Open source tools for the information theoretic analysis of neural data.

PubMed

Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano

2010-01-01

The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research.

PubMed

Heasly, Benjamin S; Cottaris, Nicolas P; Lichtman, Daniel P; Xiao, Bei; Brainard, David H

2014-02-07

RenderToolbox3 provides MATLAB utilities and prescribes a workflow that should be useful to researchers who want to employ graphics in the study of vision and perhaps in other endeavors as well. In particular, RenderToolbox3 facilitates rendering scene families in which various scene attributes and renderer behaviors are manipulated parametrically, enables spectral specification of object reflectance and illuminant spectra, enables the use of physically based material specifications, helps validate renderer output, and converts renderer output to physical units of radiance. This paper describes the design and functionality of the toolbox and discusses several examples that demonstrate its use. We have designed RenderToolbox3 to be portable across computer hardware and operating systems and to be free and open source (except for MATLAB itself). RenderToolbox3 is available at https://github.com/DavidBrainard/RenderToolbox3.

TopoToolbox: using sensor topography to calculate psychologically meaningful measures from event-related EEG/MEG.

PubMed

Tian, Xing; Poeppel, David; Huber, David E

2011-01-01

The open-source toolbox "TopoToolbox" is a suite of functions that use sensor topography to calculate psychologically meaningful measures (similarity, magnitude, and timing) from multisensor event-related EEG and MEG data. Using a GUI and data visualization, TopoToolbox can be used to calculate and test the topographic similarity between different conditions (Tian and Huber, 2008). This topographic similarity indicates whether different conditions involve a different distribution of underlying neural sources. Furthermore, this similarity calculation can be applied at different time points to discover when a response pattern emerges (Tian and Poeppel, 2010). Because the topographic patterns are obtained separately for each individual, these patterns are used to produce reliable measures of response magnitude that can be compared across individuals using conventional statistics (Davelaar et al. Submitted and Huber et al., 2008). TopoToolbox can be freely downloaded. It runs under MATLAB (The MathWorks, Inc.) and supports user-defined data structure as well as standard EEG/MEG data import using EEGLAB (Delorme and Makeig, 2004).

FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

PubMed Central

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages. PMID:21253357

GridPV Toolbox

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

Broderick, Robert; Quiroz, Jimmy; Grijalva, Santiago

2014-07-15

Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.

biomechZoo: An open-source toolbox for the processing, analysis, and visualization of biomechanical movement data.

PubMed

Dixon, Philippe C; Loh, Jonathan J; Michaud-Paquette, Yannick; Pearsall, David J

2017-03-01

It is common for biomechanics data sets to contain numerous dependent variables recorded over time, for many subjects, groups, and/or conditions. These data often require standard sorting, processing, and analysis operations to be performed in order to answer research questions. Visualization of these data is also crucial. This manuscript presents biomechZoo, an open-source toolbox that provides tools and graphical user interfaces to help users achieve these goals. The aims of this manuscript are to (1) introduce the main features of the toolbox, including a virtual three-dimensional environment to animate motion data (Director), a data plotting suite (Ensembler), and functions for the computation of three-dimensional lower-limb joint angles, moments, and power and (2) compare these computations to those of an existing validated system. To these ends, the steps required to process and analyze a sample data set via the toolbox are outlined. The data set comprises three-dimensional marker, ground reaction force (GRF), joint kinematic, and joint kinetic data of subjects performing straight walking and 90° turning manoeuvres. Joint kinematics and kinetics processed within the toolbox were found to be similar to outputs from a commercial system. The biomechZoo toolbox represents the work of several years and multiple contributors to provide a flexible platform to examine time-series data sets typical in the movement sciences. The toolbox has previously been used to process and analyse walking, running, and ice hockey data sets, and can integrate existing routines, such as the KineMat toolbox, for additional analyses. The toolbox can help researchers and clinicians new to programming or biomechanics to process and analyze their data through a customizable workflow, while advanced users are encouraged to contribute additional functionality to the project. Students may benefit from using biomechZoo as a learning and research tool. It is hoped that the toolbox can play a role in advancing research in the movement sciences. The biomechZoo m-files, sample data, and help repositories are available online (http://www.biomechzoo.com) under the Apache 2.0 License. The toolbox is supported for Matlab (r2014b or newer, The Mathworks Inc., Natick, USA) for Windows (Microsoft Corp., Redmond, USA) and Mac OS (Apple Inc., Cupertino, USA). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

NeoAnalysis: a Python-based toolbox for quick electrophysiological data processing and analysis.

PubMed

Zhang, Bo; Dai, Ji; Zhang, Tao

2017-11-13

In a typical electrophysiological experiment, especially one that includes studying animal behavior, the data collected normally contain spikes, local field potentials, behavioral responses and other associated data. In order to obtain informative results, the data must be analyzed simultaneously with the experimental settings. However, most open-source toolboxes currently available for data analysis were developed to handle only a portion of the data and did not take into account the sorting of experimental conditions. Additionally, these toolboxes require that the input data be in a specific format, which can be inconvenient to users. Therefore, the development of a highly integrated toolbox that can process multiple types of data regardless of input data format and perform basic analysis for general electrophysiological experiments is incredibly useful. Here, we report the development of a Python based open-source toolbox, referred to as NeoAnalysis, to be used for quick electrophysiological data processing and analysis. The toolbox can import data from different data acquisition systems regardless of their formats and automatically combine different types of data into a single file with a standardized format. In cases where additional spike sorting is needed, NeoAnalysis provides a module to perform efficient offline sorting with a user-friendly interface. Then, NeoAnalysis can perform regular analog signal processing, spike train, and local field potentials analysis, behavioral response (e.g. saccade) detection and extraction, with several options available for data plotting and statistics. Particularly, it can automatically generate sorted results without requiring users to manually sort data beforehand. In addition, NeoAnalysis can organize all of the relevant data into an informative table on a trial-by-trial basis for data visualization. Finally, NeoAnalysis supports analysis at the population level. With the multitude of general-purpose functions provided by NeoAnalysis, users can easily obtain publication-quality figures without writing complex codes. NeoAnalysis is a powerful and valuable toolbox for users doing electrophysiological experiments.

Putting tools in the toolbox: Development of a free, open-source toolbox for quantitative image analysis of porous media.

NASA Astrophysics Data System (ADS)

Iltis, G.; Caswell, T. A.; Dill, E.; Wilkins, S.; Lee, W. K.

2014-12-01

X-ray tomographic imaging of porous media has proven to be a valuable tool for investigating and characterizing the physical structure and state of both natural and synthetic porous materials, including glass bead packs, ceramics, soil and rock. Given that most synchrotron facilities have user programs which grant academic researchers access to facilities and x-ray imaging equipment free of charge, a key limitation or hindrance for small research groups interested in conducting x-ray imaging experiments is the financial cost associated with post-experiment data analysis. While the cost of high performance computing hardware continues to decrease, expenses associated with licensing commercial software packages for quantitative image analysis continue to increase, with current prices being as high as $24,000 USD, for a single user license. As construction of the Nation's newest synchrotron accelerator nears completion, a significant effort is being made here at the National Synchrotron Light Source II (NSLS-II), Brookhaven National Laboratory (BNL), to provide an open-source, experiment-to-publication toolbox that reduces the financial and technical 'activation energy' required for performing sophisticated quantitative analysis of multidimensional porous media data sets, collected using cutting-edge x-ray imaging techniques. Implementation focuses on leveraging existing open-source projects and developing additional tools for quantitative analysis. We will present an overview of the software suite that is in development here at BNL including major design decisions, a demonstration of several test cases illustrating currently available quantitative tools for analysis and characterization of multidimensional porous media image data sets and plans for their future development.

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.

TopoToolbox: Using Sensor Topography to Calculate Psychologically Meaningful Measures from Event-Related EEG/MEG

PubMed Central

Tian, Xing; Poeppel, David; Huber, David E.

2011-01-01

The open-source toolbox “TopoToolbox” is a suite of functions that use sensor topography to calculate psychologically meaningful measures (similarity, magnitude, and timing) from multisensor event-related EEG and MEG data. Using a GUI and data visualization, TopoToolbox can be used to calculate and test the topographic similarity between different conditions (Tian and Huber, 2008). This topographic similarity indicates whether different conditions involve a different distribution of underlying neural sources. Furthermore, this similarity calculation can be applied at different time points to discover when a response pattern emerges (Tian and Poeppel, 2010). Because the topographic patterns are obtained separately for each individual, these patterns are used to produce reliable measures of response magnitude that can be compared across individuals using conventional statistics (Davelaar et al. Submitted and Huber et al., 2008). TopoToolbox can be freely downloaded. It runs under MATLAB (The MathWorks, Inc.) and supports user-defined data structure as well as standard EEG/MEG data import using EEGLAB (Delorme and Makeig, 2004). PMID:21577268

nSTAT: Open-Source Neural Spike Train Analysis Toolbox for Matlab

PubMed Central

Cajigas, I.; Malik, W.Q.; Brown, E.N.

2012-01-01

Over the last decade there has been a tremendous advance in the analytical tools available to neuroscientists to understand and model neural function. In particular, the point process - Generalized Linear Model (PPGLM) framework has been applied successfully to problems ranging from neuro-endocrine physiology to neural decoding. However, the lack of freely distributed software implementations of published PP-GLM algorithms together with problem-specific modifications required for their use, limit wide application of these techniques. In an effort to make existing PP-GLM methods more accessible to the neuroscience community, we have developed nSTAT – an open source neural spike train analysis toolbox for Matlab®. By adopting an Object-Oriented Programming (OOP) approach, nSTAT allows users to easily manipulate data by performing operations on objects that have an intuitive connection to the experiment (spike trains, covariates, etc.), rather than by dealing with data in vector/matrix form. The algorithms implemented within nSTAT address a number of common problems including computation of peri-stimulus time histograms, quantification of the temporal response properties of neurons, and characterization of neural plasticity within and across trials. nSTAT provides a starting point for exploratory data analysis, allows for simple and systematic building and testing of point process models, and for decoding of stimulus variables based on point process models of neural function. By providing an open-source toolbox, we hope to establish a platform that can be easily used, modified, and extended by the scientific community to address limitations of current techniques and to extend available techniques to more complex problems. PMID:22981419

Obtaining of Analytical Relations for Hydraulic Parameters of Channels With Two Phase Flow Using Open CFD Toolbox

NASA Astrophysics Data System (ADS)

Varseev, E.

2017-11-01

The present work is dedicated to verification of numerical model in standard solver of open-source CFD code OpenFOAM for two-phase flow simulation and to determination of so-called “baseline” model parameters. Investigation of heterogeneous coolant flow parameters, which leads to abnormal friction increase of channel in two-phase adiabatic “water-gas” flows with low void fractions, presented.

Open-source tools for data mining.

PubMed

Zupan, Blaz; Demsar, Janez

2008-03-01

With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. In this article, we discuss the evolution of open-source toolboxes that data mining researchers and enthusiasts have developed over the span of a few decades and review several currently available open-source data mining suites. The approaches we review are diverse in data mining methods and user interfaces and also demonstrate that the field and its tools are ready to be fully exploited in biomedical research.

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.

Microbe-ID: An open source toolbox for microbial genotyping and species identification

USDA-ARS?s Scientific Manuscript database

Development of tools to identify species, genotypes, or novel strains of invasive organisms is critical for monitoring emergence and implementing rapid response measures. Molecular markers, although critical to identifying species or genotypes, require bioinformatic tools for analysis. However, user...

Direct simulation Monte Carlo method for gas flows in micro-channels with bends with added curvature

NASA Astrophysics Data System (ADS)

Tisovský, Tomáš; Vít, Tomáš

Gas flows in micro-channels are simulated using an open source Direct Simulation Monte Carlo (DSMC) code dsmcFOAM for general application to rarefied gas flow written within the framework of the open source C++ toolbox called OpenFOAM. Aim of this paper is to investigate the flow in micro-channel with bend with added curvature. Results are compared with flows in channel without added curvature and equivalent straight channel. Effects of micro-channel bend was already thoroughly investigated by White et al. Geometry proposed by White is also used here for refference.

Grid Integrated Distributed PV (GridPV) Version 2.

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

Reno, Matthew J.; Coogan, Kyle

2014-12-01

This manual provides the documentation of the MATLAB toolbox of functions for using OpenDSS to simulate the impact of solar energy on the distribution system. The majority of the functio ns are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in th e OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included tomore » show potential uses of the toolbox functions. Each function i n the toolbox is documented with the function use syntax, full description, function input list, function output list, example use, and example output.« less

PYCHEM: a multivariate analysis package for python.

PubMed

Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston

2006-10-15

We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem

Velocity Mapping Toolbox (VMT): a processing and visualization suite for moving-vessel ADCP measurements

USGS Publications Warehouse

Parsons, D.R.; Jackson, P.R.; Czuba, J.A.; Engel, F.L.; Rhoads, B.L.; Oberg, K.A.; Best, J.L.; Mueller, D.S.; Johnson, K.K.; Riley, J.D.

2013-01-01

The use of acoustic Doppler current profilers (ADCP) for discharge measurements and three-dimensional flow mapping has increased rapidly in recent years and has been primarily driven by advances in acoustic technology and signal processing. Recent research has developed a variety of methods for processing data obtained from a range of ADCP deployments and this paper builds on this progress by describing new software for processing and visualizing ADCP data collected along transects in rivers or other bodies of water. The new utility, the Velocity Mapping Toolbox (VMT), allows rapid processing (vector rotation, projection, averaging and smoothing), visualization (planform and cross-section vector and contouring), and analysis of a range of ADCP-derived datasets. The paper documents the data processing routines in the toolbox and presents a set of diverse examples that demonstrate its capabilities. The toolbox is applicable to the analysis of ADCP data collected in a wide range of aquatic environments and is made available as open-source code along with this publication.

An open-source Java-based Toolbox for environmental model evaluation: The MOUSE Software Application

USDA-ARS?s Scientific Manuscript database

A consequence of environmental model complexity is that the task of understanding how environmental models work and identifying their sensitivities/uncertainties, etc. becomes progressively more difficult. Comprehensive numerical and visual evaluation tools have been developed such as the Monte Carl...

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG

PubMed Central

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies. PMID:29163006

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG.

PubMed

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies.

SCoT: a Python toolbox for EEG source connectivity.

PubMed

Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R

2014-01-01

Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.

SCoT: a Python toolbox for EEG source connectivity

PubMed Central

Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R.

2014-01-01

Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT—a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT. PMID:24653694

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation.

PubMed

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C; Wong, Willy; Daskalakis, Zafiris J; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

PubMed Central

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C.; Wong, Willy; Daskalakis, Zafiris J.; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research. PMID:27774054

FracPaQ: A MATLAB™ toolbox for the quantification of fracture patterns

NASA Astrophysics Data System (ADS)

Healy, David; Rizzo, Roberto E.; Cornwell, David G.; Farrell, Natalie J. C.; Watkins, Hannah; Timms, Nick E.; Gomez-Rivas, Enrique; Smith, Michael

2017-02-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, and spatial distributions often exhibit some kind of order. In detail, relationships may exist among the different fracture attributes, e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture attributes and patterns. This paper describes FracPaQ, a new open source, cross-platform toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on previously published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales, rock types and tectonic settings. The implemented methods presented are inherently scale independent, and a key task where applicable is analysing and integrating quantitative fracture pattern data from micro-to macro-scales. The toolbox was developed in MATLAB™ and the source code is publicly available on GitHub™ and the Mathworks™ FileExchange. The code runs on any computer with MATLAB installed, including PCs with Microsoft Windows, Apple Macs with Mac OS X, and machines running different flavours of Linux. The application, source code and sample input files are available in open repositories in the hope that other developers and researchers will optimise and extend the functionality for the benefit of the wider community.

Forward Field Computation with OpenMEEG

PubMed Central

Gramfort, Alexandre; Papadopoulo, Théodore; Olivi, Emmanuel; Clerc, Maureen

2011-01-01

To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0. PMID:21437231

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

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

Open Babel: An open chemical toolbox

PubMed Central

2011-01-01

Background A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats. Results We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Conclusions Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org. PMID:21982300

Broadview Radar Altimetry Toolbox

NASA Astrophysics Data System (ADS)

Garcia-Mondejar, Albert; Escolà, Roger; Moyano, Gorka; Roca, Mònica; Terra-Homem, Miguel; Friaças, Ana; Martinho, Fernando; Schrama, Ernst; Naeije, Marc; Ambrózio, Américo; Restano, Marco; Benveniste, Jérôme

2017-04-01

The universal altimetry toolbox, BRAT (Broadview Radar Altimetry Toolbox) which can read all previous and current altimetry missions' data, incorporates now the capability to read the upcoming Sentinel3 L1 and L2 products. ESA endeavoured to develop and supply this capability to support the users of the future Sentinel3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats. The BratGUI is the frontend for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with MATLAB/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the dataformatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as NetCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, shows its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Broadview Radar Altimetry Toolbox is a continuation of the Basic Radar Altimetry Toolbox. While developing the new toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The first release of the new Radar Altimetry Toolbox was published in September 2015. It incorporates the capability to read S3 products as well as the new CryoSat2 Baseline C. The second release of the Toolbox, published in October 2016, has a new graphical user interface and other visualisation improvements. The third release (January 2017) includes more features and solves issues from the previous versions.

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB.

PubMed

Purvis, Lucian A B; Clarke, William T; Biasiolli, Luca; Valkovič, Ladislav; Robson, Matthew D; Rodgers, Christopher T

2017-01-01

In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from https://github.com/oxsatoolbox/oxsa.

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

Krishnamurthy, Dheepak

This paper is an overview of Power System Simulation Toolbox (psst). psst is an open-source Python application for the simulation and analysis of power system models. psst simulates the wholesale market operation by solving a DC Optimal Power Flow (DCOPF), Security Constrained Unit Commitment (SCUC) and a Security Constrained Economic Dispatch (SCED). psst also includes models for the various entities in a power system such as Generator Companies (GenCos), Load Serving Entities (LSEs) and an Independent System Operator (ISO). psst features an open modular object oriented architecture that will make it useful for researchers to customize, expand, experiment beyond solvingmore » traditional problems. psst also includes a web based Graphical User Interface (GUI) that allows for user friendly interaction and for implementation on remote High Performance Computing (HPCs) clusters for parallelized operations. This paper also provides an illustrative application of psst and benchmarks with standard IEEE test cases to show the advanced features and the performance of toolbox.« less

QuantumOptics.jl: A Julia framework for simulating open quantum systems

NASA Astrophysics Data System (ADS)

Krämer, Sebastian; Plankensteiner, David; Ostermann, Laurin; Ritsch, Helmut

2018-06-01

We present an open source computational framework geared towards the efficient numerical investigation of open quantum systems written in the Julia programming language. Built exclusively in Julia and based on standard quantum optics notation, the toolbox offers speed comparable to low-level statically typed languages, without compromising on the accessibility and code readability found in dynamic languages. After introducing the framework, we highlight its features and showcase implementations of generic quantum models. Finally, we compare its usability and performance to two well-established and widely used numerical quantum libraries.

Dheepak Krishnamurthy | NREL

Science.gov Websites

. doi: 10.1109/TPWRS.2015.2399171 D. Krishnamurthy; C. Uckun; Z. Zhou; P. Thimmapuram; A. Botterud Systems, vol.PP, no.99, pp.1-1 doi: 10.1109/TPWRS.2017.2685347 A. Pratt, D. Krishnamurthy, M. Ruth, H. Wu : 10.1109/MELE.2016.2614188 D. Krishnamurthy, psst: An open-source power system simulation toolbox in Python

Broadview Radar Altimetry Toolbox

NASA Astrophysics Data System (ADS)

Escolà, Roger; Garcia-Mondejar, Albert; Moyano, Gorka; Roca, Mònica; Terra-Homem, Miguel; Friaças, Ana; Martinho, Fernando; Schrama, Ernst; Naeije, Marc; Ambrozio, Americo; Restano, Marco; Benveniste, Jérôme

2016-04-01

The universal altimetry toolbox, BRAT (Broadview Radar Altimetry Toolbox) which can read all previous and current altimetry missions' data, incorporates now the capability to read the upcoming Sentinel-3 L1 and L2 products. ESA endeavoured to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats. The BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with MATLAB/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as NetCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, shows its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Broadview Radar Altimetry Toolbox is a continuation of the Basic Radar Altimetry Toolbox. While developing the new toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The first Release of the new Radar Altimetry Toolbox was published in September 2015. It incorporates the capability to read S3 products as well as the new CryoSat-2 Baseline C. The second Release of the Toolbox, planned for March 2016, will have a new graphical user interface and some visualisation improvements. The third release, planned for September 2016, will incorporate new datasets such as the lake and rivers or the envissat reprocessed, new features regarding data interpolation and formulas updates.

Broadview Radar Altimetry Toolbox

NASA Astrophysics Data System (ADS)

Mondéjar, Albert; Benveniste, Jérôme; Naeije, Marc; Escolà, Roger; Moyano, Gorka; Roca, Mònica; Terra-Homem, Miguel; Friaças, Ana; Martinho, Fernando; Schrama, Ernst; Ambrózio, Américo; Restano, Marco

2016-07-01

The universal altimetry toolbox, BRAT (Broadview Radar Altimetry Toolbox) which can read all previous and current altimetry missions' data, incorporates now the capability to read the upcoming Sentinel-3 L1 and L2 products. ESA endeavoured to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Études Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats. The BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with MATLAB/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as NetCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, shows its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Broadview Radar Altimetry Toolbox is a continuation of the Basic Radar Altimetry Toolbox. While developing the new toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The first Release of the new Radar Altimetry Toolbox was published in September 2015. It incorporates the capability to read S3 products as well as the new CryoSat-2 Baseline C. The second Release of the Toolbox, planned for March 2016, will have a new graphical user interface and some visualisation improvements. The third release, planned for September 2016, will incorporate new datasets such as the lake and rivers or the EnviSat reprocessed, new features regarding data interpolation and formulas updates.

40 CFR 141.716 - Source toolbox components.

Code of Federal Regulations, 2012 CFR

2012-07-01

... for Microbial Toolbox Components § 141.716 Source toolbox components. (a) Watershed control program. Systems receive 0.5-log Cryptosporidium treatment credit for implementing a watershed control program that meets the requirements of this section. (1) Systems that intend to apply for the watershed control...

40 CFR 141.716 - Source toolbox components.

Code of Federal Regulations, 2013 CFR

2013-07-01

... for Microbial Toolbox Components § 141.716 Source toolbox components. (a) Watershed control program. Systems receive 0.5-log Cryptosporidium treatment credit for implementing a watershed control program that meets the requirements of this section. (1) Systems that intend to apply for the watershed control...

40 CFR 141.716 - Source toolbox components.

Code of Federal Regulations, 2014 CFR

2014-07-01

... for Microbial Toolbox Components § 141.716 Source toolbox components. (a) Watershed control program. Systems receive 0.5-log Cryptosporidium treatment credit for implementing a watershed control program that meets the requirements of this section. (1) Systems that intend to apply for the watershed control...

Dem Generation from Close-Range Photogrammetry Using Extended Python Photogrammetry Toolbox

NASA Astrophysics Data System (ADS)

Belmonte, A. A.; Biong, M. M. P.; Macatulad, E. G.

2017-10-01

Digital elevation models (DEMs) are widely used raster data for different applications concerning terrain, such as for flood modelling, viewshed analysis, mining, land development, engineering design projects, to name a few. DEMs can be obtained through various methods, including topographic survey, LiDAR or photogrammetry, and internet sources. Terrestrial close-range photogrammetry is one of the alternative methods to produce DEMs through the processing of images using photogrammetry software. There are already powerful photogrammetry software that are commercially-available and can produce high-accuracy DEMs. However, this entails corresponding cost. Although, some of these software have free or demo trials, these trials have limits in their usable features and usage time. One alternative is the use of free and open-source software (FOSS), such as the Python Photogrammetry Toolbox (PPT), which provides an interface for performing photogrammetric processes implemented through python script. For relatively small areas such as in mining or construction excavation, a relatively inexpensive, fast and accurate method would be advantageous. In this study, PPT was used to generate 3D point cloud data from images of an open pit excavation. The PPT was extended to add an algorithm converting the generated point cloud data into a usable DEM.

BOLDSync: a MATLAB-based toolbox for synchronized stimulus presentation in functional MRI.

PubMed

Joshi, Jitesh; Saharan, Sumiti; Mandal, Pravat K

2014-02-15

Precise and synchronized presentation of paradigm stimuli in functional magnetic resonance imaging (fMRI) is central to obtaining accurate information about brain regions involved in a specific task. In this manuscript, we present a new MATLAB-based toolbox, BOLDSync, for synchronized stimulus presentation in fMRI. BOLDSync provides a user friendly platform for design and presentation of visual, audio, as well as multimodal audio-visual (AV) stimuli in functional imaging experiments. We present simulation experiments that demonstrate the millisecond synchronization accuracy of BOLDSync, and also illustrate the functionalities of BOLDSync through application to an AV fMRI study. BOLDSync gains an advantage over other available proprietary and open-source toolboxes by offering a user friendly and accessible interface that affords both precision in stimulus presentation and versatility across various types of stimulus designs and system setups. BOLDSync is a reliable, efficient, and versatile solution for synchronized stimulus presentation in fMRI study. Copyright © 2013 Elsevier B.V. All rights reserved.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

MMM: A toolbox for integrative structure modeling.

PubMed

Jeschke, Gunnar

2018-01-01

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples. © 2017 The Protein Society.

PV_LIB Toolbox v. 1.3

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

2015-12-09

PV_LIB comprises a library of Matlab? code for modeling photovoltaic (PV) systems. Included are functions to compute solar position and to estimate irradiance in the PV system's plane of array, cell temperature, PV module electrical output, and conversion from DC to AC power. Also included are functions that aid in determining parameters for module performance models from module characterization testing. PV_LIB is open source code primarily intended for research and academic purposes. All algorithms are documented in openly available literature with the appropriate references included in comments within the code.

GO2OGS 1.0: a versatile workflow to integrate complex geological information with fault data into numerical simulation models

NASA Astrophysics Data System (ADS)

Fischer, T.; Naumov, D.; Sattler, S.; Kolditz, O.; Walther, M.

2015-11-01

We offer a versatile workflow to convert geological models built with the ParadigmTM GOCAD© (Geological Object Computer Aided Design) software into the open-source VTU (Visualization Toolkit unstructured grid) format for usage in numerical simulation models. Tackling relevant scientific questions or engineering tasks often involves multidisciplinary approaches. Conversion workflows are needed as a way of communication between the diverse tools of the various disciplines. Our approach offers an open-source, platform-independent, robust, and comprehensible method that is potentially useful for a multitude of environmental studies. With two application examples in the Thuringian Syncline, we show how a heterogeneous geological GOCAD model including multiple layers and faults can be used for numerical groundwater flow modeling, in our case employing the OpenGeoSys open-source numerical toolbox for groundwater flow simulations. The presented workflow offers the chance to incorporate increasingly detailed data, utilizing the growing availability of computational power to simulate numerical models.

DAFNE: A Matlab toolbox for Bayesian multi-source remote sensing and ancillary data fusion, with application to flood mapping

NASA Astrophysics Data System (ADS)

D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco P.; Pasquariello, Guido

2018-03-01

High-resolution, remotely sensed images of the Earth surface have been proven to be of help in producing detailed flood maps, thanks to their synoptic overview of the flooded area and frequent revisits. However, flood scenarios can be complex situations, requiring the integration of different data in order to provide accurate and robust flood information. Several processing approaches have been recently proposed to efficiently combine and integrate heterogeneous information sources. In this paper, we introduce DAFNE, a Matlab®-based, open source toolbox, conceived to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of following the evolution of an event through multi-temporal output flood maps. Each DAFNE module can be easily modified or upgraded to meet different user needs. The DAFNE suite is presented together with an example of its application.

Quantifying multiple telecouplings using an integrated suite of spatially-explicit tools

NASA Astrophysics Data System (ADS)

Tonini, F.; Liu, J.

2016-12-01

Telecoupling is an interdisciplinary research umbrella concept that enables natural and social scientists to understand and generate information for managing how humans and nature can sustainably coexist worldwide. To systematically study telecoupling, it is essential to build a comprehensive set of spatially-explicit tools for describing and quantifying multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we introduce the Telecoupling Toolbox, a new free and open-source set of tools developed to map and identify the five major interrelated components of the telecoupling framework: systems, flows, agents, causes, and effects. The modular design of the toolbox allows the integration of existing tools and software (e.g. InVEST) to assess synergies and tradeoffs associated with policies and other local to global interventions. We show applications of the toolbox using a number of representative studies that address a variety of scientific and management issues related to telecouplings throughout the world. The results suggest that the toolbox can thoroughly map and quantify multiple telecouplings under various contexts while providing users with an easy-to-use interface. It provides a powerful platform to address globally important issues, such as land use and land cover change, species invasion, migration, flows of ecosystem services, and international trade of goods and products.

PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

PubMed

Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

2016-10-01

The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

Optimizing detection and analysis of slow waves in sleep EEG.

PubMed

Mensen, Armand; Riedner, Brady; Tononi, Giulio

2016-12-01

Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.

U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

USGS Publications Warehouse

Barlow, Paul M.; Cunningham, William L.; Zhai, Tong; Gray, Mark

2015-01-01

This report is a user guide for the streamflow-hydrograph analysis methods provided with version 1.0 of the U.S. Geological Survey (USGS) Groundwater Toolbox computer program. These include six hydrograph-separation methods to determine the groundwater-discharge (base-flow) and surface-runoff components of streamflow—the Base-Flow Index (BFI; Standard and Modified), HYSEP (Fixed Interval, Sliding Interval, and Local Minimum), and PART methods—and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater recharge from streamflow data. The Groundwater Toolbox is a customized interface built on the nonproprietary, open source MapWindow geographic information system software. The program provides graphing, mapping, and analysis capabilities in a Microsoft Windows computing environment. In addition to the four hydrograph-analysis methods, the Groundwater Toolbox allows for the retrieval of hydrologic time-series data (streamflow, groundwater levels, and precipitation) from the USGS National Water Information System, downloading of a suite of preprocessed geographic information system coverages and meteorological data from the National Oceanic and Atmospheric Administration National Climatic Data Center, and analysis of data with several preprocessing and postprocessing utilities. With its data retrieval and analysis tools, the Groundwater Toolbox provides methods to estimate many of the components of the water budget for a hydrologic basin, including precipitation; streamflow; base flow; runoff; groundwater recharge; and total, groundwater, and near-surface evapotranspiration.

TRIQS: A toolbox for research on interacting quantum systems

NASA Astrophysics Data System (ADS)

Parcollet, Olivier; Ferrero, Michel; Ayral, Thomas; Hafermann, Hartmut; Krivenko, Igor; Messio, Laura; Seth, Priyanka

2015-11-01

We present the TRIQS library, a Toolbox for Research on Interacting Quantum Systems. It is an open-source, computational physics library providing a framework for the quick development of applications in the field of many-body quantum physics, and in particular, strongly-correlated electronic systems. It supplies components to develop codes in a modern, concise and efficient way: e.g. Green's function containers, a generic Monte Carlo class, and simple interfaces to HDF5. TRIQS is a C++/Python library that can be used from either language. It is distributed under the GNU General Public License (GPLv3). State-of-the-art applications based on the library, such as modern quantum many-body solvers and interfaces between density-functional-theory codes and dynamical mean-field theory (DMFT) codes are distributed along with it.

An Open-Source Toolbox for Surrogate Modeling of Joint Contact Mechanics

PubMed Central

Eskinazi, Ilan

2016-01-01

Goal Incorporation of elastic joint contact models into simulations of human movement could facilitate studying the interactions between muscles, ligaments, and bones. Unfortunately, elastic joint contact models are often too expensive computationally to be used within iterative simulation frameworks. This limitation can be overcome by using fast and accurate surrogate contact models that fit or interpolate input-output data sampled from existing elastic contact models. However, construction of surrogate contact models remains an arduous task. The aim of this paper is to introduce an open-source program called Surrogate Contact Modeling Toolbox (SCMT) that facilitates surrogate contact model creation, evaluation, and use. Methods SCMT interacts with the third party software FEBio to perform elastic contact analyses of finite element models and uses Matlab to train neural networks that fit the input-output contact data. SCMT features sample point generation for multiple domains, automated sampling, sample point filtering, and surrogate model training and testing. Results An overview of the software is presented along with two example applications. The first example demonstrates creation of surrogate contact models of artificial tibiofemoral and patellofemoral joints and evaluates their computational speed and accuracy, while the second demonstrates the use of surrogate contact models in a forward dynamic simulation of an open-chain leg extension-flexion motion. Conclusion SCMT facilitates the creation of computationally fast and accurate surrogate contact models. Additionally, it serves as a bridge between FEBio and OpenSim musculoskeletal modeling software. Significance Researchers may now create and deploy surrogate models of elastic joint contact with minimal effort. PMID:26186761

The Exoplanet Simple Orbit Fitting Toolbox (ExoSOFT): An Open-source Tool for Efficient Fitting of Astrometric and Radial Velocity Data

NASA Astrophysics Data System (ADS)

Mede, Kyle; Brandt, Timothy D.

2017-03-01

We present the Exoplanet Simple Orbit Fitting Toolbox (ExoSOFT), a new, open-source suite to fit the orbital elements of planetary or stellar-mass companions to any combination of radial velocity and astrometric data. To explore the parameter space of Keplerian models, ExoSOFT may be operated with its own multistage sampling approach or interfaced with third-party tools such as emcee. In addition, ExoSOFT is packaged with a collection of post-processing tools to analyze and summarize the results. Although only a few systems have been observed with both radial velocity and direct imaging techniques, this number will increase, thanks to upcoming spacecraft and ground-based surveys. Providing both forms of data enables simultaneous fitting that can help break degeneracies in the orbital elements that arise when only one data type is available. The dynamical mass estimates this approach can produce are important when investigating the formation mechanisms and subsequent evolution of substellar companions. ExoSOFT was verified through fitting to artificial data and was implemented using the Python and Cython programming languages; it is available for public download at https://github.com/kylemede/ExoSOFT under GNU General Public License v3.

The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli.

PubMed

Crosse, Michael J; Di Liberto, Giovanni M; Bednar, Adam; Lalor, Edmund C

2016-01-01

Understanding how brains process sensory signals in natural environments is one of the key goals of twenty-first century neuroscience. While brain imaging and invasive electrophysiology will play key roles in this endeavor, there is also an important role to be played by noninvasive, macroscopic techniques with high temporal resolution such as electro- and magnetoencephalography. But challenges exist in determining how best to analyze such complex, time-varying neural responses to complex, time-varying and multivariate natural sensory stimuli. There has been a long history of applying system identification techniques to relate the firing activity of neurons to complex sensory stimuli and such techniques are now seeing increased application to EEG and MEG data. One particular example involves fitting a filter-often referred to as a temporal response function-that describes a mapping between some feature(s) of a sensory stimulus and the neural response. Here, we first briefly review the history of these system identification approaches and describe a specific technique for deriving temporal response functions known as regularized linear regression. We then introduce a new open-source toolbox for performing this analysis. We describe how it can be used to derive (multivariate) temporal response functions describing a mapping between stimulus and response in both directions. We also explain the importance of regularizing the analysis and how this regularization can be optimized for a particular dataset. We then outline specifically how the toolbox implements these analyses and provide several examples of the types of results that the toolbox can produce. Finally, we consider some of the limitations of the toolbox and opportunities for future development and application.

The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli

PubMed Central

Crosse, Michael J.; Di Liberto, Giovanni M.; Bednar, Adam; Lalor, Edmund C.

2016-01-01

Understanding how brains process sensory signals in natural environments is one of the key goals of twenty-first century neuroscience. While brain imaging and invasive electrophysiology will play key roles in this endeavor, there is also an important role to be played by noninvasive, macroscopic techniques with high temporal resolution such as electro- and magnetoencephalography. But challenges exist in determining how best to analyze such complex, time-varying neural responses to complex, time-varying and multivariate natural sensory stimuli. There has been a long history of applying system identification techniques to relate the firing activity of neurons to complex sensory stimuli and such techniques are now seeing increased application to EEG and MEG data. One particular example involves fitting a filter—often referred to as a temporal response function—that describes a mapping between some feature(s) of a sensory stimulus and the neural response. Here, we first briefly review the history of these system identification approaches and describe a specific technique for deriving temporal response functions known as regularized linear regression. We then introduce a new open-source toolbox for performing this analysis. We describe how it can be used to derive (multivariate) temporal response functions describing a mapping between stimulus and response in both directions. We also explain the importance of regularizing the analysis and how this regularization can be optimized for a particular dataset. We then outline specifically how the toolbox implements these analyses and provide several examples of the types of results that the toolbox can produce. Finally, we consider some of the limitations of the toolbox and opportunities for future development and application. PMID:27965557

Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

PubMed Central

Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

2012-01-01

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

PubMed

Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

2012-01-01

Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

PubMed

Koul, Atesh; Becchio, Cristina; Cavallo, Andrea

2017-12-12

Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible implementation. The aim of current work was to build an open-source R toolbox - "PredPsych" - that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine-learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture dataset. In addition, we discuss examples of possible research questions that can be addressed with the machine-learning algorithms implemented in PredPsych and cannot be easily addressed with univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

The iRoCS Toolbox--3D analysis of the plant root apical meristem at cellular resolution.

PubMed

Schmidt, Thorsten; Pasternak, Taras; Liu, Kun; Blein, Thomas; Aubry-Hivet, Dorothée; Dovzhenko, Alexander; Duerr, Jasmin; Teale, William; Ditengou, Franck A; Burkhardt, Hans; Ronneberger, Olaf; Palme, Klaus

2014-03-01

To achieve a detailed understanding of processes in biological systems, cellular features must be quantified in the three-dimensional (3D) context of cells and organs. We described use of the intrinsic root coordinate system (iRoCS) as a reference model for the root apical meristem of plants. iRoCS enables direct and quantitative comparison between the root tips of plant populations at single-cell resolution. The iRoCS Toolbox automatically fits standardized coordinates to raw 3D image data. It detects nuclei or segments cells, automatically fits the coordinate system, and groups the nuclei/cells into the root's tissue layers. The division status of each nucleus may also be determined. The only manual step required is to mark the quiescent centre. All intermediate outputs may be refined if necessary. The ability to learn the visual appearance of nuclei by example allows the iRoCS Toolbox to be easily adapted to various phenotypes. The iRoCS Toolbox is provided as an open-source software package, licensed under the GNU General Public License, to make it accessible to a broad community. To demonstrate the power of the technique, we measured subtle changes in cell division patterns caused by modified auxin flux within the Arabidopsis thaliana root apical meristem. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization.

PubMed

Blenkmann, Alejandro O; Phillips, Holly N; Princich, Juan P; Rowe, James B; Bekinschtein, Tristan A; Muravchik, Carlos H; Kochen, Silvia

2017-01-01

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2-3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.

ObsPy: A Python Toolbox for Seismology

NASA Astrophysics Data System (ADS)

Krischer, Lion; Megies, Tobias; Sales de Andrade, Elliott; Barsch, Robert; MacCarthy, Jonathan

2017-04-01

In recent years the Python ecosystem evolved into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community-driven, open-source project dedicated to providing a bridge for seismology into that ecosystem. It does so by offering Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than seven years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases. Additionally we will discuss the road ahead as well as the long-term sustainability of open-source scientific software.

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

PubMed

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

PubMed Central

Blenkmann, Alejandro O.; Phillips, Holly N.; Princich, Juan P.; Rowe, James B.; Bekinschtein, Tristan A.; Muravchik, Carlos H.; Kochen, Silvia

2017-01-01

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions. PMID:28303098

AnisoVis: a MATLAB™ toolbox for the visualisation of elastic anisotropy

NASA Astrophysics Data System (ADS)

Healy, D.; Timms, N.; Pearce, M. A.

2016-12-01

The elastic properties of rocks and minerals vary with direction, and this has significant consequences for their physical response to acoustic waves and natural or imposed stresses. This anisotropy of elasticity is well described mathematically by 4th rank tensors of stiffness or compliance. These tensors are not easy to visualise in a single diagram or graphic, and visualising Poisson's ratio and shear modulus presents a further challenge in that their anisotropy depends on two principal directions. Students and researchers can easily underestimate the importance of elastic anisotropy. This presentation describes an open source toolbox of MATLAB scripts that aims to visualise elastic anisotropy in rocks and minerals. The code produces linked 2-D and 3-D representations of the standard elastic constants, such as Young's modulus, Poisson's ratio and shear modulus, all from a simple GUI. The 3-D plots can be manipulated by the user (rotated, panned, zoomed), to encourage investigation and a deeper understanding of directional variations in the fundamental properties. Examples are presented of common rock forming minerals, including those with negative Poisson's ratio (auxetic behaviour). We hope that an open source code base will encourage further enhancements from the rock physics and wider geoscience communities. Eventually, we hope to generate 3-D prints of these complex and beautiful natural surfaces to provide a tactile link to the underlying physics of elastic anisotropy.

Construction of multi-functional open modulized Matlab simulation toolbox for imaging ladar system

NASA Astrophysics Data System (ADS)

Wu, Long; Zhao, Yuan; Tang, Meng; He, Jiang; Zhang, Yong

2011-06-01

Ladar system simulation is to simulate the ladar models using computer simulation technology in order to predict the performance of the ladar system. This paper presents the developments of laser imaging radar simulation for domestic and overseas studies and the studies of computer simulation on ladar system with different application requests. The LadarSim and FOI-LadarSIM simulation facilities of Utah State University and Swedish Defence Research Agency are introduced in details. This paper presents the low level of simulation scale, un-unified design and applications of domestic researches in imaging ladar system simulation, which are mostly to achieve simple function simulation based on ranging equations for ladar systems. Design of laser imaging radar simulation with open and modularized structure is proposed to design unified modules for ladar system, laser emitter, atmosphere models, target models, signal receiver, parameters setting and system controller. Unified Matlab toolbox and standard control modules have been built with regulated input and output of the functions, and the communication protocols between hardware modules. A simulation based on ICCD gain-modulated imaging ladar system for a space shuttle is made based on the toolbox. The simulation result shows that the models and parameter settings of the Matlab toolbox are able to simulate the actual detection process precisely. The unified control module and pre-defined parameter settings simplify the simulation of imaging ladar detection. Its open structures enable the toolbox to be modified for specialized requests. The modulization gives simulations flexibility.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.

PubMed

Egea, Jose A; Henriques, David; Cokelaer, Thomas; Villaverde, Alejandro F; MacNamara, Aidan; Danciu, Diana-Patricia; Banga, Julio R; Saez-Rodriguez, Julio

2014-05-10

Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics

PubMed Central

2014-01-01

Background Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. Results We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. Conclusions MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods. PMID:24885957

Compressible Flow Toolbox

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.

2006-01-01

The Compressible Flow Toolbox is primarily a MATLAB-language implementation of a set of algorithms that solve approximately 280 linear and nonlinear classical equations for compressible flow. The toolbox is useful for analysis of one-dimensional steady flow with either constant entropy, friction, heat transfer, or Mach number greater than 1. The toolbox also contains algorithms for comparing and validating the equation-solving algorithms against solutions previously published in open literature. The classical equations solved by the Compressible Flow Toolbox are as follows: The isentropic-flow equations, The Fanno flow equations (pertaining to flow of an ideal gas in a pipe with friction), The Rayleigh flow equations (pertaining to frictionless flow of an ideal gas, with heat transfer, in a pipe of constant cross section), The normal-shock equations, The oblique-shock equations, and The expansion equations.

Benchmarking heart rate variability toolboxes.

PubMed

Vest, Adriana N; Li, Qiao; Liu, Chengyu; Nemati, Shamim; Shah, Amit; Clifford, Gari D

Heart rate variability (HRV) metrics hold promise as potential indicators for autonomic function, prediction of adverse cardiovascular outcomes, psychophysiological status, and general wellness. Although the investigation of HRV has been prevalent for several decades, the methods used for preprocessing, windowing, and choosing appropriate parameters lack consensus among academic and clinical investigators. A comprehensive and open-source modular program is presented for calculating HRV implemented in Matlab with evidence-based algorithms and output formats. We compare our software with another widely used HRV toolbox written in C and available through PhysioNet.org. Our findings show substantially similar results when using high quality electrocardiograms (ECG) free from arrhythmias. Our software shows equivalent performance alongside an established predecessor and includes validated tools for performing preprocessing, signal quality, and arrhythmia detection to help provide standardization and repeatability in the field, leading to fewer errors in the presence of noise or arrhythmias. Copyright © 2017 Elsevier Inc. All rights reserved.

ROLE OF SOURCE WATER PROTECTION IN PLANNING FOR AND RESPONDING TO CONTAMINATION THREATS TO DRINKING WATER SYSTEMS

EPA Science Inventory

EPA has developed a "Response Protocol Toolbox" to address the complex, multi-faceted challenges of planning and response to intentional contamination of drinking water (http://www.epa.gov/safewater/security/ertools.html#toolbox). The toolbox is designed to be applied by a numbe...

mGrid: A load-balanced distributed computing environment for the remote execution of the user-defined Matlab code

PubMed Central

Karpievitch, Yuliya V; Almeida, Jonas S

2006-01-01

Background Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. Results mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Conclusion Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over the Internet. PMID:16539707

mGrid: a load-balanced distributed computing environment for the remote execution of the user-defined Matlab code.

PubMed

Karpievitch, Yuliya V; Almeida, Jonas S

2006-03-15

Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over the Internet.

40 CFR 141.717 - Pre-filtration treatment toolbox components.

Code of Federal Regulations, 2011 CFR

2011-07-01

... surface water or GWUDI source. (c) Bank filtration. Systems receive Cryptosporidium treatment credit for... paragraph. Systems using bank filtration when they begin source water monitoring under § 141.701(a) must... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Pre-filtration treatment toolbox...

Design and implementation of an open source indexing solution for a large set of radiological reports and images.

PubMed

Voet, T; Devolder, P; Pynoo, B; Vercruysse, J; Duyck, P

2007-11-01

This paper hopes to share the insights we experienced during designing, building, and running an indexing solution for a large set of radiological reports and images in a production environment for more than 3 years. Several technical challenges were encountered and solved in the course of this project. One hundred four million words in 1.8 million radiological reports from 1989 to the present were indexed and became instantaneously searchable in a user-friendly fashion; the median query duration is only 31 ms. Currently, our highly tuned index holds 332,088 unique words in four languages. The indexing system is feature-rich and language-independent and allows for making complex queries. For research and training purposes it certainly is a valuable and convenient addition to our radiology informatics toolbox. Extended use of open-source technology dramatically reduced both implementation time and cost. All software we developed related to the indexing project has been made available to the open-source community covered by an unrestricted Berkeley Software Distribution-style license.

NeuroPG: open source software for optical pattern generation and data acquisition

PubMed Central

Avants, Benjamin W.; Murphy, Daniel B.; Dapello, Joel A.; Robinson, Jacob T.

2015-01-01

Patterned illumination using a digital micromirror device (DMD) is a powerful tool for optogenetics. Compared to a scanning laser, DMDs are inexpensive and can easily create complex illumination patterns. Combining these complex spatiotemporal illumination patterns with optogenetics allows DMD-equipped microscopes to probe neural circuits by selectively manipulating the activity of many individual cells or many subcellular regions at the same time. To use DMDs to study neural activity, scientists must develop specialized software to coordinate optical stimulation patterns with the acquisition of electrophysiological and fluorescence data. To meet this growing need we have developed an open source optical pattern generation software for neuroscience—NeuroPG—that combines, DMD control, sample visualization, and data acquisition in one application. Built on a MATLAB platform, NeuroPG can also process, analyze, and visualize data. The software is designed specifically for the Mightex Polygon400; however, as an open source package, NeuroPG can be modified to incorporate any data acquisition, imaging, or illumination equipment that is compatible with MATLAB’s Data Acquisition and Image Acquisition toolboxes. PMID:25784873

Real-Time Motion Capture Toolbox (RTMocap): an open-source code for recording 3-D motion kinematics to study action-effect anticipations during motor and social interactions.

PubMed

Lewkowicz, Daniel; Delevoye-Turrell, Yvonne

2016-03-01

We present here a toolbox for the real-time motion capture of biological movements that runs in the cross-platform MATLAB environment (The MathWorks, Inc., Natick, MA). It provides instantaneous processing of the 3-D movement coordinates of up to 20 markers at a single instant. Available functions include (1) the setting of reference positions, areas, and trajectories of interest; (2) recording of the 3-D coordinates for each marker over the trial duration; and (3) the detection of events to use as triggers for external reinforcers (e.g., lights, sounds, or odors). Through fast online communication between the hardware controller and RTMocap, automatic trial selection is possible by means of either a preset or an adaptive criterion. Rapid preprocessing of signals is also provided, which includes artifact rejection, filtering, spline interpolation, and averaging. A key example is detailed, and three typical variations are developed (1) to provide a clear understanding of the importance of real-time control for 3-D motion in cognitive sciences and (2) to present users with simple lines of code that can be used as starting points for customizing experiments using the simple MATLAB syntax. RTMocap is freely available (http://sites.google.com/site/RTMocap/) under the GNU public license for noncommercial use and open-source development, together with sample data and extensive documentation.

Complete scanpaths analysis toolbox.

PubMed

Augustyniak, Piotr; Mikrut, Zbigniew

2006-01-01

This paper presents a complete open software environment for control, data processing and assessment of visual experiments. Visual experiments are widely used in research on human perception physiology and the results are applicable to various visual information-based man-machine interfacing, human-emulated automatic visual systems or scanpath-based learning of perceptual habits. The toolbox is designed for Matlab platform and supports infra-red reflection-based eyetracker in calibration and scanpath analysis modes. Toolbox procedures are organized in three layers: the lower one, communicating with the eyetracker output file, the middle detecting scanpath events on a physiological background and the one upper consisting of experiment schedule scripts, statistics and summaries. Several examples of visual experiments carried out with use of the presented toolbox complete the paper.

