Building a symbolic computer algebra toolbox to compute 2D Fourier transforms in polar coordinates

PubMed Central

Dovlo, Edem; Baddour, Natalie

2015-01-01

The development of a symbolic computer algebra toolbox for the computation of two dimensional (2D) Fourier transforms in polar coordinates is presented. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. The advantages of our method include: • The implementation of the 2D Fourier transform in polar coordinates within the toolbox via the combination of two significantly simpler transforms. • The modular approach along with the idea of lookup tables implemented help avoid the issue of indeterminate results which may occur when attempting to directly evaluate the transform. • The concept also helps prevent unnecessary computation of already known transforms thereby saving memory and processing time. PMID:26150988

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

ASAP (Automatic Software for ASL Processing): A toolbox for processing Arterial Spin Labeling images.

PubMed

Mato Abad, Virginia; García-Polo, Pablo; O'Daly, Owen; Hernández-Tamames, Juan Antonio; Zelaya, Fernando

2016-04-01

The method of Arterial Spin Labeling (ASL) has experienced a significant rise in its application to functional imaging, since it is the only technique capable of measuring blood perfusion in a truly non-invasive manner. Currently, there are no commercial packages for processing ASL data and there is no recognized standard for normalizing ASL data to a common frame of reference. This work describes a new Automated Software for ASL Processing (ASAP) that can automatically process several ASL datasets. ASAP includes functions for all stages of image pre-processing: quantification, skull-stripping, co-registration, partial volume correction and normalization. To assess the applicability and validity of the toolbox, this work shows its application in the study of hypoperfusion in a sample of healthy subjects at risk of progressing to Alzheimer's disease. ASAP requires limited user intervention, minimizing the possibility of random and systematic errors, and produces cerebral blood flow maps that are ready for statistical group analysis. The software is easy to operate and results in excellent quality of spatial normalization. The results found in this evaluation study are consistent with previous studies that find decreased perfusion in Alzheimer's patients in similar regions and demonstrate the applicability of ASAP. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

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.

Quantitative nanoscopy: Tackling sampling limitations in (S)TEM imaging of polymers and composites.

PubMed

Gnanasekaran, Karthikeyan; Snel, Roderick; de With, Gijsbertus; Friedrich, Heiner

2016-01-01

Sampling limitations in electron microscopy questions whether the analysis of a bulk material is representative, especially while analyzing hierarchical morphologies that extend over multiple length scales. We tackled this problem by automatically acquiring a large series of partially overlapping (S)TEM images with sufficient resolution, subsequently stitched together to generate a large-area map using an in-house developed acquisition toolbox (TU/e Acquisition ToolBox) and stitching module (TU/e Stitcher). In addition, we show that quantitative image analysis of the large scale maps provides representative information that can be related to the synthesis and process conditions of hierarchical materials, which moves electron microscopy analysis towards becoming a bulk characterization tool. We demonstrate the power of such an analysis by examining two different multi-phase materials that are structured over multiple length scales. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

ESA BRAT (Broadview Radar Altimetry Toolbox) and GUT (GOCE User Toolbox) toolboxes

NASA Astrophysics Data System (ADS)

Benveniste, J.; Ambrozio, A.; Restano, M.

2016-12-01

The Broadview Radar Altimetry Toolbox (BRAT) is a collection of tools designed to facilitate the processing of radar altimetry data from previous and current altimetry missions, including the upcoming Sentinel-3A L1 and L2 products. A tutorial is included providing plenty of use cases. BRAT's future release (4.0.0) is planned for September 2016. Based on the community feedback, the frontend has been further improved and simplified whereas the capability to use BRAT in conjunction with MATLAB/IDL or C/C++/Python/Fortran, allowing users to obtain desired data bypassing the data-formatting hassle, remains unchanged. Several kinds of computations can be done within BRAT involving the combination of data fields, that can be saved for future uses, either by using embedded formulas including those from oceanographic altimetry, or by implementing ad-hoc Python modules created by users to meet their needs. BRAT can also be used to quickly visualise data, or to translate data into other formats, e.g. from NetCDF to raster images. The GOCE User Toolbox (GUT) is a compilation of tools for the use and the analysis of GOCE gravity field models. It facilitates using, viewing and post-processing GOCE L2 data and allows gravity field data, in conjunction and consistently with any other auxiliary data set, to be pre-processed by beginners in gravity field processing, for oceanographic and hydrologic as well as for solid earth applications at both regional and global scales. Hence, GUT facilitates the extensive use of data acquired during GRACE and GOCE missions. In the current 3.0 version, GUT has been outfitted with a graphical user interface allowing users to visually program data processing workflows. Further enhancements aiming at facilitating the use of gradients, the anisotropic diffusive filtering, and the computation of Bouguer and isostatic gravity anomalies have been introduced. Packaged with GUT is also GUT's VCM (Variance-Covariance Matrix) tool for analysing GOCE's variance-covariance matrices. BRAT and GUT toolboxes can be freely downloaded, along with ancillary material, at https://earth.esa.int/brat and https://earth.esa.int/gut.

