Kim, R. M.; Sadaqathulla, S.; Rodriguez, L.

2011-12-01

The Lunar Mapping and Modeling Project (LMMP), led by the Marshall Space Flight center (MSFC), is tasked by NASA. The project is responsible for the development of an information system to support lunar exploration activities. It provides lunar explorers a set of tools and lunar map and model products that are predominantly derived from present lunar missions (e.g., the Lunar Reconnaissance Orbiter (LRO)) and from historical missions (e.g., Apollo). At Jet Propulsion Laboratory (JPL), we have built the LMMP interoperable geospatial information system's underlying infrastructure and a single point of entry - the LMMP Portal by employing a number of open standards and technologies. The Portal exposes a set of services to users to allow search, visualization, subset, and download of lunar data managed by the system. Users also have access to a set of tools that visualize, analyze and annotate the data. The infrastructure and Portal are based on web service oriented architecture. We designed the system to support solar system bodies in general including asteroids, earth and planets. We employed a combination of custom software, commercial and open-source components, off-the-shelf hardware and pay-by-use cloud computing services. The use of open standards and web service interfaces facilitate platform and application independent access to the services and data, offering for instances, iPad and Android mobile applications and large screen multi-touch with 3-D terrain viewing functions, for a rich browsing and analysis experience from a variety of platforms. The web services made use of open standards including: Representational State Transfer (REST); and Open Geospatial Consortium (OGC)'s Web Map Service (WMS), Web Coverage Service (WCS), Web Feature Service (WFS). Its data management services have been built on top of a set of open technologies including: Object Oriented Data Technology (OODT) - open source data catalog, archive, file management, data grid framework; openSSO - open source access management and federation platform; solr - open source enterprise search platform; redmine - open source project collaboration and management framework; GDAL - open source geospatial data abstraction library; and others. Its data products are compliant with Federal Geographic Data Committee (FGDC) metadata standard. This standardization allows users to access the data products via custom written applications or off-the-shelf applications such as GoogleEarth. We will demonstrate this ready-to-use system for data discovery and visualization by walking through the data services provided through the portal such as browse, search, and other tools. We will further demonstrate image viewing and layering of lunar map images from the Internet, via mobile devices such as Apple's iPad.

OpenSim: open-source software to create and analyze dynamic simulations of movement.

PubMed

Delp, Scott L; Anderson, Frank C; Arnold, Allison S; Loan, Peter; Habib, Ayman; John, Chand T; Guendelman, Eran; Thelen, Darryl G

2007-11-01

Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.

YouGenMap: a web platform for dynamic multi-comparative mapping and visualization of genetic maps

Treesearch

Keith Batesole; Kokulapalan Wimalanathan; Lin Liu; Fan Zhang; Craig S. Echt; Chun Liang

2014-01-01

Comparative genetic maps are used in examination of genome organization, detection of conserved gene order, and exploration of marker order variations. YouGenMap is an open-source web tool that offers dynamic comparative mapping capability of users' own genetic mapping between 2 or more map sets. Users' genetic map data and optional gene annotations are...

The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

NASA Astrophysics Data System (ADS)

Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

2014-03-01

We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

What Can OpenEI Do For You?

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2010-12-10

Open Energy Information (OpenEI) is an open source web platform—similar to the one used by Wikipedia—developed by the US Department of Energy (DOE) and the National Renewable Energy Laboratory (NREL) to make the large amounts of energy-related data and information more easily searched, accessed, and used both by people and automated machine processes. Built utilizing the standards and practices of the Linked Open Data community, the OpenEI platform is much more robust and powerful than typical web sites and databases. As an open platform, all users can search, edit, add, and access data in OpenEI for free. The user communitymore » contributes the content and ensures its accuracy and relevance; as the community expands, so does the content's comprehensiveness and quality. The data are structured and tagged with descriptors to enable cross-linking among related data sets, advanced search functionality, and consistent, usable formatting. Data input protocols and quality standards help ensure the content is structured and described properly and derived from a credible source. Although DOE/NREL is developing OpenEI and seeding it with initial data, it is designed to become a true community model with millions of users, a large core of active contributors, and numerous sponsors.« less

State-of-the-art radiation detectors for medical imaging: Demands and trends

NASA Astrophysics Data System (ADS)

Darambara, Dimitra G.

2006-12-01

Over the last half-century a variety of significant technical advances in several scientific fields has been pointing to an exploding growth in the field of medical imaging leading to a better interpretation of more specific anatomical, biochemical and molecular pathways. In particular, the development of novel imaging detectors and readout electronics has been critical to the advancement of medical imaging allowing the invention of breakthrough platforms for simultaneous acquisition of multi-modality images at molecular level. The present paper presents a review of the challenges, demands and constraints on radiation imaging detectors imposed by the nature of the modality and the physics of the imaging source. This is followed by a concise review and perspective on various types of state-of-the-art detector technologies that have been developed to meet these requirements. Trends, prospects and new concepts for future imaging detectors are also highlighted.

Building Energy Management Open Source Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture – BEMOSS is an open source operating system that is built upon VOLTTRON – a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications.more » (2) Plug & play – BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability – BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness – Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment – With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring – BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security – In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee – BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.« less

Architecture of a high-performance surgical guidance system based on C-arm cone-beam CT: software platform for technical integration and clinical translation

NASA Astrophysics Data System (ADS)

Uneri, Ali; Schafer, Sebastian; Mirota, Daniel; Nithiananthan, Sajendra; Otake, Yoshito; Reaungamornrat, Sureerat; Yoo, Jongheun; Stayman, J. Webster; Reh, Douglas; Gallia, Gary L.; Khanna, A. Jay; Hager, Gregory; Taylor, Russell H.; Kleinszig, Gerhard; Siewerdsen, Jeffrey H.

2011-03-01

Intraoperative imaging modalities are becoming more prevalent in recent years, and the need for integration of these modalities with surgical guidance is rising, creating new possibilities as well as challenges. In the context of such emerging technologies and new clinical applications, a software architecture for cone-beam CT (CBCT) guided surgery has been developed with emphasis on binding open-source surgical navigation libraries and integrating intraoperative CBCT with novel, application-specific registration and guidance technologies. The architecture design is focused on accelerating translation of task-specific technical development in a wide range of applications, including orthopaedic, head-and-neck, and thoracic surgeries. The surgical guidance system is interfaced with a prototype mobile C-arm for high-quality CBCT and through a modular software architecture, integration of different tools and devices consistent with surgical workflow in each of these applications is realized. Specific modules are developed according to the surgical task, such as: 3D-3D rigid or deformable registration of preoperative images, surgical planning data, and up-to-date CBCT images; 3D-2D registration of planning and image data in real-time fluoroscopy and/or digitally reconstructed radiographs (DRRs); compatibility with infrared, electromagnetic, and video-based trackers used individually or in hybrid arrangements; augmented overlay of image and planning data in endoscopic or in-room video; real-time "virtual fluoroscopy" computed from GPU-accelerated DRRs; and multi-modality image display. The platform aims to minimize offline data processing by exposing quantitative tools that analyze and communicate factors of geometric precision. The system was translated to preclinical phantom and cadaver studies for assessment of fiducial (FRE) and target registration error (TRE) showing sub-mm accuracy in targeting and video overlay within intraoperative CBCT. The work culminates in the development of a CBCT guidance system (reported here for the first time) that leverages the technical developments in Carm CBCT and associated technologies for realizing a high-performance system for translation to clinical studies.

VAGUE: a graphical user interface for the Velvet assembler.

PubMed

Powell, David R; Seemann, Torsten

2013-01-15

Velvet is a popular open-source de novo genome assembly software tool, which is run from the Unix command line. Most of the problems experienced by new users of Velvet revolve around constructing syntactically and semantically correct command lines, getting input files into acceptable formats and assessing the output. Here, we present Velvet Assembler Graphical User Environment (VAGUE), a multi-platform graphical front-end for Velvet. VAGUE aims to make sequence assembly accessible to a wider audience and to facilitate better usage amongst existing users of Velvet. VAGUE is implemented in JRuby and targets the Java Virtual Machine. It is available under an open-source GPLv2 licence from http://www.vicbioinformatics.com/. torsten.seemann@monash.edu.

MMX-I: data-processing software for multimodal X-ray imaging and tomography.

PubMed

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-05-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors' knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments.

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

PubMed

Paananen, Jussi; Storvik, Markus; Wong, Garry

2006-09-22

Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies. We have developed a web-based software resource, called CROPPER that uses the latest genomic information concerning different data identifiers and orthologous genes from the Ensembl database. CROPPER can be used to combine genomic data from different heterogeneous sources, allowing researchers to perform cross-platform/cross-species compendium studies without the need for complex computational tools or the requirement of setting up one's own in-house database. We also present an example of a simple cross-platform/cross-species compendium study based on publicly available Parkinson's disease data derived from different sources. CROPPER is a user-friendly and freely available web-based software resource that can be successfully used for cross-species/cross-platform compendium studies.

Open-Source 3-D Platform for Low-Cost Scientific Instrument Ecosystem.

PubMed

Zhang, C; Wijnen, B; Pearce, J M

2016-08-01

The combination of open-source software and hardware provides technically feasible methods to create low-cost, highly customized scientific research equipment. Open-source 3-D printers have proven useful for fabricating scientific tools. Here the capabilities of an open-source 3-D printer are expanded to become a highly flexible scientific platform. An automated low-cost 3-D motion control platform is presented that has the capacity to perform scientific applications, including (1) 3-D printing of scientific hardware; (2) laboratory auto-stirring, measuring, and probing; (3) automated fluid handling; and (4) shaking and mixing. The open-source 3-D platform not only facilities routine research while radically reducing the cost, but also inspires the creation of a diverse array of custom instruments that can be shared and replicated digitally throughout the world to drive down the cost of research and education further. © 2016 Society for Laboratory Automation and Screening.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

The Physics of Imaging with Remote Sensors : Photon State Space & Radiative Transfer

NASA Technical Reports Server (NTRS)

Davis, Anthony B.

2012-01-01

Standard (mono-pixel/steady-source) retrieval methodology is reaching its fundamental limit with access to multi-angle/multi-spectral photo- polarimetry. Next... Two emerging new classes of retrieval algorithm worth nurturing: multi-pixel time-domain Wave-radiometry transition regimes, and more... Cross-fertilization with bio-medical imaging. Physics-based remote sensing: - What is "photon state space?" - What is "radiative transfer?" - Is "the end" in sight? Two wide-open frontiers! center dot Examples (with variations.

Quality models for audiovisual streaming

NASA Astrophysics Data System (ADS)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

ERDDAP: Reducing Data Friction with an Open Source Data Platform

NASA Astrophysics Data System (ADS)

O'Brien, K.

2017-12-01

Data friction is not just an issue facing interdisciplinary research. Often times, even within disciplines, significant data friction can exist. Issues of differing formats, limited metadata and non-existent machine-to-machine data access are all issues that exist within disciplines and make it that much harder for successful interdisciplinary cooperation. Therefore, reducing data friction within disciplines is crucial first step in providing better overall collaboration. ERDDAP, an open source data platform developed at NOAA's Southwest Fisheries Center, is well poised to improve data useability and understanding and reduce data friction, both in single and multi-disciplinary research. By virtue of its ability to integrate data of varying formats and provide RESTful-based user access to data and metadata, use of ERDDAP has grown substantially throughout the ocean data community. ERDDAP also supports standards such as the DAP data protocol, the Climate and Forecast (CF) metadata conventions and the Bagit document standard for data archival. In this presentation, we will discuss the advantages of using ERDDAP as a data platform. We will also show specific use cases where utilizing ERDDAP has reduced friction within a single discipline (physical oceanography) and improved interdisciplinary collaboration as well.

MMX-I: data-processing software for multimodal X-ray imaging and tomography

PubMed Central

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-01-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors’ knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments. PMID:27140159

Sirepo for Synchrotron Radiation Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagler, Robert; Moeller, Paul; Rakitin, Maksim

Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jinja, which is a secure andmore » widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is the Synchrotron Radiation Workshop (SRW). SRW computes synchrotron radiation from relativistic electrons in arbitrary magnetic fields and propagates the radiation wavefronts through optical beamlines. SRW is open source and is primarily supported by Dr. Oleg Chubar of NSLS-II at Brookhaven National Laboratory.« less

Going "open" with mesoscopy: a new dimension on multi-view imaging.

PubMed

Gualda, Emilio; Moreno, Nuno; Tomancak, Pavel; Martins, Gabriel G

2014-03-01

OpenSPIM and OpenSpinMicroscopy emerged as open access platforms for Light Sheet and Optical Projection Imaging, often called as optical mesoscopy techniques. Both projects can be easily reproduced using comprehensive online instructions that should foster the implementation and further development of optical imaging techniques with sample rotation control. This additional dimension in an open system offers the possibility to make multi-view microscopy easily modified and will complement the emerging commercial solutions. Furthermore, it is deeply based on other open platforms such as MicroManager and Arduino, enabling development of tailored setups for very specific biological questions. In our perspective, the open access principle of OpenSPIM and OpenSpinMicroscopy is a game-changer, helping the concepts of light sheet and optical projection tomography (OPT) to enter the mainstream of biological imaging.

AIMBAT: A Python/Matplotlib Tool for Measuring Teleseismic Arrival Times

NASA Astrophysics Data System (ADS)

Lou, X.; van der Lee, S.; Lloyd, S.

2013-12-01

Python is an open-source, platform-independent, and object-oriented scripting language. It became more popular in the seismologist community since the appearance of ObsPy (Beyreuther et al. 2010, Megies et al. 2011), which provides a powerful framework for seismic data access and processing. This study introduces a new Python-based tool named AIMBAT (Automated and Interactive Measurement of Body-wave Arrival Times) for measuring teleseismic body-wave arrival times on large-scale seismic event data (Lou et al. 2013). Compared to ObsPy, AIMBAT is a lighter tool that is more focused on a particular aspect of seismic data processing. It originates from the widely used MCCC (Multi-Channel Cross-Correlation) method developed by VanDecar and Crosson (1990). On top of the original MCCC procedure, AIMBAT is automated in initial phase picking and is interactive in quality control. The core cross-correlation function is implemented in Fortran to boost up performance in addition to Python. The GUI (graphical user interface) of AIMBAT depends on Matplotlib's GUI-neutral widgets and event-handling API. A number of sorting and (de)selecting options are designed to facilitate the quality control of seismograms. By using AIMBAT, both relative and absolute teleseismic body-wave arrival times are measured. AIMBAT significantly improves efficiency and quality of the measurements. User interaction is needed only to pick the target phase arrival and to set a time window on the array stack. The package is easy to install and use, open-source, and is publicly available. Graphical user interface of AIMBAT.

Investigating common coding of observed and executed actions in the monkey brain using cross-modal multi-variate fMRI classification.

PubMed

Fiave, Prosper Agbesi; Sharma, Saloni; Jastorff, Jan; Nelissen, Koen

2018-05-19

Mirror neurons are generally described as a neural substrate hosting shared representations of actions, by simulating or 'mirroring' the actions of others onto the observer's own motor system. Since single neuron recordings are rarely feasible in humans, it has been argued that cross-modal multi-variate pattern analysis (MVPA) of non-invasive fMRI data is a suitable technique to investigate common coding of observed and executed actions, allowing researchers to infer the presence of mirror neurons in the human brain. In an effort to close the gap between monkey electrophysiology and human fMRI data with respect to the mirror neuron system, here we tested this proposal for the first time in the monkey. Rhesus monkeys either performed reach-and-grasp or reach-and-touch motor acts with their right hand in the dark or observed videos of human actors performing similar motor acts. Unimodal decoding showed that both executed or observed motor acts could be decoded from numerous brain regions. Specific portions of rostral parietal, premotor and motor cortices, previously shown to house mirror neurons, in addition to somatosensory regions, yielded significant asymmetric action-specific cross-modal decoding. These results validate the use of cross-modal multi-variate fMRI analyses to probe the representations of own and others' actions in the primate brain and support the proposed mapping of others' actions onto the observer's own motor cortices. Copyright © 2018 Elsevier Inc. All rights reserved.

An Optimised System for Generating Multi-Resolution Dtms Using NASA Mro Datasets

NASA Astrophysics Data System (ADS)

Tao, Y.; Muller, J.-P.; Sidiropoulos, P.; Veitch-Michaelis, J.; Yershov, V.

2016-06-01

Within the EU FP-7 iMars project, a fully automated multi-resolution DTM processing chain, called Co-registration ASP-Gotcha Optimised (CASP-GO) has been developed, based on the open source NASA Ames Stereo Pipeline (ASP). CASP-GO includes tiepoint based multi-resolution image co-registration and an adaptive least squares correlation-based sub-pixel refinement method called Gotcha. The implemented system guarantees global geo-referencing compliance with respect to HRSC (and thence to MOLA), provides refined stereo matching completeness and accuracy based on the ASP normalised cross-correlation. We summarise issues discovered from experimenting with the use of the open-source ASP DTM processing chain and introduce our new working solutions. These issues include global co-registration accuracy, de-noising, dealing with failure in matching, matching confidence estimation, outlier definition and rejection scheme, various DTM artefacts, uncertainty estimation, and quality-efficiency trade-offs.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Students' Multi-Modal Re-Presentations of Scientific Knowledge and Creativity

ERIC Educational Resources Information Center

Koren, Yitzhak; Klavir, Rama; Gorodetsky, Malka

2005-01-01

The paper brings the results of a project that passed on to students the opportunity for re-presenting their acquired knowledge via the construction of multi-modal "learning resources". These "learning resources" substituted for lectures and books and became the official learning sources in the classroom. The rational for the…

Open source hardware and software platform for robotics and artificial intelligence applications

NASA Astrophysics Data System (ADS)

Liang, S. Ng; Tan, K. O.; Lai Clement, T. H.; Ng, S. K.; Mohammed, A. H. Ali; Mailah, Musa; Azhar Yussof, Wan; Hamedon, Zamzuri; Yussof, Zulkifli

2016-02-01

Recent developments in open source hardware and software platforms (Android, Arduino, Linux, OpenCV etc.) have enabled rapid development of previously expensive and sophisticated system within a lower budget and flatter learning curves for developers. Using these platform, we designed and developed a Java-based 3D robotic simulation system, with graph database, which is integrated in online and offline modes with an Android-Arduino based rubbish picking remote control car. The combination of the open source hardware and software system created a flexible and expandable platform for further developments in the future, both in the software and hardware areas, in particular in combination with graph database for artificial intelligence, as well as more sophisticated hardware, such as legged or humanoid robots.

NASA World Wind, Open Source 4D Geospatial Visualization Platform: *.NET & Java* for EDUCATION

NASA Astrophysics Data System (ADS)

Hogan, P.; Kuehnel, F.

2006-12-01

NASA World Wind has only one goal, to provide the maximum opportunity for geospatial information to be experienced, be it education, science, research, business, or government. The benefits to understanding for information delivered in the context of its 4D virtual reality are extraordinary. The NASA World Wind visualization platform is open source and therefore lends itself well to being extended to service *any* requirements, be they proprietary and commercial or simply available. Data accessibility is highly optimized using standard formats including internationally certified open standards (W*S). Although proprietary applications can be built based on World Wind, and proprietary data delivered that leverage World Wind, there is nothing proprietary about the visualization platform itself or the multiple planetary data sets readily available, including global animations of live weather. NASA World Wind is being used by NASA research teams as well as being a formal part of high school and university curriculum. The National Guard uses World Wind for emergency response activities and State governments have incorporated high resolution imagery for GIS management as well as for their cross-agency emergency response activities. The U.S. federal government uses NASA World Wind for a myriad of GIS and security-related issues (NSA, NGA, DOE, FAA, etc.).

NASA World Wind, Open Source 4D Geospatial Visualization Platform: *.NET & Java*

NASA Astrophysics Data System (ADS)

Hogan, P.; Coughlan, J.

2006-12-01

NASA World Wind has only one goal, to provide the maximum opportunity for geospatial information to be experienced, be it education, science, research, business, or government. The benefits to understanding for information delivered in the context of its 4D virtual reality are extraordinary. The NASA World Wind visualization platform is open source and therefore lends itself well to being extended to service *any* requirements, be they proprietary and commercial or simply available. Data accessibility is highly optimized using standard formats including internationally certified open standards (W*S). Although proprietary applications can be built based on World Wind, and proprietary data delivered that leverage World Wind, there is nothing proprietary about the visualization platform itself or the multiple planetary data sets readily available, including global animations of live weather. NASA World Wind is being used by NASA research teams as well as being a formal part of high school and university curriculum. The National Guard uses World Wind for emergency response activities and State governments have incorporated high resolution imagery for GIS management as well as for their cross-agency emergency response activities. The U.S. federal government uses NASA World Wind for a myriad of GIS and security-related issues (NSA, NGA, DOE, FAA, etc.).

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

Multi-Fidelity Uncertainty Propagation for Cardiovascular Modeling

NASA Astrophysics Data System (ADS)

Fleeter, Casey; Geraci, Gianluca; Schiavazzi, Daniele; Kahn, Andrew; Marsden, Alison

2017-11-01

Hemodynamic models are successfully employed in the diagnosis and treatment of cardiovascular disease with increasing frequency. However, their widespread adoption is hindered by our inability to account for uncertainty stemming from multiple sources, including boundary conditions, vessel material properties, and model geometry. In this study, we propose a stochastic framework which leverages three cardiovascular model fidelities: 3D, 1D and 0D models. 3D models are generated from patient-specific medical imaging (CT and MRI) of aortic and coronary anatomies using the SimVascular open-source platform, with fluid structure interaction simulations and Windkessel boundary conditions. 1D models consist of a simplified geometry automatically extracted from the 3D model, while 0D models are obtained from equivalent circuit representations of blood flow in deformable vessels. Multi-level and multi-fidelity estimators from Sandia's open-source DAKOTA toolkit are leveraged to reduce the variance in our estimated output quantities of interest while maintaining a reasonable computational cost. The performance of these estimators in terms of computational cost reductions is investigated for a variety of output quantities of interest, including global and local hemodynamic indicators. Sandia National Labs is a multimission laboratory managed and operated by NTESS, LLC, for the U.S. DOE under contract DE-NA0003525. Funding for this project provided by NIH-NIBIB R01 EB018302.

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Cross-Modal Correspondence Among Vision, Audition, and Touch in Natural Objects: An Investigation of the Perceptual Properties of Wood.

PubMed

Kanaya, Shoko; Kariya, Kenji; Fujisaki, Waka

2016-10-01

Certain systematic relationships are often assumed between information conveyed from multiple sensory modalities; for instance, a small figure and a high pitch may be perceived as more harmonious. This phenomenon, termed cross-modal correspondence, may result from correlations between multi-sensory signals learned in daily experience of the natural environment. If so, we would observe cross-modal correspondences not only in the perception of artificial stimuli but also in perception of natural objects. To test this hypothesis, we reanalyzed data collected previously in our laboratory examining perceptions of the material properties of wood using vision, audition, and touch. We compared participant evaluations of three perceptual properties (surface brightness, sharpness of sound, and smoothness) of the wood blocks obtained separately via vision, audition, and touch. Significant positive correlations were identified for all properties in the audition-touch comparison, and for two of the three properties regarding in the vision-touch comparison. By contrast, no properties exhibited significant positive correlations in the vision-audition comparison. These results suggest that we learn correlations between multi-sensory signals through experience; however, the strength of this statistical learning is apparently dependent on the particular combination of sensory modalities involved. © The Author(s) 2016.

Earth observing system instrument pointing control modeling for polar orbiting platforms

NASA Technical Reports Server (NTRS)

Briggs, H. C.; Kia, T.; Mccabe, S. A.; Bell, C. E.

1987-01-01

An approach to instrument pointing control performance assessment for large multi-instrument platforms is described. First, instrument pointing requirements and reference platform control systems for the Eos Polar Platforms are reviewed. Performance modeling tools including NASTRAN models of two large platforms, a modal selection procedure utilizing a balanced realization method, and reduced order platform models with core and instrument pointing control loops added are then described. Time history simulations of instrument pointing and stability performance in response to commanded slewing of adjacent instruments demonstrates the limits of tolerable slew activity. Simplified models of rigid body responses are also developed for comparison. Instrument pointing control methods required in addition to the core platform control system to meet instrument pointing requirements are considered.

Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms

NASA Astrophysics Data System (ADS)

Beck, Jeffrey; Bos, Jeremy P.

2017-05-01

We compare several modifications to the open-source wave optics package, WavePy, intended to improve execution time. Specifically, we compare the relative performance of the Intel MKL, a CPU based OpenCV distribution, and GPU-based version. Performance is compared between distributions both on the same compute platform and between a fully-featured computing workstation and the NVIDIA Jetson TX1 platform. Comparisons are drawn in terms of both execution time and power consumption. We have found that substituting the Fast Fourier Transform operation from OpenCV provides a marked improvement on all platforms. In addition, we show that embedded platforms offer some possibility for extensive improvement in terms of efficiency compared to a fully featured workstation.

Free-access open-source e-learning in comprehensive neurosurgery skills training.

PubMed

Jotwani, Payal; Srivastav, Vinkle; Tripathi, Manjul; Deo, Rama Chandra; Baby, Britty; Damodaran, Natesan; Singh, Ramandeep; Suri, Ashish; Bettag, Martin; Roy, Tara Sankar; Busert, Christoph; Mehlitz, Marcus; Lalwani, Sanjeev; Garg, Kanwaljeet; Paul, Kolin; Prasad, Sanjiva; Banerjee, Subhashis; Kalra, Prem; Kumar, Subodh; Sharma, Bhavani Shankar; Mahapatra, Ashok Kumar

2014-01-01

Since the end of last century, technology has taken a front seat in dispersion of medical education. Advancements of technology in neurosurgery and traditional training methods are now being challenged by legal and ethical concerns of patient safety, resident work-hour restriction and cost of operating-room time. To supplement the existing neurosurgery education pattern, various e-learning platforms are introduced as structured, interactive learning system. This study focuses on the concept, formulation, development and impact of web based learning platforms dedicated to neurosurgery discipline to disseminate education, supplement surgical knowledge and improve skills of neurosurgeons. 'Neurosurgery Education and Training School (NETS), e-learning platform' has integration of web-based technologies like 'Content Management System' for organizing the education material and 'Learning Management System' for updating neurosurgeons. NETS discussion forum networks neurosurgeons, neuroscientists and neuro-technologists across the globe facilitating collaborative translational research. Multi-authored neurosurgical e-learning material supplements the deficiencies of regular time-bound education. Interactive open-source, global, free-access e-learning platform of NETS has around 1) 425 visitors/month from 73 countries; ratio of new visitors to returning visitors 42.3; 57.7 (2); 64,380 views from 190 subscribers for surgical videos, 3-D animation, graphics based training modules (3); average 402 views per post. The e-Learning platforms provide updated educational content that make them "quick, surf, find and extract" resources. e-Learning tools like web-based education, social interactive platform and question-answer forum will save unnecessary expenditure of time and travel of neurosurgeons seeking knowledge. The need for free access platforms is more pronounced for the neurosurgeons and patients in developing nations.

An Interprofessional Web-Based Resource for Health Professions Preceptors

PubMed Central

McLeod, Elizabeth; Kwong, Mona; Tidball, Glynnis; Collins, John; Neufeld, Lois; Drynan, Donna

2012-01-01

Objective. To develop a Web-based preceptor education resource for healthcare professionals and evaluate its usefulness. Methods. Using an open source platform, 8 online modules called “E-tips for Practice Education” (E-tips) were developed that focused on topics identified relevant across healthcare disciplines. A cross-sectional survey design was used to evaluate the online resource. Ninety preceptors from 10 health disciplines affiliated with the University of British Columbia evaluated the E-tips. Results. The modules were well received by preceptors, with all participants indicating that they would recommend these modules to their colleagues, over 80% indicating the modules were very to extremely applicable, and over 60% indicating that E-tips had increased their confidence in their ability to teach. Conclusion. Participants reported E-tips to be highly applicable to their teaching role as preceptors. Given their multidisciplinary focus, these modules address a shared language and ideas about clinical teaching among those working in multi-disciplinary settings. PMID:23193332

Sonification Prototype for Space Physics

NASA Astrophysics Data System (ADS)

Candey, R. M.; Schertenleib, A. M.; Diaz Merced, W. L.

2005-12-01

As an alternative and adjunct to visual displays, auditory exploration of data via sonification (data controlled sound) and audification (audible playback of data samples) is promising for complex or rapidly/temporally changing visualizations, for data exploration of large datasets (particularly multi-dimensional datasets), and for exploring datasets in frequency rather than spatial dimensions (see also International Conferences on Auditory Display ). Besides improving data exploration and analysis for most researchers, the use of sound is especially valuable as an assistive technology for visually-impaired people and can make science and math more exciting for high school and college students. Only recently have the hardware and software come together to make a cross-platform open-source sonification tool feasible. We have developed a prototype sonification data analysis tool using the JavaSound API and NASA GSFC's ViSBARD software . Wanda Diaz Merced, a blind astrophysicist from Puerto Rico, is instrumental in advising on and testing the tool.

Object discrimination using optimized multi-frequency auditory cross-modal haptic feedback.

PubMed

Gibson, Alison; Artemiadis, Panagiotis

2014-01-01

As the field of brain-machine interfaces and neuro-prosthetics continues to grow, there is a high need for sensor and actuation mechanisms that can provide haptic feedback to the user. Current technologies employ expensive, invasive and often inefficient force feedback methods, resulting in an unrealistic solution for individuals who rely on these devices. This paper responds through the development, integration and analysis of a novel feedback architecture where haptic information during the neural control of a prosthetic hand is perceived through multi-frequency auditory signals. Through representing force magnitude with volume and force location with frequency, the feedback architecture can translate the haptic experiences of a robotic end effector into the alternative sensory modality of sound. Previous research with the proposed cross-modal feedback method confirmed its learnability, so the current work aimed to investigate which frequency map (i.e. frequency-specific locations on the hand) is optimal in helping users distinguish between hand-held objects and tasks associated with them. After short use with the cross-modal feedback during the electromyographic (EMG) control of a prosthetic hand, testing results show that users are able to use audial feedback alone to discriminate between everyday objects. While users showed adaptation to three different frequency maps, the simplest map containing only two frequencies was found to be the most useful in discriminating between objects. This outcome provides support for the feasibility and practicality of the cross-modal feedback method during the neural control of prosthetics.

KiT: a MATLAB package for kinetochore tracking.

PubMed

Armond, Jonathan W; Vladimirou, Elina; McAinsh, Andrew D; Burroughs, Nigel J

2016-06-15

During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. Supplementary data are available at Bioinformatics online. jonathan.armond@warwick.ac.uk. © The Author 2016. Published by Oxford University Press.

Open source posturography.

PubMed

Rey-Martinez, Jorge; Pérez-Fernández, Nicolás

2016-12-01

The proposed validation goal of 0.9 in intra-class correlation coefficient was reached with the results of this study. With the obtained results we consider that the developed software (RombergLab) is a validated balance assessment software. The reliability of this software is dependent of the used force platform technical specifications. Develop and validate a posturography software and share its source code in open source terms. Prospective non-randomized validation study: 20 consecutive adults underwent two balance assessment tests, six condition posturography was performed using a clinical approved software and force platform and the same conditions were measured using the new developed open source software using a low cost force platform. Intra-class correlation index of the sway area obtained from the center of pressure variations in both devices for the six conditions was the main variable used for validation. Excellent concordance between RombergLab and clinical approved force platform was obtained (intra-class correlation coefficient =0.94). A Bland and Altman graphic concordance plot was also obtained. The source code used to develop RombergLab was published in open source terms.

Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework

PubMed Central

Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

2017-01-01

In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts. PMID:28360851

Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.

PubMed

Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

2017-01-01

In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts.

Digital Storytelling: Reinventing Literature Circles

ERIC Educational Resources Information Center

Tobin, Maryann Tatum

2012-01-01

New literacies in reading research demand the study of comprehension skills using multiple modalities through a more complex, multi-platform view of reading. Taking into account the robust roll of technology in our daily lives, this article presents an update to the traditional literature circle lesson to include digital storytelling and…

Temporal and modal characterization of DoD source air toxic ...

EPA Pesticide Factsheets

This project tested three, real-/near real-time monitoring techniques to develop air toxic emission factors for Department of Defense (DoD) platform sources. These techniques included: resonance enhanced multi photon ionization time of flight mass spectrometry (REMPI-TOFMS) for organic air toxics, laser induced breakdown spectroscopy (LIBS) for metallic air toxics, and optical remote sensing (ORS) methods for measurement of criteria pollutants and other hazardous air pollutants (HAPs). Conventional emission measurements were used for verification of the real-time monitoring results. The REMPI-TOFMS system was demonstrated on the following: --a United States U.S. Marine Corps (USMC) diesel generator, --a U.S. Air Force auxiliary power unit (APU), --the waste combustor at the Portsmouth Naval Shipyard, during a multi-monitor environmental technology verification (ETV) test for dioxin monitoring systems, --two dynamometer-driven high mobility multi-purpose wheeled vehicles (HMMWVs), --an idling Abrams battle tank, --a Bradley infantry fighting vehicle (IFV), and --an F-15 and multiple F-22 U.S. Air Force aircraft engines. LIBS was tested and applied solely to the U.S. Marine Corps diesel generator. The high detection limits of LIBS for toxic metals limited its usefulness as a real time analyzer for most DoD sources. ORS was tested only on the APU with satisfactory results for non-condensable combustion products (carbon monoxide [CO], carbon dioxide

Sirepo - Warp

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagler, Robert; Moeller, Paul

Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jin-ja, which is a secure andmore » widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is Warp. Warp is a particle-in-cell (PIC) code de-signed to simulate high-intensity charged particle beams and plasmas in both the electrostatic and electromagnetic regimes, with a wide variety of integrated physics models and diagnostics. At pre-sent, Sirepo supports a small subset of Warp’s capabilities. Warp is open source and is part of the Berkeley Lab Accelerator Simulation Toolkit.« less

DStat: A Versatile, Open-Source Potentiostat for Electroanalysis and Integration.

PubMed

Dryden, Michael D M; Wheeler, Aaron R

2015-01-01

Most electroanalytical techniques require the precise control of the potentials in an electrochemical cell using a potentiostat. Commercial potentiostats function as "black boxes," giving limited information about their circuitry and behaviour which can make development of new measurement techniques and integration with other instruments challenging. Recently, a number of lab-built potentiostats have emerged with various design goals including low manufacturing cost and field-portability, but notably lacking is an accessible potentiostat designed for general lab use, focusing on measurement quality combined with ease of use and versatility. To fill this gap, we introduce DStat (http://microfluidics.utoronto.ca/dstat), an open-source, general-purpose potentiostat for use alone or integrated with other instruments. DStat offers picoampere current measurement capabilities, a compact USB-powered design, and user-friendly cross-platform software. DStat is easy and inexpensive to build, may be modified freely, and achieves good performance at low current levels not accessible to other lab-built instruments. In head-to-head tests, DStat's voltammetric measurements are much more sensitive than those of "CheapStat" (a popular open-source potentiostat described previously), and are comparable to those of a compact commercial "black box" potentiostat. Likewise, in head-to-head tests, DStat's potentiometric precision is similar to that of a commercial pH meter. Most importantly, the versatility of DStat was demonstrated through integration with the open-source DropBot digital microfluidics platform. In sum, we propose that DStat is a valuable contribution to the "open source" movement in analytical science, which is allowing users to adapt their tools to their experiments rather than alter their experiments to be compatible with their tools.

Planetary-scale surface water detection from space

NASA Astrophysics Data System (ADS)

Donchyts, G.; Baart, F.; Winsemius, H.; Gorelick, N.

2017-12-01

Accurate, efficient and high-resolution methods of surface water detection are needed for a better water management. Datasets on surface water extent and dynamics are crucial for a better understanding of natural and human-made processes, and as an input data for hydrological and hydraulic models. In spite of considerable progress in the harmonization of freely available satellite data, producing accurate and efficient higher-level surface water data products remains very challenging. This presentation will provide an overview of existing methods for surface water extent and change detection from multitemporal and multi-sensor satellite imagery. An algorithm to detect surface water changes from multi-temporal satellite imagery will be demonstrated as well as its open-source implementation (http://aqua-monitor.deltares.nl). This algorithm was used to estimate global surface water changes at high spatial resolution. These changes include climate change, land reclamation, reservoir construction/decommissioning, erosion/accretion, and many other. This presentation will demonstrate how open satellite data and open platforms such as Google Earth Engine have helped with this research.

OpenStereo: Open Source, Cross-Platform Software for Structural Geology Analysis

NASA Astrophysics Data System (ADS)

Grohmann, C. H.; Campanha, G. A.

2010-12-01

Free and open source software (FOSS) are increasingly seen as synonyms of innovation and progress. Freedom to run, copy, distribute, study, change and improve the software (through access to the source code) assure a high level of positive feedback between users and developers, which results in stable, secure and constantly updated systems. Several software packages for structural geology analysis are available to the user, with commercial licenses or that can be downloaded at no cost from the Internet. Some provide basic tools of stereographic projections such as plotting poles, great circles, density contouring, eigenvector analysis, data rotation etc, while others perform more specific tasks, such as paleostress or geotechnical/rock stability analysis. This variety also means a wide range of data formating for input, Graphical User Interface (GUI) design and graphic export format. The majority of packages is built for MS-Windows and even though there are packages for the UNIX-based MacOS, there aren't native packages for *nix (UNIX, Linux, BSD etc) Operating Systems (OS), forcing the users to run these programs with emulators or virtual machines. Those limitations lead us to develop OpenStereo, an open source, cross-platform software for stereographic projections and structural geology. The software is written in Python, a high-level, cross-platform programming language and the GUI is designed with wxPython, which provide a consistent look regardless the OS. Numeric operations (like matrix and linear algebra) are performed with the Numpy module and all graphic capabilities are provided by the Matplolib library, including on-screen plotting and graphic exporting to common desktop formats (emf, eps, ps, pdf, png, svg). Data input is done with simple ASCII text files, with values of dip direction and dip/plunge separated by spaces, tabs or commas. The user can open multiple file at the same time (or the same file more than once), and overlay different elements of each dataset (poles, great circles etc). The GUI shows the opened files in a tree structure, similar to “layers” of many illustration software, where the vertical order of the files in the tree reflects the drawing order of the selected elements. At this stage, the software performs plotting operations of poles to planes, lineations, great circles, density contours and rose diagrams. A set of statistics is calculated for each file and its eigenvalues and eigenvectors are used to suggest if the data is clustered about a mean value or distributed along a girdle. Modified Flinn, Triangular and histograms plots are also available. Next step of development will focus on tools as merging and rotation of datasets, possibility to save 'projects' and paleostress analysis. In its current state, OpenStereo requires Python, wxPython, Numpy and Matplotlib installed in the system. We recommend installing PythonXY or the Enthought Python Distribution on MS-Windows and MacOS machines, since all dependencies are provided. Most Linux distributions provide an easy way to install all dependencies through software repositories. OpenStereo is released under the GNU General Public License. Programmers willing to contribute are encouraged to contact the authors directly. FAPESP Grant #09/17675-5

TERRA REF: Advancing phenomics with high resolution, open access sensor and genomics data

NASA Astrophysics Data System (ADS)

LeBauer, D.; Kooper, R.; Burnette, M.; Willis, C.

2017-12-01

Automated plant measurement has the potential to improve understanding of genetic and environmental controls on plant traits (phenotypes). The application of sensors and software in the automation of high throughput phenotyping reflects a fundamental shift from labor intensive hand measurements to drone, tractor, and robot mounted sensing platforms. These tools are expected to speed the rate of crop improvement by enabling plant breeders to more accurately select plants with improved yields, resource use efficiency, and stress tolerance. However, there are many challenges facing high throughput phenomics: sensors and platforms are expensive, currently there are few standard methods of data collection and storage, and the analysis of large data sets requires high performance computers and automated, reproducible computing pipelines. To overcome these obstacles and advance the science of high throughput phenomics, the TERRA Phenotyping Reference Platform (TERRA-REF) team is developing an open-access database of high resolution sensor data. TERRA REF is an integrated field and greenhouse phenotyping system that includes: a reference field scanner with fifteen sensors that can generate terrabytes of data each day at mm resolution; UAV, tractor, and fixed field sensing platforms; and an automated controlled-environment scanner. These platforms will enable investigation of diverse sensing modalities, and the investigation of traits under controlled and field environments. It is the goal of TERRA REF to lower the barrier to entry for academic and industry researchers by providing high-resolution data, open source software, and online computing resources. Our project is unique in that all data will be made fully public in November 2018, and is already available to early adopters through the beta-user program. We will describe the datasets and how to use them as well as the databases and computing pipeline and how these can be reused and remixed in other phenomics pipelines. Finally, we will describe the National Data Service workbench, a cloud computing platform that can access the petabyte scale data while supporting reproducible research.

CAGE IIIA Distributed Simulation Design Methodology

DTIC Science & Technology

2014-05-01

2 VHF Very High Frequency VLC Video LAN Codec – an Open-source cross-platform multimedia player and framework VM Virtual Machine VOIP Voice Over...Implementing Defence Experimentation (GUIDEx). The key challenges for this methodology are with understanding how to: • design it o define the...operation and to be available in the other nation’s simulations. The challenge for the CAGE campaign of experiments is to continue to build upon this

Cross-modal working memory binding and word recognition skills: how specific is the link?