SediFoam: A general-purpose, open-source CFD-DEM solver for particle-laden flow with emphasis on sediment transport

NASA Astrophysics Data System (ADS)

Sun, Rui; Xiao, Heng

2016-04-01

With the growth of available computational resource, CFD-DEM (computational fluid dynamics-discrete element method) becomes an increasingly promising and feasible approach for the study of sediment transport. Several existing CFD-DEM solvers are applied in chemical engineering and mining industry. However, a robust CFD-DEM solver for the simulation of sediment transport is still desirable. In this work, the development of a three-dimensional, massively parallel, and open-source CFD-DEM solver SediFoam is detailed. This solver is built based on open-source solvers OpenFOAM and LAMMPS. OpenFOAM is a CFD toolbox that can perform three-dimensional fluid flow simulations on unstructured meshes; LAMMPS is a massively parallel DEM solver for molecular dynamics. Several validation tests of SediFoam are performed using cases of a wide range of complexities. The results obtained in the present simulations are consistent with those in the literature, which demonstrates the capability of SediFoam for sediment transport applications. In addition to the validation test, the parallel efficiency of SediFoam is studied to test the performance of the code for large-scale and complex simulations. The parallel efficiency tests show that the scalability of SediFoam is satisfactory in the simulations using up to O(107) particles.

ePCR: an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts.

PubMed

Laajala, Teemu D; Murtojärvi, Mika; Virkki, Arho; Aittokallio, Tero

2018-06-15

Prognostic models are widely used in clinical decision-making, such as risk stratification and tailoring treatment strategies, with the aim to improve patient outcomes while reducing overall healthcare costs. While prognostic models have been adopted into clinical use, benchmarking their performance has been difficult due to lack of open clinical datasets. The recent DREAM 9.5 Prostate Cancer Challenge carried out an extensive benchmarking of prognostic models for metastatic Castration-Resistant Prostate Cancer (mCRPC), based on multiple cohorts of open clinical trial data. We make available an open-source implementation of the top-performing model, ePCR, along with an extended toolbox for its further re-use and development, and demonstrate how to best apply the implemented model to real-world data cohorts of advanced prostate cancer patients. The open-source R-package ePCR and its reference documentation are available at the Central R Archive Network (CRAN): https://CRAN.R-project.org/package=ePCR. R-vignette provides step-by-step examples for the ePCR usage. Supplementary data are available at Bioinformatics online.

GISMO: A MATLAB toolbox for seismic research, monitoring, & education

NASA Astrophysics Data System (ADS)

Thompson, G.; Reyes, C. G.; Kempler, L. A.

2017-12-01

GISMO is an open-source MATLAB toolbox which provides an object-oriented framework to build workflows and applications that read, process, visualize and write seismic waveform, catalog and instrument response data. GISMO can retrieve data from a variety of sources (e.g. FDSN web services, Earthworm/Winston servers) and data formats (SAC, Seisan, etc.). It can handle waveform data that crosses file boundaries. All this alleviates one of the most time consuming part for scientists developing their own codes. GISMO simplifies seismic data analysis by providing a common interface for your data, regardless of its source. Several common plots are built-in to GISMO, such as record section plots, spectrograms, depth-time sections, event count per unit time, energy release per unit time, etc. Other visualizations include map views and cross-sections of hypocentral data. Several common processing methods are also included, such as an extensive set of tools for correlation analysis. Support is being added to interface GISMO with ObsPy. GISMO encourages community development of an integrated set of codes and accompanying documentation, eliminating the need for seismologists to "reinvent the wheel". By sharing code the consistency and repeatability of results can be enhanced. GISMO is hosted on GitHub with documentation both within the source code and in the project wiki. GISMO has been used at the University of South Florida and University of Alaska Fairbanks in graduate-level courses including Seismic Data Analysis, Time Series Analysis and Computational Seismology. GISMO has also been tailored to interface with the common seismic monitoring software and data formats used by volcano observatories in the US and elsewhere. As an example, toolbox training was delivered to researchers at INETER (Nicaragua). Applications built on GISMO include IceWeb (e.g. web-based spectrograms), which has been used by Alaska Volcano Observatory since 1998 and became the prototype for the USGS Pensive system.

Sodium 3D COncentration MApping (COMA 3D) using 23Na and proton MRI

NASA Astrophysics Data System (ADS)

Truong, Milton L.; Harrington, Michael G.; Schepkin, Victor D.; Chekmenev, Eduard Y.

2014-10-01

Functional changes of sodium 3D MRI signals were converted into millimolar concentration changes using an open-source fully automated MATLAB toolbox. These concentration changes are visualized via 3D sodium concentration maps, and they are overlaid over conventional 3D proton images to provide high-resolution co-registration for easy correlation of functional changes to anatomical regions. Nearly 5000/h concentration maps were generated on a personal computer (ca. 2012) using 21.1 T 3D sodium MRI brain images of live rats with spatial resolution of 0.8 × 0.8 × 0.8 mm3 and imaging matrices of 60 × 60 × 60. The produced concentration maps allowed for non-invasive quantitative measurement of in vivo sodium concentration in the normal rat brain as a functional response to migraine-like conditions. The presented work can also be applied to sodium-associated changes in migraine, cancer, and other metabolic abnormalities that can be sensed by molecular imaging. The MATLAB toolbox allows for automated image analysis of the 3D images acquired on the Bruker platform and can be extended to other imaging platforms. The resulting images are presented in a form of series of 2D slices in all three dimensions in native MATLAB and PDF formats. The following is provided: (a) MATLAB source code for image processing, (b) the detailed processing procedures, (c) description of the code and all sub-routines, (d) example data sets of initial and processed data. The toolbox can be downloaded at: http://www.vuiis.vanderbilt.edu/ truongm/COMA3D/.

Software Toolbox Development for Rapid Earthquake Source Optimisation Combining InSAR Data and Seismic Waveforms

NASA Astrophysics Data System (ADS)

Isken, Marius P.; Sudhaus, Henriette; Heimann, Sebastian; Steinberg, Andreas; Bathke, Hannes M.

2017-04-01

We present a modular open-source software framework (pyrocko, kite, grond; http://pyrocko.org) for rapid InSAR data post-processing and modelling of tectonic and volcanic displacement fields derived from satellite data. Our aim is to ease and streamline the joint optimisation of earthquake observations from InSAR and GPS data together with seismological waveforms for an improved estimation of the ruptures' parameters. Through this approach we can provide finite models of earthquake ruptures and therefore contribute to a timely and better understanding of earthquake kinematics. The new kite module enables a fast processing of unwrapped InSAR scenes for source modelling: the spatial sub-sampling and data error/noise estimation for the interferogram is evaluated automatically and interactively. The rupture's near-field surface displacement data are then combined with seismic far-field waveforms and jointly modelled using the pyrocko.gf framwork, which allows for fast forward modelling based on pre-calculated elastodynamic and elastostatic Green's functions. Lastly the grond module supplies a bootstrap-based probabilistic (Monte Carlo) joint optimisation to estimate the parameters and uncertainties of a finite-source earthquake rupture model. We describe the developed and applied methods as an effort to establish a semi-automatic processing and modelling chain. The framework is applied to Sentinel-1 data from the 2016 Central Italy earthquake sequence, where we present the earthquake mechanism and rupture model from which we derive regions of increased coulomb stress. The open source software framework is developed at GFZ Potsdam and at the University of Kiel, Germany, it is written in Python and C programming languages. The toolbox architecture is modular and independent, and can be utilized flexibly for a variety of geophysical problems. This work is conducted within the BridGeS project (http://www.bridges.uni-kiel.de) funded by the German Research Foundation DFG through an Emmy-Noether grant.

PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography

NASA Astrophysics Data System (ADS)

Thomas, Benjamin A.; Cuplov, Vesna; Bousse, Alexandre; Mendes, Adriana; Thielemans, Kris; Hutton, Brian F.; Erlandsson, Kjell

2016-11-01

Positron emission tomography (PET) images are degraded by a phenomenon known as the partial volume effect (PVE). Approaches have been developed to reduce PVEs, typically through the utilisation of structural information provided by other imaging modalities such as MRI or CT. These methods, known as partial volume correction (PVC) techniques, reduce PVEs by compensating for the effects of the scanner resolution, thereby improving the quantitative accuracy. The PETPVC toolbox described in this paper comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data. Eight core PVC techniques are available. These core methods can be combined to create a total of 22 different PVC techniques. Simulated brain PET data are used to demonstrate the utility of toolbox in idealised conditions, the effects of applying PVC with mismatched point-spread function (PSF) estimates and the potential of novel hybrid PVC methods to improve the quantification of lesions. All anatomy-based PVC techniques achieve complete recovery of the PET signal in cortical grey matter (GM) when performed in idealised conditions. Applying deconvolution-based approaches results in incomplete recovery due to premature termination of the iterative process. PVC techniques are sensitive to PSF mismatch, causing a bias of up to 16.7% in GM recovery when over-estimating the PSF by 3 mm. The recovery of both GM and a simulated lesion was improved by combining two PVC techniques together. The PETPVC toolbox has been written in C++, supports Windows, Mac and Linux operating systems, is open-source and publicly available.

FACET - a "Flexible Artifact Correction and Evaluation Toolbox" for concurrently recorded EEG/fMRI data.

PubMed

Glaser, Johann; Beisteiner, Roland; Bauer, Herbert; Fischmeister, Florian Ph S

2013-11-09

In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings. FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230-239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720-737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices. The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches.

An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis.

PubMed

Fayyaz S, S Kiavash; Liu, Xiaoyue Cathy; Zhang, Guohui

2017-01-01

The social functions of urbanized areas are highly dependent on and supported by the convenient access to public transportation systems, particularly for the less privileged populations who have restrained auto ownership. To accurately evaluate the public transit accessibility, it is critical to capture the spatiotemporal variation of transit services. This can be achieved by measuring the shortest paths or minimum travel time between origin-destination (OD) pairs at each time-of-day (e.g. every minute). In recent years, General Transit Feed Specification (GTFS) data has been gaining popularity for between-station travel time estimation due to its interoperability in spatiotemporal analytics. Many software packages, such as ArcGIS, have developed toolbox to enable the travel time estimation with GTFS. They perform reasonably well in calculating travel time between OD pairs for a specific time-of-day (e.g. 8:00 AM), yet can become computational inefficient and unpractical with the increase of data dimensions (e.g. all times-of-day and large network). In this paper, we introduce a new algorithm that is computationally elegant and mathematically efficient to address this issue. An open-source toolbox written in C++ is developed to implement the algorithm. We implemented the algorithm on City of St. George's transit network to showcase the accessibility analysis enabled by the toolbox. The experimental evidence shows significant reduction on computational time. The proposed algorithm and toolbox presented is easily transferable to other transit networks to allow transit agencies and researchers perform high resolution transit performance analysis.

An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis

PubMed Central

Fayyaz S., S. Kiavash; Zhang, Guohui

2017-01-01

The social functions of urbanized areas are highly dependent on and supported by the convenient access to public transportation systems, particularly for the less privileged populations who have restrained auto ownership. To accurately evaluate the public transit accessibility, it is critical to capture the spatiotemporal variation of transit services. This can be achieved by measuring the shortest paths or minimum travel time between origin-destination (OD) pairs at each time-of-day (e.g. every minute). In recent years, General Transit Feed Specification (GTFS) data has been gaining popularity for between-station travel time estimation due to its interoperability in spatiotemporal analytics. Many software packages, such as ArcGIS, have developed toolbox to enable the travel time estimation with GTFS. They perform reasonably well in calculating travel time between OD pairs for a specific time-of-day (e.g. 8:00 AM), yet can become computational inefficient and unpractical with the increase of data dimensions (e.g. all times-of-day and large network). In this paper, we introduce a new algorithm that is computationally elegant and mathematically efficient to address this issue. An open-source toolbox written in C++ is developed to implement the algorithm. We implemented the algorithm on City of St. George’s transit network to showcase the accessibility analysis enabled by the toolbox. The experimental evidence shows significant reduction on computational time. The proposed algorithm and toolbox presented is easily transferable to other transit networks to allow transit agencies and researchers perform high resolution transit performance analysis. PMID:28981544

The GNAT: A new tool for processing NMR data.

PubMed

Castañar, Laura; Poggetto, Guilherme Dal; Colbourne, Adam A; Morris, Gareth A; Nilsson, Mathias

2018-06-01

The GNAT (General NMR Analysis Toolbox) is a free and open-source software package for processing, visualising, and analysing NMR data. It supersedes the popular DOSY Toolbox, which has a narrower focus on diffusion NMR. Data import of most common formats from the major NMR platforms is supported, as well as a GNAT generic format. Key basic processing of NMR data (e.g., Fourier transformation, baseline correction, and phasing) is catered for within the program, as well as more advanced techniques (e.g., reference deconvolution and pure shift FID reconstruction). Analysis tools include DOSY and SCORE for diffusion data, ROSY T 1 /T 2 estimation for relaxation data, and PARAFAC for multilinear analysis. The GNAT is written for the MATLAB® language and comes with a user-friendly graphical user interface. The standard version is intended to run with a MATLAB installation, but completely free-standing compiled versions for Windows, Mac, and Linux are also freely available. © 2018 The Authors Magnetic Resonance in Chemistry Published by John Wiley & Sons Ltd.

Arc_Mat: a Matlab-based spatial data analysis toolbox

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Lesage, James

2010-03-01

This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

Simple tool for the rapid, automated quantification of glacier advance/retreat observations using multiple methods

NASA Astrophysics Data System (ADS)

Lea, J.

2017-12-01

The quantification of glacier change is a key variable within glacier monitoring, with the method used potentially being crucial to ensuring that data can be appropriately compared with environmental data. The topic and timescales of study (e.g. land/marine terminating environments; sub-annual/decadal/centennial/millennial timescales) often mean that different methods are more suitable for different problems. However, depending on the GIS/coding expertise of the user, some methods can potentially be time consuming to undertake, making large-scale studies problematic. In addition, examples exist where different users have nominally applied the same methods in different studies, though with minor methodological inconsistencies in their approach. In turn, this will have implications for data homogeneity where regional/global datasets may be constructed. Here, I present a simple toolbox scripted in a Matlab® environment that requires only glacier margin and glacier centreline data to quantify glacier length, glacier change between observations, rate of change, in addition to other metrics. The toolbox includes the option to apply the established centreline or curvilinear box methods, or a new method: the variable box method - designed for tidewater margins where box width is defined as the total width of the individual terminus observation. The toolbox is extremely flexible, and has the option to be applied as either Matlab® functions within user scripts, or via a graphical user interface (GUI) for those unfamiliar with a coding environment. In both instances, there is potential to apply the methods quickly to large datasets (100s-1000s of glaciers, with potentially similar numbers of observations each), thus ensuring large scale methodological consistency (and therefore data homogeneity) and allowing regional/global scale analyses to be achievable for those with limited GIS/coding experience. The toolbox has been evaluated against idealised scenarios demonstrating its accuracy, while feedback from undergraduate students who have trialled the toolbox is that it is intuitive and simple to use. When released, the toolbox will be free and open source allowing users to potentially modify, improve and expand upon the current version.

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

User Guide for Compressible Flow Toolbox Version 2.1 for Use With MATLAB(Registered Trademark); Version 7

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.

2006-01-01

This report provides a user guide for the Compressible Flow Toolbox, a collection of algorithms that solve almost 300 linear and nonlinear classical compressible flow relations. The algorithms, implemented in the popular MATLAB programming language, are useful for analysis of one-dimensional steady flow with constant entropy, friction, heat transfer, or shock discontinuities. The solutions do not include any gas dissociative effects. The toolbox also contains functions for comparing and validating the equation-solving algorithms against solutions previously published in the open literature. The classical equations solved by the Compressible Flow Toolbox are: isentropic-flow equations, Fanno flow equations (pertaining to flow of an ideal gas in a pipe with friction), Rayleigh flow equations (pertaining to frictionless flow of an ideal gas, with heat transfer, in a pipe of constant cross section.), normal-shock equations, oblique-shock equations, and Prandtl-Meyer expansion equations. At the time this report was published, the Compressible Flow Toolbox was available without cost from the NASA Software Repository.

CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms.

PubMed

Kohlhoff, Kai J; Sosnick, Marc H; Hsu, William T; Pande, Vijay S; Altman, Russ B

2011-08-15

Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created Clustering Algorithms for Massively Parallel Architectures, Including GPU Nodes (CAMPAIGN), a central resource for data clustering algorithms and tools that are implemented specifically for execution on massively parallel processing architectures. CAMPAIGN is a library of data clustering algorithms and tools, written in 'C for CUDA' for Nvidia GPUs. The library provides up to two orders of magnitude speed-up over respective CPU-based clustering algorithms and is intended as an open-source resource. New modules from the community will be accepted into the library and the layout of it is such that it can easily be extended to promising future platforms such as OpenCL. Releases of the CAMPAIGN library are freely available for download under the LGPL from https://simtk.org/home/campaign. Source code can also be obtained through anonymous subversion access as described on https://simtk.org/scm/?group_id=453. kjk33@cantab.net.

Microbe-ID: an open source toolbox for microbial genotyping and species identification.

PubMed

Tabima, Javier F; Everhart, Sydney E; Larsen, Meredith M; Weisberg, Alexandra J; Kamvar, Zhian N; Tancos, Matthew A; Smart, Christine D; Chang, Jeff H; Grünwald, Niklaus J

2016-01-01

Development of tools to identify species, genotypes, or novel strains of invasive organisms is critical for monitoring emergence and implementing rapid response measures. Molecular markers, although critical to identifying species or genotypes, require bioinformatic tools for analysis. However, user-friendly analytical tools for fast identification are not readily available. To address this need, we created a web-based set of applications called Microbe-ID that allow for customizing a toolbox for rapid species identification and strain genotyping using any genetic markers of choice. Two components of Microbe-ID, named Sequence-ID and Genotype-ID, implement species and genotype identification, respectively. Sequence-ID allows identification of species by using BLAST to query sequences for any locus of interest against a custom reference sequence database. Genotype-ID allows placement of an unknown multilocus marker in either a minimum spanning network or dendrogram with bootstrap support from a user-created reference database. Microbe-ID can be used for identification of any organism based on nucleotide sequences or any molecular marker type and several examples are provided. We created a public website for demonstration purposes called Microbe-ID (microbe-id.org) and provided a working implementation for the genus Phytophthora (phytophthora-id.org). In Phytophthora-ID, the Sequence-ID application allows identification based on ITS or cox spacer sequences. Genotype-ID groups individuals into clonal lineages based on simple sequence repeat (SSR) markers for the two invasive plant pathogen species P. infestans and P. ramorum. All code is open source and available on github and CRAN. Instructions for installation and use are provided at https://github.com/grunwaldlab/Microbe-ID.

Optimising the Parallelisation of OpenFOAM Simulations

DTIC Science & Technology

2014-06-01

UNCLASSIFIED UNCLASSIFIED Optimising the Parallelisation of OpenFOAM Simulations Shannon Keough Maritime Division Defence...Science and Technology Organisation DSTO-TR-2987 ABSTRACT The OpenFOAM computational fluid dynamics toolbox allows parallel computation of...performance of a given high performance computing cluster with several OpenFOAM cases, running using a combination of MPI libraries and corresponding MPI

Web-based spatial analysis with the ILWIS open source GIS software and satellite images from GEONETCast

NASA Astrophysics Data System (ADS)

Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.

2009-12-01

This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the fingertips of users around the globe. This user-friendly and low-cost information dissemination provides global information as a basis for decision-making in a number of critical areas, including public health, energy, agriculture, weather, water, climate, natural disasters and ecosystems. GEONETCast makes available satellite images via Digital Video Broadcast (DVB) technology. An OGC WMS interface and plug-ins which convert GEONETCast data streams allow an ILWIS user to integrate various distributed data sources with data locally stored on his machine. Our paper describes a use case in which ILWIS is used with GEONETCast satellite imagery for decision making processes in Ghana. We also explain how the ILWIS software can be extended with additional functionality by means of building plug-ins and unfold our plans to implement other OGC standards, such as WCS and WPS in the same context. Especially, the latter one can be seen as a major step forward in terms of moving well-proven desktop based processing functionality to the web. This enables the embedding of ILWIS functionality in Spatial Data Infrastructures or even the execution in scalable and on-demand cloud computing environments.

MTpy: A Python toolbox for magnetotellurics

NASA Astrophysics Data System (ADS)

Krieger, Lars; Peacock, Jared R.

2014-11-01

We present the software package MTpy that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software. In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools, MTpy is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community. In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.

Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling

PubMed Central

Lareo, Angel; Forlim, Caroline G.; Pinto, Reynaldo D.; Varona, Pablo; Rodriguez, Francisco de Borja

2016-01-01

Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox. PMID:27766078

Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling.

PubMed

Lareo, Angel; Forlim, Caroline G; Pinto, Reynaldo D; Varona, Pablo; Rodriguez, Francisco de Borja

2016-01-01

Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis.

PubMed

McCoy, D B; Talbott, J F; Wilson, Michael; Mamlouk, M D; Cohen-Adad, J; Wilson, Mark; Narvid, J

2017-02-01

Recent advances in spinal cord imaging analysis have led to the development of a robust anatomic template and atlas incorporated into an open-source platform referred to as the Spinal Cord Toolbox. Using the Spinal Cord Toolbox, we sought to correlate measures of GM, WM, and cross-sectional area pathology on T2 MR imaging with motor disability in patients with acute flaccid myelitis. Spinal cord imaging for 9 patients with acute flaccid myelitis was analyzed by using the Spinal Cord Toolbox. A semiautomated pipeline using the Spinal Cord Toolbox measured lesion involvement in GM, WM, and total spinal cord cross-sectional area. Proportions of GM, WM, and cross-sectional area affected by T2 hyperintensity were calculated across 3 ROIs: 1) center axial section of lesion; 2) full lesion segment; and 3) full cord atlas volume. Spearman rank order correlation was calculated to compare MR metrics with clinical measures of disability. Proportion of GM metrics at the center axial section significantly correlated with measures of motor impairment upon admission ( r [9] = -0.78; P = .014) and at 3-month follow-up ( r [9] = -0.66; P = .05). Further, proportion of GM extracted across the full lesion segment significantly correlated with initial motor impairment ( r [9] = -0.74, P = .024). No significant correlation was found for proportion of WM or proportion of cross-sectional area with clinical disability. Atlas-based measures of proportion of GM T2 signal abnormality measured on a single axial MR imaging section and across the full lesion segment correlate with motor impairment and outcome in patients with acute flaccid myelitis. This is the first atlas-based study to correlate clinical outcomes with segmented measures of T2 signal abnormality in the spinal cord. © 2017 by American Journal of Neuroradiology.

SacLab: A toolbox for saccade analysis to increase usability of eye tracking systems in clinical ophthalmology practice.

PubMed

Cercenelli, Laura; Tiberi, Guido; Corazza, Ivan; Giannaccare, Giuseppe; Fresina, Michela; Marcelli, Emanuela

2017-01-01

Many open source software packages have been recently developed to expand the usability of eye tracking systems to study oculomotor behavior, but none of these is specifically designed to encompass all the main functions required for creating eye tracking tests and for providing the automatic analysis of saccadic eye movements. The aim of this study is to introduce SacLab, an intuitive, freely-available MATLAB toolbox based on Graphical User Interfaces (GUIs) that we have developed to increase the usability of the ViewPoint EyeTracker (Arrington Research, Scottsdale, AZ, USA) in clinical ophthalmology practice. SacLab consists of four processing modules that enable the user to easily create visual stimuli tests (Test Designer), record saccadic eye movements (Data Recorder), analyze the recorded data to automatically extract saccadic parameters of clinical interest (Data Analyzer) and provide an aggregate analysis from multiple eye movements recordings (Saccade Analyzer), without requiring any programming effort by the user. A demo application of SacLab to carry out eye tracking tests for the analysis of horizontal saccades was reported. We tested the usability of SacLab toolbox with three ophthalmologists who had no programming experience; the ophthalmologists were briefly trained in the use of SacLab GUIs and were asked to perform the demo application. The toolbox gained an enthusiastic feedback from all the clinicians in terms of intuitiveness, ease of use and flexibility. Test creation and data processing were accomplished in 52±21s and 46±19s, respectively, using the SacLab GUIs. SacLab may represent a useful tool to ease the application of the ViewPoint EyeTracker system in clinical routine in ophthalmology. Copyright © 2016 Elsevier Ltd. All rights reserved.

FocusStack and StimServer: a new open source MATLAB toolchain for visual stimulation and analysis of two-photon calcium neuronal imaging data.

PubMed

Muir, Dylan R; Kampa, Björn M

2014-01-01

Two-photon calcium imaging of neuronal responses is an increasingly accessible technology for probing population responses in cortex at single cell resolution, and with reasonable and improving temporal resolution. However, analysis of two-photon data is usually performed using ad-hoc solutions. To date, no publicly available software exists for straightforward analysis of stimulus-triggered two-photon imaging experiments. In addition, the increasing data rates of two-photon acquisition systems imply increasing cost of computing hardware required for in-memory analysis. Here we present a Matlab toolbox, FocusStack, for simple and efficient analysis of two-photon calcium imaging stacks on consumer-level hardware, with minimal memory footprint. We also present a Matlab toolbox, StimServer, for generation and sequencing of visual stimuli, designed to be triggered over a network link from a two-photon acquisition system. FocusStack is compatible out of the box with several existing two-photon acquisition systems, and is simple to adapt to arbitrary binary file formats. Analysis tools such as stack alignment for movement correction, automated cell detection and peri-stimulus time histograms are already provided, and further tools can be easily incorporated. Both packages are available as publicly-accessible source-code repositories.

FocusStack and StimServer: a new open source MATLAB toolchain for visual stimulation and analysis of two-photon calcium neuronal imaging data

PubMed Central

Muir, Dylan R.; Kampa, Björn M.

2015-01-01

Two-photon calcium imaging of neuronal responses is an increasingly accessible technology for probing population responses in cortex at single cell resolution, and with reasonable and improving temporal resolution. However, analysis of two-photon data is usually performed using ad-hoc solutions. To date, no publicly available software exists for straightforward analysis of stimulus-triggered two-photon imaging experiments. In addition, the increasing data rates of two-photon acquisition systems imply increasing cost of computing hardware required for in-memory analysis. Here we present a Matlab toolbox, FocusStack, for simple and efficient analysis of two-photon calcium imaging stacks on consumer-level hardware, with minimal memory footprint. We also present a Matlab toolbox, StimServer, for generation and sequencing of visual stimuli, designed to be triggered over a network link from a two-photon acquisition system. FocusStack is compatible out of the box with several existing two-photon acquisition systems, and is simple to adapt to arbitrary binary file formats. Analysis tools such as stack alignment for movement correction, automated cell detection and peri-stimulus time histograms are already provided, and further tools can be easily incorporated. Both packages are available as publicly-accessible source-code repositories1. PMID:25653614

Mars at war

NASA Astrophysics Data System (ADS)

2018-04-01

Whether the climate of early Mars was warm and wet or cold and dry remains unclear, but the debate is overheated. With a growing toolbox and increasing data to tackle the open questions, progress is possible if there is openness to bridging the divide.

A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography.

PubMed

Yang, Xiaogang; De Carlo, Francesco; Phatak, Charudatta; Gürsoy, Dogˇa

2017-03-01

This paper presents an algorithm to calibrate the center-of-rotation for X-ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential for reducing or removing other artifacts caused by instrument instability, detector non-linearity, etc. An open-source toolbox, which integrates the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.

System-Events Toolbox--Activating Urban Places for Social Cohesion through Designing a System of Events That Relies on Local Resources

ERIC Educational Resources Information Center

Fassi, Davide; Motter, Roberta

2014-01-01

This paper is a reflection on the use of public spaces in towns and the development of a system-events toolbox to activate them towards social cohesion. It is the result of a 1 year action research developed together with POLIMI DESIS Lab of the Department of Design to develop design solutions to open up the public spaces of the campus to the…

[Random Variable Read Me File

NASA Technical Reports Server (NTRS)

Teubert, Christopher; Sankararaman, Shankar; Cullo, Aiden

2017-01-01

Readme for the Random Variable Toolbox usable manner. is a Web-based Git version control repository hosting service. It is mostly used for computer code. It offers all of the distributed version control and source code management (SCM) functionality of Git as well as adding its own features. It provides access control and several collaboration features such as bug tracking, feature requests, task management, and wikis for every project.[3] GitHub offers both plans for private and free repositories on the same account[4] which are commonly used to host open-source software projects.[5] As of April 2017, GitHub reports having almost 20 million users and 57 million repositories,[6] making it the largest host of source code in the world.[7] GitHub has a mascot called Octocat, a cat with five tentacles and a human-like face

Computational investigations and grid refinement study of 3D transient flow in a cylindrical tank using OpenFOAM

NASA Astrophysics Data System (ADS)

Mohd Sakri, F.; Mat Ali, M. S.; Sheikh Salim, S. A. Z.

2016-10-01

The study of physic fluid for a liquid draining inside a tank is easily accessible using numerical simulation. However, numerical simulation is expensive when the liquid draining involves the multi-phase problem. Since an accurate numerical simulation can be obtained if a proper method for error estimation is accomplished, this paper provides systematic assessment of error estimation due to grid convergence error using OpenFOAM. OpenFOAM is an open source CFD-toolbox and it is well-known among the researchers and institutions because of its free applications and ready to use. In this study, three types of grid resolution are used: coarse, medium and fine grids. Grid Convergence Index (GCI) is applied to estimate the error due to the grid sensitivity. A monotonic convergence condition is obtained in this study that shows the grid convergence error has been progressively reduced. The fine grid has the GCI value below 1%. The extrapolated value from Richardson Extrapolation is in the range of the GCI obtained.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

PubMed

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

MEG/EEG Source Reconstruction, Statistical Evaluation, and Visualization with NUTMEG

PubMed Central

Dalal, Sarang S.; Zumer, Johanna M.; Guggisberg, Adrian G.; Trumpis, Michael; Wong, Daniel D. E.; Sekihara, Kensuke; Nagarajan, Srikantan S.

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions. PMID:21437174

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG.

PubMed

Dalal, Sarang S; Zumer, Johanna M; Guggisberg, Adrian G; Trumpis, Michael; Wong, Daniel D E; Sekihara, Kensuke; Nagarajan, Srikantan S

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.

Microbe-ID: an open source toolbox for microbial genotyping and species identification

PubMed Central

Tabima, Javier F.; Everhart, Sydney E.; Larsen, Meredith M.; Weisberg, Alexandra J.; Kamvar, Zhian N.; Tancos, Matthew A.; Smart, Christine D.; Chang, Jeff H.

2016-01-01

Development of tools to identify species, genotypes, or novel strains of invasive organisms is critical for monitoring emergence and implementing rapid response measures. Molecular markers, although critical to identifying species or genotypes, require bioinformatic tools for analysis. However, user-friendly analytical tools for fast identification are not readily available. To address this need, we created a web-based set of applications called Microbe-ID that allow for customizing a toolbox for rapid species identification and strain genotyping using any genetic markers of choice. Two components of Microbe-ID, named Sequence-ID and Genotype-ID, implement species and genotype identification, respectively. Sequence-ID allows identification of species by using BLAST to query sequences for any locus of interest against a custom reference sequence database. Genotype-ID allows placement of an unknown multilocus marker in either a minimum spanning network or dendrogram with bootstrap support from a user-created reference database. Microbe-ID can be used for identification of any organism based on nucleotide sequences or any molecular marker type and several examples are provided. We created a public website for demonstration purposes called Microbe-ID (microbe-id.org) and provided a working implementation for the genus Phytophthora (phytophthora-id.org). In Phytophthora-ID, the Sequence-ID application allows identification based on ITS or cox spacer sequences. Genotype-ID groups individuals into clonal lineages based on simple sequence repeat (SSR) markers for the two invasive plant pathogen species P. infestans and P. ramorum. All code is open source and available on github and CRAN. Instructions for installation and use are provided at https://github.com/grunwaldlab/Microbe-ID. PMID:27602267

ObsPy: A Python Toolbox for Seismology

NASA Astrophysics Data System (ADS)

Wassermann, J. M.; Krischer, L.; Megies, T.; Barsch, R.; Beyreuther, M.

2013-12-01

Python combines the power of a full-blown programming language with the flexibility and accessibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy is a community-driven, open-source project extending Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers most tasks common in seismological analysis, b) provides read and write support for many common waveform, station and event metadata formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with mature and free Python packages like NumPy, SciPy, Matplotlib, IPython, Pandas, lxml, and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI and web applications, output of modified/derived data and the creation of publication-quality figures. All functionality is extensively documented and the ObsPy Tutorial and Gallery give a good impression of the wide range of possible use cases. ObsPy is tested and running on Linux, OS X and Windows and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the LGPLv3 open source licence. Users are welcome to request help, report bugs, propose enhancements or contribute code via either the user mailing list or the project page on GitHub.

Open source data assimilation framework for hydrological modeling

NASA Astrophysics Data System (ADS)

Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

2013-04-01

An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.

Demonstrating High-Accuracy Orbital Access Using Open-Source Tools

NASA Technical Reports Server (NTRS)

Gilbertson, Christian; Welch, Bryan

2017-01-01

Orbit propagation is fundamental to almost every space-based analysis. Currently, many system analysts use commercial software to predict the future positions of orbiting satellites. This is one of many capabilities that can replicated, with great accuracy, without using expensive, proprietary software. NASAs SCaN (Space Communication and Navigation) Center for Engineering, Networks, Integration, and Communications (SCENIC) project plans to provide its analysis capabilities using a combination of internal and open-source software, allowing for a much greater measure of customization and flexibility, while reducing recurring software license costs. MATLAB and the open-source Orbit Determination Toolbox created by Goddard Space Flight Center (GSFC) were utilized to develop tools with the capability to propagate orbits, perform line-of-sight (LOS) availability analyses, and visualize the results. The developed programs are modular and can be applied for mission planning and viability analysis in a variety of Solar System applications. The tools can perform 2 and N-body orbit propagation, find inter-satellite and satellite to ground station LOS access (accounting for intermediate oblate spheroid body blocking, geometric restrictions of the antenna field-of-view (FOV), and relativistic corrections), and create animations of planetary movement, satellite orbits, and LOS accesses. The code is the basis for SCENICs broad analysis capabilities including dynamic link analysis, dilution-of-precision navigation analysis, and orbital availability calculations.

Explaining Society: An Expanded Toolbox for Social Scientists

PubMed Central

Bell, David C.; Atkinson-Schnell, Jodie L.; DiBacco, Aron E.

2012-01-01

We propose for social scientists a theoretical toolbox containing a set of motivations that neurobiologists have recently validated. We show how these motivations can be used to create a theory of society recognizably similar to existing stable societies (sustainable, self-reproducing, and largely peaceful). Using this toolbox, we describe society in terms of three institutions: economy (a source of sustainability), government (peace), and the family (reproducibility). Conducting a thought experiment in three parts, we begin with a simple theory with only two motivations. We then create successive theories that systematically add motivations, showing that each element in the toolbox makes its own contribution to explain the workings of a stable society and that the family has a critical role in this process. PMID:23082093

EEG and MEG data analysis in SPM8.

PubMed

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.

EEG and MEG Data Analysis in SPM8

PubMed Central

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools. PMID:21437221

Evol and ProDy for bridging protein sequence evolution and structural dynamics

PubMed Central

Mao, Wenzhi; Liu, Ying; Chennubhotla, Chakra; Lezon, Timothy R.; Bahar, Ivet

2014-01-01

Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics. Availability and implementation: ProDy and Evol are open-source and freely available under MIT License from http://prody.csb.pitt.edu/. Contact: bahar@pitt.edu PMID:24849577

A toolbox to visualise benefits resulting from flood hazard mitigation

NASA Astrophysics Data System (ADS)

Fuchs, Sven; Thaler, Thomas; Heiser, Micha

2017-04-01

In order to visualize the benefits resulting from technical mitigation, a toolbox was developed within an open-source environment that allows for an assessment of gains and losses for buildings exposed to flood hazards. Starting with different scenarios showing the changes in flood magnitude with respect to the considered management options, the computation was based on the amount and value of buildings exposed as well as their vulnerability, following the general concept of risk assessment. As a result, beneficiaries of risk reduction may be identified and - more general - also different mitigation options may be strategically evaluated with respect to the height of risk reduction for different elements exposed. As such, multiple management options can be ranked according to their costs and benefits, and in order of priority. A relational database composed from different modules was created in order to mirror the requirements of an open source application and to allow for future dynamics in the data availability as well as the spatiotemporal dynamics of this data (Fuchs et al. 2013). An economic module was used to compute the monetary value of buildings exposed using (a) the building footprint, (b) the information of the building cadaster such as building type, number of storeys and utilisation, and (c) regionally averaged construction costs. An exposition module was applied to connect the spatial GIS information (X and Y coordinates) of elements at risk to the hazard information in order to achieve information on exposure. An impact module linked this information to vulnerability functions (Totschnig and Fuchs 2013; Papathoma-Köhle et al. 2015) in order to achieve the monetary level of risk for every building exposed. These values were finally computed before and after the implementation of mitigation measure in order to show gains and losses, and visualised. The results can be exported in terms of spread sheets for further computation. References Fuchs S, Keiler M, Sokratov SA, Shnyparkov A (2013) Spatiotemporal dynamics: the need for an innovative approach in mountain hazard risk management. Natural Hazards 68 (3):1217-1241 Papathoma-Köhle M, Zischg A, Fuchs S, Glade T, Keiler M (2015) Loss estimation for landslides in mountain areas - An integrated toolbox for vulnerability assessment and damage documentation. Environmental Modelling and Software 63:156-169 Totschnig R, Fuchs S (2013) Mountain torrents: quantifying vulnerability and assessing uncertainties. Engineering Geology 155:31-44

A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography

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

Yang, Xiaogang; De Carlo, Francesco; Phatak, Charudatta

This paper presents an algorithm to calibrate the center-of-rotation for X-ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential forreducing or removingother artifacts caused by instrument instability, detector non-linearity,etc. An open-source toolbox, which integratesmore » the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.« less

ESA Atmospheric Toolbox

NASA Astrophysics Data System (ADS)

Niemeijer, Sander

2017-04-01

The ESA Atmospheric Toolbox (BEAT) is one of the ESA Sentinel Toolboxes. It consists of a set of software components to read, analyze, and visualize a wide range of atmospheric data products. In addition to the upcoming Sentinel-5P mission it supports a wide range of other atmospheric data products, including those of previous ESA missions, ESA Third Party missions, Copernicus Atmosphere Monitoring Service (CAMS), ground based data, etc. The toolbox consists of three main components that are called CODA, HARP and VISAN. CODA provides interfaces for direct reading of data from earth observation data files. These interfaces consist of command line applications, libraries, direct interfaces to scientific applications (IDL and MATLAB), and direct interfaces to programming languages (C, Fortran, Python, and Java). CODA provides a single interface to access data in a wide variety of data formats, including ASCII, binary, XML, netCDF, HDF4, HDF5, CDF, GRIB, RINEX, and SP3. HARP is a toolkit for reading, processing and inter-comparing satellite remote sensing data, model data, in-situ data, and ground based remote sensing data. The main goal of HARP is to assist in the inter-comparison of datasets. By appropriately chaining calls to HARP command line tools one can pre-process datasets such that two datasets that need to be compared end up having the same temporal/spatial grid, same data format/structure, and same physical unit. The toolkit comes with its own data format conventions, the HARP format, which is based on netcdf/HDF. Ingestion routines (based on CODA) allow conversion from a wide variety of atmospheric data products to this common format. In addition, the toolbox provides a wide range of operations to perform conversions on the data such as unit conversions, quantity conversions (e.g. number density to volume mixing ratios), regridding, vertical smoothing using averaging kernels, collocation of two datasets, etc. VISAN is a cross-platform visualization and analysis application for atmospheric data and can be used to visualize and analyze the data that you retrieve using the CODA and HARP interfaces. The application uses the Python language as the means through which you provide commands to the application. The Python interfaces for CODA and HARP are included so you can directly ingest product data from within VISAN. Powerful visualization functionality for 2D plots and geographical plots in VISAN will allow you to directly visualize the ingested data. All components from the ESA Atmospheric Toolbox are Open Source and freely available. Software packages can be downloaded from the BEAT website: http://stcorp.nl/beat/

FACET – a “Flexible Artifact Correction and Evaluation Toolbox” for concurrently recorded EEG/fMRI data

PubMed Central

2013-01-01

Background In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings. Results FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230–239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720–737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices. Conclusion The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches. PMID:24206927

A generic open-source toolbox to help long term irrigation monitoring for integrated water management in semi-arid Mediterranean areas.

NASA Astrophysics Data System (ADS)

Le Page, Michel; Gosset, Cindy; Oueslati, Ines; Calvez, Roger; Zribi, Mehrez; Lili Chabaane, Zohra

2016-04-01

In semi arid areas, irrigated plains are often the major consumer of water well beyond other water demands. Traditionally fed by surface water, irrigation has massively shifted to a more reliable resource: groundwater. This shift occurred in the late thirty years has also provoked an extension and intensification of irrigation, often translated into impressive groundwater table decreases. Integrated water management needs a systematic and robust way to estimate the water demands by the agricultural sector. We propose a generic toolbox based on the FAO-56 method and the Crop Coefficient/NDVI approach used in Remote Sensing. The toolbox can be separated in three main areas: 1) It facilitates the preparation of different input datasets: download, domain extraction, homogenization of formats, or spatial interpolation. 2) A collection of algorithms based on the analysis of NDVI time series is proposed: Separation of irrigated vs non-irrigated area, a simplified annual land cover classification, Crop Coefficient, Fraction Cover and Efficient Rainfall. 3) Synthesis against points or areas produces the output data at the desired spatial and temporal resolution for Integrated Water Modeling or data analysis and comparison. The toolbox has been used in order to build a WEAP21 model of the Merguellil basin in Tunisia for the period of 2000-2014. Different meteorological forcings were easily used and compared: WFDEI, AGRI4CAST, MED-CORDEX. A local rain gauges database was used to produce a daily rainfall gridded dataset. MODIS MOD13Q1 (16 days, 250m) data was used to produce the NDVI derived datasets (Kc, Fc, RainEff). Punctual evapotranspiration was compared to actual measurements obtained by flux towers on wheat and barley showing good agreements on a daily basis (r2=0.77). Finally, the comparison to monthly statistics of three irrigated commands was performed over 4 years. This late comparison showed a bad agreement which led us to suppose two things: First, the simple approach of (Evapotranspiration minus Efficient Rainfall) to estimate Irrigation at the monthly time step is not pertinent because only a subset of the irrigated commands is actually irrigated. Hence, a higher spatial resolution of remote sensing imagery is needed. Second, in this particular area, farmers have a different rationale about rainfall and irrigation water needs. Those two aspects need to be further investigated. The toolbox has proven to be an interesting tool to integrate different sources of data, efficiently process them and easily produce input data for the WEAP1 model on a long term range. Yet some new challenges have been raised.

Toolbox for Urban Mobility Simulation: High Resolution Population Dynamics for Global Cities

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Lu, W.; Liu, C.; Thakur, G.; Karthik, R.

2015-12-01

In this rapidly urbanizing world, unprecedented rate of population growth is not only mirrored by increasing demand for energy, food, water, and other natural resources, but has detrimental impacts on environmental and human security. Transportation simulations are frequently used for mobility assessment in urban planning, traffic operation, and emergency management. Previous research, involving purely analytical techniques to simulations capturing behavior, has investigated questions and scenarios regarding the relationships among energy, emissions, air quality, and transportation. Primary limitations of past attempts have been availability of input data, useful "energy and behavior focused" models, validation data, and adequate computational capability that allows adequate understanding of the interdependencies of our transportation system. With increasing availability and quality of traditional and crowdsourced data, we have utilized the OpenStreetMap roads network, and has integrated high resolution population data with traffic simulation to create a Toolbox for Urban Mobility Simulations (TUMS) at global scale. TUMS consists of three major components: data processing, traffic simulation models, and Internet-based visualizations. It integrates OpenStreetMap, LandScanTM population, and other open data (Census Transportation Planning Products, National household Travel Survey, etc.) to generate both normal traffic operation and emergency evacuation scenarios. TUMS integrates TRANSIMS and MITSIM as traffic simulation engines, which are open-source and widely-accepted for scalable traffic simulations. Consistent data and simulation platform allows quick adaption to various geographic areas that has been demonstrated for multiple cities across the world. We are combining the strengths of geospatial data sciences, high performance simulations, transportation planning, and emissions, vehicle and energy technology development to design and develop a simulation framework to assist decision makers at all levels - local, state, regional, and federal. Using Cleveland, Tennessee as an example, in this presentation, we illustrate how emerging cities could easily assess future land use scenario driven impacts on energy and environment utilizing such a capability.

A versatile software package for inter-subject correlation based analyses of fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

2014-01-01

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/

A versatile software package for inter-subject correlation based analyses of fMRI

PubMed Central

Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

2014-01-01

In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/ PMID:24550818

FISSA: A neuropil decontamination toolbox for calcium imaging signals.

PubMed

Keemink, Sander W; Lowe, Scott C; Pakan, Janelle M P; Dylda, Evelyn; van Rossum, Mark C W; Rochefort, Nathalie L

2018-02-22

In vivo calcium imaging has become a method of choice to image neuronal population activity throughout the nervous system. These experiments generate large sequences of images. Their analysis is computationally intensive and typically involves motion correction, image segmentation into regions of interest (ROIs), and extraction of fluorescence traces from each ROI. Out of focus fluorescence from surrounding neuropil and other cells can strongly contaminate the signal assigned to a given ROI. In this study, we introduce the FISSA toolbox (Fast Image Signal Separation Analysis) for neuropil decontamination. Given pre-defined ROIs, the FISSA toolbox automatically extracts the surrounding local neuropil and performs blind-source separation with non-negative matrix factorization. Using both simulated and in vivo data, we show that this toolbox performs similarly or better than existing published methods. FISSA requires only little RAM, and allows for fast processing of large datasets even on a standard laptop. The FISSA toolbox is available in Python, with an option for MATLAB format outputs, and can easily be integrated into existing workflows. It is available from Github and the standard Python repositories.

Evaluating a 2D image-based computerized approach for measuring riverine pebble roundness

NASA Astrophysics Data System (ADS)

Cassel, Mathieu; Piégay, Hervé; Lavé, Jérôme; Vaudor, Lise; Hadmoko Sri, Danang; Wibiwo Budi, Sandy; Lavigne, Franck

2018-06-01

The geometrical characteristics of pebbles are important features to study transport pathways, sedimentary history, depositional environments, abrasion processes or to target sediment sources. Both the shape and roundness of pebbles can be described by a still growing number of metrics in 2D and 3D or by visual charts. Despite new developments, existing tools remain proprietary and no pebble roundness toolbox has been available widely within the scientific community. The toolbox developed by Roussillon et al. (2009) automatically computes the size, shape and roundness indexes of pebbles from their 2D maximal projection plans. Using a digital camera, this toolbox operates using 2D pictures taken of pebbles placed on a one square meter red board, allowing data collection to be quickly and efficiently acquired at a large scale. Now that the toolbox is freely available for download,

Operational aspects of asynchronous filtering for improved flood forecasting

NASA Astrophysics Data System (ADS)

Rakovec, Oldrich; Weerts, Albrecht; Sumihar, Julius; Uijlenhoet, Remko

2014-05-01

Hydrological forecasts can be made more reliable and less uncertain by recursively improving initial conditions. A common way of improving the initial conditions is to make use of data assimilation (DA), a feedback mechanism or update methodology which merges model estimates with available real world observations. The traditional implementation of the Ensemble Kalman Filter (EnKF; e.g. Evensen, 2009) is synchronous, commonly named a three dimensional (3-D) assimilation, which means that all assimilated observations correspond to the time of update. Asynchronous DA, also called four dimensional (4-D) assimilation, refers to an updating methodology, in which observations being assimilated into the model originate from times different to the time of update (Evensen, 2009; Sakov 2010). This study investigates how the capabilities of the DA procedure can be improved by applying alternative Kalman-type methods, e.g., the Asynchronous Ensemble Kalman Filter (AEnKF). The AEnKF assimilates observations with smaller computational costs than the original EnKF, which is beneficial for operational purposes. The results of discharge assimilation into a grid-based hydrological model for the Upper Ourthe catchment in Belgian Ardennes show that including past predictions and observations in the AEnKF improves the model forecasts as compared to the traditional EnKF. Additionally we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for an improved operational forecasting, which is evaluated using several validation measures. In the current study we employed the HBV-96 model built within a recently developed open source modelling environment OpenStreams (2013). The advantage of using OpenStreams (2013) is that it enables direct communication with OpenDA (2013), an open source data assimilation toolbox. OpenDA provides a number of algorithms for model calibration and assimilation and is suitable to be connected to any kind of environmental model. This setup is embedded in the Delft Flood Early Warning System (Delft-FEWS, Werner et al., 2013) for making all simulations and forecast runs and handling of all hydrological and meteorological data. References: Evensen, G. (2009), Data Assimilation: The Ensemble Kalman Filter, Springer, doi:10.1007/978-3-642-03711-5. OpenDA (2013), The OpenDA data-assimilation toolbox, www.openda.org, (last access: 1 November 2013). OpenStreams (2013), OpenStreams, www.openstreams.nl, (last access: 1 November 2013). Sakov, P., G. Evensen, and L. Bertino (2010), Asynchronous data assimilation with the EnKF, Tellus, Series A: Dynamic Meteorology and Oceanography, 62(1), 24-29, doi:10.1111/j.1600-0870.2009.00417.x. Werner, M., J. Schellekens, P. Gijsbers, M. van Dijk, O. van den Akker, and K. Heynert (2013), The Delft-FEWS flow forecasting system, Environ. Mod. & Soft., 40(0), 65-77, doi: http://dx.doi.org/10.1016/j.envsoft.2012.07.010.

ObsPy: A Python Toolbox for Seismology - Recent Developments and Applications

NASA Astrophysics Data System (ADS)

Megies, T.; Krischer, L.; Barsch, R.; Sales de Andrade, E.; Beyreuther, M.

2014-12-01

ObsPy (http://www.obspy.org) is a community-driven, open-source project dedicated to building a bridge for seismology into the scientific Python ecosystem. It offersa) read and write support for essentially all commonly used waveform, station, and event metadata file formats with a unified interface,b) a comprehensive signal processing toolbox tuned to the needs of seismologists,c) integrated access to all large data centers, web services and databases, andd) convenient wrappers to legacy codes like libtau and evalresp.Python, currently the most popular language for teaching introductory computer science courses at top-ranked U.S. departments, is a full-blown programming language with the flexibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. Together with packages like NumPy, SciPy, Matplotlib, IPython, Pandas, lxml, and PyQt, ObsPy enables the construction of complete workflows in Python. These vary from reading locally stored data or requesting data from one or more different data centers through to signal analysis and data processing and on to visualizations in GUI and web applications, output of modified/derived data and the creation of publication-quality figures.ObsPy enjoys a large world-wide rate of adoption in the community. Applications successfully using it include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. All functionality is extensively documented and the ObsPy tutorial and gallery give a good impression of the wide range of possible use cases.We will present the basic features of ObsPy, new developments and applications, and a roadmap for the near future and discuss the sustainability of our open-source development model.

ObsPy: A Python toolbox for seismology - Sustainability, New Features, and Applications

NASA Astrophysics Data System (ADS)

Krischer, L.; Megies, T.; Sales de Andrade, E.; Barsch, R.; MacCarthy, J.

2016-12-01

ObsPy (https://www.obspy.org) is a community-driven, open-source project dedicated to offer a bridge for seismology into the scientific Python ecosystem. Amongst other things, it provides Read and write support for essentially every commonly used data format in seismology with a unified interface. This includes waveform data as well as station and event meta information. A signal processing toolbox tuned to the specific needs of seismologists. Integrated access to the largest data centers, web services, and databases. Wrappers around third party codes like libmseed and evalresp. Using ObsPy enables users to take advantage of the vast scientific ecosystem that has developed around Python. In contrast to many other programming languages and tools, Python is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often must be translated to stable and production ready environments, especially in the age of big data. ObsPy has seen constant development for more than six years and enjoys a large rate of adoption in the seismological community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it. We will present a short overview of the capabilities of ObsPy and point out several representative use cases and more specialized software built around ObsPy. Additionally we will discuss new and upcoming features, as well as the sustainability of open-source scientific software.

ImgLib2--generic image processing in Java.

PubMed

Pietzsch, Tobias; Preibisch, Stephan; Tomancák, Pavel; Saalfeld, Stephan

2012-11-15

ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins. ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib. Supplementary data are available at Bioinformatics Online. saalfeld@mpi-cbg.de

PANDA: a pipeline toolbox for analyzing brain diffusion images.

PubMed

Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang

2013-01-01

Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named "Pipeline for Analyzing braiN Diffusion imAges" (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies.

BiKEGG: a COBRA toolbox extension for bridging the BiGG and KEGG databases.

PubMed

Jamialahmadi, Oveis; Motamedian, Ehsan; Hashemi-Najafabadi, Sameereh

2016-10-18

Development of an interface tool between the Biochemical, Genetic and Genomic (BiGG) and KEGG databases is necessary for simultaneous access to the features of both databases. For this purpose, we present the BiKEGG toolbox, an open source COBRA toolbox extension providing a set of functions to infer the reaction correspondences between the KEGG reaction identifiers and those in the BiGG knowledgebase using a combination of manual verification and computational methods. Inferred reaction correspondences using this approach are supported by evidence from the literature, which provides a higher number of reconciled reactions between these two databases compared to the MetaNetX and MetRxn databases. This set of equivalent reactions is then used to automatically superimpose the predicted fluxes using COBRA methods on classical KEGG pathway maps or to create a customized metabolic map based on the KEGG global metabolic pathway, and to find the corresponding reactions in BiGG based on the genome annotation of an organism in the KEGG database. Customized metabolic maps can be created for a set of pathways of interest, for the whole KEGG global map or exclusively for all pathways for which there exists at least one flux carrying reaction. This flexibility in visualization enables BiKEGG to indicate reaction directionality as well as to visualize the reaction fluxes for different static or dynamic conditions in an animated manner. BiKEGG allows the user to export (1) the output visualized metabolic maps to various standard image formats or save them as a video or animated GIF file, and (2) the equivalent reactions for an organism as an Excel spreadsheet.

FracPaQ: a MATLAB™ Toolbox for the Quantification of Fracture Patterns

NASA Astrophysics Data System (ADS)

Healy, D.; Rizzo, R. E.; Cornwell, D. G.; Timms, N.; Farrell, N. J.; Watkins, H.; Gomez-Rivas, E.; Smith, M.

2016-12-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying the fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The method presented is inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. Planned future releases will incorporate multi-scale analyses based on a wavelet method to look for scale transitions, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern.

PANDA: a pipeline toolbox for analyzing brain diffusion images

PubMed Central

Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang

2013-01-01

Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named “Pipeline for Analyzing braiN Diffusion imAges” (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies. PMID:23439846

A new technique for quantifying symmetry and opening angles in quartz c-axis pole figures: Implications for interpreting the kinematic and thermal properties of rocks

NASA Astrophysics Data System (ADS)

Hunter, N. J. R.; Weinberg, R. F.; Wilson, C. J. L.; Law, R. D.

2018-07-01

Variations in flow kinematics influence the type of crystallographic preferred orientations (CPOs) in plastically deformed quartz, yet we currently lack a robust means of quantifying the diagnostic symmetries that develop in the c-axis (0001) pole figure. In this contribution, we demonstrate how the symmetry of common c-axis topologies may be quantified by analysing the intensity distribution across a line transect of the pole figure margin. A symmetry value (S) measures the relative difference in intensities between marginal girdle maxima in the pole figure, and thus the degree to which the pole figure defines orthorhombic or monoclinic end member symmetries. This provides a semi-quantitative depiction of whether the rocks underwent coaxial or non-coaxial flow, respectively, and may subsequently be used to quantify other topological properties, such as the opening angle of girdle maxima. The open source Matlab® toolbox MTEX is used to quantify pole figure symmetries in quartzite samples from the Main Central Thrust (NW Himalaya) and the Moine Thrust (NW Scotland).

Automatic analysis of online image data for law enforcement agencies by concept detection and instance search

NASA Astrophysics Data System (ADS)

de Boer, Maaike H. T.; Bouma, Henri; Kruithof, Maarten C.; ter Haar, Frank B.; Fischer, Noëlle M.; Hagendoorn, Laurens K.; Joosten, Bart; Raaijmakers, Stephan

2017-10-01

The information available on-line and off-line, from open as well as from private sources, is growing at an exponential rate and places an increasing demand on the limited resources of Law Enforcement Agencies (LEAs). The absence of appropriate tools and techniques to collect, process, and analyze the volumes of complex and heterogeneous data has created a severe information overload. If a solution is not found, the impact on law enforcement will be dramatic, e.g. because important evidence is missed or the investigation time is too long. Furthermore, there is an uneven level of capabilities to deal with the large volumes of complex and heterogeneous data that come from multiple open and private sources at national level across the EU, which hinders cooperation and information sharing. Consequently, there is a pertinent need to develop tools, systems and processes which expedite online investigations. In this paper, we describe a suite of analysis tools to identify and localize generic concepts, instances of objects and logos in images, which constitutes a significant portion of everyday law enforcement data. We describe how incremental learning based on only a few examples and large-scale indexing are addressed in both concept detection and instance search. Our search technology allows querying of the database by visual examples and by keywords. Our tools are packaged in a Docker container to guarantee easy deployment on a system and our tools exploit possibilities provided by open source toolboxes, contributing to the technical autonomy of LEAs.

MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.

PubMed

Mantoan, Alice; Pizzolato, Claudio; Sartori, Massimo; Sawacha, Zimi; Cobelli, Claudio; Reggiani, Monica

2015-01-01

Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust tools for the pre-processing of experimental movement data for their use in neuromusculoskeletal modeling software. This paper presents MOtoNMS (matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications), a toolbox freely available to the community, that aims to fill this lack. MOtoNMS processes experimental data from different motion analysis devices and generates input data for neuromusculoskeletal modeling and simulation software, such as OpenSim and CEINMS (Calibrated EMG-Informed NMS Modelling Toolbox). MOtoNMS implements commonly required processing steps and its generic architecture simplifies the integration of new user-defined processing components. MOtoNMS allows users to setup their laboratory configurations and processing procedures through user-friendly graphical interfaces, without requiring advanced computer skills. Finally, configuration choices can be stored enabling the full reproduction of the processing steps. MOtoNMS is released under GNU General Public License and it is available at the SimTK website and from the GitHub repository. Motion data collected at four institutions demonstrate that, despite differences in laboratory instrumentation and procedures, MOtoNMS succeeds in processing data and producing consistent inputs for OpenSim and CEINMS. MOtoNMS fills the gap between motion analysis and neuromusculoskeletal modeling and simulation. Its support to several devices, a complete implementation of the pre-processing procedures, its simple extensibility, the available user interfaces, and its free availability can boost the translation of neuromusculoskeletal methods in daily and clinical practice.

Evol and ProDy for bridging protein sequence evolution and structural dynamics.

PubMed

Bakan, Ahmet; Dutta, Anindita; Mao, Wenzhi; Liu, Ying; Chennubhotla, Chakra; Lezon, Timothy R; Bahar, Ivet

2014-09-15

Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics. ProDy and Evol are open-source and freely available under MIT License from http://prody.csb.pitt.edu/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An open architecture for hybrid force-visual servo control of robotic manipulators in unstructured environments

NASA Astrophysics Data System (ADS)

Hassanzadeh, Iraj; Janabi-Sharifi, Farrokh

2005-12-01

In this paper, a new open architecture for visual servo control tasks is illustrated. A Puma-560 robotic manipulator is used to prove the concept. This design enables doing hybrid forcehisual servo control in an unstructured environment in different modes. Also, it can be controlled through Internet in teleoperation mode using a haptic device. Our proposed structure includes two major parts, hardware and software. In terms of hardware, it consists of a master (host) computer, a slave (target) computer, a Puma 560 manipulator, a CCD camera, a force sensor and a haptic device. There are five DAQ cards, interfacing Puma 560 and a slave computer. An open architecture package is developed using Matlab (R), Simulink (R) and XPC target toolbox. This package has the Hardware-In-the-Loop (HIL) property, i.e., enables one to readily implement different configurations of force, visual or hybrid control in real time. The implementation includes the following stages. First of all, retrofitting of puma was carried out. Then a modular joint controller for Puma 560 was realized using Simulink (R). Force sensor driver and force control implementation were written, using sjknction blocks of Simulink (R). Visual images were captured through Image Acquisition Toolbox of Matlab (R), and processed using Image Processing Toolbox. A haptic device interface was also written in Simulink (R). Thus, this setup could be readily reconfigured and accommodate any other robotic manipulator and/or other sensors without the trouble of the external issues relevant to the control, interface and software, while providing flexibility in components modification.

A Toolbox to Improve Algorithms for Insulin-Dosing Decision Support

PubMed Central

Donsa, K.; Plank, J.; Schaupp, L.; Mader, J. K.; Truskaller, T.; Tschapeller, B.; Höll, B.; Spat, S.; Pieber, T. R.

2014-01-01

Summary Background Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions. Objective To develop a toolbox for improving clinical decision-support algorithms. Methods The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) Analysis: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients. Results Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms. Conclusion These results are a first step towards individualized algorithm modifications for specific patient subgroups. PMID:25024768

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

PubMed

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Hanson, Stephen José; Haxby, James V.; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

Spatially constrained Bayesian inversion of frequency- and time-domain electromagnetic data from the Tellus projects

NASA Astrophysics Data System (ADS)

Kiyan, Duygu; Rath, Volker; Delhaye, Robert

2017-04-01

The frequency- and time-domain airborne electromagnetic (AEM) data collected under the Tellus projects of the Geological Survey of Ireland (GSI) which represent a wealth of information on the multi-dimensional electrical structure of Ireland's near-surface. Our project, which was funded by GSI under the framework of their Short Call Research Programme, aims to develop and implement inverse techniques based on various Bayesian methods for these densely sampled data. We have developed a highly flexible toolbox using Python language for the one-dimensional inversion of AEM data along the flight lines. The computational core is based on an adapted frequency- and time-domain forward modelling core derived from the well-tested open-source code AirBeo, which was developed by the CSIRO (Australia) and the AMIRA consortium. Three different inversion methods have been implemented: (i) Tikhonov-type inversion including optimal regularisation methods (Aster el al., 2012; Zhdanov, 2015), (ii) Bayesian MAP inversion in parameter and data space (e.g. Tarantola, 2005), and (iii) Full Bayesian inversion with Markov Chain Monte Carlo (Sambridge and Mosegaard, 2002; Mosegaard and Sambridge, 2002), all including different forms of spatial constraints. The methods have been tested on synthetic and field data. This contribution will introduce the toolbox and present case studies on the AEM data from the Tellus projects.

ORBKIT: A modular python toolbox for cross-platform postprocessing of quantum chemical wavefunction data.

PubMed

Hermann, Gunter; Pohl, Vincent; Tremblay, Jean Christophe; Paulus, Beate; Hege, Hans-Christian; Schild, Axel

2016-06-15

ORBKIT is a toolbox for postprocessing electronic structure calculations based on a highly modular and portable Python architecture. The program allows computing a multitude of electronic properties of molecular systems on arbitrary spatial grids from the basis set representation of its electronic wavefunction, as well as several grid-independent properties. The required data can be extracted directly from the standard output of a large number of quantum chemistry programs. ORBKIT can be used as a standalone program to determine standard quantities, for example, the electron density, molecular orbitals, and derivatives thereof. The cornerstone of ORBKIT is its modular structure. The existing basic functions can be arranged in an individual way and can be easily extended by user-written modules to determine any other derived quantity. ORBKIT offers multiple output formats that can be processed by common visualization tools (VMD, Molden, etc.). Additionally, ORBKIT possesses routines to order molecular orbitals computed at different nuclear configurations according to their electronic character and to interpolate the wavefunction between these configurations. The program is open-source under GNU-LGPLv3 license and freely available at https://github.com/orbkit/orbkit/. This article provides an overview of ORBKIT with particular focus on its capabilities and applicability, and includes several example calculations. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Sentinel-2 data exploitation with ESA's Sentinel-2 Toolbox

NASA Astrophysics Data System (ADS)

Gascon, Ferran; Ramoino, Fabrizzio; deanos, Yves-louis

2017-04-01

The Sentinel-2 Toolbox is a project kicked off by ESA in early 2014, under the umbrella of the ESA SEOM programme with the aim to provide a tool for visualizing, analysing, and processing the Sentinel-2 datasets. The toolbox is an extension of the SeNtinel Application Platform (SNAP), a project resulting from the effort of the developers of the Sentinel-1, Sentinel-2 and Sentinel-3 toolbox to provide a single common application framework suited for the mixed exploitation of SAR, high resolution optical and medium resolution optical datasets. All three development teams collaborate to drive the evolution of the common SNAP framework in a developer forum. In this triplet, the Sentinel-2 toolbox is dedicated to enhance SNAP support for high resolution optical imagery. It is a multi-mission toolbox, already providing support for Sentinel-2, RapidEye, Deimos, SPOT 1 to SPOT 5 datasets. In terms of processing algorithms, SNAP provides tools specific to the Sentinel-2 mission : • An atmospheric correction module, Sen2Cor, is integrated into the toolbox, and provides scene classification, atmospheric correction, cirrus detection and correction. The output L2A products can be opened seamlessly in the toolbox. • A multitemporal synthesis processor (L3) • A biophysical products processor (L2B) • A water processor • A deforestation detector • OTB tools integration • SNAP Engine for Cloud Exploitation along with a set of more generic tools for high resolution optical data exploitation. Together with the generic functionalities of SNAP this provides an ideal environment for designing multi-missions processing chains and producing value-added products from raw datasets. The use of SNAP is manifold and the desktop tools provides a rich application for interactive visualization, analysis and processing of data. But all tools available from SNAP can be accessed via command-line through the Graph Processing Framework (GPT), the kernel of the SNAP processing engine. This makes it a perfect candidate for driving the processing of data on servers for bulk processing.

Real-time Adaptive EEG Source Separation using Online Recursive Independent Component Analysis

PubMed Central

Hsu, Sheng-Hsiou; Mullen, Tim; Jung, Tzyy-Ping; Cauwenberghs, Gert

2016-01-01

Independent Component Analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: (a) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; (b) capability to detect and adapt to non-stationarity in 64-ch simulated EEG data; and (c) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces. PMID:26685257

Tracking the Sources of Fecal Contaminations: an Interdisciplinary Toolbox

NASA Astrophysics Data System (ADS)

Jeanneau, L.; Jarde, E.; Derrien, M.; Gruau, G.; Solecki, O.; Pourcher, A.; Marti, R.; Wéry, N.; Caprais, M.; Gourmelon, M.; Mieszkin, S.; Jadas-Hécart, A.; Communal, P.

2011-12-01

Fecal contaminations of inland and coastal waters induce risks to human health and economic losses. In order to improve water management, it is necessary to identify the sources of contamination, which implies the development of specific markers. In order to be considered as a valuable host-specific marker, one must (1) be source specific, (2) occur in high concentration in polluting matrices, (3) exhibit extra-intestinal persistence similar to fecal indicator bacteria (FIB) and (4) not grow out of the host. However, up to day no single marker has fulfilled all those criteria. Thus, it has been suggested to use a combination of markers in order to generate more reliable data. This has lead to the development of a Microbial Source Tracking (MST) toolbox including FIB and microbial and chemical specific markers in order to differentiate between human, bovine and porcine fecal contaminations. Those specific markers are, (1) genotypes of F-specific RNA bacteriophages, (2) bacterial markers belonging to the Bacteroidales (human-specific HF183, ruminant-specific Rum-2-Bac and pig-specific Pig-2-Bac markers), to the Bifidobacterium (Bifidobacterium adolescentis) and pig-specific Lactobacillus amylovorus, (3) fecal stanols and (4) caffeine. The development of this MST toolbox was composed of four steps, from the molecular scale to the watershed scale. At the molecular scale, the specificity and the concentration of those markers were studied in cattle and pig manures and in waste water treatment plant (WWTP) effluents and influents. At the microcosm scale, the transfer of bovine and porcine specific markers was investigated by rainfall simulations on agricultural plots amended with cattle or pig manure. Moreover, the relative persistence of FIB and human, porcine and bovine specific markers was investigated in freshwater and seawater microcosms inoculated with a WWTP influent, pig manure and cow manure. Finally, the aforementioned MST toolbox has been validated at the catchment scale by analysing three rivers impacted by fecal contaminations. The development and the application of this MST toolbox have highlighted (1) the specificity of the aforementioned markers, (2) their conservative transfer from soils to rivers and (3) their difference of persistence in seawater and in freshwater. Those results provide useful data in order to identify and manage fecal contaminations of superficial waters. In the case of single source contaminations, the markers provide coherent information: (1) the bovine or porcine markers were not detected in a river impacted by a WWTP effluent; (2) the occurrence of Rum-2-Bac and the distribution of stanols indicated a bovine contamination in a river flowing through cattle pasture. In the case of multiple source contaminations, the combination of markers is necessary to identify the main sources and the statistical treatment of the distribution of stanols could provide an approximation of their proportion.

Watershed Modeling Applications with the Open-Access Modular Distributed Watershed Educational Toolbox (MOD-WET) and Introductory Hydrology Textbook

NASA Astrophysics Data System (ADS)

Huning, L. S.; Margulis, S. A.

2014-12-01

Traditionally, introductory hydrology courses focus on hydrologic processes as independent or semi-independent concepts that are ultimately integrated into a watershed model near the end of the term. When an "off-the-shelf" watershed model is introduced in the curriculum, this approach can result in a potential disconnect between process-based hydrology and the inherent interconnectivity of processes within the water cycle. In order to curb this and reduce the learning curve associated with applying hydrologic concepts to complex real-world problems, we developed the open-access Modular Distributed Watershed Educational Toolbox (MOD-WET). The user-friendly, MATLAB-based toolbox contains the same physical equations for hydrological processes (i.e. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) that are presented in the companion e-textbook (http://aqua.seas.ucla.edu/margulis_intro_to_hydro_textbook.html) and taught in the classroom. The modular toolbox functions can be used by students to study individual hydrologic processes. These functions are integrated together to form a simple spatially-distributed watershed model, which reinforces a holistic understanding of how hydrologic processes are interconnected and modeled. Therefore when watershed modeling is introduced, students are already familiar with the fundamental building blocks that have been unified in the MOD-WET model. Extensive effort has been placed on the development of a highly modular and well-documented code that can be run on a personal computer within the commonly-used MATLAB environment. MOD-WET was designed to: 1) increase the qualitative and quantitative understanding of hydrological processes at the basin-scale and demonstrate how they vary with watershed properties, 2) emphasize applications of hydrologic concepts rather than computer programming, 3) elucidate the underlying physical processes that can often be obscured with a complicated "off-the-shelf" watershed model in an introductory hydrology course, and 4) reduce the learning curve associated with analyzing meaningful real-world problems. The open-access MOD-WET and e-textbook have already been successfully incorporated within our undergraduate curriculum.

Pythran: enabling static optimization of scientific Python programs

NASA Astrophysics Data System (ADS)

Guelton, Serge; Brunet, Pierrick; Amini, Mehdi; Merlini, Adrien; Corbillon, Xavier; Raynaud, Alan

2015-01-01

Pythran is an open source static compiler that turns modules written in a subset of Python language into native ones. Assuming that scientific modules do not rely much on the dynamic features of the language, it trades them for powerful, possibly inter-procedural, optimizations. These optimizations include detection of pure functions, temporary allocation removal, constant folding, Numpy ufunc fusion and parallelization, explicit thread-level parallelism through OpenMP annotations, false variable polymorphism pruning, and automatic vector instruction generation such as AVX or SSE. In addition to these compilation steps, Pythran provides a C++ runtime library that leverages the C++ STL to provide generic containers, and the Numeric Template Toolbox for Numpy support. It takes advantage of modern C++11 features such as variadic templates, type inference, move semantics and perfect forwarding, as well as classical idioms such as expression templates. Unlike the Cython approach, Pythran input code remains compatible with the Python interpreter. Output code is generally as efficient as the annotated Cython equivalent, if not more, but without the backward compatibility loss.

40 CFR 141.716 - Source toolbox components.

Code of Federal Regulations, 2011 CFR

2011-07-01

... undertake to reduce source water Cryptosporidium levels. The plan must explain how the actions are expected... Section 141.716 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Enhanced Treatment for Cryptosporidium Requirements...

40 CFR 141.716 - Source toolbox components.

Code of Federal Regulations, 2010 CFR

2010-07-01

... undertake to reduce source water Cryptosporidium levels. The plan must explain how the actions are expected... Section 141.716 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Enhanced Treatment for Cryptosporidium Requirements...

GIAnT - Generic InSAR Analysis Toolbox

NASA Astrophysics Data System (ADS)

Agram, P.; Jolivet, R.; Riel, B. V.; Simons, M.; Doin, M.; Lasserre, C.; Hetland, E. A.

2012-12-01

We present a computing framework for studying the spatio-temporal evolution of ground deformation from interferometric synthetic aperture radar (InSAR) data. Several open-source tools including Repeat Orbit Interferometry PACkage (ROI-PAC) and InSAR Scientific Computing Environment (ISCE) from NASA-JPL, and Delft Object-oriented Repeat Interferometric Software (DORIS), have enabled scientists to generate individual interferograms from raw radar data with relative ease. Numerous computational techniques and algorithms that reduce phase information from multiple interferograms to a deformation time-series have been developed and verified over the past decade. However, the sharing and direct comparison of products from multiple processing approaches has been hindered by - 1) absence of simple standards for sharing of estimated time-series products, 2) use of proprietary software tools with license restrictions and 3) the closed source nature of the exact implementation of many of these algorithms. We have developed this computing framework to address all of the above issues. We attempt to take the first steps towards creating a community software repository for InSAR time-series analysis. To date, we have implemented the short baseline subset algorithm (SBAS), NSBAS and multi-scale interferometric time-series (MInTS) in this framework and the associated source code is included in the GIAnT distribution. A number of the associated routines have been optimized for performance and scalability with large data sets. Some of the new features in our processing framework are - 1) the use of daily solutions from continuous GPS stations to correct for orbit errors, 2) the use of meteorological data sets to estimate the tropospheric delay screen and 3) a data-driven bootstrapping approach to estimate the uncertainties associated with estimated time-series products. We are currently working on incorporating tidal load corrections for individual interferograms and propagation of noise covariance models through the processing chain for robust estimation of uncertainties in the deformation estimates. We will demonstrate the ease of use of our framework with results ranging from regional scale analysis around Long Valley, CA and Parkfield, CA to continental scale analysis in Western South America. We will also present preliminary results from a new time-series approach that simultaneously estimates deformation over the complete spatial domain at all time epochs on a distributed computing platform. GIAnT has been developed entirely using open source tools and uses Python as the underlying platform. We build on the extensive numerical (NumPy) and scientific (SciPy) computing Python libraries to develop an object-oriented, flexible and modular framework for time-series InSAR applications. The toolbox is currently configured to work with outputs from ROI-PAC, ISCE and DORIS, but can easily be extended to support products from other SAR/InSAR processors. The toolbox libraries include support for hierarchical data format (HDF5) memory mapped files, parallel processing with Python's multi-processing module and support for many convex optimization solvers like CSDP, CVXOPT etc. An extensive set of routines to deal with ASCII and XML files has also been included for controlling the processing parameters.

ObsPy: Establishing and maintaining an open-source community package

NASA Astrophysics Data System (ADS)

Krischer, L.; Megies, T.; Barsch, R.

2017-12-01

Python's ecosystem evolved into one of the most powerful and productive research environment across disciplines. ObsPy (https://obspy.org) is a fully community driven, open-source project dedicated to provide a bridge for seismology into that ecosystem. It does so by offering Read and write support for essentially every commonly used data format in seismology, Integrated access to the largest data centers, web services, and real-time data streams, A powerful signal processing toolbox tuned to the specific needs of seismologists, and Utility functionality like travel time calculations, geodetic functions, and data visualizations. ObsPy has been in constant unfunded development for more than eight years and is developed and used by scientists around the world with successful applications in all branches of seismology. By now around 70 people directly contributed code to ObsPy and we aim to make it a self-sustaining community project.This contributions focusses on several meta aspects of open-source software in science, in particular how we experienced them. During the panel we would like to discuss obvious questions like long-term sustainability with very limited to no funding, insufficient computer science training in many sciences, and gaining hard scientific credits for software development, but also the following questions: How to best deal with the fact that a lot of scientific software is very specialized thus usually solves a complex problem but at the same time can only ever reach a limited pool of developers and users by virtue of it being so specialized? Therefore the "many eyes on the code" approach to develop and improve open-source software only applies in a limited fashion. An initial publication for a significant new scientific software package is fairly straightforward. How to on-board and motivate potential new contributors when they can no longer be lured by a potential co-authorship? When is spending significant time and effort on reusable scientific open-source development a reasonable choice for young researchers? The effort to go from purpose tailored code for a single application resulting in a scientific publication is significantly less compared to generalising and engineering it well enough so it can be used by others.

An integrated, open-source set of tools for urban vulnerability monitoring from Earth observation data

NASA Astrophysics Data System (ADS)

De Vecchi, Daniele; Harb, Mostapha; Dell'Acqua, Fabio; Aurelio Galeazzo, Daniel

2015-04-01

Aim: The paper introduces an integrated set of open-source tools designed to process medium and high-resolution imagery with the aim to extract vulnerability indicators [1]. Problem: In the context of risk monitoring [2], a series of vulnerability proxies can be defined, such as the extension of a built-up area or buildings regularity [3]. Different open-source C and Python libraries are already available for image processing and geospatial information (e.g. OrfeoToolbox, OpenCV and GDAL). They include basic processing tools but not vulnerability-oriented workflows. Therefore, it is of significant importance to provide end-users with a set of tools capable to return information at a higher level. Solution: The proposed set of python algorithms is a combination of low-level image processing and geospatial information handling tools along with high-level workflows. In particular, two main products are released under the GPL license: source code, developers-oriented, and a QGIS plugin. These tools were produced within the SENSUM project framework (ended December 2014) where the main focus was on earthquake and landslide risk. Further development and maintenance is guaranteed by the decision to include them in the platform designed within the FP 7 RASOR project . Conclusion: With the lack of a unified software suite for vulnerability indicators extraction, the proposed solution can provide inputs for already available models like the Global Earthquake Model. The inclusion of the proposed set of algorithms within the RASOR platforms can guarantee support and enlarge the community of end-users. Keywords: Vulnerability monitoring, remote sensing, optical imagery, open-source software tools References [1] M. Harb, D. De Vecchi, F. Dell'Acqua, "Remote sensing-based vulnerability proxies in the EU FP7 project SENSUM", Symposium on earthquake and landslide risk in Central Asia and Caucasus: exploiting remote sensing and geo-spatial information management, 29-30th January 2014, Bishkek, Kyrgyz Republic. [2] UNISDR, "Living with Risk", Geneva, Switzerland, 2004. [3] P. Bisch, E. Carvalho, H. Degree, P. Fajfar, M. Fardis, P. Franchin, M. Kreslin, A. Pecker, "Eurocode 8: Seismic Design of Buildings", Lisbon, 2011. (SENSUM: www.sensum-project.eu, grant number: 312972 ) (RASOR: www.rasor-project.eu, grant number: 606888 )

NEDE: an open-source scripting suite for developing experiments in 3D virtual environments.

PubMed

Jangraw, David C; Johri, Ansh; Gribetz, Meron; Sajda, Paul

2014-09-30

As neuroscientists endeavor to understand the brain's response to ecologically valid scenarios, many are leaving behind hyper-controlled paradigms in favor of more realistic ones. This movement has made the use of 3D rendering software an increasingly compelling option. However, mastering such software and scripting rigorous experiments requires a daunting amount of time and effort. To reduce these startup costs and make virtual environment studies more accessible to researchers, we demonstrate a naturalistic experimental design environment (NEDE) that allows experimenters to present realistic virtual stimuli while still providing tight control over the subject's experience. NEDE is a suite of open-source scripts built on the widely used Unity3D game development software, giving experimenters access to powerful rendering tools while interfacing with eye tracking and EEG, randomizing stimuli, and providing custom task prompts. Researchers using NEDE can present a dynamic 3D virtual environment in which randomized stimulus objects can be placed, allowing subjects to explore in search of these objects. NEDE interfaces with a research-grade eye tracker in real-time to maintain precise timing records and sync with EEG or other recording modalities. Python offers an alternative for experienced programmers who feel comfortable mastering and integrating the various toolboxes available. NEDE combines many of these capabilities with an easy-to-use interface and, through Unity's extensive user base, a much more substantial body of assets and tutorials. Our flexible, open-source experimental design system lowers the barrier to entry for neuroscientists interested in developing experiments in realistic virtual environments. Copyright © 2014 Elsevier B.V. All rights reserved.

ESA's Multi-mission Sentinel-1 Toolbox

NASA Astrophysics Data System (ADS)

Veci, Luis; Lu, Jun; Foumelis, Michael; Engdahl, Marcus

2017-04-01

The Sentinel-1 Toolbox is a new open source software for scientific learning, research and exploitation of the large archives of Sentinel and heritage missions. The Toolbox is based on the proven BEAM/NEST architecture inheriting all current NEST functionality including multi-mission support for most civilian satellite SAR missions. The project is funded through ESA's Scientific Exploitation of Operational Missions (SEOM). The Sentinel-1 Toolbox will strive to serve the SEOM mandate by providing leading-edge software to the science and application users in support of ESA's operational SAR mission as well as by educating and growing a SAR user community. The Toolbox consists of a collection of processing tools, data product readers and writers and a display and analysis application. A common architecture for all Sentinel Toolboxes is being jointly developed by Brockmann Consult, Array Systems Computing and C-S called the Sentinel Application Platform (SNAP). The SNAP architecture is ideal for Earth Observation processing and analysis due the following technological innovations: Extensibility, Portability, Modular Rich Client Platform, Generic EO Data Abstraction, Tiled Memory Management, and a Graph Processing Framework. The project has developed new tools for working with Sentinel-1 data in particular for working with the new Interferometric TOPSAR mode. TOPSAR Complex Coregistration and a complete Interferometric processing chain has been implemented for Sentinel-1 TOPSAR data. To accomplish this, a coregistration following the Spectral Diversity[4] method has been developed as well as special azimuth handling in the coherence, interferogram and spectral filter operators. The Toolbox includes reading of L0, L1 and L2 products in SAFE format, calibration and de-noising, slice product assembling, TOPSAR deburst and sub-swath merging, terrain flattening radiometric normalization, and visualization for L2 OCN products. The Toolbox also provides several new tools for exploitation of polarimetric data including speckle filters, decompositions, and classifiers. The Toolbox will also include tools for large data stacks, supervised and unsupervised classification, improved vector handling and change detection. Architectural improvements such as smart memory configuration, task queuing, and optimizations for complex data will provide better support and performance for very large products and stacks.In addition, a Cloud Exploitation Platform Extension (CEP) has been developed to add the capability to smoothly utilize a cloud computing platform where EO data repositories and high performance processing capabilities are available. The extension to the SENTINEL Application Platform would facilitate entry into cloud processing services for supporting bulk processing on high performance clusters. Since December 2016, the COMET-LiCS InSAR portal (http://comet.nerc.ac.uk/COMET-LiCS-portal/) has been live, delivering interferograms and coherence estimates over the entire Alpine-Himalayan belt. The portal already contains tens of thousands of products, which can be browsed in a user-friendly portal, and downloaded for free by the general public. For our processing, we use the facilities at the Climate and Environmental Monitoring from Space (CEMS). Here we have large storage and processing facilities to our disposal, and a complete duplicate of the Sentinel-1 archive is maintained. This greatly simplifies the infrastructure we had to develop for automated processing of large areas. Here we will give an overview of the current status of the processing system, as well as discuss future plans. We will cover the infrastructure we developed to automatically produce interferograms and its challenges, and the processing strategy for time series analysis. We will outline the objectives of the system in the near and distant future, and a roadmap for its continued development. Finally, we will highlight some of the scientific results and projects linked to the system.

EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing.

PubMed

Delorme, Arnaud; Mullen, Tim; Kothe, Christian; Akalin Acar, Zeynep; Bigdely-Shamlo, Nima; Vankov, Andrey; Makeig, Scott

2011-01-01

We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments.

Open Source GIS based integrated watershed management

NASA Astrophysics Data System (ADS)

Byrne, J. M.; Lindsay, J.; Berg, A. A.

2013-12-01

Optimal land and water management to address future and current resource stresses and allocation challenges requires the development of state-of-the-art geomatics and hydrological modelling tools. Future hydrological modelling tools should be of high resolution, process based with real-time capability to assess changing resource issues critical to short, medium and long-term enviromental management. The objective here is to merge two renowned, well published resource modeling programs to create an source toolbox for integrated land and water management applications. This work will facilitate a much increased efficiency in land and water resource security, management and planning. Following an 'open-source' philosophy, the tools will be computer platform independent with source code freely available, maximizing knowledge transfer and the global value of the proposed research. The envisioned set of water resource management tools will be housed within 'Whitebox Geospatial Analysis Tools'. Whitebox, is an open-source geographical information system (GIS) developed by Dr. John Lindsay at the University of Guelph. The emphasis of the Whitebox project has been to develop a user-friendly interface for advanced spatial analysis in environmental applications. The plugin architecture of the software is ideal for the tight-integration of spatially distributed models and spatial analysis algorithms such as those contained within the GENESYS suite. Open-source development extends knowledge and technology transfer to a broad range of end-users and builds Canadian capability to address complex resource management problems with better tools and expertise for managers in Canada and around the world. GENESYS (Generate Earth Systems Science input) is an innovative, efficient, high-resolution hydro- and agro-meteorological model for complex terrain watersheds developed under the direction of Dr. James Byrne. GENESYS is an outstanding research and applications tool to address challenging resource management issues in industry, government and nongovernmental agencies. Current research and analysis tools were developed to manage meteorological, climatological, and land and water resource data efficiently at high resolution in space and time. The deliverable for this work is a Whitebox-GENESYS open-source resource management capacity with routines for GIS based watershed management including water in agriculture and food production. We are adding urban water management routines through GENESYS in 2013-15 with an engineering PhD candidate. Both Whitebox-GAT and GENESYS are already well-established tools. The proposed research will combine these products to create an open-source geomatics based water resource management tool that is revolutionary in both capacity and availability to a wide array of Canadian and global users

The ESA Scientific Exploitation of Operational Missions element, first results

NASA Astrophysics Data System (ADS)

Desnos, Yves-Louis; Regner, Peter; Delwart, Steven; Benveniste, Jerome; Engdahl, Marcus; Mathieu, Pierre-Philippe; Gascon, Ferran; Donlon, Craig; Davidson, Malcolm; Pinnock, Simon; Foumelis, Michael; Ramoino, Fabrizio

2016-04-01

SEOM is a program element within the fourth period (2013-2017) of ESA's Earth Observation Envelope Programme (http://seom.esa.int/). The prime objective is to federate, support and expand the international research community that the ERS, ENVISAT and the Envelope programmes have built up over the last 25 years. It aims to further strengthen the leadership of the European Earth Observation research community by enabling them to extensively exploit future European operational EO missions. SEOM will enable the science community to address new scientific research that are opened by free and open access to data from operational EO missions. Based on community-wide recommendations for actions on key research issues, gathered through a series of international thematic workshops and scientific user consultation meetings, a work plan is established and is approved every year by ESA Members States. During 2015 SEOM, Science users consultation workshops have been organized for Sentinel1/3/5P ( Fringe, S3 Symposium and Atmospheric science respectively) , new R&D studies for scientific exploitation of the Sentinels have been launched ( S3 for Science SAR Altimetry and Ocean Color , S2 for Science,) , open-source multi-mission scientific toolboxes have been launched (in particular the SNAP/S1-2-3 Toolbox). In addition two advanced international training courses have been organized in Europe to exploit the new S1-A and S2-A data for Land and Ocean remote sensing (over 120 participants from 25 countries) as well as activities for promoting the first scientific results ( e.g. Chili Earthquake) . In addition the First EO Open Science 2.0 was organised at ESA in October 2015 with 225 participants from 31 countries bringing together young EO scientists and data scientists. During the conference precursor activities in EO Open Science and Innovation were presented, while developing a Roadmap preparing for future ESA scientific exploitation activities. Within the conference, the first EO Hackathon event took place bringing together volunteered programmers with the developers of SNAP. An interactive "Jam" session was also held that discussed and scoped challenging scientific and societal issues (e.g. climate change, quality of life and air quality). The status and first results from these SEOM projects will be presented and an outlook for upcoming SEOM studies and events in 2016 will be given.

NATbox: a network analysis toolbox in R.

PubMed

Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

2009-10-08

There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments. NATbox is especially suited for interdisciplinary researchers and biologists with minimal programming experience and would like to use systems biology approaches without delving into the algorithmic aspects. The GUI provides appropriate parameter recommendations for the various menu options including default parameter choices for the user. NATbox can also prove to be a useful demonstration and teaching tool in graduate and undergraduate course in systems biology. It has been tested successfully under Windows and Linux operating systems. The source code along with installation instructions and accompanying tutorial can be found at http://bioinformatics.ualr.edu/natboxWiki/index.php/Main_Page.

Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS).

PubMed

Lajnef, Tarek; O'Reilly, Christian; Combrisson, Etienne; Chaibi, Sahbi; Eichenlaub, Jean-Baptiste; Ruby, Perrine M; Aguera, Pierre-Emmanuel; Samet, Mounir; Kachouri, Abdennaceur; Frenette, Sonia; Carrier, Julie; Jerbi, Karim

2017-01-01

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Reilly et al., 2014). Importantly, the obtained scores were compared to alternative methods that were previously tested on the same database. With respect to spindle detection, our method achieved higher performance than most of the alternative methods. This was corroborated with statistic tests that took into account both sensitivity and precision (i.e., Matthew's coefficient of correlation (MCC), F1, Cohen κ). Our proposed method has been made available to the community via an open-source tool named Spinky (for spindle and K-complex detection). Thanks to a GUI implementation and access to Matlab and Python resources, Spinky is expected to contribute to an open-science approach that will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in both healthy and patient populations.

Diagnostic index: an open-source tool to classify TMJ OA condyles

NASA Astrophysics Data System (ADS)

Paniagua, Beatriz; Pascal, Laura; Prieto, Juan; Vimort, Jean Baptiste; Gomes, Liliane; Yatabe, Marilia; Ruellas, Antonio Carlos; Budin, Francois; Pieper, Steve; Styner, Martin; Benavides, Erika; Cevidanes, Lucia

2017-03-01

Osteoarthritis (OA) of temporomandibular joints (TMJ) occurs in about 40% of the patients who present TMJ disorders. Despite its prevalence, OA diagnosis and treatment remain controversial since there are no clear symptoms of the disease, especially in early stages. Quantitative tools based on 3D imaging of the TMJ condyle have the potential to help characterize TMJ OA changes. The goals of the tools proposed in this study are to ultimately develop robust imaging markers for diagnosis and assessment of treatment efficacy. This work proposes to identify differences among asymptomatic controls and different clinical phenotypes of TMJ OA by means of Statistical Shape Modeling (SSM), obtained via clinical expert consensus. From three different grouping schemes (with 3, 5 and 7 groups), our best results reveal that that the majority (74.5%) of the classifications occur in agreement with the groups assigned by consensus between our clinical experts. Our findings suggest the existence of different disease-based phenotypic morphologies in TMJ OA. Our preliminary findings with statistical shape modeling based biomarkers may provide a quantitative staging of the disease. The methodology used in this study is included in an open source image analysis toolbox, to ensure reproducibility and appropriate distribution and dissemination of the solution proposed.

Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data

NASA Astrophysics Data System (ADS)

Teodoro, Ana C.; Araujo, Ricardo

2016-01-01

The use of unmanned aerial vehicles (UAVs) for remote sensing applications is becoming more frequent. However, this type of information can result in several software problems related to the huge amount of data available. Object-based image analysis (OBIA) has proven to be superior to pixel-based analysis for very high-resolution images. The main objective of this work was to explore the potentialities of the OBIA methods available in two different open source software applications, Spring and OTB/Monteverdi, in order to generate an urban land cover map. An orthomosaic derived from UAVs was considered, 10 different regions of interest were selected, and two different approaches were followed. The first one (Spring) uses the region growing segmentation algorithm followed by the Bhattacharya classifier. The second approach (OTB/Monteverdi) uses the mean shift segmentation algorithm followed by the support vector machine (SVM) classifier. Two strategies were followed: four classes were considered using Spring and thereafter seven classes were considered for OTB/Monteverdi. The SVM classifier produces slightly better results and presents a shorter processing time. However, the poor spectral resolution of the data (only RGB bands) is an important factor that limits the performance of the classifiers applied.

The Air Sensor Citizen Science Toolbox: A Collaboration in Community Air Quality Monitoring and Mapping

EPA Science Inventory

Research in Action: Collect air quality data to characterize near-road/near-source hotspots; Determine potential impact on nearby residences & roadways; Case study of successful use of such data; Relationship between distance to roadways and industrial sources, exposure to...

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

EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing

PubMed Central

Delorme, Arnaud; Mullen, Tim; Kothe, Christian; Akalin Acar, Zeynep; Bigdely-Shamlo, Nima; Vankov, Andrey; Makeig, Scott

2011-01-01

We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments. PMID:21687590

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

FracPaQ: a MATLAB™ toolbox for the quantification of fracture patterns

NASA Astrophysics Data System (ADS)

Healy, David; Rizzo, Roberto; Farrell, Natalie; Watkins, Hannah; Cornwell, David; Gomez-Rivas, Enrique; Timms, Nick

2017-04-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying crack and fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The methods presented are inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. New features in this release include multi-scale analyses based on a wavelet method to look for scale transitions, support for multi-colour traces in the input file processed as separate fracture sets, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern expressed as a 2nd rank crack tensor.

ObsPy - A Python Toolbox for Seismology - and Applications

NASA Astrophysics Data System (ADS)

Krischer, L.; Megies, T.; Barsch, R.; MacCarthy, J.; Lecocq, T.; Koymans, M. R.; Carothers, L.; Eulenfeld, T.; Reyes, C. G.; Falco, N.; Sales de Andrade, E.

2017-12-01

Recent years witnessed the evolution of Python's ecosystem into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community driven, open-source project dedicated to provide a bridge for seismology into that ecosystem. It is a Python toolbox offering: Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, SC3ML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than eight years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. Newest features include: Full interoperability of SEED and StationXML/Inventory objects Access to the Nominal Response Library (NRL) for easy and quick creation of station metadata from scratch Support for the IRIS Federated Catalog Service Improved performance of the EarthWorm client Several improvements to MiniSEED read/write module Improved plotting capabilities for PPSD (spectrograms, PSD of discrete frequencies over time, ..) Support for.. Reading ArcLink Inventory XML Reading Reftek data format Writing SeisComp3 ML (SC3ML) Writing StationTXT format This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases and show-case some projects that are based on ObsPy, e.g.: seismo-live.org Seedlink-plotter MSNoise, and others..

Contributions to the Nutrient Toolbox: Identifying Drivers, Nutrient Sources, and Attribution of Exceedances

EPA Science Inventory

Nutrients are a leading cause of impairments in the United States, and as a result tools are needed to identify drivers of nutrients and response variables (such as chlorophyll a), nutrient sources, and identify causes of exceedances of water quality thresholds. This presentatio...

Aerospace Toolbox--a flight vehicle design, analysis, simulation, and software development environment II: an in-depth overview

NASA Astrophysics Data System (ADS)

Christian, Paul M.

2002-07-01

This paper presents a demonstrated approach to significantly reduce the cost and schedule of non real-time modeling and simulation, real-time HWIL simulation, and embedded code development. The tool and the methodology presented capitalize on a paradigm that has become a standard operating procedure in the automotive industry. The tool described is known as the Aerospace Toolbox, and it is based on the MathWorks Matlab/Simulink framework, which is a COTS application. Extrapolation of automotive industry data and initial applications in the aerospace industry show that the use of the Aerospace Toolbox can make significant contributions in the quest by NASA and other government agencies to meet aggressive cost reduction goals in development programs. The part I of this paper provided a detailed description of the GUI based Aerospace Toolbox and how it is used in every step of a development program; from quick prototyping of concept developments that leverage built-in point of departure simulations through to detailed design, analysis, and testing. Some of the attributes addressed included its versatility in modeling 3 to 6 degrees of freedom, its library of flight test validated library of models (including physics, environments, hardware, and error sources), and its built-in Monte Carlo capability. Other topics that were covered in part I included flight vehicle models and algorithms, and the covariance analysis package, Navigation System Covariance Analysis Tools (NavSCAT). Part II of this series will cover a more in-depth look at the analysis and simulation capability and provide an update on the toolbox enhancements. It will also address how the Toolbox can be used as a design hub for Internet based collaborative engineering tools such as NASA's Intelligent Synthesis Environment (ISE) and Lockheed Martin's Interactive Missile Design Environment (IMD).

ICT: isotope correction toolbox.

PubMed

Jungreuthmayer, Christian; Neubauer, Stefan; Mairinger, Teresa; Zanghellini, Jürgen; Hann, Stephan

2016-01-01

Isotope tracer experiments are an invaluable technique to analyze and study the metabolism of biological systems. However, isotope labeling experiments are often affected by naturally abundant isotopes especially in cases where mass spectrometric methods make use of derivatization. The correction of these additive interferences--in particular for complex isotopic systems--is numerically challenging and still an emerging field of research. When positional information is generated via collision-induced dissociation, even more complex calculations for isotopic interference correction are necessary. So far, no freely available tools can handle tandem mass spectrometry data. We present isotope correction toolbox, a program that corrects tandem mass isotopomer data from tandem mass spectrometry experiments. Isotope correction toolbox is written in the multi-platform programming language Perl and, therefore, can be used on all commonly available computer platforms. Source code and documentation can be freely obtained under the Artistic License or the GNU General Public License from: https://github.com/jungreuc/isotope_correction_toolbox/ {christian.jungreuthmayer@boku.ac.at,juergen.zanghellini@boku.ac.at} Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A new software for deformation source optimization, the Bayesian Earthquake Analysis Tool (BEAT)

NASA Astrophysics Data System (ADS)

Vasyura-Bathke, H.; Dutta, R.; Jonsson, S.; Mai, P. M.

2017-12-01

Modern studies of crustal deformation and the related source estimation, including magmatic and tectonic sources, increasingly use non-linear optimization strategies to estimate geometric and/or kinematic source parameters and often consider both jointly, geodetic and seismic data. Bayesian inference is increasingly being used for estimating posterior distributions of deformation source model parameters, given measured/estimated/assumed data and model uncertainties. For instance, some studies consider uncertainties of a layered medium and propagate these into source parameter uncertainties, while others use informative priors to reduce the model parameter space. In addition, innovative sampling algorithms have been developed to efficiently explore the high-dimensional parameter spaces. Compared to earlier studies, these improvements have resulted in overall more robust source model parameter estimates that include uncertainties. However, the computational burden of these methods is high and estimation codes are rarely made available along with the published results. Even if the codes are accessible, it is usually challenging to assemble them into a single optimization framework as they are typically coded in different programing languages. Therefore, further progress and future applications of these methods/codes are hampered, while reproducibility and validation of results has become essentially impossible. In the spirit of providing open-access and modular codes to facilitate progress and reproducible research in deformation source estimations, we undertook the effort of developing BEAT, a python package that comprises all the above-mentioned features in one single programing environment. The package builds on the pyrocko seismological toolbox (www.pyrocko.org), and uses the pymc3 module for Bayesian statistical model fitting. BEAT is an open-source package (https://github.com/hvasbath/beat), and we encourage and solicit contributions to the project. Here, we present our strategy for developing BEAT and show application examples; especially the effect of including the model prediction uncertainty of the velocity model in following source optimizations: full moment tensor, Mogi source, moderate strike-slip earth-quake.