PubMed

Wang, Shinmin; Allen, Richard J

2018-04-01

Recent research has suggested that the creation of temporary bound representations of information from different sources within working memory uniquely relates to word recognition abilities in school-age children. However, it is unclear to what extent this link is attributable specifically to the binding ability for cross-modal information. This study examined the performance of Grade 3 (8-9 years old) children on binding tasks requiring either temporary association formation of two visual items (i.e., within-modal binding) or pairs of visually presented abstract shapes and auditorily presented nonwords (i.e., cross-modal binding). Children's word recognition skills were related to performance on the cross-modal binding task but not on the within-modal binding task. Further regression models showed that cross-modal binding memory was a significant predictor of word recognition when memory for its constituent elements, general abilities, and crucially, within-modal binding memory were taken into account. These findings may suggest a specific link between the ability to bind information across modalities within working memory and word recognition skills.

Sensor Networks, Dataloggers, and Other Handy Gadgets Using Open-Source Electronics for the Christina River Basin CZO

NASA Astrophysics Data System (ADS)

Hicks, S. D.; Aufdenkampe, A. K.; Montgomery, D. S.

2011-12-01

The search for biogeochemical "hot spots" and "hot moments" that control ecosystem-level processes requires a rethinking of how we observe the environment. Extensive multi-sensor/measurement arrays are required to realize 2D, 3D, or 4D maps of environmental properties with sufficient spatial and temporal resolution to find and understand hot spots and hot moments. To date, the cost of the data logging and communication infrastructure has been a major limitation to large-scale sensor deployment, especially for near-real-time (NRT) wireless networks. A low-cost, user-friendly alternative is needed so that resources can be prioritized toward sensor hardware rather than data acquisition and communication hardware. A flexible development platform would also allow for easy creation of other useful devices in addition to the already apparent need for economical dataloggers. The recent proliferation of open-source electronics platforms offers an opportunity for environmental observatories to deploy sensors at large scales by reducing data logging and communications costs by more than an order of magnitude. Leading the open-source electronics revolution is the Arduino project, designed to make the process of using electronics in multidisciplinary projects more accessible to hobbyists and professionals alike. A large user community has developed and shared hundreds of practical applications for projects that interface with a variety of sensors and use embedded logic to control external hardware. Likewise, dozens of companies and individuals sell low-cost Arduino-compatible boards that can connect together in a modular framework, allowing the user to quickly create devices for a wide range of applications. Based on these open-source technologies and products, we are designing and building a variety of circuit devices for use in our research watersheds. One Arduino-based device is a multi-channel datalogger that can be used with a variety of analog and digital sensors, such as pressure transducers, conductivity sensors, soil moisture and temperature probes, and redox probes. Radio modules can be added to the loggers to create a self-meshing wireless network for streaming live sensor data. A variation of the logger circuit is a smaller handheld unit with a text display that can be used when testing sensors in the field. Another useful custom device is a remote streamwater sampling system, made up of an Arduino circuit and a prepaid cell phone, allowing a user to remotely control multiple pumps by following interactive voice menus and hearing live sensor value readouts. In the lab, an Arduino circuit is used in a multi-chamber CO2 respiration experiment where it is controlling dozens of solenoid valves and logging the data from the analytical instruments. One of the biggest benefits of open source hardware is the low cost of the components. Each of the devices we have built costs less than $100 and can be assembled in a few hours. These circuits could easily be adapted to other applications or interfaced with other sensors in a variety of configurations, making the Arduino platform an incredibly useful tool for researchers.

EPRI and Schneider Electric Demonstrate Distributed Resource Communications

Science.gov Websites

Electric Power Research Institute (EPRI) is designing, building, and testing a flexible, open-source Schneider Electric ADMS, open software platforms, an open-platform home energy management system

OMPC: an Open-Source MATLAB®-to-Python Compiler

PubMed Central

Jurica, Peter; van Leeuwen, Cees

2008-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB®, the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB®-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB® functions into Python programs. The imported MATLAB® modules will run independently of MATLAB®, relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB®. OMPC is available at http://ompc.juricap.com. PMID:19225577

On the prospects of cross-calibrating the Cherenkov Telescope Array with an airborne calibration platform

NASA Astrophysics Data System (ADS)

Brown, Anthony M.

2018-01-01

Recent advances in unmanned aerial vehicle (UAV) technology have made UAVs an attractive possibility as an airborne calibration platform for astronomical facilities. This is especially true for arrays of telescopes spread over a large area such as the Cherenkov Telescope Array (CTA). In this paper, the feasibility of using UAVs to calibrate CTA is investigated. Assuming a UAV at 1km altitude above CTA, operating on astronomically clear nights with stratified, low atmospheric dust content, appropriate thermal protection for the calibration light source and an onboard photodiode to monitor its absolute light intensity, inter-calibration of CTA's telescopes of the same size class is found to be achievable with a 6 - 8 % uncertainty. For cross-calibration of different telescope size classes, a systematic uncertainty of 8 - 10 % is found to be achievable. Importantly, equipping the UAV with a multi-wavelength calibration light source affords us the ability to monitor the wavelength-dependent degradation of CTA telescopes' optical system, allowing us to not only maintain this 6 - 10 % uncertainty after the first few years of telescope deployment, but also to accurately account for the effect of multi-wavelength degradation on the cross-calibration of CTA by other techniques, namely with images of air showers and local muons. A UAV-based system thus provides CTA with several independent and complementary methods of cross-calibrating the optical throughput of individual telescopes. Furthermore, housing environmental sensors on the UAV system allows us to not only minimise the systematic uncertainty associated with the atmospheric transmission of the calibration signal, it also allows us to map the dust content above CTA as well as monitor the temperature, humidity and pressure profiles of the first kilometre of atmosphere above CTA with each UAV flight.

OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data.

PubMed

Wenig, Philip; Odermatt, Juergen

2010-07-30

Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform. This work describes a native approach to handle chromatographic data files. The approach can be extended in its functionality such as facilities to detect baselines, to detect, integrate and identify peaks and to compare mass spectra, as well as the ability to internationalize the application. Additionally, filters can be applied on the chromatographic data to enhance its quality, for example to remove background and noise. Extended operations like do, undo and redo are supported. OpenChrom is a software application to edit and analyze mass spectrometric chromatographic data. It is extensible in many different ways, depending on the demands of the users or the analytical procedures and algorithms. It offers a customizable graphical user interface. The software is independent of the operating system, due to the fact that the Rich Client Platform is written in Java. OpenChrom is released under the Eclipse Public License 1.0 (EPL). There are no license constraints regarding extensions. They can be published using open source as well as proprietary licenses. OpenChrom is available free of charge at http://www.openchrom.net.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

Open-Source Learning Management System and Web 2.0 Online Social Software Applications as Learning Platforms for an Elementary School in Singapore

ERIC Educational Resources Information Center

Tay, Lee Yong; Lim, Cher Ping; Lye, Sze Yee; Ng, Kay Joo; Lim, Siew Khiaw

2011-01-01

This paper analyses how an elementary-level future school in Singapore implements and uses various open-source online platforms, which are easily available online and could be implemented with minimal software cost, for the purpose of teaching and learning. Online platforms have the potential to facilitate students' engagement for independent and…

A gantry-based tri-modality system for bioluminescence tomography

PubMed Central

Yan, Han; Lin, Yuting; Barber, William C.; Unlu, Mehmet Burcin; Gulsen, Gultekin

2012-01-01

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information. PMID:22559540

77 FR 33739 - Announcement of Requirements and Registration for “Health Data Platform Metadata Challenge”

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-07

... Information Technology. SUMMARY: As part of the HHS Open Government Plan, the HealthData.gov Platform (HDP) is... application of existing voluntary consensus standards for metadata common to all open government data, and... vocabulary recommendations for Linked Data publishers, defining cross domain semantic metadata of open...

Global Health Innovation Technology Models.

PubMed

Harding, Kimberly

2016-01-01

Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC) research collaborators directly prevent the growth of sustainable Global Health innovation for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utilizing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to accelerate their clinical trial process maturity in the field of drug discovery, population health innovation initiatives and public domain knowledge networks. When sponsored, this concept will be tested by 12 confirmed clinical research and public health organizations in six countries. The potential impact of this platform is reduced drug discovery and public health innovation lag time and improved clinical trial interventions, due to reliable clinical intelligence and bio-surveillance across all phases of the clinical innovation process.

Global Health Innovation Technology Models

PubMed Central

Harding, Kimberly

2016-01-01

Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC) research collaborators directly prevent the growth of sustainable Global Health innovation for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utilizing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to accelerate their clinical trial process maturity in the field of drug discovery, population health innovation initiatives and public domain knowledge networks. When sponsored, this concept will be tested by 12 confirmed clinical research and public health organizations in six countries. The potential impact of this platform is reduced drug discovery and public health innovation lag time and improved clinical trial interventions, due to reliable clinical intelligence and bio-surveillance across all phases of the clinical innovation process.

CompactPCI/Linux Platform in FTU Slow Control System

NASA Astrophysics Data System (ADS)

Iannone, F.; Wang, L.; Centioli, C.; Panella, M.; Mazza, G.; Vitale, V.

2004-12-01

In large fusion experiments, such as tokamak devices, there is a common trend for slow control systems. Because of complexity of the plants, the so-called `Standard Model' (SM) in slow control has been adopted on several tokamak machines. This model is based on a three-level hierarchical control: 1) High-Level Control (HLC) with a supervisory function; 2) Medium-Level Control (MLC) to interface and concentrate I/O field equipments; 3) Low-Level Control (LLC) with hard real-time I/O function, often managed by PLCs. FTU control system designed with SM concepts has underwent several stages of developments in its fifteen years duration of runs. The latest evolution was inevitable, due to the obsolescence of the MLC CPUs, based on VME-MOTOROLA 68030 with OS9 operating system. A large amount of C code was developed for that platform to route the data flow from LLC, which is constituted by 24 Westinghouse Numalogic PC-700 PLCs with about 8000 field-points, to HLC, based on a commercial Object-Oriented Real-Time database on Alpha/CompaqTru64 platform. Therefore, we have to look for cost-effective solutions and finally a CompactPCI-Intel x86 platform with Linux operating system was chosen. A software porting has been done, taking into account the differences between OS9 and Linux operating system in terms of Inter/Network Processes Communications and I/O multi-ports serial driver. This paper describes the hardware/software architecture of the new MLC system, emphasizing the reliability and the low costs of the open source solutions. Moreover, a huge amount of software packages available in open source environment will assure a less painful maintenance, and will open the way to further improvements of the system itself.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.

PubMed

Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

PubMed Central

Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA PMID:27499741

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

An i2b2-based, generalizable, open source, self-scaling chronic disease registry

PubMed Central

Quan, Justin; Ortiz, David M; Bousvaros, Athos; Ilowite, Norman T; Inman, Christi J; Marsolo, Keith; McMurry, Andrew J; Sandborg, Christy I; Schanberg, Laura E; Wallace, Carol A; Warren, Robert W; Weber, Griffin M; Mandl, Kenneth D

2013-01-01

Objective Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. Materials and methods Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. Results The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. Discussion We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. Conclusions The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases. PMID:22733975

An i2b2-based, generalizable, open source, self-scaling chronic disease registry.

PubMed

Natter, Marc D; Quan, Justin; Ortiz, David M; Bousvaros, Athos; Ilowite, Norman T; Inman, Christi J; Marsolo, Keith; McMurry, Andrew J; Sandborg, Christy I; Schanberg, Laura E; Wallace, Carol A; Warren, Robert W; Weber, Griffin M; Mandl, Kenneth D

2013-01-01

Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.

General Mission Analysis Tool (GMAT) Architectural Specification. Draft

NASA Technical Reports Server (NTRS)

Hughes, Steven P.; Conway, Darrel, J.

2007-01-01

Early in 2002, Goddard Space Flight Center (GSFC) began to identify requirements for the flight dynamics software needed to fly upcoming missions that use formations of spacecraft to collect data. These requirements ranged from low level modeling features to large scale interoperability requirements. In 2003 we began work on a system designed to meet these requirement; this system is GMAT. The General Mission Analysis Tool (GMAT) is a general purpose flight dynamics modeling tool built on open source principles. The GMAT code is written in C++, and uses modern C++ constructs extensively. GMAT can be run through either a fully functional Graphical User Interface (GUI) or as a command line program with minimal user feedback. The system is built and runs on Microsoft Windows, Linux, and Macintosh OS X platforms. The GMAT GUI is written using wxWidgets, a cross platform library of components that streamlines the development and extension of the user interface Flight dynamics modeling is performed in GMAT by building components that represent the players in the analysis problem that is being modeled. These components interact through the sequential execution of instructions, embodied in the GMAT Mission Sequence. A typical Mission Sequence will model the trajectories of a set of spacecraft evolving over time, calculating relevant parameters during this propagation, and maneuvering individual spacecraft to maintain a set of mission constraints as established by the mission analyst. All of the elements used in GMAT for mission analysis can be viewed in the GMAT GUI or through a custom scripting language. Analysis problems modeled in GMAT are saved as script files, and these files can be read into GMAT. When a script is read into the GMAT GUI, the corresponding user interface elements are constructed in the GMAT GUI. The GMAT system was developed from the ground up to run in a platform agnostic environment. The source code compiles on numerous different platforms, and is regularly exercised running on Windows, Linux and Macintosh computers by the development and analysis teams working on the project. The system can be run using either a graphical user interface, written using the open source wxWidgets framework, or from a text console. The GMAT source code was written using open source tools. GSFC has released the code using the NASA open source license.

Crossing the Virtual World Barrier with OpenAvatar

NASA Technical Reports Server (NTRS)

Joy, Bruce; Kavle, Lori; Tan, Ian

2012-01-01

There are multiple standards and formats for 3D models in virtual environments. The problem is that there is no open source platform for generating models out of discrete parts; this results in the process of having to "reinvent the wheel" when new games, virtual worlds and simulations want to enable their users to create their own avatars or easily customize in-world objects. OpenAvatar is designed to provide a framework to allow artists and programmers to create reusable assets which can be used by end users to generate vast numbers of complete models that are unique and functional. OpenAvatar serves as a framework which facilitates the modularization of 3D models allowing parts to be interchanged within a set of logical constraints.

Statistical learning of multisensory regularities is enhanced in musicians: An MEG study.

PubMed

Paraskevopoulos, Evangelos; Chalas, Nikolas; Kartsidis, Panagiotis; Wollbrink, Andreas; Bamidis, Panagiotis

2018-07-15

The present study used magnetoencephalography (MEG) to identify the neural correlates of audiovisual statistical learning, while disentangling the differential contributions of uni- and multi-modal statistical mismatch responses in humans. The applied paradigm was based on a combination of a statistical learning paradigm and a multisensory oddball one, combining an audiovisual, an auditory and a visual stimulation stream, along with the corresponding deviances. Plasticity effects due to musical expertise were investigated by comparing the behavioral and MEG responses of musicians to non-musicians. The behavioral results indicated that the learning was successful for both musicians and non-musicians. The unimodal MEG responses are consistent with previous studies, revealing the contribution of Heschl's gyrus for the identification of auditory statistical mismatches and the contribution of medial temporal and visual association areas for the visual modality. The cortical network underlying audiovisual statistical learning was found to be partly common and partly distinct from the corresponding unimodal networks, comprising right temporal and left inferior frontal sources. Musicians showed enhanced activation in superior temporal and superior frontal gyrus. Connectivity and information processing flow amongst the sources comprising the cortical network of audiovisual statistical learning, as estimated by transfer entropy, was reorganized in musicians, indicating enhanced top-down processing. This neuroplastic effect showed a cross-modal stability between the auditory and audiovisual modalities. Copyright © 2018 Elsevier Inc. All rights reserved.

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration.

PubMed

Ikumi, Nara; Soto-Faraco, Salvador

2016-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands.

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration

PubMed Central

Ikumi, Nara; Soto-Faraco, Salvador

2017-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands. PMID:28154529

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

PubMed

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W; Gautier, Virginie W

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells

PubMed Central

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W.; Gautier, Virginie W.

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip. PMID:26485569

Virtual Observer Controller (VOC) for Small Unit Infantry Laser Simulation Training

DTIC Science & Technology

2007-04-01

per-seat license when deployed. As a result, ViaVoice was abandoned early in development. Next, the SPHINX engine from Carnegie Mellon University was...examined. Sphinx is Java-based software, providing cross-platform functionality, and it is also free, open-source software. Software developers at...IST had experience using SPHINX , so it was initially selected it to be the VOC speech engine. After implementing a small portion of the VOC grammar

Study of Adversarial and Defensive Components in an Experimental Machinery Control Systems Laboratory Environment

DTIC Science & Technology

2014-09-01

prevention system (IPS), capable of performing real-time traffic analysis and packet logging on IP networks [25]. Snort’s features include protocol... analysis and content searching/matching. Snort can detect a variety of attacks and network probes, such as buffer overflows, port scans and OS...www.digitalbond.com/tools/the- rack/jtr-s7-password-cracking/ Kismet Mike Kershaw Cross- platform Open source wireless network detector and wireless sniffer

Media-Education Convergence: Applying Transmedia Storytelling Edutainment in E-Learning Environments

ERIC Educational Resources Information Center

Kalogeras, Stavroula

2013-01-01

In the era of media convergence, transmedia (cross-media/cross-platform/multi-platform) narratives are catering to users who are willing to immerse themselves in their favorite entertainment content. The inherent interactivity of the Internet and the emotional engagement of story can lead to innovative pedagogies in media rich environments. This…

DStat: A Versatile, Open-Source Potentiostat for Electroanalysis and Integration

PubMed Central

Dryden, Michael D. M.; Wheeler, Aaron R.

2015-01-01

Most electroanalytical techniques require the precise control of the potentials in an electrochemical cell using a potentiostat. Commercial potentiostats function as “black boxes,” giving limited information about their circuitry and behaviour which can make development of new measurement techniques and integration with other instruments challenging. Recently, a number of lab-built potentiostats have emerged with various design goals including low manufacturing cost and field-portability, but notably lacking is an accessible potentiostat designed for general lab use, focusing on measurement quality combined with ease of use and versatility. To fill this gap, we introduce DStat (http://microfluidics.utoronto.ca/dstat), an open-source, general-purpose potentiostat for use alone or integrated with other instruments. DStat offers picoampere current measurement capabilities, a compact USB-powered design, and user-friendly cross-platform software. DStat is easy and inexpensive to build, may be modified freely, and achieves good performance at low current levels not accessible to other lab-built instruments. In head-to-head tests, DStat’s voltammetric measurements are much more sensitive than those of “CheapStat” (a popular open-source potentiostat described previously), and are comparable to those of a compact commercial “black box” potentiostat. Likewise, in head-to-head tests, DStat’s potentiometric precision is similar to that of a commercial pH meter. Most importantly, the versatility of DStat was demonstrated through integration with the open-source DropBot digital microfluidics platform. In sum, we propose that DStat is a valuable contribution to the “open source” movement in analytical science, which is allowing users to adapt their tools to their experiments rather than alter their experiments to be compatible with their tools. PMID:26510100

OMPC: an Open-Source MATLAB-to-Python Compiler.

PubMed

Jurica, Peter; van Leeuwen, Cees

2009-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

Design of Control Plane Architecture Based on Cloud Platform and Experimental Network Demonstration for Multi-domain SDON

NASA Astrophysics Data System (ADS)

Li, Ming; Yin, Hongxi; Xing, Fangyuan; Wang, Jingchao; Wang, Honghuan

2016-02-01

With the features of network virtualization and resource programming, Software Defined Optical Network (SDON) is considered as the future development trend of optical network, provisioning a more flexible, efficient and open network function, supporting intraconnection and interconnection of data centers. Meanwhile cloud platform can provide powerful computing, storage and management capabilities. In this paper, with the coordination of SDON and cloud platform, a multi-domain SDON architecture based on cloud control plane has been proposed, which is composed of data centers with database (DB), path computation element (PCE), SDON controller and orchestrator. In addition, the structure of the multidomain SDON orchestrator and OpenFlow-enabled optical node are proposed to realize the combination of centralized and distributed effective management and control platform. Finally, the functional verification and demonstration are performed through our optical experiment network.

Combination of microneedle radiofrequency (RF), fractional RF skin resurfacing and multi-source non-ablative skin tightening for minimal-downtime, full-face skin rejuvenation.

PubMed

Kaplan, Haim; Kaplan, Lilach

2016-12-01

In the recent years, there is a growth in demand for radiofrequency (RF)-based procedures to improve skin texture, laxity and contour. The new generation of systems allow non-invasive and fractional resurfacing treatments on one platform. The aim of this study was to evaluate the safety and efficacy of a new treatment protocol using a multisource RF, combining 3 different modalities in each patient: [1] non-ablative RF skin tightening, [2] fractional skin resurfacing, and [3] microneedling RF for non-ablative coagulation and collagen remodelling. 14 subjects were enrolled in this study using EndyMed PRO ™ platform. Each patient had 8 non-ablative treatments and 4 fractional treatments (fractional skin resurfacing and Intensif). The global aesthetic score was used to evaluate improvement. All patients had improvement in skin appearance. About 43% had excellent or very good improvement above 50%, 18% had good improvement between 25 and 50%, and the rest 39% had a mild improvement of < 25%. Downtime was minimal and no adverse effect was reported. Our data show significant improvement of skin texture, skin laxity and wrinkle reduction achieved using RF treatment platform.

MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

NASA Astrophysics Data System (ADS)

Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

2018-05-01

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

Cross-platform validation and analysis environment for particle physics

NASA Astrophysics Data System (ADS)

Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.

2017-11-01

A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for online validation of Monte Carlo event samples through a web interface.

SNPConvert: SNP Array Standardization and Integration in Livestock Species.

PubMed

Nicolazzi, Ezequiel Luis; Marras, Gabriele; Stella, Alessandra

2016-06-09

One of the main advantages of single nucleotide polymorphism (SNP) array technology is providing genotype calls for a specific number of SNP markers at a relatively low cost. Since its first application in animal genetics, the number of available SNP arrays for each species has been constantly increasing. However, conversely to that observed in whole genome sequence data analysis, SNP array data does not have a common set of file formats or coding conventions for allele calling. Therefore, the standardization and integration of SNP array data from multiple sources have become an obstacle, especially for users with basic or no programming skills. Here, we describe the difficulties related to handling SNP array data, focusing on file formats, SNP allele coding, and mapping. We also present SNPConvert suite, a multi-platform, open-source, and user-friendly set of tools to overcome these issues. This tool, which can be integrated with open-source and open-access tools already available, is a first step towards an integrated system to standardize and integrate any type of raw SNP array data. The tool is available at: https://github. com/nicolazzie/SNPConvert.git.

Sharing Lessons-Learned on Effective Open Data, Open-Source Practices from OpenAQ, a Global Open Air Quality Community.

NASA Astrophysics Data System (ADS)

Hasenkopf, C. A.

2017-12-01

Increasingly, open data, open-source projects are unearthing rich datasets and tools, previously impossible for more traditional avenues to generate. These projects are possible, in part, because of the emergence of online collaborative and code-sharing tools, decreasing costs of cloud-based services to fetch, store, and serve data, and increasing interest of individuals to contribute their time and skills to 'open projects.' While such projects have generated palpable enthusiasm from many sectors, many of these projects face uncharted paths for sustainability, visibility, and acceptance. Our project, OpenAQ, is an example of an open-source, open data community that is currently forging its own uncharted path. OpenAQ is an open air quality data platform that aggregates and universally formats government and research-grade air quality data from 50 countries across the world. To date, we make available more than 76 million air quality (PM2.5, PM10, SO2, NO2, O3, CO and black carbon) data points through an open Application Programming Interface (API) and a user-customizable download interface at https://openaq.org. The goal of the platform is to enable an ecosystem of users to advance air pollution efforts from science to policy to the private sector. The platform is also an open-source project (https://github.com/openaq) and has only been made possible through the coding and data contributions of individuals around the world. In our first two years of existence, we have seen requests for data to our API skyrocket to more than 6 million datapoints per month, and use-cases as varied as ingesting data aggregated from our system into real-time models of wildfires to building open-source statistical packages (e.g. ropenaq and py-openaq) on top of the platform to creating public-friendly apps and chatbots. We will share a whirl-wind trip through our evolution and the many lessons learned so far related to platform structure, community engagement, organizational model type and sustainability.

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Open-source Framework for Storing and Manipulation of Plasma Chemical Reaction Data

NASA Astrophysics Data System (ADS)

Jenkins, T. G.; Averkin, S. N.; Cary, J. R.; Kruger, S. E.

2017-10-01

We present a new open-source framework for storage and manipulation of plasma chemical reaction data that has emerged from our in-house project MUNCHKIN. This framework consists of python scripts and C + + programs. It stores data in an SQL data base for fast retrieval and manipulation. For example, it is possible to fit cross-section data into most widely used analytical expressions, calculate reaction rates for Maxwellian distribution functions of colliding particles, and fit them into different analytical expressions. Another important feature of this framework is the ability to calculate transport properties based on the cross-section data and supplied distribution functions. In addition, this framework allows the export of chemical reaction descriptions in LaTeX format for ease of inclusion in scientific papers. With the help of this framework it is possible to generate corresponding VSim (Particle-In-Cell simulation code) and USim (unstructured multi-fluid code) input blocks with appropriate cross-sections.

A new, open-source, multi-modality digital breast phantom

NASA Astrophysics Data System (ADS)

Graff, Christian G.

2016-03-01

An anthropomorphic digital breast phantom has been developed with the goal of generating random voxelized breast models that capture the anatomic variability observed in vivo. This is a new phantom and is not based on existing digital breast phantoms or segmentation of patient images. It has been designed at the outset to be modality agnostic (i.e., suitable for use in modeling x-ray based imaging systems, magnetic resonance imaging, and potentially other imaging systems) and open source so that users may freely modify the phantom to suit a particular study. In this work we describe the modeling techniques that have been developed, the capabilities and novel features of this phantom, and study simulated images produced from it. Starting from a base quadric, a series of deformations are performed to create a breast with a particular volume and shape. Initial glandular compartments are generated using a Voronoi technique and a ductal tree structure with terminal duct lobular units is grown from the nipple into each compartment. An additional step involving the creation of fat and glandular lobules using a Perlin noise function is performed to create more realistic glandular/fat tissue interfaces and generate a Cooper's ligament network. A vascular tree is grown from the chest muscle into the breast tissue. Breast compression is performed using a neo-Hookean elasticity model. We show simulated mammographic and T1-weighted MRI images and study properties of these images.

Social network of PESCA (Open Source Platform for eHealth).

PubMed

Sanchez, Carlos L; Romero-Cuevas, Miguel; Lopez, Diego M; Lorca, Julio; Alcazar, Francisco J; Ruiz, Sergio; Mercado, Carmen; Garcia-Fortea, Pedro

2008-01-01

Information and Communication Technologies (ICTs) are revolutionizing how healthcare systems deliver top-quality care to citizens. In this way, Open Source Software (OSS) has demonstrated to be an important strategy to spread ICTs use. Several human and technological barriers in adopting OSS for healthcare have been identified. Human barriers include user acceptance, limited support, technical skillfulness, awareness, resistance to change, etc., while Technological barriers embrace need for open standards, heterogeneous OSS developed without normalization and metrics, lack of initiatives to evaluate existing health OSS and need for quality control and functional validation. The goals of PESCA project are to create a platform of interoperable modules to evaluate, classify and validate good practices in health OSS. Furthermore, a normalization platform will provide interoperable solutions in the fields of healthcare services, health surveillance, health literature, and health education, knowledge and research. Within the platform, the first goal to achieve is the setup of the collaborative work infrastructure. The platform is being organized as a Social Network which works to evaluate five scopes of every existing open source tools for eHealth: Open Source Software, Quality, Pedagogical, Security and privacy and Internationalization/I18N. In the meantime, the knowledge collected from the networking will configure a Good Practice Repository on eHealth promoting the effective use of ICT on behalf of the citizen's health.

A modal approach based on perfectly matched layers for the forced response of elastic open waveguides

NASA Astrophysics Data System (ADS)

Gallezot, M.; Treyssède, F.; Laguerre, L.

2018-03-01

This paper investigates the computation of the forced response of elastic open waveguides with a numerical modal approach based on perfectly matched layers (PML). With a PML of infinite thickness, the solution can theoretically be expanded as a discrete sum of trapped modes, a discrete sum of leaky modes and a continuous sum of radiation modes related to the PML branch cuts. Yet with numerical methods (e.g. finite elements), the waveguide cross-section is discretized and the PML must be truncated to a finite thickness. This truncation transforms the continuous sum into a discrete set of PML modes. To guarantee the uniqueness of the numerical solution of the forced response problem, an orthogonality relationship is proposed. This relationship is applicable to any type of modes (trapped, leaky and PML modes) and hence allows the numerical solution to be expanded on a discrete sum in a convenient manner. This also leads to an expression for the modal excitability valid for leaky modes. The physical relevance of each type of mode for the solution is clarified through two numerical test cases, a homogeneous medium and a circular bar waveguide example, excited by a point source. The former is favourably compared to a transient analytical solution, showing that PML modes reassemble the bulk wave contribution in a homogeneous medium. The latter shows that the PML mode contribution yields the long-term diffraction phenomenon whereas the leaky mode contribution prevails closer to the source. The leaky mode contribution is shown to remain accurate even with a relatively small PML thickness, hence reducing the computational cost. This is of particular interest for solving three-dimensional waveguide problems, involving two-dimensional cross-sections of arbitrary shapes. Such a problem is handled in a third numerical example by considering a buried square bar.

NucliTrack: an integrated nuclei tracking application.

PubMed

Cooper, Sam; Barr, Alexis R; Glen, Robert; Bakal, Chris

2017-10-15

Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack's interactive, graphical interface makes it significantly more user friendly. NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab. sam@socooper.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

NucliTrack: an integrated nuclei tracking application

PubMed Central

Cooper, Sam; Barr, Alexis R.; Glen, Robert; Bakal, Chris

2017-01-01

Abstract Summary Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack’s interactive, graphical interface makes it significantly more user friendly. Availability and implementation NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab. Contact sam@socooper.com Supplementary information Supplementary data are available at Bioinformatics online. PMID:28637183

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

PubMed Central

2010-01-01

Background Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism. PMID:20380733

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

PubMed

Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism.

A software framework for real-time multi-modal detection of microsleeps.

PubMed

Knopp, Simon J; Bones, Philip J; Weddell, Stephen J; Jones, Richard D

2017-09-01

A software framework is described which was designed to process EEG, video of one eye, and head movement in real time, towards achieving early detection of microsleeps for prevention of fatal accidents, particularly in transport sectors. The framework is based around a pipeline structure with user-replaceable signal processing modules. This structure can encapsulate a wide variety of feature extraction and classification techniques and can be applied to detecting a variety of aspects of cognitive state. Users of the framework can implement signal processing plugins in C++ or Python. The framework also provides a graphical user interface and the ability to save and load data to and from arbitrary file formats. Two small studies are reported which demonstrate the capabilities of the framework in typical applications: monitoring eye closure and detecting simulated microsleeps. While specifically designed for microsleep detection/prediction, the software framework can be just as appropriately applied to (i) other measures of cognitive state and (ii) development of biomedical instruments for multi-modal real-time physiological monitoring and event detection in intensive care, anaesthesiology, cardiology, neurosurgery, etc. The software framework has been made freely available for researchers to use and modify under an open source licence.

Aerostat-Lofted Instrument Platform and Sampling Method for Determination of Emissions from Open Area Sources

EPA Science Inventory

Sampling emissions from open area sources, particularly sources of open burning, is difficult due to fast dilution of emissions and safety concerns for personnel. Representative emission samples can be difficult to obtain with flaming and explosive sources since personnel safety ...

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.

PubMed

Razzaq, Muhammad Asif; Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Ali Khan, Wajahat

2017-10-24

The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification

PubMed Central

Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Kim, Dohyeong; Ali Khan, Wajahat

2017-01-01

The emerging research on automatic identification of user’s contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user’s contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts. PMID:29064459

Cortical reorganization in postlingually deaf cochlear implant users: Intra-modal and cross-modal considerations.

PubMed

Stropahl, Maren; Chen, Ling-Chia; Debener, Stefan

2017-01-01

With the advances of cochlear implant (CI) technology, many deaf individuals can partially regain their hearing ability. However, there is a large variation in the level of recovery. Cortical changes induced by hearing deprivation and restoration with CIs have been thought to contribute to this variation. The current review aims to identify these cortical changes in postlingually deaf CI users and discusses their maladaptive or adaptive relationship to the CI outcome. Overall, intra-modal and cross-modal reorganization patterns have been identified in postlingually deaf CI users in visual and in auditory cortex. Even though cross-modal activation in auditory cortex is considered as maladaptive for speech recovery in CI users, a similar activation relates positively to lip reading skills. Furthermore, cross-modal activation of the visual cortex seems to be adaptive for speech recognition. Currently available evidence points to an involvement of further brain areas and suggests that a focus on the reversal of visual take-over of the auditory cortex may be too limited. Future investigations should consider expanded cortical as well as multi-sensory processing and capture different hierarchical processing steps. Furthermore, prospective longitudinal designs are needed to track the dynamics of cortical plasticity that takes place before and after implantation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications

PubMed Central

Kalinin, Alexandr A.; Palanimalai, Selvam; Dinov, Ivo D.

2018-01-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis. PMID:29630069

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications.

PubMed

Kalinin, Alexandr A; Palanimalai, Selvam; Dinov, Ivo D

2017-04-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis.

Gamma-Ray imaging for nuclear security and safety: Towards 3-D gamma-ray vision

NASA Astrophysics Data System (ADS)

Vetter, Kai; Barnowksi, Ross; Haefner, Andrew; Joshi, Tenzing H. Y.; Pavlovsky, Ryan; Quiter, Brian J.

2018-01-01

The development of portable gamma-ray imaging instruments in combination with the recent advances in sensor and related computer vision technologies enable unprecedented capabilities in the detection, localization, and mapping of radiological and nuclear materials in complex environments relevant for nuclear security and safety. Though multi-modal imaging has been established in medicine and biomedical imaging for some time, the potential of multi-modal data fusion for radiological localization and mapping problems in complex indoor and outdoor environments remains to be explored in detail. In contrast to the well-defined settings in medical or biological imaging associated with small field-of-view and well-constrained extension of the radiation field, in many radiological search and mapping scenarios, the radiation fields are not constrained and objects and sources are not necessarily known prior to the measurement. The ability to fuse radiological with contextual or scene data in three dimensions, in analog to radiological and functional imaging with anatomical fusion in medicine, provides new capabilities enhancing image clarity, context, quantitative estimates, and visualization of the data products. We have developed new means to register and fuse gamma-ray imaging with contextual data from portable or moving platforms. These developments enhance detection and mapping capabilities as well as provide unprecedented visualization of complex radiation fields, moving us one step closer to the realization of gamma-ray vision in three dimensions.

Cross-platform validation and analysis environment for particle physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.

A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for onlinemore » validation of Monte Carlo event samples through a web interface.« less

Earthscape, a Multi-Purpose Interactive 3d Globe Viewer for Hybrid Data Visualization and Analysis

NASA Astrophysics Data System (ADS)

Sarthou, A.; Mas, S.; Jacquin, M.; Moreno, N.; Salamon, A.

2015-08-01

The hybrid visualization and interaction tool EarthScape is presented here. The software is able to display simultaneously LiDAR point clouds, draped videos with moving footprint, volume scientific data (using volume rendering, isosurface and slice plane), raster data such as still satellite images, vector data and 3D models such as buildings or vehicles. The application runs on touch screen devices such as tablets. The software is based on open source libraries, such as OpenSceneGraph, osgEarth and OpenCV, and shader programming is used to implement volume rendering of scientific data. The next goal of EarthScape is to perform data analysis using ENVI Services Engine, a cloud data analysis solution. EarthScape is also designed to be a client of Jagwire which provides multisource geo-referenced video fluxes. When all these components will be included, EarthScape will be a multi-purpose platform that will provide at the same time data analysis, hybrid visualization and complex interactions. The software is available on demand for free at france@exelisvis.com.

Extinction cross-section suppression and active acoustic invisibility cloaking

NASA Astrophysics Data System (ADS)

Mitri, F. G.

2017-10-01

Invisibility in its canonical form requires rendering a zero extinction cross-section (or energy efficiency) from an active or a passive object. This work demonstrates the successful theoretical realization of this physical effect for an active cylindrically radiating acoustic body, undergoing periodic axisymmetric harmonic vibrations near a flat rigid boundary. Radiating, amplification and extinction cross-sections of the active source are defined. Assuming monopole and dipole modal oscillations of the circular source, conditions are found where the extinction energy efficiency factor of the active source vanishes, achieving total invisibility with minimal influence of the source size. It also takes positive or negative values, depending on its size and distance from the boundary. Moreover, the amplification energy efficiency factor is negative for the acoustically-active source. These effects also occur for higher-order modal oscillations of the active source. The results find potential applications in the development of acoustic cloaking devices and invisibility.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

Anser EMT: the first open-source electromagnetic tracking platform for image-guided interventions.

PubMed

Jaeger, Herman Alexander; Franz, Alfred Michael; O'Donoghue, Kilian; Seitel, Alexander; Trauzettel, Fabian; Maier-Hein, Lena; Cantillon-Murphy, Pádraig

2017-06-01

Electromagnetic tracking is the gold standard for instrument tracking and navigation in the clinical setting without line of sight. Whilst clinical platforms exist for interventional bronchoscopy and neurosurgical navigation, the limited flexibility and high costs of electromagnetic tracking (EMT) systems for research investigations mitigate against a better understanding of the technology's characterisation and limitations. The Anser project provides an open-source implementation for EMT with particular application to image-guided interventions. This work provides implementation schematics for our previously reported EMT system which relies on low-cost acquisition and demodulation techniques using both National Instruments and Arduino hardware alongside MATLAB support code. The system performance is objectively compared to other commercial tracking platforms using the Hummel assessment protocol. Positional accuracy of 1.14 mm and angular rotation accuracy of [Formula: see text] are reported. Like other EMT platforms, Anser is susceptible to tracking errors due to eddy current and ferromagnetic distortion. The system is compatible with commercially available EMT sensors as well as the Open Network Interface for image-guided therapy (OpenIGTLink) for easy communication with visualisation and medical imaging toolkits such as MITK and 3D Slicer. By providing an open-source platform for research investigations, we believe that novel and collaborative approaches can overcome the limitations of current EMT technology.

Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

PubMed Central

O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R

2008-01-01

Background Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Results Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Conclusion Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers. PMID:18328109

Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit.

PubMed

O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R

2008-03-09

Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers.

One bout of open skill exercise improves cross-modal perception and immediate memory in healthy older adults who habitually exercise.

PubMed

O'Brien, Jessica; Ottoboni, Giovanni; Tessari, Alessia; Setti, Annalisa

2017-01-01

One single bout of exercise can be associated with positive effects on cognition, due to physiological changes associated with muscular activity, increased arousal, and training of cognitive skills during exercise. While the positive effects of life-long physical activity on cognitive ageing are well demonstrated, it is not well established whether one bout of exercise is sufficient to register such benefits in older adults. The aim of this study was to test the effect of one bout of exercise on two cognitive processes essential to daily life and known to decline with ageing: audio-visual perception and immediate memory. Fifty-eight older adults took part in a quasi-experimental design study and were divided into three groups based on their habitual activity (open skill exercise (mean age = 69.65, SD = 5.64), closed skill exercise, N = 18, 94% female; sedentary activity-control group, N = 21, 62% female). They were then tested before and after their activity (duration between 60 and 80 minutes). Results showed improvement in sensitivity in audio-visual perception in the open skill group and improvements in one of the measures of immediate memory in both exercise groups, after controlling for baseline differences including global cognition and health. These findings indicate that immediate benefits for cross-modal perception and memory can be obtained after open skill exercise. However, improvements after closed skill exercise may be limited to memory benefits. Perceptual benefits are likely to be associated with arousal, while memory benefits may be due to the training effects provided by task requirements during exercise. The respective role of qualitative and quantitative differences between these activities in terms of immediate cognitive benefits should be further investigated. Importantly, the present results present the first evidence for a modulation of cross-modal perception by exercise, providing a plausible avenue for rehabilitation of cross-modal perception deficits, which are emerging as a significant contributor to functional decline in ageing.

Light-sheet microscopy for everyone? Experience of building an OpenSPIM to study flatworm development.