Advanced functional network analysis in the geosciences: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

2013-04-01

Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

SedFoam-2.0: a 3-D two-phase flow numerical model for sediment transport

NASA Astrophysics Data System (ADS)

Chauchat, Julien; Cheng, Zhen; Nagel, Tim; Bonamy, Cyrille; Hsu, Tian-Jian

2017-11-01

In this paper, a three-dimensional two-phase flow solver, SedFoam-2.0, is presented for sediment transport applications. The solver is extended from twoPhaseEulerFoam available in the 2.1.0 release of the open-source CFD (computational fluid dynamics) toolbox OpenFOAM. In this approach the sediment phase is modeled as a continuum, and constitutive laws have to be prescribed for the sediment stresses. In the proposed solver, two different intergranular stress models are implemented: the kinetic theory of granular flows and the dense granular flow rheology μ(I). For the fluid stress, laminar or turbulent flow regimes can be simulated and three different turbulence models are available for sediment transport: a simple mixing length model (one-dimensional configuration only), a k - ɛ, and a k - ω model. The numerical implementation is demonstrated on four test cases: sedimentation of suspended particles, laminar bed load, sheet flow, and scour at an apron. These test cases illustrate the capabilities of SedFoam-2.0 to deal with complex turbulent sediment transport problems with different combinations of intergranular stress and turbulence models.

Computational Testing for Automated Preprocessing 2: Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG

PubMed Central

Cowley, Benjamin U.; Korpela, Jussi

2018-01-01

Existing tools for the preprocessing of EEG data provide a large choice of methods to suitably prepare and analyse a given dataset. Yet it remains a challenge for the average user to integrate methods for batch processing of the increasingly large datasets of modern research, and compare methods to choose an optimal approach across the many possible parameter configurations. Additionally, many tools still require a high degree of manual decision making for, e.g., the classification of artifacts in channels, epochs or segments. This introduces extra subjectivity, is slow, and is not reproducible. Batching and well-designed automation can help to regularize EEG preprocessing, and thus reduce human effort, subjectivity, and consequent error. The Computational Testing for Automated Preprocessing (CTAP) toolbox facilitates: (i) batch processing that is easy for experts and novices alike; (ii) testing and comparison of preprocessing methods. Here we demonstrate the application of CTAP to high-resolution EEG data in three modes of use. First, a linear processing pipeline with mostly default parameters illustrates ease-of-use for naive users. Second, a branching pipeline illustrates CTAP's support for comparison of competing methods. Third, a pipeline with built-in parameter-sweeping illustrates CTAP's capability to support data-driven method parameterization. CTAP extends the existing functions and data structure from the well-known EEGLAB toolbox, based on Matlab, and produces extensive quality control outputs. CTAP is available under MIT open-source licence from https://github.com/bwrc/ctap. PMID:29692705

Computational Testing for Automated Preprocessing 2: Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG.

PubMed

Cowley, Benjamin U; Korpela, Jussi

2018-01-01

Existing tools for the preprocessing of EEG data provide a large choice of methods to suitably prepare and analyse a given dataset. Yet it remains a challenge for the average user to integrate methods for batch processing of the increasingly large datasets of modern research, and compare methods to choose an optimal approach across the many possible parameter configurations. Additionally, many tools still require a high degree of manual decision making for, e.g., the classification of artifacts in channels, epochs or segments. This introduces extra subjectivity, is slow, and is not reproducible. Batching and well-designed automation can help to regularize EEG preprocessing, and thus reduce human effort, subjectivity, and consequent error. The Computational Testing for Automated Preprocessing (CTAP) toolbox facilitates: (i) batch processing that is easy for experts and novices alike; (ii) testing and comparison of preprocessing methods. Here we demonstrate the application of CTAP to high-resolution EEG data in three modes of use. First, a linear processing pipeline with mostly default parameters illustrates ease-of-use for naive users. Second, a branching pipeline illustrates CTAP's support for comparison of competing methods. Third, a pipeline with built-in parameter-sweeping illustrates CTAP's capability to support data-driven method parameterization. CTAP extends the existing functions and data structure from the well-known EEGLAB toolbox, based on Matlab, and produces extensive quality control outputs. CTAP is available under MIT open-source licence from https://github.com/bwrc/ctap.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets

NASA Astrophysics Data System (ADS)

Hosseini, Kasra; Sigloch, Karin

2017-10-01

We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control - routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS).

BCILAB: a platform for brain-computer interface development

NASA Astrophysics Data System (ADS)

Kothe, Christian Andreas; Makeig, Scott

2013-10-01

Objective. The past two decades have seen dramatic progress in our ability to model brain signals recorded by electroencephalography, functional near-infrared spectroscopy, etc., and to derive real-time estimates of user cognitive state, response, or intent for a variety of purposes: to restore communication by the severely disabled, to effect brain-actuated control and, more recently, to augment human-computer interaction. Continuing these advances, largely achieved through increases in computational power and methods, requires software tools to streamline the creation, testing, evaluation and deployment of new data analysis methods. Approach. Here we present BCILAB, an open-source MATLAB-based toolbox built to address the need for the development and testing of brain-computer interface (BCI) methods by providing an organized collection of over 100 pre-implemented methods and method variants, an easily extensible framework for the rapid prototyping of new methods, and a highly automated framework for systematic testing and evaluation of new implementations. Main results. To validate and illustrate the use of the framework, we present two sample analyses of publicly available data sets from recent BCI competitions and from a rapid serial visual presentation task. We demonstrate the straightforward use of BCILAB to obtain results compatible with the current BCI literature. Significance. The aim of the BCILAB toolbox is to provide the BCI community a powerful toolkit for methods research and evaluation, thereby helping to accelerate the pace of innovation in the field, while complementing the existing spectrum of tools for real-time BCI experimentation, deployment and use.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

A comprehensive validation toolbox for regional ocean models - Outline, implementation and application to the Baltic Sea

NASA Astrophysics Data System (ADS)

Jandt, Simon; Laagemaa, Priidik; Janssen, Frank

2014-05-01

The systematic and objective comparison between output from a numerical ocean model and a set of observations, called validation in the context of this presentation, is a beneficial activity at several stages, starting from early steps in model development and ending at the quality control of model based products delivered to customers. Even though the importance of this kind of validation work is widely acknowledged it is often not among the most popular tasks in ocean modelling. In order to ease the validation work a comprehensive toolbox has been developed in the framework of the MyOcean-2 project. The objective of this toolbox is to carry out validation integrating different data sources, e.g. time-series at stations, vertical profiles, surface fields or along track satellite data, with one single program call. The validation toolbox, implemented in MATLAB, features all parts of the validation process - ranging from read-in procedures of datasets to the graphical and numerical output of statistical metrics of the comparison. The basic idea is to have only one well-defined validation schedule for all applications, in which all parts of the validation process are executed. Each part, e.g. read-in procedures, forms a module in which all available functions of this particular part are collected. The interface between the functions, the module and the validation schedule is highly standardized. Functions of a module are set up for certain validation tasks, new functions can be implemented into the appropriate module without affecting the functionality of the toolbox. The functions are assigned for each validation task in user specific settings, which are externally stored in so-called namelists and gather all information of the used datasets as well as paths and metadata. In the framework of the MyOcean-2 project the toolbox is frequently used to validate the forecast products of the Baltic Sea Marine Forecasting Centre. Hereby the performance of any new product version is compared with the previous version. Although, the toolbox is mainly tested for the Baltic Sea yet, it can easily be adapted to different datasets and parameters, regardless of the geographic region. In this presentation the usability of the toolbox is demonstrated along with several results of the validation process.

TTLEM: Open access tool for building numerically accurate landscape evolution models in MATLAB

NASA Astrophysics Data System (ADS)

Campforts, Benjamin; Schwanghart, Wolfgang; Govers, Gerard

2017-04-01

Despite a growing interest in LEMs, accuracy assessment of the numerical methods they are based on has received little attention. Here, we present TTLEM which is an open access landscape evolution package designed to develop and test your own scenarios and hypothesises. TTLEM uses a higher order flux-limiting finite-volume method to simulate river incision and tectonic displacement. We show that this scheme significantly influences the evolution of simulated landscapes and the spatial and temporal variability of erosion rates. Moreover, it allows the simulation of lateral tectonic displacement on a fixed grid. Through the use of a simple GUI the software produces visible output of evolving landscapes through model run time. In this contribution, we illustrate numerical landscape evolution through a set of movies spanning different spatial and temporal scales. We focus on the erosional domain and use both spatially constant and variable input values for uplift, lateral tectonic shortening, erodibility and precipitation. Moreover, we illustrate the relevance of a stochastic approach for realistic hillslope response modelling. TTLEM is a fully open source software package, written in MATLAB and based on the TopoToolbox platform (topotoolbox.wordpress.com). Installation instructions can be found on this website and the therefore designed GitHub repository.

Near-optimal experimental design for model selection in systems biology.

PubMed

Busetto, Alberto Giovanni; Hauser, Alain; Krummenacher, Gabriel; Sunnåker, Mikael; Dimopoulos, Sotiris; Ong, Cheng Soon; Stelling, Jörg; Buhmann, Joachim M

2013-10-15

Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Toolbox 'NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org).

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

Condenser: a statistical aggregation tool for multi-sample quantitative proteomic data from Matrix Science Mascot Distiller™.

PubMed

Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan

2014-05-30

We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.

BurnMan: Towards a multidisciplinary toolkit for reproducible deep Earth science

NASA Astrophysics Data System (ADS)

Myhill, R.; Cottaar, S.; Heister, T.; Rose, I.; Unterborn, C. T.; Dannberg, J.; Martin-Short, R.

2016-12-01

BurnMan (www.burnman.org) is an open-source toolbox to compute thermodynamic and thermoelastic properties as a function of pressure and temperature using published mineral physical parameters and equations-of-state. The framework is user-friendly, written in Python, and modular, allowing the user to implement their own equations of state, endmember and solution model libraries, geotherms, and averaging schemes. Here we introduce various new modules, which can be used to: Fit thermodynamic variables to data from high pressure static and shock wave experiments, Calculate equilibrium assemblages given a bulk composition, pressure and temperature, Calculate chemical potentials and oxygen fugacities for given assemblages Compute 3D synthetic seismic models using output from geodynamic models and compare these results with global seismic tomographic models, Create input files for synthetic seismogram codes. Users can contribute scripts that reproduce the results from peer-reviewed articles and practical demonstrations (e.g. Cottaar et al., 2014).

EasyDIAg: A tool for easy determination of interrater agreement.

PubMed

Holle, Henning; Rein, Robert

2015-09-01

Reliable measurements are fundamental for the empirical sciences. In observational research, measurements often consist of observers categorizing behavior into nominal-scaled units. Since the categorization is the outcome of a complex judgment process, it is important to evaluate the extent to which these judgments are reproducible, by having multiple observers independently rate the same behavior. A challenge in determining interrater agreement for timed-event sequential data is to develop clear objective criteria to determine whether two raters' judgments relate to the same event (the linking problem). Furthermore, many studies presently report only raw agreement indices, without considering the degree to which agreement can occur by chance alone. Here, we present a novel, free, and open-source toolbox (EasyDIAg) designed to assist researchers with the linking problem, while also providing chance-corrected estimates of interrater agreement. Additional tools are included to facilitate the development of coding schemes and rater training.

Automated Analysis of Stateflow Models

NASA Technical Reports Server (NTRS)

Bourbouh, Hamza; Garoche, Pierre-Loic; Garion, Christophe; Gurfinkel, Arie; Kahsaia, Temesghen; Thirioux, Xavier

2017-01-01

Stateflow is a widely used modeling framework for embedded and cyber physical systems where control software interacts with physical processes. In this work, we present a framework a fully automated safety verification technique for Stateflow models. Our approach is two-folded: (i) we faithfully compile Stateflow models into hierarchical state machines, and (ii) we use automated logic-based verification engine to decide the validity of safety properties. The starting point of our approach is a denotational semantics of State flow. We propose a compilation process using continuation-passing style (CPS) denotational semantics. Our compilation technique preserves the structural and modal behavior of the system. The overall approach is implemented as an open source toolbox that can be integrated into the existing Mathworks Simulink Stateflow modeling framework. We present preliminary experimental evaluations that illustrate the effectiveness of our approach in code generation and safety verification of industrial scale Stateflow models.

GCE Data Toolbox for MATLAB - a software framework for automating environmental data processing, quality control and documentation

NASA Astrophysics Data System (ADS)

Sheldon, W.; Chamblee, J.; Cary, R. H.

2013-12-01

Environmental scientists are under increasing pressure from funding agencies and journal publishers to release quality-controlled data in a timely manner, as well as to produce comprehensive metadata for submitting data to long-term archives (e.g. DataONE, Dryad and BCO-DMO). At the same time, the volume of digital data that researchers collect and manage is increasing rapidly due to advances in high frequency electronic data collection from flux towers, instrumented moorings and sensor networks. However, few pre-built software tools are available to meet these data management needs, and those tools that do exist typically focus on part of the data management lifecycle or one class of data. The GCE Data Toolbox has proven to be both a generalized and effective software solution for environmental data management in the Long Term Ecological Research Network (LTER). This open source MATLAB software library, developed by the Georgia Coastal Ecosystems LTER program, integrates metadata capture, creation and management with data processing, quality control and analysis to support the entire data lifecycle. Raw data can be imported directly from common data logger formats (e.g. SeaBird, Campbell Scientific, YSI, Hobo), as well as delimited text files, MATLAB files and relational database queries. Basic metadata are derived from the data source itself (e.g. parsed from file headers) and by value inspection, and then augmented using editable metadata templates containing boilerplate documentation, attribute descriptors, code definitions and quality control rules. Data and metadata content, quality control rules and qualifier flags are then managed together in a robust data structure that supports database functionality and ensures data validity throughout processing. A growing suite of metadata-aware editing, quality control, analysis and synthesis tools are provided with the software to support managing data using graphical forms and command-line functions, as well as developing automated workflows for unattended processing. Finalized data and structured metadata can be exported in a wide variety of text and MATLAB formats or uploaded to a relational database for long-term archiving and distribution. The GCE Data Toolbox can be used as a complete, light-weight solution for environmental data and metadata management, but it can also be used in conjunction with other cyber infrastructure to provide a more comprehensive solution. For example, newly acquired data can be retrieved from a Data Turbine or Campbell LoggerNet Database server for quality control and processing, then transformed to CUAHSI Observations Data Model format and uploaded to a HydroServer for distribution through the CUAHSI Hydrologic Information System. The GCE Data Toolbox can also be leveraged in analytical workflows developed using Kepler or other systems that support MATLAB integration or tool chaining. This software can therefore be leveraged in many ways to help researchers manage, analyze and distribute the data they collect.

The ESA scientific exploitation element results and outlook

NASA Astrophysics Data System (ADS)

Desnos, Yves-louis; Regner, Peter; Delwart, Steven; Benveniste, Jerome; Engdahl, Marcus; Donlon, Craig; Mathieu, Pierre-Philippe; Fernandez, Diego; Gascon, Ferran; Zehner, Claus; Davidson, Malcolm; Goryl, Philippe; Koetz, Benjamin; Pinnock, Simon

2017-04-01

The Scientific Exploitation of Operational Missions (SEOM) element of ESA's fourth Earth Observation Envelope Programme (EOEP4) prime objective is to federate, support and expand the international research community built up over the last 25 years exploiting ESA's EO missions. SEOM enables the science community to address new scientific research areas that are opened by the free and open access to data from operational EO missions. Based on community-wide recommendations, gathered through a series of international thematic workshops and scientific user consultation meetings, key research studies have been launched over the last years to further exploit data from the Sentinels (http://seom.esa.int/). During 2016 several Science users consultation workshops have been organized, new results from scientific studies have been published and open-source multi-mission scientific toolboxes have been distributed (SNAP 80000 users from 190 countries). In addition the first ESA Massive Open Online Courses on Climate from space have been deployed (20000 participants) and the second EO Open Science conference was organized at ESA in September 2016 bringing together young EO scientists and data scientists. The new EOEP5 Exploitation element approved in 2016 and starting in 2017 is taking stock of all precursor activities in EO Open Science and Innovation and in particular a workplan for ESA scientific exploitation activities has been presented to Member States taking full benefit of the latest information and communication technology. The results and highlights from current scientific exploitation activities will be presented and an outlook on the upcoming activities under the new EOEP5 exploitation element will be given.

Aerospace Toolbox---a flight vehicle design, analysis, simulation ,and software development environment: I. An introduction and tutorial

NASA Astrophysics Data System (ADS)

Christian, Paul M.; Wells, Randy

2001-09-01

This paper presents a demonstrated approach to significantly reduce the cost and schedule of non real-time modeling and simulation, real-time HWIL simulation, and embedded code development. The tool and the methodology presented capitalize on a paradigm that has become a standard operating procedure in the automotive industry. The tool described is known as the Aerospace Toolbox, and it is based on the MathWorks Matlab/Simulink framework, which is a COTS application. Extrapolation of automotive industry data and initial applications in the aerospace industry show that the use of the Aerospace Toolbox can make significant contributions in the quest by NASA and other government agencies to meet aggressive cost reduction goals in development programs. The part I of this paper provides a detailed description of the GUI based Aerospace Toolbox and how it is used in every step of a development program; from quick prototyping of concept developments that leverage built-in point of departure simulations through to detailed design, analysis, and testing. Some of the attributes addressed include its versatility in modeling 3 to 6 degrees of freedom, its library of flight test validated library of models (including physics, environments, hardware, and error sources), and its built-in Monte Carlo capability. Other topics to be covered in this part include flight vehicle models and algorithms, and the covariance analysis package, Navigation System Covariance Analysis Tools (NavSCAT). Part II of this paper, to be published at a later date, will conclude with a description of how the Aerospace Toolbox is an integral part of developing embedded code directly from the simulation models by using the Mathworks Real Time Workshop and optimization tools. It will also address how the Toolbox can be used as a design hub for Internet based collaborative engineering tools such as NASA's Intelligent Synthesis Environment (ISE) and Lockheed Martin's Interactive Missile Design Environment (IMD).

A LAN Toolbox.

ERIC Educational Resources Information Center

Eddison, Elizabeth B.

1989-01-01

This bibliographic essay reviews sources that aid in the planning and management aspects of local area networks. Areas covered include system components; basic vocabularies; planning issues, including needs assessment, peripheral sharing alternatives and costs; and management issues, including purchasing, operating systems, installation, network…

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

Galperin, Michael

The progress of experimental techniques at the nanoscale in the last decade made optical measurements in current-carrying nanojunctions a reality, thus indicating the emergence of a new field of research coined optoelectronics. Optical spectroscopy of open nonequilibrium systems is a natural meeting point for (at least) two research areas: nonlinear optical spectroscopy and quantum transport, each with its own theoretical toolbox. We review recent progress in the field comparing theoretical treatments of optical response in nanojunctions as is accepted in nonlinear spectroscopy and quantum transport communities. A unified theoretical description of spectroscopy in nanojunctions is presented. Here, we argue thatmore » theoretical approaches of the quantum transport community (and in particular, the Green function based considerations) yield a convenient tool for optoelectronics when the radiation field is treated classically, and that differences between the toolboxes may become critical when studying the quantum radiation field in junctions.« less

Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG

PubMed Central

Mullen, Tim R.; Kothe, Christian A.E.; Chi, Mike; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Jung, Tzyy-Ping; Cauwenberghs, Gert

2015-01-01

Goal We present and evaluate a wearable high-density dry electrode EEG system and an open-source software framework for online neuroimaging and state classification. Methods The system integrates a 64-channel dry EEG form-factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in 9 subjects using the dry EEG system. Results Simulations yielded high accuracy (AUC=0.97±0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity (sdDTF) was significantly above chance with similar performance (AUC) for cLORETA (0.74±0.09) and LCMV (0.72±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74±0.16) but significantly better for LCMV (0.82±0.12). Conclusion We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. Significance This paper is the first validated application of these methods to 64-channel dry EEG. The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes. PMID:26415149

Proba-V Mission Exploitation Platform

NASA Astrophysics Data System (ADS)

Goor, E.

2017-12-01

VITO and partners developed the Proba-V Mission Exploitation Platform (MEP) as an end-to-end solution to drastically improve the exploitation of the Proba-V (an EC Copernicus contributing mission) EO-data archive, the past mission SPOT-VEGETATION and derived vegetation parameters by researchers, service providers (e.g. the EC Copernicus Global Land Service) and end-users. The analysis of time series of data (PB range) is addressed, as well as the large scale on-demand processing of near real-time data on a powerful and scalable processing environment. New features are still developed, but the platform is yet fully operational since November 2016 and offers A time series viewer (browser web client and API), showing the evolution of Proba-V bands and derived vegetation parameters for any country, region, pixel or polygon defined by the user. Full-resolution viewing services for the complete data archive. On-demand processing chains on a powerfull Hadoop/Spark backend. Virtual Machines can be requested by users with access to the complete data archive mentioned above and pre-configured tools to work with this data, e.g. various toolboxes and support for R and Python. This allows users to immediately work with the data without having to install tools or download data, but as well to design, debug and test applications on the platform. Jupyter Notebooks is available with some examples python and R projects worked out to show the potential of the data. Today the platform is already used by several international third party projects to perform R&D activities on the data, and to develop/host data analysis toolboxes. From the Proba-V MEP, access to other data sources such as Sentinel-2 and landsat data is also addressed. Selected components of the MEP are also deployed on public cloud infrastructures in various R&D projects. Users can make use of powerful Web based tools and can self-manage virtual machines to perform their work on the infrastructure at VITO with access to the complete data archive. To realise this, private cloud technology (openStack) is used and a distributed processing environment is built based on Hadoop. The Hadoop ecosystem offers a lot of technologies (Spark, Yarn, Accumulo) which we integrate with several open-source components (e.g. Geotrellis).

CEINMS: a toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks

PubMed Central

Pizzolato, Claudio; Lloyd, David G.; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F.; Fregly, Benjamin J.; Reggiani, Monica

2015-01-01

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. PMID:26522621

Fecal pollution source tracking toolbox for identification, evaluation and characterization of fecal contamination in receiving urban surface waters and groundwater.

PubMed

Tran, Ngoc Han; Gin, Karina Yew-Hoong; Ngo, Huu Hao

2015-12-15

The quality of surface waters/groundwater of a geographical region can be affected by anthropogenic activities, land use patterns and fecal pollution sources from humans and animals. Therefore, the development of an efficient fecal pollution source tracking toolbox for identifying the origin of the fecal pollution sources in surface waters/groundwater is especially helpful for improving management efforts and remediation actions of water resources in a more cost-effective and efficient manner. This review summarizes the updated knowledge on the use of fecal pollution source tracking markers for detecting, evaluating and characterizing fecal pollution sources in receiving surface waters and groundwater. The suitability of using chemical markers (i.e. fecal sterols, fluorescent whitening agents, pharmaceuticals and personal care products, and artificial sweeteners) and/or microbial markers (e.g. F+RNA coliphages, enteric viruses, and host-specific anaerobic bacterial 16S rDNA genetic markers) for tracking fecal pollution sources in receiving water bodies is discussed. In addition, this review also provides a comprehensive approach, which is based on the detection ratios (DR), detection frequencies (DF), and fate of potential microbial and chemical markers. DR and DF are considered as the key criteria for selecting appropriate markers for identifying and evaluating the impacts of fecal contamination in surface waters/groundwater. Copyright © 2015 Elsevier B.V. All rights reserved.

Proba-V Mission Exploitation Platform

NASA Astrophysics Data System (ADS)

Goor, Erwin; Dries, Jeroen

2017-04-01

VITO and partners developed the Proba-V Mission Exploitation Platform (MEP) as an end-to-end solution to drastically improve the exploitation of the Proba-V (a Copernicus contributing mission) EO-data archive (http://proba-v.vgt.vito.be/), the past mission SPOT-VEGETATION and derived vegetation parameters by researchers, service providers and end-users. The analysis of time series of data (+1PB) is addressed, as well as the large scale on-demand processing of near real-time data on a powerful and scalable processing environment. Furthermore data from the Copernicus Global Land Service is in scope of the platform. From November 2015 an operational Proba-V MEP environment, as an ESA operation service, is gradually deployed at the VITO data center with direct access to the complete data archive. Since autumn 2016 the platform is operational and yet several applications are released to the users, e.g. - A time series viewer, showing the evolution of Proba-V bands and derived vegetation parameters from the Copernicus Global Land Service for any area of interest. - Full-resolution viewing services for the complete data archive. - On-demand processing chains on a powerfull Hadoop/Spark backend e.g. for the calculation of N-daily composites. - Virtual Machines can be provided with access to the data archive and tools to work with this data, e.g. various toolboxes (GDAL, QGIS, GrassGIS, SNAP toolbox, …) and support for R and Python. This allows users to immediately work with the data without having to install tools or download data, but as well to design, debug and test applications on the platform. - A prototype of jupyter Notebooks is available with some examples worked out to show the potential of the data. Today the platform is used by several third party projects to perform R&D activities on the data, and to develop/host data analysis toolboxes. In parallel the platform is further improved and extended. From the MEP PROBA-V, access to Sentinel-2 and landsat data will be available as well soon. Users can make use of powerful Web based tools and can self-manage virtual machines to perform their work on the infrastructure at VITO with access to the complete data archive. To realise this, private cloud technology (openStack) is used and a distributed processing environment is built based on Hadoop. The Hadoop ecosystem offers a lot of technologies (Spark, Yarn, Accumulo, etc.) which we integrate with several open-source components (e.g. Geotrellis). The impact of this MEP on the user community will be high and will completely change the way of working with the data and hence open the large time series to a larger community of users. The presentation will address these benefits for the users and discuss on the technical challenges in implementing this MEP. Furthermore demonstrations will be done. Platform URL: https://proba-v-mep.esa.int/

Sentinel-3 SAR Altimetry Toolbox - Scientific Exploitation of Operational Missions (SEOM) Program Element

NASA Astrophysics Data System (ADS)

Benveniste, Jérôme; Lucas, Bruno; Dinardo, Salvatore

2014-05-01

The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage pioneered by ERS-1, ERS-2, Envisat and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the Sentinel-3 series is planned for launch in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission's data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales, the French Space Agency), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the Sentinel-3 SAR Altimetry Toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The ITT is expected to be launched in Q1 2014 and have the 1st version available before the launch of Sentinel-3.

Sentinel-3 SAR Altimetry Toolbox - Scientific Exploitation of Operational Missions (SEOM) Program Element

NASA Astrophysics Data System (ADS)

Benveniste, Jérôme; Dinardo, Salvatore; Lucas, Bruno Manuel

The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage pioneered by ERS-1, ERS-2, Envisat and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the Sentinel-3 series is planned for launch in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission’s data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d’Etudes Spatiales, the French Space Agency), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also “use cases”, with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the Sentinel-3 SAR Altimetry Toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific “use-cases” for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The ITT is expected to be launched in Q1 2014 and have the 1st version available before the launch of Sentinel-3.

Sentinel-3 SAR Altimetry Toolbox

NASA Astrophysics Data System (ADS)

Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

2015-04-01

The prime objective of the SEOM (Scientific Exploitation of Operational Missions) element is to federate, support and expand the large international research community that the ERS, ENVISAT and the Envelope programmes have build up over the last 20 years for the future European operational Earth Observation missions, the Sentinels. Sentinel-3 builds directly on a proven heritage of ERS-2 and Envisat, and CryoSat-2, with a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter (SRAL) that provides measurements at a resolution of ~300m in SAR mode along track. Sentinel-3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The first of the two Sentinels is expected to be launched in early 2015. The current universal altimetry toolbox is BRAT (Basic Radar Altimetry Toolbox) which can read all previous and current altimetry mission's data, but it does not have the capabilities to read the upcoming Sentinel-3 L1 and L2 products. ESA will endeavour to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats, the BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the Sentinel-3 SAR Altimetry Toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Kick Off is expected to be happen in Q1 2015 and have the 1st version available before the launch of Sentinel-3.

Validation of an Actuator Line Model Coupled to a Dynamic Stall Model for Pitching Motions Characteristic to Vertical Axis Turbines

NASA Astrophysics Data System (ADS)

Mendoza, Victor; Bachant, Peter; Wosnik, Martin; Goude, Anders

2016-09-01

Vertical axis wind turbines (VAWT) can be used to extract renewable energy from wind flows. A simpler design, low cost of maintenance, and the ability to accept flow from all directions perpendicular to the rotor axis are some of the most important advantages over conventional horizontal axis wind turbines (HAWT). However, VAWT encounter complex and unsteady fluid dynamics, which present significant modeling challenges. One of the most relevant phenomena is dynamic stall, which is caused by the unsteady variation of angle of attack throughout the blade rotation, and is the focus of the present study. Dynamic stall is usually used as a passive control for VAWT operating conditions, hence the importance of predicting its effects. In this study, a coupled model is implemented with the open-source CFD toolbox OpenFOAM for solving the Navier-Stokes equations, where an actuator line model and dynamic stall model are used to compute the blade loading and body force. Force coefficients obtained from the model are validated with experimental data of pitching airfoil in similar operating conditions as an H-rotor type VAWT. Numerical results show reasonable agreement with experimental data for pitching motion.

PREMER: a Tool to Infer Biological Networks.

PubMed

Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

2017-10-04

Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Martin, Dawn (Elliott); Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Improve Data Mining and Knowledge Discovery through the use of MatLab

NASA Technical Reports Server (NTRS)

Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms.

PubMed

Andreotti, Fernando; Behar, Joachim; Zaunseder, Sebastian; Oster, Julien; Clifford, Gari D

2016-05-01

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be avoided. Data, extraction algorithms and evaluation routines were released as part of the fecgsyn toolbox on Physionet under an GNU GPL open-source license. This contribution provides a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms.

Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox

EPA Science Inventory

Rainfall-derived infiltration and inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby receiving waters and can also ...

Origins and Evolution of Stomatal Development1[OPEN

PubMed Central

2017-01-01

The fossil record suggests stomata-like pores were present on the surfaces of land plants over 400 million years ago. Whether stomata arose once or whether they arose independently across newly evolving land plant lineages has long been a matter of debate. In Arabidopsis, a genetic toolbox has been identified that tightly controls stomatal development and patterning. This includes the basic helix-loop-helix (bHLH) transcription factors SPEECHLESS (SPCH), MUTE, FAMA, and ICE/SCREAMs (SCRMs), which promote stomatal formation. These factors are regulated via a signaling cascade, which includes mobile EPIDERMAL PATTERNING FACTOR (EPF) peptides to enforce stomatal spacing. Mosses and hornworts, the most ancient extant lineages to possess stomata, possess orthologs of these Arabidopsis (Arabidopsis thaliana) stomatal toolbox genes, and manipulation in the model bryophyte Physcomitrella patens has shown that the bHLH and EPF components are also required for moss stomatal development and patterning. This supports an ancient and tightly conserved genetic origin of stomata. Here, we review recent discoveries and, by interrogating newly available plant genomes, we advance the story of stomatal development and patterning across land plant evolution. Furthermore, we identify potential orthologs of the key toolbox genes in a hornwort, further supporting a single ancient genetic origin of stomata in the ancestor to all stomatous land plants. PMID:28356502

HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

PubMed

Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

2013-01-01

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

Wave data processing toolbox manual

USGS Publications Warehouse

Sullivan, Charlene M.; Warner, John C.; Martini, Marinna A.; Lightsom, Frances S.; Voulgaris, George; Work, Paul

2006-01-01

Researchers routinely deploy oceanographic equipment in estuaries, coastal nearshore environments, and shelf settings. These deployments usually include tripod-mounted instruments to measure a suite of physical parameters such as currents, waves, and pressure. Instruments such as the RD Instruments Acoustic Doppler Current Profiler (ADCP(tm)), the Sontek Argonaut, and the Nortek Aquadopp(tm) Profiler (AP) can measure these parameters. The data from these instruments must be processed using proprietary software unique to each instrument to convert measurements to real physical values. These processed files are then available for dissemination and scientific evaluation. For example, the proprietary processing program used to process data from the RD Instruments ADCP for wave information is called WavesMon. Depending on the length of the deployment, WavesMon will typically produce thousands of processed data files. These files are difficult to archive and further analysis of the data becomes cumbersome. More imperative is that these files alone do not include sufficient information pertinent to that deployment (metadata), which could hinder future scientific interpretation. This open-file report describes a toolbox developed to compile, archive, and disseminate the processed wave measurement data from an RD Instruments ADCP, a Sontek Argonaut, or a Nortek AP. This toolbox will be referred to as the Wave Data Processing Toolbox. The Wave Data Processing Toolbox congregates the processed files output from the proprietary software into two NetCDF files: one file contains the statistics of the burst data and the other file contains the raw burst data (additional details described below). One important advantage of this toolbox is that it converts the data into NetCDF format. Data in NetCDF format is easy to disseminate, is portable to any computer platform, and is viewable with public-domain freely-available software. Another important advantage is that a metadata structure is embedded with the data to document pertinent information regarding the deployment and the parameters used to process the data. Using this format ensures that the relevant information about how the data was collected and converted to physical units is maintained with the actual data. EPIC-standard variable names have been utilized where appropriate. These standards, developed by the NOAA Pacific Marine Environmental Laboratory (PMEL) (http://www.pmel.noaa.gov/epic/), provide a universal vernacular allowing researchers to share data without translation.

Photonics and spectroscopy in nanojunctions: a theoretical insight

DOE PAGES

Galperin, Michael

2017-04-11

The progress of experimental techniques at the nanoscale in the last decade made optical measurements in current-carrying nanojunctions a reality, thus indicating the emergence of a new field of research coined optoelectronics. Optical spectroscopy of open nonequilibrium systems is a natural meeting point for (at least) two research areas: nonlinear optical spectroscopy and quantum transport, each with its own theoretical toolbox. We review recent progress in the field comparing theoretical treatments of optical response in nanojunctions as is accepted in nonlinear spectroscopy and quantum transport communities. A unified theoretical description of spectroscopy in nanojunctions is presented. Here, we argue thatmore » theoretical approaches of the quantum transport community (and in particular, the Green function based considerations) yield a convenient tool for optoelectronics when the radiation field is treated classically, and that differences between the toolboxes may become critical when studying the quantum radiation field in junctions.« less

System/observer/controller identification toolbox

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

1992-01-01

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

CFD simulations of power coefficients for an innovative Darrieus style vertical axis wind turbine with auxiliary straight blades

NASA Astrophysics Data System (ADS)

Arpino, F.; Cortellessa, G.; Dell'Isola, M.; Scungio, M.; Focanti, V.; Profili, M.; Rotondi, M.

2017-11-01

The increasing price of fossil derivatives, global warming and energy market instabilities, have led to an increasing interest in renewable energy sources such as wind energy. Amongst the different typologies of wind generators, small scale Vertical Axis Wind Turbines (VAWT) present the greatest potential for off grid power generation at low wind speeds. In the present work, Computational Fluid Dynamic (CFD) simulations were performed in order to investigate the performance of an innovative configuration of straight-blades Darrieus-style vertical axis micro wind turbine, specifically developed for small scale energy conversion at low wind speeds. The micro turbine under investigation is composed of three pairs of airfoils, consisting of a main and auxiliary blades with different chord lengths. The simulations were made using the open source finite volume based CFD toolbox OpenFOAM, considering different turbulence models and adopting a moving mesh approach for the turbine rotor. The simulated data were reported in terms of dimensionless power coefficients for dynamic performance analysis. The results from the simulations were compared to the data obtained from experiments on a scaled model of the same VAWT configuration, conducted in a closed circuit open chamber wind tunnel facility available at the Laboratory of Industrial Measurements (LaMI) of the University of Cassino and Lazio Meridionale (UNICLAM). From the proposed analysis, it was observed that the most suitable model for the simulation of the performances of the micro turbine under investigation is the one-equation Spalart-Allmaras, even if under the conditions analysed in the present work and for TSR values higher than 1.1, some discrepancies between numerical and experimental data can be observed.

From Particles and Point Clouds to Voxel Models: High Resolution Modeling of Dynamic Landscapes in Open Source GIS

NASA Astrophysics Data System (ADS)

Mitasova, H.; Hardin, E. J.; Kratochvilova, A.; Landa, M.

2012-12-01

Multitemporal data acquired by modern mapping technologies provide unique insights into processes driving land surface dynamics. These high resolution data also offer an opportunity to improve the theoretical foundations and accuracy of process-based simulations of evolving landforms. We discuss development of new generation of visualization and analytics tools for GRASS GIS designed for 3D multitemporal data from repeated lidar surveys and from landscape process simulations. We focus on data and simulation methods that are based on point sampling of continuous fields and lead to representation of evolving surfaces as series of raster map layers or voxel models. For multitemporal lidar data we present workflows that combine open source point cloud processing tools with GRASS GIS and custom python scripts to model and analyze dynamics of coastal topography (Figure 1) and we outline development of coastal analysis toolbox. The simulations focus on particle sampling method for solving continuity equations and its application for geospatial modeling of landscape processes. In addition to water and sediment transport models, already implemented in GIS, the new capabilities under development combine OpenFOAM for wind shear stress simulation with a new module for aeolian sand transport and dune evolution simulations. Comparison of observed dynamics with the results of simulations is supported by a new, integrated 2D and 3D visualization interface that provides highly interactive and intuitive access to the redesigned and enhanced visualization tools. Several case studies will be used to illustrate the presented methods and tools and demonstrate the power of workflows built with FOSS and highlight their interoperability.Figure 1. Isosurfaces representing evolution of shoreline and a z=4.5m contour between the years 1997-2011at Cape Hatteras, NC extracted from a voxel model derived from series of lidar-based DEMs.

An open-source framework for analyzing N-electron dynamics. II. Hybrid density functional theory/configuration interaction methodology.

PubMed

Hermann, Gunter; Pohl, Vincent; Tremblay, Jean Christophe

2017-10-30

In this contribution, we extend our framework for analyzing and visualizing correlated many-electron dynamics to non-variational, highly scalable electronic structure method. Specifically, an explicitly time-dependent electronic wave packet is written as a linear combination of N-electron wave functions at the configuration interaction singles (CIS) level, which are obtained from a reference time-dependent density functional theory (TDDFT) calculation. The procedure is implemented in the open-source Python program detCI@ORBKIT, which extends the capabilities of our recently published post-processing toolbox (Hermann et al., J. Comput. Chem. 2016, 37, 1511). From the output of standard quantum chemistry packages using atom-centered Gaussian-type basis functions, the framework exploits the multideterminental structure of the hybrid TDDFT/CIS wave packet to compute fundamental one-electron quantities such as difference electronic densities, transient electronic flux densities, and transition dipole moments. The hybrid scheme is benchmarked against wave function data for the laser-driven state selective excitation in LiH. It is shown that all features of the electron dynamics are in good quantitative agreement with the higher-level method provided a judicious choice of functional is made. Broadband excitation of a medium-sized organic chromophore further demonstrates the scalability of the method. In addition, the time-dependent flux densities unravel the mechanistic details of the simulated charge migration process at a glance. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure.

PubMed

Shen, Yi; Dai, Wei; Richards, Virginia M

2015-03-01

A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. The toolbox uses an object-oriented architecture for organizing the experimental variables and computational algorithms, which provides experimenters with flexibility in experimental design and data management. Descriptions of the UML procedure and the UML Toolbox are provided, followed by toolbox use examples. Finally, guidelines and recommendations of parameter configurations are given.

SSOAP - A USEPA TOOLBOX FOR SSO ANALYSIS AND CONTROL PLANNING

EPA Science Inventory

Rainfall Derived Infiltration and Inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby streams and can also cause seriou...

DEVELOPMENT OF SANITARY SEWER OVERFLOW ANALYSIS AND PLANNING (SSOAP) TOOLBOX

EPA Science Inventory

Rainfall Derived Infiltration and Inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby streams. RDII can also cause se...

SSOAP - A TOOLBOX FOR SANITARY SEWER OVERFLOW ANALYSIS AND PLANNING

EPA Science Inventory

Rainfall Derived Infiltration and Inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby streams and can also cause serio...

SSOAP - A TOOLBOX FOR SANITARY SEWER OVERFLOW ANALYSIS AND PLANNING

EPA Science Inventory

Rainfall Derived Infiltration and Inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby streams and can also cause seriou...

pyBadlands: A framework to simulate sediment transport, landscape dynamics and basin stratigraphic evolution through space and time

PubMed Central

2018-01-01

Understanding Earth surface responses in terms of sediment dynamics to climatic variability and tectonics forcing is hindered by limited ability of current models to simulate long-term evolution of sediment transfer and associated morphological changes. This paper presents pyBadlands, an open-source python-based framework which computes over geological time (1) sediment transport from landmasses to coasts, (2) reworking of marine sediments by longshore currents and (3) development of coral reef systems. pyBadlands is cross-platform, distributed under the GPLv3 license and available on GitHub (http://github.com/badlands-model). Here, we describe the underlying physical assumptions behind the simulated processes and the main options already available in the numerical framework. Along with the source code, a list of hands-on examples is provided that illustrates the model capabilities. In addition, pre and post-processing classes have been built and are accessible as a companion toolbox which comprises a series of workflows to efficiently build, quantify and explore simulation input and output files. While the framework has been primarily designed for research, its simplicity of use and portability makes it a great tool for teaching purposes. PMID:29649301

MetNetMaker: a free and open-source tool for the creation of novel metabolic networks in SBML format.

PubMed

Forth, Thomas; McConkey, Glenn A; Westhead, David R

2010-09-15

An application has been developed to help with the creation and editing of Systems Biology Markup Language (SBML) format metabolic networks up to the organism scale. Networks are defined as a collection of Kyoto Encyclopedia of Genes and Genomes (KEGG) LIGAND reactions with an optional associated Enzyme Classification (EC) number for each reaction. Additional custom reactions can be defined by the user. Reactions within the network can be assigned flux constraints and compartmentalization is supported for each reaction in addition to the support for reactions that occur across compartment boundaries. Exported networks are fully SBML L2V4 compatible with an optional L2V1 export for compatibility with old versions of the COBRA toolbox. The software runs in the free Microsoft Access 2007 Runtime (Microsoft Inc.), which is included with the installer and works on Windows XP SP2 or better. Full source code is viewable in the full version of Access 2007 or 2010. Users must have a license to use the KEGG LIGAND database (free academic licensing is available). Please go to www.bioinformatics.leeds.ac.uk/~pytf/metnetmaker for software download, help and tutorials.

A MATLAB toolbox for the efficient estimation of the psychometric function using the updated maximum-likelihood adaptive procedure

PubMed Central

Richards, V. M.; Dai, W.

2014-01-01

A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. The toolbox uses an object-oriented architecture for organizing the experimental variables and computational algorithms, which provides experimenters with flexibility in experimental design and data management. Descriptions of the UML procedure and the UML Toolbox are provided, followed by toolbox use examples. Finally, guidelines and recommendations of parameter configurations are given. PMID:24671826

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

PubMed

Pizzolato, Claudio; Lloyd, David G; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F; Fregly, Benjamin J; Reggiani, Monica

2015-11-05

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A New User Interface for On-Demand Customizable Data Products for Sensors in a SensorWeb

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Sullivan, Don

2011-01-01

A SensorWeb is a set of sensors, which can consist of ground, airborne and space-based sensors interoperating in an automated or autonomous collaborative manner. The NASA SensorWeb toolbox, developed at NASA/GSFC in collaboration with NASA/JPL, NASA/Ames and other partners, is a set of software and standards that (1) enables users to create virtual private networks of sensors over open networks; (2) provides the capability to orchestrate their actions; (3) provides the capability to customize the output data products and (4) enables automated delivery of the data products to the users desktop. A recent addition to the SensorWeb Toolbox is a new user interface, together with web services co-resident with the sensors, to enable rapid creation, loading and execution of new algorithms for processing sensor data. The web service along with the user interface follows the Open Geospatial Consortium (OGC) standard called Web Coverage Processing Service (WCPS). This presentation will detail the prototype that was built and how the WCPS was tested against a HyspIRI flight testbed and an elastic computation cloud on the ground with EO-1 data. HyspIRI is a future NASA decadal mission. The elastic computation cloud stores EO-1 data and runs software similar to Amazon online shopping.

Java simulations of embedded control systems.

PubMed

Farias, Gonzalo; Cervin, Anton; Arzén, Karl-Erik; Dormido, Sebastián; Esquembre, Francisco

2010-01-01

This paper introduces a new Open Source Java library suited for the simulation of embedded control systems. The library is based on the ideas and architecture of TrueTime, a toolbox of Matlab devoted to this topic, and allows Java programmers to simulate the performance of control processes which run in a real time environment. Such simulations can improve considerably the learning and design of multitasking real-time systems. The choice of Java increases considerably the usability of our library, because many educators program already in this language. But also because the library can be easily used by Easy Java Simulations (EJS), a popular modeling and authoring tool that is increasingly used in the field of Control Education. EJS allows instructors, students, and researchers with less programming capabilities to create advanced interactive simulations in Java. The paper describes the ideas, implementation, and sample use of the new library both for pure Java programmers and for EJS users. The JTT library and some examples are online available on http://lab.dia.uned.es/jtt.

Java Simulations of Embedded Control Systems

PubMed Central

Farias, Gonzalo; Cervin, Anton; Årzén, Karl-Erik; Dormido, Sebastián; Esquembre, Francisco

2010-01-01

This paper introduces a new Open Source Java library suited for the simulation of embedded control systems. The library is based on the ideas and architecture of TrueTime, a toolbox of Matlab devoted to this topic, and allows Java programmers to simulate the performance of control processes which run in a real time environment. Such simulations can improve considerably the learning and design of multitasking real-time systems. The choice of Java increases considerably the usability of our library, because many educators program already in this language. But also because the library can be easily used by Easy Java Simulations (EJS), a popular modeling and authoring tool that is increasingly used in the field of Control Education. EJS allows instructors, students, and researchers with less programming capabilities to create advanced interactive simulations in Java. The paper describes the ideas, implementation, and sample use of the new library both for pure Java programmers and for EJS users. The JTT library and some examples are online available on http://lab.dia.uned.es/jtt. PMID:22163674

The AI Bus architecture for distributed knowledge-based systems

NASA Technical Reports Server (NTRS)

Schultz, Roger D.; Stobie, Iain

1991-01-01

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

Anti-Americanism: A Perfect Addition to a Russian Authoritarian’s Political Toolbox

DTIC Science & Technology

2013-12-01

Putin’s autobiographical interview book First Person. Primary source transcripts from the Russian government’s public online archives will be...80. 36 Ibid., 106. 20 could not directly affect the repeated snubbing that Yeltsin incurred from the West, the memories of how the United

Gammapy: Python toolbox for gamma-ray astronomy

NASA Astrophysics Data System (ADS)

Deil, Christoph; Donath, Axel; Owen, Ellis; Terrier, Regis; Bühler, Rolf; Armstrong, Thomas

2017-11-01

Gammapy analyzes gamma-ray data and creates sky images, spectra and lightcurves, from event lists and instrument response information; it can also determine the position, morphology and spectra of gamma-ray sources. It is used to analyze data from H.E.S.S., Fermi-LAT, and the Cherenkov Telescope Array (CTA).

A TOOLBOX FOR SANITARY SEWER OVERFLOW ANALYSIS AND PLANNING (SSOAP) AND APPLICATIONS

EPA Science Inventory

Rainfall Derived Infiltration and Inflow (RDII) into sanitary sewer systems has long been recognized as a source of operating problems in sewerage systems. RDII is the main cause of sanitary sewer overflows (SSOs) to basements, streets, or nearby streams and can also cause seriou...

Testing adaptive toolbox models: a Bayesian hierarchical approach.

PubMed

Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

LESTO: an Open Source GIS-based toolbox for LiDAR analysis

NASA Astrophysics Data System (ADS)

Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

2015-04-01

During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed considering an Optimizer Algorithm based on Particle Swarm (PS) and a matching procedure which takes the position and the height of the extracted trees respect to the measured ones and iteratively tries to improve the candidate solution changing the models' parameters. Example of application of the LESTO tools will be presented on test sites. Test area consists in a series of circular sampling plots randomly selected from a 50x50 m regular grid within a buffer zone of 150 m from the forest road. Other studies on the same sites take as reference measurements of position, diameter, species and height and proposed allometric relationships. These allometric relationship were obtained for each species deriving the stem volume of single trees based on height and diameter at breast height. LESTO is integrated in the JGrassTools project and available for download at www.jgrasstools.org. A simple and easy to use graphical interface to run the models is available at https://github.com/moovida/STAGE/releases.

Hydratools, a MATLAB® based data processing package for Sontek Hydra data

USGS Publications Warehouse

Martini, M.; Lightsom, F.L.; Sherwood, C.R.; Xu, Jie; Lacy, J.R.; Ramsey, A.; Horwitz, R.

2005-01-01

The U.S. Geological Survey (USGS) has developed a set of MATLAB tools to process and convert data collected by Sontek Hydra instruments to netCDF, which is a format used by the USGS to process and archive oceanographic time-series data. The USGS makes high-resolution current measurements within 1.5 meters of the bottom. These data are used in combination with other instrument data from sediment transport studies to develop sediment transport models. Instrument manufacturers provide software which outputs unique binary data formats. Multiple data formats are cumbersome. The USGS solution is to translate data streams into a common data format: netCDF. The Hydratools toolbox is written to create netCDF format files following EPIC conventions, complete with embedded metadata. Data are accepted from both the ADV and the PCADP. The toolbox will detect and remove bad data, substitute other sources of heading and tilt measurements if necessary, apply ambiguity corrections, calculate statistics, return information about data quality, and organize metadata. Standardized processing and archiving makes these data more easily and routinely accessible locally and over the Internet. In addition, documentation of the techniques used in the toolbox provides a baseline reference for others utilizing the data.

A new Bayesian Earthquake Analysis Tool (BEAT)

NASA Astrophysics Data System (ADS)

Vasyura-Bathke, Hannes; Dutta, Rishabh; Jónsson, Sigurjón; Mai, Martin

2017-04-01

Modern earthquake source estimation studies increasingly use non-linear optimization strategies to estimate kinematic rupture parameters, often considering geodetic and seismic data jointly. However, the optimization process is complex and consists of several steps that need to be followed in the earthquake parameter estimation procedure. These include pre-describing or modeling the fault geometry, calculating the Green's Functions (often assuming a layered elastic half-space), and estimating the distributed final slip and possibly other kinematic source parameters. Recently, Bayesian inference has become popular for estimating posterior distributions of earthquake source model parameters given measured/estimated/assumed data and model uncertainties. For instance, some research groups consider uncertainties of the layered medium and propagate these to the source parameter uncertainties. Other groups make use of informative priors to reduce the model parameter space. In addition, innovative sampling algorithms have been developed that efficiently explore the often high-dimensional parameter spaces. Compared to earlier studies, these improvements have resulted in overall more robust source model parameter estimates that include uncertainties. However, the computational demands of these methods are high and estimation codes are rarely distributed along with the published results. Even if codes are made available, it is often difficult to assemble them into a single optimization framework as they are typically coded in different programing languages. Therefore, further progress and future applications of these methods/codes are hampered, while reproducibility and validation of results has become essentially impossible. In the spirit of providing open-access and modular codes to facilitate progress and reproducible research in earthquake source estimations, we undertook the effort of producing BEAT, a python package that comprises all the above-mentioned features in one single programing environment. The package is build on top of the pyrocko seismological toolbox (www.pyrocko.org) and makes use of the pymc3 module for Bayesian statistical model fitting. BEAT is an open-source package (https://github.com/hvasbath/beat) and we encourage and solicit contributions to the project. In this contribution, we present our strategy for developing BEAT, show application examples, and discuss future developments.

FAST: FAST Analysis of Sequences Toolbox

PubMed Central

Lawrence, Travis J.; Kauffman, Kyle T.; Amrine, Katherine C. H.; Carper, Dana L.; Lee, Raymond S.; Becich, Peter J.; Canales, Claudia J.; Ardell, David H.

2015-01-01

FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought. PMID:26042145

ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

NASA Astrophysics Data System (ADS)

Lecocq, Thomas; Megies, Tobias; Krischer, Lion; Sales de Andrade, Elliott; Barsch, Robert; Beyreuther, Moritz

2016-04-01

ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides * read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, * a comprehensive signal processing toolbox tuned to the needs of seismologists, * integrated access to all large data centers, web services and databases, and * convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software. ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it. This contribution will give a short introduction and overview of ObsPy and highlight a number of use cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

NASA Astrophysics Data System (ADS)

Krischer, L.; Megies, T.; Sales de Andrade, E.; Barsch, R.; Beyreuther, M.

2015-12-01

ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, a comprehensive signal processing toolbox tuned to the needs of seismologists, integrated access to all large data centers, web services and databases, and convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software.ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it.This contribution will give a short introduction and overview of ObsPy and highlight a number of us cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data.

PubMed

Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J

2017-04-01

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.

Cortical surface-based threshold-free cluster enhancement and cortexwise mediation.

PubMed

Lett, Tristram A; Waller, Lea; Tost, Heike; Veer, Ilya M; Nazeri, Arash; Erk, Susanne; Brandl, Eva J; Charlet, Katrin; Beck, Anne; Vollstädt-Klein, Sabine; Jorde, Anne; Kiefer, Falk; Heinz, Andreas; Meyer-Lindenberg, Andreas; Chakravarty, M Mallar; Walter, Henrik

2017-06-01

Threshold-free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel- or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE. The toolbox is open source and publicly available (https://github.com/trislett/TFCE_mediation). We validated TFCE_mediation in healthy controls from two independent multimodal neuroimaging samples (N = 199 and N = 183). We found a consistent structure-function relationship between surface area and the first independent component (IC1) of the N-back task, that white matter fractional anisotropy is strongly associated with IC1 N-back, and that our voxel-based results are essentially identical to FSL randomise using TFCE (all P FWE <0.05). Using cortexwise mediation, we showed that the relationship between white matter FA and IC1 N-back is mediated by surface area in the right superior frontal cortex (P FWE  < 0.05). We also demonstrated that the same mediation model is present using vertexwise mediation (P FWE  < 0.05). In conclusion, cortexwise analysis with TFCE provides an effective analysis of multimodal neuroimaging data. Furthermore, cortexwise mediation analysis may identify or explain a mechanism that underlies an observed relationship among a predictor, intermediary, and dependent variables in which one of these variables is assessed at a whole-brain scale. Hum Brain Mapp 38:2795-2807, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The Schultz MIDI Benchmarking Toolbox for MIDI interfaces, percussion pads, and sound cards.

PubMed

Schultz, Benjamin G

2018-04-17

The Musical Instrument Digital Interface (MIDI) was readily adopted for auditory sensorimotor synchronization experiments. These experiments typically use MIDI percussion pads to collect responses, a MIDI-USB converter (or MIDI-PCI interface) to record responses on a PC and manipulate feedback, and an external MIDI sound module to generate auditory feedback. Previous studies have suggested that auditory feedback latencies can be introduced by these devices. The Schultz MIDI Benchmarking Toolbox (SMIDIBT) is an open-source, Arduino-based package designed to measure the point-to-point latencies incurred by several devices used in the generation of response-triggered auditory feedback. Experiment 1 showed that MIDI messages are sent and received within 1 ms (on average) in the absence of any external MIDI device. Latencies decreased when the baud rate increased above the MIDI protocol default (31,250 bps). Experiment 2 benchmarked the latencies introduced by different MIDI-USB and MIDI-PCI interfaces. MIDI-PCI was superior to MIDI-USB, primarily because MIDI-USB is subject to USB polling. Experiment 3 tested three MIDI percussion pads. Both the audio and MIDI message latencies were significantly greater than 1 ms for all devices, and there were significant differences between percussion pads and instrument patches. Experiment 4 benchmarked four MIDI sound modules. Audio latencies were significantly greater than 1 ms, and there were significant differences between sound modules and instrument patches. These experiments suggest that millisecond accuracy might not be achievable with MIDI devices. The SMIDIBT can be used to benchmark a range of MIDI devices, thus allowing researchers to make informed decisions when choosing testing materials and to arrive at an acceptable latency at their discretion.

The C6H6 NMR repository: An integral solution to control the flow of your data from the magnet to the public.

PubMed

Patiny, Luc; Zasso, Michaël; Kostro, Daniel; Bernal, Andrés; Castillo, Andrés M; Bolaños, Alejandro; Asencio, Miguel A; Pellet, Norman; Todd, Matthew; Schloerer, Nils; Kuhn, Stefan; Holmes, Elaine; Javor, Sacha; Wist, Julien

2017-10-05

NMR is a mature technique that is well established and adopted in a wide range of research facilities from laboratories to hospitals. This accounts for large amounts of valuable experimental data that may be readily exported into a standard and open format. Yet the publication of these data faces an important issue: Raw data are not made available; instead, the information is slimed down into a string of characters (the list of peaks). Although historical limitations of technology explain this practice, it is not acceptable in the era of Internet. The idea of modernizing the strategy for sharing NMR data is not new, and some repositories exist, but sharing raw data is still not an established practice. Here, we present a powerful toolbox built on recent technologies that runs inside the browser and provides a means to store, share, analyse, and interact with original NMR data. Stored spectra can be streamlined into the publication pipeline, to improve the revision process for instance. The set of tools is still basic but is intended to be extended. The project is open source under the Massachusetts Institute of Technology (MIT) licence. Copyright © 2017 John Wiley & Sons, Ltd.

Two-phase flow simulation of scour around a cylindrical pile

NASA Astrophysics Data System (ADS)

Nagel, T.; Chauchat, J.; Bonamy, C.; Liu, X.; Cheng, Z.; Hsu, T. J.

2017-12-01

Scour around structures is a major engineering issue that requires a detailed description of the flow field but also a consistent description of sediment transport processes that could not only be related to bed shear stress, like Shields parameter based sediment transport formula. In order to address this issue we used a multi-dimensional two-phase flow solver, sedFoam-2.0 (Chauchat et al., GMD 2017) implemented under the open-source CFD toolbox OpenFoam. Three-dimensional simulations have been performed on Roulund et al. (JFM 2005) configurations for clear-water and live bed cases. The k-omega model from Wilcox (AIAA Journal 2006) is used for the turbulent stress and the granular rheology μ(I) is used for the granular stress in the live bed case. The hydrodynamic is validated on the clear water case and the numerical results obtained for the live bed case provide a proof of concept that two-phase flow model is applicable to such problem with quantitative results for the prediction of scour depth upstream and downstream the cylinder at short timescales, up to 300s. Analyzing the simulation results in term of classical dimensionless sediment transport flux versus Shields parameter allows to get more insight into the fine scale sediment transport mechanisms involved in the scour process.

The numerical model of multi-layer insulation with a defined wrapping pattern immersed in superfluid helium

NASA Astrophysics Data System (ADS)

Malecha, Ziemowit; Lubryka, Eliza

2017-11-01

The numerical model of thin layers, characterized by a defined wrapping pattern can be a crucial element of many computational problems related to engineering and science. A motivating example is found in multilayer electrical insulation, which is an important component of superconducting magnets and other cryogenic installations. The wrapping pattern of the insulation can significantly affect heat transport and the performance of the considered instruments. The major objective of this study is to develop the numerical boundary conditions (BC) needed to model the wrapping pattern of thin insulation. An example of the practical application of the proposed BC includes the heat transfer of Rutherford NbTi cables immersed in super-fluid helium (He II) across thin layers of electrical insulation. The proposed BC and a mathematical model of heat transfer in He II are implemented in the open source CFD toolbox OpenFOAM. The implemented mathematical model and the BC are compared in the experiments. The study confirms that the thermal resistance of electrical insulation can be lowered by implementing the proper wrapping pattern. The proposed BC can be useful in the study of new patterns for wrapping schemes. The work has been supported by statutory funds from Polish Ministry for Science and Higher Education for the year of 2017.

Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data

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

Pelt, Daniël M.; Gürsoy, Dogˇa; Palenstijn, Willem Jan

2016-04-28

The processing of tomographic synchrotron data requires advanced and efficient software to be able to produce accurate results in reasonable time. In this paper, the integration of two software toolboxes, TomoPy and the ASTRA toolbox, which, together, provide a powerful framework for processing tomographic data, is presented. The integration combines the advantages of both toolboxes, such as the user-friendliness and CPU-efficient methods of TomoPy and the flexibility and optimized GPU-based reconstruction methods of the ASTRA toolbox. It is shown that both toolboxes can be easily installed and used together, requiring only minor changes to existing TomoPy scripts. Furthermore, it ismore » shown that the efficient GPU-based reconstruction methods of the ASTRA toolbox can significantly decrease the time needed to reconstruct large datasets, and that advanced reconstruction methods can improve reconstruction quality compared with TomoPy's standard reconstruction method.« less

Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data

PubMed Central

Pelt, Daniël M.; Gürsoy, Doǧa; Palenstijn, Willem Jan; Sijbers, Jan; De Carlo, Francesco; Batenburg, Kees Joost

2016-01-01

The processing of tomographic synchrotron data requires advanced and efficient software to be able to produce accurate results in reasonable time. In this paper, the integration of two software toolboxes, TomoPy and the ASTRA toolbox, which, together, provide a powerful framework for processing tomographic data, is presented. The integration combines the advantages of both toolboxes, such as the user-friendliness and CPU-efficient methods of TomoPy and the flexibility and optimized GPU-based reconstruction methods of the ASTRA toolbox. It is shown that both toolboxes can be easily installed and used together, requiring only minor changes to existing TomoPy scripts. Furthermore, it is shown that the efficient GPU-based reconstruction methods of the ASTRA toolbox can significantly decrease the time needed to reconstruct large datasets, and that advanced reconstruction methods can improve reconstruction quality compared with TomoPy’s standard reconstruction method. PMID:27140167

The CatchMod toolbox: easy and guided access to ICT tools for Water Framework Directive implementation.

PubMed

van Griensven, A; Vanrolleghem, P A

2006-01-01

Web-based toolboxes are handy tools to inform experienced users of existing software in their disciplines. However, for the implementation of the Water Framework Directive, a much more diverse public (water managers, consultancy firms, scientists, etc.) will ask for a very wide diversity of Information and Communication Technology (ICT) tools. It is obvious that the users of a web-based ICT-toolbox providing all this will not be experts in all of the disciplines and that a toolbox for ICT tools for Water Framework Directive implementation should thus go beyond just making interesting web-links. To deal with this issue, expert knowledge is brought to the users through the incorporation of visitor-geared guidance (materials) in the Harmoni-CA toolbox. Small workshops of expert teams were organized to deliver documents explaining why the tools are important, when they are required and what activity they support/perform, as well as a categorization of the multitude of available tools. An integration of this information in the web-based toolbox helps the users to browse through a toolbox containing tools, reports, guidance documents and interesting links. The Harmoni-CA toolbox thus provides not only a virtual toolbox, but incorporates a virtual expert as well.

The FieldTrip-SimBio pipeline for EEG forward solutions.

PubMed

Vorwerk, Johannes; Oostenveld, Robert; Piastra, Maria Carla; Magyari, Lilla; Wolters, Carsten H

2018-03-27

Accurately solving the electroencephalography (EEG) forward problem is crucial for precise EEG source analysis. Previous studies have shown that the use of multicompartment head models in combination with the finite element method (FEM) can yield high accuracies both numerically and with regard to the geometrical approximation of the human head. However, the workload for the generation of multicompartment head models has often been too high and the use of publicly available FEM implementations too complicated for a wider application of FEM in research studies. In this paper, we present a MATLAB-based pipeline that aims to resolve this lack of easy-to-use integrated software solutions. The presented pipeline allows for the easy application of five-compartment head models with the FEM within the FieldTrip toolbox for EEG source analysis. The FEM from the SimBio toolbox, more specifically the St. Venant approach, was integrated into the FieldTrip toolbox. We give a short sketch of the implementation and its application, and we perform a source localization of somatosensory evoked potentials (SEPs) using this pipeline. We then evaluate the accuracy that can be achieved using the automatically generated five-compartment hexahedral head model [skin, skull, cerebrospinal fluid (CSF), gray matter, white matter] in comparison to a highly accurate tetrahedral head model that was generated on the basis of a semiautomatic segmentation with very careful and time-consuming manual corrections. The source analysis of the SEP data correctly localizes the P20 component and achieves a high goodness of fit. The subsequent comparison to the highly detailed tetrahedral head model shows that the automatically generated five-compartment head model performs about as well as a highly detailed four-compartment head model (skin, skull, CSF, brain). This is a significant improvement in comparison to a three-compartment head model, which is frequently used in praxis, since the importance of modeling the CSF compartment has been shown in a variety of studies. The presented pipeline facilitates the use of five-compartment head models with the FEM for EEG source analysis. The accuracy with which the EEG forward problem can thereby be solved is increased compared to the commonly used three-compartment head models, and more reliable EEG source reconstruction results can be obtained.

Sentinel-3 for Science

NASA Astrophysics Data System (ADS)

Benveniste, J.; Regner, P.; Desnos, Y. L.

2015-12-01

The Scientific Exploitation of Operational Mission (SEOM) programme element (http://seom.esa.int/) is part of the ESA's Fourth Earth Observation Envelope Programme (2013-2017). The prime objective is to federate, support and expand the international research community that the ERS, ENVISAT and the Envelope programmes have built up over the last 25 years. It aims to further strengthen the leadership of the European Earth Observation research community by enabling them to extensively exploit future European operational EO missions. SEOM is enabling the science community to address new scientific research that are opened by free and open access to data from operational EO missions. The Programme is based on community-wide recommendations for actions on key research issues, gathered through a series of international thematic workshops and scientific user consultation meetings such as the Sentinel-3 for Science Workshop held last June in Venice, Italy (see http://seom.esa.int/S3forScience2015). The 2015 SEOM work plan includes the launch of new R&D studies for scientific exploitation of the Sentinels, the development of open-source multi-mission scientific toolboxes, the organization of advanced international training courses, summer schools and educational materials, as well as activities for promoting the scientific use of EO data, also via the organization of Workshops. This paper will report the recommendations from the International Scientific Community concerning the Sentinel-3 Scientific Exploitation, as expressed in Venice, keeping in mind that Sentinel-3 is an operational mission to provide operational services (see http://www.copernicus.eu).

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.

Matlab Geochemistry: An open source geochemistry solver based on MRST

NASA Astrophysics Data System (ADS)

McNeece, C. J.; Raynaud, X.; Nilsen, H.; Hesse, M. A.

2017-12-01

The study of geological systems often requires the solution of complex geochemical relations. To address this need we present an open source geochemical solver based on the Matlab Reservoir Simulation Toolbox (MRST) developed by SINTEF. The implementation supports non-isothermal multicomponent aqueous complexation, surface complexation, ion exchange, and dissolution/precipitation reactions. The suite of tools available in MRST allows for rapid model development, in particular the incorporation of geochemical calculations into transport simulations of multiple phases, complex domain geometry and geomechanics. Different numerical schemes and additional physics can be easily incorporated into the existing tools through the object-oriented framework employed by MRST. The solver leverages the automatic differentiation tools available in MRST to solve arbitrarily complex geochemical systems with any choice of species or element concentration as input. Four mathematical approaches enable the solver to be quite robust: 1) the choice of chemical elements as the basis components makes all entries in the composition matrix positive thus preserving convexity, 2) a log variable transformation is used which transfers the nonlinearity to the convex composition matrix, 3) a priori bounds on variables are calculated from the structure of the problem, constraining Netwon's path and 4) an initial guess is calculated implicitly by sequentially adding model complexity. As a benchmark we compare the model to experimental and semi-analytic solutions of the coupled salinity-acidity transport system. Together with the reservoir simulation capabilities of MRST the solver offers a promising tool for geochemical simulations in reservoir domains for applications in a diversity of fields from enhanced oil recovery to radionuclide storage.

Mindcontrol: A web application for brain segmentation quality control.

PubMed

Keshavan, Anisha; Datta, Esha; M McDonough, Ian; Madan, Christopher R; Jordan, Kesshi; Henry, Roland G

2018-04-15

Tissue classification plays a crucial role in the investigation of normal neural development, brain-behavior relationships, and the disease mechanisms of many psychiatric and neurological illnesses. Ensuring the accuracy of tissue classification is important for quality research and, in particular, the translation of imaging biomarkers to clinical practice. Assessment with the human eye is vital to correct various errors inherent to all currently available segmentation algorithms. Manual quality assurance becomes methodologically difficult at a large scale - a problem of increasing importance as the number of data sets is on the rise. To make this process more efficient, we have developed Mindcontrol, an open-source web application for the collaborative quality control of neuroimaging processing outputs. The Mindcontrol platform consists of a dashboard to organize data, descriptive visualizations to explore the data, an imaging viewer, and an in-browser annotation and editing toolbox for data curation and quality control. Mindcontrol is flexible and can be configured for the outputs of any software package in any data organization structure. Example configurations for three large, open-source datasets are presented: the 1000 Functional Connectomes Project (FCP), the Consortium for Reliability and Reproducibility (CoRR), and the Autism Brain Imaging Data Exchange (ABIDE) Collection. These demo applications link descriptive quality control metrics, regional brain volumes, and thickness scalars to a 3D imaging viewer and editing module, resulting in an easy-to-implement quality control protocol that can be scaled for any size and complexity of study. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)

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

Tuffner, Francis; Marinovici, PNNL Laurentiu; Hauer, PNNL John

2014-02-21

The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to helpmore » guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.« less

MOEMS Modeling Using the Geometrical Matrix Toolbox

NASA Technical Reports Server (NTRS)

Wilson, William C.; Atkinson, Gary M.

2005-01-01

New technologies such as MicroOptoElectro-Mechanical Systems (MOEMS) require new modeling tools. These tools must simultaneously model the optical, electrical, and mechanical domains and the interactions between these domains. To facilitate rapid prototyping of these new technologies an optical toolbox has been developed for modeling MOEMS devices. The toolbox models are constructed using MATLAB's dynamical simulator, Simulink. Modeling toolboxes will allow users to focus their efforts on system design and analysis as opposed to developing component models. This toolbox was developed to facilitate rapid modeling and design of a MOEMS based laser ultrasonic receiver system.

C%2B%2B tensor toolbox user manual.

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

Plantenga, Todd D.; Kolda, Tamara Gibson

2012-04-01

The C++ Tensor Toolbox is a software package for computing tensor decompositions. It is based on the Matlab Tensor Toolbox, and is particularly optimized for sparse data sets. This user manual briefly overviews tensor decomposition mathematics, software capabilities, and installation of the package. Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors in C++. The Toolbox compiles into libraries and is intended for use with custom applications written by users.

Facilitating open global data use in earthquake source modelling to improve geodetic and seismological approaches

NASA Astrophysics Data System (ADS)

Sudhaus, Henriette; Heimann, Sebastian; Steinberg, Andreas; Isken, Marius; Vasyura-Bathke, Hannes

2017-04-01

In the last few years impressive achievements have been made in improving inferences about earthquake sources by using InSAR (Interferometric Synthetic Aperture Radar) data. Several factors aided these developments. The open data basis of earthquake observations has expanded vastly with the two powerful Sentinel-1 SAR sensors up in space. Increasing computer power allows processing of large data sets for more detailed source models. Moreover, data inversion approaches for earthquake source inferences are becoming more advanced. By now data error propagation is widely implemented and the estimation of model uncertainties is a regular feature of reported optimum earthquake source models. Also, more regularly InSAR-derived surface displacements and seismological waveforms are combined, which requires finite rupture models instead of point-source approximations and layered medium models instead of homogeneous half-spaces. In other words the disciplinary differences in geodetic and seismological earthquake source modelling shrink towards common source-medium descriptions and a source near-field/far-field data point of view. We explore and facilitate the combination of InSAR-derived near-field static surface displacement maps and dynamic far-field seismological waveform data for global earthquake source inferences. We join in the community efforts with the particular goal to improve crustal earthquake source inferences in generally not well instrumented areas, where often only the global backbone observations of earthquakes are available provided by seismological broadband sensor networks and, since recently, by Sentinel-1 SAR acquisitions. We present our work on modelling standards for the combination of static and dynamic surface displacements in the source's near-field and far-field, e.g. on data and prediction error estimations as well as model uncertainty estimation. Rectangular dislocations and moment-tensor point sources are exchanged by simple planar finite rupture models. 1d-layered medium models are implemented for both near- and far-field data predictions. A highlight of our approach is a weak dependence on earthquake bulletin information: hypocenter locations and source origin times are relatively free source model parameters. We present this harmonized source modelling environment based on example earthquake studies, e.g. the 2010 Haiti earthquake, the 2009 L'Aquila earthquake and others. We discuss the benefit of combined-data non-linear modelling on the resolution of first-order rupture parameters, e.g. location, size, orientation, mechanism, moment/slip and rupture propagation. The presented studies apply our newly developed software tools which build up on the open-source seismological software toolbox pyrocko (www.pyrocko.org) in the form of modules. We aim to facilitate a better exploitation of open global data sets for a wide community studying tectonics, but the tools are applicable also for a large range of regional to local earthquake studies. Our developments therefore ensure a large flexibility in the parametrization of medium models (e.g. 1d to 3d medium models), source models (e.g. explosion sources, full moment tensor sources, heterogeneous slip models, etc) and of the predicted data (e.g. (high-rate) GPS, strong motion, tilt). This work is conducted within the project "Bridging Geodesy and Seismology" (www.bridges.uni-kiel.de) funded by the German Research Foundation DFG through an Emmy-Noether grant.

Operational Research: Evaluating Multimodel Implementations for 24/7 Runtime Environments

NASA Astrophysics Data System (ADS)

Burkhart, J. F.; Helset, S.; Abdella, Y. S.; Lappegard, G.

2016-12-01

We present a new open source framework for operational hydrologic rainfall-runoff modeling. The Statkraft Hydrologic Forecasting Toolbox (Shyft) is unique from existing frameworks in that two primary goals are to provide: i) modern, professionally developed source code, and ii) a platform that is robust and ready for operational deployment. Developed jointly between Statkraft AS and The University of Oslo, the framework is currently in operation in both private and academic environments. The hydrology presently available in the distribution is simple and proven. Shyft provides a platform for distributed hydrologic modeling in a highly efficient manner. In it's current operational deployment at Statkraft, Shyft is used to provide daily 10-day forecasts for critical reservoirs. In a research setting, we have developed a novel implementation of the SNICAR model to assess the impact of aerosol deposition on snow packs. Several well known rainfall-runoff algorithms are available for use, allowing for intercomparing different approaches based on available data and the geographical environment. The well known HBV model is a default option, and other routines with more localized methods handling snow and evapotranspiration, or simplifications of catchment scale processes are included. For the latter, we have implemented the Kirchner response routine. Being developed in Norway, a variety snow-melt routines, including simplified degree day models or more advanced energy balance models, may be selected. Ensemble forecasts, multi-model implementations, and statistical post-processing routines enable a robust toolbox for investigating optimal model configurations in an operational setting. The Shyft core is written in modern templated C++ and has Python wrappers developed for easy access to module sub-routines. The code is developed such that the modules that make up a "method stack" are easy to modify and customize, allowing one to create new methods and test them rapidly. Due to the simple architecture and ease of access to the module routines, we see Shyft as an optimal choice to evaluate new hydrologic routines in an environment requiring robust, professionally developed software and welcome further community participation.

Speed management toolbox for rural communities.

DOT National Transportation Integrated Search

2013-04-01

The primary objective of this toolbox is to summarize various known traffic-calming treatments and their effectiveness. This toolbox focuses on roadway-based treatments for speed management, particularly for rural communities with transition zones. E...

Development of reference transcriptomes for the major insect pests of cowpea: a toolbox for insect pest management approaches in West Africa

USDA-ARS?s Scientific Manuscript database

Cowpea crops are widely cultivated and a major nutritional source of protein for indigenous human populations in West Africa. Annual yields and longevity of grain storage is greatly reduced by feeding damage caused by a complex of insect pests that include Anoplocnemis curvipes, Aphis craccivora, Cl...

Analyzing Public Discourse: Using Media Content Analysis to Understand the Policy Process

ERIC Educational Resources Information Center

Saraisky, Nancy Green

2016-01-01

One of the most basic and obvious sources of data for education policy analysis is text. This article discusses content analysis as an important part of the methodological toolbox for elucidating patterns and trends about education policy. Focusing specifically on media, I show how media content analysis can produce nuanced insights about the ways…

Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart Rate Estimation.

PubMed

Andreotti, Fernando; Graser, Felix; Malberg, Hagen; Zaunseder, Sebastian

2017-12-01

The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of NI-FECG to improve fetal heart rate (FHR) estimation. Using a naive Bayes classifier, state-of-the-art and novel signal quality indices (SQIs), and an existing adaptive Kalman filter, FHR estimation was improved. For the purpose of training and validating the proposed methods, a large annotated private clinical dataset was used. The suggested classification scheme demonstrated an accuracy of Krippendorff's alpha in determining the overall quality of NI-FECG signals. The proposed Kalman filter outperformed alternative methods for FHR estimation achieving accuracy. The proposed algorithm was able to reliably reflect changes of signal quality and can be used in improving FHR estimation. NI-ECG signal quality estimation and multichannel information fusion are largely unexplored topics. Based on previous works, multichannel FHR estimation is a field that could strongly benefit from such methods. The developed SQI algorithms as well as resulting classifier were made available under a GNU GPL open-source license and contributed to the FECGSYN toolbox.

Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox.

PubMed

Leveridge, Melanie; Chung, Chun-Wa; Gross, Jeffrey W; Phelps, Christopher B; Green, Darren

2018-06-01

There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

PubMed Central

Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.; Thiele, Ines; Orth, Jeffrey D.; Feist, Adam M.; Zielinski, Daniel C.; Bordbar, Aarash; Lewis, Nathan E.; Rahmanian, Sorena; Kang, Joseph; Hyduke, Daniel R.; Palsson, Bernhard Ø.

2012-01-01

Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) visualization. As with the first version, the COBRA Toolbox reads and writes Systems Biology Markup Language formatted models. In version 2.0, we improved performance, usability, and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the Toolbox and validate results. This Toolbox lowers the barrier of entry to use powerful COBRA methods. PMID:21886097

FRACOR-software toolbox for deterministic mapping of fracture corridors in oil fields on AutoCAD platform

NASA Astrophysics Data System (ADS)

Ozkaya, Sait I.

2018-03-01

Fracture corridors are interconnected large fractures in a narrow sub vertical tabular array, which usually traverse entire reservoir vertically and extended for several hundreds of meters laterally. Fracture corridors with their huge conductivities constitute an important element of many fractured reservoirs. Unlike small diffuse fractures, actual fracture corridors must be mapped deterministically for simulation or field development purposes. Fracture corridors can be identified and quantified definitely with borehole image logs and well testing. However, there are rarely sufficient image logs or well tests, and it is necessary to utilize various fracture corridor indicators with varying degrees of reliability. Integration of data from many different sources, in turn, requires a platform with powerful editing and layering capability. Available commercial reservoir characterization software packages, with layering and editing capabilities, can be cost intensive. CAD packages are far more affordable and may easily acquire the versatility and power of commercial software packages with addition of a small software toolbox. The objective of this communication is to present FRACOR, a software toolbox which enables deterministic 2D fracture corridor mapping and modeling on AutoCAD platform. The FRACOR toolbox is written in AutoLISPand contains several independent routines to import and integrate available fracture corridor data from an oil field, and export results as text files. The resulting fracture corridor maps consists mainly of fracture corridors with different confidence levels from combination of static and dynamic data and exclusion zones where no fracture corridor can exist. The exported text file of fracture corridors from FRACOR can be imported into an upscaling programs to generate fracture grid for dual porosity simulation or used for field development and well planning.

Orbit Determination Toolbox

NASA Technical Reports Server (NTRS)

Carpenter, James R.; Berry, Kevin; Gregpru. Late; Speckman, Keith; Hur-Diaz, Sun; Surka, Derek; Gaylor, Dave

2010-01-01

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

The ROC Toolbox: A toolbox for analyzing receiver-operating characteristics derived from confidence ratings.

PubMed

Koen, Joshua D; Barrett, Frederick S; Harlow, Iain M; Yonelinas, Andrew P

2017-08-01

Signal-detection theory, and the analysis of receiver-operating characteristics (ROCs), has played a critical role in the development of theories of episodic memory and perception. The purpose of the current paper is to present the ROC Toolbox. This toolbox is a set of functions written in the Matlab programming language that can be used to fit various common signal detection models to ROC data obtained from confidence rating experiments. The goals for developing the ROC Toolbox were to create a tool (1) that is easy to use and easy for researchers to implement with their own data, (2) that can flexibly define models based on varying study parameters, such as the number of response options (e.g., confidence ratings) and experimental conditions, and (3) that provides optimal routines (e.g., Maximum Likelihood estimation) to obtain parameter estimates and numerous goodness-of-fit measures.The ROC toolbox allows for various different confidence scales and currently includes the models commonly used in recognition memory and perception: (1) the unequal variance signal detection (UVSD) model, (2) the dual process signal detection (DPSD) model, and (3) the mixture signal detection (MSD) model. For each model fit to a given data set the ROC toolbox plots summary information about the best fitting model parameters and various goodness-of-fit measures. Here, we present an overview of the ROC Toolbox, illustrate how it can be used to input and analyse real data, and finish with a brief discussion on features that can be added to the toolbox.

WEC Design Response Toolbox v. 1.0

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

Coe, Ryan; Michelen, Carlos; Eckert-Gallup, Aubrey

2016-03-30

The WEC Design Response Toolbox (WDRT) is a numerical toolbox for design-response analysis of wave energy converters (WECs). The WDRT was developed during a series of efforts to better understand WEC survival design. The WDRT has been designed as a tool for researchers and developers, enabling the straightforward application of statistical and engineering methods. The toolbox includes methods for short-term extreme response, environmental characterization, long-term extreme response and risk analysis, fatigue, and design wave composition.

Screening and assessment of chronic pain among children with cerebral palsy: a process evaluation of a pain toolbox.

PubMed

Orava, Taryn; Provvidenza, Christine; Townley, Ashleigh; Kingsnorth, Shauna

2018-06-08

Though high numbers of children with cerebral palsy experience chronic pain, it remains under-recognized. This paper describes an evaluation of implementation supports and adoption of the Chronic Pain Assessment Toolbox for Children with Disabilities (the Toolbox) to enhance pain screening and assessment practices within a pediatric rehabilitation and complex continuing care hospital. A multicomponent knowledge translation strategy facilitated Toolbox adoption, inclusive of a clinical practice guideline, cerebral palsy practice points and assessment tools. Across the hospital, seven ambulatory care clinics with cerebral palsy caseloads participated in a staggered roll-out (Group 1: exclusive CP caseloads, March-December; Group 2: mixed diagnostic caseloads, August-December). Evaluation measures included client electronic medical record audit, document review and healthcare provider survey and interviews. A significant change in documentation of pain screening and assessment practice from pre-Toolbox (<2%) to post-Toolbox adoption (53%) was found. Uptake in Group 2 clinics lagged behind Group 1. Opportunities to use the Toolbox consistently (based on diagnostic caseload) and frequently (based on client appointments) were noted among contextual factors identified. Overall, the Toolbox was positively received and clinically useful. Findings affirm that the Toolbox, in conjunction with the application of integrated knowledge translation principles and an established knowledge translation framework, has potential to be a useful resource to enrich and standardize chronic pain screening and assessment practices among children with cerebral palsy. Implications for Rehabilitation It is important to engage healthcare providers in the conceptualization, development, implementation and evaluation of a knowledge-to-action best practice product. The Chronic Pain Toolbox for Children with Disabilities provides rehabilitation staff with guidance on pain screening and assessment best practice and offers a range of validated tools that can be incorporated in ambulatory clinic settings to meet varied client needs. Considering unique clinical contexts (i.e., opportunities for use, provider engagement, staffing absences/turnover) is required to optimize and sustain chronic pain screening and assessment practices in rehabilitation outpatient settings.

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis.

PubMed

Morales, Yeimy; Bosque, Gabriel; Vehí, Josep; Picó, Jesús; Llaneras, Francisco

2016-07-11

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples. The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

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.

Using Arduino microcontroller boards to measure response latencies.

PubMed

Schubert, Thomas W; D'Ausilio, Alessandro; Canto, Rosario

2013-12-01

Latencies of buttonpresses are a staple of cognitive science paradigms. Often keyboards are employed to collect buttonpresses, but their imprecision and variability decreases test power and increases the risk of false positives. Response boxes and data acquisition cards are precise, but expensive and inflexible, alternatives. We propose using open-source Arduino microcontroller boards as an inexpensive and flexible alternative. These boards connect to standard experimental software using a USB connection and a virtual serial port, or by emulating a keyboard. In our solution, an Arduino measures response latencies after being signaled the start of a trial, and communicates the latency and response back to the PC over a USB connection. We demonstrated the reliability, robustness, and precision of this communication in six studies. Test measures confirmed that the error added to the measurement had an SD of less than 1 ms. Alternatively, emulation of a keyboard results in similarly precise measurement. The Arduino performs as well as a serial response box, and better than a keyboard. In addition, our setup allows for the flexible integration of other sensors, and even actuators, to extend the cognitive science toolbox.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

2015-11-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Pointing System Simulation Toolbox with Application to a Balloon Mission Simulator

NASA Technical Reports Server (NTRS)

Maringolo Baldraco, Rosana M.; Aretskin-Hariton, Eliot D.; Swank, Aaron J.

2017-01-01

The development of attitude estimation and pointing-control algorithms is necessary in order to achieve high-fidelity modeling for a Balloon Mission Simulator (BMS). A pointing system simulation toolbox was developed to enable this. The toolbox consists of a star-tracker (ST) and Inertial Measurement Unit (IMU) signal generator, a UDP (User Datagram Protocol) communication le (bridge), and an indirect-multiplicative extended Kalman filter (imEKF). This document describes the Python toolbox developed and the results of its implementation in the imEKF.

How Significant is the Slope of the Sea-side Boundary for Modelling Seawater Intrusion in Coastal Aquifers?

NASA Astrophysics Data System (ADS)

Walther, Marc; Graf, Thomas; Kolditz, Olaf; Lield, Rudolf; Post, Vincent

2017-04-01

A large number of people live in coastal areas using the available water resources, which in (semi-)arid regions are often taken from groundwater resources as the only sufficient source. Compared to surface water, these usually provide a safe water supply due to the remediation and retention capabilities of the subsurface, their high yield, and potentially longer term stability. With a water withdrawal from a coastal aquifer, coastal water management, however, has to ensure that seawater intrusion is retained in order to keep the water salinity at an acceptable level for all water users (e.g. agriculture, industry, households). Besides monitoring of water levels and saline intrusion, it has become a common practice to use numerical modeling for evaluating the coastal water resources and projecting future scenarios. When applying a model, it is necessary for the simplifications implied during the conceptualization of the setup to include the relevant processes (here variable-density flow and mass transport) and sensitive parameters (for a steady state commonly hydraulic conductivity, density ratio, dispersivity). Additionally, the model's boundary conditions are essential to the simulation results. In order to reduce the number of elements, and thus, the computational burden, one simplification that is made in most regional scale saltwater intrusion applications, is to represent the sea-side boundary with a vertical geometry, contrary to the natural conditions, that usually show a very shallow decent of the interface between the aquifer and the open seawater. We use the scientific open-source modeling toolbox OpenGeoSys [1] to quantify the influence of this simplification on the saline intrusion, submarine groundwater discharge, and groundwater residence times. Using an ensemble of different shelf shapes for a steady state setup, we identified a significant dependency of saline intrusion length on the geometric parameters of the sea-side boundary. Results show that the additional effort to implement a sloped sea-side boundary may have a significant impact for assessing coastal water resources, and its influence may be of a similar magnitude as that of other common uncertainties in numerical modelling. Literature [1] Kolditz, O., Bauer, S., Bilke, L., Böttcher, N., Delfs, J. O., Fischer, T., Görke, U. J., et al. (2012). OpenGeoSys: an open-source initiative for numerical simulation of thermo-hydro-mechanical/chemical (THM/C) processes in porous media. Environmental Earth Sciences, 67(2), 589-599. doi:10.1007/s12665-012-1546-x

A Module for Graphical Display of Model Results with the CBP Toolbox

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

Smith, F.

2015-04-21

This report describes work performed by the Savannah River National Laboratory (SRNL) in fiscal year 2014 to add enhanced graphical capabilities to display model results in the Cementitious Barriers Project (CBP) Toolbox. Because Version 2.0 of the CBP Toolbox has just been released, the graphing enhancements described in this report have not yet been integrated into a new version of the Toolbox. Instead they have been tested using a standalone GoldSim model and, while they are substantially complete, may undergo further refinement before full implementation. Nevertheless, this report is issued to document the FY14 development efforts which will provide amore » basis for further development of the CBP Toolbox.« less

Identification of the origin of faecal contamination in estuarine oysters using Bacteroidales and F-specific RNA bacteriophage markers.

PubMed

Mieszkin, S; Caprais, M P; Le Mennec, C; Le Goff, M; Edge, T A; Gourmelon, M

2013-09-01

The aim of this study was to identify the origin of faecal pollution impacting the Elorn estuary (Brittany, France) by applying microbial source tracking (MST) markers in both oysters and estuarine waters. The MST markers used were as follows: (i) human-, ruminant- and pig-associated Bacteroidales markers by real-time PCR and (ii) human genogroup II and animal genogroup I of F-specific RNA bacteriophages (FRNAPH) by culture/genotyping and by direct real-time reverse-transcriptase PCR. The higher occurrence of the human genogroup II of F-specific RNA bacteriophages using a culture/genotyping method, and human-associated Bacteroidales marker by real-time PCR, allowed the identification of human faecal contamination as the predominant source of contamination in oysters (total of 18 oyster batches tested) and waters (total of 24 water samples tested). The importance of using the intravalvular liquids instead of digestive tissues, when applying host-associated Bacteroidales markers in oysters, was also revealed. This study has shown that the application of a MST toolbox of diverse bacterial and viral methods can provide multiple lines of evidence to identify the predominant source of faecal contamination in shellfish from an estuarine environment. Application of this MST toolbox is a useful approach to understand the origin of faecal contamination in shellfish harvesting areas in an estuarine setting. © 2013 The Society for Applied Microbiology.

Methods for transition toward computer assisted cognitive examination.

PubMed

Jurica, P; Valenzi, S; Struzik, Z R; Cichocki, A

2015-01-01

We present a software framework which enables the extension of current methods for the assessment of cognitive fitness using recent technological advances. Screening for cognitive impairment is becoming more important as the world's population grows older. Current methods could be enhanced by use of computers. Introduction of new methods to clinics requires basic tools for collection and communication of collected data. To develop tools that, with minimal interference, offer new opportunities for the enhancement of the current interview based cognitive examinations. We suggest methods and discuss process by which established cognitive tests can be adapted for data collection through digitization by pen enabled tablets. We discuss a number of methods for evaluation of collected data, which promise to increase the resolution and objectivity of the common scoring strategy based on visual inspection. By involving computers in the roles of both instructing and scoring, we aim to increase the precision and reproducibility of cognitive examination. The tools provided in Python framework CogExTools available at http://bsp. brain.riken.jp/cogextools/ enable the design, application and evaluation of screening tests for assessment of cognitive impairment. The toolbox is a research platform; it represents a foundation for further collaborative development by the wider research community and enthusiasts. It is free to download and use, and open-source. We introduce a set of open-source tools that facilitate the design and development of new cognitive tests for modern technology. We provide these tools in order to enable the adaptation of technology for cognitive examination in clinical settings. The tools provide the first step in a possible transition toward standardized mental state examination using computers.

An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited.

PubMed

Zöllner, Frank G; Daab, Markus; Sourbron, Steven P; Schad, Lothar R; Schoenberg, Stefan O; Weisser, Gerald

2016-01-14

Perfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology. Five compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft's model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters. We developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control.

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera.

PubMed

Clausner, Tommy; Dalal, Sarang S; Crespo-García, Maité

2017-01-01

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D . Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera

PubMed Central

Clausner, Tommy; Dalal, Sarang S.; Crespo-García, Maité

2017-01-01

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D. Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position. PMID:28559791

Eddy current loss analysis of open-slot fault-tolerant permanent-magnet machines based on conformal mapping method

NASA Astrophysics Data System (ADS)

Ji, Jinghua; Luo, Jianhua; Lei, Qian; Bian, Fangfang

2017-05-01

This paper proposed an analytical method, based on conformal mapping (CM) method, for the accurate evaluation of magnetic field and eddy current (EC) loss in fault-tolerant permanent-magnet (FTPM) machines. The aim of modulation function, applied in CM method, is to change the open-slot structure into fully closed-slot structure, whose air-gap flux density is easy to calculate analytically. Therefore, with the help of Matlab Schwarz-Christoffel (SC) Toolbox, both the magnetic flux density and EC density of FTPM machine are obtained accurately. Finally, time-stepped transient finite-element method (FEM) is used to verify the theoretical analysis, showing that the proposed method is able to predict the magnetic flux density and EC loss precisely.

RESPONSE PROTOCOL TOOLBOX: OVERVIEW, STATUS UPDATE, AND RELATIONSHIP TO OTHER WATER SECURITY PRODUCTS

EPA Science Inventory

The Response Protocol Toolbox was released by USEPA to address the complex, multi-faceted challenges of a water utility's planning and response to the threat or act of intentional contamination of drinking water (1). The Toolbox contains guidance that may be adopted voluntarily,...

RESPONSE PROTOCOL TOOLBOX: OVERVIEW, STATUS UPDATE, AND RELATIONSHIP TO OTHER WATER SECURITY PRODUCTS

EPA Science Inventory

The Response Protocol Toolbox was released by USEPA to address the complex, multi-faceted challenges of a water utility's planning and response to the threat or act of intentional contamination of drinking water(1). The Toolbox contains guidance that may be adopted voluntarily, a...

RESPONSE PROTOCOL TOOLBOX OVERVIEW, STATUS UPDATE, AND RELATIONSHIP TO OTHER WATER SECURITY PRODUCTS

EPA Science Inventory

The Response Protocol Toolbox was released by USEPA to address the complex, multi-faceted challenges of a water utility's planning and response to the threat or act of intentional contamination of drinking water (1). The Toolbox contains guidance that may be adopted voluntarily,...

The Brain's Versatile Toolbox.

ERIC Educational Resources Information Center

Pinker, Steven

1997-01-01

Considers the role of evolution and natural selection in the functioning of the modern human brain. Natural selection equipped humans with a mental toolbox of intuitive theories about the world which were used to master rocks, tools, plants, animals, and one another. The same toolbox is used today to master the intellectual challenges of modern…

A toolbox for safety instrumented system evaluation based on improved continuous-time Markov chain

NASA Astrophysics Data System (ADS)

Wardana, Awang N. I.; Kurniady, Rahman; Pambudi, Galih; Purnama, Jaka; Suryopratomo, Kutut

2017-08-01

Safety instrumented system (SIS) is designed to restore a plant into a safe condition when pre-hazardous event is occur. It has a vital role especially in process industries. A SIS shall be meet with safety requirement specifications. To confirm it, SIS shall be evaluated. Typically, the evaluation is calculated by hand. This paper presents a toolbox for SIS evaluation. It is developed based on improved continuous-time Markov chain. The toolbox supports to detailed approach of evaluation. This paper also illustrates an industrial application of the toolbox to evaluate arch burner safety system of primary reformer. The results of the case study demonstrates that the toolbox can be used to evaluate industrial SIS in detail and to plan the maintenance strategy.

Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.

PubMed

Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-11-01

Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes. Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes.

SinCHet: a MATLAB toolbox for single cell heterogeneity analysis in cancer.

PubMed

Li, Jiannong; Smalley, Inna; Schell, Michael J; Smalley, Keiran S M; Chen, Y Ann

2017-09-15

Single-cell technologies allow characterization of transcriptomes and epigenomes for individual cells under different conditions and provide unprecedented resolution for researchers to investigate cellular heterogeneity in cancer. The SinCHet ( gle ell erogeneity) toolbox is developed in MATLAB and has a graphical user interface (GUI) for visualization and user interaction. It analyzes both continuous (e.g. mRNA expression) and binary omics data (e.g. discretized methylation data). The toolbox does not only quantify cellular heterogeneity using S hannon P rofile (SP) at different clonal resolutions but also detects heterogeneity differences using a D statistic between two populations. It is defined as the area under the P rofile of S hannon D ifference (PSD). This flexible tool provides a default clonal resolution using the change point of PSD detected by multivariate adaptive regression splines model; it also allows user-defined clonal resolutions for further investigation. This tool provides insights into emerging or disappearing clones between conditions, and enables the prioritization of biomarkers for follow-up experiments based on heterogeneity or marker differences between and/or within cell populations. The SinCHet software is freely available for non-profit academic use. The source code, example datasets, and the compiled package are available at http://labpages2.moffitt.org/chen/software/ . ann.chen@moffitt.org. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Using a Toolbox of Tailored Educational Lessons to Improve Fruit, Vegetable, and Physical Activity Behaviors among African American Women in California

ERIC Educational Resources Information Center

Backman, Desiree; Scruggs, Valarie; Atiedu, Akpene Ama; Bowie, Shene; Bye, Larry; Dennis, Angela; Hall, Melanie; Ossa, Alexandra; Wertlieb, Stacy; Foerster, Susan B.

2011-01-01

Objective: Evaluate the effectiveness of the "Fruit, Vegetable, and Physical Activity Toolbox for Community Educators" ("Toolbox"), an intervention originally designed for Spanish- and English-speaking audiences, in changing knowledge, attitudes, and behavior among low-income African American women. Design: Quasi-experimental…

Travel demand management : a toolbox of strategies to reduce single\\0x2010occupant vehicle trips and increase alternate mode usage in Arizona.

DOT National Transportation Integrated Search

2012-02-01

The report provides a suite of recommended strategies to reduce single-occupant vehicle traffic in the urban : areas of Phoenix and Tucson, Arizona, which are presented as a travel demand management toolbox. The : toolbox includes supporting research...

Proposal for the design of a zero gravity tool storage device

NASA Technical Reports Server (NTRS)

Stuckwisch, Sue; Carrion, Carlos A.; Phillips, Lee; Laughlin, Julia; Francois, Jason

1994-01-01

Astronauts frequently use a variety of hand tools during space missions, especially on repair missions. A toolbox is needed to allow storage and retrieval of tools with minimal difficulties. The toolbox must contain tools during launch, landing, and on-orbit operations. The toolbox will be used in the Shuttle Bay and therefore must withstand the hazardous space environment. The three main functions of the toolbox in space are: to protect the tools from the space environment and from damaging one another, to allow for quick, one-handed access to the tools; and to minimize the heat transfer between the astronaut's hand and the tools. This proposal explores the primary design issues associated with the design of the toolbox. Included are the customer and design specifications, global and refined function structures, possible solution principles, concept variants, and finally design recommendations.

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

JWST Wavefront Control Toolbox

NASA Technical Reports Server (NTRS)

Shin, Shahram Ron; Aronstein, David L.