PubMed

Girstmair, Johannes; Zakrzewski, Anne; Lapraz, François; Handberg-Thorsager, Mette; Tomancak, Pavel; Pitrone, Peter Gabriel; Simpson, Fraser; Telford, Maximilian J

2016-06-30

Selective plane illumination microscopy (SPIM a type of light-sheet microscopy) involves focusing a thin sheet of laser light through a specimen at right angles to the objective lens. As only the thin section of the specimen at the focal plane of the lens is illuminated, out of focus light is naturally absent and toxicity due to light (phototoxicity) is greatly reduced enabling longer term live imaging. OpenSPIM is an open access platform (Pitrone et al. 2013 and OpenSPIM.org) created to give new users step-by-step instructions on building a basic configuration of a SPIM microscope, which can in principle be adapted and upgraded to each laboratory's own requirements and budget. Here we describe our own experience with the process of designing, building, configuring and using an OpenSPIM for our research into the early development of the polyclad flatworm Maritigrella crozieri - a non-model animal. Our OpenSPIM builds on the standard design with the addition of two colour laser illumination for simultaneous detection of two probes/molecules and dual sided illumination, which provides more even signal intensity across a specimen. Our OpenSPIM provides high resolution 3d images and time lapse recordings, and we demonstrate the use of two colour lasers and the benefits of two color dual-sided imaging. We used our microscope to study the development of the embryo of the polyclad flatworm M. crozieri. The capabilities of our microscope are demonstrated by our ability to record the stereotypical spiral cleavage pattern of M. crozieri with high-speed multi-view time lapse imaging. 3D and 4D (3D + time) reconstruction of early development from these data is possible using image registration and deconvolution tools provided as part of the open source Fiji platform. We discuss our findings on the pros and cons of a self built microscope. We conclude that home-built microscopes, such as an OpenSPIM, together with the available open source software, such as MicroManager and Fiji, make SPIM accessible to anyone interested in having continuous access to their own light-sheet microscope. However, building an OpenSPIM is not without challenges and an open access microscope is a worthwhile, if significant, investment of time and money. Multi-view 4D microscopy is more challenging than we had expected. We hope that our experience gained during this project will help future OpenSPIM users with similar ambitions.

Architecture and Implementation of OpenPET Firmware and Embedded Software

PubMed Central

Abu-Nimeh, Faisal T.; Ito, Jennifer; Moses, William W.; Peng, Qiyu; Choong, Woon-Seng

2016-01-01

OpenPET is an open source, modular, extendible, and high-performance platform suitable for multi-channel data acquisition and analysis. Due to the flexibility of the hardware, firmware, and software architectures, the platform is capable of interfacing with a wide variety of detector modules not only in medical imaging but also in homeland security applications. Analog signals from radiation detectors share similar characteristics – a pulse whose area is proportional to the deposited energy and whose leading edge is used to extract a timing signal. As a result, a generic design method of the platform is adopted for the hardware, firmware, and software architectures and implementations. The analog front-end is hosted on a module called a Detector Board, where each board can filter, combine, timestamp, and process multiple channels independently. The processed data is formatted and sent through a backplane bus to a module called Support Board, where 1 Support Board can host up to eight Detector Board modules. The data in the Support Board, coming from 8 Detector Board modules, can be aggregated or correlated (if needed) depending on the algorithm implemented or runtime mode selected. It is then sent out to a computer workstation for further processing. The number of channels (detector modules), to be processed, mandates the overall OpenPET System Configuration, which is designed to handle up to 1,024 channels using 16-channel Detector Boards in the Standard System Configuration and 16,384 channels using 32-channel Detector Boards in the Large System Configuration. PMID:27110034

openECA Platform and Analytics Alpha Test Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Russell

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

openECA Platform and Analytics Beta Demonstration Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Russell

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

Testing RISKGIS Platform with Students to Improve Learning and Teaching Skills

NASA Astrophysics Data System (ADS)

Olyazadeh, R.; Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2016-12-01

Nowadays, open-source developments in the field of natural hazards and risk management increase rapidly. The governments, NGOs and other research institutes are producing data for risk and disaster analysis, but a few platforms are available to bring a real-life experience to the students. This work focuses on the preliminary results of testing a WebGIS platform called RISKGIS with the bachelor students at the University of Lausanne. The platform is designed based on a geospatial open-source technology called OpenGeo (Boundless). This platform can calculate the potential risk of the buildings and assist the students to understand the situations for risk reduction mitigation and decision-making. The center of Jomsom in Nepal was selected for the first exercise that may be affected by amplifications of earthquake. The shaking intensity map was designed by an expert based on the geological characteristics and DEM (Digital Elevation Model) of the area. All buildings data were extracted from OpenStreetMap using QGIS and adapted to the platform. The video tutorial was prepared to guide the students through the platform, and 80 students have tested the application online successfully and 40 of them participated in Moodle (a free Open Source software package for educators) for online feedback and quiz. Among those, 30 of them have completely answered to both. We had interesting results for effectiveness, efficiency and satisfaction based on System Usability Scale (SUS). The SUS score for this platform was 68.6 out of 100. The average result of the quiz was 9.39 out of 10 with a duration of 8 to 33 minutes to answer the quiz. There were several outliers for this duration with 2 minutes (two students) and 9 to 18 hours (three students). Further exercises will be carried out with students by adding more advanced functions to the platform and improving the willingness of participation in this online learning platform. This project is funded by Fonds d'innovation pédagogique de l'Université de Lausanne (FIP). We think this initial, ongoing platform can help both students and teachers to improve their skills in the field of risk and disaster management.Keywords: Risk and disaster Management, GIS, Open-Source, Boundless, Moodle, Teaching and learning

OMERO and Bio-Formats 5: flexible access to large bioimaging datasets at scale

NASA Astrophysics Data System (ADS)

Moore, Josh; Linkert, Melissa; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Li, Simon; Lindner, Dominik; Moore, William J.; Patterson, Andrew J.; Pindelski, Blazej; Ramalingam, Balaji; Rozbicki, Emil; Tarkowska, Aleksandra; Walczysko, Petr; Allan, Chris; Burel, Jean-Marie; Swedlow, Jason

2015-03-01

The Open Microscopy Environment (OME) has built and released Bio-Formats, a Java-based proprietary file format conversion tool and OMERO, an enterprise data management platform under open source licenses. In this report, we describe new versions of Bio-Formats and OMERO that are specifically designed to support large, multi-gigabyte or terabyte scale datasets that are routinely collected across most domains of biological and biomedical research. Bio- Formats reads image data directly from native proprietary formats, bypassing the need for conversion into a standard format. It implements the concept of a file set, a container that defines the contents of multi-dimensional data comprised of many files. OMERO uses Bio-Formats to read files natively, and provides a flexible access mechanism that supports several different storage and access strategies. These new capabilities of OMERO and Bio-Formats make them especially useful for use in imaging applications like digital pathology, high content screening and light sheet microscopy that create routinely large datasets that must be managed and analyzed.

Computational toxicology using the OpenTox application programming interface and Bioclipse

PubMed Central

2011-01-01

Background Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. Findings This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. Conclusions A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers. PMID:22075173

Auditory cross-modal reorganization in cochlear implant users indicates audio-visual integration.

PubMed

Stropahl, Maren; Debener, Stefan

2017-01-01

There is clear evidence for cross-modal cortical reorganization in the auditory system of post-lingually deafened cochlear implant (CI) users. A recent report suggests that moderate sensori-neural hearing loss is already sufficient to initiate corresponding cortical changes. To what extend these changes are deprivation-induced or related to sensory recovery is still debated. Moreover, the influence of cross-modal reorganization on CI benefit is also still unclear. While reorganization during deafness may impede speech recovery, reorganization also has beneficial influences on face recognition and lip-reading. As CI users were observed to show differences in multisensory integration, the question arises if cross-modal reorganization is related to audio-visual integration skills. The current electroencephalography study investigated cortical reorganization in experienced post-lingually deafened CI users ( n  = 18), untreated mild to moderately hearing impaired individuals (n = 18) and normal hearing controls ( n  = 17). Cross-modal activation of the auditory cortex by means of EEG source localization in response to human faces and audio-visual integration, quantified with the McGurk illusion, were measured. CI users revealed stronger cross-modal activations compared to age-matched normal hearing individuals. Furthermore, CI users showed a relationship between cross-modal activation and audio-visual integration strength. This may further support a beneficial relationship between cross-modal activation and daily-life communication skills that may not be fully captured by laboratory-based speech perception tests. Interestingly, hearing impaired individuals showed behavioral and neurophysiological results that were numerically between the other two groups, and they showed a moderate relationship between cross-modal activation and the degree of hearing loss. This further supports the notion that auditory deprivation evokes a reorganization of the auditory system even at early stages of hearing loss.

Cross-Modal Bilingualism: Language Contact as Evidence of Linguistic Transfer in Sign Bilingual Education

ERIC Educational Resources Information Center

Menendez, Bruno

2010-01-01

New positive attitudes towards language interaction in the realm of bilingualism open new horizons for sign bilingual education. Plaza-Pust and Morales-Lopez have innovatively reconceptualised a new cross-disciplinary approach to sign bilingualism, based on both sociolinguistics and psycholinguistics. According to this framework, cross-modal…

MetaboLights: An Open-Access Database Repository for Metabolomics Data.

PubMed

Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

2016-03-24

MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

Behold the voice of wrath: cross-modal modulation of visual attention by anger prosody.

PubMed

Brosch, Tobias; Grandjean, Didier; Sander, David; Scherer, Klaus R

2008-03-01

Emotionally relevant stimuli are prioritized in human information processing. It has repeatedly been shown that selective spatial attention is modulated by the emotional content of a stimulus. Until now, studies investigating this phenomenon have only examined within-modality effects, most frequently using pictures of emotional stimuli to modulate visual attention. In this study, we used simultaneously presented utterances with emotional and neutral prosody as cues for a visually presented target in a cross-modal dot probe task. Response times towards targets were faster when they appeared at the location of the source of the emotional prosody. Our results show for the first time a cross-modal attentional modulation of visual attention by auditory affective prosody.

Robotics-assisted mass spectrometry assay platform enabled by open-source electronics.

PubMed

Chiu, Shih-Hao; Urban, Pawel L

2015-02-15

Mass spectrometry (MS) is an important analytical technique with numerous applications in clinical analysis, biochemistry, environmental analysis, geology and physics. Its success builds on the ability of MS to determine molecular weights of analytes, and elucidate their structures. However, sample handling prior to MS requires a lot of attention and labor. In this work we were aiming to automate processing samples for MS so that analyses could be conducted without much supervision of experienced analysts. The goal of this study was to develop a robotics and information technology-oriented platform that could control the whole analysis process including sample delivery, reaction-based assay, data acquisition, and interaction with the analyst. The proposed platform incorporates a robotic arm for handling sample vials delivered to the laboratory, and several auxiliary devices which facilitate and secure the analysis process. They include: multi-relay board, infrared sensors, photo-interrupters, gyroscopes, force sensors, fingerprint scanner, barcode scanner, touch screen panel, and internet interface. The control of all the building blocks is achieved through implementation of open-source electronics (Arduino), and enabled by custom-written programs in C language. The advantages of the proposed system include: low cost, simplicity, small size, as well as facile automation of sample delivery and processing without the intervention of the analyst. It is envisaged that this simple robotic system may be the forerunner of automated laboratories dedicated to mass spectrometric analysis of biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

What is the link between synaesthesia and sound symbolism?

PubMed Central

Bankieris, Kaitlyn; Simner, Julia

2015-01-01

Sound symbolism is a property of certain words which have a direct link between their phonological form and their semantic meaning. In certain instances, sound symbolism can allow non-native speakers to understand the meanings of etymologically unfamiliar foreign words, although the mechanisms driving this are not well understood. We examined whether sound symbolism might be mediated by the same types of cross-modal processes that typify synaesthetic experiences. Synaesthesia is an inherited condition in which sensory or cognitive stimuli (e.g., sounds, words) cause additional, unusual cross-modal percepts (e.g., sounds trigger colours, words trigger tastes). Synaesthesia may be an exaggeration of normal cross-modal processing, and if so, there may be a link between synaesthesia and the type of cross-modality inherent in sound symbolism. To test this we predicted that synaesthetes would have superior understanding of unfamiliar (sound symbolic) foreign words. In our study, 19 grapheme-colour synaesthetes and 57 non-synaesthete controls were presented with 400 adjectives from 10 unfamiliar languages and were asked to guess the meaning of each word in a two-alternative forced-choice task. Both groups showed superior understanding compared to chance levels, but synaesthetes significantly outperformed controls. This heightened ability suggests that sound symbolism may rely on the types of cross-modal integration that drive synaesthetes’ unusual experiences. It also suggests that synaesthesia endows or co-occurs with heightened multi-modal skills, and that this can arise in domains unrelated to the specific form of synaesthesia. PMID:25498744

Using Multi-Media Projects to Foster Teacher Candidates' Multiple Literacy Skills

ERIC Educational Resources Information Center

Lawrence, Salika A.

2010-01-01

This article describes the strategies used to incorporate multi-modal technology literacy experiences into a graduate level course for literacy specialists. The candidates created a multi-media project in response to literature. Their projects revealed that the teacher candidates used a variety of sources to create the project but the Internet was…

A coupled modal-finite element method for the wave propagation modeling in irregular open waveguides.

PubMed

Pelat, Adrien; Felix, Simon; Pagneux, Vincent

2011-03-01

In modeling the wave propagation within a street canyon, particular attention must be paid to the description of both the multiple reflections of the wave on the building facades and the radiation in the free space above the street. The street canyon being considered as an open waveguide with a discontinuously varying cross-section, a coupled modal-finite element formulation is proposed to solve the three-dimensional wave equation within. The originally open configuration-the street canyon open in the sky above-is artificially turned into a close waveguiding structure by using perfectly matched layers that truncate the infinite sky without introducing numerical reflection. Then the eigenmodes of the resulting waveguide are determined by a finite element method computation in the cross-section. The eigensolutions can finally be used in a multimodal formulation of the wave propagation along the canyon, given its geometry and the end conditions at its extremities: initial field condition at the entrance and radiation condition at the output. © 2011 Acoustical Society of America

PyGaze: an open-source, cross-platform toolbox for minimal-effort programming of eyetracking experiments.

PubMed

Dalmaijer, Edwin S; Mathôt, Sebastiaan; Van der Stigchel, Stefan

2014-12-01

The PyGaze toolbox is an open-source software package for Python, a high-level programming language. It is designed for creating eyetracking experiments in Python syntax with the least possible effort, and it offers programming ease and script readability without constraining functionality and flexibility. PyGaze can be used for visual and auditory stimulus presentation; for response collection via keyboard, mouse, joystick, and other external hardware; and for the online detection of eye movements using a custom algorithm. A wide range of eyetrackers of different brands (EyeLink, SMI, and Tobii systems) are supported. The novelty of PyGaze lies in providing an easy-to-use layer on top of the many different software libraries that are required for implementing eyetracking experiments. Essentially, PyGaze is a software bridge for eyetracking research.

Harvesting rockfall hazard evaluation parameters from Google Earth Street View

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Agioutantis, Zacharias; Tripolitsiotis, Achilles; Steiakakis, Chrysanthos; Mertikas, Stelios

2015-04-01

Rockfall incidents along highways and railways prove extremely dangerous for properties, infrastructures and human lives. Several qualitative metrics such as the Rockfall Hazard Rating System (RHRS) and the Colorado Rockfall Hazard Rating System (CRHRS) have been established to estimate rockfall potential and provide risk maps in order to control and monitor rockfall incidents. The implementation of such metrics for efficient and reliable risk modeling require accurate knowledge of multi-parametric attributes such as the geological, geotechnical, topographic parameters of the study area. The Missouri Rockfall Hazard Rating System (MORH RS) identifies the most potentially problematic areas using digital video logging for the determination of parameters like slope height and angle, face irregularities, etc. This study aims to harvest in a semi-automated approach geometric and qualitative measures through open source platforms that may provide 3-dimensional views of the areas of interest. More specifically, the Street View platform from Google Maps, is hereby used to provide essential information that can be used towards 3-dimensional reconstruction of slopes along highways. The potential of image capturing along a programmable virtual route to provide the input data for photogrammetric processing is also evaluated. Moreover, qualitative characterization of the geological and geotechnical status, based on the Street View images, is performed. These attributes are then integrated to deliver a GIS-based rockfall hazard map. The 3-dimensional models are compared to actual photogrammetric measures in a rockfall prone area in Crete, Greece while in-situ geotechnical characterization is also used to compare and validate the hazard risk. This work is considered as the first step towards the exploitation of open source platforms to improve road safety and the development of an operational system where authorized agencies (i.e., civil protection) will be able to acquire near-real time hazard maps based on video images retrieved either by open source platforms, operational unmanned aerial vehicles, and/or simple video recordings from users. This work has been performed under the framework of the "Cooperation 2011" project ISTRIA (11_SYN_9_13989) funded from the Operational Program "Competitiveness and Entrepreneurship" (co-funded by the European Regional Development Fund (ERDF)) and managed by the Greek General Secretariat for Research and Technology.

Develop Direct Geo-referencing System Based on Open Source Software and Hardware Platform

NASA Astrophysics Data System (ADS)

Liu, H. S.; Liao, H. M.

2015-08-01

Direct geo-referencing system uses the technology of remote sensing to quickly grasp images, GPS tracks, and camera position. These data allows the construction of large volumes of images with geographic coordinates. So that users can be measured directly on the images. In order to properly calculate positioning, all the sensor signals must be synchronized. Traditional aerial photography use Position and Orientation System (POS) to integrate image, coordinates and camera position. However, it is very expensive. And users could not use the result immediately because the position information does not embed into image. To considerations of economy and efficiency, this study aims to develop a direct geo-referencing system based on open source software and hardware platform. After using Arduino microcontroller board to integrate the signals, we then can calculate positioning with open source software OpenCV. In the end, we use open source panorama browser, panini, and integrate all these to open source GIS software, Quantum GIS. A wholesome collection of data - a data processing system could be constructed.

mmpdb: An Open-Source Matched Molecular Pair Platform for Large Multiproperty Data Sets.

PubMed

Dalke, Andrew; Hert, Jérôme; Kramer, Christian

2018-05-29

Matched molecular pair analysis (MMPA) enables the automated and systematic compilation of medicinal chemistry rules from compound/property data sets. Here we present mmpdb, an open-source matched molecular pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large data sets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. It is freely available from https://github.com/rdkit/mmpdb .

Acoustic change detection algorithm using an FM radio

NASA Astrophysics Data System (ADS)

Goldman, Geoffrey H.; Wolfe, Owen

2012-06-01

The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.

Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.

2016-12-01

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.

Design of Open Content Social Learning That Increases Learning Efficiency and Engagement Based on Open Pedagogy

ERIC Educational Resources Information Center

John, Benneaser; Thavavel, V.; Jayaraj, Jayakumar; Muthukumar, A.; Jeevanandam, Poornaselvan Kittu

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

ScaMo: Realisation of an OO-functional DSL for cross platform mobile applications development

NASA Astrophysics Data System (ADS)

Macos, Dragan; Solymosi, Andreas

2013-10-01

The software market is dynamically changing: the Internet is going mobile, the software applications are shifting from the desktop hardware onto the mobile devices. The largest markets are the mobile applications for iOS, Android and Windows Phone and for the purpose the typical programming languages include Objective-C, Java and C ♯. The realization of the native applications implies the integration of the developed software into the environments of mentioned mobile operating systems to enable the access to different hardware components of the devices: GPS module, display, GSM module, etc. This paper deals with the definition and possible implementation of an environment for the automatic application generation for multiple mobile platforms. It is based on a DSL for mobile application development, which includes the programming language Scala and a DSL defined in Scala. As part of a multi-stage cross-compiling algorithm, this language is translated into the language of the affected mobile platform. The advantage of our method lies in the expressiveness of the defined language and the transparent source code translation between different languages, which implies, for example, the advantages of debugging and development of the generated code.

FloorspaceJS - A New, Open Source, Web-Based Geometry Editor for Building Energy Modeling (BEM): Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Macumber, Daniel L; Horowitz, Scott G; Schott, Marjorie

Across most industries, desktop applications are being rapidly migrated to web applications for a variety of reasons. Web applications are inherently cross platform, mobile, and easier to distribute than desktop applications. Fueling this trend are a wide range of free, open source libraries and frameworks that make it incredibly easy to develop powerful web applications. The building energy modeling community is just beginning to pick up on these larger trends, with a small but growing number of building energy modeling applications starting on or moving to the web. This paper presents a new, open source, web based geometry editor formore » Building Energy Modeling (BEM). The editor is written completely in JavaScript and runs in a modern web browser. The editor works on a custom JSON file format and is designed to be integrated into a variety of web and desktop applications. The web based editor is available to use as a standalone web application at: https://nrel.github.io/openstudio-geometry-editor/. An example integration is demonstrated with the OpenStudio desktop application. Finally, the editor can be easily integrated with a wide range of possible building energy modeling web applications.« less

Ocean acoustic interferometry.

PubMed

Brooks, Laura A; Gerstoft, Peter

2007-06-01

Ocean acoustic interferometry refers to an approach whereby signals recorded from a line of sources are used to infer the Green's function between two receivers. An approximation of the time domain Green's function is obtained by summing, over all source positions (stacking), the cross-correlations between the receivers. Within this paper a stationary phase argument is used to describe the relationship between the stacked cross-correlations from a line of vertical sources, located in the same vertical plane as two receivers, and the Green's function between the receivers. Theory and simulations demonstrate the approach and are in agreement with those of a modal based approach presented by others. Results indicate that the stacked cross-correlations can be directly related to the shaded Green's function, so long as the modal continuum of any sediment layers is negligible.

Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2011-01-01

Systems analysis of a planetary entry (SAPE), descent, and landing (EDL) is a multidisciplinary activity in nature. SAPE improves the performance of the systems analysis team by automating and streamlining the process, and this improvement can reduce the errors that stem from manual data transfer among discipline experts. SAPE is a multidisciplinary tool for systems analysis of planetary EDL for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. It performs EDL systems analysis for any planet, operates cross-platform (i.e., Windows, Mac, and Linux operating systems), uses existing software components and open-source software to avoid software licensing issues, performs low-fidelity systems analysis in one hour on a computer that is comparable to an average laptop, and keeps discipline experts in the analysis loop. SAPE uses Python, a platform-independent, open-source language, for integration and for the user interface. Development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE currently includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and interface for structural sizing.

Neurocognitive insights on conceptual knowledge and its breakdown

PubMed Central

Lambon Ralph, Matthew A.

2014-01-01

Conceptual knowledge reflects our multi-modal ‘semantic database’. As such, it brings meaning to all verbal and non-verbal stimuli, is the foundation for verbal and non-verbal expression and provides the basis for computing appropriate semantic generalizations. Multiple disciplines (e.g. philosophy, cognitive science, cognitive neuroscience and behavioural neurology) have striven to answer the questions of how concepts are formed, how they are represented in the brain and how they break down differentially in various neurological patient groups. A long-standing and prominent hypothesis is that concepts are distilled from our multi-modal verbal and non-verbal experience such that sensation in one modality (e.g. the smell of an apple) not only activates the intramodality long-term knowledge, but also reactivates the relevant intermodality information about that item (i.e. all the things you know about and can do with an apple). This multi-modal view of conceptualization fits with contemporary functional neuroimaging studies that observe systematic variation of activation across different modality-specific association regions dependent on the conceptual category or type of information. A second vein of interdisciplinary work argues, however, that even a smorgasbord of multi-modal features is insufficient to build coherent, generalizable concepts. Instead, an additional process or intermediate representation is required. Recent multidisciplinary work, which combines neuropsychology, neuroscience and computational models, offers evidence that conceptualization follows from a combination of modality-specific sources of information plus a transmodal ‘hub’ representational system that is supported primarily by regions within the anterior temporal lobe, bilaterally. PMID:24324236

A Dual-Modality System for Both Multi-Color Ultrasound-Switchable Fluorescence and Ultrasound Imaging

PubMed Central

Kandukuri, Jayanth; Yu, Shuai; Cheng, Bingbing; Bandi, Venugopal; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Yuan, Baohong

2017-01-01

Simultaneous imaging of multiple targets (SIMT) in opaque biological tissues is an important goal for molecular imaging in the future. Multi-color fluorescence imaging in deep tissues is a promising technology to reach this goal. In this work, we developed a dual-modality imaging system by combining our recently developed ultrasound-switchable fluorescence (USF) imaging technology with the conventional ultrasound (US) B-mode imaging. This dual-modality system can simultaneously image tissue acoustic structure information and multi-color fluorophores in centimeter-deep tissue with comparable spatial resolutions. To conduct USF imaging on the same plane (i.e., x-z plane) as US imaging, we adopted two 90°-crossed ultrasound transducers with an overlapped focal region, while the US transducer (the third one) was positioned at the center of these two USF transducers. Thus, the axial resolution of USF is close to the lateral resolution, which allows a point-by-point USF scanning on the same plane as the US imaging. Both multi-color USF and ultrasound imaging of a tissue phantom were demonstrated. PMID:28165390

CHRONIOUS: a wearable platform for monitoring and management of patients with chronic disease.

PubMed

Bellos, Christos; Papadopoulos, Athanassios; Rosso, Roberto; Fotiadis, Dimitrios I

2011-01-01

The CHRONIOUS system has been developed based on an open architecture design that consists of a set of subsystems which interact in order to provide all the needed services to the chronic disease patients. An advanced multi-parametric expert system is being implemented that fuses information effectively from various sources using intelligent techniques. Data are collected by sensors of a body network controlling vital signals while additional tools record dietary habits and plans, drug intake, environmental and biochemical parameters and activity data. The CHRONIOUS platform provides guidelines and standards for the future generations of "chronic disease management systems" and facilitates sophisticated monitoring tools. In addition, an ontological information retrieval system is being delivered satisfying the necessities for up-to-date clinical information of Chronic Obstructive pulmonary disease (COPD) and Chronic Kidney Disease (CKD). Moreover, support tools are being embedded in the system, such as the Mental Tools for the monitoring of patient mental health status. The integrated platform provides real-time patient monitoring and supervision, both indoors and outdoors and represents a generic platform for the management of various chronic diseases.

A Case Study in User Support for Managing OpenSim Based Multi User Learning Environments

ERIC Educational Resources Information Center

Perera, Indika; Miller, Alan; Allison, Colin

2017-01-01

Immersive 3D Multi User Learning Environments (MULE) have shown sufficient success to warrant their consideration as a mainstream educational paradigm. These are based on 3D Multi User Virtual Environment platforms (MUVE), and although they have been used for various innovative educational projects their complex permission systems and large…

Specification Patent Management for Web Application Platform Ecosystem

NASA Astrophysics Data System (ADS)

Fukami, Yoshiaki; Isshiki, Masao; Takeda, Hideaki; Ohmukai, Ikki; Kokuryo, Jiro

Diversified usage of web applications has encouraged disintegration of web platform into management of identification and applications. Users make use of various kinds of data linked to their identity with multiple applications on certain social web platforms such as Facebook or MySpace. There has emerged competition among web application platforms. Platformers can design relationship with developers by controlling patent of their own specification and adopt open technologies developed external organizations. Platformers choose a way to open according to feature of the specification and their position. Patent management of specification come to be a key success factor to build competitive web application platforms. Each way to attract external developers such as standardization, open source has not discussed and analyzed all together.

Citizen Sensors for SHM: Towards a Crowdsourcing Platform

PubMed Central

Ozer, Ekin; Feng, Maria Q.; Feng, Dongming

2015-01-01

This paper presents an innovative structural health monitoring (SHM) platform in terms of how it integrates smartphone sensors, the web, and crowdsourcing. The ubiquity of smartphones has provided an opportunity to create low-cost sensor networks for SHM. Crowdsourcing has given rise to citizen initiatives becoming a vast source of inexpensive, valuable but heterogeneous data. Previously, the authors have investigated the reliability of smartphone accelerometers for vibration-based SHM. This paper takes a step further to integrate mobile sensing and web-based computing for a prospective crowdsourcing-based SHM platform. An iOS application was developed to enable citizens to measure structural vibration and upload the data to a server with smartphones. A web-based platform was developed to collect and process the data automatically and store the processed data, such as modal properties of the structure, for long-term SHM purposes. Finally, the integrated mobile and web-based platforms were tested to collect the low-amplitude ambient vibration data of a bridge structure. Possible sources of uncertainties related to citizens were investigated, including the phone location, coupling conditions, and sampling duration. The field test results showed that the vibration data acquired by smartphones operated by citizens without expertise are useful for identifying structural modal properties with high accuracy. This platform can be further developed into an automated, smart, sustainable, cost-free system for long-term monitoring of structural integrity of spatially distributed urban infrastructure. Citizen Sensors for SHM will be a novel participatory sensing platform in the way that it offers hybrid solutions to transitional crowdsourcing parameters. PMID:26102490

An open-source framework for testing tracking devices using Lego Mindstorms

NASA Astrophysics Data System (ADS)

Jomier, Julien; Ibanez, Luis; Enquobahrie, Andinet; Pace, Danielle; Cleary, Kevin

2009-02-01

In this paper, we present an open-source framework for testing tracking devices in surgical navigation applications. At the core of image-guided intervention systems is the tracking interface that handles communication with the tracking device and gathers tracking information. Given that the correctness of tracking information is critical for protecting patient safety and for ensuring the successful execution of an intervention, the tracking software component needs to be thoroughly tested on a regular basis. Furthermore, with widespread use of extreme programming methodology that emphasizes continuous and incremental testing of application components, testing design becomes critical. While it is easy to automate most of the testing process, it is often more difficult to test components that require manual intervention such as tracking device. Our framework consists of a robotic arm built from a set of Lego Mindstorms and an open-source toolkit written in C++ to control the robot movements and assess the accuracy of the tracking devices. The application program interface (API) is cross-platform and runs on Windows, Linux and MacOS. We applied this framework for the continuous testing of the Image-Guided Surgery Toolkit (IGSTK), an open-source toolkit for image-guided surgery and shown that regression testing on tracking devices can be performed at low cost and improve significantly the quality of the software.

HydroDesktop as a Community Designed and Developed Resource for Hydrologic Data Discovery and Analysis

NASA Astrophysics Data System (ADS)

Ames, D. P.

2013-12-01

As has been seen in other informatics fields, well-documented and appropriately licensed open source software tools have the potential to significantly increase both opportunities and motivation for inter-institutional science and technology collaboration. The CUAHSI HIS (and related HydroShare) projects have aimed to foster such activities in hydrology resulting in the development of many useful community software components including the HydroDesktop software application. HydroDesktop is an open source, GIS-based, scriptable software application for discovering data on the CUAHSI Hydrologic Information System and related resources. It includes a well-defined plugin architecture and interface to allow 3rd party developers to create extensions and add new functionality without requiring recompiling of the full source code. HydroDesktop is built in the C# programming language and uses the open source DotSpatial GIS engine for spatial data management. Capabilities include data search, discovery, download, visualization, and export. An extension that integrates the R programming language with HydroDesktop provides scripting and data automation capabilities and an OpenMI plugin provides the ability to link models. Current revision and updates to HydroDesktop include migration of core business logic to cross platform, scriptable Python code modules that can be executed in any operating system or linked into other software front-end applications.

An Embedded Systems Course for Engineering Students Using Open-Source Platforms in Wireless Scenarios

ERIC Educational Resources Information Center

Rodriguez-Sanchez, M. C.; Torrado-Carvajal, Angel; Vaquero, Joaquin; Borromeo, Susana; Hernandez-Tamames, Juan A.

2016-01-01

This paper presents a case study analyzing the advantages and disadvantages of using project-based learning (PBL) combined with collaborative learning (CL) and industry best practices, integrated with information communication technologies, open-source software, and open-source hardware tools, in a specialized microcontroller and embedded systems…

"Combo" nanomedicine: Co-delivery of multi-modal therapeutics for efficient, targeted, and safe cancer therapy.

PubMed

Kemp, Jessica A; Shim, Min Suk; Heo, Chan Yeong; Kwon, Young Jik

2016-03-01

The dynamic and versatile nature of diseases such as cancer has been a pivotal challenge for developing efficient and safe therapies. Cancer treatments using a single therapeutic agent often result in limited clinical outcomes due to tumor heterogeneity and drug resistance. Combination therapies using multiple therapeutic modalities can synergistically elevate anti-cancer activity while lowering doses of each agent, hence, reducing side effects. Co-administration of multiple therapeutic agents requires a delivery platform that can normalize pharmacokinetics and pharmacodynamics of the agents, prolong circulation, selectively accumulate, specifically bind to the target, and enable controlled release in target site. Nanomaterials, such as polymeric nanoparticles, gold nanoparticles/cages/shells, and carbon nanomaterials, have the desired properties, and they can mediate therapeutic effects different from those generated by small molecule drugs (e.g., gene therapy, photothermal therapy, photodynamic therapy, and radiotherapy). This review aims to provide an overview of developing multi-modal therapies using nanomaterials ("combo" nanomedicine) along with the rationale, up-to-date progress, further considerations, and the crucial roles of interdisciplinary approaches. Copyright © 2015 Elsevier B.V. All rights reserved.

Tracking fluid-borne odors in diverse and dynamic environments using multiple sensory mechanisms

NASA Astrophysics Data System (ADS)

Taylor, Brian Kyle

The ability to locate odor sources in different types of environments (i.e. diverse) and environments that change radically during the mission (i.e., dynamic) is essential. While many engineered odor tracking systems have been developed, they appear to be designed for a particular environment (e.g., strong or low flow). In field conditions, agents may encounter both. Insect olfactory orientation studies show that several animals can locate odor sources in both high and low flow environments, and environments where the wind vanishes during tracking behavior. Furthermore, animals use multi-modal sensing, including olfaction, vision and touch to localize a source. This work uses simulated and hardware environments to explore how engineered systems can maintain wind-driven tracking behavior in diverse and dynamic environments. The simulation uses olfaction, vision and tactile attributes to track and localize a source in the following environments: high flow, low flow, and transition from high to low flow (i.e., Wind Stop). The hardware platform tests two disparate tracking strategies (including the simulated strategy) in an environment that transitions from strong to low flow. Results indicate that using a remembered wind direction post wind-shutoff is a viable way to maintain wind-driven tracking behavior in a wind stop environment, which can help bridge the gap between high flow and low flow strategies. Also, multi-modal sensing with tactile attributes, vision and olfaction helps a vehicle to localize a source. In addition to engineered systems, the moth Manduca sexta is challenged to track in the following environments: Wind and Odor, Wind Stop, Odor and No Wind, No Odor and No Wind to gain a better understanding of animal behavior in these environments. Results show that contrary to previous studies of different moth species, M. sexta does not generally maintain its wind-driven tracking behavior post-wind shutoff, but instead executes a stereotyped sequence of maneuvers followed by odor-modulated undirected exploration of its environment. In the Odor and No Wind environment, animals become biased towards the area of the arena where odor is located compared to the No Odor and No Wind environment. Robot and animal results are compared to learn more about both.

The taste-visual cross-modal Stroop effect: An event-related brain potential study.

PubMed

Xiao, X; Dupuis-Roy, N; Yang, X L; Qiu, J F; Zhang, Q L

2014-03-28

Event-related potentials (ERPs) were recorded to explore, for the first time, the electrophysiological correlates of the taste-visual cross-modal Stroop effect. Eighteen healthy participants were presented with a taste stimulus and a food image, and asked to categorize the image as "sweet" or "sour" by pressing the relevant button as quickly as possible. Accurate categorization of the image was faster when it was presented with a congruent taste stimulus (e.g., sour taste/image of lemon) than with an incongruent one (e.g., sour taste/image of ice cream). ERP analyses revealed a negative difference component (ND430-620) between 430 and 620ms in the taste-visual cross-modal Stroop interference. Dipole source analysis of the difference wave (incongruent minus congruent) indicated that two generators localized in the prefrontal cortex and the parahippocampal gyrus contributed to this taste-visual cross-modal Stroop effect. This result suggests that the prefrontal cortex is associated with the process of conflict control in the taste-visual cross-modal Stroop effect. Also, we speculate that the parahippocampal gyrus is associated with the process of discordant information in the taste-visual cross-modal Stroop effect. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Next Stop: OpenSim!

ERIC Educational Resources Information Center

Korolov, Maria

2011-01-01

Unhappy with conditions in Second Life, educators are migrating to a developing virtual world that offers them greater autonomy and a safer platform for their students at far less a cost. OpenSimulator is an open source virtual world platform that schools can run for free on their own servers or can get cheaply and quickly--the space can be up and…

Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

NASA Astrophysics Data System (ADS)

Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

2015-03-01

Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

Cultivating engineering innovation ability based on optoelectronic experimental platform

NASA Astrophysics Data System (ADS)

Li, Dangjuan; Wu, Shenjiang

2017-08-01

As the supporting experimental platform of the Xi'an Technological University education reform experimental class, "optical technological innovation experimental platform" integrated the design and comprehensive experiments of the optical multi-class courses. On the basis of summing up the past two years teaching experience, platform pilot projects were improve. It has played a good role by making the use of an open teaching model in the cultivating engineering innovation spirit and scientific thinking of the students.

DICOM image secure communications with Internet protocols IPv6 and IPv4.

PubMed

Zhang, Jianguo; Yu, Fenghai; Sun, Jianyong; Yang, Yuanyuan; Liang, Chenwen

2007-01-01

Image-data transmission from one site to another through public network is usually characterized in term of privacy, authenticity, and integrity. In this paper, we first describe a general scenario about how image is delivered from one site to another through a wide-area network (WAN) with security features of data privacy, integrity, and authenticity. Second, we give the common implementation method of the digital imaging and communication in medicine (DICOM) image communication software library with IPv6/IPv4 for high-speed broadband Internet by using open-source software. Third, we discuss two major security-transmission methods, the IP security (IPSec) and the secure-socket layer (SSL) or transport-layer security (TLS), being used currently in medical-image-data communication with privacy support. Fourth, we describe a test schema of multiple-modality DICOM-image communications through TCP/IPv4 and TCP/IPv6 with different security methods, different security algorithms, and operating systems, and evaluate the test results. We found that there are tradeoff factors between choosing the IPsec and the SSL/TLS-based security implementation of IPv6/IPv4 protocols. If the WAN networks only use IPv6 such as in high-speed broadband Internet, the choice is IPsec-based security. If the networks are IPv4 or the combination of IPv6 and IPv4, it is better to use SSL/TLS security. The Linux platform has more security algorithms implemented than the Windows (XP) platform, and can achieve better performance in most experiments of IPv6 and IPv4-based DICOM-image communications. In teleradiology or enterprise-PACS applications, the Linux operating system may be the better choice as peer security gateways for both the IPsec and the SSL/TLS-based secure DICOM communications cross public networks.

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

PubMed

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Open source OCR framework using mobile devices

NASA Astrophysics Data System (ADS)

Zhou, Steven Zhiying; Gilani, Syed Omer; Winkler, Stefan

2008-02-01

Mobile phones have evolved from passive one-to-one communication device to powerful handheld computing device. Today most new mobile phones are capable of capturing images, recording video, and browsing internet and do much more. Exciting new social applications are emerging on mobile landscape, like, business card readers, sing detectors and translators. These applications help people quickly gather the information in digital format and interpret them without the need of carrying laptops or tablet PCs. However with all these advancements we find very few open source software available for mobile phones. For instance currently there are many open source OCR engines for desktop platform but, to our knowledge, none are available on mobile platform. Keeping this in perspective we propose a complete text detection and recognition system with speech synthesis ability, using existing desktop technology. In this work we developed a complete OCR framework with subsystems from open source desktop community. This includes a popular open source OCR engine named Tesseract for text detection & recognition and Flite speech synthesis module, for adding text-to-speech ability.

Architecture and Implementation of OpenPET Firmware and Embedded Software

DOE PAGES

Abu-Nimeh, Faisal T.; Ito, Jennifer; Moses, William W.; ...

2016-01-11

OpenPET is an open source, modular, extendible, and high-performance platform suitable for multi-channel data acquisition and analysis. Due to the versatility of the hardware, firmware, and software architectures, the platform is capable of interfacing with a wide variety of detector modules not only in medical imaging but also in homeland security applications. Analog signals from radiation detectors share similar characteristics-a pulse whose area is proportional to the deposited energy and whose leading edge is used to extract a timing signal. As a result, a generic design method of the platform is adopted for the hardware, firmware, and software architectures andmore » implementations. The analog front-end is hosted on a module called a Detector Board, where each board can filter, combine, timestamp, and process multiple channels independently. The processed data is formatted and sent through a backplane bus to a module called Support Board, where 1 Support Board can host up to eight Detector Board modules. The data in the Support Board, coming from 8 Detector Board modules, can be aggregated or correlated (if needed) depending on the algorithm implemented or runtime mode selected. It is then sent out to a computer workstation for further processing. The number of channels (detector modules), to be processed, mandates the overall OpenPET System Configuration, which is designed to handle up to 1,024 channels using 16-channel Detector Boards in the Standard System Configuration and 16,384 channels using 32-channel Detector Boards in the Large System Configuration.« less

MpTheory Java library: a multi-platform Java library for systems biology based on the Metabolic P theory.

PubMed

Marchetti, Luca; Manca, Vincenzo

2015-04-15

MpTheory Java library is an open-source project collecting a set of objects and algorithms for modeling observed dynamics by means of the Metabolic P (MP) theory, that is, a mathematical theory introduced in 2004 for modeling biological dynamics. By means of the library, it is possible to model biological systems both at continuous and at discrete time. Moreover, the library comprises a set of regression algorithms for inferring MP models starting from time series of observations. To enhance the modeling experience, beside a pure Java usage, the library can be directly used within the most popular computing environments, such as MATLAB, GNU Octave, Mathematica and R. The library is open-source and licensed under the GNU Lesser General Public License (LGPL) Version 3.0. Source code, binaries and complete documentation are available at http://mptheory.scienze.univr.it. luca.marchetti@univr.it, marchetti@cosbi.eu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Medical information, communication, and archiving system (MICAS): Phase II integration and acceptance testing

NASA Astrophysics Data System (ADS)

Smith, Edward M.; Wandtke, John; Robinson, Arvin E.

1999-07-01

The Medical Information, Communication and Archive System (MICAS) is a multi-modality integrated image management system that is seamlessly integrated with the Radiology Information System (RIS). This project was initiated in the summer of 1995 with the first phase being installed during the first half of 1997 and the second phase installed during the summer of 1998. Phase II enhancements include a permanent archive, automated workflow including modality worklist, study caches, NT diagnostic workstations with all components adhering to Digital Imaging and Communications in Medicine (DICOM) standards. This multi-vendor phased approach to PACS implementation is designed as an enterprise-wide PACS to provide images and reports throughout our healthcare network. MICAS demonstrates that aa multi-vendor open system phased approach to PACS is feasible, cost-effective, and has significant advantages over a single vendor implementation.

PDDL4J: a planning domain description library for java

NASA Astrophysics Data System (ADS)

Pellier, D.; Fiorino, H.

2018-01-01

PDDL4J (Planning Domain Description Library for Java) is an open source toolkit for Java cross-platform developers meant (1) to provide state-of-the-art planners based on the Pddl language, and (2) to facilitate research works on new planners. In this article, we present an overview of the Automated Planning concepts and languages. We present some planning systems and their most significant applications. Then, we detail the Pddl4j toolkit with an emphasis on the available informative structures, heuristics and search algorithms.

Development of a structural concept to resist impacts from multiyear ice floes, ridges, and icebergs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerwick, B.C.; Potter, R.E.; Rojansky, M.

1984-05-01

Large multi-year ice features and icebergs may have masses ranging up to 20 million tons or more and may move in the open water at speeds up to 1 knot, thus developing tremendous kinetic energy. A stepped structure concept has been developed to resist these impacts and to transfer the resultant forces and moments into the foundation thus developing a relatively high concentrated reaction force against the ice tending to spall and split it, thus causing a multi-modal failure of the ice, as well as using up kinetic energy at a relatively controlled rate. Calculated ice forces and ice failuremore » modes will be presented. The stepped structure concept is primarily applicable to production platforms in water depths of 50 to 200 meters, which are subject to impact of large ice features such as multi-year ridges, floes, and icebergs The resulting global ice loads are reduced by 50 percent or more as compared to those developed by a vertical or a steep sided structure. Overturning moments are reduced, thus reducing maxima soil bearing values. The structure itself is efficient in its use of structural materials, and is practicable for construction in prestressed reinforced concrete or steel/ concrete hybrid construction. It has acceptable draft during tow and can carry a fully outfitted deck. It is stable during all stages of installation.« less

Comparison of balance assessment modalities in emergency department elders: a pilot cross-sectional observational study.

PubMed

Caterino, Jeffrey M; Karaman, Rowan; Arora, Vinay; Martin, Jacqueline L; Hiestand, Brian C

2009-09-28

More than one-third of US adults 65 and over fall every year. These falls may cause serious injury including substantial long-term morbidity (due declines in activities of daily living) and death. The emergency department (ED) visit represents an opportunity for identifying high risk elders and potentially instituting falls-related interventions. The unique characteristic of the ED environment and patient population necessitate that risk-assessment modalities be validated in this specific setting. In order to better identify elders at risk of falls, we examined the relationship between patient-provided history of falling and two testing modalities (a balance plate system and the timed up-and-go [TUG] test) in elder emergency department (ED) patients. We conducted a cross-sectional observational study of patients > or = 60 years old being discharged from the ED. Patient history of falls in the past week, month, 6 months, and year was obtained. Balance plate center of pressure excursion (COP) measurements and TUG testing times were recorded. COP was recorded under four conditions: normal stability eyes open (NSEO) and closed (NSEC), and perturbed stability eyes open and closed. Correlation between TUG and COP scores was measured. Univariate logistic regression was used to identify the relationship between patient-provided falls history and the two testing modalities. Proportions, likelihood ratios, and receiver-operating-characteristic (ROC) curves for prediction of previous falls were reported. Fifty-three subjects were enrolled, 11% had fallen in the previous week and 42% in the previous year. There was no correlation between TUG and any balance plate measurements. In logistic regression, neither testing modality was associated with prior history of falls (p > 0.05 for all time periods). Balance plate NSEO and NSEC testing cutoffs could be identified which were 83% sensitive and had a negative likelihood ratio (LR-) of 0.3 for falls in the past week. TUG testing was not useful for falls in the past week, but performed best for more distant falls in the past month, 6 months, or year. TUG cutoffs with sensitivity over 80% and LR(-) of 0.17-0.32 could be identified for these time periods. Over 40% of community-dwelling elder ED patients report a fall within the past year. Balance plate and TUG testing were feasibly conducted in an ED setting. There is no relationship between scores on balance plate and TUG testing in these patients. In regression analysis, neither modality was significantly associated with patient provided history of falls. These modalities should not be adopted for screening purposes in elders in the ED setting without validation in future studies or as part of multi-factorial risk assessment.

Adaptation of Physiological and Cognitive Workload via Interactive Multi-modal Displays

DTIC Science & Technology

2014-05-28

peer-reviewed journals (N/A for none) 09/07/2013 Received Paper 8.00 James Merlo, Joseph E. Mercado , Jan B.F. Van Erp, Peter A. Hancock. Improving...08, . : , Mr. Joseph Mercado , Mr. Timothy White, Dr. Peter Hancock. Effects of Cross-Modal Sensory Cueing Automation Failurein a Target Detection Task...fields:...... ...... ...... ...... ...... PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: Discipline Joseph Mercado 0.50 Timothy White 0.50 1.00 2

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.

PubMed

Argelaguet, Ricard; Velten, Britta; Arnol, Damien; Dietrich, Sascha; Zenz, Thorsten; Marioni, John C; Buettner, Florian; Huber, Wolfgang; Stegle, Oliver

2018-06-20

Multi-omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy-chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multi-omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

An open source framework for tracking and state estimation ('Stone Soup')

NASA Astrophysics Data System (ADS)

Thomas, Paul A.; Barr, Jordi; Balaji, Bhashyam; White, Kruger

2017-05-01

The ability to detect and unambiguously follow all moving entities in a state-space is important in multiple domains both in defence (e.g. air surveillance, maritime situational awareness, ground moving target indication) and the civil sphere (e.g. astronomy, biology, epidemiology, dispersion modelling). However, tracking and state estimation researchers and practitioners have difficulties recreating state-of-the-art algorithms in order to benchmark their own work. Furthermore, system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather than intuitively or driven by personal favourites. We have therefore commenced the development of a collaborative initiative to create an open source framework for production, demonstration and evaluation of Tracking and State Estimation algorithms. The initiative will develop a (MIT-licensed) software platform for researchers and practitioners to test, verify and benchmark a variety of multi-sensor and multi-object state estimation algorithms. The initiative is supported by four defence laboratories, who will contribute to the development effort for the framework. The tracking and state estimation community will derive significant benefits from this work, including: access to repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple algorithms, standardisation of interfaces and access to challenging data sets. Keywords: Tracking,

WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research.

PubMed

Nazir, Sajid; Newey, Scott; Irvine, R Justin; Verdicchio, Fabio; Davidson, Paul; Fairhurst, Gorry; Wal, René van der

2017-01-01

The widespread availability of relatively cheap, reliable and easy to use digital camera traps has led to their extensive use for wildlife research, monitoring and public outreach. Users of these units are, however, often frustrated by the limited options for controlling camera functions, the generation of large numbers of images, and the lack of flexibility to suit different research environments and questions. We describe the development of a user-customisable open source camera trap platform named 'WiseEye', designed to provide flexible camera trap technology for wildlife researchers. The novel platform is based on a Raspberry Pi single-board computer and compatible peripherals that allow the user to control its functions and performance. We introduce the concept of confirmatory sensing, in which the Passive Infrared triggering is confirmed through other modalities (i.e. radar, pixel change) to reduce the occurrence of false positives images. This concept, together with user-definable metadata, aided identification of spurious images and greatly reduced post-collection processing time. When tested against a commercial camera trap, WiseEye was found to reduce the incidence of false positive images and false negatives across a range of test conditions. WiseEye represents a step-change in camera trap functionality, greatly increasing the value of this technology for wildlife research and conservation management.

WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research

PubMed Central

Nazir, Sajid; Newey, Scott; Irvine, R. Justin; Verdicchio, Fabio; Davidson, Paul; Fairhurst, Gorry; van der Wal, René

2017-01-01

The widespread availability of relatively cheap, reliable and easy to use digital camera traps has led to their extensive use for wildlife research, monitoring and public outreach. Users of these units are, however, often frustrated by the limited options for controlling camera functions, the generation of large numbers of images, and the lack of flexibility to suit different research environments and questions. We describe the development of a user-customisable open source camera trap platform named ‘WiseEye’, designed to provide flexible camera trap technology for wildlife researchers. The novel platform is based on a Raspberry Pi single-board computer and compatible peripherals that allow the user to control its functions and performance. We introduce the concept of confirmatory sensing, in which the Passive Infrared triggering is confirmed through other modalities (i.e. radar, pixel change) to reduce the occurrence of false positives images. This concept, together with user-definable metadata, aided identification of spurious images and greatly reduced post-collection processing time. When tested against a commercial camera trap, WiseEye was found to reduce the incidence of false positive images and false negatives across a range of test conditions. WiseEye represents a step-change in camera trap functionality, greatly increasing the value of this technology for wildlife research and conservation management. PMID:28076444

Enabling the Integrated Assessment of Large Marine Ecosystems: Informatics to the Forefront of Science-Based Decision Support

NASA Astrophysics Data System (ADS)

Di Stefano, M.; Fox, P. A.; Beaulieu, S. E.; Maffei, A. R.; West, P.; Hare, J. A.

2012-12-01

Integrated assessments of large marine ecosystems require the understanding of interactions between environmental, ecological, and socio-economic factors that affect production and utilization of marine natural resources. Assessing the functioning of complex coupled natural-human systems calls for collaboration between natural and social scientists across disciplinary and national boundaries. We are developing a platform to implement and sustain informatics solutions for these applications, providing interoperability among very diverse and heterogeneous data and information sources, as well as multi-disciplinary organizations and people. We have partnered with NOAA NMFS scientists to facilitate the deployment of an integrated ecosystem approach to management in the Northeast U.S. (NES) and California Current Large Marine Ecosystems (LMEs). Our platform will facilitate the collaboration and knowledge sharing among NMFS natural and social scientists, promoting community participation in integrating data, models, and knowledge. Here, we present collaborative software tools developed to aid the production of the Ecosystem Status Report (ESR) for the NES LME. The ESR addresses the D-P-S portion of the DPSIR (Driver-Pressure-State-Impact-Response) management framework: reporting data, indicators, and information products for climate drivers, physical and human (fisheries) pressures, and ecosystem state (primary and secondary production and higher trophic levels). We are developing our tools in open-source software, with the main tool based on a web application capable of providing the ability to work on multiple data types from a variety of sources, providing an effective way to share the source code used to generate data products and associated metadata as well as track workflow provenance to allow in the reproducibility of a data product. Our platform retrieves data, conducts standard analyses, reports data quality and other standardized metadata, provides iterative and interactive visualization, and enables the download of data plotted in the ESR. Data, indicators, and information products include time series, geographic maps, and uni-variate and multi-variate analyses. Also central to the success of this initiative is the commitment to accommodate and train scientists of multiple disciplines who will learn to interact effectively with this new integrated and interoperable ecosystem assessment capability. Traceability, repeatability, explanation, verification, and validation of data, indicators, and information products are important for cross-disciplinary understanding and sharing with managers, policymakers, and the public. We are also developing an ontology to support the implementation of the DPSIR framework. These new capabilities will serve as the essential foundation for the formal synthesis and quantitative analysis of information on relevant natural and socio-economic factors in relation to specified ecosystem management goals which can be applied in other LMEs.

Open Energy Info (OpenEI) (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2010-12-01

The Open Energy Information (OpenEI.org) initiative is a free, open-source, knowledge-sharing platform. OpenEI was created to provide access to data, models, tools, and information that accelerate the transition to clean energy systems through informed decisions.

Open-Source 3D-Printable Optics Equipment

PubMed Central

Zhang, Chenlong; Anzalone, Nicholas C.; Faria, Rodrigo P.; Pearce, Joshua M.

2013-01-01

Just as the power of the open-source design paradigm has driven down the cost of software to the point that it is accessible to most people, the rise of open-source hardware is poised to drive down the cost of doing experimental science to expand access to everyone. To assist in this aim, this paper introduces a library of open-source 3-D-printable optics components. This library operates as a flexible, low-cost public-domain tool set for developing both research and teaching optics hardware. First, the use of parametric open-source designs using an open-source computer aided design package is described to customize the optics hardware for any application. Second, details are provided on the use of open-source 3-D printers (additive layer manufacturing) to fabricate the primary mechanical components, which are then combined to construct complex optics-related devices. Third, the use of the open-source electronics prototyping platform are illustrated as control for optical experimental apparatuses. This study demonstrates an open-source optical library, which significantly reduces the costs associated with much optical equipment, while also enabling relatively easily adapted customizable designs. The cost reductions in general are over 97%, with some components representing only 1% of the current commercial investment for optical products of similar function. The results of this study make its clear that this method of scientific hardware development enables a much broader audience to participate in optical experimentation both as research and teaching platforms than previous proprietary methods. PMID:23544104

Open-source 3D-printable optics equipment.

PubMed

Zhang, Chenlong; Anzalone, Nicholas C; Faria, Rodrigo P; Pearce, Joshua M

2013-01-01

Just as the power of the open-source design paradigm has driven down the cost of software to the point that it is accessible to most people, the rise of open-source hardware is poised to drive down the cost of doing experimental science to expand access to everyone. To assist in this aim, this paper introduces a library of open-source 3-D-printable optics components. This library operates as a flexible, low-cost public-domain tool set for developing both research and teaching optics hardware. First, the use of parametric open-source designs using an open-source computer aided design package is described to customize the optics hardware for any application. Second, details are provided on the use of open-source 3-D printers (additive layer manufacturing) to fabricate the primary mechanical components, which are then combined to construct complex optics-related devices. Third, the use of the open-source electronics prototyping platform are illustrated as control for optical experimental apparatuses. This study demonstrates an open-source optical library, which significantly reduces the costs associated with much optical equipment, while also enabling relatively easily adapted customizable designs. The cost reductions in general are over 97%, with some components representing only 1% of the current commercial investment for optical products of similar function. The results of this study make its clear that this method of scientific hardware development enables a much broader audience to participate in optical experimentation both as research and teaching platforms than previous proprietary methods.

Maritime Analytics Prototype: Final Development Report

DTIC Science & Technology

2014-04-01

access management platform OpenAM , support for multiple instances of the same type of widget and support for installation specific configuration files to...et de la gestion de l’accès OpenAM , le support pour plusieurs instances du même type de widget et le support des fichiers d’installation de...open source authentication and access management platform OpenAM , support for multiple instances of the same type of widget and support for

Toward more efficient fabrication of high-density 2-D VCSEL arrays for spatial redundancy and/or multi-level signal communication

NASA Astrophysics Data System (ADS)

Roscher, Hendrik; Gerlach, Philipp; Khan, Faisal Nadeem; Kroner, Andrea; Stach, Martin; Weigl, Alexander; Michalzik, Rainer

2006-04-01

We present flip-chip attached high-speed VCSELs in 2-D arrays with record-high intra-cell packing densities. The advances of VCSEL array technology toward improved thermal performance and more efficient fabrication are reviewed, and the introduction of self-aligned features to these devices is pointed out. The structure of close-spaced wedge-shaped VCSELs is discussed and their static and dynamic characteristics are presented including an examination of the modal structure by near-field measurements. The lasers flip-chip bonded to a silicon-based test platform exhibit 3-dB and 10-dB bandwidths of 7.7 GHz and 9.8 GHz, respectively. Open 12.5 Gbit/s two-level eye patterns are demonstrated. We discuss the uses of high packing densities for the increase of the total amount of data throughput an array can deliver in the course of its life. One such approach is to provide up to two backup VCSELs per fiber channel that can extend the lifetimes of parallel transmitters through redundancy of light sources. Another is to increase the information density by using multiple VCSELs per 50 μm core diameter multimode fiber to generate more complex signals. A novel scheme using three butt-coupled VCSELs per fiber for the generation of four-level signals in the optical domain is proposed. First experiments are demonstrated using two VCSELs butt-coupled to the same standard glass fiber, each modulated with two-level signals to produce four-level signals at the photoreceiver. A four-level direct modulation of one VCSEL within a triple of devices produced first 20.6 Gbit/s (10.3 Gsymbols/s) four-level eyes, leaving two VCSELs as backup sources.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

EverVIEW: a visualization platform for hydrologic and Earth science gridded data

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Suir, Kevin J.; Conzelmann, Craig

2015-01-01

The EverVIEW Data Viewer is a cross-platform desktop application that combines and builds upon multiple open source libraries to help users to explore spatially-explicit gridded data stored in Network Common Data Form (NetCDF). Datasets are displayed across multiple side-by-side geographic or tabular displays, showing colorized overlays on an Earth globe or grid cell values, respectively. Time-series datasets can be animated to see how water surface elevation changes through time or how habitat suitability for a particular species might change over time under a given scenario. Initially targeted toward Florida's Everglades restoration planning, EverVIEW has been flexible enough to address the varied needs of large-scale planning beyond Florida, and is currently being used in biological planning efforts nationally and internationally.

Depth-resolved imaging of colon tumor using optical coherence tomography and fluorescence laminar optical tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tang, Qinggong; Frank, Aaron; Wang, Jianting; Chen, Chao-wei; Jin, Lily; Lin, Jon; Chan, Joanne M.; Chen, Yu

2016-03-01

Early detection of neoplastic changes remains a critical challenge in clinical cancer diagnosis and treatment. Many cancers arise from epithelial layers such as those of the gastrointestinal (GI) tract. Current standard endoscopic technology is unable to detect those subsurface lesions. Since cancer development is associated with both morphological and molecular alterations, imaging technologies that can quantitative image tissue's morphological and molecular biomarkers and assess the depth extent of a lesion in real time, without the need for tissue excision, would be a major advance in GI cancer diagnostics and therapy. In this research, we investigated the feasibility of multi-modal optical imaging including high-resolution optical coherence tomography (OCT) and depth-resolved high-sensitivity fluorescence laminar optical tomography (FLOT) for structural and molecular imaging. APC (adenomatous polyposis coli) mice model were imaged using OCT and FLOT and the correlated histopathological diagnosis was obtained. Quantitative structural (the scattering coefficient) and molecular imaging parameters (fluorescence intensity) from OCT and FLOT images were developed for multi-parametric analysis. This multi-modal imaging method has demonstrated the feasibility for more accurate diagnosis with 87.4% (87.3%) for sensitivity (specificity) which gives the most optimal diagnosis (the largest area under receiver operating characteristic (ROC) curve). This project results in a new non-invasive multi-modal imaging platform for improved GI cancer detection, which is expected to have a major impact on detection, diagnosis, and characterization of GI cancers, as well as a wide range of epithelial cancers.

The Multi-energy High precision Data Processor Based on AD7606

NASA Astrophysics Data System (ADS)

Zhao, Chen; Zhang, Yanchi; Xie, Da

2017-11-01

This paper designs an information collector based on AD7606 to realize the high-precision simultaneous acquisition of multi-source information of multi-energy systems to form the information platform of the energy Internet at Laogang with electricty as its major energy source. Combined with information fusion technologies, this paper analyzes the data to improve the overall energy system scheduling capability and reliability.

Dynamic XRD, Shock and Static Compression of CaF2

NASA Astrophysics Data System (ADS)

Kalita, Patricia; Specht, Paul; Root, Seth; Sinclair, Nicholas; Schuman, Adam; White, Melanie; Cornelius, Andrew; Smith, Jesse; Sinogeikin, Stanislav

2017-06-01

The high-pressure behavior of CaF2 is probed with x-ray diffraction (XRD) combined with both dynamic compression, using a two-stage light gas gun, and static compression, using diamond anvil cells. We use XRD to follow the unfolding of a shock-driven, fluorite to cotunnite phase transition, on the timescale of nanoseconds. The dynamic behavior of CaF2 under shock loading is contrasted with that under static compression. This work leverages experimental capabilities at the Advanced Photon Source: dynamic XRD and shock experiments at the Dynamic Compression Sector, as well as XRD and static compression in diamond anvil cell at the High-Pressure Collaborative Access Team. These experiments and cross-platform comparisons, open the door to an unprecedented understanding of equations of state and phase transitions at the microstructural level and at different time scales and will ultimately improve our capability to simulate the behavior of materials at extreme conditions. Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Spatial surveys of CH4 emissions with a mobile multi-gas sensing platform during DISCOVER-AQ and CAREBEIJING-NCP field campaigns

NASA Astrophysics Data System (ADS)

Tao, L.; Sun, K.; Miller, D. J.; Zhu, T.; Zondlo, M. A.

2013-12-01

Methane (CH4) is the second most important greenhouse gas, which has a greenhouse warming potential 25 times that of carbon dioxide (CO2) on a per molecule basis and century timescale. Since pre-industrial times, the atmospheric concentration of CH4 has increased by 150% and contributes significantly to global warming. CH4 emits from a wide range of both anthropogenic and natural sources, which make the CH4 emission measurements difficult. As a result, there is still a large uncertainty in the partitioning of estimated CH4 emissions. Mobile platforms have been used and demonstrated as an effective tool to map the CH4 emissions and provide a large spatial coverage over cities and localized rural sources. However, the information we can get is very limited based on the measured atmospheric CH4 concentrations solely, due to the complexity of the various CH4 sources and limited time resolution. We have developed a mobile multi-gas open-path laser-based sensing platform that performs high resolution (5 Hz), in-situ and simultaneous measurements of NH3, CH4, CO2, N2O, CO and H2O. The combination of six important trace gases helps to understand the characteristics of different CH4 sources and identify them. With this mobile platform, we have participated and perform spatial surveys in two field campaigns: DISCOVER-AQ in California and CAREBEIJING-NCP in China. During the DISCOVER-AQ campaigns, our mobile platform has covered around 4300 km (81 hours) in winter 2013 including agricultural regions in San Joaquin Valley and multiple cities urban areas along the coast. In the CAREBEIJING-NCP campaign, a survey along 3300 km (61 hours) of roadway in Beijing and its surrounding North China Plain has been conducted in June, 2013. A wide variety of CH4 emission sources have been identified and measured, such as livestock farming, oil/gas drilling, wastewater treatment, landfill, biomass burning and motor vehicles (include liquefied nature gas (LNG) vehicles). For example, the averaged value of measured CH4 in Tulare County, CA is ~2.44 ppmv with a maximum and minimum value of 1.91 ppmv and 67.80 ppmv, respectively. The dominant sources in Tulare County are dairy farms. Whereas in Beijing , the mean value of measured CH4 concentration for a full day sampling on the fourth ring road is ~2.40 ppmv with a minimum and maximum value of 2.18 ppmv and 12.8 ppmv CH4. The major sources in Beijing are motor vehicles, wastewater treatment facilities and gas stations. We analyze the signatures of different CH4 emission sources and provide their partitioning in our sample dataset.

VitaPad: visualization tools for the analysis of pathway data.

PubMed

Holford, Matthew; Li, Naixin; Nadkarni, Prakash; Zhao, Hongyu

2005-04-15

Packages that support the creation of pathway diagrams are limited by their inability to be readily extended to new classes of pathway-related data. VitaPad is a cross-platform application that enables users to create and modify biological pathway diagrams and incorporate microarray data with them. It improves on existing software in the following areas: (i) It can create diagrams dynamically through graph layout algorithms. (ii) It is open-source and uses an open XML format to store data, allowing for easy extension or integration with other tools. (iii) It features a cutting-edge user interface with intuitive controls, high-resolution graphics and fully customizable appearance. http://bioinformatics.med.yale.edu matthew.holford@yale.edu; hongyu.zhao@yale.edu.

Performance Evaluation Modeling of Network Sensors

NASA Technical Reports Server (NTRS)

Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.

2003-01-01

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akyol, Bora A.; Allwardt, Craig H.; Beech, Zachary W.

VOLTTRON is a flexible, reliable, and scalable platform for distributed control and sensing. VOLTTRON serves in four primary roles: •A reference platform for researchers to quickly develop control applications for transactive energy. •A reference platform with flexible data store support for energy analytics applications either in academia or in commercial enterprise. •A platform from which commercial enterprise can develop products without license issues and easily integrate into their product line. •An accelerator to drive industry adoption of transactive energy and advanced building energy analytics. Pacific Northwest National Laboratory, with funding from the U.S. Department of Energy’s Building Technologies Office, developedmore » and maintains VOLTTRON as an open-source community project. VOLTTRON source code includes agent execution software; agents that perform critical services that enable and enhance VOLTTRON functionality; and numerous agents that utilize the platform to perform a specific function (fault detection, demand response, etc.). The platform supports energy, operational, and financial transactions between networked entities (equipment, organizations, buildings, grid, etc.) and enhance the control infrastructure of existing buildings through the use of open-source device communication, control protocols, and integrated analytics.« less

MarDRe: efficient MapReduce-based removal of duplicate DNA reads in the cloud.

PubMed

Expósito, Roberto R; Veiga, Jorge; González-Domínguez, Jorge; Touriño, Juan

2017-09-01

This article presents MarDRe, a de novo cloud-ready duplicate and near-duplicate removal tool that can process single- and paired-end reads from FASTQ/FASTA datasets. MarDRe takes advantage of the widely adopted MapReduce programming model to fully exploit Big Data technologies on cloud-based infrastructures. Written in Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for scalable Big Data processing. On a 16-node cluster deployed on the Amazon EC2 cloud platform, MarDRe is up to 8.52 times faster than a representative state-of-the-art tool. Source code in Java and Hadoop as well as a user's guide are freely available under the GNU GPLv3 license at http://mardre.des.udc.es . rreye@udc.es. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Generalization of cross-modal stimulus equivalence classes: operant processes as components in human category formation.

PubMed Central

Lane, S D; Clow, J K; Innis, A; Critchfield, T S

1998-01-01

This study employed a stimulus-class rating procedure to explore whether stimulus equivalence and stimulus generalization can combine to promote the formation of open-ended categories incorporating cross-modal stimuli. A pretest of simple auditory discrimination indicated that subjects (college students) could discriminate among a range of tones used in the main study. Before beginning the main study, 10 subjects learned to use a rating procedure for categorizing sets of stimuli as class consistent or class inconsistent. After completing conditional discrimination training with new stimuli (shapes and tones), the subjects demonstrated the formation of cross-modal equivalence classes. Subsequently, the class-inclusion rating procedure was reinstituted, this time with cross-modal sets of stimuli drawn from the equivalence classes. On some occasions, the tones of the equivalence classes were replaced by novel tones. The probability that these novel sets would be rated as class consistent was generally a function of the auditory distance between the novel tone and the tone that was explicitly included in the equivalence class. These data extend prior work on generalization of equivalence classes, and support the role of operant processes in human category formation. PMID:9821680

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2017-01-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

Li, Alan; Chirayath, Ved

2017-01-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

NASA Astrophysics Data System (ADS)

Li, A. S. X.; Chirayath, V.; Segal-Rosenhaimer, M.; Das, K.

2017-12-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8% error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Python's extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Akuna: An Open Source User Environment for Managing Subsurface Simulation Workflows

NASA Astrophysics Data System (ADS)

Freedman, V. L.; Agarwal, D.; Bensema, K.; Finsterle, S.; Gable, C. W.; Keating, E. H.; Krishnan, H.; Lansing, C.; Moeglein, W.; Pau, G. S. H.; Porter, E.; Scheibe, T. D.

2014-12-01

The U.S. Department of Energy (DOE) is investing in development of a numerical modeling toolset called ASCEM (Advanced Simulation Capability for Environmental Management) to support modeling analyses at legacy waste sites. ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. The ASCEM toolset includes both a Platform with Integrated Toolsets (called Akuna) and a High-Performance Computing multi-process simulator (called Amanzi). The focus of this presentation is on Akuna, an open-source user environment that manages subsurface simulation workflows and associated data and metadata. In this presentation, key elements of Akuna are demonstrated, which includes toolsets for model setup, database management, sensitivity analysis, parameter estimation, uncertainty quantification, and visualization of both model setup and simulation results. A key component of the workflow is in the automated job launching and monitoring capabilities, which allow a user to submit and monitor simulation runs on high-performance, parallel computers. Visualization of large outputs can also be performed without moving data back to local resources. These capabilities make high-performance computing accessible to the users who might not be familiar with batch queue systems and usage protocols on different supercomputers and clusters.

Squid - a simple bioinformatics grid.

PubMed

Carvalho, Paulo C; Glória, Rafael V; de Miranda, Antonio B; Degrave, Wim M

2005-08-03

BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management.

PubMed

Neinstein, Aaron; Wong, Jenise; Look, Howard; Arbiter, Brandon; Quirk, Kent; McCanne, Steve; Sun, Yao; Blum, Michael; Adi, Saleh

2016-03-01

Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management

PubMed Central

Wong, Jenise; Look, Howard; Arbiter, Brandon; Quirk, Kent; McCanne, Steve; Sun, Yao; Blum, Michael; Adi, Saleh

2016-01-01

Objective Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. Materials and Methods An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. Results Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application (“app”), Blip, to visualize the data. Tidepool’s software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. Discussion By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. Conclusion The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool’s open source, cloud model for health data interoperability is applicable to other healthcare use cases. PMID:26338218

Fiji: an open-source platform for biological-image analysis.

PubMed

Schindelin, Johannes; Arganda-Carreras, Ignacio; Frise, Erwin; Kaynig, Verena; Longair, Mark; Pietzsch, Tobias; Preibisch, Stephan; Rueden, Curtis; Saalfeld, Stephan; Schmid, Benjamin; Tinevez, Jean-Yves; White, Daniel James; Hartenstein, Volker; Eliceiri, Kevin; Tomancak, Pavel; Cardona, Albert

2012-06-28

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

SIG Contribution in the Making of Geotechnical Maps in Urban Areas

NASA Astrophysics Data System (ADS)

Monteiro, António; Pais, Luís Andrade; Rodrigues, Carlos; Carvalho, Paulo

2017-10-01

The use of Geographic Information Systems (GIS) has spread to several science areas, from oceanography to geotechnics. Its application in the urban mapping was intensified in the last century, which allowed a great development, due to the use of geographic database, new analysis tools and, more recently, free open source software. Geotechnical cartography struggle with a permanent and large environment re-organization in urban area, due to new building construction, trenching and the drilling of sampling wells and holes. This creates an extra important and largest volume of data at any pre-existence geological map. The main problem results on the fact that the natural environment is covered with buildings and communications system. The purpose of this work is to create a viable geographic information base for geotechnical mapping through a free GIS computer program and open source, with non-traditional cartographic sources, giving preference to open platforms. QGIS was used as software and “Google Maps”, “Bing Maps” and “OpenStreetMap” were applied as cartographic sources using the “OpenLayers plugin” module. Finally, we also pretend to identify and delimit the degree of granite’s change and fracturing areas using a “Streetview” platform. This model has cartographic input which are a geological map study area, open cartographic web archives and the use of “Streetview” platform. The output has several layouts, such as topography intersection (roads, borders, etc.), with geological map and the bordering area of Guarda Urban Zone. The use of this platform types decrease the collect data time and, sometimes, a careful observation of pictures that were taken during excavations may reveal important details for geological mapping in the study area.

phylo-node: A molecular phylogenetic toolkit using Node.js.

PubMed

O'Halloran, Damien M

2017-01-01

Node.js is an open-source and cross-platform environment that provides a JavaScript codebase for back-end server-side applications. JavaScript has been used to develop very fast and user-friendly front-end tools for bioinformatic and phylogenetic analyses. However, no such toolkits are available using Node.js to conduct comprehensive molecular phylogenetic analysis. To address this problem, I have developed, phylo-node, which was developed using Node.js and provides a stable and scalable toolkit that allows the user to perform diverse molecular and phylogenetic tasks. phylo-node can execute the analysis and process the resulting outputs from a suite of software options that provides tools for read processing and genome alignment, sequence retrieval, multiple sequence alignment, primer design, evolutionary modeling, and phylogeny reconstruction. Furthermore, phylo-node enables the user to deploy server dependent applications, and also provides simple integration and interoperation with other Node modules and languages using Node inheritance patterns, and a customized piping module to support the production of diverse pipelines. phylo-node is open-source and freely available to all users without sign-up or login requirements. All source code and user guidelines are openly available at the GitHub repository: https://github.com/dohalloran/phylo-node.

GeneLab: NASA's Open Access, Collaborative Platform for Systems Biology and Space Medicine

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Thompson, Terri G.; Fogle, Homer W.; Rask, Jon C.; Coughlan, Joseph C.

2015-01-01

NASA is investing in GeneLab1 (http:genelab.nasa.gov), a multi-year effort to maximize utilization of the limited resources to conduct biological and medical research in space, principally aboard the International Space Station (ISS). High-throughput genomic, transcriptomic, proteomic or other omics analyses from experiments conducted on the ISS will be stored in the GeneLab Data Systems (GLDS), an open-science information system that will also include a biocomputation platform with collaborative science capabilities, to enable the discovery and validation of molecular networks.

moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization

ERIC Educational Resources Information Center

Pardos, Zachary A.; Whyte, Anthony; Kao, Kevin

2016-01-01

In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload…

U.S. Army Research Laboratory (ARL) multimodal signatures database

NASA Astrophysics Data System (ADS)

Bennett, Kelly

2008-04-01

The U.S. Army Research Laboratory (ARL) Multimodal Signatures Database (MMSDB) is a centralized collection of sensor data of various modalities that are co-located and co-registered. The signatures include ground and air vehicles, personnel, mortar, artillery, small arms gunfire from potential sniper weapons, explosives, and many other high value targets. This data is made available to Department of Defense (DoD) and DoD contractors, Intel agencies, other government agencies (OGA), and academia for use in developing target detection, tracking, and classification algorithms and systems to protect our Soldiers. A platform independent Web interface disseminates the signatures to researchers and engineers within the scientific community. Hierarchical Data Format 5 (HDF5) signature models provide an excellent solution for the sharing of complex multimodal signature data for algorithmic development and database requirements. Many open source tools for viewing and plotting HDF5 signatures are available over the Web. Seamless integration of HDF5 signatures is possible in both proprietary computational environments, such as MATLAB, and Free and Open Source Software (FOSS) computational environments, such as Octave and Python, for performing signal processing, analysis, and algorithm development. Future developments include extending the Web interface into a portal system for accessing ARL algorithms and signatures, High Performance Computing (HPC) resources, and integrating existing database and signature architectures into sensor networking environments.

OpenDA-WFLOW framework for improving hydrologic predictions using distributed hydrologic models

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Schellekens, Jaap; Kockx, Arno; Hummel, Stef

2017-04-01

Data assimilation (DA) holds considerable potential for improving hydrologic predictions (Liu et al., 2012) and increase the potential for early warning and/or smart water management. However, advances in hydrologic DA research have not yet been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. The objective of this work is to highlight the development of a generic linkage of the open source OpenDA package and the open source community hydrologic modeling framework Openstreams/WFLOW and its application in operational hydrological forecasting on various spatial scales. The coupling between OpenDA and Openstreams/wflow framework is based on the emerging standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift) developed by Hut et al. (2016). The potential application of the OpenDA-WFLOW for operational hydrologic forecasting including its integration with Delft-FEWS (used by more than 40 operational forecast centers around the world (Werner et al., 2013)) is demonstrated by the presented case studies. We will also highlight the possibility to give real-time insight into the working of the DA methods applied for supporting the forecaster as mentioned as one of the burning issues by Liu et al., (2012).

Development of a platform for co-registered ultrasound and MR contrast imaging in vivo

NASA Astrophysics Data System (ADS)

Chandrana, Chaitanya; Bevan, Peter; Hudson, John; Pang, Ian; Burns, Peter; Plewes, Donald; Chopra, Rajiv

2011-02-01

Imaging of the microvasculature is often performed using contrast agents in combination with either ultrasound (US) or magnetic resonance (MR) imaging. Contrast agents are used to enhance medical imaging by highlighting microvascular properties and function. Dynamic signal changes arising from the passage of contrast agents through the microvasculature can be used to characterize different pathologies; however, comparisons across modalities are difficult due to differences in the interactions of contrast agents with the microvasculature. Better knowledge of the relationship of contrast enhancement patterns with both modalities could enable better characterization of tissue microvasculature. We developed a co-registration platform for multi-modal US and MR imaging using clinical imaging systems in order to study the relationship between US and MR contrast enhancement. A preliminary validation study was performed in phantoms to determine the registration accuracy of the platform. In phantoms, the in-plane registration accuracy was measured to be 0.2 ± 0.2 and 0.3 ± 0.2 mm, in the lateral and axial directions, respectively. The out-of-plane registration accuracy was estimated to be 0.5 mm ±0.1. Co-registered US and MR imaging was performed in a rabbit model to evaluate contrast kinetics in different tissue types after bolus injections of US and MR contrast agents. The arrival time of the contrast agent in the plane of imaging was relatively similar for both modalities. We studied three different tissue types: muscle, large vessels and fat. In US, the temporal kinetics of signal enhancement were not strongly dependent on tissue type. In MR, however, due to the different amounts of agent extravasation in each tissue type, tissue-specific contrast kinetics were observed. This study demonstrates the feasibility of performing in vivo co-registered contrast US and MR imaging to study the relationships of the enhancement patterns with each modality.

Strategy and Structure for Online News Production - Case Studies of CNN and NRK

NASA Astrophysics Data System (ADS)

Krumsvik, Arne H.

This cross-national comparative case study of online news production analyzes the strategies of Cable News Network (CNN) and the Norwegian Broadcasting Corporation (NRK), aiming at understanding of the implications of organizational strategy on the role of journalists, explains why traditional media organizations have a tendency to develop a multi-platform approach (distributing content on several platforms, such as television, online, mobile) rather than developing the cross-media (with interplay between media types) or multimedia approach anticipated by both scholars and practitioners.

Multi-photon vertical cross-sectional imaging with a dynamically-balanced thin-film PZT z-axis microactuator.

PubMed

Choi, Jongsoo; Duan, Xiyu; Li, Haijun; Wang, Thomas D; Oldham, Kenn R

2017-10-01

Use of a thin-film piezoelectric microactuator for axial scanning during multi-photon vertical cross-sectional imaging is described. The actuator uses thin-film lead-zirconate-titanate (PZT) to generate upward displacement of a central mirror platform, micro-machined from a silicon-on-insulator (SOI) wafer to dimensions compatible with endoscopic imaging instruments. Device modeling in this paper focuses on existence of frequencies near device resonance producing vertical motion with minimal off-axis tilt even in the presence of multiple vibration modes and non-uniformity in fabrication outcomes. Operation near rear resonance permits large stroke lengths at low voltages relative to other vertical microactuators. Highly uniform vertical motion of the mirror platform is a key requirement for vertical cross-sectional imaging in the remote scan architecture being used for multi-photon instrument prototyping. The stage is installed in a benchtop testbed in combination with an electrostatic mirror that performs in-plane scanning. Vertical sectional images are acquired from 15 μm diameter beads and excised mouse colon tissue.

Enlisting User Community Perspectives to Inform Development of a Semantic Web Application for Discovery of Cross-Institutional Research Information and Data

NASA Astrophysics Data System (ADS)

Johns, E. M.; Mayernik, M. S.; Boler, F. M.; Corson-Rikert, J.; Daniels, M. D.; Gross, M. B.; Khan, H.; Maull, K. E.; Rowan, L. R.; Stott, D.; Williams, S.; Krafft, D. B.

2015-12-01

Researchers seek information and data through a variety of avenues: published literature, search engines, repositories, colleagues, etc. In order to build a web application that leverages linked open data to enable multiple paths for information discovery, the EarthCollab project has surveyed two geoscience user communities to consider how researchers find and share scholarly output. EarthCollab, a cross-institutional, EarthCube funded project partnering UCAR, Cornell University, and UNAVCO, is employing the open-source semantic web software, VIVO, as the underlying technology to connect the people and resources of virtual research communities. This study will present an analysis of survey responses from members of the two case study communities: (1) the Bering Sea Project, an interdisciplinary field program whose data archive is hosted by NCAR's Earth Observing Laboratory (EOL), and (2) UNAVCO, a geodetic facility and consortium that supports diverse research projects informed by geodesy. The survey results illustrate the types of research products that respondents indicate should be discoverable within a digital platform and the current methods used to find publications, data, personnel, tools, and instrumentation. The responses showed that scientists rely heavily on general purpose search engines, such as Google, to find information, but that data center websites and the published literature were also critical sources for finding collaborators, data, and research tools.The survey participants also identify additional features of interest for an information platform such as search engine indexing, connection to institutional web pages, generation of bibliographies and CVs, and outward linking to social media. Through the survey, the user communities prioritized the type of information that is most important to display and describe their work within a research profile. The analysis of this survey will inform our further development of a platform that will facilitate different types of information discovery strategies, and help researchers to find and use the associated resources of a research project.