2011-01-01

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

A CRISPR-Based Toolbox for Studying T Cell Signal Transduction

PubMed Central

Chi, Shen; Weiss, Arthur; Wang, Haopeng

2016-01-01

CRISPR/Cas9 system is a powerful technology to perform genome editing in a variety of cell types. To facilitate the application of Cas9 in mapping T cell signaling pathways, we generated a toolbox for large-scale genetic screens in human Jurkat T cells. The toolbox has three different Jurkat cell lines expressing distinct Cas9 variants, including wild-type Cas9, dCas9-KRAB, and sunCas9. We demonstrated that the toolbox allows us to rapidly disrupt endogenous gene expression at the DNA level and to efficiently repress or activate gene expression at the transcriptional level. The toolbox, in combination with multiple currently existing genome-wide sgRNA libraries, will be useful to systematically investigate T cell signal transduction using both loss-of-function and gain-of-function genetic screens. PMID:27057542

Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing

PubMed Central

Huth, Jacob; Masquelier, Timothée; Arleo, Angelo

2018-01-01

We developed Convis, a Python simulation toolbox for large scale neural populations which offers arbitrary receptive fields by 3D convolutions executed on a graphics card. The resulting software proves to be flexible and easily extensible in Python, while building on the PyTorch library (The Pytorch Project, 2017), which was previously used successfully in deep learning applications, for just-in-time optimization and compilation of the model onto CPU or GPU architectures. An alternative implementation based on Theano (Theano Development Team, 2016) is also available, although not fully supported. Through automatic differentiation, any parameter of a specified model can be optimized to approach a desired output which is a significant improvement over e.g., Monte Carlo or particle optimizations without gradients. We show that a number of models including even complex non-linearities such as contrast gain control and spiking mechanisms can be implemented easily. We show in this paper that we can in particular recreate the simulation results of a popular retina simulation software VirtualRetina (Wohrer and Kornprobst, 2009), with the added benefit of providing (1) arbitrary linear filters instead of the product of Gaussian and exponential filters and (2) optimization routines utilizing the gradients of the model. We demonstrate the utility of 3d convolution filters with a simple direction selective filter. Also we show that it is possible to optimize the input for a certain goal, rather than the parameters, which can aid the design of experiments as well as closed-loop online stimulus generation. Yet, Convis is more than a retina simulator. For instance it can also predict the response of V1 orientation selective cells. Convis is open source under the GPL-3.0 license and available from https://github.com/jahuth/convis/ with documentation at https://jahuth.github.io/convis/. PMID:29563867

Assessing Ecosystem Model Performance in Semiarid Systems

NASA Astrophysics Data System (ADS)

Thomas, A.; Dietze, M.; Scott, R. L.; Biederman, J. A.

2017-12-01

In ecosystem process modelling, comparing outputs to benchmark datasets observed in the field is an important way to validate models, allowing the modelling community to track model performance over time and compare models at specific sites. Multi-model comparison projects as well as models themselves have largely been focused on temperate forests and similar biomes. Semiarid regions, on the other hand, are underrepresented in land surface and ecosystem modelling efforts, and yet will be disproportionately impacted by disturbances such as climate change due to their sensitivity to changes in the water balance. Benchmarking models at semiarid sites is an important step in assessing and improving models' suitability for predicting the impact of disturbance on semiarid ecosystems. In this study, several ecosystem models were compared at a semiarid grassland in southwestern Arizona using PEcAn, or the Predictive Ecosystem Analyzer, an open-source eco-informatics toolbox ideal for creating the repeatable model workflows necessary for benchmarking. Models included SIPNET, DALEC, JULES, ED2, GDAY, LPJ-GUESS, MAESPA, CLM, CABLE, and FATES. Comparison between model output and benchmarks such as net ecosystem exchange (NEE) tended to produce high root mean square error and low correlation coefficients, reflecting poor simulation of seasonality and the tendency for models to create much higher carbon sources than observed. These results indicate that ecosystem models do not currently adequately represent semiarid ecosystem processes.

The Handover Toolbox: a knowledge exchange and training platform for improving patient care.

PubMed

Drachsler, Hendrik; Kicken, Wendy; van der Klink, Marcel; Stoyanov, Slavi; Boshuizen, Henny P A; Barach, Paul

2012-12-01

Safe and effective patient handovers remain a global organisational and training challenge. Limited evidence supports available handover training programmes. Customisable training is a promising approach to improve the quality and sustainability of handover training and outcomes. We present a Handover Toolbox designed in the context of the European HANDOVER Project. The Toolbox aims to support physicians, nurses, individuals in health professions training, medical educators and handover experts by providing customised handover training tools for different clinical needs and contexts. The Handover Toolbox uses the Technology Enhanced Learning Design Process (TEL-DP), which encompasses user requirements analysis; writing personas; group concept mapping; analysis of suitable software; plus, minus, interesting rating; and usability testing. TEL-DP is aligned with participatory design approaches and ensures development occurs in close collaboration with, and engagement of, key stakeholders. Application of TEL-DP confirmed that the ideal formats of handover training differs for practicing professionals versus individuals in health profession education programmes. Training experts from different countries differed in their views on the optimal content and delivery of training. Analysis of suitable software identified ready-to-use systems that provide required functionalities and can be further customised to users' needs. Interest rating and usability testing resulted in improved usability, navigation and uptake of the Handover Toolbox. The design of the Handover Toolbox was based on a carefully led stakeholder participatory design using the TEL-DP approach. The Toolbox supports a customisable learning approach that allows trainers to design training that addresses the specific information needs of the various target groups. We offer recommendations regarding the application of the Handover Toolbox to medical educators.

Integrating hidden Markov model and PRAAT: a toolbox for robust automatic speech transcription

NASA Astrophysics Data System (ADS)

Kabir, A.; Barker, J.; Giurgiu, M.

2010-09-01

An automatic time-aligned phone transcription toolbox of English speech corpora has been developed. Especially the toolbox would be very useful to generate robust automatic transcription and able to produce phone level transcription using speaker independent models as well as speaker dependent models without manual intervention. The system is based on standard Hidden Markov Models (HMM) approach and it was successfully experimented over a large audiovisual speech corpus namely GRID corpus. One of the most powerful features of the toolbox is the increased flexibility in speech processing where the speech community would be able to import the automatic transcription generated by HMM Toolkit (HTK) into a popular transcription software, PRAAT, and vice-versa. The toolbox has been evaluated through statistical analysis on GRID data which shows that automatic transcription deviates by an average of 20 ms with respect to manual transcription.

Building Interdisciplinary Research Models Through Interactive Education.

PubMed

Hessels, Amanda J; Robinson, Brian; O'Rourke, Michael; Begg, Melissa D; Larson, Elaine L

2015-12-01

Critical interdisciplinary research skills include effective communication with diverse disciplines and cultivating collaborative relationships. Acquiring these skills during graduate education may foster future interdisciplinary research quality and productivity. The project aim was to develop and evaluate an interactive Toolbox workshop approach within an interprofessional graduate level course to enhance student learning and skill in interdisciplinary research. We sought to examine the student experience of integrating the Toolbox workshop in modular format over the duration of a 14-week course. The Toolbox Health Sciences Instrument includes six modules that were introduced in a 110-minute dialogue session during the first class and then integrated into the course in a series of six individual workshops in three phases over the course of the semester. Seventeen students participated; the majority were nursing students. Three measures were used to assess project outcomes: pre-post intervention Toolbox survey, competency self-assessment, and a postcourse survey. All measures indicated the objectives were met by a change in survey responses, improved competencies, and favorable experience of the Toolbox modular intervention. Our experience indicates that incorporating this Toolbox modular approach into research curricula can enhance individual level scientific capacity, future interdisciplinary research project success, and ultimately impact on practice and policy. © 2015 Wiley Periodicals, Inc.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

FOLDER: A numerical tool to simulate the development of structures in layered media

NASA Astrophysics Data System (ADS)

Adamuszek, Marta; Dabrowski, Marcin; Schmid, Daniel W.

2015-04-01

FOLDER is a numerical toolbox for modelling deformation in layered media during layer parallel shortening or extension in two dimensions. FOLDER builds on MILAMIN [1], a finite element method based mechanical solver, with a range of utilities included from the MUTILS package [2]. Numerical mesh is generated using the Triangle software [3]. The toolbox includes features that allow for: 1) designing complex structures such as multi-layer stacks, 2) accurately simulating large-strain deformation of linear and non-linear viscous materials, 3) post-processing of various physical fields such as velocity (total and perturbing), rate of deformation, finite strain, stress, deviatoric stress, pressure, apparent viscosity. FOLDER is designed to ensure maximum flexibility to configure model geometry, define material parameters, specify range of numerical parameters in simulations and choose the plotting options. FOLDER is an open source MATLAB application and comes with a user friendly graphical interface. The toolbox additionally comprises an educational application that illustrates various analytical solutions of growth rates calculated for the cases of folding and necking of a single layer with interfaces perturbed with a single sinusoidal waveform. We further derive two novel analytical expressions for the growth rate in the cases of folding and necking of a linear viscous layer embedded in a linear viscous medium of a finite thickness. We use FOLDER to test the accuracy of single-layer folding simulations using various 1) spatial and temporal resolutions, 2) time integration schemes, and 3) iterative algorithms for non-linear materials. The accuracy of the numerical results is quantified by: 1) comparing them to analytical solution, if available, or 2) running convergence tests. As a result, we provide a map of the most optimal choice of grid size, time step, and number of iterations to keep the results of the numerical simulations below a given error for a given time integration scheme. We also demonstrate that Euler and Leapfrog time integration schemes are not recommended for any practical use. Finally, the capabilities of the toolbox are illustrated based on two examples: 1) shortening of a synthetic multi-layer sequence and 2) extension of a folded quartz vein embedded in phyllite from Sprague Upper Reservoir (example discussed by Sherwin and Chapple [4]). The latter example demonstrates that FOLDER can be successfully used for reverse modelling and mechanical restoration. [1] Dabrowski, M., Krotkiewski, M., and Schmid, D. W., 2008, MILAMIN: MATLAB-based finite element method solver for large problems. Geochemistry Geophysics Geosystems, vol. 9. [2] Krotkiewski, M. and Dabrowski M., 2010 Parallel symmetric sparse matrix-vector product on scalar multi-core cpus. Parallel Computing, 36(4):181-198 [3] Shewchuk, J. R., 1996, Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator, In: Applied Computational Geometry: Towards Geometric Engineering'' (Ming C. Lin and Dinesh Manocha, editors), Vol. 1148 of Lecture Notes in Computer Science, pp. 203-222, Springer-Verlag, Berlin [4] Sherwin, J.A., Chapple, W.M., 1968. Wavelengths of single layer folds - a Comparison between theory and Observation. American Journal of Science 266 (3), p. 167-179

Toolbox for the design of LiNbO3-based passive and active integrated quantum circuits

NASA Astrophysics Data System (ADS)

Sharapova, P. R.; Luo, K. H.; Herrmann, H.; Reichelt, M.; Meier, T.; Silberhorn, C.

2017-12-01

We present and discuss perspectives of current developments on advanced quantum optical circuits monolithically integrated in the lithium niobate platform. A set of basic components comprising photon pair sources based on parametric down conversion (PDC), passive routing elements and active electro-optically controllable switches and polarisation converters are building blocks of a toolbox which is the basis for a broad range of diverse quantum circuits. We review the state-of-the-art of these components and provide models that properly describe their performance in quantum circuits. As an example for applications of these models we discuss design issues for a circuit providing on-chip two-photon interference. The circuit comprises a PDC section for photon pair generation followed by an actively controllable modified mach-Zehnder structure for observing Hong-Ou-Mandel interference. The performance of such a chip is simulated theoretically by taking even imperfections of the properties of the individual components into account.

Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox

PubMed Central

Sato, João R.; Basilio, Rodrigo; Paiva, Fernando F.; Garrido, Griselda J.; Bramati, Ivanei E.; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge

2013-01-01

The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available. PMID:24312569

National Water-Quality Assessment (NAWQA) Area-Characterization Toolbox

USGS Publications Warehouse

Price, Curtis

2010-01-01

This is release 1.0 of the National Water-Quality Assessment (NAWQA) Area-Characterization Toolbox. These tools are designed to be accessed using ArcGIS Desktop software (versions 9.3 and 9.3.1). The toolbox is composed of a collection of custom tools that implement geographic information system (GIS) techniques used by the NAWQA Program to characterize aquifer areas, drainage basins, and sampled wells.

Soil Monitor: an open source web application for real-time soil sealing monitoring and assessment

NASA Astrophysics Data System (ADS)

Langella, Giuliano; Basile, Angelo; Giannecchini, Simone; Iamarino, Michela; Munafò, Michele; Terribile, Fabio

2016-04-01

Soil sealing is one of the most important causes of land degradation and desertification. In Europe, soil covered by impermeable materials has increased by about 80% from the Second World War till nowadays, while population has only grown by one third. There is an increasing concern at the high political levels about the need to attenuate imperviousness itself and its effects on soil functions. European Commission promulgated a roadmap (COM(2011) 571) by which the net land take would be zero by 2050. Furthermore, European Commission also published a report in 2011 providing best practices and guidelines for limiting soil sealing and imperviousness. In this scenario, we developed an open source and an open source based Soil Sealing Geospatial Cyber Infrastructure (SS-GCI) named as "Soil Monitor". This tool merges a webGIS with parallel geospatial computation in a fast and dynamic fashion in order to provide real-time assessments of soil sealing at high spatial resolution (20 meters and below) over the whole Italy. Common open source webGIS packages are used to implement both the data management and visualization infrastructures, such as GeoServer and MapStore. The high-speed geospatial computation is ensured by a GPU parallelism using the CUDA (Computing Unified Device Architecture) framework by NVIDIA®. This kind of parallelism required the writing - from scratch - all codes needed to fulfil the geospatial computation built behind the soil sealing toolbox. The combination of GPU computing with webGIS infrastructures is relatively novel and required particular attention at the Java-CUDA programming interface. As a result, Soil Monitor is smart because it can perform very high time-consuming calculations (querying for instance an Italian administrative region as area of interest) in less than one minute. The web application is embedded in a web browser and nothing must be installed before using it. Potentially everybody can use it, but the main targets are the stakeholders dealing with sealing, such as policy makers, land owners and asphalt/cement companies. As a matter of fact, Soil Monitor can be used to improve the spatial planning therefore limiting the progression of disordered soil sealing which causes both the direct loss of soils due to imperviousness but also the indirect loss caused by fragmentation of soils (which has different negative effects on the durability of soil functions, such as habitat corridors). Further, in a future version, Soil Monitor would estimate the best location for a new building or help compensating soil losses by actions in other areas to offset drawbacks at zero. The presented SS-GCI dealing with soil sealing - if opportunely scaled - would aid the implementation of best practices for limiting soil sealing or mitigating its effects on soil functions.

SOCIB Glider toolbox: from sensor to data repository

NASA Astrophysics Data System (ADS)

Pau Beltran, Joan; Heslop, Emma; Ruiz, Simón; Troupin, Charles; Tintoré, Joaquín

2015-04-01

Nowadays in oceanography, gliders constitutes a mature, cost-effective technology for the acquisition of measurements independently of the sea state (unlike ships), providing subsurface data during sustained periods, including extreme weather events. The SOCIB glider toolbox is a set of MATLAB/Octave scripts and functions developed in order to manage the data collected by a glider fleet. They cover the main stages of the data management process, both in real-time and delayed-time modes: metadata aggregation, downloading, processing, and automatic generation of data products and figures. The toolbox is distributed under the GNU licence (http://www.gnu.org/copyleft/gpl.html) and is available at http://www.socib.es/users/glider/glider_toolbox.

A Data Analysis Toolbox for Modeling the Global Food-Energy-Water Nexus

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Sadegh, M.; Mallakpour, I.

2017-12-01

Water, Food and energy systems are highly interconnected. More than seventy percent of global water resource is used for food production. Water withdrawal, purification, and transfer systems are energy intensive. Furthermore, energy generation strongly depends on water availability. Therefore, considering the interactions in the nexus of water, food and energy is crucial for sustainable management of available resources. In this presentation, we introduce a user-friendly data analysis toolbox that mines the available global data on food, energy and water, and analyzes their interactions. This toolbox provides estimates of water footprint for a wide range of food types in different countries and also approximates the required energy and water resources. The toolbox also provides estimates of the corresponding emissions and biofuel production of different crops. In summary, this toolbox allows evaluating dependencies of the food, energy, and water systems at the country scale. We present global analysis of the interactions between water, food and energy from different perspectives including efficiency and diversity of resources use.

Evaluation of Proteus as a Tool for the Rapid Development of Models of Hydrologic Systems

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Farthing, M. W.; Kees, C. E.; Miller, C. T.

2013-12-01

Models of modern hydrologic systems can be complex and involve a variety of operators with varying character. The goal is to implement approximations of such models that are both efficient for the developer and computationally efficient, which is a set of naturally competing objectives. Proteus is a Python-based toolbox that supports prototyping of model formulations as well as a wide variety of modern numerical methods and parallel computing. We used Proteus to develop numerical approximations for three models: Richards' equation, a brine flow model derived using the Thermodynamically Constrained Averaging Theory (TCAT), and a multiphase TCAT-based tumor growth model. For Richards' equation, we investigated discontinuous Galerkin solutions with higher order time integration based on the backward difference formulas. The TCAT brine flow model was implemented using Proteus and a variety of numerical methods were compared to hand coded solutions. Finally, an existing tumor growth model was implemented in Proteus to introduce more advanced numerics and allow the code to be run in parallel. From these three example models, Proteus was found to be an attractive open-source option for rapidly developing high quality code for solving existing and evolving computational science models.

Session 6: Dynamic Modeling and Systems Analysis

NASA Technical Reports Server (NTRS)

Csank, Jeffrey; Chapman, Jeffryes; May, Ryan

2013-01-01

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

DoOR 2.0 - Comprehensive Mapping of Drosophila melanogaster Odorant Responses

NASA Astrophysics Data System (ADS)

Münch, Daniel; Galizia, C. Giovanni

2016-02-01

Odors elicit complex patterns of activated olfactory sensory neurons. Knowing the complete olfactome, i.e. the responses in all sensory neurons for all relevant odorants, is desirable to understand olfactory coding. The DoOR project combines all available Drosophila odorant response data into a single consensus response matrix. Since its first release many studies were published: receptors were deorphanized and several response profiles were expanded. In this study, we add unpublished data to the odor-response profiles for four odorant receptors (Or10a, Or42b, Or47b, Or56a). We deorphanize Or69a, showing a broad response spectrum with the best ligands including 3-hydroxyhexanoate, alpha-terpineol, 3-octanol and linalool. We include all of these datasets into DoOR, provide a comprehensive update of both code and data, and new tools for data analyses and visualizations. The DoOR project has a web interface for quick queries (http://neuro.uni.kn/DoOR), and a downloadable, open source toolbox written in R, including all processed and original datasets. DoOR now gives reliable odorant-responses for nearly all Drosophila olfactory responding units, listing 693 odorants, for a total of 7381 data points.

GOCE User Toolbox and Tutorial

NASA Astrophysics Data System (ADS)

Benveniste, Jérôme; Knudsen, Per

2016-07-01

The GOCE User Toolbox GUT is a compilation of tools for the utilisation and analysis of GOCE Level 2 products. GUT support applications in Geodesy, Oceanography and Solid Earth Physics. The GUT Tutorial provides information and guidance in how to use the toolbox for a variety of applications. GUT consists of a series of advanced computer routines that carry out the required computations. It may be used on Windows PCs, UNIX/Linux Workstations, and Mac. The toolbox is supported by The GUT Algorithm Description and User Guide and The GUT Install Guide. A set of a-priori data and models are made available as well. Without any doubt the development of the GOCE user toolbox have played a major role in paving the way to successful use of the GOCE data for oceanography. The GUT version 2.2 was released in April 2014 and beside some bug-fixes it adds the capability for the computation of Simple Bouguer Anomaly (Solid-Earth). During this fall a new GUT version 3 has been released. GUTv3 was further developed through a collaborative effort where the scientific communities participate aiming on an implementation of remaining functionalities facilitating a wider span of research in the fields of Geodesy, Oceanography and Solid earth studies. Accordingly, the GUT version 3 has: - An attractive and easy to use Graphic User Interface (GUI) for the toolbox, - Enhance the toolbox with some further software functionalities such as to facilitate the use of gradients, anisotropic diffusive filtering and computation of Bouguer and isostatic gravity anomalies. - An associated GUT VCM tool for analyzing the GOCE variance covariance matrices.

Stochastic theory of non-Markovian open quantum system

NASA Astrophysics Data System (ADS)

Zhao, Xinyu

In this thesis, a stochastic approach to solving non-Markovian open quantum system called "non-Markovian quantum state diffusion" (NMQSD) approach is discussed in details. The NMQSD approach can serve as an analytical and numerical tool to study the dynamics of the open quantum systems. We explore three main topics of the NMQSD approach. First, we extend the NMQSD approach to many-body open systems such as two-qubit system and coupled N-cavity system. Based on the exact NMQSD equations and the corresponding master equations, we investigate several interesting non-Markovian features due to the memory effect of the environment such as the entanglement generation in two-qubit system and the coherence and entanglement transfer between cavities. Second, we extend the original NMQSD approach to the case that system is coupled to a fermionic bath or a spin bath. By introducing the anti-commutative Grassmann noise and the fermionic coherent state, we derive a fermionic NMQSD equation and the corresponding master equation. The fermionic NMQSD is illustrated by several examples. In a single qubit dissipative example, we have explicitly demonstrated that the NMQSD approach and the ordinary quantum mechanics give rise to the exactly same results. We also show the difference between fermionic bath and bosonic bath. Third, we combine the bosonic and fermionic NMQSD approach to develop a unified NMQSD approach to study the case that an open system is coupled to a bosonic bath and a fermionic bath simultaneously. For all practical purposes, we develop a set of useful computer programs (NMQSD Toolbox) to implement the NMQSD equation in realistic computations. In particular, we develop an algorithm to calculate the exact O operator involved in the NMQSD equation. The NMQSD toolbox is designed to be user friendly, so it will be especially valuable for a non-expert who has interest to employ the NMQSD equation to solve a practical problem. Apart from the central topics on the NMQSD approach, we also study the environment-assisted error correction (EAEC) scheme. We have proposed two new schemes beyond the original EAEC scheme. Our schemes can be used to recover an unknown entangled initial state for a dephasing channel and recover an arbitrary unknown initial state for a dissipative channel using a generalized quantum measurement.

Scanning quantum gas atom chip microscopy of strongly correlated and topologically nontrivial materials

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

Lev, Benjamin

The SQCRAMscope, Scanning Quantum Cryogenic Atom Microscope, is a novel scanning probe microscope we developed during this DOE fund period. It is now capable of imaging transport in cryogenically cooled solid-state samples, as we have recently demonstrated with iron-based pnictide superconductors. As such, it opens a new frontier in the quantum-based metrology of materials and is the first example of the direct marriage of ultracold AMO physics with condensed matter physics. We predict the SQCRAMscope will become an important element in the toolbox for exploring strongly correlated and topologically nontrivial materials.

Air Sensor Toolbox

EPA Pesticide Factsheets

Air Sensor Toolbox provides information to citizen scientists, researchers and developers interested in learning more about new lower-cost compact air sensor technologies and tools for measuring air quality.

Demonstration of a Fractured Rock Geophysical Toolbox (FRGT) for Characterization and Monitoring of DNAPL Biodegradation in Fractured Rock Aquifers

DTIC Science & Technology

2016-01-01

USER’S GUIDE Demonstration of a Fractured Rock Geophysical Toolbox (FRGT) for Characterization and Monitoring of DNAPL Biodegradation in...Toolbox (FRGT) for Characterization and Monitoring of DNAPL Biodegradation in Fractured Rock Aquifers F.D. Day-Lewis, C.D. Johnson, J.H. Williams, C.L...are doomed to failure. DNAPL biodegradation charactrization and monitoring, remediation, fractured rock aquifers. Unclassified Unclassified UU UL 6

Toolbox for Renewable Energy Project Development

EPA Pesticide Factsheets

The Toolbox for Renewable Energy Project Development summarizes key project development issues, addresses how to overcome major hurdles, and provides a curated directory of project development resources.

Acrylamide mitigation strategies: critical appraisal of the FoodDrinkEurope toolbox.

PubMed

Palermo, M; Gökmen, V; De Meulenaer, B; Ciesarová, Z; Zhang, Y; Pedreschi, F; Fogliano, V

2016-06-15

FoodDrinkEurope Federation recently released the latest version of the Acrylamide Toolbox to support manufacturers in acrylamide reduction activities giving indication about the possible mitigation strategies. The Toolbox is intended for small and medium size enterprises with limited R&D resources, however no comments about the pro and cons of the different measures were provided to advise the potential users. Experts of the field are aware that not all the strategies proposed have equal value in terms of efficacy and cost/benefit ratio. This consideration prompted us to provide a qualitative science-based ranking of the mitigation strategies proposed in the acrylamide Toolbox, focusing on bakery and fried potato products. Five authors from different geographical areas having a publication record on acrylamide mitigation strategies worked independently ranking the efficacy of the acrylamide mitigation strategies taking into account three key parameters: (i) reduction rate; (ii) side effects; and (iii) applicability and economic impact. On the basis of their own experience and considering selected literature of the last ten years, the authors scored for each key parameter the acrylamide mitigation strategies proposed in the Toolbox. As expected, all strategies selected in the Toolbox turned out to be useful, however, not at the same level. The use of enzyme asparaginase and the selection of low sugar varieties were considered the best mitigation strategies in bakery and in potato products, respectively. According to authors' opinion most of the other mitigation strategies, although effective, either have relevant side effects on the sensory profile of the products, or they are not easy to implement in industrial production. The final outcome was a science based commented ranking which can enrich the acrylamide Toolbox supporting individual manufacturer in taking the best actions to reduce the acrylamide content in their specific production context.

GOCE User Toolbox and Tutorial

NASA Astrophysics Data System (ADS)

Knudsen, Per; Benveniste, Jerome

2017-04-01

The GOCE User Toolbox GUT is a compilation of tools for the utilisation and analysis of GOCE Level 2 products.
GUT support applications in Geodesy, Oceanography and Solid Earth Physics. The GUT Tutorial provides information
and guidance in how to use the toolbox for a variety of applications. GUT consists of a series of advanced
computer routines that carry out the required computations. It may be used on Windows PCs, UNIX/Linux Workstations,
and Mac. The toolbox is supported by The GUT Algorithm Description and User Guide and The GUT
Install Guide. A set of a-priori data and models are made available as well. Without any doubt the development
of the GOCE user toolbox have played a major role in paving the way to successful use of the GOCE data for
oceanography. The GUT version 2.2 was released in April 2014 and beside some bug-fixes it adds the capability for the computation of Simple Bouguer Anomaly (Solid-Earth). During this fall a new GUT version 3 has been released. GUTv3 was further developed through a collaborative effort where the scientific communities participate aiming
on an implementation of remaining functionalities facilitating a wider span of research in the fields of Geodesy,
Oceanography and Solid earth studies.
Accordingly, the GUT version 3 has:
 - An attractive and easy to use Graphic User Interface (GUI) for the toolbox,
 - Enhance the toolbox with some further software functionalities such as to facilitate the use of gradients,
anisotropic diffusive filtering and computation of Bouguer and isostatic gravity anomalies.
 - An associated GUT VCM tool for analyzing the GOCE variance covariance matrices.

GOCE User Toolbox and Tutorial

NASA Astrophysics Data System (ADS)

Knudsen, Per; Benveniste, Jerome; Team Gut

2016-04-01

The GOCE User Toolbox GUT is a compilation of tools for the utilisation and analysis of GOCE Level 2 products.
GUT support applications in Geodesy, Oceanography and Solid Earth Physics. The GUT Tutorial provides information
and guidance in how to use the toolbox for a variety of applications. GUT consists of a series of advanced
computer routines that carry out the required computations. It may be used on Windows PCs, UNIX/Linux Workstations,
and Mac. The toolbox is supported by The GUT Algorithm Description and User Guide and The GUT
Install Guide. A set of a-priori data and models are made available as well. Without any doubt the development
of the GOCE user toolbox have played a major role in paving the way to successful use of the GOCE data for
oceanography. The GUT version 2.2 was released in April 2014 and beside some bug-fixes it adds the capability for the computation of Simple Bouguer Anomaly (Solid-Earth). During this fall a new GUT version 3 has been released. GUTv3 was further developed through a collaborative effort where the scientific communities participate aiming
on an implementation of remaining functionalities facilitating a wider span of research in the fields of Geodesy,
Oceanography and Solid earth studies.
Accordingly, the GUT version 3 has:
 - An attractive and easy to use Graphic User Interface (GUI) for the toolbox,
 - Enhance the toolbox with some further software functionalities such as to facilitate the use of gradients,
anisotropic diffusive filtering and computation of Bouguer and isostatic gravity anomalies.
 - An associated GUT VCM tool for analyzing the GOCE variance covariance matrices.

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

PubMed

Lawhern, Vernon; Hairston, W David; Robbins, Kay

2013-01-01

Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

PubMed Central

Lawhern, Vernon; Hairston, W. David; Robbins, Kay

2013-01-01

Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration. PMID:23638169

A preclinical cognitive test battery to parallel the National Institute of Health Toolbox in humans: bridging the translational gap.

PubMed

Snigdha, Shikha; Milgram, Norton W; Willis, Sherry L; Albert, Marylin; Weintraub, S; Fortin, Norbert J; Cotman, Carl W

2013-07-01

A major goal of animal research is to identify interventions that can promote successful aging and delay or reverse age-related cognitive decline in humans. Recent advances in standardizing cognitive assessment tools for humans have the potential to bring preclinical work closer to human research in aging and Alzheimer's disease. The National Institute of Health (NIH) has led an initiative to develop a comprehensive Toolbox for Neurologic Behavioral Function (NIH Toolbox) to evaluate cognitive, motor, sensory and emotional function for use in epidemiologic and clinical studies spanning 3 to 85 years of age. This paper aims to analyze the strengths and limitations of animal behavioral tests that can be used to parallel those in the NIH Toolbox. We conclude that there are several paradigms available to define a preclinical battery that parallels the NIH Toolbox. We also suggest areas in which new tests may benefit the development of a comprehensive preclinical test battery for assessment of cognitive function in animal models of aging and Alzheimer's disease. Copyright © 2013 Elsevier Inc. All rights reserved.

A preclinical cognitive test battery to parallel the National Institute of Health Toolbox in humans: bridging the translational gap

PubMed Central

Snigdha, Shikha; Milgram, Norton W.; Willis, Sherry L.; Albert, Marylin; Weintraub, S.; Fortin, Norbert J.; Cotman, Carl W.

2013-01-01

A major goal of animal research is to identify interventions that can promote successful aging and delay or reverse age-related cognitive decline in humans. Recent advances in standardizing cognitive assessment tools for humans have the potential to bring preclinical work closer to human research in aging and Alzheimer’s disease. The National Institute of Health (NIH) has led an initiative to develop a comprehensive Toolbox for Neurologic Behavioral Function (NIH Toolbox) to evaluate cognitive, motor, sensory and emotional function for use in epidemiologic and clinical studies spanning 3 to 85 years of age. This paper aims to analyze the strengths and limitations of animal behavioral tests that can be used to parallel those in the NIH Toolbox. We conclude that there are several paradigms available to define a preclinical battery that parallels the NIH Toolbox. We also suggest areas in which new tests may benefit the development of a comprehensive preclinical test battery for assessment of cognitive function in animal models of aging and Alzheimer’s disease. PMID:23434040

A GIS tool for two-dimensional glacier-terminus change tracking

NASA Astrophysics Data System (ADS)

Urbanski, Jacek Andrzej

2018-02-01

This paper presents a Glacier Termini Tracking (GTT) toolbox for the two-dimensional analysis of glacier-terminus position changes. The input consists of a vector layer with several termini lines relating to the same glacier at different times. The output layers allow analyses to be conducted of glacier-terminus retreats, changes in retreats over time and along the ice face, and glacier-terminus fluctuations over time. The application of three tools from the toolbox is demonstrated via the analysis of eight glacier-terminus retreats and fluctuations at the Hornsund fjord in south Svalbard. It is proposed that this toolbox may also be useful in the study of other line features that change over time, like coastlines and rivers. The toolbox has been coded in Python and runs via ArcGIS.

The GMT/MATLAB Toolbox

NASA Astrophysics Data System (ADS)

Wessel, Paul; Luis, Joaquim F.

2017-02-01

The GMT/MATLAB toolbox is a basic interface between MATLAB® (or Octave) and GMT, the Generic Mapping Tools, which allows MATLAB users full access to all GMT modules. Data may be passed between the two programs using intermediate MATLAB structures that organize the metadata needed; these are produced when GMT modules are run. In addition, standard MATLAB matrix data can be used directly as input to GMT modules. The toolbox improves interoperability between two widely used tools in the geosciences and extends the capability of both tools: GMT gains access to the powerful computational capabilities of MATLAB while the latter gains the ability to access specialized gridding algorithms and can produce publication-quality PostScript-based illustrations. The toolbox is available on all platforms and may be downloaded from the GMT website.

An Open-Source Galaxy Redshift Survey Simulator for next-generation Large Scale Structure Surveys

NASA Astrophysics Data System (ADS)

Seijak, Uros

Galaxy redshift surveys produce three-dimensional maps of the galaxy distribution. On large scales these maps trace the underlying matter fluctuations in a relatively simple manner, so that the properties of the primordial fluctuations along with the overall expansion history and growth of perturbations can be extracted. The BAO standard ruler method to measure the expansion history of the universe using galaxy redshift surveys is thought to be robust to observational artifacts and understood theoretically with high precision. These same surveys can offer a host of additional information, including a measurement of the growth rate of large scale structure through redshift space distortions, the possibility of measuring the sum of neutrino masses, tighter constraints on the expansion history through the Alcock-Paczynski effect, and constraints on the scale-dependence and non-Gaussianity of the primordial fluctuations. Extracting this broadband clustering information hinges on both our ability to minimize and subtract observational systematics to the observed galaxy power spectrum, and our ability to model the broadband behavior of the observed galaxy power spectrum with exquisite precision. Rapid development on both fronts is required to capitalize on WFIRST's data set. We propose to develop an open-source computational toolbox that will propel development in both areas by connecting large scale structure modeling and instrument and survey modeling with the statistical inference process. We will use the proposed simulator to both tailor perturbation theory and fully non-linear models of the broadband clustering of WFIRST galaxies and discover novel observables in the non-linear regime that are robust to observational systematics and able to distinguish between a wide range of spatial and dynamic biasing models for the WFIRST galaxy redshift survey sources. We have demonstrated the utility of this approach in a pilot study of the SDSS-III BOSS galaxies, in which we improved the redshift space distortion growth rate measurement precision by a factor of 2.5 using customized clustering statistics in the non-linear regime that were immunized against observational systematics. We look forward to addressing the unique challenges of modeling and empirically characterizing the WFIRST galaxies and observational systematics.

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

DTIC Science & Technology

2013-04-24

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals Vernon...datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal . We have developed...As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis.

PubMed

Liu, Gang; Cheng, Kai; Lo, Chi Y; Li, Jun; Qu, Jun; Neelamegham, Sriram

2017-11-01

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MS n proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MS n data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MS n spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.

PubMed

Birkel, Garrett W; Ghosh, Amit; Kumar, Vinay S; Weaver, Daniel; Ando, David; Backman, Tyler W H; Arkin, Adam P; Keasling, Jay D; Martín, Héctor García

2017-04-05

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13 C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

DOE PAGES

Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.; ...

2017-04-05

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.« less

Rugged: an operational, open-source solution for Sentinel-2 mapping

NASA Astrophysics Data System (ADS)

Maisonobe, Luc; Seyral, Jean; Prat, Guylaine; Guinet, Jonathan; Espesset, Aude

2015-10-01

When you map the entire Earth every 5 days with the aim of generating high-quality time series over land, there is no room for geometrical error: the algorithms have to be stable, reliable, and precise. Rugged, a new open-source library for pixel geolocation, is at the geometrical heart of the operational processing for Sentinel-2. Rugged performs sensor-to-terrain mapping taking into account ground Digital Elevation Models, Earth rotation with all its small irregularities, on-board sensor pixel individual lines-of-sight, spacecraft motion and attitude, and all significant physical effects. It provides direct and inverse location, i.e. it allows the accurate computation of which ground point is viewed from a specific pixel in a spacecraft instrument, and conversely which pixel will view a specified ground point. Direct and inverse location can be used to perform full ortho-rectification of images and correlation between sensors observing the same area. Implemented as an add-on for Orekit (Orbits Extrapolation KIT; a low-level space dynamics library), Rugged also offers the possibility of simulating satellite motion and attitude auxiliary data using Orekit's full orbit propagation capability. This is a considerable advantage for test data generation and mission simulation activities. Together with the Orfeo ToolBox (OTB) image processing library, Rugged provides the algorithmic core of Sentinel-2 Instrument Processing Facilities. The S2 complex viewing model - with 12 staggered push-broom detectors and 13 spectral bands - is built using Rugged objects, enabling the computation of rectification grids for mapping between cartographic and focal plane coordinates. These grids are passed to the OTB library for further image resampling, thus completing the ortho-rectification chain. Sentinel-2 stringent operational requirements to process several terabytes of data per week represented a tough challenge, though one that was well met by Rugged in terms of the robustness and performance of the library.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

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

Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.« less

A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings

PubMed Central

Magri, Cesare; Whittingstall, Kevin; Singh, Vanessa; Logothetis, Nikos K; Panzeri, Stefano

2009-01-01

Background Information theory is an increasingly popular framework for studying how the brain encodes sensory information. Despite its widespread use for the analysis of spike trains of single neurons and of small neural populations, its application to the analysis of other types of neurophysiological signals (EEGs, LFPs, BOLD) has remained relatively limited so far. This is due to the limited-sampling bias which affects calculation of information, to the complexity of the techniques to eliminate the bias, and to the lack of publicly available fast routines for the information analysis of multi-dimensional responses. Results Here we introduce a new C- and Matlab-based information theoretic toolbox, specifically developed for neuroscience data. This toolbox implements a novel computationally-optimized algorithm for estimating many of the main information theoretic quantities and bias correction techniques used in neuroscience applications. We illustrate and test the toolbox in several ways. First, we verify that these algorithms provide accurate and unbiased estimates of the information carried by analog brain signals (i.e. LFPs, EEGs, or BOLD) even when using limited amounts of experimental data. This test is important since existing algorithms were so far tested primarily on spike trains. Second, we apply the toolbox to the analysis of EEGs recorded from a subject watching natural movies, and we characterize the electrodes locations, frequencies and signal features carrying the most visual information. Third, we explain how the toolbox can be used to break down the information carried by different features of the neural signal into distinct components reflecting different ways in which correlations between parts of the neural signal contribute to coding. We illustrate this breakdown by analyzing LFPs recorded from primary visual cortex during presentation of naturalistic movies. Conclusion The new toolbox presented here implements fast and data-robust computations of the most relevant quantities used in information theoretic analysis of neural data. The toolbox can be easily used within Matlab, the environment used by most neuroscience laboratories for the acquisition, preprocessing and plotting of neural data. It can therefore significantly enlarge the domain of application of information theory to neuroscience, and lead to new discoveries about the neural code. PMID:19607698

A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings.

PubMed

Magri, Cesare; Whittingstall, Kevin; Singh, Vanessa; Logothetis, Nikos K; Panzeri, Stefano

2009-07-16

Information theory is an increasingly popular framework for studying how the brain encodes sensory information. Despite its widespread use for the analysis of spike trains of single neurons and of small neural populations, its application to the analysis of other types of neurophysiological signals (EEGs, LFPs, BOLD) has remained relatively limited so far. This is due to the limited-sampling bias which affects calculation of information, to the complexity of the techniques to eliminate the bias, and to the lack of publicly available fast routines for the information analysis of multi-dimensional responses. Here we introduce a new C- and Matlab-based information theoretic toolbox, specifically developed for neuroscience data. This toolbox implements a novel computationally-optimized algorithm for estimating many of the main information theoretic quantities and bias correction techniques used in neuroscience applications. We illustrate and test the toolbox in several ways. First, we verify that these algorithms provide accurate and unbiased estimates of the information carried by analog brain signals (i.e. LFPs, EEGs, or BOLD) even when using limited amounts of experimental data. This test is important since existing algorithms were so far tested primarily on spike trains. Second, we apply the toolbox to the analysis of EEGs recorded from a subject watching natural movies, and we characterize the electrodes locations, frequencies and signal features carrying the most visual information. Third, we explain how the toolbox can be used to break down the information carried by different features of the neural signal into distinct components reflecting different ways in which correlations between parts of the neural signal contribute to coding. We illustrate this breakdown by analyzing LFPs recorded from primary visual cortex during presentation of naturalistic movies. The new toolbox presented here implements fast and data-robust computations of the most relevant quantities used in information theoretic analysis of neural data. The toolbox can be easily used within Matlab, the environment used by most neuroscience laboratories for the acquisition, preprocessing and plotting of neural data. It can therefore significantly enlarge the domain of application of information theory to neuroscience, and lead to new discoveries about the neural code.

Improving student comprehension of the interconnectivity of the hydrologic cycle with a novel 'hydrology toolbox', integrated watershed model, and companion textbook

NASA Astrophysics Data System (ADS)

Huning, L. S.; Margulis, S. A.

2013-12-01

Concepts in introductory hydrology courses are often taught in the context of process-based modeling that ultimately is integrated into a watershed model. In an effort to reduce the learning curve associated with applying hydrologic concepts to real-world applications, we developed and incorporated a 'hydrology toolbox' that complements a new, companion textbook into introductory undergraduate hydrology courses. The hydrology toolbox contains the basic building blocks (functions coded in MATLAB) for an integrated spatially-distributed watershed model that makes hydrologic topics (e.g. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) more user-friendly and accessible for students. The toolbox functions can be used in a modular format so that students can study individual hydrologic processes and become familiar with the hydrology toolbox. This approach allows such courses to emphasize understanding and application of hydrologic concepts rather than computer coding or programming. While topics in introductory hydrology courses are often introduced and taught independently or semi-independently, they are inherently interconnected. These toolbox functions are therefore linked together at the end of the course to reinforce a holistic understanding of how these hydrologic processes are measured, interconnected, and modeled. They are integrated into a spatially-distributed watershed model or numerical laboratory where students can explore a range of topics such as rainfall-runoff modeling, urbanization, deforestation, watershed response to changes in parameters or forcings, etc. Model output can readily be visualized and analyzed by students to understand watershed response in a real river basin or a simple 'toy' basin. These tools complement the textbook, each of which has been well received by students in multiple hydrology courses with various disciplinary backgrounds. The same governing equations that students have studied in the textbook and used in the toolbox have been encapsulated in the watershed model. Therefore, the combination of the hydrology toolbox, integrated watershed model, and textbook tends to eliminate the potential disconnect between process-based modeling and an 'off-the-shelf' watershed model.

The Basic Radar Altimetry Toolbox for Sentinel 3 Users

NASA Astrophysics Data System (ADS)

Lucas, Bruno; Rosmorduc, Vinca; Niemeijer, Sander; Bronner, Emilie; Dinardo, Salvatore; Benveniste, Jérôme

2013-04-01

The Basic Radar Altimetry Toolbox (BRAT) is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data. This project started in 2006 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d'Etudes Spatiales). The latest version of the software, 3.1, was released on March 2012. The tools enable users to interact with the most common altimetry data formats, being the most used way, the Graphical User Interface (BratGui). This GUI is a front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with Matlab/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. The BratDisplay (graphic visualizer) can be launched from BratGui, or used as a stand-alone tool to visualize netCDF files - it is distributed with another ESA toolbox (GUT) as the visualizer. The most frequent uses of BRAT are teaching remote sensing, altimetry data reading (all missions from ERS-1 to Saral and soon Sentinel-3), quick data visualization/export and simple computation on the data fields. BRAT can be used for importing data and having a quick look at his contents, with several different types of plotting available. One can also use it to translate the data into other formats such as netCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BratGui involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas (MSS, -SSH, MSLA, editing of spurious data, etc.). The documentation collection includes the standard user manual explaining all the ways to interact with the set of software tools but the most important item is the Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "data use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The upcoming release that is on the forge will focus on Sentinel 3 Surface Topography Mission that is build on the successful heritage of ERS, Envisat and Cryosat. The first of the two sentinel is expected to be launched in 2014. It will have on-board a dual-frequency (Ku and C band) advanced Synthetic Aperture Radar Altimeter and will provide measurements at a resolution of ~300m in SAR mode along track. Sentinel 3 will provide exact measurements of sea-surface height along with accurate topography measurements over sea ice, ice sheets, rivers and lakes. The future version will provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and made them aware of the great potential of SAR altimetery for coastal and inland applications. The BRAT software is distributed under the GNU GPL open-source license and can be obtained, along with all the documentation (including the tutorial), on the webstite: http://earth.esa.int/brat

Integrated Budget Office Toolbox

NASA Technical Reports Server (NTRS)

Rushing, Douglas A.; Blakeley, Chris; Chapman, Gerry; Robertson, Bill; Horton, Allison; Besser, Thomas; McCarthy, Debbie

2010-01-01

The Integrated Budget Office Toolbox (IBOT) combines budgeting, resource allocation, organizational funding, and reporting features in an automated, integrated tool that provides data from a single source for Johnson Space Center (JSC) personnel. Using a common interface, concurrent users can utilize the data without compromising its integrity. IBOT tracks planning changes and updates throughout the year using both phasing and POP-related (program-operating-plan-related) budget information for the current year, and up to six years out. Separating lump-sum funds received from HQ (Headquarters) into separate labor, travel, procurement, Center G&A (general & administrative), and servicepool categories, IBOT creates a script that significantly reduces manual input time. IBOT also manages the movement of travel and procurement funds down to the organizational level and, using its integrated funds management feature, helps better track funding at lower levels. Third-party software is used to create integrated reports in IBOT that can be generated for plans, actuals, funds received, and other combinations of data that are currently maintained in the centralized format. Based on Microsoft SQL, IBOT incorporates generic budget processes, is transportable, and is economical to deploy and support.

Smoke Ready Toolbox for Wildfires

EPA Pesticide Factsheets

This site provides an online Smoke Ready Toolbox for Wildfires, which lists resources and tools that provide information on health impacts from smoke exposure, current fire conditions and forecasts and strategies to reduce exposure to smoke.

Developing a congestion mitigation toolbox.

DOT National Transportation Integrated Search

2011-09-30

Researchers created A Michigan Toolbox for Mitigating Traffic Congestion to be a useful desk reference for practitioners and an educational tool for elected officials acting through public policy boards to better understand the development, planning,...

CBP TOOLBOX VERSION 2.0: CODE INTEGRATION ENHANCEMENTS

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

Smith, F.; Flach, G.; BROWN, K.

2013-06-01

This report describes enhancements made to code integration aspects of the Cementitious Barriers Project (CBP) Toolbox as a result of development work performed at the Savannah River National Laboratory (SRNL) in collaboration with Vanderbilt University (VU) in the first half of fiscal year 2013. Code integration refers to the interfacing to standalone CBP partner codes, used to analyze the performance of cementitious materials, with the CBP Software Toolbox. The most significant enhancements are: 1) Improved graphical display of model results. 2) Improved error analysis and reporting. 3) Increase in the default maximum model mesh size from 301 to 501 nodes.more » 4) The ability to set the LeachXS/Orchestra simulation times through the GoldSim interface. These code interface enhancements have been included in a new release (Version 2.0) of the CBP Toolbox.« less

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Toolbox for Research, or how to facilitate a central data management in small-scale research projects.

PubMed

Bialke, Martin; Rau, Henriette; Thamm, Oliver C; Schuldt, Ronny; Penndorf, Peter; Blumentritt, Arne; Gött, Robert; Piegsa, Jens; Bahls, Thomas; Hoffmann, Wolfgang

2018-01-25

In most research projects budget, staff and IT infrastructures are limiting resources. Especially for small-scale registries and cohort studies professional IT support and commercial electronic data capture systems are too expensive. Consequently, these projects use simple local approaches (e.g. Excel) for data capture instead of a central data management including web-based data capture and proper research databases. This leads to manual processes to merge, analyze and, if possible, pseudonymize research data of different study sites. To support multi-site data capture, storage and analyses in small-scall research projects, corresponding requirements were analyzed within the MOSAIC project. Based on the identified requirements, the Toolbox for Research was developed as a flexible software solution for various research scenarios. Additionally, the Toolbox facilitates data integration of research data as well as metadata by performing necessary procedures automatically. Also, Toolbox modules allow the integration of device data. Moreover, separation of personally identifiable information and medical data by using only pseudonyms for storing medical data ensures the compliance to data protection regulations. This pseudonymized data can then be exported in SPSS format in order to enable scientists to prepare reports and analyses. The Toolbox for Research was successfully piloted in the German Burn Registry in 2016 facilitating the documentation of 4350 burn cases at 54 study sites. The Toolbox for Research can be downloaded free of charge from the project website and automatically installed due to the use of Docker technology.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

PubMed

Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

2013-08-08

COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

Numerical investigations on the aerodynamic performance of wind turbine: Downwind versus upwind configuration

NASA Astrophysics Data System (ADS)

Zhou, Hu; Wan, Decheng

2015-03-01

Although the upwind configuration is more popular in the field of wind energy, the downwind one is a promising type for the offshore wind energy due to its special advantages. Different configurations have different aerodynamic performance and it is important to predict the performance of both downwind and upwind configurations accurately for designing and developing more reliable wind turbines. In this paper, a numerical investigation on the aerodynamic performance of National Renewable Energy Laboratory (NREL) phase VI wind turbine in downwind and upwind configurations is presented. The open source toolbox OpenFOAM coupled with arbitrary mesh interface (AMI) method is applied to tackle rotating problems of wind turbines. Two 3D numerical models of NREL phase VI wind turbine with downwind and upwind configurations under four typical working conditions of incoming wind velocities are set up for the study of different unsteady characteristics of the downwind and upwind configurations, respectively. Numerical results of wake vortex structure, time histories of thrust, pressure distribution on the blade and limiting streamlines which can be used to identify points of separation in a 3D flow are presented. It can be concluded that thrust reduction due to blade-tower interaction is small for upwind wind turbines but relatively large for downwind wind turbines and attention should be paid to the vibration at a certain frequency induced by the cyclic reduction for both configurations. The results and conclusions are helpful to analyze the different aerodynamic performance of wind turbines between downwind and upwind configurations, providing useful references for practical design of wind turbine.