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes - the MID-Frail study: study protocol for a randomised controlled trial

PubMed Central

2014-01-01

Background Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. Methods/Design The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. Discussion The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. Trial registration ClinicalTrials.gov: NCT01654341. PMID:24456998

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes--the MID-Frail study: study protocol for a randomised controlled trial.

PubMed

Rodríguez-Mañas, Leocadio; Bayer, Antony J; Kelly, Mark; Zeyfang, Andrej; Izquierdo, Mikel; Laosa, Olga; Hardman, Timothy C; Sinclair, Alan J; Moreira, Severina; Cook, Justin

2014-01-24

Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. ClinicalTrials.gov: NCT01654341.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Coupling between Theta Oscillations and Cognitive Control Network during Cross-Modal Visual and Auditory Attention: Supramodal vs Modality-Specific Mechanisms.

PubMed

Wang, Wuyi; Viswanathan, Shivakumar; Lee, Taraz; Grafton, Scott T

2016-01-01

Cortical theta band oscillations (4-8 Hz) in EEG signals have been shown to be important for a variety of different cognitive control operations in visual attention paradigms. However the synchronization source of these signals as defined by fMRI BOLD activity and the extent to which theta oscillations play a role in multimodal attention remains unknown. Here we investigated the extent to which cross-modal visual and auditory attention impacts theta oscillations. Using a simultaneous EEG-fMRI paradigm, healthy human participants performed an attentional vigilance task with six cross-modal conditions using naturalistic stimuli. To assess supramodal mechanisms, modulation of theta oscillation amplitude for attention to either visual or auditory stimuli was correlated with BOLD activity by conjunction analysis. Negative correlation was localized to cortical regions associated with the default mode network and positively with ventral premotor areas. Modality-associated attention to visual stimuli was marked by a positive correlation of theta and BOLD activity in fronto-parietal area that was not observed in the auditory condition. A positive correlation of theta and BOLD activity was observed in auditory cortex, while a negative correlation of theta and BOLD activity was observed in visual cortex during auditory attention. The data support a supramodal interaction of theta activity with of DMN function, and modality-associated processes within fronto-parietal networks related to top-down theta related cognitive control in cross-modal visual attention. On the other hand, in sensory cortices there are opposing effects of theta activity during cross-modal auditory attention.

Multi-modal diffuse optical techniques for breast cancer neoadjuvant chemotherapy monitoring (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cochran, Jeffrey M.; Busch, David R.; Ban, Han Y.; Kavuri, Venkaiah C.; Schweiger, Martin J.; Arridge, Simon R.; Yodh, Arjun G.

2017-02-01

We present high spatial density, multi-modal, parallel-plate Diffuse Optical Tomography (DOT) imaging systems for the purpose of breast tumor detection. One hybrid instrument provides time domain (TD) and continuous wave (CW) DOT at 64 source fiber positions. The TD diffuse optical spectroscopy with PMT- detection produces low-resolution images of absolute tissue scattering and absorption while the spatially dense array of CCD-coupled detector fibers (108 detectors) provides higher-resolution CW images of relative tissue optical properties. Reconstruction of the tissue optical properties, along with total hemoglobin concentration and tissue oxygen saturation, is performed using the TOAST software suite. Comparison of the spatially-dense DOT images and MR images allows for a robust validation of DOT against an accepted clinical modality. Additionally, the structural information from co-registered MR images is used as a spatial prior to improve the quality of the functional optical images and provide more accurate quantification of the optical and hemodynamic properties of tumors. We also present an optical-only imaging system that provides frequency domain (FD) DOT at 209 source positions with full CCD detection and incorporates optical fringe projection profilometry to determine the breast boundary. This profilometry serves as a spatial constraint, improving the quality of the DOT reconstructions while retaining the benefits of an optical-only device. We present initial images from both human subjects and phantoms to display the utility of high spatial density data and multi-modal information in DOT reconstruction with the two systems.

Dynamic Facial Expressions Prime the Processing of Emotional Prosody.

PubMed

Garrido-Vásquez, Patricia; Pell, Marc D; Paulmann, Silke; Kotz, Sonja A

2018-01-01

Evidence suggests that emotion is represented supramodally in the human brain. Emotional facial expressions, which often precede vocally expressed emotion in real life, can modulate event-related potentials (N100 and P200) during emotional prosody processing. To investigate these cross-modal emotional interactions, two lines of research have been put forward: cross-modal integration and cross-modal priming. In cross-modal integration studies, visual and auditory channels are temporally aligned, while in priming studies they are presented consecutively. Here we used cross-modal emotional priming to study the interaction of dynamic visual and auditory emotional information. Specifically, we presented dynamic facial expressions (angry, happy, neutral) as primes and emotionally-intoned pseudo-speech sentences (angry, happy) as targets. We were interested in how prime-target congruency would affect early auditory event-related potentials, i.e., N100 and P200, in order to shed more light on how dynamic facial information is used in cross-modal emotional prediction. Results showed enhanced N100 amplitudes for incongruently primed compared to congruently and neutrally primed emotional prosody, while the latter two conditions did not significantly differ. However, N100 peak latency was significantly delayed in the neutral condition compared to the other two conditions. Source reconstruction revealed that the right parahippocampal gyrus was activated in incongruent compared to congruent trials in the N100 time window. No significant ERP effects were observed in the P200 range. Our results indicate that dynamic facial expressions influence vocal emotion processing at an early point in time, and that an emotional mismatch between a facial expression and its ensuing vocal emotional signal induces additional processing costs in the brain, potentially because the cross-modal emotional prediction mechanism is violated in case of emotional prime-target incongruency.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Raspberry Pi-powered imaging for plant phenotyping.

PubMed

Tovar, Jose C; Hoyer, J Steen; Lin, Andy; Tielking, Allison; Callen, Steven T; Elizabeth Castillo, S; Miller, Michael; Tessman, Monica; Fahlgren, Noah; Carrington, James C; Nusinow, Dmitri A; Gehan, Malia A

2018-03-01

Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

Alternative magnetic flux leakage modalities for pipeline inspection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katragadda, G.; Lord, W.; Sun, Y.S.

1996-05-01

Increasing quality consciousness is placing higher demands on the accuracy and reliability of inspection systems used in defect detection and characterization. Nondestructive testing techniques often rely on using multi-transducer approaches to obtain greater defect sensitivity. This paper investigates the possibility of taking advantage of alternative modalities associated with the standard magnetic flux leakage tool to obtain additional defect information, while still using a single excitation source.

Open Source in Education

ERIC Educational Resources Information Center

Lakhan, Shaheen E.; Jhunjhunwala, Kavita

2008-01-01

Educational institutions have rushed to put their academic resources and services online, beginning the global community onto a common platform and awakening the interest of investors. Despite continuing technical challenges, online education shows great promise. Open source software offers one approach to addressing the technical problems in…

Easy research data handling with an OpenEarth DataLab for geo-monitoring research

NASA Astrophysics Data System (ADS)

Vanderfeesten, Maurice; van der Kuil, Annemiek; Prinčič, Alenka; den Heijer, Kees; Rombouts, Jeroen

2015-04-01

OpenEarth DataLab is an open source-based collaboration and processing platform to enable streamlined research data management from raw data ingest and transformation to interoperable distribution. It enables geo-scientists to easily synchronise, share, compute and visualise the dynamic and most up-to-date research data, scripts and models in multi-stakeholder geo-monitoring programs. This DataLab is developed by the Research Data Services team of TU Delft Library and 3TU.Datacentrum together with coastal engineers of Delft University of Technology and Deltares. Based on the OpenEarth software stack an environment has been developed to orchestrate numerous geo-related open source software components that can empower researchers and increase the overall research quality by managing research data; enabling automatic and interoperable data workflows between all the components with track & trace, hit & run data transformation processing in cloud infrastructure using MatLab and Python, synchronisation of data and scripts (SVN), and much more. Transformed interoperable data products (KML, NetCDF, PostGIS) can be used by ready-made OpenEarth tools for further analyses and visualisation, and can be distributed via interoperable channels such as THREDDS (OpenDAP) and GeoServer. An example of a successful application of OpenEarth DataLab is the Sand Motor, an innovative method for coastal protection in the Netherlands. The Sand Motor is a huge volume of sand that has been applied along the coast to be spread naturally by wind, waves and currents. Different research disciplines are involved concerned with: weather, waves and currents, sand distribution, water table and water quality, flora and fauna, recreation and management. Researchers share and transform their data in the OpenEarth DataLab, that makes it possible to combine their data and to see influence of different aspects of the coastal protection on their models. During the project the data are available only for the researchers involved. After the project a large part of the data and scripts will be published with DOI in the Data Archive of 3TU.Datacentrum for reuse in new research. For the 83 project members of the Sand Motor, the OpenEarth DataLab is available on www.zandmotordata.nl. The OpenEarth DataLab not only saves time and increases quality, but has the potential to open new frontiers for exploring cross-domain analysis and visualisations, revealing new scientific insights.

Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

2008-01-01

Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

Validation of diffuse optical tomography using a bi-functional optical-MRI contrast agent and a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Luk, Alex T.; Lin, Yuting; Grimmond, Brian; Sood, Anup; Uzgiris, Egidijus E.; Nalcioglu, Orhan; Gulsen, Gultekin

2013-03-01

Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"

GridAPPS-D

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-03-28

GridAPPS-D is an open-source, open architecture, standards based platform for development of advanced electric power system planning and operations applications. GridAPPS-D provides a documented data abstraction for the application developer enabling creation of applications that can be run in any compliant system or platform. This enables development of applications that are platform vendor independent applications and applications that take advantage of the possibility of data rich and data driven applications based on deployment of smart grid devices and systems.

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

PubMed

Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

2016-05-01

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

Xi-cam: Flexible High Throughput Data Processing for GISAXS

NASA Astrophysics Data System (ADS)

Pandolfi, Ronald; Kumar, Dinesh; Venkatakrishnan, Singanallur; Sarje, Abinav; Krishnan, Hari; Pellouchoud, Lenson; Ren, Fang; Fournier, Amanda; Jiang, Zhang; Tassone, Christopher; Mehta, Apurva; Sethian, James; Hexemer, Alexander

With increasing capabilities and data demand for GISAXS beamlines, supporting software is under development to handle larger data rates, volumes, and processing needs. We aim to provide a flexible and extensible approach to GISAXS data treatment as a solution to these rising needs. Xi-cam is the CAMERA platform for data management, analysis, and visualization. The core of Xi-cam is an extensible plugin-based GUI platform which provides users an interactive interface to processing algorithms. Plugins are available for SAXS/GISAXS data and data series visualization, as well as forward modeling and simulation through HipGISAXS. With Xi-cam's advanced mode, data processing steps are designed as a graph-based workflow, which can be executed locally or remotely. Remote execution utilizes HPC or de-localized resources, allowing for effective reduction of high-throughput data. Xi-cam is open-source and cross-platform. The processing algorithms in Xi-cam include parallel cpu and gpu processing optimizations, also taking advantage of external processing packages such as pyFAI. Xi-cam is available for download online.

Performance Evaluation of Block Acquisition and Tracking Algorithms Using an Open Source GPS Receiver Platform

NASA Technical Reports Server (NTRS)

Ramachandran, Ganesh K.; Akopian, David; Heckler, Gregory W.; Winternitz, Luke B.

2011-01-01

Location technologies have many applications in wireless communications, military and space missions, etc. US Global Positioning System (GPS) and other existing and emerging Global Navigation Satellite Systems (GNSS) are expected to provide accurate location information to enable such applications. While GNSS systems perform very well in strong signal conditions, their operation in many urban, indoor, and space applications is not robust or even impossible due to weak signals and strong distortions. The search for less costly, faster and more sensitive receivers is still in progress. As the research community addresses more and more complicated phenomena there exists a demand on flexible multimode reference receivers, associated SDKs, and development platforms which may accelerate and facilitate the research. One of such concepts is the software GPS/GNSS receiver (GPS SDR) which permits a facilitated access to algorithmic libraries and a possibility to integrate more advanced algorithms without hardware and essential software updates. The GNU-SDR and GPS-SDR open source receiver platforms are such popular examples. This paper evaluates the performance of recently proposed block-corelator techniques for acquisition and tracking of GPS signals using open source GPS-SDR platform.

A-Track: A new approach for detection of moving objects in FITS images

NASA Astrophysics Data System (ADS)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2016-10-01

We have developed a fast, open-source, cross-platform pipeline, called A-Track, for detecting the moving objects (asteroids and comets) in sequential telescope images in FITS format. The pipeline is coded in Python 3. The moving objects are detected using a modified line detection algorithm, called MILD. We tested the pipeline on astronomical data acquired by an SI-1100 CCD with a 1-meter telescope. We found that A-Track performs very well in terms of detection efficiency, stability, and processing time. The code is hosted on GitHub under the GNU GPL v3 license.

SolarPILOT Feature Requests and Collaboration | Concentrating Solar Power |

Science.gov Websites

DOE of the CSP community's needs. As of March 2018, SolarPILOT is also available as an open source project. While not every project benefits from an open source approach, several factors influenced this , but lack of availability has, in some cases, prevented widespread adoption of a common platform. Open

Pyteomics--a Python framework for exploratory data analysis and rapid software prototyping in proteomics.

PubMed

Goloborodko, Anton A; Levitsky, Lev I; Ivanov, Mark V; Gorshkov, Mikhail V

2013-02-01

Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python.org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com.

Command & Control in Virtual Environments: Designing a Virtual Environment for Experimentation

DTIC Science & Technology

2010-06-01

proceed with the research: Second Life/ OpenSim A popular leader in the desktop virtual worlds revolution, for many Second Life has become...prototype environments and adapt them quickly within the world. OpenSim is an open-source community built around upon the Second Life platform...functionality natively present in Second Life and the Opensim platform. With the recent release of Second Life Viewer 2.0, which contains a complete

RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration.

PubMed

Luo, Jake; Apperson-Hansen, Carolyn; Pelfrey, Clara M; Zhang, Guo-Qiang

2014-11-30

Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration. The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators' initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators' collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects. Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and increase research interactions among investigators.

Image-guided thoracic surgery in the hybrid operation room.

PubMed

Ujiie, Hideki; Effat, Andrew; Yasufuku, Kazuhiro

2017-01-01

There has been an increase in the use of image-guided technology to facilitate minimally invasive therapy. The next generation of minimally invasive therapy is focused on advancement and translation of novel image-guided technologies in therapeutic interventions, including surgery, interventional pulmonology, radiation therapy, and interventional laser therapy. To establish the efficacy of different minimally invasive therapies, we have developed a hybrid operating room, known as the guided therapeutics operating room (GTx OR) at the Toronto General Hospital. The GTx OR is equipped with multi-modality image-guidance systems, which features a dual source-dual energy computed tomography (CT) scanner, a robotic cone-beam CT (CBCT)/fluoroscopy, high-performance endobronchial ultrasound system, endoscopic surgery system, near-infrared (NIR) fluorescence imaging system, and navigation tracking systems. The novel multimodality image-guidance systems allow physicians to quickly, and accurately image patients while they are on the operating table. This yield improved outcomes since physicians are able to use image guidance during their procedures, and carry out innovative multi-modality therapeutics. Multiple preclinical translational studies pertaining to innovative minimally invasive technology is being developed in our guided therapeutics laboratory (GTx Lab). The GTx Lab is equipped with similar technology, and multimodality image-guidance systems as the GTx OR, and acts as an appropriate platform for translation of research into human clinical trials. Through the GTx Lab, we are able to perform basic research, such as the development of image-guided technologies, preclinical model testing, as well as preclinical imaging, and then translate that research into the GTx OR. This OR allows for the utilization of new technologies in cancer therapy, including molecular imaging, and other innovative imaging modalities, and therefore enables a better quality of life for patients, both during and after the procedure. In this article, we describe capabilities of the GTx systems, and discuss the first-in-human technologies used, and evaluated in GTx OR.

A Generic Software Architecture For Prognostics

NASA Technical Reports Server (NTRS)

Teubert, Christopher; Daigle, Matthew J.; Sankararaman, Shankar; Goebel, Kai; Watkins, Jason

2017-01-01

Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. As a result, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use.

Online molecular image repository and analysis system: A multicenter collaborative open-source infrastructure for molecular imaging research and application.

PubMed

Rahman, Mahabubur; Watabe, Hiroshi

2018-05-01

Molecular imaging serves as an important tool for researchers and clinicians to visualize and investigate complex biochemical phenomena using specialized instruments; these instruments are either used individually or in combination with targeted imaging agents to obtain images related to specific diseases with high sensitivity, specificity, and signal-to-noise ratios. However, molecular imaging, which is a multidisciplinary research field, faces several challenges, including the integration of imaging informatics with bioinformatics and medical informatics, requirement of reliable and robust image analysis algorithms, effective quality control of imaging facilities, and those related to individualized disease mapping, data sharing, software architecture, and knowledge management. As a cost-effective and open-source approach to address these challenges related to molecular imaging, we develop a flexible, transparent, and secure infrastructure, named MIRA, which stands for Molecular Imaging Repository and Analysis, primarily using the Python programming language, and a MySQL relational database system deployed on a Linux server. MIRA is designed with a centralized image archiving infrastructure and information database so that a multicenter collaborative informatics platform can be built. The capability of dealing with metadata, image file format normalization, and storing and viewing different types of documents and multimedia files make MIRA considerably flexible. With features like logging, auditing, commenting, sharing, and searching, MIRA is useful as an Electronic Laboratory Notebook for effective knowledge management. In addition, the centralized approach for MIRA facilitates on-the-fly access to all its features remotely through any web browser. Furthermore, the open-source approach provides the opportunity for sustainable continued development. MIRA offers an infrastructure that can be used as cross-boundary collaborative MI research platform for the rapid achievement in cancer diagnosis and therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Building a Billion Spatio-Temporal Object Search and Visualization Platform

NASA Astrophysics Data System (ADS)

Kakkar, D.; Lewis, B.

2017-10-01

With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Extinction cross-section cancellation of a cylindrical radiating active source near a rigid corner and acoustic invisibility

NASA Astrophysics Data System (ADS)

Mitri, F. G.

2017-11-01

Active cloaking in its basic form requires that the extinction cross-section (or energy efficiency) from a radiating body vanishes. In this analysis, this physical effect is demonstrated for an active cylindrically radiating acoustic source in a non-viscous fluid, undergoing periodic axisymmetric harmonic vibrations near a rigid corner (i.e., quarter-space). The rigorous multipole expansion method in cylindrical coordinates, the method of images, and the addition theorem of cylindrical wave functions are used to derive closed-form mathematical expressions for the radiating, amplification, and extinction cross-sections of the active source. Numerical computations are performed assuming monopole and dipole modal oscillations of the circular source. The results reveal some of the situations where the extinction energy efficiency factor of the active source vanishes depending on its size and location with respect to the rigid corner, thus, achieving total invisibility. Moreover, the extinction energy efficiency factor varies between positive or negative values. These effects also occur for higher-order modal oscillations of the active source. The results find potential applications in the development of acoustic cloaking devices and invisibility in underwater acoustics or other areas.

Sensor-agnostic photogrammetric image registration with applications to population modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Devin A; Moehl, Jessica J

2016-01-01

Photogrammetric registration of airborne and spaceborne imagery is a crucial prerequisite to many data fusion tasks. While embedded sensor models provide a rough geolocation estimate, these metadata may be incomplete or imprecise. Manual solutions are appropriate for small-scale projects, but for rapid streams of cross-modal, multi-sensor, multi-temporal imagery with varying metadata standards, an automated approach is required. We present a high-performance image registration workflow to address this need. This paper outlines the core development concepts and demonstrates its utility with respect to the 2016 data fusion contest imagery. In particular, Iris ultra-HD video is georeferenced to the Earth surface viamore » registration to DEIMOS-2 imagery, which serves as a trusted control source. Geolocation provides opportunity to augment the video with spatial context, stereo-derived disparity, spectral sensitivity, change detection, and numerous ancillary geospatial layers. We conclude by leveraging these derivative data layers towards one such fusion application: population distribution modeling.« less

Coupled auralization and virtual video for immersive multimedia displays

NASA Astrophysics Data System (ADS)

Henderson, Paul D.; Torres, Rendell R.; Shimizu, Yasushi; Radke, Richard; Lonsway, Brian

2003-04-01

The implementation of maximally-immersive interactive multimedia in exhibit spaces requires not only the presentation of realistic visual imagery but also the creation of a perceptually accurate aural experience. While conventional implementations treat audio and video problems as essentially independent, this research seeks to couple the visual sensory information with dynamic auralization in order to enhance perceptual accuracy. An implemented system has been developed for integrating accurate auralizations with virtual video techniques for both interactive presentation and multi-way communication. The current system utilizes a multi-channel loudspeaker array and real-time signal processing techniques for synthesizing the direct sound, early reflections, and reverberant field excited by a moving sound source whose path may be interactively defined in real-time or derived from coupled video tracking data. In this implementation, any virtual acoustic environment may be synthesized and presented in a perceptually-accurate fashion to many participants over a large listening and viewing area. Subject tests support the hypothesis that the cross-modal coupling of aural and visual displays significantly affects perceptual localization accuracy.

An Open Source Model for Open Access Journal Publication

PubMed Central

Blesius, Carl R.; Williams, Michael A.; Holzbach, Ana; Huntley, Arthur C.; Chueh, Henry

2005-01-01

We describe an electronic journal publication infrastructure that allows a flexible publication workflow, academic exchange around different forms of user submissions, and the exchange of articles between publishers and archives using a common XML based standard. This web-based application is implemented on a freely available open source software stack. This publication demonstrates the Dermatology Online Journal's use of the platform for non-biased independent open access publication. PMID:16779183

E-learning and blended learning in textile engineering education: a closed feedback loop approach

NASA Astrophysics Data System (ADS)

Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

2017-10-01

E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.

Trends in electro-optical electronic warfare

NASA Astrophysics Data System (ADS)

Smith, Carl R.; Grasso, Robert; Pledger, Jack; Murarka, Naveen

2012-09-01

Protection of military aircraft from hostile threats is paramount to ensure the survivability of aircrews, platforms, and mission success. While the threat environment continues to become more complex, shrinking defense budgets places new challenges on the development of electronic warfare (EW) systems. This paper presents the trends in electro-optical EW system development including 1) features, 2) affordability, 3) open architecture, 4) multi-functionality, 5) integrated avionics survivability equipment, and 6) enabling technologies for sensors, and optical sources. While these system attributes are not new, they have grown in importance in the design of EW systems. And, if treated correctly can have a beneficial symbiotic relationship to each other and to the airframe they support.

Open-source mobile digital platform for clinical trial data collection in low-resource settings.

PubMed

van Dam, Joris; Omondi Onyango, Kevin; Midamba, Brian; Groosman, Nele; Hooper, Norman; Spector, Jonathan; Pillai, Goonaseelan Colin; Ogutu, Bernhards

2017-02-01

Governments, universities and pan-African research networks are building durable infrastructure and capabilities for biomedical research in Africa. This offers the opportunity to adopt from the outset innovative approaches and technologies that would be challenging to retrofit into fully established research infrastructures such as those regularly found in high-income countries. In this context we piloted the use of a novel mobile digital health platform, designed specifically for low-resource environments, to support high-quality data collection in a clinical research study. Our primary aim was to assess the feasibility of a using a mobile digital platform for clinical trial data collection in a low-resource setting. Secondarily, we sought to explore the potential benefits of such an approach. The investigative site was a research institute in Nairobi, Kenya. We integrated an open-source platform for mobile data collection commonly used in the developing world with an open-source, standard platform for electronic data capture in clinical trials. The integration was developed using common data standards (Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model), maximising the potential to extend the approach to other platforms. The system was deployed in a pharmacokinetic study involving healthy human volunteers. The electronic data collection platform successfully supported conduct of the study. Multidisciplinary users reported high levels of satisfaction with the mobile application and highlighted substantial advantages when compared with traditional paper record systems. The new system also demonstrated a potential for expediting data quality review. This pilot study demonstrated the feasibility of using a mobile digital platform for clinical research data collection in low-resource settings. Sustainable scientific capabilities and infrastructure are essential to attract and support clinical research studies. Since many research structures in Africa are being developed anew, stakeholders should consider implementing innovative technologies and approaches.

AirShow 1.0 CFD Software Users' Guide

NASA Technical Reports Server (NTRS)

Mohler, Stanley R., Jr.

2005-01-01

AirShow is visualization post-processing software for Computational Fluid Dynamics (CFD). Upon reading binary PLOT3D grid and solution files into AirShow, the engineer can quickly see how hundreds of complex 3-D structured blocks are arranged and numbered. Additionally, chosen grid planes can be displayed and colored according to various aerodynamic flow quantities such as Mach number and pressure. The user may interactively rotate and translate the graphical objects using the mouse. The software source code was written in cross-platform Java, C++, and OpenGL, and runs on Unix, Linux, and Windows. The graphical user interface (GUI) was written using Java Swing. Java also provides multiple synchronized threads. The Java Native Interface (JNI) provides a bridge between the Java code and the C++ code where the PLOT3D files are read, the OpenGL graphics are rendered, and numerical calculations are performed. AirShow is easy to learn and simple to use. The source code is available for free from the NASA Technology Transfer and Partnership Office.

Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu

2015-01-01

Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data.

PubMed

Vaccarino, Anthony L; Dharsee, Moyez; Strother, Stephen; Aldridge, Don; Arnott, Stephen R; Behan, Brendan; Dafnas, Costas; Dong, Fan; Edgecombe, Kenneth; El-Badrawi, Rachad; El-Emam, Khaled; Gee, Tom; Evans, Susan G; Javadi, Mojib; Jeanson, Francis; Lefaivre, Shannon; Lutz, Kristen; MacPhee, F Chris; Mikkelsen, Jordan; Mikkelsen, Tom; Mirotchnick, Nicholas; Schmah, Tanya; Studzinski, Christa M; Stuss, Donald T; Theriault, Elizabeth; Evans, Kenneth R

2018-01-01

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute's "Brain-CODE" is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

PubMed Central

Vaccarino, Anthony L.; Dharsee, Moyez; Strother, Stephen; Aldridge, Don; Arnott, Stephen R.; Behan, Brendan; Dafnas, Costas; Dong, Fan; Edgecombe, Kenneth; El-Badrawi, Rachad; El-Emam, Khaled; Gee, Tom; Evans, Susan G.; Javadi, Mojib; Jeanson, Francis; Lefaivre, Shannon; Lutz, Kristen; MacPhee, F. Chris; Mikkelsen, Jordan; Mikkelsen, Tom; Mirotchnick, Nicholas; Schmah, Tanya; Studzinski, Christa M.; Stuss, Donald T.; Theriault, Elizabeth; Evans, Kenneth R.

2018-01-01

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute’s “Brain-CODE” is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care. PMID:29875648

A new tool for converting food frequency questionnaire data into nutrient and food group values: FETA research methods and availability

PubMed Central

Mulligan, Angela A; Luben, Robert N; Bhaniani, Amit; Parry-Smith, David J; O'Connor, Laura; Khawaja, Anthony P; Forouhi, Nita G; Khaw, Kay-Tee

2014-01-01

Objectives To describe the research methods for the development of a new open source, cross-platform tool which processes data from the European Prospective Investigation into Cancer and Nutrition Norfolk Food Frequency Questionnaire (EPIC-Norfolk FFQ). A further aim was to compare nutrient and food group values derived from the current tool (FETA, FFQ EPIC Tool for Analysis) with the previously validated but less accessible tool, CAFÉ (Compositional Analyses from Frequency Estimates). The effect of text matching on intake data was also investigated. Design Cross-sectional analysis of a prospective cohort study—EPIC-Norfolk. Setting East England population (city of Norwich and its surrounding small towns and rural areas). Participants Complete FFQ data from 11 250 men and 13 602 women (mean age 59 years; range 40–79 years). Outcome measures Nutrient and food group intakes derived from FETA and CAFÉ analyses of EPIC-Norfolk FFQ data. Results Nutrient outputs from FETA and CAFÉ were similar; mean (SD) energy intake from FETA was 9222 kJ (2633) in men, 8113 kJ (2296) in women, compared with CAFÉ intakes of 9175 kJ (2630) in men, 8091 kJ (2298) in women. The majority of differences resulted in one or less quintile change (98.7%). Only mean daily fruit and vegetable food group intakes were higher in women than in men (278 vs 212 and 284 vs 255 g, respectively). Quintile changes were evident for all nutrients, with the exception of alcohol, when text matching was not executed; however, only the cereals food group was affected. Conclusions FETA produces similar nutrient and food group values to the previously validated CAFÉ but has the advantages of being open source, cross-platform and complete with a data-entry form directly compatible with the software. The tool will facilitate research using the EPIC-Norfolk FFQ, and can be customised for different study populations. PMID:24674997

Cloud Based Earth Observation Data Exploitation Platforms

NASA Astrophysics Data System (ADS)

Romeo, A.; Pinto, S.; Loekken, S.; Marin, A.

2017-12-01

In the last few years data produced daily by several private and public Earth Observation (EO) satellites reached the order of tens of Terabytes, representing for scientists and commercial application developers both a big opportunity for their exploitation and a challenge for their management. New IT technologies, such as Big Data and cloud computing, enable the creation of web-accessible data exploitation platforms, which offer to scientists and application developers the means to access and use EO data in a quick and cost effective way. RHEA Group is particularly active in this sector, supporting the European Space Agency (ESA) in the Exploitation Platforms (EP) initiative, developing technology to build multi cloud platforms for the processing and analysis of Earth Observation data, and collaborating with larger European initiatives such as the European Plate Observing System (EPOS) and the European Open Science Cloud (EOSC). An EP is a virtual workspace, providing a user community with access to (i) large volume of data, (ii) algorithm development and integration environment, (iii) processing software and services (e.g. toolboxes, visualization routines), (iv) computing resources, (v) collaboration tools (e.g. forums, wiki, etc.). When an EP is dedicated to a specific Theme, it becomes a Thematic Exploitation Platform (TEP). Currently, ESA has seven TEPs in a pre-operational phase dedicated to geo-hazards monitoring and prevention, costal zones, forestry areas, hydrology, polar regions, urban areas and food security. On the technology development side, solutions like the multi cloud EO data processing platform provides the technology to integrate ICT resources and EO data from different vendors in a single platform. In particular it offers (i) Multi-cloud data discovery, (ii) Multi-cloud data management and access and (iii) Multi-cloud application deployment. This platform has been demonstrated with the EGI Federated Cloud, Innovation Platform Testbed Poland and the Amazon Web Services cloud. This work will present an overview of the TEPs and the multi-cloud EO data processing platform, and discuss their main achievements and their impacts in the context of distributed Research Infrastructures such as EPOS and EOSC.

Magnetic Nanoparticles for Multi-Imaging and Drug Delivery

PubMed Central

Lee, Jae-Hyun; Kim, Ji-wook; Cheon, Jinwoo

2013-01-01

Various bio-medical applications of magnetic nanoparticles have been explored during the past few decades. As tools that hold great potential for advancing biological sciences, magnetic nanoparticles have been used as platform materials for enhanced magnetic resonance imaging (MRI) agents, biological separation and magnetic drug delivery systems, and magnetic hyperthermia treatment. Furthermore, approaches that integrate various imaging and bioactive moieties have been used in the design of multi-modality systems, which possess synergistically enhanced properties such as better imaging resolution and sensitivity, molecular recognition capabilities, stimulus responsive drug delivery with on-demand control, and spatio-temporally controlled cell signal activation. Below, recent studies that focus on the design and synthesis of multi-mode magnetic nanoparticles will be briefly reviewed and their potential applications in the imaging and therapy areas will be also discussed. PMID:23579479

e-Science platform for translational biomedical imaging research: running, statistics, and analysis

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

2015-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

Optical sedimentation recorder

DOEpatents

Bishop, James K.B.

2014-05-06

A robotic optical sedimentation recorder is described for the recordation of carbon flux in the oceans wherein both POC and PIC particles are captured at the open end of a submersible sampling platform, the captured particles allowed to drift down onto a collection plate where they can be imaged over time. The particles are imaged using three separate light sources, activated in sequence, one source being a back light, a second source being a side light to provide dark field illumination, and a third source comprising a cross polarized light source to illuminate birefringent particles. The recorder in one embodiment is attached to a buoyancy unit which is capable upon command for bringing the sedimentation recorder to a programmed depth below the ocean surface during recordation mode, and on command returning the unit to the ocean surface for transmission of recorded data and receipt of new instructions. The combined unit is provided with its own power source and is designed to operate autonomously in the ocean for extended periods of time.

Therapeutic potential of CAR-T cell-derived exosomes: a cell-free modality for targeted cancer therapy.

PubMed

Tang, Xiang-Jun; Sun, Xu-Yong; Huang, Kuan-Ming; Zhang, Li; Yang, Zhuo-Shun; Zou, Dan-Dan; Wang, Bin; Warnock, Garth L; Dai, Long-Jun; Luo, Jie

2015-12-29

Chimeric antigen receptor (CAR)-based T-cell adoptive immunotherapy is a distinctively promising therapy for cancer. The engineering of CARs into T cells provides T cells with tumor-targeting capabilities and intensifies their cytotoxic activity through stimulated cell expansion and enhanced cytokine production. As a novel and potent therapeutic modality, there exists some uncontrollable processes which are the potential sources of adverse events. As an extension of this impactful modality, CAR-T cell-derived exosomes may substitute CAR-T cells to act as ultimate attackers, thereby overcoming some limitations. Exosomes retain most characteristics of parent cells and play an essential role in intercellular communications via transmitting their cargo to recipient cells. The application of CAR-T cell-derived exosomes will make this cell-based therapy more clinically controllable as it also provides a cell-free platform to diversify anticancer mediators, which responds effectively to the complexity and volatility of cancer. It is believed that the appropriate application of both cellular and exosomal platforms will make this effective treatment more practicable.

OpenQuake, a platform for collaborative seismic hazard and risk assessment

NASA Astrophysics Data System (ADS)

Henshaw, Paul; Burton, Christopher; Butler, Lars; Crowley, Helen; Danciu, Laurentiu; Nastasi, Matteo; Monelli, Damiano; Pagani, Marco; Panzeri, Luigi; Simionato, Michele; Silva, Vitor; Vallarelli, Giuseppe; Weatherill, Graeme; Wyss, Ben

2013-04-01

Sharing of data and risk information, best practices, and approaches across the globe is key to assessing risk more effectively. Through global projects, open-source IT development and collaborations with more than 10 regions, leading experts are collaboratively developing unique global datasets, best practice, tools and models for global seismic hazard and risk assessment, within the context of the Global Earthquake Model (GEM). Guided by the needs and experiences of governments, companies and international organisations, all contributions are being integrated into OpenQuake: a web-based platform that - together with other resources - will become accessible in 2014. With OpenQuake, stakeholders worldwide will be able to calculate, visualize and investigate earthquake hazard and risk, capture new data and share findings for joint learning. The platform is envisaged as a collaborative hub for earthquake risk assessment, used at global and local scales, around which an active network of users has formed. OpenQuake will comprise both online and offline tools, many of which can also be used independently. One of the first steps in OpenQuake development was the creation of open-source software for advanced seismic hazard and risk calculations at any scale, the OpenQuake Engine. Although in continuous development, a command-line version of the software is already being test-driven and used by hundreds worldwide; from non-profits in Central Asia, seismologists in sub-Saharan Africa and companies in South Asia to the European seismic hazard harmonization programme (SHARE). In addition, several technical trainings were organized with scientists from different regions of the world (sub-Saharan Africa, Central Asia, Asia-Pacific) to introduce the engine and other OpenQuake tools to the community, something that will continue to happen over the coming years. Other tools that are being developed of direct interest to the hazard community are: • OpenQuake Modeller; fundamental instruments for the creation of seismogenic input models for seismic hazard assessment, a critical input to the OpenQuake Engine. OpenQuake Modeller will consist of a suite of tools (Hazard Modellers Toolkit) for characterizing the seismogenic sources of earthquakes and their models of earthquakes recurrence. An earthquake catalogue homogenization tool, for integration, statistical comparison and user-defined harmonization of multiple catalogues of earthquakes is also included in the OpenQuake modeling tools. • A data capture tool for active faults; a tool that allows geologists to draw (new) fault discoveries on a map in an intuitive GIS-environment and add details on the fault through the tool. This data, once quality checked, can then be integrated with the global active faults database, which will increase in value with every new fault insertion. Building on many ongoing efforts and the knowledge of scientists worldwide, GEM will for the first time integrate state-of-the-art data, models, results and open-source tools into a single platform. The platform will continue to increase in value, in particular for use in local contexts, through contributions from and collaborations with scientists and organisations worldwide. This presentation will showcase the OpenQuake Platform, focusing on the IT solutions that have been adopted as well as the added value that the platform will bring to scientists worldwide.

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

PubMed Central

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron

2017-01-01

Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. PMID:28814063

Evaluation of DICOM viewer software for workflow integration in clinical trials

NASA Astrophysics Data System (ADS)

Haak, Daniel; Page, Charles E.; Kabino, Klaus; Deserno, Thomas M.

2015-03-01

The digital imaging and communications in medicine (DICOM) protocol is nowadays the leading standard for capture, exchange and storage of image data in medical applications. A broad range of commercial, free, and open source software tools supporting a variety of DICOM functionality exists. However, different from patient's care in hospital, DICOM has not yet arrived in electronic data capture systems (EDCS) for clinical trials. Due to missing integration, even just the visualization of patient's image data in electronic case report forms (eCRFs) is impossible. Four increasing levels for integration of DICOM components into EDCS are conceivable, raising functionality but also demands on interfaces with each level. Hence, in this paper, a comprehensive evaluation of 27 DICOM viewer software projects is performed, investigating viewing functionality as well as interfaces for integration. Concerning general, integration, and viewing requirements the survey involves the criteria (i) license, (ii) support, (iii) platform, (iv) interfaces, (v) two-dimensional (2D) and (vi) three-dimensional (3D) image viewing functionality. Optimal viewers are suggested for applications in clinical trials for 3D imaging, hospital communication, and workflow. Focusing on open source solutions, the viewers ImageJ and MicroView are superior for 3D visualization, whereas GingkoCADx is advantageous for hospital integration. Concerning workflow optimization in multi-centered clinical trials, we suggest the open source viewer Weasis. Covering most use cases, an EDCS and PACS interconnection with Weasis is suggested.

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

PubMed

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

2017-08-01

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

Multi-modal molecular diffuse optical tomography system for small animal imaging

PubMed Central

Guggenheim, James A.; Basevi, Hector R. A.; Frampton, Jon; Styles, Iain B.; Dehghani, Hamid

2013-01-01

A multi-modal optical imaging system for quantitative 3D bioluminescence and functional diffuse imaging is presented, which has no moving parts and uses mirrors to provide multi-view tomographic data for image reconstruction. It is demonstrated that through the use of trans-illuminated spectral near infrared measurements and spectrally constrained tomographic reconstruction, recovered concentrations of absorbing agents can be used as prior knowledge for bioluminescence imaging within the visible spectrum. Additionally, the first use of a recently developed multi-view optical surface capture technique is shown and its application to model-based image reconstruction and free-space light modelling is demonstrated. The benefits of model-based tomographic image recovery as compared to 2D planar imaging are highlighted in a number of scenarios where the internal luminescence source is not visible or is confounding in 2D images. The results presented show that the luminescence tomographic imaging method produces 3D reconstructions of individual light sources within a mouse-sized solid phantom that are accurately localised to within 1.5mm for a range of target locations and depths indicating sensitivity and accurate imaging throughout the phantom volume. Additionally the total reconstructed luminescence source intensity is consistent to within 15% which is a dramatic improvement upon standard bioluminescence imaging. Finally, results from a heterogeneous phantom with an absorbing anomaly are presented demonstrating the use and benefits of a multi-view, spectrally constrained coupled imaging system that provides accurate 3D luminescence images. PMID:24954977

C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

NASA Astrophysics Data System (ADS)

Riccio, Giuseppe; Brescia, Massimo; Cavuoti, Stefano; Mercurio, Amata; di Giorgio, Anna Maria; Molinari, Sergio

2017-06-01

In the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We present C 3 (Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.

A multi-modal training programme to improve physical activity, physical fitness and perceived physical ability in obese children.

PubMed

Morano, Milena; Colella, Dario; Rutigliano, Irene; Fiore, Pietro; Pettoello-Mantovani, Massimo; Campanozzi, Angelo

2014-01-01

Actual and perceived physical abilities are important correlates of physical activity (PA) and fitness, but little research has explored these relationships over time in obese children. This study was designed: (a) to assess the feasibility of a multi-modal training programme promoting changes in PA, fundamental motor skills and real and perceived physical abilities of obese children; and (b) to explore cross-sectional and longitudinal relationships between real and perceived physical competence in boys and girls. Forty-one participants (9.2 ± 1.2 years) were assessed before and after an 8-month intervention with respect to body composition, physical fitness, self-reported PA and perceived physical ability. After treatment, obese children reported improvements in the body mass index, PA levels, gross motor performance and actual and perceived physical abilities. Real and perceived physical competence was correlated in boys, but not in girls. Results indicate that a multi-modal programme focused on actual and perceived physical competence as associated with the gradual increase in the volume of activity might be an effective strategy to improve adherence of the participants and to increase the lifelong exercise skills of obese children.

Dynamic Dependence Analysis : Modeling and Inference of Changing Dependence Among Multiple Time-Series

DTIC Science & Technology

2009-06-01

isolation. In addition to being inherently multi-modal, human perception takes advantages of multiple sources of information within a single modality...restric- tion was reasonable for the applications we looked at. However, consider using a TIM to model a teacher student relationship among moving objects...That is, imagine one teacher object demonstrating a behavior for a student object. The student can observe the teacher and then recreate the behavior

A Platform for Scalable Satellite and Geospatial Data Analysis

NASA Astrophysics Data System (ADS)

Beneke, C. M.; Skillman, S.; Warren, M. S.; Kelton, T.; Brumby, S. P.; Chartrand, R.; Mathis, M.

2017-12-01

At Descartes Labs, we use the commercial cloud to run global-scale machine learning applications over satellite imagery. We have processed over 5 Petabytes of public and commercial satellite imagery, including the full Landsat and Sentinel archives. By combining open-source tools with a FUSE-based filesystem for cloud storage, we have enabled a scalable compute platform that has demonstrated reading over 200 GB/s of satellite imagery into cloud compute nodes. In one application, we generated global 15m Landsat-8, 20m Sentinel-1, and 10m Sentinel-2 composites from 15 trillion pixels, using over 10,000 CPUs. We recently created a public open-source Python client library that can be used to query and access preprocessed public satellite imagery from within our platform, and made this platform available to researchers for non-commercial projects. In this session, we will describe how you can use the Descartes Labs Platform for rapid prototyping and scaling of geospatial analyses and demonstrate examples in land cover classification.

An ontology based information system for the management of institutional repository's collections

NASA Astrophysics Data System (ADS)

Tsolakidis, A.; Kakoulidis, P.; Skourlas, C.

2015-02-01

In this paper we discuss a simple methodological approach to create, and customize institutional repositories for the domain of the technological education. The use of the open source software platform of DSpace is proposed to build up the repository application and provide access to digital resources including research papers, dissertations, administrative documents, educational material, etc. Also the use of owl ontologies is proposed for indexing and accessing the various, heterogeneous items stored in the repository. Customization and operation of a platform for the selection and use of terms or parts of similar existing owl ontologies is also described. This platform could be based on the open source software Protégé that supports owl, is widely used, and also supports visualization, SPARQL etc. The combined use of the owl platform and the DSpace repository form a basis for creating customized ontologies, accommodating the semantic metadata of items and facilitating searching.

An open-source platform to study uniaxial stress effects on nanoscale devices

NASA Astrophysics Data System (ADS)

Signorello, G.; Schraff, M.; Zellekens, P.; Drechsler, U.; Bürge, M.; Steinauer, H. R.; Heller, R.; Tschudy, M.; Riel, H.

2017-05-01

We present an automatic measurement platform that enables the characterization of nanodevices by electrical transport and optical spectroscopy as a function of the uniaxial stress. We provide insights into and detailed descriptions of the mechanical device, the substrate design and fabrication, and the instrument control software, which is provided under open-source license. The capability of the platform is demonstrated by characterizing the piezo-resistance of an InAs nanowire device using a combination of electrical transport and Raman spectroscopy. The advantages of this measurement platform are highlighted by comparison with state-of-the-art piezo-resistance measurements in InAs nanowires. We envision that the systematic application of this methodology will provide new insights into the physics of nanoscale devices and novel materials for electronics, and thus contribute to the assessment of the potential of strain as a technology booster for nanoscale electronics.

Suppression of fiber modal noise induced radial velocity errors for bright emission-line calibration sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahadevan, Suvrath; Halverson, Samuel; Ramsey, Lawrence

2014-05-01

Modal noise in optical fibers imposes limits on the signal-to-noise ratio (S/N) and velocity precision achievable with the next generation of astronomical spectrographs. This is an increasingly pressing problem for precision radial velocity spectrographs in the near-infrared (NIR) and optical that require both high stability of the observed line profiles and high S/N. Many of these spectrographs plan to use highly coherent emission-line calibration sources like laser frequency combs and Fabry-Perot etalons to achieve precision sufficient to detect terrestrial-mass planets. These high-precision calibration sources often use single-mode fibers or highly coherent sources. Coupling light from single-mode fibers to multi-mode fibersmore » leads to only a very low number of modes being excited, thereby exacerbating the modal noise measured by the spectrograph. We present a commercial off-the-shelf solution that significantly mitigates modal noise at all optical and NIR wavelengths, and which can be applied to spectrograph calibration systems. Our solution uses an integrating sphere in conjunction with a diffuser that is moved rapidly using electrostrictive polymers, and is generally superior to most tested forms of mechanical fiber agitation. We demonstrate a high level of modal noise reduction with a narrow bandwidth 1550 nm laser. Our relatively inexpensive solution immediately enables spectrographs to take advantage of the innate precision of bright state-of-the art calibration sources by removing a major source of systematic noise.« less

A Roadmap to Continuous Integration for ATLAS Software Development

NASA Astrophysics Data System (ADS)

Elmsheuser, J.; Krasznahorkay, A.; Obreshkov, E.; Undrus, A.; ATLAS Collaboration

2017-10-01

The ATLAS software infrastructure facilitates efforts of more than 1000 developers working on the code base of 2200 packages with 4 million lines of C++ and 1.4 million lines of python code. The ATLAS offline code management system is the powerful, flexible framework for processing new package versions requests, probing code changes in the Nightly Build System, migration to new platforms and compilers, deployment of production releases for worldwide access and supporting physicists with tools and interfaces for efficient software use. It maintains multi-stream, parallel development environment with about 70 multi-platform branches of nightly releases and provides vast opportunities for testing new packages, for verifying patches to existing software and for migrating to new platforms and compilers. The system evolution is currently aimed on the adoption of modern continuous integration (CI) practices focused on building nightly releases early and often, with rigorous unit and integration testing. This paper describes the CI incorporation program for the ATLAS software infrastructure. It brings modern open source tools such as Jenkins and GitLab into the ATLAS Nightly System, rationalizes hardware resource allocation and administrative operations, provides improved feedback and means to fix broken builds promptly for developers. Once adopted, ATLAS CI practices will improve and accelerate innovation cycles and result in increased confidence in new software deployments. The paper reports the status of Jenkins integration with the ATLAS Nightly System as well as short and long term plans for the incorporation of CI practices.

20170917 - A Cross-platform Format to Associate NMR-extracted data (NMReDATA) to Chemical Structures (SMASHNMR)

EPA Science Inventory

An open initiative involving cross-disciplinary contributors of computer-assisted structure elucidation (CASE), including methodology specialists, software and database developers and the editorial board of Magnetic Resonance in Chemistry, is addressing the old problem of reporti...

Stories from OpenAQ, a Global and Grassroots Open Air Quality Community

NASA Astrophysics Data System (ADS)

Hasenkopf, C. A.; Flasher, J. C.; Veerman, O.; Scalamogna, A.; Silva, D.; Salmon, M.; Buuralda, D.; DeWitt, L. H.

2016-12-01

Air pollution, responsible for more deaths each year than HIV/AIDS and malaria, combined, is a global public health crisis. Yet many scientific questions, including those directly relevant for policy, remain unanswered when it comes to the impact of air pollution on health in highly polluted environments. Often, specific solutions to improving air quality are local and sustained through public engagement, policy and monitoring. Both the overarching science of air quality and health and local solutions rely on access to reliable, timely air quality data. Over the past year, the OpenAQ community has opened up existing disparate air quality data in 24 countries through an open source platform (openaq.org) so that communities around the world can use it to advance science, public engagement, and policy. We will share stories of communities, from Delhi to Ulaanbaatar and from scientists to journalists, using open air quality data from our platform to advance their fight against air inequality. We will share recent research we have conducted on best practices for engaging different communities and building tools that enable the public to fully unleash the power of open air quality data to fight air inequality. The subsequent open-source tools (github.com/openaq) we have developed from this research and our entire data-sharing platform may be of interest to other open data communities.

An open-source software platform for data management, visualisation, model building and model sharing in water, energy and other resource modelling domains.

NASA Astrophysics Data System (ADS)

Knox, S.; Meier, P.; Mohammed, K.; Korteling, B.; Matrosov, E. S.; Hurford, A.; Huskova, I.; Harou, J. J.; Rosenberg, D. E.; Thilmant, A.; Medellin-Azuara, J.; Wicks, J.

2015-12-01

Capacity expansion on resource networks is essential to adapting to economic and population growth and pressures such as climate change. Engineered infrastructure systems such as water, energy, or transport networks require sophisticated and bespoke models to refine management and investment strategies. Successful modeling of such complex systems relies on good data management and advanced methods to visualize and share data.Engineered infrastructure systems are often represented as networks of nodes and links with operating rules describing their interactions. Infrastructure system management and planning can be abstracted to simulating or optimizing new operations and extensions of the network. By separating the data storage of abstract networks from manipulation and modeling we have created a system where infrastructure modeling across various domains is facilitated.We introduce Hydra Platform, a Free Open Source Software designed for analysts and modelers to store, manage and share network topology and data. Hydra Platform is a Python library with a web service layer for remote applications, called Apps, to connect. Apps serve various functions including network or results visualization, data export (e.g. into a proprietary format) or model execution. This Client-Server architecture allows users to manipulate and share centrally stored data. XML templates allow a standardised description of the data structure required for storing network data such that it is compatible with specific models.Hydra Platform represents networks in an abstract way and is therefore not bound to a single modeling domain. It is the Apps that create domain-specific functionality. Using Apps researchers from different domains can incorporate different models within the same network enabling cross-disciplinary modeling while minimizing errors and streamlining data sharing. Separating the Python library from the web layer allows developers to natively expand the software or build web-based apps in other languages for remote functionality. Partner CH2M is developing a commercial user-interface for Hydra Platform however custom interfaces and visualization tools can be built. Hydra Platform is available on GitHub while Apps will be shared on a central repository.

Paleomagnetism.org: An online multi-platform open source environment for paleomagnetic data analysis

NASA Astrophysics Data System (ADS)

Koymans, Mathijs R.; Langereis, Cor G.; Pastor-Galán, Daniel; van Hinsbergen, Douwe J. J.

2016-08-01

This contribution provides an overview of Paleomagnetism.org, an open-source, multi-platform online environment for paleomagnetic data analysis. Paleomagnetism.org provides an interactive environment where paleomagnetic data can be interpreted, evaluated, visualized, and exported. The Paleomagnetism.org application is split in to an interpretation portal, a statistics portal, and a portal for miscellaneous paleomagnetic tools. In the interpretation portal, principle component analysis can be performed on visualized demagnetization diagrams. Interpreted directions and great circles can be combined to find great circle solutions. These directions can be used in the statistics portal, or exported as data and figures. The tools in the statistics portal cover standard Fisher statistics for directions and VGPs, including other statistical parameters used as reliability criteria. Other available tools include an eigenvector approach foldtest, two reversal test including a Monte Carlo simulation on mean directions, and a coordinate bootstrap on the original data. An implementation is included for the detection and correction of inclination shallowing in sediments following TK03.GAD. Finally we provide a module to visualize VGPs and expected paleolatitudes, declinations, and inclinations relative to widely used global apparent polar wander path models in coordinates of major continent-bearing plates. The tools in the miscellaneous portal include a net tectonic rotation (NTR) analysis to restore a body to its paleo-vertical and a bootstrapped oroclinal test using linear regressive techniques, including a modified foldtest around a vertical axis. Paleomagnetism.org provides an integrated approach for researchers to work with visualized (e.g. hemisphere projections, Zijderveld diagrams) paleomagnetic data. The application constructs a custom exportable file that can be shared freely and included in public databases. This exported file contains all data and can later be imported to the application by other researchers. The accessibility and simplicity through which paleomagnetic data can be interpreted, analyzed, visualized, and shared makes Paleomagnetism.org of interest to the community.

Multi-octave spectral beam combiner on ultra-broadband photonic integrated circuit platform.

PubMed

Stanton, Eric J; Heck, Martijn J R; Bovington, Jock; Spott, Alexander; Bowers, John E

2015-05-04

We present the design of a novel platform that is able to combine optical frequency bands spanning 4.2 octaves from ultraviolet to mid-wave infrared into a single, low M2 output waveguide. We present the design and realization of a key component in this platform that combines the wavelength bands of 350 nm - 1500 nm and 1500 nm - 6500 nm with demonstrated efficiency greater than 90% in near-infrared and mid-wave infrared. The multi-octave spectral beam combiner concept is realized using an integrated platform with silicon nitride waveguides and silicon waveguides. Simulated bandwidth is shown to be over four octaves, and measured bandwidth is shown over two octaves, limited by the availability of sources.

Software Tools for Development on the Peregrine System | High-Performance

Science.gov Websites

Computing | NREL Software Tools for Development on the Peregrine System Software Tools for and manage software at the source code level. Cross-Platform Make and SCons The "Cross-Platform Make" (CMake) package is from Kitware, and SCons is a modern software build tool based on Python

Developing effective serious games: the effect of background sound on visual fidelity perception with varying texture resolution.

PubMed

Rojas, David; Kapralos, Bill; Cristancho, Sayra; Collins, Karen; Hogue, Andrew; Conati, Cristina; Dubrowski, Adam

2012-01-01

Despite the benefits associated with virtual learning environments and serious games, there are open, fundamental issues regarding simulation fidelity and multi-modal cue interaction and their effect on immersion, transfer of knowledge, and retention. Here we describe the results of a study that examined the effect of ambient (background) sound on the perception of visual fidelity (defined with respect to texture resolution). Results suggest that the perception of visual fidelity is dependent on ambient sound and more specifically, white noise can have detrimental effects on our perception of high quality visuals. The results of this study will guide future studies that will ultimately aid in developing an understanding of the role that fidelity, and multi-modal interactions play with respect to knowledge transfer and retention for users of virtual simulations and serious games.

Real-time implementation of logo detection on open source BeagleBoard

NASA Astrophysics Data System (ADS)

George, M.; Kehtarnavaz, N.; Estevez, L.

2011-03-01

This paper presents the real-time implementation of our previously developed logo detection and tracking algorithm on the open source BeagleBoard mobile platform. This platform has an OMAP processor that incorporates an ARM Cortex processor. The algorithm combines Scale Invariant Feature Transform (SIFT) with k-means clustering, online color calibration and moment invariants to robustly detect and track logos in video. Various optimization steps that are carried out to allow the real-time execution of the algorithm on BeagleBoard are discussed. The results obtained are compared to the PC real-time implementation results.

Cultural Geography Model Validation

DTIC Science & Technology

2010-03-01

the Cultural Geography Model (CGM), a government owned, open source multi - agent system utilizing Bayesian networks, queuing systems, the Theory of...referent determined either from theory or SME opinion. 4. CGM Overview The CGM is a government-owned, open source, data driven multi - agent social...HSCB, validation, social network analysis ABSTRACT: In the current warfighting environment , the military needs robust modeling and simulation (M&S

X-ray Diffraction and Multi-Frame Phase Contrast Imaging Diagnostics for IMPULSE at the Advanced Photon Source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iverson, Adam; Carlson, Carl; Young, Jason

2013-07-08

The diagnostic needs of any dynamic loading platform present unique technical challenges that must be addressed in order to accurately measure in situ material properties in an extreme environment. The IMPULSE platform (IMPact system for Ultrafast Synchrotron Experiments) at the Advanced Photon Source (APS) is no exception and, in fact, may be more challenging, as the imaging diagnostics must be synchronized to both the experiment and the 60 ps wide x-ray bunches produced at APS. The technical challenges of time-resolved x-ray diffraction imaging and high-resolution multi-frame phase contrast imaging (PCI) are described in this paper. Example data from recent IMPULSEmore » experiments are shown to illustrate the advances and evolution of these diagnostics with a focus on comparing the performance of two intensified CCD cameras and their suitability for multi-frame PCI. The continued development of these diagnostics is fundamentally important to IMPULSE and many other loading platforms and will benefit future facilities such as the Dynamic Compression Sector at APS and MaRIE at Los Alamos National Laboratory.« less

Grounding language in action and perception: From cognitive agents to humanoid robots

NASA Astrophysics Data System (ADS)

Cangelosi, Angelo

2010-06-01

In this review we concentrate on a grounded approach to the modeling of cognition through the methodologies of cognitive agents and developmental robotics. This work will focus on the modeling of the evolutionary and developmental acquisition of linguistic capabilities based on the principles of symbol grounding. We review cognitive agent and developmental robotics models of the grounding of language to demonstrate their consistency with the empirical and theoretical evidence on language grounding and embodiment, and to reveal the benefits of such an approach in the design of linguistic capabilities in cognitive robotic agents. In particular, three different models will be discussed, where the complexity of the agent's sensorimotor and cognitive system gradually increases: from a multi-agent simulation of language evolution, to a simulated robotic agent model for symbol grounding transfer, to a model of language comprehension in the humanoid robot iCub. The review also discusses the benefits of the use of humanoid robotic platform, and specifically of the open source iCub platform, for the study of embodied cognition.

Open chemistry registry and mapping platform based on open source cheminformatics toolkits (ACS Fall meeting)

EPA Science Inventory

TheOpen PHACTS project (openphacts.org) is a European initiative, constituting a public–private partnership to enable easier, cheaper and faster drug discovery [1]. The project is supported by the Open PHACTS Foundation (www.openphactsfoundation.org) and funded by contributions f...

OpenHealth Platform for Interactive Contextualization of Population Health Open Data.

PubMed

Almeida, Jonas S; Hajagos, Janos; Crnosija, Ivan; Kurc, Tahsin; Saltz, Mary; Saltz, Joel

The financial incentives for data science applications leading to improved health outcomes, such as DSRIP (bit.ly/dsrip), are well-aligned with the broad adoption of Open Data by State and Federal agencies. This creates entirely novel opportunities for analytical applications that make exclusive use of the pervasive Web Computing platform. The framework described here explores this new avenue to contextualize Health data in a manner that relies exclusively on the native JavaScript interpreter and data processing resources of the ubiquitous Web Browser. The OpenHealth platform is made publicly available, and is publicly hosted with version control and open source, at https://github.com/mathbiol/openHealth. The different data/analytics workflow architectures explored are accompanied with live applications ranging from DSRIP, such as Hospital Inpatient Prevention Quality Indicators at http://bit.ly/pqiSuffolk, to The Cancer Genome Atlas (TCGA) as illustrated by http://bit.ly/tcgascopeGBM.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

PubMed

Liu, Fang; Velikina, Julia V; Block, Walter F; Kijowski, Richard; Samsonov, Alexey A

2017-02-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed  ∼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

PubMed Central

Velikina, Julia V.; Block, Walter F.; Kijowski, Richard; Samsonov, Alexey A.

2017-01-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure. PMID:28113746

PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems.

PubMed

Ghaffarizadeh, Ahmadreza; Heiland, Randy; Friedman, Samuel H; Mumenthaler, Shannon M; Macklin, Paul

2018-02-01

Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal "virtual laboratory" for such multicellular systems simulates both the biochemical microenvironment (the "stage") and many mechanically and biochemically interacting cells (the "players" upon the stage). PhysiCell-physics-based multicellular simulator-is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility "out of the box." The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations; larger simulations are attainable on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a "cellular cargo delivery" system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net.

Microstructured fibres: a positive impact on defence technology?

NASA Astrophysics Data System (ADS)

O'Driscoll, E. J.; Watson, M. A.; Delmonte, T.; Petrovich, M. N.; Feng, X.; Flanagan, J. C.; Hayes, J. R.; Richardson, D. J.

2006-09-01

In this paper we seek to assess the potential impact of microstructured fibres for security and defence applications. Recent literature has presented results on using microstructured fibre for delivery of high power, high quality radiation and also on the use of microstructured fibre for broadband source generation. Whilst these two applications may appear contradictory to one another the inherent design flexibility of microstructured fibres allows fibres to be fabricated for the specific application requirements, either minimising (for delivery) or maximising (for broadband source generation) the nonlinear effects. In platform based laser applications such as infrared counter measures, remote sensing and laser directed-energy weapons, a suitable delivery fibre providing high power, high quality light delivery would allow a laser to be sited remotely from the sensor/device head. This opens up the possibility of several sensor/device types sharing the same multi-functional laser, thus reducing the complexity and hence the cost of such systems. For applications requiring broadband source characteristics, microstructured fibres can also offer advantages over conventional sources. By exploiting the nonlinear effects it is possible to realise a multifunctional source for applications such as active hyperspectral imaging, countermeasures, and biochemical sensing. These recent results suggest enormous potential for these novel fibre types to influence the next generation of photonic systems for security and defence applications. However, it is important to establish where the fibres can offer the greatest advantages and what research still needs to be done to drive the technology towards real platform solutions.

Open-WiSe: a solar powered wireless sensor network platform.

PubMed

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

LK Scripting Language

DOE Office of Scientific and Technical Information (OSTI.GOV)

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Versionmore » 3.0+ toolkit.« less

The Unidata Integrated Data Viewer

NASA Astrophysics Data System (ADS)

Weber, W. J.; Ho, Y.

2016-12-01

The Unidata Integrated Data Viewer (IDV) is a free and open source, virtual globe, software application that enables three dimensional viewing of earth science data. The Unidata IDV is data agnostic and can display and analyze disparate data in a single view. This capability facilitates cross discipline research and allows for multiple observation platforms to be displayed simultaneously for any given event. The Unidata IDV is a mature application, written in JAVA, and has been serving the earth science community for over 15 years. This demonstration will focus on near real time global satelliteobservations, the integration of the COSMIC radio occultation data set that profiles the atmosphere, and high resolution numerical weather prediction.

OSIRIX: open source multimodality image navigation software

NASA Astrophysics Data System (ADS)

Rosset, Antoine; Pysher, Lance; Spadola, Luca; Ratib, Osman

2005-04-01

The goal of our project is to develop a completely new software platform that will allow users to efficiently and conveniently navigate through large sets of multidimensional data without the need of high-end expensive hardware or software. We also elected to develop our system on new open source software libraries allowing other institutions and developers to contribute to this project. OsiriX is a free and open-source imaging software designed manipulate and visualize large sets of medical images: http://homepage.mac.com/rossetantoine/osirix/

Open Ephys: an open-source, plugin-based platform for multichannel electrophysiology.

PubMed

Siegle, Joshua H; López, Aarón Cuevas; Patel, Yogi A; Abramov, Kirill; Ohayon, Shay; Voigts, Jakob

2017-08-01

Closed-loop experiments, in which causal interventions are conditioned on the state of the system under investigation, have become increasingly common in neuroscience. Such experiments can have a high degree of explanatory power, but they require a precise implementation that can be difficult to replicate across laboratories. We sought to overcome this limitation by building open-source software that makes it easier to develop and share algorithms for closed-loop control. We created the Open Ephys GUI, an open-source platform for multichannel electrophysiology experiments. In addition to the standard 'open-loop' visualization and recording functionality, the GUI also includes modules for delivering feedback in response to events detected in the incoming data stream. Importantly, these modules can be built and shared as plugins, which makes it possible for users to extend the functionality of the GUI through a simple API, without having to understand the inner workings of the entire application. In combination with low-cost, open-source hardware for amplifying and digitizing neural signals, the GUI has been used for closed-loop experiments that perturb the hippocampal theta rhythm in a phase-specific manner. The Open Ephys GUI is the first widely used application for multichannel electrophysiology that leverages a plugin-based workflow. We hope that it will lower the barrier to entry for electrophysiologists who wish to incorporate real-time feedback into their research.

Open Ephys: an open-source, plugin-based platform for multichannel electrophysiology

NASA Astrophysics Data System (ADS)

Siegle, Joshua H.; Cuevas López, Aarón; Patel, Yogi A.; Abramov, Kirill; Ohayon, Shay; Voigts, Jakob

2017-08-01

Objective. Closed-loop experiments, in which causal interventions are conditioned on the state of the system under investigation, have become increasingly common in neuroscience. Such experiments can have a high degree of explanatory power, but they require a precise implementation that can be difficult to replicate across laboratories. We sought to overcome this limitation by building open-source software that makes it easier to develop and share algorithms for closed-loop control. Approach. We created the Open Ephys GUI, an open-source platform for multichannel electrophysiology experiments. In addition to the standard ‘open-loop’ visualization and recording functionality, the GUI also includes modules for delivering feedback in response to events detected in the incoming data stream. Importantly, these modules can be built and shared as plugins, which makes it possible for users to extend the functionality of the GUI through a simple API, without having to understand the inner workings of the entire application. Main results. In combination with low-cost, open-source hardware for amplifying and digitizing neural signals, the GUI has been used for closed-loop experiments that perturb the hippocampal theta rhythm in a phase-specific manner. Significance. The Open Ephys GUI is the first widely used application for multichannel electrophysiology that leverages a plugin-based workflow. We hope that it will lower the barrier to entry for electrophysiologists who wish to incorporate real-time feedback into their research.

Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

PubMed

Kapur, Tina; Pieper, Steve; Fedorov, Andriy; Fillion-Robin, J-C; Halle, Michael; O'Donnell, Lauren; Lasso, Andras; Ungi, Tamas; Pinter, Csaba; Finet, Julien; Pujol, Sonia; Jagadeesan, Jayender; Tokuda, Junichi; Norton, Isaiah; Estepar, Raul San Jose; Gering, David; Aerts, Hugo J W L; Jakab, Marianna; Hata, Nobuhiko; Ibanez, Luiz; Blezek, Daniel; Miller, Jim; Aylward, Stephen; Grimson, W Eric L; Fichtinger, Gabor; Wells, William M; Lorensen, William E; Schroeder, Will; Kikinis, Ron

2016-10-01

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigation into the use of satellite remote sensing data products as part of a multi-modal marine environmental monitoring network

NASA Astrophysics Data System (ADS)

O'Connor, Edel; Smeaton, Alan F.; O'Connor, Noel E.; Regan, Fiona

2012-09-01

In this paper it is investigated how conventional in-situ sensor networks can be complemented by the satellite data streams available through numerous platforms orbiting the earth and the combined analyses products available through services such as MyOcean. Despite the numerous benefits associated with the use of satellite remote sensing data products, there are a number of limitations with their use in coastal zones. Here the ability of these data sources to provide contextual awareness, redundancy and increased efficiency to an in-situ sensor network is investigated. The potential use of a variety of chlorophyll and SST data products as additional data sources in the SmartBay monitoring network in Galway Bay, Ireland is analysed. The ultimate goal is to investigate the ability of these products to create a smarter marine monitoring network with increased efficiency. Overall it was found that while care needs to be taken in choosing these products, there was extremely promising performance from a number of these products that would be suitable in the context of a number of applications especially in relation to SST. It was more difficult to come to conclusive results for the chlorophyll analysis.

Engaging older adults in the visualization of sensor data facilitated by an open platform for connected devices.

PubMed

Bock, Christian; Demiris, George; Choi, Yong; Le, Thai; Thompson, Hilaire J; Samuel, Arjmand; Huang, Danny

2016-03-11

The use of smart home sensor systems is growing primarily due to the appeal of unobtrusively monitoring older adult health and wellness. However, integrating large-scale sensor systems within residential settings can be challenging when deployment takes place across multiple environments, requiring customization of applications, connection across various devices and effective visualization of complex longitudinal data. The objective of the study was to demonstrate the implementation of a smart home system using an open, extensible platform in a real-world setting and develop an application to visualize data real time. We deployed the open source Lab of Things platform in a house of 11 residents as a demonstration of feasibility over the course of 3 months. The system consisted of Aeon Labs Z-wave Door/Window sensors and an Aeon Labs Multi-sensor that collected data on motion, temperature, luminosity, and humidity. We applied a Rapid Iterative Testing and Evaluation approach towards designing a visualization interface engaging gerontological experts. We then conducted a survey with 19 older adult and caregiver stakeholders to inform further design revisions. Our initial visualization mockups consisted of a bar chart representing activity level over time. Family members felt comfortable using the application. Older adults however, indicated it would be difficult to learn to use the application, and had trouble identifying utility. A key for older adults was ensuring that the data collected could be utilized by their family members, physicians, or caregivers. The approach described in this work is generalizable towards future smart home deployments and can be a valuable guide for researchers to scale a study across multiple homes and connected devices, and to create personalized interfaces for end users.

Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools.

PubMed

Ham, Timothy S; Dmytriv, Zinovii; Plahar, Hector; Chen, Joanna; Hillson, Nathan J; Keasling, Jay D

2012-10-01

The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about 'legacy' parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.

Multi-contrast light profile microscopy for the depth-resolved imaging of the properties of multi-ply thin films.

PubMed

Power, J F

2009-06-01

Light profile microscopy (LPM) is a direct method for the spectral depth imaging of thin film cross-sections on the micrometer scale. LPM uses a perpendicular viewing configuration that directly images a source beam propagated through a thin film. Images are formed in dark field contrast, which is highly sensitive to subtle interfacial structures that are invisible to reference methods. The independent focusing of illumination and imaging systems allows multiple registered optical sources to be hosted on a single platform. These features make LPM a powerful multi-contrast (MC) imaging technique, demonstrated in this work with six modes of imaging in a single instrument, based on (1) broad-band elastic scatter; (2) laser excited wideband luminescence; (3) coherent elastic scatter; (4) Raman scatter (three channels with RGB illumination); (5) wavelength resolved luminescence; and (6) spectral broadband scatter, resolved in immediate succession. MC-LPM integrates Raman images with a wider optical and morphological picture of the sample than prior art microprobes. Currently, MC-LPM resolves images at an effective spectral resolution better than 9 cm(-1), at a spatial resolution approaching 1 microm, with optics that operate in air at half the maximum numerical aperture of the prior art microprobes.

Cross-modal Association between Auditory and Visuospatial Information in Mandarin Tone Perception in Noise by Native and Non-native Perceivers.

PubMed

Hannah, Beverly; Wang, Yue; Jongman, Allard; Sereno, Joan A; Cao, Jiguo; Nie, Yunlong

2017-01-01

Speech perception involves multiple input modalities. Research has indicated that perceivers establish cross-modal associations between auditory and visuospatial events to aid perception. Such intermodal relations can be particularly beneficial for speech development and learning, where infants and non-native perceivers need additional resources to acquire and process new sounds. This study examines how facial articulatory cues and co-speech hand gestures mimicking pitch contours in space affect non-native Mandarin tone perception. Native English as well as Mandarin perceivers identified tones embedded in noise with either congruent or incongruent Auditory-Facial (AF) and Auditory-FacialGestural (AFG) inputs. Native Mandarin results showed the expected ceiling-level performance in the congruent AF and AFG conditions. In the incongruent conditions, while AF identification was primarily auditory-based, AFG identification was partially based on gestures, demonstrating the use of gestures as valid cues in tone identification. The English perceivers' performance was poor in the congruent AF condition, but improved significantly in AFG. While the incongruent AF identification showed some reliance on facial information, incongruent AFG identification relied more on gestural than auditory-facial information. These results indicate positive effects of facial and especially gestural input on non-native tone perception, suggesting that cross-modal (visuospatial) resources can be recruited to aid auditory perception when phonetic demands are high. The current findings may inform patterns of tone acquisition and development, suggesting how multi-modal speech enhancement principles may be applied to facilitate speech learning.

Cross-modal Association between Auditory and Visuospatial Information in Mandarin Tone Perception in Noise by Native and Non-native Perceivers

PubMed Central

Hannah, Beverly; Wang, Yue; Jongman, Allard; Sereno, Joan A.; Cao, Jiguo; Nie, Yunlong

2017-01-01

Speech perception involves multiple input modalities. Research has indicated that perceivers establish cross-modal associations between auditory and visuospatial events to aid perception. Such intermodal relations can be particularly beneficial for speech development and learning, where infants and non-native perceivers need additional resources to acquire and process new sounds. This study examines how facial articulatory cues and co-speech hand gestures mimicking pitch contours in space affect non-native Mandarin tone perception. Native English as well as Mandarin perceivers identified tones embedded in noise with either congruent or incongruent Auditory-Facial (AF) and Auditory-FacialGestural (AFG) inputs. Native Mandarin results showed the expected ceiling-level performance in the congruent AF and AFG conditions. In the incongruent conditions, while AF identification was primarily auditory-based, AFG identification was partially based on gestures, demonstrating the use of gestures as valid cues in tone identification. The English perceivers’ performance was poor in the congruent AF condition, but improved significantly in AFG. While the incongruent AF identification showed some reliance on facial information, incongruent AFG identification relied more on gestural than auditory-facial information. These results indicate positive effects of facial and especially gestural input on non-native tone perception, suggesting that cross-modal (visuospatial) resources can be recruited to aid auditory perception when phonetic demands are high. The current findings may inform patterns of tone acquisition and development, suggesting how multi-modal speech enhancement principles may be applied to facilitate speech learning. PMID:29255435

Mousetrap: An integrated, open-source mouse-tracking package.

PubMed

Kieslich, Pascal J; Henninger, Felix

2017-10-01

Mouse-tracking - the analysis of mouse movements in computerized experiments - is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os .

Cross-modal face recognition using multi-matcher face scores

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2015-05-01

The performance of face recognition can be improved using information fusion of multimodal images and/or multiple algorithms. When multimodal face images are available, cross-modal recognition is meaningful for security and surveillance applications. For example, a probe face is a thermal image (especially at nighttime), while only visible face images are available in the gallery database. Matching a thermal probe face onto the visible gallery faces requires crossmodal matching approaches. A few such studies were implemented in facial feature space with medium recognition performance. In this paper, we propose a cross-modal recognition approach, where multimodal faces are cross-matched in feature space and the recognition performance is enhanced with stereo fusion at image, feature and/or score level. In the proposed scenario, there are two cameras for stereo imaging, two face imagers (visible and thermal images) in each camera, and three recognition algorithms (circular Gaussian filter, face pattern byte, linear discriminant analysis). A score vector is formed with three cross-matched face scores from the aforementioned three algorithms. A classifier (e.g., k-nearest neighbor, support vector machine, binomial logical regression [BLR]) is trained then tested with the score vectors by using 10-fold cross validations. The proposed approach was validated with a multispectral stereo face dataset from 105 subjects. Our experiments show very promising results: ACR (accuracy rate) = 97.84%, FAR (false accept rate) = 0.84% when cross-matching the fused thermal faces onto the fused visible faces by using three face scores and the BLR classifier.

Computational high-resolution heart phantoms for medical imaging and dosimetry simulations

NASA Astrophysics Data System (ADS)

Gu, Songxiang; Gupta, Rajiv; Kyprianou, Iacovos

2011-09-01

Cardiovascular disease in general and coronary artery disease (CAD) in particular, are the leading cause of death worldwide. They are principally diagnosed using either invasive percutaneous transluminal coronary angiograms or non-invasive computed tomography angiograms (CTA). Minimally invasive therapies for CAD such as angioplasty and stenting are rendered under fluoroscopic guidance. Both invasive and non-invasive imaging modalities employ ionizing radiation and there is concern for deterministic and stochastic effects of radiation. Accurate simulation to optimize image quality with minimal radiation dose requires detailed, gender-specific anthropomorphic phantoms with anatomically correct heart and associated vasculature. Such phantoms are currently unavailable. This paper describes an open source heart phantom development platform based on a graphical user interface. Using this platform, we have developed seven high-resolution cardiac/coronary artery phantoms for imaging and dosimetry from seven high-quality CTA datasets. To extract a phantom from a coronary CTA, the relationship between the intensity distribution of the myocardium, the ventricles and the coronary arteries is identified via histogram analysis of the CTA images. By further refining the segmentation using anatomy-specific criteria such as vesselness, connectivity criteria required by the coronary tree and image operations such as active contours, we are able to capture excellent detail within our phantoms. For example, in one of the female heart phantoms, as many as 100 coronary artery branches could be identified. Triangular meshes are fitted to segmented high-resolution CTA data. We have also developed a visualization tool for adding stenotic lesions to the coronaries. The male and female heart phantoms generated so far have been cross-registered and entered in the mesh-based Virtual Family of phantoms with matched age/gender information. Any phantom in this family, along with user-defined stenoses, can be used to obtain clinically realistic projection images with the Monte Carlo code penMesh for optimizing imaging and dosimetry.

OpenAQ: A Platform to Aggregate and Freely Share Global Air Quality Data

NASA Astrophysics Data System (ADS)

Hasenkopf, C. A.; Flasher, J. C.; Veerman, O.; DeWitt, H. L.

2015-12-01

Thousands of ground-based air quality monitors around the world publicly publish real-time air quality data; however, researchers and the public do not have access to this information in the ways most useful to them. Often, air quality data are posted on obscure websites showing only current values, are programmatically inaccessible, and/or are in inconsistent data formats across sites. Yet, historical and programmatic access to such a global dataset would be transformative to several scientific fields, from epidemiology to low-cost sensor technologies to estimates of ground-level aerosol by satellite retrievals. To increase accessibility and standardize this disparate dataset, we have built OpenAQ, an innovative, open platform created by a group of scientists and open data programmers. The source code for the platform is viewable at github.com/openaq. Currently, we are aggregating, storing, and making publicly available real-time air quality data (PM2.5, PM10, SO2, NO2, and O3) via an Application Program Interface (API). We will present the OpenAQ platform, which currently has the following specific capabilities: A continuous ingest mechanism for some of the most polluted cities, generalizable to more sources An API providing data-querying, including ability to filter by location, measurement type and value and date, as well as custom sort options A generalized, chart-based visualization tool to explore data accessible via the API At this stage, we are seeking wider participation and input from multiple research communities in expanding our data retrieval sites, standardizing our protocols, receiving feedback on quality issues, and creating tools that can be built on top of this open platform.

RadMAP: The Radiological Multi-sensor Analysis Platform

NASA Astrophysics Data System (ADS)

Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik; Chivers, Daniel H.; Cooper, Reynold J.; Curtis, Joseph C.; Davis, John R.; Joshi, Tenzing H.; Kua, John; Meyer, Ross; Negut, Victor; Quinlan, Michael; Quiter, Brian J.; Srinivasan, Shreyas; Zakhor, Avideh; Zhang, Richard; Vetter, Kai

2016-12-01

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. In this paper we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

KOLAM: a cross-platform architecture for scalable visualization and tracking in wide-area imagery

NASA Astrophysics Data System (ADS)

Fraser, Joshua; Haridas, Anoop; Seetharaman, Guna; Rao, Raghuveer M.; Palaniappan, Kannappan

2013-05-01

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness.

Research on Visualization of Ground Laser Radar Data Based on Osg

NASA Astrophysics Data System (ADS)

Huang, H.; Hu, C.; Zhang, F.; Xue, H.

2018-04-01

Three-dimensional (3D) laser scanning is a new advanced technology integrating light, machine, electricity, and computer technologies. It can conduct 3D scanning to the whole shape and form of space objects with high precision. With this technology, you can directly collect the point cloud data of a ground object and create the structure of it for rendering. People use excellent 3D rendering engine to optimize and display the 3D model in order to meet the higher requirements of real time realism rendering and the complexity of the scene. OpenSceneGraph (OSG) is an open source 3D graphics engine. Compared with the current mainstream 3D rendering engine, OSG is practical, economical, and easy to expand. Therefore, OSG is widely used in the fields of virtual simulation, virtual reality, science and engineering visualization. In this paper, a dynamic and interactive ground LiDAR data visualization platform is constructed based on the OSG and the cross-platform C++ application development framework Qt. In view of the point cloud data of .txt format and the triangulation network data file of .obj format, the functions of 3D laser point cloud and triangulation network data display are realized. It is proved by experiments that the platform is of strong practical value as it is easy to operate and provides good interaction.

Cloudwave: distributed processing of "big data" from electrophysiological recordings for epilepsy clinical research using Hadoop.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical "big data" consisting of more than 100 multi-channel signals with recordings from each patient generating 5-10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a "private cloud". Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with "montages" for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave).

Cloudwave: Distributed Processing of “Big Data” from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

PubMed Central

Jayapandian, Catherine P.; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D.; Zhang, Guo-Qiang; Sahoo, Satya S.