Polymer application for separation/filtration of biological active compounds

NASA Astrophysics Data System (ADS)

Tylkowski, B.; Tsibranska, I.

2017-06-01

Membrane technology is an important part of the engineer's toolbox. This is especially true for industries that process food and other products with their primary source from nature. This review is focused on ongoing development work using membrane technologies for concentration and separation of biologically active compounds, such as polyphenols and flavonoids. We provide the readers not only with the last results achieve in this field but also, we deliver detailed information about the membrane types and polymers used for their preparation.

A Molecular Toolbox for Rapid Generation of Viral Vectors to Up- or Down-Regulate Neuronal Gene Expression in vivo

PubMed Central

White, Melanie D.; Milne, Ruth V. J.; Nolan, Matthew F.

2011-01-01

We introduce a molecular toolbox for manipulation of neuronal gene expression in vivo. The toolbox includes promoters, ion channels, optogenetic tools, fluorescent proteins, and intronic artificial microRNAs. The components are easily assembled into adeno-associated virus (AAV) or lentivirus vectors using recombination cloning. We demonstrate assembly of toolbox components into lentivirus and AAV vectors and use these vectors for in vivo expression of inwardly rectifying potassium channels (Kir2.1, Kir3.1, and Kir3.2) and an artificial microRNA targeted against the ion channel HCN1 (HCN1 miRNA). We show that AAV assembled to express HCN1 miRNA produces efficacious and specific in vivo knockdown of HCN1 channels. Comparison of in vivo viral transduction using HCN1 miRNA with mice containing a germ line deletion of HCN1 reveals similar physiological phenotypes in cerebellar Purkinje cells. The easy assembly and re-usability of the toolbox components, together with the ability to up- or down-regulate neuronal gene expression in vivo, may be useful for applications in many areas of neuroscience. PMID:21772812

Ensemble of classifiers for ontology enrichment

NASA Astrophysics Data System (ADS)

Semenova, A. V.; Kureichik, V. M.

2018-05-01

A classifier is a basis of ontology learning systems. Classification of text documents is used in many applications, such as information retrieval, information extraction, definition of spam. A new ensemble of classifiers based on SVM (a method of support vectors), LSTM (neural network) and word embedding are suggested. An experiment was conducted on open data, which allows us to conclude that the proposed classification method is promising. The implementation of the proposed classifier is performed in the Matlab using the functions of the Text Analytics Toolbox. The principal difference between the proposed ensembles of classifiers is the high quality of classification of data at acceptable time costs.

A Michigan toolbox for mitigating traffic congestion.

DOT National Transportation Integrated Search

2011-09-30

"Researchers created A Michigan Toolbox for Mitigating Traffic Congestion to be a useful desk reference : for practitioners and an educational tool for elected officials acting through public policy boards to better : understand the development, plan...

Drinking Water Cyanotoxin Risk Communication Toolbox

EPA Pesticide Factsheets

The drinking water cyanotoxin risk communication toolbox is a ready-to-use, “one-stop-shop” to support public water systems, states, and local governments in developing, as they deem appropriate, their own risk communication materials.

EPA ExpoBox Toolbox Search

EPA Pesticide Factsheets

EPA ExpoBox is a toolbox for exposure assessors. Its purpose is to provide a compendium of exposure assessment and risk characterization tools that will present comprehensive step-by-step guidance and links to relevant assessment data bases,

40 CFR 141.715 - Microbial toolbox options for meeting Cryptosporidium treatment requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... criteria are in § 141.716(b). Pre Filtration Toolbox Options (3) Presedimentation basin with coagulation 0... separate granular media filtration stage if treatment train includes coagulation prior to first filter...

40 CFR 141.715 - Microbial toolbox options for meeting Cryptosporidium treatment requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... criteria are in § 141.716(b). Pre Filtration Toolbox Options (3) Presedimentation basin with coagulation 0... separate granular media filtration stage if treatment train includes coagulation prior to first filter...

Air Sensor Toolbox for Citizen Scientists

EPA Pesticide Factsheets

EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.

A portable toolbox to monitor and evaluate signal operations.

DOT National Transportation Integrated Search

2011-10-01

Researchers from the Texas Transportation Institute developed a portable tool consisting of a fieldhardened : computer interfacing with the traffic signal cabinet through special enhanced Bus Interface Units. : The toolbox consisted of a monitoring t...

Air Sensor Toolbox: Resources and Funding

EPA Pesticide Factsheets

EPA’s Air Sensor Toolbox provides information and guidance on new low-cost compact technologies for measuring air quality. It provides information to help citizens more effectively and accurately collect air quality data in their community.

An evaluative study of the impact of the "Curriculum Alignment Toolbox" on middle school science achievement

NASA Astrophysics Data System (ADS)

Jones, Carol L.

The number of computer-assisted education programs on the market is overwhelming science teachers all over the Michigan. Though the need is great, many teachers are reluctant to procure computer-assisted science education programs because they are unsure of the effectiveness of such programs. The Curriculum Alignment Toolbox (CAT) is a computer-based program, aligned to the Michigan Curriculum Framework's Benchmarks for Science Education and designed to supplement science instruction in Michigan middle schools. The purpose of this study was to evaluate the effectiveness of CAT in raising the standardized test scores of Michigan students. This study involved 419 students from one urban, one suburban and one rural middle school. Data on these students was collected from 4 sources: (1) the 8th grade Michigan Education Assessment Program (MEAP) test, (2) a 9 question, 5-point Likert-type scale student survey, (3) 4 open-response student survey questions and (4) classroom observations. Results of this study showed that the experimental group of 226 students who utilized the CAT program in addition to traditional instruction did significantly better on the Science MEAP test than the control group of 193 students who received only traditional instruction. The study also showed that the urban students from a "high needs" school seemed to benefit most from the program. Additionally, though both genders and all identified ethnic groups benefited from the program, males benefited more than females and whites, blacks and Asian/Pacific Islander students benefited more than Hispanic and multi-racial students. The CAT program's success helping raise the middle school MEAP scores may well be due to some of its components. CAT provided students with game-like experiences all based on the benchmarks required for science education and upon which the MEAP test is based. The program also provided visual and auditory stimulation as well as numerous references which students indicated they enjoyed. Additionally, as best-practice, the questioning in all the gaming within CAT did not allow a student to continue until he/she had given the correct answer, thus reinforcing the correct response.

Applications of New Surrogate Global Optimization Algorithms including Efficient Synchronous and Asynchronous Parallelism for Calibration of Expensive Nonlinear Geophysical Simulation Models.

NASA Astrophysics Data System (ADS)

Shoemaker, C. A.; Pang, M.; Akhtar, T.; Bindel, D.

2016-12-01

New parallel surrogate global optimization algorithms are developed and applied to objective functions that are expensive simulations (possibly with multiple local minima). The algorithms can be applied to most geophysical simulations, including those with nonlinear partial differential equations. The optimization does not require simulations be parallelized. Asynchronous (and synchronous) parallel execution is available in the optimization toolbox "pySOT". The parallel algorithms are modified from serial to eliminate fine grained parallelism. The optimization is computed with open source software pySOT, a Surrogate Global Optimization Toolbox that allows user to pick the type of surrogate (or ensembles), the search procedure on surrogate, and the type of parallelism (synchronous or asynchronous). pySOT also allows the user to develop new algorithms by modifying parts of the code. In the applications here, the objective function takes up to 30 minutes for one simulation, and serial optimization can take over 200 hours. Results from Yellowstone (NSF) and NCSS (Singapore) supercomputers are given for groundwater contaminant hydrology simulations with applications to model parameter estimation and decontamination management. All results are compared with alternatives. The first results are for optimization of pumping at many wells to reduce cost for decontamination of groundwater at a superfund site. The optimization runs with up to 128 processors. Superlinear speed up is obtained for up to 16 processors, and efficiency with 64 processors is over 80%. Each evaluation of the objective function requires the solution of nonlinear partial differential equations to describe the impact of spatially distributed pumping and model parameters on model predictions for the spatial and temporal distribution of groundwater contaminants. The second application uses an asynchronous parallel global optimization for groundwater quality model calibration. The time for a single objective function evaluation varies unpredictably, so efficiency is improved with asynchronous parallel calculations to improve load balancing. The third application (done at NCSS) incorporates new global surrogate multi-objective parallel search algorithms into pySOT and applies it to a large watershed calibration problem.

Learning GIS and exploring geolocated data with the all-in-one Geolokit toolbox for Google Earth

NASA Astrophysics Data System (ADS)

Watlet, A.; Triantafyllou, A.; Bastin, C.

2016-12-01

GIS software are today's essential tools to gather and visualize geological data, to apply spatial and temporal analysis and finally, to create and share interactive maps for further investigations in geosciences. Such skills are especially essential to learn for students who go through fieldtrips, samples collections or field experiments. However, time is generally missing to teach in detail all the aspects of visualizing geolocated geoscientific data. For these purposes, we developed Geolokit: a lightweight freeware dedicated to geodata visualization and 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, benefitting from the numerous interactive capabilities. It is designed as a very 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 visualize these into the Google Earth environment using KML code; with no require of third party software, except Google Earth itself. Geolokit comes with a large number of geosciences labels, symbols, colours and placemarks and is applicable to display several types of geolocated data, including: Multi-points datasets Automatically computed contours of multi-points datasets via several interpolation methods Discrete planar and linear structural geology data in 2D or 3D supporting large range of structures input format Clustered stereonets and rose diagrams 2D cross-sections as vertical sections Georeferenced maps and grids with user defined coordinates Field pictures using either geo-tracking metadata from a camera built-in GPS module, or the same-day track of an external GPS In the end, Geolokit is helpful for quickly visualizing and exploring data without losing too much time in the numerous capabilities of GIS software suites. We are looking for students and teachers to discover all the functionalities of Geolokit. As this project is under development and planned to be open source, we are definitely looking to discussions regarding particular needs or ideas, and to contributions in the Geolokit project.

a Matlab Toolbox for Basin Scale Fluid Flow Modeling Applied to Hydrology and Geothermal Energy

NASA Astrophysics Data System (ADS)

Alcanie, M.; Lupi, M.; Carrier, A.

2017-12-01

Recent boosts in the development of geothermal energy were fostered by the latest oil crises and by the need of reducing CO2 emissions generated by the combustion of fossil fuels. Various numerical codes (e.g. FEHM, CSMP++, HYDROTHERM, TOUGH) have thus been implemented for the simulation and quantification of fluid flow in the upper crust. One possible limitation of such codes is the limited accessibility and the complex structure of the simulators. For this reason, we began to develop a Hydrothermal Fluid Flow Matlab library as part of MRST (Matlab Reservoir Simulation Toolbox). MRST is designed for the simulation of oil and gas problems including carbon capture storage. However, a geothermal module is still missing. We selected the Geneva Basin as a natural laboratory because of the large amount of data available in the region. The Geneva Basin has been intensely investigated in the past with exploration wells, active seismic and gravity surveys. In addition, the energy strategy of Switzerland promotes the development of geothermal energy that lead to recent geophysical prospections. Previous and ongoing projects have shown the geothermal potential of the Geneva Basin but a consistent fluid flow model assessing the deep circulation in the region is yet to be defined. The first step of the study was to create the basin-scale static model. We integrated available active seismic, gravity inversions and borehole data to describe the principal geologic and tectonic features of the Geneva Basin. Petrophysical parameters were obtained from available and widespread well logs. This required adapting MRST to standard text format file imports and outline a new methodology for quick static model creation in an open source environment. We implemented several basin-scale fluid flow models to test the effects of petrophysical properties on the circulation dynamics of deep fluids in the Geneva Basin. Preliminary results allow the identification of preferential fluid flow pathways, which are critical information to define geothermal exploitation locations. The next step will be the implementation of the equation of state for pure water, CO2 - H2O and H2O - CH4 fluid mixtures.

EPA EMERGENCY PLANNING TOOLBOX

EPA Science Inventory

EPA's Office of Research and Development and Office of Water/Water Security Division have jointly developed a Response Protocol Toolbox (RPTB) to address the complex, multi-faceted challenges of a water utility's planning and response to intentional contamination of drinking wate...

Ironbound Community Citizen Science Toolbox Fact Sheet

EPA Pesticide Factsheets

EPA is partnering with Newark’s Ironbound Community Corporation (ICC) to design, develop, and pilot a Citizen Science Toolbox that will enable communities to collect their own environmental data and increase their ability to understand local conditions.

System engineering toolbox for design-oriented engineers

NASA Technical Reports Server (NTRS)

Goldberg, B. E.; Everhart, K.; Stevens, R.; Babbitt, N., III; Clemens, P.; Stout, L.

1994-01-01

This system engineering toolbox is designed to provide tools and methodologies to the design-oriented systems engineer. A tool is defined as a set of procedures to accomplish a specific function. A methodology is defined as a collection of tools, rules, and postulates to accomplish a purpose. For each concept addressed in the toolbox, the following information is provided: (1) description, (2) application, (3) procedures, (4) examples, if practical, (5) advantages, (6) limitations, and (7) bibliography and/or references. The scope of the document includes concept development tools, system safety and reliability tools, design-related analytical tools, graphical data interpretation tools, a brief description of common statistical tools and methodologies, so-called total quality management tools, and trend analysis tools. Both relationship to project phase and primary functional usage of the tools are also delineated. The toolbox also includes a case study for illustrative purposes. Fifty-five tools are delineated in the text.

National Water-Quality Assessment (NAWQA) area-characterization toolbox

USGS Publications Warehouse

Price, Curtis V.; Nakagaki, Naomi; Hitt, Kerie J.

2010-01-01

This is release 1.0 of the National Water-Quality Assessment (NAWQA) Area-Characterization Toolbox. These tools are designed to be accessed using ArcGIS Desktop software (versions 9.3 and 9.3.1). The toolbox is composed of a collection of custom tools that implement geographic information system (GIS) techniques used by the NAWQA Program to characterize aquifer areas, drainage basins, and sampled wells. These tools are built on top of standard functionality included in ArcGIS Desktop running at the ArcInfo license level. Most of the tools require a license for the ArcGIS Spatial Analyst extension. ArcGIS is a commercial GIS software system produced by ESRI, Inc. (http://www.esri.com). The NAWQA Area-Characterization Toolbox is not supported by ESRI, Inc. or its technical support staff. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Traffic analysis toolbox volume XIII : integrated corridor management analysis, modeling, and simulation guide

DOT National Transportation Integrated Search

2017-02-01

As part of the Federal Highway Administration (FHWA) Traffic Analysis Toolbox (Volume XIII), this guide was designed to help corridor stakeholders implement the Integrated Corridor Management (ICM) Analysis, Modeling, and Simulation (AMS) methodology...

Traffic analysis toolbox volume XIII : integrated corridor management analysis, modeling, and simulation guide.

DOT National Transportation Integrated Search

2017-02-01

As part of the Federal Highway Administration (FHWA) Traffic Analysis Toolbox (Volume XIII), this guide was designed to help corridor stakeholders implement the Integrated Corridor Management (ICM) Analysis, Modeling, and Simulation (AMS) methodology...

Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a - model description and implementation

NASA Astrophysics Data System (ADS)

Herman, Agnieszka

2016-04-01

This paper presents theoretical foundations, numerical implementation and examples of application of the two-dimensional Discrete-Element bonded-particle Sea Ice model - DESIgn. In the model, sea ice is represented as an assemblage of objects of two types: disk-shaped "grains" and semi-elastic bonds connecting them. Grains move on the sea surface under the influence of forces from the atmosphere and the ocean, as well as interactions with surrounding grains through direct contact (Hertzian contact mechanics) and/or through bonds. The model has an experimental option of taking into account quasi-three-dimensional effects related to the space- and time-varying curvature of the sea surface, thus enabling simulation of ice breaking due to stresses resulting from bending moments associated with surface waves. Examples of the model's application to simple sea ice deformation and breaking problems are presented, with an analysis of the influence of the basic model parameters ("microscopic" properties of grains and bonds) on the large-scale response of the modeled material. The model is written as a toolbox suitable for usage with the open-source numerical library LIGGGHTS. The code, together with full technical documentation and example input files, is freely available with this paper and on the Internet.

Fortran graphics routines for the Macintosh

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

Shore, B.W.

1992-06-01

The Language Systems MPW Fortran is a popular Fortran compiler for the Macintosh. Unfortunately, it does not have any built-in calls to graphics routines (such as are available with Graflib on the NLTSS), so there is no simple way to make x-y plots from calls within Fortran. Instead, a file of data must be created and a commercial plotting routine (such as IGOR or KALEIDAGRAPH) or a spreadsheet with graphics (such as WINGZ) must be applied to post-process the data. The Macintosh does have available many built-in calls (to the Macintosh Toolbox) that allow drawing shapes and lines with quickdraw,more » but these are not designed for plotting functions and are difficult to learn to use. This work outlines some Fortran routines that can be called from LS Fortran to make the necessary calls to the Macintosh toolbox to create simple two-dimensional plots or contour plots. The source code DEMOGRAF.F shows how these routines may be used. DEMOGRAF.F simply demonstrates some Fortran subroutines that can be called with language systems MPW Fortran on the Macintosh to plot arrays of numbers. The subroutines essentially mimic the functionality that has been available at LTSS and NLTSS and UNICOS at LLNL. The graphics primitives are kept in four separate files, each containing several subroutines. The subroutines are compiled and stored in a library file, LIBgraf.o. Makefile is used to link this library to the source code. A discussion is included on requirements for interactive plotting of functions.« less

Technical skills assessment toolbox: a review using the unitary framework of validity.

PubMed

Ghaderi, Iman; Manji, Farouq; Park, Yoon Soo; Juul, Dorthea; Ott, Michael; Harris, Ilene; Farrell, Timothy M

2015-02-01

The purpose of this study was to create a technical skills assessment toolbox for 35 basic and advanced skills/procedures that comprise the American College of Surgeons (ACS)/Association of Program Directors in Surgery (APDS) surgical skills curriculum and to provide a critical appraisal of the included tools, using contemporary framework of validity. Competency-based training has become the predominant model in surgical education and assessment of performance is an essential component. Assessment methods must produce valid results to accurately determine the level of competency. A search was performed, using PubMed and Google Scholar, to identify tools that have been developed for assessment of the targeted technical skills. A total of 23 assessment tools for the 35 ACS/APDS skills modules were identified. Some tools, such as Operative Performance Rating System (OSATS) and Objective Structured Assessment of Technical Skill (OPRS), have been tested for more than 1 procedure. Therefore, 30 modules had at least 1 assessment tool, with some common surgical procedures being addressed by several tools. Five modules had none. Only 3 studies used Messick's framework to design their validity studies. The remaining studies used an outdated framework on the basis of "types of validity." When analyzed using the contemporary framework, few of these studies demonstrated validity for content, internal structure, and relationship to other variables. This study provides an assessment toolbox for common surgical skills/procedures. Our review shows that few authors have used the contemporary unitary concept of validity for development of their assessment tools. As we progress toward competency-based training, future studies should provide evidence for various sources of validity using the contemporary framework.

Planetary Geologic Mapping Python Toolbox: A Suite of Tools to Support Mapping Workflows

NASA Astrophysics Data System (ADS)

Hunter, M. A.; Skinner, J. A.; Hare, T. M.; Fortezzo, C. M.

2017-06-01

The collective focus of the Planetary Geologic Mapping Python Toolbox is to provide researchers with additional means to migrate legacy GIS data, assess the quality of data and analysis results, and simplify common mapping tasks.

SSOAP Toolbox Enhancements and Case Study

EPA Science Inventory

Recognizing the need for tools to support the development of sanitary sewer overflow (SSO) control plans, in October 2009 the U.S. Environmental Protection Agency (EPA) released the first version of the Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox. This first ve...

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic System (T-MATS)

NASA Technical Reports Server (NTRS)

Chapman, Jeffryes W.; Lavelle, Thomas M.; May, Ryan D.; Litt, Jonathan S.; Guo, Ten-Huei (OA)

2014-01-01

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This presentation describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this presentation is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture.

An Educational Model for Hands-On Hydrology Education

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

2014-12-01

This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

Emotion assessment using the NIH Toolbox

PubMed Central

Butt, Zeeshan; Pilkonis, Paul A.; Cyranowski, Jill M.; Zill, Nicholas; Hendrie, Hugh C.; Kupst, Mary Jo; Kelly, Morgen A. R.; Bode, Rita K.; Choi, Seung W.; Lai, Jin-Shei; Griffith, James W.; Stoney, Catherine M.; Brouwers, Pim; Knox, Sarah S.; Cella, David

2013-01-01

One of the goals of the NIH Toolbox for Assessment of Neurological and Behavioral Function was to identify or develop brief measures of emotion for use in prospective epidemiologic and clinical research. Emotional health has significant links to physical health and exerts a powerful effect on perceptions of life quality. Based on an extensive literature review and expert input, the Emotion team identified 4 central subdomains: Negative Affect, Psychological Well-Being, Stress and Self-Efficacy, and Social Relationships. A subsequent psychometric review identified several existing self-report and proxy measures of these subdomains with measurement characteristics that met the NIH Toolbox criteria. In cases where adequate measures did not exist, robust item banks were developed to assess concepts of interest. A population-weighted sample was recruited by an online survey panel to provide initial item calibration and measure validation data. Participants aged 8 to 85 years completed self-report measures whereas parents/guardians responded for children aged 3 to 12 years. Data were analyzed using a combination of classic test theory and item response theory methods, yielding efficient measures of emotional health concepts. An overview of the development of the NIH Toolbox Emotion battery is presented along with preliminary results. Norming activities led to further refinement of the battery, thus enhancing the robustness of emotional health measurement for researchers using the NIH Toolbox. PMID:23479549

Atlas - a data warehouse for integrative bioinformatics.

PubMed

Shah, Sohrab P; Huang, Yong; Xu, Tao; Yuen, Macaire M S; Ling, John; Ouellette, B F Francis

2005-02-21

We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: http://bioinformatics.ubc.ca/atlas/

Atlas – a data warehouse for integrative bioinformatics

PubMed Central

Shah, Sohrab P; Huang, Yong; Xu, Tao; Yuen, Macaire MS; Ling, John; Ouellette, BF Francis

2005-01-01

Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: PMID:15723693

A web-based tool for ranking landslide mitigation measures

NASA Astrophysics Data System (ADS)

Lacasse, S.; Vaciago, G.; Choi, Y. J.; Kalsnes, B.

2012-04-01

As part of the research done in the European project SafeLand "Living with landslide risk in Europe: Assessment, effects of global change, and risk management strategies", a compendium of structural and non-structural mitigation measures for different landslide types in Europe was prepared, and the measures were assembled into a web-based "toolbox". Emphasis was placed on providing a rational and flexible framework applicable to existing and future mitigation measures. The purpose of web-based toolbox is to assist decision-making and to guide the user in the choice of the most appropriate mitigation measures. The mitigation measures were classified into three categories, describing whether the mitigation measures addressed the landslide hazard, the vulnerability or the elements at risk themselves. The measures considered include structural measures reducing hazard and non-structural mitigation measures, reducing either the hazard or the consequences (or vulnerability and exposure of elements at risk). The structural measures include surface protection and control of surface erosion; measures modifying the slope geometry and/or mass distribution; measures modifying surface water regime - surface drainage; measures mo¬difying groundwater regime - deep drainage; measured modifying the mechanical charac¬teristics of unstable mass; transfer of loads to more competent strata; retaining structures (to modify slope geometry and/or to transfer stress to compe¬tent layer); deviating the path of landslide debris; dissipating the energy of debris flows; and arresting and containing landslide debris or rock fall. The non-structural mitigation measures, reducing either the hazard or the consequences: early warning systems; restricting or discouraging construction activities; increasing resistance or coping capacity of elements at risk; relocation of elements at risk; sharing of risk through insurance. The measures are described in the toolbox with fact sheets providing a brief description, guidance on design, schematic details, practical examples and references for each mitigation measure. Each of the measures was given a score on its ability and applicability for different types of landslides and boundary conditions, and a decision support matrix was established. The web-based toolbox organizes the information in the compendium and provides an algorithm to rank the measures on the basis of the decision support matrix, and on the basis of the risk level estimated at the site. The toolbox includes a description of the case under study and offers a simplified option for estimating the hazard and risk levels of the slide at hand. The user selects the mitigation measures to be included in the assessment. The toolbox then ranks, with built-in assessment factors and weights and/or with user-defined ranking values and criteria, the mitigation measures included in the analysis. The toolbox includes data management, e.g. saving data half-way in an analysis, returning to an earlier case, looking up prepared examples or looking up information on mitigation measures. The toolbox also generates a report and has user-forum and help features. The presentation will give an overview of the mitigation measures considered and examples of the use of the toolbox, and will take the attendees through the application of the toolbox.

Large Scale Integration of Renewable Power Sources into the Vietnamese Power System

NASA Astrophysics Data System (ADS)

Kies, Alexander; Schyska, Bruno; Thanh Viet, Dinh; von Bremen, Lueder; Heinemann, Detlev; Schramm, Stefan

2017-04-01

The Vietnamese Power system is expected to expand considerably in upcoming decades. Power capacities installed are projected to grow from 39 GW in 2015 to 129.5 GW by 2030. Installed wind power capacities are expected to grow to 6 GW (0.8 GW 2015) and solar power capacities to 12 GW (0.85 GW 2015). This goes hand in hand with an increase of the renewable penetration in the power mix from 1.3% from wind and photovoltaics (PV) in 2015 to 5.4% by 2030. The overall potential for wind power in Vietnam is estimated to be around 24 GW. Moreover, the up-scaling of renewable energy sources was formulated as one of the priorized targets of the Vietnamese government in the National Power Development Plan VII. In this work, we investigate the transition of the Vietnamese power system towards high shares of renewables. For this purpose, we jointly optimise the expansion of renewable generation facilities for wind and PV, and the transmission grid within renewable build-up pathways until 2030 and beyond. To simulate the Vietnamese power system and its generation from renewable sources, we use highly spatially and temporally resolved historical weather and load data and the open source modelling toolbox Python for Power System Analysis (PyPSA). We show that the highest potential of renewable generation for wind and PV is observed in southern Vietnam and discuss the resulting need for transmission grid extensions in dependency of the optimal pathway. Furthermore, we show that the smoothing effect of wind power has several considerable beneficial effects and that the Vietnamese hydro power potential can be efficiently used to provide balancing opportunities. This work is part of the R&D Project "Analysis of the Large Scale Integration of Renewable Power into the Future Vietnamese Power System" (GIZ, 2016-2018).

Complete synthetic seismograms based on a spherical self-gravitating Earth model with an atmosphere-ocean-mantle-core structure

NASA Astrophysics Data System (ADS)

Wang, Rongjiang; Heimann, Sebastian; Zhang, Yong; Wang, Hansheng; Dahm, Torsten

2017-04-01

A hybrid method is proposed to calculate complete synthetic seismograms based on a spherically symmetric and self-gravitating Earth with a multi-layered structure of atmosphere, ocean, mantle, liquid core and solid core. For large wavelengths, a numerical scheme is used to solve the geodynamic boundary-value problem without any approximation on the deformation and gravity coupling. With the decreasing wavelength, the gravity effect on the deformation becomes negligible and the analytical propagator scheme can be used. Many useful approaches are used to overcome the numerical problems that may arise in both analytical and numerical schemes. Some of these approaches have been established in the seismological community and the others are developed for the first time. Based on the stable and efficient hybrid algorithm, an all-in-one code QSSP is implemented to cover the complete spectrum of seismological interests. The performance of the code is demonstrated by various tests including the curvature effect on teleseismic body and surface waves, the appearance of multiple reflected, teleseismic core phases, the gravity effect on long period surface waves and free oscillations, the simulation of near-field displacement seismograms with the static offset, the coupling of tsunami and infrasound waves, and free oscillations of the solid Earth, the atmosphere and the ocean. QSSP is open source software that can be used as a stand-alone FORTRAN code or may be applied in combination with a Python toolbox to calculate and handle Green's function databases for efficient coding of source inversion problems.

Complete synthetic seismograms based on a spherical self-gravitating Earth model with an atmosphere-ocean-mantle-core structure

NASA Astrophysics Data System (ADS)

Wang, Rongjiang; Heimann, Sebastian; Zhang, Yong; Wang, Hansheng; Dahm, Torsten

2017-09-01

A hybrid method is proposed to calculate complete synthetic seismograms based on a spherically symmetric and self-gravitating Earth with a multilayered structure of atmosphere, ocean, mantle, liquid core and solid core. For large wavelengths, a numerical scheme is used to solve the geodynamic boundary-value problem without any approximation on the deformation and gravity coupling. With decreasing wavelength, the gravity effect on the deformation becomes negligible and the analytical propagator scheme can be used. Many useful approaches are used to overcome the numerical problems that may arise in both analytical and numerical schemes. Some of these approaches have been established in the seismological community and the others are developed for the first time. Based on the stable and efficient hybrid algorithm, an all-in-one code QSSP is implemented to cover the complete spectrum of seismological interests. The performance of the code is demonstrated by various tests including the curvature effect on teleseismic body and surface waves, the appearance of multiple reflected, teleseismic core phases, the gravity effect on long period surface waves and free oscillations, the simulation of near-field displacement seismograms with the static offset, the coupling of tsunami and infrasound waves, and free oscillations of the solid Earth, the atmosphere and the ocean. QSSP is open source software that can be used as a stand-alone FORTRAN code or may be applied in combination with a Python toolbox to calculate and handle Green's function databases for efficient coding of source inversion problems.

Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images.

PubMed

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-03-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Automated Method for the Rapid and Precise Estimation of Adherent Cell Culture Characteristics from Phase Contrast Microscopy Images

PubMed Central

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-01-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. Biotechnol. Bioeng. 2014;111: 504–517. © 2013 Wiley Periodicals, Inc. PMID:24037521

Integrated system dynamics toolbox for water resources planning.

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

Reno, Marissa Devan; Passell, Howard David; Malczynski, Leonard A.

2006-12-01

Public mediated resource planning is quickly becoming the norm rather than the exception. Unfortunately, supporting tools are lacking that interactively engage the public in the decision-making process and integrate over the myriad values that influence water policy. In the pages of this report we document the first steps toward developing a specialized decision framework to meet this need; specifically, a modular and generic resource-planning ''toolbox''. The technical challenge lies in the integration of the disparate systems of hydrology, ecology, climate, demographics, economics, policy and law, each of which influence the supply and demand for water. Specifically, these systems, their associatedmore » processes, and most importantly the constitutive relations that link them must be identified, abstracted, and quantified. For this reason, the toolbox forms a collection of process modules and constitutive relations that the analyst can ''swap'' in and out to model the physical and social systems unique to their problem. This toolbox with all of its modules is developed within the common computational platform of system dynamics linked to a Geographical Information System (GIS). Development of this resource-planning toolbox represents an important foundational element of the proposed interagency center for Computer Aided Dispute Resolution (CADRe). The Center's mission is to manage water conflict through the application of computer-aided collaborative decision-making methods. The Center will promote the use of decision-support technologies within collaborative stakeholder processes to help stakeholders find common ground and create mutually beneficial water management solutions. The Center will also serve to develop new methods and technologies to help federal, state and local water managers find innovative and balanced solutions to the nation's most vexing water problems. The toolbox is an important step toward achieving the technology development goals of this center.« less

Focused Field Investigations for Sewer Condition Assessment with EPA SSOAP Toolbox

EPA Science Inventory

The Nation’s sanitary sewer infrastructure is aging, and is currently one of the top national water program priorities. The U.S. Environmental Protection Agency (EPA) developed the Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox to assist communities in developing ...

A Toolbox for Corrective Action: Resource Conservation and Recovery Act Facilities Investigation Remedy Selection Track

EPA Pesticide Factsheets

The purpose of this toolbox is to help EPA Regional staff and their partners to take advantage of the efficiency and quality gains from the Resource Conservation and Recovery Act (RCRA) Facilities Investigation Remedy Selection Track (FIRST) approach.

Traffic analysis toolbox volume IX : work zone modeling and simulation, a guide for analysts

DOT National Transportation Integrated Search

2009-03-01

This document is the second volume in the FHWA Traffic Analysis Toolbox: Work Zone Analysis series. Whereas the first volume provides guidance to decision-makers at agencies and jurisdictions considering the role of analytical tools in work zone plan...

An analysis toolbox to explore mesenchymal migration heterogeneity reveals adaptive switching between distinct modes

PubMed Central

Shafqat-Abbasi, Hamdah; Kowalewski, Jacob M; Kiss, Alexa; Gong, Xiaowei; Hernandez-Varas, Pablo; Berge, Ulrich; Jafari-Mamaghani, Mehrdad; Lock, John G; Strömblad, Staffan

2016-01-01

Mesenchymal (lamellipodial) migration is heterogeneous, although whether this reflects progressive variability or discrete, 'switchable' migration modalities, remains unclear. We present an analytical toolbox, based on quantitative single-cell imaging data, to interrogate this heterogeneity. Integrating supervised behavioral classification with multivariate analyses of cell motion, membrane dynamics, cell-matrix adhesion status and F-actin organization, this toolbox here enables the detection and characterization of two quantitatively distinct mesenchymal migration modes, termed 'Continuous' and 'Discontinuous'. Quantitative mode comparisons reveal differences in cell motion, spatiotemporal coordination of membrane protrusion/retraction, and how cells within each mode reorganize with changed cell speed. These modes thus represent distinctive migratory strategies. Additional analyses illuminate the macromolecular- and cellular-scale effects of molecular targeting (fibronectin, talin, ROCK), including 'adaptive switching' between Continuous (favored at high adhesion/full contraction) and Discontinuous (low adhesion/inhibited contraction) modes. Overall, this analytical toolbox now facilitates the exploration of both spontaneous and adaptive heterogeneity in mesenchymal migration. DOI: http://dx.doi.org/10.7554/eLife.11384.001 PMID:26821527

A Transcription Activator-Like Effector (TALE) Toolbox for Genome Engineering

PubMed Central

Sanjana, Neville E.; Cong, Le; Zhou, Yang; Cunniff, Margaret M.; Feng, Guoping; Zhang, Feng

2013-01-01

Transcription activator-like effectors (TALEs) are a class of naturally occurring DNA binding proteins found in the plant pathogen Xanthomonas sp. The DNA binding domain of each TALE consists of tandem 34-amino acid repeat modules that can be rearranged according to a simple cipher to target new DNA sequences. Customized TALEs can be used for a wide variety of genome engineering applications, including transcriptional modulation and genome editing. Here we describe a toolbox for rapid construction of custom TALE transcription factors (TALE-TFs) and nucleases (TALENs) using a hierarchical ligation procedure. This toolbox facilitates affordable and rapid construction of custom TALE-TFs and TALENs within one week and can be easily scaled up to construct TALEs for multiple targets in parallel. We also provide details for testing the activity in mammalian cells of custom TALE-TFs and TALENs using, respectively, qRT-PCR and Surveyor nuclease. The TALE toolbox described here will enable a broad range of biological applications. PMID:22222791

Biomedical Big Data Training Collaborative (BBDTC): An effort to bridge the talent gap in biomedical science and research.

PubMed

Purawat, Shweta; Cowart, Charles; Amaro, Rommie E; Altintas, Ilkay

2017-05-01

The BBDTC (https://biobigdata.ucsd.edu) is a community-oriented platform to encourage high-quality knowledge dissemination with the aim of growing a well-informed biomedical big data community through collaborative efforts on training and education. The BBDTC is an e-learning platform that empowers the biomedical community to develop, launch and share open training materials. It deploys hands-on software training toolboxes through virtualization technologies such as Amazon EC2 and Virtualbox. The BBDTC facilitates migration of courses across other course management platforms. The framework encourages knowledge sharing and content personalization through the playlist functionality that enables unique learning experiences and accelerates information dissemination to a wider community.

eXtended CASA Line Analysis Software Suite (XCLASS)

NASA Astrophysics Data System (ADS)

Möller, T.; Endres, C.; Schilke, P.

2017-02-01

The eXtended CASA Line Analysis Software Suite (XCLASS) is a toolbox for the Common Astronomy Software Applications package (CASA) containing new functions for modeling interferometric and single dish data. Among the tools is the myXCLASS program which calculates synthetic spectra by solving the radiative transfer equation for an isothermal object in one dimension, whereas the finite source size and dust attenuation are considered as well. Molecular data required by the myXCLASS program are taken from an embedded SQLite3 database containing entries from the Cologne Database for Molecular Spectroscopy (CDMS) and JPL using the Virtual Atomic and Molecular Data Center (VAMDC) portal. Additionally, the toolbox provides an interface for the model optimizer package Modeling and Analysis Generic Interface for eXternal numerical codes (MAGIX), which helps to find the best description of observational data using myXCLASS (or another external model program), that is, finding the parameter set that most closely reproduces the data. http://www.astro.uni-koeln.de/projects/schilke/myXCLASSInterface A copy of the code is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/598/A7

Rapid prototyping of an adaptive light-source for mobile manipulators with EasyKit and EasyLab

NASA Astrophysics Data System (ADS)

Wojtczyk, Martin; Barner, Simon; Geisinger, Michael; Knoll, Alois

2008-08-01

While still not common in day-to-day business, mobile robot platforms form a growing market in robotics. Mobile platforms equipped with a manipulator for increased flexibility have been used successfully in biotech laboratories for sample management as shown on the well-known ESACT meetings. Navigation and object recognition is carried out by the utilization of a mounted machine vision camera. To cope with the different illumination conditions in a large laboratory, development of an adaptive light source was indispensable. We present our approach of rapid developing a computer controlled, adaptive LED light within one single business day, by utilizing the hardware toolbox EasyKit and our appropriate software counterpart EasyLab.

ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

PubMed Central

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section. PMID:21577273

ElectroMagnetoEncephalography software: overview and integration with other EEG/MEG toolboxes.

PubMed

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section.

RESPONSE PROTOCOL TOOLBOX: PLANNING FOR AND RESPONDING TO CONTAMINATION THREATS TO DRINKING WATER SYSTEMS

EPA Science Inventory

EPA's Office of Research and Development and Office of Water/Water Security Division have jointly developed a Response Protocol Toolbox (RPTB) to address the complex, multi-faceted challenges of a water utility's planning and response to intentional contamination of drinking wate...

UAS-NAS Live Virtual Constructive Distributed Environment (LVC): LVC Gateway, Gateway Toolbox, Gateway Data Logger (GDL), SaaProc Software Design Description

NASA Technical Reports Server (NTRS)

Jovic, Srboljub

2015-01-01

This document provides the software design description for the two core software components, the LVC Gateway, the LVC Gateway Toolbox, and two participants, the LVC Gateway Data Logger and the SAA Processor (SaaProc).

Expanding the seat belt program strategies toolbox: a starter kit for trying new program ideas : traffic tech.

DOT National Transportation Integrated Search

2016-10-01

The National Highway Traffic Safety Administration has just : released a new resource for developing seat belt programs in : the traffic safety communityExpanding the Seat Belt Program : Toolbox: A Starter Kit for Trying New Program Ideas. : Resea...

Focused Field Investigations for Sewer Condition Assessment with EPA SSOAP Toolbox - slides

EPA Science Inventory

The Nation’s sanitary sewer infrastructure is aging, and is currently one of the top national water program priorities. The U.S. Environmental Protection Agency (EPA) developed the Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox to assist communities in developing S...

Motor assessment using the NIH Toolbox

PubMed Central

Magasi, Susan; McCreath, Heather E.; Bohannon, Richard W.; Wang, Ying-Chih; Bubela, Deborah J.; Rymer, William Z.; Beaumont, Jennifer; Rine, Rose Marie; Lai, Jin-Shei; Gershon, Richard C.

2013-01-01

Motor function involves complex physiologic processes and requires the integration of multiple systems, including neuromuscular, musculoskeletal, and cardiopulmonary, and neural motor and sensory-perceptual systems. Motor-functional status is indicative of current physical health status, burden of disease, and long-term health outcomes, and is integrally related to daily functioning and quality of life. Given its importance to overall neurologic health and function, motor function was identified as a key domain for inclusion in the NIH Toolbox for Assessment of Neurological and Behavioral Function (NIH Toolbox). We engaged in a 3-stage developmental process to: 1) identify key subdomains and candidate measures for inclusion in the NIH Toolbox, 2) pretest candidate measures for feasibility across the age span of people aged 3 to 85 years, and 3) validate candidate measures against criterion measures in a sample of healthy individuals aged 3 to 85 years (n = 340). Based on extensive literature review and input from content experts, the 5 subdomains of dexterity, strength, balance, locomotion, and endurance were recommended for inclusion in the NIH Toolbox motor battery. Based on our validation testing, valid and reliable measures that are simultaneously low-cost and portable have been recommended to assess each subdomain, including the 9-hole peg board for dexterity, grip dynamometry for upper-extremity strength, standing balance test, 4-m walk test for gait speed, and a 2-minute walk test for endurance. PMID:23479547

MatTAP: A MATLAB toolbox for the control and analysis of movement synchronisation experiments.

PubMed

Elliott, Mark T; Welchman, Andrew E; Wing, Alan M

2009-02-15

Investigating movement timing and synchronisation at the sub-second range relies on an experimental setup that has high temporal fidelity, is able to deliver output cues and can capture corresponding responses. Modern, multi-tasking operating systems make this increasingly challenging when using standard PC hardware and programming languages. This paper describes a new free suite of tools (available from http://www.snipurl.com/mattap) for use within the MATLAB programming environment, compatible with Microsoft Windows and a range of data acquisition hardware. The toolbox allows flexible generation of timing cues with high temporal accuracy, the capture and automatic storage of corresponding participant responses and an integrated analysis module for the rapid processing of results. A simple graphical user interface is used to navigate the toolbox and so can be operated easily by users not familiar with programming languages. However, it is also fully extensible and customisable, allowing adaptation for individual experiments and facilitating the addition of new modules in future releases. Here we discuss the relevance of the MatTAP (MATLAB Timing Analysis Package) toolbox to current timing experiments and compare its use to alternative methods. We validate the accuracy of the analysis module through comparison to manual observation methods and replicate a previous sensorimotor synchronisation experiment to demonstrate the versatility of the toolbox features demanded by such movement synchronisation paradigms.

How Well Can Saliency Models Predict Fixation Selection in Scenes Beyond Central Bias? A New Approach to Model Evaluation Using Generalized Linear Mixed Models.

PubMed

Nuthmann, Antje; Einhäuser, Wolfgang; Schütz, Immo

2017-01-01

Since the turn of the millennium, a large number of computational models of visual salience have been put forward. How best to evaluate a given model's ability to predict where human observers fixate in images of real-world scenes remains an open research question. Assessing the role of spatial biases is a challenging issue; this is particularly true when we consider the tendency for high-salience items to appear in the image center, combined with a tendency to look straight ahead ("central bias"). This problem is further exacerbated in the context of model comparisons, because some-but not all-models implicitly or explicitly incorporate a center preference to improve performance. To address this and other issues, we propose to combine a-priori parcellation of scenes with generalized linear mixed models (GLMM), building upon previous work. With this method, we can explicitly model the central bias of fixation by including a central-bias predictor in the GLMM. A second predictor captures how well the saliency model predicts human fixations, above and beyond the central bias. By-subject and by-item random effects account for individual differences and differences across scene items, respectively. Moreover, we can directly assess whether a given saliency model performs significantly better than others. In this article, we describe the data processing steps required by our analysis approach. In addition, we demonstrate the GLMM analyses by evaluating the performance of different saliency models on a new eye-tracking corpus. To facilitate the application of our method, we make the open-source Python toolbox "GridFix" available.

Simplifying the complexity of a coupled carbon turnover and pesticide degradation model

NASA Astrophysics Data System (ADS)

Marschmann, Gianna; Erhardt, André H.; Pagel, Holger; Kügler, Philipp; Streck, Thilo

2016-04-01

The mechanistic one-dimensional model PECCAD (PEsticide degradation Coupled to CArbon turnover in the Detritusphere; Pagel et al. 2014, Biogeochemistry 117, 185-204) has been developed as a tool to elucidate regulation mechanisms of pesticide degradation in soil. A feature of this model is that it integrates functional traits of microorganisms, identifiable by molecular tools, and physicochemical processes such as transport and sorption that control substrate availability. Predicting the behavior of microbially active interfaces demands a fundamental understanding of factors controlling their dynamics. Concepts from dynamical systems theory allow us to study general properties of the model such as its qualitative behavior, intrinsic timescales and dynamic stability: Using a Latin hypercube method we sampled the parameter space for physically realistic steady states of the PECCAD ODE system and set up a numerical continuation and bifurcation problem with the open-source toolbox MatCont in order to obtain a complete classification of the dynamical system's behaviour. Bifurcation analysis reveals an equilibrium state of the system entirely controlled by fungal kinetic parameters. The equilibrium is generally unstable in response to small perturbations except for a small band in parameter space where the pesticide pool is stable. Time scale separation is a phenomenon that occurs in almost every complex open physical system. Motivated by the notion of "initial-stage" and "late-stage" decomposers and the concept of r-, K- or L-selected microbial life strategies, we test the applicability of geometric singular perturbation theory to identify fast and slow time scales of PECCAD. Revealing a generic fast-slow structure would greatly simplify the analysis of complex models of organic matter turnover by reducing the number of unknowns and parameters and providing a systematic mathematical framework for studying their properties.

Appalachian Basin Play Fairway Analysis: Thermal Quality Analysis in Low-Temperature Geothermal Play Fairway Analysis (GPFA-AB

DOE Data Explorer

Teresa E. Jordan

2015-11-15

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB, DOE Project DE-EE0006726). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria or ‘risks’: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS). This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain “item description” documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations. Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015. Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted.

An ethics toolbox for neurotechnology.

PubMed

Farah, Martha J

2015-04-08

Advances in neurotechnology will raise new ethical dilemmas, to which scientists and the rest of society must respond. Here I present a "toolbox" of concepts to help us analyze these issues and communicate with each other about them across differences of ethical intuition. Copyright © 2015 Elsevier Inc. All rights reserved.

The triticeae toolbox: combining phenotype and genotype data to advance small-grains breeding

USDA-ARS?s Scientific Manuscript database

The Triticeae Toolbox (http://triticeaetoolbox.org; T3) is the database schema enabling plant breeders and researchers to combine, visualize, and interrogate the wealth of phenotype and genotype data generated by the Triticeae Coordinated Agricultural Project (TCAP). T3 enables users to define speci...

Wastewater Collection System Toolbox | Eliminating Sanitary ...

EPA Pesticide Factsheets

2017-04-10

Communities across the United States are working to find cost-effective, long-term approaches to managing their aging wastewater infrastructure and preventing the problems that lead to sanitary sewer overflows. The Toolbox is an effort by EPA New England to provide examples of programs and educational efforts from New England and beyond.

LAB ANALYSIS OF EMERGENCY WATER SAMPLES CONTAINING UNKNOWN CONTAMINANTS: CONSIDERATIONS FROM THE USEPA RESPONSE PROTOCOL TOOLBOX

EPA Science Inventory

EPA's Office of Research and Development and Office of Water/Water Security Division have jointly developed a Response Protocol Toolbox (RPTB) to address the complex, multi-faceted challenges of a water utility's planning and response to intentional contamination of drinking wate...

Testing Adaptive Toolbox Models: A Bayesian Hierarchical Approach

ERIC Educational Resources Information Center

Scheibehenne, Benjamin; Rieskamp, Jorg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox…

Biomedical Big Data Training Collaborative (BBDTC): An effort to bridge the talent gap in biomedical science and research.

PubMed

Purawat, Shweta; Cowart, Charles; Amaro, Rommie E; Altintas, Ilkay

2016-06-01

The BBDTC (https://biobigdata.ucsd.edu) is a community-oriented platform to encourage high-quality knowledge dissemination with the aim of growing a well-informed biomedical big data community through collaborative efforts on training and education. The BBDTC collaborative is an e-learning platform that supports the biomedical community to access, develop and deploy open training materials. The BBDTC supports Big Data skill training for biomedical scientists at all levels, and from varied backgrounds. The natural hierarchy of courses allows them to be broken into and handled as modules . Modules can be reused in the context of multiple courses and reshuffled, producing a new and different, dynamic course called a playlist . Users may create playlists to suit their learning requirements and share it with individual users or the wider public. BBDTC leverages the maturity and design of the HUBzero content-management platform for delivering educational content. To facilitate the migration of existing content, the BBDTC supports importing and exporting course material from the edX platform. Migration tools will be extended in the future to support other platforms. Hands-on training software packages, i.e., toolboxes , are supported through Amazon EC2 and Virtualbox virtualization technologies, and they are available as: ( i ) downloadable lightweight Virtualbox Images providing a standardized software tool environment with software packages and test data on their personal machines, and ( ii ) remotely accessible Amazon EC2 Virtual Machines for accessing biomedical big data tools and scalable big data experiments. At the moment, the BBDTC site contains three open Biomedical big data training courses with lecture contents, videos and hands-on training utilizing VM toolboxes, covering diverse topics. The courses have enhanced the hands-on learning environment by providing structured content that users can use at their own pace. A four course biomedical big data series is planned for development in 2016.

Impact-oriented steering--the concept of NGO-IDEAs 'impact toolbox'.

PubMed

2008-03-01

The NGO-IDEAs 'Impact Toolbox' has been developed with a group of NGOs all of which are active in the area of saving and credit in South India. This compilation of methods to apply in impact-oriented steering was devised by the executive staff of the Indian partner NGOs, also known as the Resource Persons, in 2006 and tested from late 2006 to early 2007. At first glance, the approach may appear to be highly specialised and difficult to transfer. However, in fact it follows principles that can be adapted for several NGOs in other countries and in other sectors. The following article presents the concept of the NGO-IDEAs 'Impact Toolbox'.

PSYCHOACOUSTICS: a comprehensive MATLAB toolbox for auditory testing.