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave) PMID:24551370

Open Targets: a platform for therapeutic target identification and validation

PubMed Central

Koscielny, Gautier; An, Peter; Carvalho-Silva, Denise; Cham, Jennifer A.; Fumis, Luca; Gasparyan, Rippa; Hasan, Samiul; Karamanis, Nikiforos; Maguire, Michael; Papa, Eliseo; Pierleoni, Andrea; Pignatelli, Miguel; Platt, Theo; Rowland, Francis; Wankar, Priyanka; Bento, A. Patrícia; Burdett, Tony; Fabregat, Antonio; Forbes, Simon; Gaulton, Anna; Gonzalez, Cristina Yenyxe; Hermjakob, Henning; Hersey, Anne; Jupe, Steven; Kafkas, Şenay; Keays, Maria; Leroy, Catherine; Lopez, Francisco-Javier; Magarinos, Maria Paula; Malone, James; McEntyre, Johanna; Munoz-Pomer Fuentes, Alfonso; O'Donovan, Claire; Papatheodorou, Irene; Parkinson, Helen; Palka, Barbara; Paschall, Justin; Petryszak, Robert; Pratanwanich, Naruemon; Sarntivijal, Sirarat; Saunders, Gary; Sidiropoulos, Konstantinos; Smith, Thomas; Sondka, Zbyslaw; Stegle, Oliver; Tang, Y. Amy; Turner, Edward; Vaughan, Brendan; Vrousgou, Olga; Watkins, Xavier; Martin, Maria-Jesus; Sanseau, Philippe; Vamathevan, Jessica; Birney, Ewan; Barrett, Jeffrey; Dunham, Ian

2017-01-01

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org. PMID:27899665

Three-dimensional multi bioluminescent sources reconstruction based on adaptive finite element method

NASA Astrophysics Data System (ADS)

Ma, Xibo; Tian, Jie; Zhang, Bo; Zhang, Xing; Xue, Zhenwen; Dong, Di; Han, Dong

2011-03-01

Among many optical molecular imaging modalities, bioluminescence imaging (BLI) has more and more wide application in tumor detection and evaluation of pharmacodynamics, toxicity, pharmacokinetics because of its noninvasive molecular and cellular level detection ability, high sensitivity and low cost in comparison with other imaging technologies. However, BLI can not present the accurate location and intensity of the inner bioluminescence sources such as in the bone, liver or lung etc. Bioluminescent tomography (BLT) shows its advantage in determining the bioluminescence source distribution inside a small animal or phantom. Considering the deficiency of two-dimensional imaging modality, we developed three-dimensional tomography to reconstruct the information of the bioluminescence source distribution in transgenic mOC-Luc mice bone with the boundary measured data. In this paper, to study the osteocalcin (OC) accumulation in transgenic mOC-Luc mice bone, a BLT reconstruction method based on multilevel adaptive finite element (FEM) algorithm was used for localizing and quantifying multi bioluminescence sources. Optical and anatomical information of the tissues are incorporated as a priori knowledge in this method, which can reduce the ill-posedness of BLT. The data was acquired by the dual modality BLT and Micro CT prototype system that was developed by us. Through temperature control and absolute intensity calibration, a relative accurate intensity can be calculated. The location of the OC accumulation was reconstructed, which was coherent with the principle of bone differentiation. This result also was testified by ex vivo experiment in the black 96-plate well using the BLI system and the chemiluminescence apparatus.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

Amanzi: An Open-Source Multi-process Simulator for Environmental Applications

NASA Astrophysics Data System (ADS)

Moulton, J. D.; Molins, S.; Johnson, J. N.; Coon, E.; Lipnikov, K.; Day, M.; Barker, E.

2014-12-01

The Advanced Simulation Capabililty for Environmental Management (ASCEM) program is developing an approach and open-source tool suite for standardized risk and performance assessments at legacy nuclear waste sites. These assessments begin with simplified models, and add geometric and geologic complexity as understanding is gained. The Platform toolsets (Akuna) generates these conceptual models and Amanzi provides the computational engine to perform the simulations, returning the results for analysis and visualization. In this presentation we highlight key elements of the design, algorithms and implementations used in Amanzi. In particular, the hierarchical and modular design is aligned with the coupled processes being sumulated, and naturally supports a wide range of model complexity. This design leverages a dynamic data manager and the synergy of two graphs (one from the high-level perspective of the models the other from the dependencies of the variables in the model) to enable this flexible model configuration at run time. Moreover, to model sites with complex hydrostratigraphy, as well as engineered systems, we are developing a dual unstructured/structured capability. Recently, these capabilities have been collected in a framework named Arcos, and efforts have begun to improve interoperability between the unstructured and structured AMR approaches in Amanzi. To leverage a range of biogeochemistry capability from the community (e.g., CrunchFlow, PFLOTRAN, etc.), a biogeochemistry interface library was developed called Alquimia. To ensure that Amanzi is truly an open-source community code we require a completely open-source tool chain for our development. We will comment on elements of this tool chain, including the testing and documentation development tools such as docutils, and Sphinx. Finally, we will show simulation results from our phased demonstrations, including the geochemically complex Savannah River F-Area seepage basins.

Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances.

PubMed

Sáez, Carlos; Robles, Montserrat; García-Gómez, Juan M

2017-02-01

Biomedical data may be composed of individuals generated from distinct, meaningful sources. Due to possible contextual biases in the processes that generate data, there may exist an undesirable and unexpected variability among the probability distribution functions (PDFs) of the source subsamples, which, when uncontrolled, may lead to inaccurate or unreproducible research results. Classical statistical methods may have difficulties to undercover such variabilities when dealing with multi-modal, multi-type, multi-variate data. This work proposes two metrics for the analysis of stability among multiple data sources, robust to the aforementioned conditions, and defined in the context of data quality assessment. Specifically, a global probabilistic deviation and a source probabilistic outlyingness metrics are proposed. The first provides a bounded degree of the global multi-source variability, designed as an estimator equivalent to the notion of normalized standard deviation of PDFs. The second provides a bounded degree of the dissimilarity of each source to a latent central distribution. The metrics are based on the projection of a simplex geometrical structure constructed from the Jensen-Shannon distances among the sources PDFs. The metrics have been evaluated and demonstrated their correct behaviour on a simulated benchmark and with real multi-source biomedical data using the UCI Heart Disease data set. The biomedical data quality assessment based on the proposed stability metrics may improve the efficiency and effectiveness of biomedical data exploitation and research.

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

KNIME for reproducible cross-domain analysis of life science data.

PubMed

Fillbrunn, Alexander; Dietz, Christian; Pfeuffer, Julianus; Rahn, René; Landrum, Gregory A; Berthold, Michael R

2017-11-10

Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing. Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis. Such scripts are not only prone to be platform dependent, they also tend to grow as the experiment progresses and are seldomly well documented, a fact that hinders the reproducibility of the experiment. Workflow systems such as KNIME Analytics Platform aim to solve these problems by providing a platform for connecting tools graphically and guaranteeing the same results on different operating systems. As an open source software, KNIME allows scientists and programmers to provide their own extensions to the scientific community. In this review paper we present selected extensions from the life sciences that simplify data exploration, analysis, and visualization and are interoperable due to KNIME's unified data model. Additionally, we name other workflow systems that are commonly used in the life sciences and highlight their similarities and differences to KNIME. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Development and validation of an open source quantification tool for DSC-MRI studies.

PubMed

Gordaliza, P M; Mateos-Pérez, J M; Montesinos, P; Guzmán-de-Villoria, J A; Desco, M; Vaquero, J J

2015-03-01

This work presents the development of an open source tool for the quantification of dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies. The development of this tool is motivated by the lack of open source tools implemented on open platforms to allow external developers to implement their own quantification methods easily and without the need of paying for a development license. This quantification tool was developed as a plugin for the ImageJ image analysis platform using the Java programming language. A modular approach was used in the implementation of the components, in such a way that the addition of new methods can be done without breaking any of the existing functionalities. For the validation process, images from seven patients with brain tumors were acquired and quantified with the presented tool and with a widely used clinical software package. The resulting perfusion parameters were then compared. Perfusion parameters and the corresponding parametric images were obtained. When no gamma-fitting is used, an excellent agreement with the tool used as a gold-standard was obtained (R(2)>0.8 and values are within 95% CI limits in Bland-Altman plots). An open source tool that performs quantification of perfusion studies using magnetic resonance imaging has been developed and validated using a clinical software package. It works as an ImageJ plugin and the source code has been published with an open source license. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fabrication of uniform multi-compartment particles using microfludic electrospray technology for cell co-culture studies.

PubMed

Liu, Zhou; Shum, Ho Cheung

2013-01-01

In this work, we demonstrate a robust and reliable approach to fabricate multi-compartment particles for cell co-culture studies. By taking advantage of the laminar flow within our microfluidic nozzle, multiple parallel streams of liquids flow towards the nozzle without significant mixing. Afterwards, the multiple parallel streams merge into a single stream, which is sprayed into air, forming monodisperse droplets under an electric field with a high field strength. The resultant multi-compartment droplets are subsequently cross-linked in a calcium chloride solution to form calcium alginate micro-particles with multiple compartments. Each compartment of the particles can be used for encapsulating different types of cells or biological cell factors. These hydrogel particles with cross-linked alginate chains show similarity in the physical and mechanical environment as the extracellular matrix of biological cells. Thus, the multi-compartment particles provide a promising platform for cell studies and co-culture of different cells. In our study, cells are encapsulated in the multi-compartment particles and the viability of cells is quantified using a fluorescence microscope after the cells are stained for a live/dead assay. The high cell viability after encapsulation indicates the cytocompatibility and feasibility of our technique. Our multi-compartment particles have great potential as a platform for studying cell-cell interactions as well as interactions of cells with extracellular factors.

Fabrication of uniform multi-compartment particles using microfludic electrospray technology for cell co-culture studies

PubMed Central

Liu, Zhou; Shum, Ho Cheung

2013-01-01

In this work, we demonstrate a robust and reliable approach to fabricate multi-compartment particles for cell co-culture studies. By taking advantage of the laminar flow within our microfluidic nozzle, multiple parallel streams of liquids flow towards the nozzle without significant mixing. Afterwards, the multiple parallel streams merge into a single stream, which is sprayed into air, forming monodisperse droplets under an electric field with a high field strength. The resultant multi-compartment droplets are subsequently cross-linked in a calcium chloride solution to form calcium alginate micro-particles with multiple compartments. Each compartment of the particles can be used for encapsulating different types of cells or biological cell factors. These hydrogel particles with cross-linked alginate chains show similarity in the physical and mechanical environment as the extracellular matrix of biological cells. Thus, the multi-compartment particles provide a promising platform for cell studies and co-culture of different cells. In our study, cells are encapsulated in the multi-compartment particles and the viability of cells is quantified using a fluorescence microscope after the cells are stained for a live/dead assay. The high cell viability after encapsulation indicates the cytocompatibility and feasibility of our technique. Our multi-compartment particles have great potential as a platform for studying cell-cell interactions as well as interactions of cells with extracellular factors. PMID:24404050

Operation of Lanzhou all permanent electron cyclotron resonance ion source No. 2 on 320 kV platform with highly charged ions.

PubMed

Lu, W; Li, J Y; Kang, L; Liu, H P; Li, H; Li, J D; Sun, L T; Ma, X W

2014-02-01

The 320 kV platform for multi-discipline research with highly charged ions is a heavy ion beam acceleration instrument developed by Institute of Modern Physics, which is dedicated to basic scientific researches such as plasma, atom, material physics, and astrophysics, etc. The platform has delivered ion beams of 400 species for 36,000 h. The average operation time is around 5000 h/year. With the beams provided by the platform, lots of outstanding progresses were made in various research fields. The ion source of the platform is an all-permanent magnet electron cyclotron resonance ion source, LAPECR2 (Lanzhou All Permanent ECR ion source No. 2). The maximum axial magnetic fields are 1.28 T at injection and 1.07 T at extraction, and the radial magnetic field is up to 1.21 T at the inner wall of the plasma chamber. The ion source is capable to produce low, medium, and high charge state gaseous and metallic ion beams, such as H(+), (40)Ar(8+), (129)Xe(30+), (209)Bi(33+), etc. This paper will present the latest result of LAPECR2 and the routine operation status for the high voltage platform.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peffer, Therese; Blumstein, Carl; Culler, David

The Project uses state-of-the-art computer science to extend the benefits of Building Automation Systems (BAS) typically found in large buildings (>100,000 square foot) to medium-sized commercial buildings (<50,000 sq ft). The BAS developed in this project, termed OpenBAS, uses an open-source and open software architecture platform, user interface, and plug-and-play control devices to facilitate adoption of energy efficiency strategies in the commercial building sector throughout the United States. At the heart of this “turn key” BAS is the platform with three types of controllers—thermostat, lighting controller, and general controller—that are easily “discovered” by the platform in a plug-and-play fashion. Themore » user interface showcases the platform and provides the control system set-up, system status display and means of automatically mapping the control points in the system.« less

PRGdb: a bioinformatics platform for plant resistance gene analysis

PubMed Central

Sanseverino, Walter; Roma, Guglielmo; De Simone, Marco; Faino, Luigi; Melito, Sara; Stupka, Elia; Frusciante, Luigi; Ercolano, Maria Raffaella

2010-01-01

PRGdb is a web accessible open-source (http://www.prgdb.org) database that represents the first bioinformatic resource providing a comprehensive overview of resistance genes (R-genes) in plants. PRGdb holds more than 16 000 known and putative R-genes belonging to 192 plant species challenged by 115 different pathogens and linked with useful biological information. The complete database includes a set of 73 manually curated reference R-genes, 6308 putative R-genes collected from NCBI and 10463 computationally predicted putative R-genes. Thanks to a user-friendly interface, data can be examined using different query tools. A home-made prediction pipeline called Disease Resistance Analysis and Gene Orthology (DRAGO), based on reference R-gene sequence data, was developed to search for plant resistance genes in public datasets such as Unigene and Genbank. New putative R-gene classes containing unknown domain combinations were discovered and characterized. The development of the PRG platform represents an important starting point to conduct various experimental tasks. The inferred cross-link between genomic and phenotypic information allows access to a large body of information to find answers to several biological questions. The database structure also permits easy integration with other data types and opens up prospects for future implementations. PMID:19906694

Multiscale and multi-modality visualization of angiogenesis in a human breast cancer model

PubMed Central

Cebulla, Jana; Kim, Eugene; Rhie, Kevin; Zhang, Jiangyang

2017-01-01

Angiogenesis in breast cancer helps fulfill the metabolic demands of the progressing tumor and plays a critical role in tumor metastasis. Therefore, various imaging modalities have been used to characterize tumor angiogenesis. While micro-CT (μCT) is a powerful tool for analyzing the tumor microvascular architecture at micron-scale resolution, magnetic resonance imaging (MRI) with its sub-millimeter resolution is useful for obtaining in vivo vascular data (e.g. tumor blood volume and vessel size index). However, integration of these microscopic and macroscopic angiogenesis data across spatial resolutions remains challenging. Here we demonstrate the feasibility of ‘multiscale’ angiogenesis imaging in a human breast cancer model, wherein we bridge the resolution gap between ex vivo μCT and in vivo MRI using intermediate resolution ex vivo MR microscopy (μMRI). To achieve this integration, we developed suitable vessel segmentation techniques for the ex vivo imaging data and co-registered the vascular data from all three imaging modalities. We showcase two applications of this multiscale, multi-modality imaging approach: (1) creation of co-registered maps of vascular volume from three independent imaging modalities, and (2) visualization of differences in tumor vasculature between viable and necrotic tumor regions by integrating μCT vascular data with tumor cellularity data obtained using diffusion-weighted MRI. Collectively, these results demonstrate the utility of ‘mesoscopic’ resolution μMRI for integrating macroscopic in vivo MRI data and microscopic μCT data. Although focused on the breast tumor xenograft vasculature, our imaging platform could be extended to include additional data types for a detailed characterization of the tumor microenvironment and computational systems biology applications. PMID:24719185

Performance evaluation of multi-channel wireless mesh networks with embedded systems.

PubMed

Lam, Jun Huy; Lee, Sang-Gon; Tan, Whye Kit

2012-01-01

Many commercial wireless mesh network (WMN) products are available in the marketplace with their own proprietary standards, but interoperability among the different vendors is not possible. Open source communities have their own WMN implementation in accordance with the IEEE 802.11s draft standard, Linux open80211s project and FreeBSD WMN implementation. While some studies have focused on the test bed of WMNs based on the open80211s project, none are based on the FreeBSD. In this paper, we built an embedded system using the FreeBSD WMN implementation that utilizes two channels and evaluated its performance. This implementation allows the legacy system to connect to the WMN independent of the type of platform and distributes the load between the two non-overlapping channels. One channel is used for the backhaul connection and the other one is used to connect to the stations to wireless mesh network. By using the power efficient 802.11 technology, this device can also be used as a gateway for the wireless sensor network (WSN).

Multipurpose floating platform for hyperspectral imaging, sampling and sensing of surface water sources used in irrigation and recreation

USDA-ARS?s Scientific Manuscript database

The objective of this work was to design, construct, and test the self-propelled aquatic platform for imaging, multi-tier water sampling, water quality sensing, and depth profiling to document microbial content and environmental covariates in the interior of irrigation ponds and reservoirs. The plat...

Modal Analysis of Space-rocket Equipment Components

NASA Astrophysics Data System (ADS)

Igolkin, A. A.; Safin, A. I.; Prokofiev, A. B.

2018-01-01

In order to prevent vibration damage an analysis of natural frequencies and mode shapes of elements of rocket and space technology should be developed. This paper discusses technique of modal analysis on the example of the carrier platform. Modal analysis was performed by using mathematical modeling and laser vibrometer. Experimental data was clarified by using Test.Lab software. As a result of modal analysis amplitude-frequency response of carrier platform was obtained and the parameters of the elasticity was clarified.

Enhancing resource coordination for multi-modal evacuation planning.

DOT National Transportation Integrated Search

2013-01-01

This research project seeks to increase knowledge about coordinating effective multi-modal evacuation for disasters. It does so by identifying, evaluating, and assessing : current transportation management approaches for multi-modal evacuation planni...

Open-WiSe: A Solar Powered Wireless Sensor Network Platform

PubMed Central

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396

The Role of Semantics in Open-World, Integrative, Collaborative Science Data Platforms

NASA Astrophysics Data System (ADS)

Fox, Peter; Chen, Yanning; Wang, Han; West, Patrick; Erickson, John; Ma, Marshall

2014-05-01

As collaborative science spreads into more and more Earth and space science fields, both participants and funders are expressing stronger needs for highly functional data and information capabilities. Characteristics include a) easy to use, b) highly integrated, c) leverage investments, d) accommodate rapid technical change, and e) do not incur undue expense or time to build or maintain - these are not a small set of requirements. Based on our accumulated experience over the last ~ decade and several key technical approaches, we adapt, extend, and integrate several open source applications and frameworks to handle major portions of functionality for these platforms. This includes: an object-type repository, collaboration tools, identity management, all within a portal managing diverse content and applications. In this contribution, we present our methods and results of information models, adaptation, integration and evolution of a networked data science architecture based on several open source technologies (Drupal, VIVO, the Comprehensive Knowledge Archive Network; CKAN, and the Global Handle System; GHS). In particular we present the Deep Carbon Observatory - a platform for international science collaboration. We present and discuss key functional and non-functional attributes, and discuss the general applicability of the platform.

OpenDrop: An Integrated Do-It-Yourself Platform for Personal Use of Biochips

PubMed Central

Alistar, Mirela; Gaudenz, Urs

2017-01-01

Biochips, or digital labs-on-chip, are developed with the purpose of being used by laboratory technicians or biologists in laboratories or clinics. In this article, we expand this vision with the goal of enabling everyone, regardless of their expertise, to use biochips for their own personal purposes. We developed OpenDrop, an integrated electromicrofluidic platform that allows users to develop and program their own bio-applications. We address the main challenges that users may encounter: accessibility, bio-protocol design and interaction with microfluidics. OpenDrop consists of a do-it-yourself biochip, an automated software tool with visual interface and a detailed technique for at-home operations of microfluidics. We report on two years of use of OpenDrop, released as an open-source platform. Our platform attracted a highly diverse user base with participants originating from maker communities, academia and industry. Our findings show that 47% of attempts to replicate OpenDrop were successful, the main challenge remaining the assembly of the device. In terms of usability, the users managed to operate their platforms at home and are working on designing their own bio-applications. Our work provides a step towards a future in which everyone will be able to create microfluidic devices for their personal applications, thereby democratizing parts of health care. PMID:28952524

Development of a UAS-based survey module for ecological research

NASA Astrophysics Data System (ADS)

Meng, R.; McMahon, A. M.; Serbin, S.

2016-12-01

The development of small unmanned aircraft system (UAS, < 25 kg) techniques is enabling measurements of terrestrial ecosystems at unprecedented temporal and spatial scales. Given the potential for improved mission safety, high revisit frequency, and reduced operation cost, UAS platforms are of particular interest in the development for scientific research. Our group is developing a UAS-based survey module for ecological research (e.g. scaling and mapping plant functional traits). However, in addition to technical challenges, the complicated regulations required to operate a UAS for research (e.g. Certificates of Waiver or Authorization, COA, for each location) and complying with Federal Aviation Administration (FAA) restrictions, which still actively evolving, can have significant impacts on research and schedules. Here we briefly discuss our lessons-learned related to FAA registration and COA procedures, requirements, and regulations in the US, accompanied by our hand-on experiences (our group currently have two COA granted and three more under review by FAA). We then introduce our design for a modular data collection software framework. This framework is open source (available on GitHub) and cross-platform compatible (written in Python), providing flexibility in development and deployment hardware configurations. In addition our framework uses a central module to coordinate the data acquisition, synchronization with the UAS control system and data storage through a common interface and interchangeable, hardware specific software modules. Utilizing this structure and a common data transfer format, the system can be easily reconfigured to meet the needs of a specific platform or operation, eliminating the need to redevelop acquisition systems for specific instrument/platform configurations. On-site data measurement tests of UAS-based survey module were conducted and data quality from multi-sensors (e.g. a high-resolution digital camera, spectroradiometer, and a thermal infrared camera) was reported. Finally, the results of this prototype study show that the UAS techniques can be used to develop a low-cost alternative for ecological research, but much effort is still needed to carefully deal with flight regulations and integrate off-the-shelf instrumentation, by the practitioner.

Laser-driven x-ray and neutron source development for industrial applications of plasma accelerators

NASA Astrophysics Data System (ADS)

Brenner, C. M.; Mirfayzi, S. R.; Rusby, D. R.; Armstrong, C.; Alejo, A.; Wilson, L. A.; Clarke, R.; Ahmed, H.; Butler, N. M. H.; Haddock, D.; Higginson, A.; McClymont, A.; Murphy, C.; Notley, M.; Oliver, P.; Allott, R.; Hernandez-Gomez, C.; Kar, S.; McKenna, P.; Neely, D.

2016-01-01

Pulsed beams of energetic x-rays and neutrons from intense laser interactions with solid foils are promising for applications where bright, small emission area sources, capable of multi-modal delivery are ideal. Possible end users of laser-driven multi-modal sources are those requiring advanced non-destructive inspection techniques in industry sectors of high value commerce such as aerospace, nuclear and advanced manufacturing. We report on experimental work that demonstrates multi-modal operation of high power laser-solid interactions for neutron and x-ray beam generation. Measurements and Monte Carlo radiation transport simulations show that neutron yield is increased by a factor ~2 when a 1 mm copper foil is placed behind a 2 mm lithium foil, compared to using a 2 cm block of lithium only. We explore x-ray generation with a 10 picosecond drive pulse in order to tailor the spectral content for radiography with medium density alloy metals. The impact of using  >1 ps pulse duration on laser-accelerated electron beam generation and transport is discussed alongside the optimisation of subsequent bremsstrahlung emission in thin, high atomic number target foils. X-ray spectra are deconvolved from spectrometer measurements and simulation data generated using the GEANT4 Monte Carlo code. We also demonstrate the unique capability of laser-driven x-rays in being able to deliver single pulse high spatial resolution projection imaging of thick metallic objects. Active detector radiographic imaging of industrially relevant sample objects with a 10 ps drive pulse is presented for the first time, demonstrating that features of 200 μm size are resolved when projected at high magnification.

Information Systems for Subject Specialists: A Multi-Modal Approach to Indexing and Classification.

ERIC Educational Resources Information Center

Swift, D.F.; And Others

A fundamental problem in the two broad approaches to indexing in the social sciences--providing structure using preferred terms, cross references, and groupings of sets of materials, or compiling a concordance of an author's terms based on occurrence, leaving users free to impose their own structure--is that different indexers and users focus on…

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

tranSMART: An Open Source and Community-Driven Informatics and Data Sharing Platform for Clinical and Translational Research.

PubMed

Athey, Brian D; Braxenthaler, Michael; Haas, Magali; Guo, Yike

2013-01-01

tranSMART is an emerging global open source public private partnership community developing a comprehensive informatics-based analysis and data-sharing cloud platform for clinical and translational research. The tranSMART consortium includes pharmaceutical and other companies, not-for-profits, academic entities, patient advocacy groups, and government stakeholders. The tranSMART value proposition relies on the concept that the global community of users, developers, and stakeholders are the best source of innovation for applications and for useful data. Continued development and use of the tranSMART platform will create a means to enable "pre-competitive" data sharing broadly, saving money and, potentially accelerating research translation to cures. Significant transformative effects of tranSMART includes 1) allowing for all its user community to benefit from experts globally, 2) capturing the best of innovation in analytic tools, 3) a growing 'big data' resource, 4) convergent standards, and 5) new informatics-enabled translational science in the pharma, academic, and not-for-profit sectors.

Blue Guardian: open architecture intelligence, surveillance, and reconnaissance (ISR) demonstrations

NASA Astrophysics Data System (ADS)

Shirey, Russell G.; Borntrager, Luke A.; Soine, Andrew T.; Green, David M.

2017-04-01

The Air Force Research Laboratory (AFRL) - Sensors Directorate has developed the Blue Guardian program to demonstrate advanced sensing technology utilizing open architectures in operationally relevant environments. Blue Guardian has adopted the core concepts and principles of the Air Force Rapid Capabilities Office (AFRCO) Open Mission Systems (OMS) initiative to implement an open Intelligence, Surveillance and Reconnaissance (ISR) platform architecture. Using this new OMS standard provides a business case to reduce cost and program schedules for industry and the Department of Defense (DoD). Blue Guardian is an early adopting program of OMS and provides much needed science and technology improvements, development, testing, and implementation of OMS for ISR purposes. This paper presents results and lessons learned under the Blue Guardian Project Shepherd program which conducted Multi-INT operational demonstrations in the Joint Interagency Task Force - South (JIATF-S) and USSOUTHCOM area of operations in early 2016. Further, on-going research is discussed to enhance Blue Guardian Multi-INT ISR capabilities to support additional mission sets and platforms, including unmanned operations over line of sight (LOS) and beyond line of sight (BLOS) datalinks. An implementation of additional OMS message sets and services to support off-platform sensor command and control using OMS/UCI data structures and dissemination of sensor product data/metadata is explored. Lastly, the Blue Guardian team is working with the AgilePod program to use OMS in a full Government Data Rights Pod to rapidly swap these sensors to different aircraft. The union of the AgilePod (which uses SOSA compliant standards) and OMS technologies under Blue Guardian programs is discussed.

Bioclipse: an open source workbench for chemo- and bioinformatics.

PubMed

Spjuth, Ola; Helmus, Tobias; Willighagen, Egon L; Kuhn, Stefan; Eklund, Martin; Wagener, Johannes; Murray-Rust, Peter; Steinbeck, Christoph; Wikberg, Jarl E S

2007-02-22

There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no successful attempts have been made to integrate chemo- and bioinformatics into a single framework. Bioclipse is an advanced workbench for resources in chemo- and bioinformatics, such as molecules, proteins, sequences, spectra, and scripts. It provides 2D-editing, 3D-visualization, file format conversion, calculation of chemical properties, and much more; all fully integrated into a user-friendly desktop application. Editing supports standard functions such as cut and paste, drag and drop, and undo/redo. Bioclipse is written in Java and based on the Eclipse Rich Client Platform with a state-of-the-art plugin architecture. This gives Bioclipse an advantage over other systems as it can easily be extended with functionality in any desired direction. Bioclipse is a powerful workbench for bio- and chemoinformatics as well as an advanced integration platform. The rich functionality, intuitive user interface, and powerful plugin architecture make Bioclipse the most advanced and user-friendly open source workbench for chemo- and bioinformatics. Bioclipse is released under Eclipse Public License (EPL), an open source license which sets no constraints on external plugin licensing; it is totally open for both open source plugins as well as commercial ones. Bioclipse is freely available at http://www.bioclipse.net.

Quantitative Radiomics System Decoding the Tumor Phenotype | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Our goal is to construct a publicly available computational radiomics system for the objective and automated extraction of quantitative imaging features that we believe will yield biomarkers of greater prognostic value compared with routinely extracted descriptors of tumor size. We will create a generalized, open, portable, and extensible radiomics platform that is widely applicable across cancer types and imaging modalities and describe how we will use lung and head and neck cancers as models to validate our developments.

A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System.

PubMed

Gichoya, Judy W; Kohli, Marc; Ivange, Larry; Schmidt, Teri S; Purkayastha, Saptarshi

2018-05-10

Open-source development can provide a platform for innovation by seeking feedback from community members as well as providing tools and infrastructure to test new standards. Vendors of proprietary systems may delay adoption of new standards until there are sufficient incentives such as legal mandates or financial incentives to encourage/mandate adoption. Moreover, open-source systems in healthcare have been widely adopted in low- and middle-income countries and can be used to bridge gaps that exist in global health radiology. Since 2011, the authors, along with a community of open-source contributors, have worked on developing an open-source radiology information system (RIS) across two communities-OpenMRS and LibreHealth. The main purpose of the RIS is to implement core radiology workflows, on which others can build and test new radiology standards. This work has resulted in three major releases of the system, with current architectural changes driven by changing technology, development of new standards in health and imaging informatics, and changing user needs. At their core, both these communities are focused on building general-purpose EHR systems, but based on user contributions from the fringes, we have been able to create an innovative system that has been used by hospitals and clinics in four different countries. We provide an overview of the history of the LibreHealth RIS, the architecture of the system, overview of standards integration, describe challenges of developing an open-source product, and future directions. Our goal is to attract more participation and involvement to further develop the LibreHealth RIS into an Enterprise Imaging System that can be used in other clinical imaging including pathology and dermatology.

OpenICE medical device interoperability platform overview and requirement analysis.

PubMed

Arney, David; Plourde, Jeffrey; Goldman, Julian M

2018-02-23

We give an overview of OpenICE, an open source implementation of the ASTM standard F2761 for the Integrated Clinical Environment (ICE) that leverages medical device interoperability, together with an analysis of the clinical and non-functional requirements and community process that inspired its design.

Cpu/gpu Computing for AN Implicit Multi-Block Compressible Navier-Stokes Solver on Heterogeneous Platform

NASA Astrophysics Data System (ADS)

Deng, Liang; Bai, Hanli; Wang, Fang; Xu, Qingxin

2016-06-01

CPU/GPU computing allows scientists to tremendously accelerate their numerical codes. In this paper, we port and optimize a double precision alternating direction implicit (ADI) solver for three-dimensional compressible Navier-Stokes equations from our in-house Computational Fluid Dynamics (CFD) software on heterogeneous platform. First, we implement a full GPU version of the ADI solver to remove a lot of redundant data transfers between CPU and GPU, and then design two fine-grain schemes, namely “one-thread-one-point” and “one-thread-one-line”, to maximize the performance. Second, we present a dual-level parallelization scheme using the CPU/GPU collaborative model to exploit the computational resources of both multi-core CPUs and many-core GPUs within the heterogeneous platform. Finally, considering the fact that memory on a single node becomes inadequate when the simulation size grows, we present a tri-level hybrid programming pattern MPI-OpenMP-CUDA that merges fine-grain parallelism using OpenMP and CUDA threads with coarse-grain parallelism using MPI for inter-node communication. We also propose a strategy to overlap the computation with communication using the advanced features of CUDA and MPI programming. We obtain speedups of 6.0 for the ADI solver on one Tesla M2050 GPU in contrast to two Xeon X5670 CPUs. Scalability tests show that our implementation can offer significant performance improvement on heterogeneous platform.

OpenMP-accelerated SWAT simulation using Intel C and FORTRAN compilers: Development and benchmark

NASA Astrophysics Data System (ADS)

Ki, Seo Jin; Sugimura, Tak; Kim, Albert S.

2015-02-01

We developed a practical method to accelerate execution of Soil and Water Assessment Tool (SWAT) using open (free) computational resources. The SWAT source code (rev 622) was recompiled using a non-commercial Intel FORTRAN compiler in Ubuntu 12.04 LTS Linux platform, and newly named iOMP-SWAT in this study. GNU utilities of make, gprof, and diff were used to develop the iOMP-SWAT package, profile memory usage, and check identicalness of parallel and serial simulations. Among 302 SWAT subroutines, the slowest routines were identified using GNU gprof, and later modified using Open Multiple Processing (OpenMP) library in an 8-core shared memory system. In addition, a C wrapping function was used to rapidly set large arrays to zero by cross compiling with the original SWAT FORTRAN package. A universal speedup ratio of 2.3 was achieved using input data sets of a large number of hydrological response units. As we specifically focus on acceleration of a single SWAT run, the use of iOMP-SWAT for parameter calibrations will significantly improve the performance of SWAT optimization.

A Mobile Multi-Agent Information System for Ubiquitous Fetal Monitoring

PubMed Central

Su, Chuan-Jun; Chu, Ta-Wei

2014-01-01

Electronic fetal monitoring (EFM) systems integrate many previously separate clinical activities related to fetal monitoring. Promoting the use of ubiquitous fetal monitoring services with real time status assessments requires a robust information platform equipped with an automatic diagnosis engine. This paper presents the design and development of a mobile multi-agent platform-based open information systems (IMAIS) with an automated diagnosis engine to support intensive and distributed ubiquitous fetal monitoring. The automatic diagnosis engine that we developed is capable of analyzing data in both traditional paper-based and digital formats. Issues related to interoperability, scalability, and openness in heterogeneous e-health environments are addressed through the adoption of a FIPA2000 standard compliant agent development platform—the Java Agent Development Environment (JADE). Integrating the IMAIS with light-weight, portable fetal monitor devices allows for continuous long-term monitoring without interfering with a patient’s everyday activities and without restricting her mobility. The system architecture can be also applied to vast monitoring scenarios such as elder care and vital sign monitoring. PMID:24452256

The SCEC Broadband Platform: A Collaborative Open-Source Software Package for Strong Ground Motion Simulation and Validation

NASA Astrophysics Data System (ADS)

Silva, F.; Maechling, P. J.; Goulet, C. A.; Somerville, P.; Jordan, T. H.

2014-12-01

The Southern California Earthquake Center (SCEC) Broadband Platform is a collaborative software development project involving geoscientists, earthquake engineers, graduate students, and the SCEC Community Modeling Environment. The SCEC Broadband Platform (BBP) is open-source scientific software that can generate broadband (0-100Hz) ground motions for earthquakes, integrating complex scientific modules that implement rupture generation, low and high-frequency seismogram synthesis, non-linear site effects calculation, and visualization into a software system that supports easy on-demand computation of seismograms. The Broadband Platform operates in two primary modes: validation simulations and scenario simulations. In validation mode, the Platform runs earthquake rupture and wave propagation modeling software to calculate seismograms for a well-observed historical earthquake. Then, the BBP calculates a number of goodness of fit measurements that quantify how well the model-based broadband seismograms match the observed seismograms for a certain event. Based on these results, the Platform can be used to tune and validate different numerical modeling techniques. In scenario mode, the Broadband Platform can run simulations for hypothetical (scenario) earthquakes. In this mode, users input an earthquake description, a list of station names and locations, and a 1D velocity model for their region of interest, and the Broadband Platform software then calculates ground motions for the specified stations. Working in close collaboration with scientists and research engineers, the SCEC software development group continues to add new capabilities to the Broadband Platform and to release new versions as open-source scientific software distributions that can be compiled and run on many Linux computer systems. Our latest release includes 5 simulation methods, 7 simulation regions covering California, Japan, and Eastern North America, the ability to compare simulation results against GMPEs, and several new data products, such as map and distance-based goodness of fit plots. As the number and complexity of scenarios simulated using the Broadband Platform increases, we have added batching utilities to substantially improve support for running large-scale simulations on computing clusters.

An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow

NASA Astrophysics Data System (ADS)

Hicks, S.; Damiano, S. G.; Smith, K. M.; Olexy, J.; Horsburgh, J. S.; Mayorga, E.; Aufdenkampe, A. K.

2013-12-01

Implementing a large-scale streaming environmental sensor network has previously been limited by the high cost of the datalogging and data communication infrastructure. The Christina River Basin Critical Zone Observatory (CRB-CZO) is overcoming the obstacles to large near-real-time data collection networks by using Arduino, an open source electronics platform, in combination with XBee ZigBee wireless radio modules. These extremely low-cost and easy-to-use open source electronics are at the heart of the new DIY movement and have provided solutions to countless projects by over half a million users worldwide. However, their use in environmental sensing is in its infancy. At present a primary limitation to widespread deployment of open-source electronics for environmental sensing is the lack of a simple, open-source software stack to manage streaming data from heterogeneous sensor networks. Here we present a functioning prototype software stack that receives sensor data over a self-meshing ZigBee wireless network from over a hundred sensors, stores the data locally and serves it on demand as a CUAHSI Water One Flow (WOF) web service. We highlight a few new, innovative components, including: (1) a versatile open data logger design based the Arduino electronics platform and ZigBee radios; (2) a software library implementing SDI-12 communication protocol between any Arduino platform and SDI12-enabled sensors without the need for additional hardware (https://github.com/StroudCenter/Arduino-SDI-12); and (3) 'midStream', a light-weight set of Python code that receives streaming sensor data, appends it with metadata on the fly by querying a relational database structured on an early version of the Observations Data Model version 2.0 (ODM2), and uses the WOFpy library to serve the data as WaterML via SOAP and REST web services.

Sensing Slow Mobility and Interesting Locations for Lombardy Region (italy): a Case Study Using Pointwise Geolocated Open Data

NASA Astrophysics Data System (ADS)

Brovelli, M. A.; Oxoli, D.; Zurbarán, M. A.

2016-06-01

During the past years Web 2.0 technologies have caused the emergence of platforms where users can share data related to their activities which in some cases are then publicly released with open licenses. Popular categories for this include community platforms where users can upload GPS tracks collected during slow travel activities (e.g. hiking, biking and horse riding) and platforms where users share their geolocated photos. However, due to the high heterogeneity of the information available on the Web, the sole use of these user-generated contents makes it an ambitious challenge to understand slow mobility flows as well as to detect the most visited locations in a region. Exploiting the available data on community sharing websites allows to collect near real-time open data streams and enables rigorous spatial-temporal analysis. This work presents an approach for collecting, unifying and analysing pointwise geolocated open data available from different sources with the aim of identifying the main locations and destinations of slow mobility activities. For this purpose, we collected pointwise open data from the Wikiloc platform, Twitter, Flickr and Foursquare. The analysis was confined to the data uploaded in Lombardy Region (Northern Italy) - corresponding to millions of pointwise data. Collected data was processed through the use of Free and Open Source Software (FOSS) in order to organize them into a suitable database. This allowed to run statistical analyses on data distribution in both time and space by enabling the detection of users' slow mobility preferences as well as places of interest at a regional scale.

IPeak: An open source tool to combine results from multiple MS/MS search engines.

PubMed

Wen, Bo; Du, Chaoqin; Li, Guilin; Ghali, Fawaz; Jones, Andrew R; Käll, Lukas; Xu, Shaohang; Zhou, Ruo; Ren, Zhe; Feng, Qiang; Xu, Xun; Wang, Jun

2015-09-01

Liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post-processing algorithm and multi-search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command-line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml-lib/. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Parallel processing implementation for the coupled transport of photons and electrons using OpenMP

NASA Astrophysics Data System (ADS)

Doerner, Edgardo

2016-05-01

In this work the use of OpenMP to implement the parallel processing of the Monte Carlo (MC) simulation of the coupled transport for photons and electrons is presented. This implementation was carried out using a modified EGSnrc platform which enables the use of the Microsoft Visual Studio 2013 (VS2013) environment, together with the developing tools available in the Intel Parallel Studio XE 2015 (XE2015). The performance study of this new implementation was carried out in a desktop PC with a multi-core CPU, taking as a reference the performance of the original platform. The results were satisfactory, both in terms of scalability as parallelization efficiency.

Nonspinning numerical relativity waveform surrogates: assessing the model

NASA Astrophysics Data System (ADS)

Field, Scott; Blackman, Jonathan; Galley, Chad; Scheel, Mark; Szilagyi, Bela; Tiglio, Manuel

2015-04-01

Recently, multi-modal gravitational waveform surrogate models have been built directly from data numerically generated by the Spectral Einstein Code (SpEC). I will describe ways in which the surrogate model error can be quantified. This task, in turn, requires (i) characterizing differences between waveforms computed by SpEC with those predicted by the surrogate model and (ii) estimating errors associated with the SpEC waveforms from which the surrogate is built. Both pieces can have numerous sources of numerical and systematic errors. We make an attempt to study the most dominant error sources and, ultimately, the surrogate model's fidelity. These investigations yield information about the surrogate model's uncertainty as a function of time (or frequency) and parameter, and could be useful in parameter estimation studies which seek to incorporate model error. Finally, I will conclude by comparing the numerical relativity surrogate model to other inspiral-merger-ringdown models. A companion talk will cover the building of multi-modal surrogate models.

Multi-threaded integration of HTC-Vive and MeVisLab

NASA Astrophysics Data System (ADS)

Gunacker, Simon; Gall, Markus; Schmalstieg, Dieter; Egger, Jan

2018-03-01

This work presents how Virtual Reality (VR) can easily be integrated into medical applications via a plugin for a medical image processing framework called MeVisLab. A multi-threaded plugin has been developed using OpenVR, a VR library that can be used for developing vendor and platform independent VR applications. The plugin is tested using the HTC Vive, a head-mounted display developed by HTC and Valve Corporation.

DeepFruits: A Fruit Detection System Using Deep Neural Networks

PubMed Central

Sa, Inkyu; Ge, Zongyuan; Dayoub, Feras; Upcroft, Ben; Perez, Tristan; McCool, Chris

2016-01-01

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from 0.807 to 0.838 for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit. PMID:27527168

DeepFruits: A Fruit Detection System Using Deep Neural Networks.

PubMed

Sa, Inkyu; Ge, Zongyuan; Dayoub, Feras; Upcroft, Ben; Perez, Tristan; McCool, Chris

2016-08-03

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from 0 . 807 to 0 . 838 for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit.

Data Fusion and Visualization with the OpenEarth Framework (OEF)

NASA Astrophysics Data System (ADS)

Nadeau, D. R.; Baru, C.; Fouch, M. J.; Crosby, C. J.

2010-12-01

Data fusion is an increasingly important problem to solve as we strive to integrate data from multiple sources and build better models of the complex processes operating at the Earth’s surface and its interior. These data are often large, multi-dimensional, and subject to differing conventions for file formats, data structures, coordinate spaces, units of measure, and metadata organization. When visualized, these data require differing, and often conflicting, conventions for visual representations, dimensionality, icons, color schemes, labeling, and interaction. These issues make the visualization of fused Earth science data particularly difficult. The OpenEarth Framework (OEF) is an open-source data fusion and visualization suite of software being developed at the Supercomputer Center at the University of California, San Diego. Funded by the NSF, the project is leveraging virtual globe technology from NASA’s WorldWind to create interactive 3D visualization tools that combine layered data from a variety of sources to create a holistic view of features at, above, and beneath the Earth’s surface. The OEF architecture is cross-platform, multi-threaded, modular, and based upon Java. The OEF’s modular approach yields a collection of compatible mix-and-match components for assembling custom applications. Available modules support file format handling, web service communications, data management, data filtering, user interaction, and 3D visualization. File parsers handle a variety of formal and de facto standard file formats. Each one imports data into a general-purpose data representation that supports multidimensional grids, topography, points, lines, polygons, images, and more. From there these data then may be manipulated, merged, filtered, reprojected, and visualized. Visualization features support conventional and new visualization techniques for looking at topography, tomography, maps, and feature geometry. 3D grid data such as seismic tomography may be sliced by multiple oriented cutting planes and isosurfaced to create 3D skins that trace feature boundaries within the data. Topography may be overlaid with satellite imagery along with data such as gravity and magnetics measurements. Multiple data sets may be visualized simultaneously using overlapping layers and a common 3D+time coordinate space. Data management within the OEF handles and hides the quirks of differing file formats, web protocols, storage structures, coordinate spaces, and metadata representations. Derived data are computed automatically to support interaction and visualization while the original data is left unchanged in its original form. Data is cached for better memory and network efficiency, and all visualization is accelerated by 3D graphics hardware found on today’s computers. The OpenEarth Framework project is currently prototyping the software for use in the visualization, and integration of continental scale geophysical data being produced by EarthScope-related research in the Western US. The OEF is providing researchers with new ways to display and interrogate their data and is anticipated to be a valuable tool for future EarthScope-related research.

Developing and Benchmarking Native Linux Applications on Android

NASA Astrophysics Data System (ADS)

Batyuk, Leonid; Schmidt, Aubrey-Derrick; Schmidt, Hans-Gunther; Camtepe, Ahmet; Albayrak, Sahin

Smartphones get increasingly popular where more and more smartphone platforms emerge. Special attention was gained by the open source platform Android which was presented by the Open Handset Alliance (OHA) hosting members like Google, Motorola, and HTC. Android uses a Linux kernel and a stripped-down userland with a custom Java VM set on top. The resulting system joins the advantages of both environments, while third-parties are intended to develop only Java applications at the moment.

Guide to Sea Ice Information and Sea Ice Data Online - the Sea Ice Knowledge and Data Platform www.meereisportal.de and www.seaiceportal.de

NASA Astrophysics Data System (ADS)

Treffeisen, R. E.; Nicolaus, M.; Bartsch, A.; Fritzsch, B.; Grosfeld, K.; Haas, C.; Hendricks, S.; Heygster, G.; Hiller, W.; Krumpen, T.; Melsheimer, C.; Ricker, R.; Weigelt, M.

2016-12-01

The combination of multi-disciplinary sea ice science and the rising demand of society for up-to-date information and user customized products places emphasis on creating new ways of communication between science and society. The new knowledge platform is a contribution to the cross-linking of scientifically qualified information on climate change, and focuses on the theme: `sea ice' in both Polar Regions. With this platform, the science opens to these changing societal demands. It is the first comprehensive German speaking knowledge platform on sea ice; the platform went online in 2013. The web site delivers popularized information for the general public as well as scientific data meant primarily for the more expert readers and scientists. It also provides various tools allowing for visitor interaction. The demand for the web site indicates a high level of interest from both the general public and experts. It communicates science-based information to improve awareness and understanding of sea ice related research. The principle concept of the new knowledge platform is based on three pillars: (1) sea ice knowledge and background information, (2) data portal with visualizations, and (3) expert knowledge, latest research results and press releases. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archived data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations (e.g., AMSR2, CryoSat-2 and SMOS) of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous ice-tethered platforms (buoys). Additional ship observations, ice station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. We will present the portal, its content and function, but we are also asking for direct user feedback and are open for potential new partners.

Crowd Sourcing for Challenging Technical Problems and Business Model

NASA Technical Reports Server (NTRS)

Davis, Jeffrey R.; Richard, Elizabeth

2011-01-01

Crowd sourcing may be defined as the act of outsourcing tasks that are traditionally performed by an employee or contractor to an undefined, generally large group of people or community (a crowd) in the form of an open call. The open call may be issued by an organization wishing to find a solution to a particular problem or complete a task, or by an open innovation service provider on behalf of that organization. In 2008, the Space Life Sciences Directorate (SLSD), with the support of Wyle Integrated Science and Engineering, established and implemented pilot projects in open innovation (crowd sourcing) to determine if these new internet-based platforms could indeed find solutions to difficult technical challenges. These unsolved technical problems were converted to problem statements, also called "Challenges" or "Technical Needs" by the various open innovation service providers, and were then posted externally to seek solutions. In addition, an open call was issued internally to NASA employees Agency wide (10 Field Centers and NASA HQ) using an open innovation service provider crowd sourcing platform to post NASA challenges from each Center for the others to propose solutions). From 2008 to 2010, the SLSD issued 34 challenges, 14 externally and 20 internally. The 14 external problems or challenges were posted through three different vendors: InnoCentive, Yet2.com and TopCoder. The 20 internal challenges were conducted using the InnoCentive crowd sourcing platform designed for internal use by an organization. This platform was customized for NASA use and promoted as NASA@Work. The results were significant. Of the seven InnoCentive external challenges, two full and five partial awards were made in complex technical areas such as predicting solar flares and long-duration food packaging. Similarly, the TopCoder challenge yielded an optimization algorithm for designing a lunar medical kit. The Yet2.com challenges yielded many new industry and academic contacts in bone imaging, microbial detection and even the use of pharmaceuticals for radiation protection. The internal challenges through NASA@Work drew over 6000 participants across all NASA centers. Challenges conducted by each NASA center elicited ideas and solutions from several other NASA centers and demonstrated rapid and efficient participation from employees at multiple centers to contribute to problem solving. Finally, on January 19, 2011, the SLSD conducted a workshop on open collaboration and innovation strategies and best practices through the newly established NASA Human Health and Performance Center (NHHPC). Initial projects will be described leading to a new business model for SLSD.

Viewpoints: A New Computer Program for Interactive Exploration of Large Multivariate Space Science and Astrophysics Data.

NASA Astrophysics Data System (ADS)

Levit, Creon; Gazis, P.

2006-06-01

The graphics processing units (GPUs) built in to all professional desktop and laptop computers currently on the market are capable of transforming, filtering, and rendering hundreds of millions of points per second. We present a prototype open-source cross-platform (windows, linux, Apple OSX) application which leverages some of the power latent in the GPU to enable smooth interactive exploration and analysis of large high-dimensional data using a variety of classical and recent techniques. The targeted application area is the interactive analysis of complex, multivariate space science and astrophysics data sets, with dimensionalities that may surpass 100 and sample sizes that may exceed 10^6-10^8.

FreeTure: A Free software to capTure meteors for FRIPON

NASA Astrophysics Data System (ADS)

Audureau, Yoan; Marmo, Chiara; Bouley, Sylvain; Kwon, Min-Kyung; Colas, François; Vaubaillon, Jérémie; Birlan, Mirel; Zanda, Brigitte; Vernazza, Pierre; Caminade, Stephane; Gattecceca, Jérôme

2014-02-01

The Fireball Recovery and Interplanetary Observation Network (FRIPON) is a French project started in 2014 which will monitor the sky, using 100 all-sky cameras to detect meteors and to retrieve related meteorites on the ground. There are several detection software all around. Some of them are proprietary. Also, some of them are hardware dependent. We present here the open source software for meteor detection to be installed on the FRIPON network's stations. The software will run on Linux with gigabit Ethernet cameras and we plan to make it cross platform. This paper is focused on the meteor detection method used for the pipeline development and the present capabilities.

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

Plenario: An Open Data Discovery and Exploration Platform for Urban Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Catlett, Charlie; Malik, Tanu; Goldstein, Brett J.

2014-12-01

The past decade has seen the widespread release of open data concerning city services, conditions, and activities by government bodies and public institutions of all sizes. Hundreds of open data portals now host thousands of datasets of many different types. These new data sources represent enormous po- tential for improved understanding of urban dynamics and processes—and, ultimately, for more livable, efficient, and prosperous communities. However, those who seek to realize this potential quickly discover that discovering and applying those data relevant to any particular question can be extraordinarily dif- ficult, due to decentralized storage, heterogeneous formats, and poor documentation. Inmore » this context, we introduce Plenario, a platform designed to automating time-consuming tasks associated with the discovery, exploration, and application of open city data—and, in so doing, reduce barriers to data use for researchers, policymakers, service providers, journalists, and members of the general public. Key innovations include a geospatial data warehouse that allows data from many sources to be registered into a common spatial and temporal frame; simple and intuitive interfaces that permit rapid discovery and exploration of data subsets pertaining to a particular area and time, regardless of type and source; easy export of such data subsets for further analysis; a user-configurable data ingest framework for automated importing and periodic updating of new datasets into the data warehouse; cloud hosting for elastic scaling and rapid creation of new Plenario instances; and an open source implementation to enable community contributions. We describe here the architecture and implementation of the Plenario platform, discuss lessons learned from its use by several communities, and outline plans for future work.« less

Zero shot Event Detection using Multi modal Fusion of Weakly Supervised Concepts (Open Access)

DTIC Science & Technology

2014-09-25

I. Laptev. On space-time interest points. IJCV, 64(2-3):107– 123, 2005. [21] L.-J. Li, H. Su, E . Xing, and L. Fei-Fei. Object bank: A high-level image...invariant keypoints. IJCV, 60:91–110, 2004. [23] P. Natarajan, S. Wu, S. N. P. Vitaladevuni, X. Zhuang, S. Tsakalidis , U. Park, R. Prasad, and P

The multilayer temporal network of public transport in Great Britain

NASA Astrophysics Data System (ADS)

Gallotti, Riccardo; Barthelemy, Marc

2015-01-01

Despite the widespread availability of information concerning public transport coming from different sources, it is extremely hard to have a complete picture, in particular at a national scale. Here, we integrate timetable data obtained from the United Kingdom open-data program together with timetables of domestic flights, and obtain a comprehensive snapshot of the temporal characteristics of the whole UK public transport system for a week in October 2010. In order to focus on multi-modal aspects of the system, we use a coarse graining procedure and define explicitly the coupling between different transport modes such as connections at airports, ferry docks, rail, metro, coach and bus stations. The resulting weighted, directed, temporal and multilayer network is provided in simple, commonly used formats, ensuring easy access and the possibility of a straightforward use of old or specifically developed methods on this new and extensive dataset.

Open source Modeling and optimization tools for Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peles, S.

Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward tomore » complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.« less

Incomplete Intelligence: Is the Information Sharing Environment an Effective Platform?

DTIC Science & Technology

2012-09-01

Initiative NYFD New York Fire Department NYPD New York Police Department OLAP On Line Analytics Processing OSINT Open Source Intelligence...Intelligence ( OSINT ), from public websites, media sources, and other unclassified events and reports. Although some of these sources do not have a direct

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

ProXL (Protein Cross-Linking Database): A Platform for Analysis, Visualization, and Sharing of Protein Cross-Linking Mass Spectrometry Data

PubMed Central

2016-01-01

ProXL is a Web application and accompanying database designed for sharing, visualizing, and analyzing bottom-up protein cross-linking mass spectrometry data with an emphasis on structural analysis and quality control. ProXL is designed to be independent of any particular software pipeline. The import process is simplified by the use of the ProXL XML data format, which shields developers of data importers from the relative complexity of the relational database schema. The database and Web interfaces function equally well for any software pipeline and allow data from disparate pipelines to be merged and contrasted. ProXL includes robust public and private data sharing capabilities, including a project-based interface designed to ensure security and facilitate collaboration among multiple researchers. ProXL provides multiple interactive and highly dynamic data visualizations that facilitate structural-based analysis of the observed cross-links as well as quality control. ProXL is open-source, well-documented, and freely available at https://github.com/yeastrc/proxl-web-app. PMID:27302480

ProXL (Protein Cross-Linking Database): A Platform for Analysis, Visualization, and Sharing of Protein Cross-Linking Mass Spectrometry Data.

PubMed

Riffle, Michael; Jaschob, Daniel; Zelter, Alex; Davis, Trisha N

2016-08-05

ProXL is a Web application and accompanying database designed for sharing, visualizing, and analyzing bottom-up protein cross-linking mass spectrometry data with an emphasis on structural analysis and quality control. ProXL is designed to be independent of any particular software pipeline. The import process is simplified by the use of the ProXL XML data format, which shields developers of data importers from the relative complexity of the relational database schema. The database and Web interfaces function equally well for any software pipeline and allow data from disparate pipelines to be merged and contrasted. ProXL includes robust public and private data sharing capabilities, including a project-based interface designed to ensure security and facilitate collaboration among multiple researchers. ProXL provides multiple interactive and highly dynamic data visualizations that facilitate structural-based analysis of the observed cross-links as well as quality control. ProXL is open-source, well-documented, and freely available at https://github.com/yeastrc/proxl-web-app .

Correlative imaging across microscopy platforms using the fast and accurate relocation of microscopic experimental regions (FARMER) method

NASA Astrophysics Data System (ADS)

Huynh, Toan; Daddysman, Matthew K.; Bao, Ying; Selewa, Alan; Kuznetsov, Andrey; Philipson, Louis H.; Scherer, Norbert F.

2017-05-01

Imaging specific regions of interest (ROIs) of nanomaterials or biological samples with different imaging modalities (e.g., light and electron microscopy) or at subsequent time points (e.g., before and after off-microscope procedures) requires relocating the ROIs. Unfortunately, relocation is typically difficult and very time consuming to achieve. Previously developed techniques involve the fabrication of arrays of features, the procedures for which are complex, and the added features can interfere with imaging the ROIs. We report the Fast and Accurate Relocation of Microscopic Experimental Regions (FARMER) method, which only requires determining the coordinates of 3 (or more) conspicuous reference points (REFs) and employs an algorithm based on geometric operators to relocate ROIs in subsequent imaging sessions. The 3 REFs can be quickly added to various regions of a sample using simple tools (e.g., permanent markers or conductive pens) and do not interfere with the ROIs. The coordinates of the REFs and the ROIs are obtained in the first imaging session (on a particular microscope platform) using an accurate and precise encoded motorized stage. In subsequent imaging sessions, the FARMER algorithm finds the new coordinates of the ROIs (on the same or different platforms), using the coordinates of the manually located REFs and the previously recorded coordinates. FARMER is convenient, fast (3-15 min/session, at least 10-fold faster than manual searches), accurate (4.4 μm average error on a microscope with a 100x objective), and precise (almost all errors are <8 μm), even with deliberate rotating and tilting of the sample well beyond normal repositioning accuracy. We demonstrate this versatility by imaging and re-imaging a diverse set of samples and imaging methods: live mammalian cells at different time points; fixed bacterial cells on two microscopes with different imaging modalities; and nanostructures on optical and electron microscopes. FARMER can be readily adapted to any imaging system with an encoded motorized stage and can facilitate multi-session and multi-platform imaging experiments in biology, materials science, photonics, and nanoscience.

Analysis of Magnetic Resonance Image Signal Fluctuations Acquired During MR-Guided Radiotherapy.

PubMed

Breto, Adrian L; Padgett, Kyle R; Ford, John C; Kwon, Deukwoo; Chang, Channing; Fuss, Martin; Stoyanova, Radka; Mellon, Eric A

2018-03-28

Magnetic resonance-guided radiotherapy (MRgRT) is a new and evolving treatment modality that allows unprecedented visualization of the tumor and surrounding anatomy. MRgRT includes daily 3D magnetic resonance imaging (MRI) for setup and rapidly repeated near real-time MRI scans during treatment for target tracking. One of the more exciting potential benefits of MRgRT is the ability to analyze serial MRIs to monitor treatment response or predict outcomes. A typical radiation treatment (RT) over the span of 10-15 minutes on the MRIdian system (ViewRay, Cleveland, OH) yields thousands of "cine" images, each acquired in 250 ms. This unique data allows for a glimpse in image intensity changes during RT delivery. In this report, we analyze cine images from a single fraction RT of a glioblastoma patient on the ViewRay platform in order to characterize the dynamic signal changes occurring during RT therapy. The individual frames in the cines were saved into DICOM format and read into an MIM image analysis platform (MIM Software, Cleveland, OH) as a time series. The three possible states of the three Cobalt-60 radiation sources-OFF, READY, and ON-were also recorded. An in-house Java plugin for MIM was created in order to perform principal component analysis (PCA) on each of the datasets. The analysis resulted in first PC, related to monotonous signal increase over the course of the treatment fraction. We found several distortion patterns in the data that we postulate result from the perturbation of the magnetic field due to the moving metal parts in the platform while treatment was being administered. The largest variations were detected when all Cobalt-60 sources were OFF. During this phase of the treatment, the gantry and multi-leaf collimators (MLCs) are moving. Conversely, when all Cobalt-60 sources were in the ON position, the image signal fluctuations were minimal, relating to very little mechanical motion. At this phase, the gantry, the MLCs, and sources are fixed in their positions. These findings were confirmed in a study with the daily quality assurance (QA) phantom. While the identified variations were not related to physiological processes, our findings confirm the sensitivity of the developed approach to identify very small fluctuations. Relating these variations to the physical changes that occur during treatment shows the methodical ability of the technique to uncover their underlying sources.

Towards Networked Knowledge: The Learning Registry, an Infrastructure for Sharing Online Learning Resources

ERIC Educational Resources Information Center

Lee, Ashley; Hobson, Joe; Bienkowski, Marie; Midgley, Steve; Currier, Sarah; Campbell, Lorna M.; Novoselova, Tatiana

2012-01-01

In this article, the authors describe an open-source, open-data digital infrastructure for sharing information about open educational resources (OERs) across disparate systems and platforms. The Learning Registry, which began as a project funded by the U.S. Departments of Education and Defense, currently has an active international community…

Safe Operations of Unmanned Systems for Reconnaissance in Complex Environments Army Technology Objective (SOURCE ATO)

DTIC Science & Technology

2011-04-25

must adapt its planning to vehicle size, shape, wheelbase, wheel and axle configuration, the specific obstacle-crossing capabilities of the vehicle...scalability of the ANS is a consequence of making each sensing modality capable of performing reasonable perception tasks while allowing a wider...autonomous system design achieves flexibility by exploiting redundant sensing modalities where possible, and by a decision-making process that

High density electronic circuit and process for making

DOEpatents

Morgan, William P.

1999-01-01

High density circuits with posts that protrude beyond one surface of a substrate to provide easy mounting of devices such as integrated circuits. The posts also provide stress relief to accommodate differential thermal expansion. The process allows high interconnect density with fewer alignment restrictions and less wasted circuit area than previous processes. The resulting substrates can be test platforms for die testing and for multi-chip module substrate testing. The test platform can contain active components and emulate realistic operational conditions, replacing shorts/opens net testing.

Operation of Lanzhou all permanent electron cyclotron resonance ion source No. 2 on 320 kV platform with highly charged ions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, W., E-mail: luwang@impcas.ac.cn; University of Chinese Academy of Sciences, Beijing 100049; Li, J. Y.

2014-02-15

The 320 kV platform for multi-discipline research with highly charged ions is a heavy ion beam acceleration instrument developed by Institute of Modern Physics, which is dedicated to basic scientific researches such as plasma, atom, material physics, and astrophysics, etc. The platform has delivered ion beams of 400 species for 36 000 h. The average operation time is around 5000 h/year. With the beams provided by the platform, lots of outstanding progresses were made in various research fields. The ion source of the platform is an all-permanent magnet electron cyclotron resonance ion source, LAPECR2 (Lanzhou All Permanent ECR ion source No.more » 2). The maximum axial magnetic fields are 1.28 T at injection and 1.07 T at extraction, and the radial magnetic field is up to 1.21 T at the inner wall of the plasma chamber. The ion source is capable to produce low, medium, and high charge state gaseous and metallic ion beams, such as H{sup +}, {sup 40}Ar{sup 8+}, {sup 129}Xe{sup 30+}, {sup 209}Bi{sup 33+}, etc. This paper will present the latest result of LAPECR2 and the routine operation status for the high voltage platform.« less

ALLTEM Multi-Axis Electromagnetic Induction System Demonstration and Validation

DTIC Science & Technology

2011-11-17

fencing that test the capabilities of the platform systems Recently the Open Field area was reconfigured to emulate typical impact area conditions. The...surveyed. • Open field (indirect fire) The indirect fire subarea contains only three munition types that could be typically found at an impact area...direct fire subarea contains only three munition types that could be typically found at an impact area of a direct fire weapons range. These are 25 mm

CosmoQuest: A Cyber-Infrastructure for Crowdsourcing Planetary Surface Mapping and More

NASA Astrophysics Data System (ADS)

Gay, P.; Lehan, C.; Moore, J.; Bracey, G.; Gugliucci, N.

2014-04-01

The design and implementation of programs to crowdsource science presents a unique set of challenges to system architects, programmers, and designers. The CosmoQuest Citizen Science Builder (CSB) is an open source platform designed to take advantage of crowd computing and open source platforms to solve crowdsourcing problems in Planetary Science. CSB combines a clean user interface with a powerful back end to allow the quick design and deployment of citizen science sites that meet the needs of both the random Joe Public, and the detail driven Albert Professional. In this talk, the software will be overviewed, and the results of usability testing and accuracy testing with both citizen and professional scientists will be discussed.

The EDRN knowledge environment: an open source, scalable informatics platform for biological sciences research

NASA Astrophysics Data System (ADS)

Crichton, Daniel; Mahabal, Ashish; Anton, Kristen; Cinquini, Luca; Colbert, Maureen; Djorgovski, S. George; Kincaid, Heather; Kelly, Sean; Liu, David

2017-05-01

We describe here the Early Detection Research Network (EDRN) for Cancer's knowledge environment. It is an open source platform built by NASA's Jet Propulsion Laboratory with contributions from the California Institute of Technology, and Giesel School of Medicine at Dartmouth. It uses tools like Apache OODT, Plone, and Solr, and borrows heavily from JPL's Planetary Data System's ontological infrastructure. It has accumulated data on hundreds of thousands of biospecemens and serves over 1300 registered users across the National Cancer Institute (NCI). The scalable computing infrastructure is built such that we are being able to reach out to other agencies, provide homogeneous access, and provide seamless analytics support and bioinformatics tools through community engagement.

Veterans Health Administration's Disaster Emergency Medical Personnel System (DEMPS) Training Evaluation: Potential Implications for Disaster Health Care Volunteers.

PubMed

Schmitz, Susan; Radcliff, Tiffany A; Chu, Karen; Smith, Robert E; Dobalian, Aram

2018-02-20

The US Veterans Health Administration's Disaster Emergency Medical Personnel System (DEMPS) is a team of employee disaster response volunteers who provide clinical and non-clinical staffing assistance when local systems are overwhelmed. This study evaluated attitudes and recommendations of the DEMPS program to understand the impact of multi-modal training on volunteer perceptions. DEMPS volunteers completed an electronic survey in 2012 (n=2120). Three training modes were evaluated: online, field exercise, and face-to-face. Measures included: "Training Satisfaction," "Attitudes about Training," "Continued Engagement in DEMPS." Data were analyzed using χ2 and logistic regression. Open-ended questions were evaluated in a manner consistent with grounded theory methodology. Most respondents participated in DEMPS training (80%). Volunteers with multi-modal training who completed all 3 modes (14%) were significantly more likely to have positive attitudes about training, plan to continue as volunteers, and would recommend DEMPS to others (P-value<0.001). Some respondents requested additional interactive activities and suggested increased availability of training may improve volunteer engagement. A blended learning environment using multi-modal training methods, could enhance satisfaction and attitudes and possibly encourage continued engagement in DEMPS or similar programs. DEMPS training program modifications in 2015 expanded this blended learning approach through new interactive online learning opportunities. (Disaster Med Public Health Preparedness. 2018; page 1 of 8).

Efficient Comparison between Windows and Linux Platform Applicable in a Virtual Architectural Walkthrough Application

NASA Astrophysics Data System (ADS)

Thubaasini, P.; Rusnida, R.; Rohani, S. M.

This paper describes Linux, an open source platform used to develop and run a virtual architectural walkthrough application. It proposes some qualitative reflections and observations on the nature of Linux in the concept of Virtual Reality (VR) and on the most popular and important claims associated with the open source approach. The ultimate goal of this paper is to measure and evaluate the performance of Linux used to build the virtual architectural walkthrough and develop a proof of concept based on the result obtain through this project. Besides that, this study reveals the benefits of using Linux in the field of virtual reality and reflects a basic comparison and evaluation between Windows and Linux base operating system. Windows platform is use as a baseline to evaluate the performance of Linux. The performance of Linux is measured based on three main criteria which is frame rate, image quality and also mouse motion.

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

Increasing Flight Software Reuse with OpenSatKit

NASA Technical Reports Server (NTRS)

McComas, David C.

2018-01-01

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospace's command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for users to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS "App Store".. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

A System for Multi-Domain Contextualization of Personal Health Data.

PubMed

Pustišek, Matevž

2017-01-01

Current telehealth systems are used to improve the treatment of chronic diseases by collecting medical data at the patient and transferring them to a remote medical institution. Research shows that such medical practice can be substantially improved if the measured parameters are greater in number and of more diverse nature. Emerging consumer solutions for monitoring personal health and wellness, as well as various resources from domains like internet, telecommunications and smart living, can be used as possible sources for exploration of an individual's wider health context. It was our aim to design an internet of things solutions, which would combine these sources of information into context information, complementary to health data. An internet of things platform was designed and implemented and integration with an established e-health system was provided to enrich telehealth data with context information by aggregating and processing cross-domain inputs from various sources. The approach was validated on a use case scenario. The concept was tried in a scenario related to prevention and management of heart disease. The system's advanced graphic correlation features are expected to help physicians and patients identify true roots of health problems. Medical researchers are also expected to benefit from a deeper insight into complex cross-domain parameter dependencies that determine an individual's health.

Intra-operative label-free multimodal multiphoton imaging of breast cancer margins and microenvironment (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sun, Yi; You, Sixian; Tu, Haohua; Spillman, Darold R.; Marjanovic, Marina; Chaney, Eric J.; Liu, George Z.; Ray, Partha S.; Higham, Anna; Boppart, Stephen A.

2017-02-01

Label-free multi-photon imaging has been a powerful tool for studying tissue microstructures and biochemical distributions, particularly for investigating tumors and their microenvironments. However, it remains challenging for traditional bench-top multi-photon microscope systems to conduct ex vivo tumor tissue imaging in the operating room due to their bulky setups and laser sources. In this study, we designed, built, and clinically demonstrated a portable multi-modal nonlinear label-free microscope system that combined four modalities, including two- and three- photon fluorescence for studying the distributions of FAD and NADH, and second and third harmonic generation, respectively, for collagen fiber structures and the distribution of micro-vesicles found in tumors and the microenvironment. Optical realignments and switching between modalities were motorized for more rapid and efficient imaging and for a light-tight enclosure, reducing ambient light noise to only 5% within the brightly lit operating room. Using up to 20 mW of laser power after a 20x objective, this system can acquire multi-modal sets of images over 600 μm × 600 μm at an acquisition rate of 60 seconds using galvo-mirror scanning. This portable microscope system was demonstrated in the operating room for imaging fresh, resected, unstained breast tissue specimens, and for assessing tumor margins and the tumor microenvironment. This real-time label-free nonlinear imaging system has the potential to uniquely characterize breast cancer margins and the microenvironment of tumors to intraoperatively identify structural, functional, and molecular changes that could indicate the aggressiveness of the tumor.

MSiReader v1.0: Evolving Open-Source Mass Spectrometry Imaging Software for Targeted and Untargeted Analyses.

PubMed

Bokhart, Mark T; Nazari, Milad; Garrard, Kenneth P; Muddiman, David C

2018-01-01

A major update to the mass spectrometry imaging (MSI) software MSiReader is presented, offering a multitude of newly added features critical to MSI analyses. MSiReader is a free, open-source, and vendor-neutral software written in the MATLAB platform and is capable of analyzing most common MSI data formats. A standalone version of the software, which does not require a MATLAB license, is also distributed. The newly incorporated data analysis features expand the utility of MSiReader beyond simple visualization of molecular distributions. The MSiQuantification tool allows researchers to calculate absolute concentrations from quantification MSI experiments exclusively through MSiReader software, significantly reducing data analysis time. An image overlay feature allows the incorporation of complementary imaging modalities to be displayed with the MSI data. A polarity filter has also been incorporated into the data loading step, allowing the facile analysis of polarity switching experiments without the need for data parsing prior to loading the data file into MSiReader. A quality assurance feature to generate a mass measurement accuracy (MMA) heatmap for an analyte of interest has also been added to allow for the investigation of MMA across the imaging experiment. Most importantly, as new features have been added performance has not degraded, in fact it has been dramatically improved. These new tools and the improvements to the performance in MSiReader v1.0 enable the MSI community to evaluate their data in greater depth and in less time. Graphical Abstract ᅟ.

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.

PubMed

Taylor, Jason R; Williams, Nitin; Cusack, Rhodri; Auer, Tibor; Shafto, Meredith A; Dixon, Marie; Tyler, Lorraine K; Cam-Can; Henson, Richard N

2017-01-01

This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N=700), cross-sectional adult lifespan (18-87years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

OpenSHS: Open Smart Home Simulator.

PubMed

Alshammari, Nasser; Alshammari, Talal; Sedky, Mohamed; Champion, Justin; Bauer, Carolin

2017-05-02

This paper develops a new hybrid, open-source, cross-platform 3D smart home simulator, OpenSHS, for dataset generation. OpenSHS offers an opportunity for researchers in the field of the Internet of Things (IoT) and machine learning to test and evaluate their models. Following a hybrid approach, OpenSHS combines advantages from both interactive and model-based approaches. This approach reduces the time and efforts required to generate simulated smart home datasets. We have designed a replication algorithm for extending and expanding a dataset. A small sample dataset produced, by OpenSHS, can be extended without affecting the logical order of the events. The replication provides a solution for generating large representative smart home datasets. We have built an extensible library of smart devices that facilitates the simulation of current and future smart home environments. Our tool divides the dataset generation process into three distinct phases: first design: the researcher designs the initial virtual environment by building the home, importing smart devices and creating contexts; second, simulation: the participant simulates his/her context-specific events; and third, aggregation: the researcher applies the replication algorithm to generate the final dataset. We conducted a study to assess the ease of use of our tool on the System Usability Scale (SUS).

OpenSHS: Open Smart Home Simulator

PubMed Central

Alshammari, Nasser; Alshammari, Talal; Sedky, Mohamed; Champion, Justin; Bauer, Carolin

2017-01-01

This paper develops a new hybrid, open-source, cross-platform 3D smart home simulator, OpenSHS, for dataset generation. OpenSHS offers an opportunity for researchers in the field of the Internet of Things (IoT) and machine learning to test and evaluate their models. Following a hybrid approach, OpenSHS combines advantages from both interactive and model-based approaches. This approach reduces the time and efforts required to generate simulated smart home datasets. We have designed a replication algorithm for extending and expanding a dataset. A small sample dataset produced, by OpenSHS, can be extended without affecting the logical order of the events. The replication provides a solution for generating large representative smart home datasets. We have built an extensible library of smart devices that facilitates the simulation of current and future smart home environments. Our tool divides the dataset generation process into three distinct phases: first design: the researcher designs the initial virtual environment by building the home, importing smart devices and creating contexts; second, simulation: the participant simulates his/her context-specific events; and third, aggregation: the researcher applies the replication algorithm to generate the final dataset. We conducted a study to assess the ease of use of our tool on the System Usability Scale (SUS). PMID:28468330

The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes.

PubMed

Treangen, Todd J; Ondov, Brian D; Koren, Sergey; Phillippy, Adam M

2014-01-01

Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

Study on the E-commerce platform based on the agent

NASA Astrophysics Data System (ADS)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

T-Check in Technologies for Interoperability: Web Services and Security--Single Sign-On

DTIC Science & Technology

2007-12-01

following tools: • Apache Tomcat 6.0—a Java Servlet container to host the Web services and a simple Web client application [Apache 2007a] • Apache Axis...Eclipse. Eclipse – an open development platform. http://www.eclipse.org/ (2007) [Hunter 2001] Hunter, Jason. Java Servlet Programming, 2nd Edition...Citation SAML 1.1 Java Toolkit SAML Ping Identity’s SAML-1.1 implementation [SourceID 2006] OpenSAML SAML An open source implementation of SAML 1.1

Multi-Modality Phantom Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huber, Jennifer S.; Peng, Qiyu; Moses, William W.

2009-03-20

Multi-modality imaging has an increasing role in the diagnosis and treatment of a large number of diseases, particularly if both functional and anatomical information are acquired and accurately co-registered. Hence, there is a resulting need for multi modality phantoms in order to validate image co-registration and calibrate the imaging systems. We present our PET-ultrasound phantom development, including PET and ultrasound images of a simple prostate phantom. We use agar and gelatin mixed with a radioactive solution. We also present our development of custom multi-modality phantoms that are compatible with PET, transrectal ultrasound (TRUS), MRI and CT imaging. We describe bothmore » our selection of tissue mimicking materials and phantom construction procedures. These custom PET-TRUS-CT-MRI prostate phantoms use agargelatin radioactive mixtures with additional contrast agents and preservatives. We show multi-modality images of these custom prostate phantoms, as well as discuss phantom construction alternatives. Although we are currently focused on prostate imaging, this phantom development is applicable to many multi-modality imaging applications.« less

The successes and challenges of open-source biopharmaceutical innovation.

PubMed

Allarakhia, Minna

2014-05-01

Increasingly, open-source-based alliances seek to provide broad access to data, research-based tools, preclinical samples and downstream compounds. The challenge is how to create value from open-source biopharmaceutical innovation. This value creation may occur via transparency and usage of data across the biopharmaceutical value chain as stakeholders move dynamically between open source and open innovation. In this article, several examples are used to trace the evolution of biopharmaceutical open-source initiatives. The article specifically discusses the technological challenges associated with the integration and standardization of big data; the human capacity development challenges associated with skill development around big data usage; and the data-material access challenge associated with data and material access and usage rights, particularly as the boundary between open source and open innovation becomes more fluid. It is the author's opinion that the assessment of when and how value creation will occur, through open-source biopharmaceutical innovation, is paramount. The key is to determine the metrics of value creation and the necessary technological, educational and legal frameworks to support the downstream outcomes of now big data-based open-source initiatives. The continued focus on the early-stage value creation is not advisable. Instead, it would be more advisable to adopt an approach where stakeholders transform open-source initiatives into open-source discovery, crowdsourcing and open product development partnerships on the same platform.

Supervised Semi-Automated Data Analysis Software for Gas Chromatography / Differential Mobility Spectrometry (GC/DMS) Metabolomics Applications.

PubMed

Peirano, Daniel J; Pasamontes, Alberto; Davis, Cristina E

2016-09-01

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

PubMed

Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie

2016-01-01

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

The dynamic flexural response of propeller blades. M.S. Thesis

NASA Technical Reports Server (NTRS)

Djordjevic, S. Z.

1982-01-01

The determination of the torsional constants of three blade models having NACA four-digit symmetrical airfoil cross sections is presented. Values were obtained for these models analytically and experimentally. Results were also obtained for three other models having rectangular, elliptical, and parabolic cross sections. Complete modal analyses were performed for five blade models. The identification of modal parameters was done for cases when the blades were modeled as either undamped or damped multi-degree-of-freedom systems. For the experimental phase of this study, the modal testing was performed using a Dual Channel FFT analyzer and an impact hammer (which produced an impulsive excitation). The natural frequency and damping of each mode in the frequency range up to 2 kHz were measured. A small computer code was developed to calculate the dynamic response of the blade models for comparison with the experimental results. A comparison of the undamped and damped cases was made for all five blade models at the instant of maximum excitation force. The program was capable of handling models where the excitation forces were distributed arbitrarily along the length of the blade.

Implementation and performance test of cloud platform based on Hadoop

NASA Astrophysics Data System (ADS)

Xu, Jingxian; Guo, Jianhong; Ren, Chunlan

2018-01-01

Hadoop, as an open source project for the Apache foundation, is a distributed computing framework that deals with large amounts of data and has been widely used in the Internet industry. Therefore, it is meaningful to study the implementation of Hadoop platform and the performance of test platform. The purpose of this subject is to study the method of building Hadoop platform and to study the performance of test platform. This paper presents a method to implement Hadoop platform and a test platform performance method. Experimental results show that the proposed test performance method is effective and it can detect the performance of Hadoop platform.

Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry.

PubMed

Röst, Hannes L; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

2015-01-01

In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size. Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data. Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS.

Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry

PubMed Central

Röst, Hannes L.; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

2015-01-01

Motivation In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size. Results Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data. Availability Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS. PMID:25927999

Generic HRTFs May be Good Enough in Virtual Reality. Improving Source Localization through Cross-Modal Plasticity.

PubMed

Berger, Christopher C; Gonzalez-Franco, Mar; Tajadura-Jiménez, Ana; Florencio, Dinei; Zhang, Zhengyou

2018-01-01

Auditory spatial localization in humans is performed using a combination of interaural time differences, interaural level differences, as well as spectral cues provided by the geometry of the ear. To render spatialized sounds within a virtual reality (VR) headset, either individualized or generic Head Related Transfer Functions (HRTFs) are usually employed. The former require arduous calibrations, but enable accurate auditory source localization, which may lead to a heightened sense of presence within VR. The latter obviate the need for individualized calibrations, but result in less accurate auditory source localization. Previous research on auditory source localization in the real world suggests that our representation of acoustic space is highly plastic. In light of these findings, we investigated whether auditory source localization could be improved for users of generic HRTFs via cross-modal learning. The results show that pairing a dynamic auditory stimulus, with a spatio-temporally aligned visual counterpart, enabled users of generic HRTFs to improve subsequent auditory source localization. Exposure to the auditory stimulus alone or to asynchronous audiovisual stimuli did not improve auditory source localization. These findings have important implications for human perception as well as the development of VR systems as they indicate that generic HRTFs may be enough to enable good auditory source localization in VR.

A microfluidic multi-injector for gradient generation.

PubMed

Chung, Bong Geun; Lin, Francis; Jeon, Noo Li

2006-06-01

This paper describes a microfluidic multi-injector (MMI) that can generate temporal and spatial concentration gradients of soluble molecules. Compared to conventional glass micropipette-based methods that generate a single gradient, the MMI exploits microfluidic integration and actuation of multiple pulsatile injectors to generate arbitrary overlapping gradients that have not previously been possible. The MMI device is fabricated in poly(dimethylsiloxane) (PDMS) using multi-layer soft lithography and consists of fluidic channels and control channels with pneumatically actuated on-chip barrier valves. Repetitive actuation of on-chip valves control pulsatile release of solution that establishes microscopic chemical gradients around the orifice. The volume of solution released per actuation cycle ranged from 30 picolitres to several hundred picolitres and increased linearly with the duration of valve opening. The shape of the measured gradient profile agreed closely with the simulated diffusion profile from a point source. Steady state gradient profiles could be attained within 10 minutes, or less with an optimized pulse sequence. Overlapping gradients from 2 injectors were generated and characterized to highlight the advantages of MMI over conventional micropipette assays. The MMI platform should be useful for a wide range of basic and applied studies on chemotaxis and axon guidance.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.