PubMed

Soranzo, Alessandro; Grassi, Massimo

2014-01-01

PSYCHOACOUSTICS is a new MATLAB toolbox which implements three classic adaptive procedures for auditory threshold estimation. The first includes those of the Staircase family (method of limits, simple up-down and transformed up-down); the second is the Parameter Estimation by Sequential Testing (PEST); and the third is the Maximum Likelihood Procedure (MLP). The toolbox comes with more than twenty built-in experiments each provided with the recommended (default) parameters. However, if desired, these parameters can be modified through an intuitive and user friendly graphical interface and stored for future use (no programming skills are required). Finally, PSYCHOACOUSTICS is very flexible as it comes with several signal generators and can be easily extended for any experiment.

PSYCHOACOUSTICS: a comprehensive MATLAB toolbox for auditory testing

PubMed Central

Soranzo, Alessandro; Grassi, Massimo

2014-01-01

PSYCHOACOUSTICS is a new MATLAB toolbox which implements three classic adaptive procedures for auditory threshold estimation. The first includes those of the Staircase family (method of limits, simple up-down and transformed up-down); the second is the Parameter Estimation by Sequential Testing (PEST); and the third is the Maximum Likelihood Procedure (MLP). The toolbox comes with more than twenty built-in experiments each provided with the recommended (default) parameters. However, if desired, these parameters can be modified through an intuitive and user friendly graphical interface and stored for future use (no programming skills are required). Finally, PSYCHOACOUSTICS is very flexible as it comes with several signal generators and can be easily extended for any experiment. PMID:25101013

Modern CACSD using the Robust-Control Toolbox

NASA Technical Reports Server (NTRS)

Chiang, Richard Y.; Safonov, Michael G.

1989-01-01

The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.

Policy Analysis for Sustainable Development: The Toolbox for the Environmental Social Scientist

ERIC Educational Resources Information Center

Runhaar, Hens; Dieperink, Carel; Driessen, Peter

2006-01-01

Purpose: The paper seeks to propose the basic competencies of environmental social scientists regarding policy analysis for sustainable development. The ultimate goal is to contribute to an improvement of educational programmes in higher education by suggesting a toolbox that should be integrated in the curriculum. Design/methodology/approach:…

EPA RESPONSE PROTOCOL TOOLBOX TO HELP EVALUATION OF CONTAMINATION THREATS & RESPONDING TO THREATS: MODULE 1-WATER UTILITY PLANNING GUIDE

EPA Science Inventory

EPA's Office of Research and Development and Office of Water/Water Security Division have jointly developed a Response Protocol Toolbox (RPTB) to address the complex, multi-faceted challenges of a water utility's planning and response to intentional contamination of drinking wate...

Rural ITS toolbox and deployment plan for Regions 2, 6, 7 and 9 : ITS toolbox for rural and small urban areas

DOT National Transportation Integrated Search

1998-12-01

As a part of the Small Urban and Rural ITS Study it conducted in 4 of its more rural regions, the New York State Department of Transportation has developed a compendium of systems, devices and strategies that can enhance safety, provide information, ...

RESPONSE PROTOCOL TOOLBOX: PLANNING FOR AND RESPONDING TO DRINKING WATER CONTAMINATION THREATS AND INCIDENTS. OVERVIEW AND APPLICATION. INTERIM FINAL - DECEMBER 2003

EPA Science Inventory

The interim final Response Protocol Toolbox: Planning for and Responding to Contamination Threats to Drinking Water Systems is designed to help the water sector effectively and appropriately respond to intentional contamination threats and incidents. It was produced by EPA, buil...

RESPONSE PROTOCOL TOOLBOX: PLANNING FOR AND RESPONDING TO DRINKING WATER CONTAMINATION THREATS AND INCIDENTS. MODULE 4: ANALYTICAL GUIDE. INTERIM FINAL - DECEMBER 2003

EPA Science Inventory

The interim final Response Protocol Toolbox: Planning for and Responding to Contamination Threats to Drinking Water Systems is designed to help the water sector effectively and appropriately respond to intentional contamination threats and incidents. It was produced by EPA, buil...

The Psychometric Toolbox: An Excel Package for Use in Measurement and Psychometrics Courses

ERIC Educational Resources Information Center

Ferrando, Pere J.; Masip-Cabrera, Antoni; Navarro-González, David; Lorenzo-Seva, Urbano

2017-01-01

The Psychometric Toolbox (PT) is a user-friendly, non-commercial package mainly intended to be used for instructional purposes in introductory courses of educational and psychological measurement, psychometrics and statistics. The PT package is organized in six separate modules or sub-programs: Data preprocessor (descriptive analyses and data…

Toolbox or Adjustable Spanner? A Critical Comparison of Two Metaphors for Adaptive Decision Making

ERIC Educational Resources Information Center

Söllner, Anke; Bröder, Arndt

2016-01-01

For multiattribute decision tasks, different metaphors exist that describe the process of decision making and its adaptation to diverse problems and situations. Multiple strategy models (MSMs) assume that decision makers choose adaptively from a set of different strategies (toolbox metaphor), whereas evidence accumulation models (EAMs) hold that a…

FALCON: a toolbox for the fast contextualization of logical networks

PubMed Central

De Landtsheer, Sébastien; Trairatphisan, Panuwat; Lucarelli, Philippe; Sauter, Thomas

2017-01-01

Abstract Motivation Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. Results We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. Availability and implementation FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. Contact thomas.sauter@uni.lu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28673016

FALCON: a toolbox for the fast contextualization of logical networks.

PubMed

De Landtsheer, Sébastien; Trairatphisan, Panuwat; Lucarelli, Philippe; Sauter, Thomas

2017-11-01

Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. thomas.sauter@uni.lu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

NASA Astrophysics Data System (ADS)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

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

Vinuesa, Ricardo; Fick, Lambert; Negi, Prabal

In the present document we describe a toolbox for the spectral-element code Nek5000, aimed at computing turbulence statistics. The toolbox is presented for a small test case, namely a square duct with L x = 2h, L y = 2h and L z = 4h, where x, y and z are the horizontal, vertical and streamwise directions, respectively. The number of elements in the xy-plane is 16 X 16 = 256, and the number of elements in z is 4, leading to a total of 1,204 spectral elements. A polynomial order of N = 5 is chosen, and the meshmore » is generated using the Nek5000 tool genbox. The toolbox presented here allows to compute mean-velocity components, the Reynolds-stress tensor as well as turbulent kinetic energy (TKE) and Reynolds-stress budgets. Note that the present toolbox allows to compute turbulence statistics in turbulent flows with one homogeneous direction (where the statistics are based on time-averaging as well as averaging in the homogeneous direction), as well as in fully three-dimensional flows (with no periodic directions, where only time-averaging is considered).« less

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

Cross-species 3D virtual reality toolbox for visual and cognitive experiments.

PubMed

Doucet, Guillaume; Gulli, Roberto A; Martinez-Trujillo, Julio C

2016-06-15

Although simplified visual stimuli, such as dots or gratings presented on homogeneous backgrounds, provide strict control over the stimulus parameters during visual experiments, they fail to approximate visual stimulation in natural conditions. Adoption of virtual reality (VR) in neuroscience research has been proposed to circumvent this problem, by combining strict control of experimental variables and behavioral monitoring within complex and realistic environments. We have created a VR toolbox that maximizes experimental flexibility while minimizing implementation costs. A free VR engine (Unreal 3) has been customized to interface with any control software via text commands, allowing seamless introduction into pre-existing laboratory data acquisition frameworks. Furthermore, control functions are provided for the two most common programming languages used in visual neuroscience: Matlab and Python. The toolbox offers milliseconds time resolution necessary for electrophysiological recordings and is flexible enough to support cross-species usage across a wide range of paradigms. Unlike previously proposed VR solutions whose implementation is complex and time-consuming, our toolbox requires minimal customization or technical expertise to interface with pre-existing data acquisition frameworks as it relies on already familiar programming environments. Moreover, as it is compatible with a variety of display and input devices, identical VR testing paradigms can be used across species, from rodents to humans. This toolbox facilitates the addition of VR capabilities to any laboratory without perturbing pre-existing data acquisition frameworks, or requiring any major hardware changes. Copyright © 2016 Z. All rights reserved.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.

PubMed

Abulnaga, S Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M; Onyike, Chiadi U; Ying, Sarah H; Prince, Jerry L

2016-02-27

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

NASA Astrophysics Data System (ADS)

Abulnaga, S. Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M.; Onyike, Chiadi U.; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Online model evaluation of large-eddy simulations covering Germany with a horizontal resolution of 156 m

NASA Astrophysics Data System (ADS)

Hansen, Akio; Ament, Felix; Lammert, Andrea

2017-04-01

Large-eddy simulations have been performed since several decades, but due to computational limits most studies were restricted to small domains or idealised initial-/boundary conditions. Within the High definition clouds and precipitation for advancing climate prediction (HD(CP)2) project realistic weather forecasting like LES simulations were performed with the newly developed ICON LES model for several days. The domain covers central Europe with a horizontal resolution down to 156 m. The setup consists of more than 3 billion grid cells, by what one 3D dump requires roughly 500 GB. A newly developed online evaluation toolbox was created to check instantaneously for realistic model simulations. The toolbox automatically combines model results with observations and generates several quicklooks for various variables. So far temperature-/humidity profiles, cloud cover, integrated water vapour, precipitation and many more are included. All kind of observations like aircraft observations, soundings or precipitation radar networks are used. For each dataset, a specific module is created, which allows for an easy handling and enhancement of the toolbox. Most of the observations are automatically downloaded from the Standardized Atmospheric Measurement Database (SAMD). The evaluation tool should support scientists at monitoring computational costly model simulations as well as to give a first overview about model's performance. The structure of the toolbox as well as the SAMD database are presented. Furthermore, the toolbox was applied on an ICON LES sensitivity study, where example results are shown.

Using OPeNDAP's Data-Services Framework to Lift Mash-Ups above Blind Dates

NASA Astrophysics Data System (ADS)

Gallagher, J. H. R.; Fulker, D. W.

2015-12-01

OPeNDAP's data-as-service framework (Hyrax) matches diverse sources with many end-user tools and contexts. Keys to its flexibility include: A data model embracing tabular data alongside n-dim arrays and other structures useful in geoinformatics. A REST-like protocol that supports—via suffix notation—a growing set of output forms (netCDF, XML, etc.) plus a query syntax for subsetting. Subsetting applies (via constraints on column values) to tabular data or (via constraints on indices or coordinates) to array-style data . A handler-style architecture that admits a growing set of input types. Community members may contribute handlers, making Hyrax effective as middleware, where N sources are mapped to M outputs with order N+M effort (not NxM). Hyrax offers virtual aggregations of source data, enabling granularity aimed at users, not data-collectors. OPeNDAP-access libraries exist in multiple languages, including Python, Java, and C++. Recent enhancements are increasing this framework's interoperability (i.e., its mash-up) potential. Extensions implemented as servlets—running adjacent to Hyrax—are enriching the forms of aggregation and enabling new protocols: User-specified aggregations, namely, applying a query to (huge) lists of source granules, and receiving one (large) table or zipped netCDF file. OGC (Open Geospatial Consortium) protocols, WMS and WCS. A Webification (W10n) protocol that returns JavaScript Object Notation (JSON). Extensions to OPeNDAP's query language are reducing transfer volumes and enabling new forms of inspection. Advances underway include: Functions that, for triangular-mesh sources, return sub-meshes spec'd via geospatial bounding boxes. Functions that, for data from multiple, satellite-borne sensors (with differing orbits), select observations based on coincidence. Calculations of means, histograms, etc. that greatly reduce output volumes.. Paths for communities to contribute new server functions (in Python, e.g.) that data providers may incorporate into Hyrax via installation parameters. One could say Hyrax itself is a mash-up, but we suggest it as an instrument for a mash-up artist's toolbox. This instrument can support mash-ups built on netCDF files, OGC protocols, JavaScript Web pages, and/or programs written in Python, Java, C or C++.

Evidence for a Common Toolbox Based on Necrotrophy in a Fungal Lineage Spanning Necrotrophs, Biotrophs, Endophytes, Host Generalists and Specialists

PubMed Central

Andrew, Marion; Barua, Reeta; Short, Steven M.; Kohn, Linda M.

2012-01-01

The Sclerotiniaceae (Ascomycotina, Leotiomycetes) is a relatively recently evolved lineage of necrotrophic host generalists, and necrotrophic or biotrophic host specialists, some latent or symptomless. We hypothesized that they inherited a basic toolbox of genes for plant symbiosis from their common ancestor. Maintenance and evolutionary diversification of symbiosis could require selection on toolbox genes or on timing and magnitude of gene expression. The genes studied were chosen because their products have been previously investigated as pathogenicity factors in the Sclerotiniaceae. They encode proteins associated with cell wall degradation: acid protease 1 (acp1), aspartyl protease (asps), and polygalacturonases (pg1, pg3, pg5, pg6), and the oxalic acid (OA) pathway: a zinc finger transcription factor (pac1), and oxaloacetate acetylhydrolase (oah), catalyst in OA production, essential for full symptom production in Sclerotinia sclerotiorum. Site-specific likelihood analyses provided evidence for purifying selection in all 8 pathogenicity-related genes. Consistent with an evolutionary arms race model, positive selection was detected in 5 of 8 genes. Only generalists produced large, proliferating disease lesions on excised Arabidopsis thaliana leaves and oxalic acid by 72 hours in vitro. In planta expression of oah was 10–300 times greater among the necrotrophic host generalists than necrotrophic and biotrophic host specialists; pac1 was not differentially expressed. Ability to amplify 6/8 pathogenicity related genes and produce oxalic acid in all genera are consistent with the common toolbox hypothesis for this gene sample. That our data did not distinguish biotrophs from necrotrophs is consistent with 1) a common toolbox based on necrotrophy and 2) the most conservative interpretation of the 3-locus housekeeping gene phylogeny – a baseline of necrotrophy from which forms of biotrophy emerged at least twice. Early oah overexpression likely expands the host range of necrotrophic generalists in the Sclerotiniaceae, while specialists and biotrophs deploy oah, or other as-yet-unknown toolbox genes, differently. PMID:22253834

The 'Toolbox' of strategies for managing Haemonchus contortus in goats: What's in and what's out.

PubMed

Kearney, P E; Murray, P J; Hoy, J M; Hohenhaus, M; Kotze, A

2016-04-15

A dynamic and innovative approach to managing the blood-consuming nematode Haemonchus contortus in goats is critical to crack dependence on veterinary anthelmintics. H. contortus management strategies have been the subject of intense research for decades, and must be selected to create a tailored, individualized program for goat farms. Through the selection and combination of strategies from the Toolbox, an effective management program for H. contortus can be designed according to the unique conditions of each particular farm. This Toolbox investigates strategies including vaccines, bioactive forages, pasture/grazing management, behavioural management, natural immunity, FAMACHA, Refugia and strategic drenching, mineral/vitamin supplementation, copper Oxide Wire Particles (COWPs), breeding and selection/selecting resistant and resilient individuals, biological control and anthelmintic drugs. Barbervax(®), the ground-breaking Haemonchus vaccine developed and currently commercially available on a pilot scale for sheep, is prime for trialling in goats and would be an invaluable inclusion to this Toolbox. The specialised behaviours of goats, specifically their preferences to browse a variety of plants and accompanying physiological adaptations to the consumption of secondary compounds contained in browse, have long been unappreciated and thus overlooked as a valuable, sustainable strategy for Haemonchus management. These strategies are discussed in this review as to their value for inclusion into the 'Toolbox' currently, and the future implications of ongoing research for goat producers. Combining and manipulating strategies such as browsing behaviour, pasture management, bioactive forages and identifying and treating individual animals for haemonchosis, in addition to continuous evaluation of strategy effectiveness, is conducted using a model farm scenario. Selecting strategies from the Toolbox, with regard to their current availability, feasibility, economical cost and potential ease of implementation depending on the systems of production and their complementary nature, is the future of managing H. contortus in farmed goats internationally and maintaining the remaining efficacy of veterinary anthelmintics. Copyright © 2016 Elsevier B.V. All rights reserved.

Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities

NASA Astrophysics Data System (ADS)

Badjana, Hèou Maléki; Olofsson, Pontus; Woodcock, Curtis E.; Helmschrot, Joerg; Wala, Kpérkouma; Akpagana, Koffi

2017-12-01

In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol - all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land management planning, and the implementation of the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD).

Large-Eddy Simulation of Wind-Plant Aerodynamics: Preprint

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

Churchfield, M. J.; Lee, S.; Moriarty, P. J.

In this work, we present results of a large-eddy simulation of the 48 multi-megawatt turbines composing the Lillgrund wind plant. Turbulent inflow wind is created by performing an atmospheric boundary layer precursor simulation and turbines are modeled using a rotating, variable-speed actuator line representation. The motivation for this work is that few others have done wind plant large-eddy simulations with a substantial number of turbines, and the methods for carrying out the simulations are varied. We wish to draw upon the strengths of the existing simulations and our growing atmospheric large-eddy simulation capability to create a sound methodology for performingmore » this type of simulation. We have used the OpenFOAM CFD toolbox to create our solver.« less

3D capillary stop valves for versatile patterning inside microfluidic chips.

PubMed

Papadimitriou, V A; Segerink, L I; van den Berg, A; Eijkel, J C T

2018-02-13

The patterning of antibodies in microfluidics chips is always a delicate process that is usually done in an open chip before bonding. Typical bonding techniques such as plasma treatment can harm the antibodies with as result that they are removed from our fabrication toolbox. Here we propose a method, based on capillary phenomena using 3D capillary valves, that autonomously and conveniently allows us to pattern liquids inside closed chips. We theoretically analyse the system and demonstrate how our analysis can be used as a design tool for various applications. Chips patterned with the method were used for simple immunodetection of a cardiac biomarker which demonstrates its suitability for antibody patterning. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Psychometric considerations in the measurement of event-related brain potentials: Guidelines for measurement and reporting.

PubMed

Clayson, Peter E; Miller, Gregory A

2017-01-01

Failing to consider psychometric issues related to reliability and validity, differential deficits, and statistical power potentially undermines the conclusions of a study. In research using event-related brain potentials (ERPs), numerous contextual factors (population sampled, task, data recording, analysis pipeline, etc.) can impact the reliability of ERP scores. The present review considers the contextual factors that influence ERP score reliability and the downstream effects that reliability has on statistical analyses. Given the context-dependent nature of ERPs, it is recommended that ERP score reliability be formally assessed on a study-by-study basis. Recommended guidelines for ERP studies include 1) reporting the threshold of acceptable reliability and reliability estimates for observed scores, 2) specifying the approach used to estimate reliability, and 3) justifying how trial-count minima were chosen. A reliability threshold for internal consistency of at least 0.70 is recommended, and a threshold of 0.80 is preferred. The review also advocates the use of generalizability theory for estimating score dependability (the generalizability theory analog to reliability) as an improvement on classical test theory reliability estimates, suggesting that the latter is less well suited to ERP research. To facilitate the calculation and reporting of dependability estimates, an open-source Matlab program, the ERP Reliability Analysis Toolbox, is presented. Copyright © 2016 Elsevier B.V. All rights reserved.

A task-related and resting state realistic fMRI simulator for fMRI data validation

NASA Astrophysics Data System (ADS)

Hill, Jason E.; Liu, Xiangyu; Nutter, Brian; Mitra, Sunanda

2017-02-01

After more than 25 years of published functional magnetic resonance imaging (fMRI) studies, careful scrutiny reveals that most of the reported results lack fully decisive validation. The complex nature of fMRI data generation and acquisition results in unavoidable uncertainties in the true estimation and interpretation of both task-related activation maps and resting state functional connectivity networks, despite the use of various statistical data analysis methodologies. The goal of developing the proposed STANCE (Spontaneous and Task-related Activation of Neuronally Correlated Events) simulator is to generate realistic task-related and/or resting-state 4D blood oxygenation level dependent (BOLD) signals, given the experimental paradigm and scan protocol, by using digital phantoms of twenty normal brains available from BrainWeb (http://brainweb.bic.mni.mcgill.ca/brainweb/). The proposed simulator will include estimated system and modelled physiological noise as well as motion to serve as a reference to measured brain activities. In its current form, STANCE is a MATLAB toolbox with command line functions serving as an open-source add-on to SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The STANCE simulator has been designed in a modular framework so that the hemodynamic response (HR) and various noise models can be iteratively improved to include evolving knowledge about such models.

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Computer-intensive simulation of solid-state NMR experiments using SIMPSON.

PubMed

Tošner, Zdeněk; Andersen, Rasmus; Stevensson, Baltzar; Edén, Mattias; Nielsen, Niels Chr; Vosegaard, Thomas

2014-09-01

Conducting large-scale solid-state NMR simulations requires fast computer software potentially in combination with efficient computational resources to complete within a reasonable time frame. Such simulations may involve large spin systems, multiple-parameter fitting of experimental spectra, or multiple-pulse experiment design using parameter scan, non-linear optimization, or optimal control procedures. To efficiently accommodate such simulations, we here present an improved version of the widely distributed open-source SIMPSON NMR simulation software package adapted to contemporary high performance hardware setups. The software is optimized for fast performance on standard stand-alone computers, multi-core processors, and large clusters of identical nodes. We describe the novel features for fast computation including internal matrix manipulations, propagator setups and acquisition strategies. For efficient calculation of powder averages, we implemented interpolation method of Alderman, Solum, and Grant, as well as recently introduced fast Wigner transform interpolation technique. The potential of the optimal control toolbox is greatly enhanced by higher precision gradients in combination with the efficient optimization algorithm known as limited memory Broyden-Fletcher-Goldfarb-Shanno. In addition, advanced parallelization can be used in all types of calculations, providing significant time reductions. SIMPSON is thus reflecting current knowledge in the field of numerical simulations of solid-state NMR experiments. The efficiency and novel features are demonstrated on the representative simulations. Copyright © 2014 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

PubMed

Magnusson, Rasmus; Mariotti, Guido Pio; Köpsén, Mattias; Lövfors, William; Gawel, Danuta R; Jörnsten, Rebecka; Linde, Jörg; Nordling, Torbjörn E M; Nyman, Elin; Schulze, Sylvie; Nestor, Colm E; Zhang, Huan; Cedersund, Gunnar; Benson, Mikael; Tjärnberg, Andreas; Gustafsson, Mika

2017-06-01

Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naïve Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.

Verification of ARMA identification for modelling temporal correlation of GPS observations using the toolbox ARMASA

NASA Astrophysics Data System (ADS)

Luo, Xiaoguang; Mayer, Michael; Heck, Bernhard

2010-05-01

One essential deficiency of the stochastic model used in many GNSS (Global Navigation Satellite Systems) software products consists in neglecting temporal correlation of GNSS observations. Analysing appropriately detrended time series of observation residuals resulting from GPS (Global Positioning System) data processing, the temporal correlation behaviour of GPS observations can be sufficiently described by means of so-called autoregressive moving average (ARMA) processes. Using the toolbox ARMASA which is available free of charge in MATLAB® Central (open exchange platform for the MATLAB® and SIMULINK® user community), a well-fitting time series model can be identified automatically in three steps. Firstly, AR, MA, and ARMA models are computed up to some user-specified maximum order. Subsequently, for each model type, the best-fitting model is selected using the combined (for AR processes) resp. generalised (for MA and ARMA processes) information criterion. The final model identification among the best-fitting AR, MA, and ARMA models is performed based on the minimum prediction error characterising the discrepancies between the given data and the fitted model. The ARMA coefficients are computed using Burg's maximum entropy algorithm (for AR processes), Durbin's first (for MA processes) and second (for ARMA processes) methods, respectively. This paper verifies the performance of the automated ARMA identification using the toolbox ARMASA. For this purpose, a representative data base is generated by means of ARMA simulation with respect to sample size, correlation level, and model complexity. The model error defined as a transform of the prediction error is used as measure for the deviation between the true and the estimated model. The results of the study show that the recognition rates of underlying true processes increase with increasing sample sizes and decrease with rising model complexity. Considering large sample sizes, the true underlying processes can be correctly recognised for nearly 80% of the analysed data sets. Additionally, the model errors of first-order AR resp. MA processes converge clearly more rapidly to the corresponding asymptotical values than those of high-order ARMA processes.

An experimental toolbox for the generation of cold and ultracold polar molecules

NASA Astrophysics Data System (ADS)

Zeppenfeld, Martin; Gantner, Thomas; Glöckner, Rosa; Ibrügger, Martin; Koller, Manuel; Prehn, Alexander; Wu, Xing; Chervenkov, Sotir; Rempe, Gerhard

2017-01-01

Cold and ultracold molecules enable fascinating applications in quantum science. We present our toolbox of techniques to generate the required molecule ensembles, including buffergas cooling, centrifuge deceleration and optoelectrical Sisyphus cooling. We obtain excellent control over both the motional and internal molecular degrees of freedom, allowing us to aim at various applications.

Water Power Data and Tools | Water Power | NREL

Science.gov Websites

computer modeling tools and data with state-of-the-art design and analysis. Photo of a buoy designed around National Wind Technology Center's Information Portal as well as a WEC-Sim fact sheet. WEC Design Response Toolbox The WEC Design Response Toolbox provides extreme response and fatigue analysis tools specifically

Tensor Toolbox for MATLAB v. 3.0

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

Kola, Tamara; Bader, Brett W.; Acar Ataman, Evrim NMN

Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.

MOFA Software for the COBRA Toolbox

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

Griesemer, Marc; Navid, Ali

MOFA-COBRA is a software code for Matlab that performs Multi-Objective Flux Analysis (MOFA), a solving of linear programming problems. Teh leading software package for conducting different types of analyses using constrain-based models is the COBRA Toolbox for Matlab. MOFA-COBRA is an added tool for COBRA that solves multi-objective problems using a novel algorithm.

RESPONSE PROTOCOL TOOLBOX: PLANNING FOR AND RESPONDING TO DRINKING WATER CONTAMINATION THREATS AND INCIDENTS. MODULE 1: WATER UTILITIES PLANNING GUIDE - INTERIM FINAL - DECEMBER 2003

EPA Science Inventory

The interim final Response Protocol Toolbox: Planning for and Responding to Contamination Threats to Drinking Water Systems is designed to help the water sector effectively and appropriately respond to intentional contamination threats and incidents. It was produced by EPA, buil...

RESPONSE PROTOCOL TOOLBOX: PLANNING FOR AND RESPONDING TO DRINKING WATER CONTAMINATION THREATS AND INCIDENTS, MODULE 3: SITE CHARACTERIZATION AND SAMPLING GUIDE. INTERIM FINAL - DECEMBER 2003

EPA Science Inventory

The interim final Response Protocol Toolbox: Planning for and Responding to Contamination Threats to Drinking Water Systems is designed to help the water sector effectively and appropriately respond to intentional contamination threats and incidents. It was produced by EPA, buil...

The panacea toolbox of a PhD biomedical student.

PubMed

Skaik, Younis

2014-01-01

Doing a PhD (doctor of philosophy) for the sake of contribution to knowledge should give the student an immense enthusiasm through the PhD period. It is the time in one's life that one spends to "hit the nail on the head" in a specific area and topic of interest. A PhD consists mostly of hard work and tenacity; however, luck and genius might also play a little role. You can pass all PhD phases without having both luck and genius. The PhD student should have pre-PhD and PhD toolboxes, which are "sine quibus non" for getting successfully a PhD degree. In this manuscript, the toolboxes of the PhD student are discussed.

A Tol2 Gateway-Compatible Toolbox for the Study of the Nervous System and Neurodegenerative Disease.

PubMed

Don, Emily K; Formella, Isabel; Badrock, Andrew P; Hall, Thomas E; Morsch, Marco; Hortle, Elinor; Hogan, Alison; Chow, Sharron; Gwee, Serene S L; Stoddart, Jack J; Nicholson, Garth; Chung, Roger; Cole, Nicholas J

2017-02-01

Currently there is a lack in fundamental understanding of disease progression of most neurodegenerative diseases, and, therefore, treatments and preventative measures are limited. Consequently, there is a great need for adaptable, yet robust model systems to both investigate elementary disease mechanisms and discover effective therapeutics. We have generated a Tol2 Gateway-compatible toolbox to study neurodegenerative disorders in zebrafish, which includes promoters for astrocytes, microglia and motor neurons, multiple fluorophores, and compatibility for the introduction of genes of interest or disease-linked genes. This toolbox will advance the rapid and flexible generation of zebrafish models to discover the biology of the nervous system and the disease processes that lead to neurodegeneration.

Spectral analysis and filtering techniques in digital spatial data processing

USGS Publications Warehouse

Pan, Jeng-Jong

1989-01-01

A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

Cooling it gets hot.

PubMed

Weber, D O

1999-01-01

Conflict is an inevitable part of work and relationships. How it is handled determines what can and cannot be accomplished personally, professionally, and organizationally. The pressures and complexities of health care interactions breeds conflicts that require constant, skillful negotiation. Increasingly, health care leaders are recognizing that proficiency at recognizing sources of friction before trouble flares up and at managing and resolving disputes that do break out is an essential part of their executive "toolbox." Resources are now widely available for acquiring fundamental knowledge of dispute prevention and negotiation techniques, and for locating and engaging reliable expertise when third-party intervention appears necessarily to reconcile apparently intractable differences.

Innovative online faculty development utilizing the power of social media.

PubMed

Klein, Melissa; Niebuhr, Virginia; D'Alessandro, Donna

2013-01-01

Faculty development (FD) is important for continued professional development, but expense and distance remain challenging. These challenges could be minimized by the free and asynchronous nature of social media (SM). We sought to determine the utility and effectiveness of conducting a national online FD activity on Facebook by assessing participants' perceptions and use and facilitators' challenges. An educational activity of a national FD program was managed on a closed Facebook group. Activities included postings of educational technology goals, abstracting an article, and commenting on peers' postings. Sources of quantitative data included the Facebook postings and the survey responses. Surveys before, after, and 6 months after the activity assessed knowledge, attitudes and self-reported behaviors. Sources of qualitative data were the open-ended survey questions and the content of the Facebook postings. All participants completed the FD activity and evaluations, yielding 38 postings and 115 comments. Before the activity, 88% had a personal Facebook account, 64% were somewhat/very confident using Facebook, 77% thought SM would be useful for professional networking, and 12% had used it professionally. Six months after the activity, professional usage had increased to 35%. Continued use of Facebook for future presentations of this FD activity was recommended by 76%. Qualitative analysis yielded 12 types of Facebook postings and 7 themes related to using SM for FD. Conducting a national FD activity on Facebook yielded excellent participation rates and positive participant impressions, and it affected professional usage. Facebook may become an additional tool in the educator's toolbox for FD as a result of its acceptability and accessibility. Copyright © 2013 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Application of a moment tensor inversion code developed for mining-induced seismicity to fracture monitoring of civil engineering materials

NASA Astrophysics Data System (ADS)

Linzer, Lindsay; Mhamdi, Lassaad; Schumacher, Thomas

2015-01-01

A moment tensor inversion (MTI) code originally developed to compute source mechanisms from mining-induced seismicity data is now being used in the laboratory in a civil engineering research environment. Quantitative seismology methods designed for geological environments are being tested with the aim of developing techniques to assess and monitor fracture processes in structural concrete members such as bridge girders. In this paper, we highlight aspects of the MTI_Toolbox programme that make it applicable to performing inversions on acoustic emission (AE) data recorded by networks of uniaxial sensors. The influence of the configuration of a seismic network on the conditioning of the least-squares system and subsequent moment tensor results for a real, 3-D network are compared to a hypothetical 2-D version of the same network. This comparative analysis is undertaken for different cases: for networks consisting entirely of triaxial or uniaxial sensors; for both P and S-waves, and for P-waves only. The aim is to guide the optimal design of sensor configurations where only uniaxial sensors can be installed. Finally, the findings of recent laboratory experiments where the MTI_Toolbox has been applied to a concrete beam test are presented and discussed.

Streptomyces spp. in the biocatalysis toolbox.

PubMed

Spasic, Jelena; Mandic, Mina; Djokic, Lidija; Nikodinovic-Runic, Jasmina

2018-04-01

About 20,100 research publications dated 2000-2017 were recovered searching the PubMed and Web of Science databases for Streptomyces, which are the richest known source of bioactive molecules. However, these bacteria with versatile metabolism are powerful suppliers of biocatalytic tools (enzymes) for advanced biotechnological applications such as green chemical transformations and biopharmaceutical and biofuel production. The recent technological advances, especially in DNA sequencing coupled with computational tools for protein functional and structural prediction, and the improved access to microbial diversity enabled the easier access to enzymes and the ability to engineer them to suit a wider range of biotechnological processes. The major driver behind a dramatic increase in the utilization of biocatalysis is sustainable development and the shift toward bioeconomy that will, in accordance to the UN policy agenda "Bioeconomy to 2030," become a global effort in the near future. Streptomyces spp. already play a significant role among industrial microorganisms. The intention of this minireview is to highlight the presence of Streptomyces in the toolbox of biocatalysis and to give an overview of the most important advances in novel biocatalyst discovery and applications. Judging by the steady increase in a number of recent references (228 for the 2000-2017 period), it is clear that biocatalysts from Streptomyces spp. hold promises in terms of valuable properties and applicative industrial potential.

FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

NASA Astrophysics Data System (ADS)

Noel, Jean; Prieto, Juan C.; Styner, Martin

2017-03-01

Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.

Delft Dashboard: a quick setup tool for coastal and estuarine models

NASA Astrophysics Data System (ADS)

Nederhoff, C., III; Van Dongeren, A.; Van Ormondt, M.; Veeramony, J.

2016-02-01

We developed easy-to-use Delft DashBoard (DDB) software for the rapid set-up of coastal and estuarine hydrodynamic and basic morphological numerical models. In the "Model Maker" toolbox, users have the capability to set-up Delft3D models, in a minimal amount of time (in the order of a hour), for any location in the world. DDB draws upon public internet data sources of bathymetry and tidesto construct the model. With additional toolboxes, these models can be forced with parameterized hurricane wind fields, uplift of the sea surface due to tsunamis nested in publically available ocean models and forced with meteo data (wind speed, pressure, temperature) In this presentation we will show the skill of a model which is setup with Delft Dashboard and compare it to well-calibrated benchmark models. These latter models have been set-up using detailed input data and boundary conditions. We have tested the functionality of Delft DashBoard and evaluate the performance and robustness of the DDB model system on a variety of cases, ranging from a coastal to basin models. Furthermore, we have performed a sensitivity study to investigate the most critical physical and numerical processes. The software can benefit operational modellers, as well as scientists and consultants.

The Generic Mapping Tools 6: Classic versus Modern Mode

NASA Astrophysics Data System (ADS)

Wessel, P.; Uieda, L.; Luis, J. M. F.; Scharroo, R.; Smith, W. H. F.; Wobbe, F.

2017-12-01

The Generic Mapping Tools (GMT; gmt.soest.hawaii.edu) is a 25-year old, mature open-source software package for the analysis and display of geoscience data (e.g., interpolate, filter, manipulate, project and plot temporal and spatial data). The GMT "toolbox" includes about 80 core and 40 supplemental modules sharing a common set of command options, file structures, and documentation. GMT5, when released in 2013, introduced an application programming interface (API) to allow programmatic access to GMT from other computing environments. Since then, we have released a GMT/MATLAB toolbox, an experimental GMT/Julia package, and will soon introduce a GMT/Python module. In developing these extensions, we wanted to simplify the GMT learning curve but quickly realized the main stumbling blocks to GMT command-line mastery would be ported to the external environments unless we introduced major changes. With thousands of GMT scripts already in use by scientists around the world, we were acutely aware of the need for backwards compatibility. Our solution, to be released as GMT 6, was to add a modern run mode that complements the classic mode offered so far. Modern mode completely eliminates the top three obstacles for new (and not so new) GMT users: (1) The responsibility to properly stack PostScript layers manually (i.e., the -O -K dance), (2) the responsibility of handling output redirection of PostScript (create versus append), and (3) the need to provide commands with repeated information about regions (-R) and projections (-J). Thus, modern mode results in shorter, simpler scripts with fewer pitfalls, without interfering with classic scripts. Our implementation adds five new commands that begin and end a modern session, simplify figure management, automate the conversion of PostScript to more suitable formats, automate region detection, and offer a new automated subplot environment for multi-panel illustrations. Here, we highlight the GMT modern mode and the simplifications it offers, both for command-line use and in external environments. GMT 6 is in beta mode but accessible from our repository. Numerous improvements have been added in addition to modern mode; we expect a formal release in early 2018. Publication partially supported by FCT project UID/GEO/50019/2013 - Instituto D. Luiz.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

PubMed

Ferreira, Fábio S; Pereira, João M S; Duarte, João V; Castelo-Branco, Miguel

2017-01-01

Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Review of Qualitative Approaches for the Construction Industry: Designing a Risk Management Toolbox

PubMed Central

Spee, Ton; Gillen, Matt; Lentz, Thomas J.; Garrod, Andrew; Evans, Paul; Swuste, Paul

2011-01-01

Objectives This paper presents the framework and protocol design for a construction industry risk management toolbox. The construction industry needs a comprehensive, systematic approach to assess and control occupational risks. These risks span several professional health and safety disciplines, emphasized by multiple international occupational research agenda projects including: falls, electrocution, noise, silica, welding fumes, and musculoskeletal disorders. Yet, the International Social Security Association says, "whereas progress has been made in safety and health, the construction industry is still a high risk sector." Methods Small- and medium-sized enterprises (SMEs) employ about 80% of the world's construction workers. In recent years a strategy for qualitative occupational risk management, known as Control Banding (CB) has gained international attention as a simplified approach for reducing work-related risks. CB groups hazards into stratified risk 'bands', identifying commensurate controls to reduce the level of risk and promote worker health and safety. We review these qualitative solutions-based approaches and identify strengths and weaknesses toward designing a simplified CB 'toolbox' approach for use by SMEs in construction trades. Results This toolbox design proposal includes international input on multidisciplinary approaches for performing a qualitative risk assessment determining a risk 'band' for a given project. Risk bands are used to identify the appropriate level of training to oversee construction work, leading to commensurate and appropriate control methods to perform the work safely. Conclusion The Construction Toolbox presents a review-generated format to harness multiple solutions-based national programs and publications for controlling construction-related risks with simplified approaches across the occupational safety, health and hygiene professions. PMID:22953194

COMETS2: An advanced MATLAB toolbox for the numerical analysis of electric fields generated by transcranial direct current stimulation.

PubMed

Lee, Chany; Jung, Young-Jin; Lee, Sang Jun; Im, Chang-Hwan

2017-02-01

Since there is no way to measure electric current generated by transcranial direct current stimulation (tDCS) inside the human head through in vivo experiments, numerical analysis based on the finite element method has been widely used to estimate the electric field inside the head. In 2013, we released a MATLAB toolbox named COMETS, which has been used by a number of groups and has helped researchers to gain insight into the electric field distribution during stimulation. The aim of this study was to develop an advanced MATLAB toolbox, named COMETS2, for the numerical analysis of the electric field generated by tDCS. COMETS2 can generate any sizes of rectangular pad electrodes on any positions on the scalp surface. To reduce the large computational burden when repeatedly testing multiple electrode locations and sizes, a new technique to decompose the global stiffness matrix was proposed. As examples of potential applications, we observed the effects of sizes and displacements of electrodes on the results of electric field analysis. The proposed mesh decomposition method significantly enhanced the overall computational efficiency. We implemented an automatic electrode modeler for the first time, and proposed a new technique to enhance the computational efficiency. In this paper, an efficient toolbox for tDCS analysis is introduced (freely available at http://www.cometstool.com). It is expected that COMETS2 will be a useful toolbox for researchers who want to benefit from the numerical analysis of electric fields generated by tDCS. Copyright © 2016. Published by Elsevier B.V.

Review of qualitative approaches for the construction industry: designing a risk management toolbox.

PubMed

Zalk, David M; Spee, Ton; Gillen, Matt; Lentz, Thomas J; Garrod, Andrew; Evans, Paul; Swuste, Paul

2011-06-01

This paper presents the framework and protocol design for a construction industry risk management toolbox. The construction industry needs a comprehensive, systematic approach to assess and control occupational risks. These risks span several professional health and safety disciplines, emphasized by multiple international occupational research agenda projects including: falls, electrocution, noise, silica, welding fumes, and musculoskeletal disorders. Yet, the International Social Security Association says, "whereas progress has been made in safety and health, the construction industry is still a high risk sector." Small- and medium-sized enterprises (SMEs) employ about 80% of the world's construction workers. In recent years a strategy for qualitative occupational risk management, known as Control Banding (CB) has gained international attention as a simplified approach for reducing work-related risks. CB groups hazards into stratified risk 'bands', identifying commensurate controls to reduce the level of risk and promote worker health and safety. We review these qualitative solutions-based approaches and identify strengths and weaknesses toward designing a simplified CB 'toolbox' approach for use by SMEs in construction trades. This toolbox design proposal includes international input on multidisciplinary approaches for performing a qualitative risk assessment determining a risk 'band' for a given project. Risk bands are used to identify the appropriate level of training to oversee construction work, leading to commensurate and appropriate control methods to perform the work safely. The Construction Toolbox presents a review-generated format to harness multiple solutions-based national programs and publications for controlling construction-related risks with simplified approaches across the occupational safety, health and hygiene professions.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

PubMed Central

Ferreira, Fábio S.; Pereira, João M.S.; Duarte, João V.; Castelo-Branco, Miguel

2017-01-01

Background: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Objective: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). Method: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately – using standard univariate VBM - and simultaneously, with multivariate analyses. Results: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. Conclusion: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities. PMID:28761571

e-Infrastuctures interoperability: the Geohazards Exploitation Platform for the use of satellite earth observations in Geosciences

NASA Astrophysics Data System (ADS)

Caumont, Herve; Brito, Fabrice; Mathot, Emmanuel; Barchetta, Francesco; Loeschau, Frank

2015-04-01

We present recent achievements with the Geohazards Exploitation Platform (GEP), a European contribution to the GEO SuperSites, and its interoperability with the MEDiterranean SUpersite Volcanoes (MED-SUV) e- infrastructure. The GEP is a catalyst for the use of satellite Earth observation missions, providing data to initiatives such as the GEO Geohazard Supersites and Natural Laboratories (GSNL), the Volcano and Seismic Hazards CEOS Pilots or the European Plate Observing System (EPOS). As satellite sensors are delivering increasing amounts of data, researchers need more computational science tools and services. The GEP contribution in this regard allows scientists to access different data types, relevant to the same area and phenomena and to directly stage selected inputs to scalable processing applications that deliver EO-based science products. With the GEP concept of operation for improved collaboration, a partner can bring its processing tools, use from his workspace other shared toolboxes and access large data repositories. GEP is based on Open Source Software components, on a Cloud Services architecture inheriting a range of ESA and EC funded innovations, and is associating the scientific community and SMEs in implementing new capabilities. Via MED-SUV, we are making discoverable and accessible a large number of products over the Mt. Etna, Vesu- vius/Campi Flegrei volcanic areas, which are of broader interest for Geosciences researchers, so they can process ENVISAT MERIS, ENVISAT ASAR, and ERS SAR data (both Level 1 and Level 2) hosted in the ESA clusters and in ESA's Virtual Archive, TerraSAR-X data hosted in DLR's Virtual Archive, as well as data hosted in other dedicated MED-SUV Virtual Archives (e.g. for LANDSAT, EOS-1). GEP will gradually access Sentinel-1A data, other space agencies data and value-added products. Processed products can also be published and archived on the MED-SUV e-Infrastructure. In this effort, data policy rules applied to the acquisitions are verified against the GEOSS Data Collection of Open Resources for Everyone (GEOSS Data-CORE) principles. The resulting infras- tructure repositories include connectivity to the GEOSS Data Access Broker (DAB), through the "OGC CS-W OpenSearch Geo and Time extensions" interface standard, a key interoperability arrangement used by the MED- SUV systems, making EO data products available to both the project partners and the broader initiatives. GEP is also proposing and further developing hosted processing, aimed at MED-SUV researchers' work on new methods to integrate in-situ and satellite sensors data: a set of users services (concept of Platform-as-a-Service, or PaaS) for generating value-added products, including tools to design and develop Hadoop-enabled processing chains. The PaaS core engine is the Developer Cloud Sandboxes service, where scalable processing chains are prepared and validated. The PaaS makes use of Virtual Machines technology, and of middleware for scaling-out processing tasks via interfaces to commercial Cloud Providers, or through research agreements to academic re- sources like EGI.eu. After integration, processors are deployed and invoked 'as-a-Service' by partners via OGC Web Processing Service standard interface, or shared as reusable virtualized resources. Recent integration work covered e.g. ROI_PAC, GMTSAR and DORIS ADORE toolboxes along with supporting processing services such as DEM generation. Such approach has been discussed also with the MARSite project, ensuring the adopted solu- tions are aligned. As part of the MED-SUV project, we are developing tools and services supporting researchers working on new data fusion methods, and fostering collaboration between different end users and partners, including towards the GEO communities. Overall, the approach provides an integrated European contribution for the exploitation of decades of scientific data gathered from Earth observation satellites.

T-MATS Toolbox for the Modeling and Analysis of Thermodynamic Systems

NASA Technical Reports Server (NTRS)

Chapman, Jeffryes W.

2014-01-01

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a MATLABSimulink (The MathWorks Inc.) plug-in for creating and simulating thermodynamic systems and controls. The package contains generic parameterized components that can be combined with a variable input iterative solver and optimization algorithm to create complex system models, such as gas turbines.

Various Solution Methods, Accompanied by Dynamic Investigation, for the Same Problem as a Means for Enriching the Mathematical Toolbox

ERIC Educational Resources Information Center

Oxman, Victor; Stupel, Moshe

2018-01-01

A geometrical task is presented with multiple solutions using different methods, in order to show the connection between various branches of mathematics and to highlight the importance of providing the students with an extensive 'mathematical toolbox'. Investigation of the property that appears in the task was carried out using a computerized tool.

Various solution methods, accompanied by dynamic investigation, for the same problem as a means for enriching the mathematical toolbox

NASA Astrophysics Data System (ADS)

Oxman, Victor; Stupel, Moshe

2018-04-01

A geometrical task is presented with multiple solutions using different methods, in order to show the connection between various branches of mathematics and to highlight the importance of providing the students with an extensive 'mathematical toolbox'. Investigation of the property that appears in the task was carried out using a computerized tool.

GOCE User Toolbox and Tutorial

NASA Astrophysics Data System (ADS)

Knudsen, P.; Benveniste, J.

2011-07-01

The GOCE User Toolbox GUT is a compilation of tools for the utilisation and analysis of GOCE Level 2 products. GUT support applications in Geodesy, Oceanography and Solid Earth Physics. The GUT Tutorial provides information and guidance in how to use the toolbox for a variety of applications. GUT consists of a series of advanced computer routines that carry out the required computations. It may be used on Windows PCs, UNIX/Linux Workstations, and Mac. The toolbox is supported by The GUT Algorithm Description and User Guide and The GUT Install Guide. A set of a-priori data and models are made available as well. GUT has been developed in a collaboration within the GUT Core Group. The GUT Core Group: S. Dinardo, D. Serpe, B.M. Lucas, R. Floberghagen, A. Horvath (ESA), O. Andersen, M. Herceg (DTU), M.-H. Rio, S. Mulet, G. Larnicol (CLS), J. Johannessen, L.Bertino (NERSC), H. Snaith, P. Challenor (NOC), K. Haines, D. Bretherton (NCEO), C. Hughes (POL), R.J. Bingham (NU), G. Balmino, S. Niemeijer, I. Price, L. Cornejo (S&T), M. Diament, I Panet (IPGP), C.C. Tscherning (KU), D. Stammer, F. Siegismund (UH), T. Gruber (TUM),

Turbo-Satori: a neurofeedback and brain-computer interface toolbox for real-time functional near-infrared spectroscopy.

PubMed

Lührs, Michael; Goebel, Rainer

2017-10-01

Turbo-Satori is a neurofeedback and brain-computer interface (BCI) toolbox for real-time functional near-infrared spectroscopy (fNIRS). It incorporates multiple pipelines from real-time preprocessing and analysis to neurofeedback and BCI applications. The toolbox is designed with a focus in usability, enabling a fast setup and execution of real-time experiments. Turbo-Satori uses an incremental recursive least-squares procedure for real-time general linear model calculation and support vector machine classifiers for advanced BCI applications. It communicates directly with common NIRx fNIRS hardware and was tested extensively ensuring that the calculations can be performed in real time without a significant change in calculation times for all sampling intervals during ongoing experiments of up to 6 h of recording. Enabling immediate access to advanced processing features also allows the use of this toolbox for students and nonexperts in the field of fNIRS data acquisition and processing. Flexible network interfaces allow third party stimulus applications to access the processed data and calculated statistics in real time so that this information can be easily incorporated in neurofeedback or BCI presentations.

HYDRORECESSION: A toolbox for streamflow recession analysis

NASA Astrophysics Data System (ADS)

Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

A novel toolbox for E. coli lysis monitoring.

PubMed

Rajamanickam, Vignesh; Wurm, David; Slouka, Christoph; Herwig, Christoph; Spadiut, Oliver

2017-01-01

The bacterium Escherichia coli is a well-studied recombinant host organism with a plethora of applications in biotechnology. Highly valuable biopharmaceuticals, such as antibody fragments and growth factors, are currently being produced in E. coli. However, the high metabolic burden during recombinant protein production can lead to cell death, consequent lysis, and undesired product loss. Thus, fast and precise analyzers to monitor E. coli bioprocesses and to retrieve key process information, such as the optimal time point of harvest, are needed. However, such reliable monitoring tools are still scarce to date. In this study, we cultivated an E. coli strain producing a recombinant single-chain antibody fragment in the cytoplasm. In bioreactor cultivations, we purposely triggered cell lysis by pH ramps. We developed a novel toolbox using UV chromatograms as fingerprints and chemometric techniques to monitor these lysis events and used flow cytometry (FCM) as reference method to quantify viability offline. Summarizing, we were able to show that a novel toolbox comprising HPLC chromatogram fingerprinting and data science tools allowed the identification of E. coli lysis in a fast and reliable manner. We are convinced that this toolbox will not only facilitate E. coli bioprocess monitoring but will also allow enhanced process control in the future.