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

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.

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

Introduction of A New Toolbox for Processing Digital Images From Multiple Camera Networks: FMIPROT

NASA Astrophysics Data System (ADS)

Melih Tanis, Cemal; Nadir Arslan, Ali

2017-04-01

Webcam networks intended for scientific monitoring of ecosystems is providing digital images and other environmental data for various studies. Also, other types of camera networks can also be used for scientific purposes, e.g. usage of traffic webcams for phenological studies, camera networks for ski tracks and avalanche monitoring over mountains for hydrological studies. To efficiently harness the potential of these camera networks, easy to use software which can obtain and handle images from different networks having different protocols and standards is necessary. For the analyses of the images from webcam networks, numerous software packages are freely available. These software packages have different strong features not only for analyzing but also post processing digital images. But specifically for the ease of use, applicability and scalability, a different set of features could be added. Thus, a more customized approach would be of high value, not only for analyzing images of comprehensive camera networks, but also considering the possibility to create operational data extraction and processing with an easy to use toolbox. At this paper, we introduce a new toolbox, entitled; Finnish Meteorological Institute Image PROcessing Tool (FMIPROT) which a customized approach is followed. FMIPROT has currently following features: • straightforward installation, • no software dependencies that require as extra installations, • communication with multiple camera networks, • automatic downloading and handling images, • user friendly and simple user interface, • data filtering, • visualizing results on customizable plots, • plugins; allows users to add their own algorithms. Current image analyses in FMIPROT include "Color Fraction Extraction" and "Vegetation Indices". The analysis of color fraction extraction is calculating the fractions of the colors in a region of interest, for red, green and blue colors along with brightness and luminance parameters. The analysis of vegetation indices is a collection of indices used in vegetation phenology and includes "Green Fraction" (green chromatic coordinate), "Green-Red Vegetation Index" and "Green Excess Index". "Snow cover fraction" analysis which detects snow covered pixels in the images and georeference them on a geospatial plane to calculate the snow cover fraction is being implemented at the moment. FMIPROT is being developed during the EU Life+ MONIMET project. Altogether we mounted 28 cameras at 14 different sites in Finland as MONIMET camera network. In this paper, we will present details of FMIPROT and analysis results from MONIMET camera network. We will also discuss on future planned developments of FMIPROT.

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

Graphical user interface for image acquisition and processing

DOEpatents

Goldberg, Kenneth A.

2002-01-01

An event-driven GUI-based image acquisition interface for the IDL programming environment designed for CCD camera control and image acquisition directly into the IDL environment where image manipulation and data analysis can be performed, and a toolbox of real-time analysis applications. Running the image acquisition hardware directly from IDL removes the necessity of first saving images in one program and then importing the data into IDL for analysis in a second step. Bringing the data directly into IDL creates an opportunity for the implementation of IDL image processing and display functions in real-time. program allows control over the available charge coupled device (CCD) detector parameters, data acquisition, file saving and loading, and image manipulation and processing, all from within IDL. The program is built using IDL's widget libraries to control the on-screen display and user interface.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology.

PubMed

Markiewicz, Tomasz

2011-03-30

The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8 GHz 4 GB RAM server with 768x576 pixel size, 1.28 Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server - 3.5 seconds, at remote analysis - 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology

PubMed Central

2011-01-01

Background The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. Methods In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. Results The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8GHz 4GB RAM server with 768x576 pixel size, 1.28Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server – 3.5 seconds, at remote analysis – 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. Conclusions The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system. PMID:21489188

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.

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

TH-CD-206-01: Expectation-Maximization Algorithm-Based Tissue Mixture Quantification for Perfusion MRI

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

Han, H; Xing, L; Liang, Z

Purpose: To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images. Methods: The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1- and T2-weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non-brain structures from the T1- and T2-weighted MR images. (3) We applied a multi-spectral tissue-mixture segmentation algorithm on both T1- and T2-structural MR images to roughly estimate the fraction of eachmore » tissue type - white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down-sampled and mapped onto the ASL voxel array via a co-registration operation. (5) The presented 4-dimensional expectation-maximization (4D-EM) algorithm takes the down-sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest. Results: Experimental results on three volunteer datasets demonstrated that the multi-spectral tissue-mixture segmentation algorithm was effective to initialize tissue mixtures from T1- and T2-weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D-EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images. Conclusion: A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions, which is valuable for the early diagnosis of certain brain diseases, e.g. multiple sclerosis.« less

The InSAR Scientific Computing Environment (ISCE): An Earth Science SAR Processing Framework, Toolbox, and Foundry

NASA Astrophysics Data System (ADS)

Agram, P. S.; Gurrola, E. M.; Lavalle, M.; Sacco, G. F.; Rosen, P. A.

2016-12-01

The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.

Characterization of Disease-Related Covariance Topographies with SSMPCA Toolbox: Effects of Spatial Normalization and PET Scanners

PubMed Central

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2013-01-01

In order to generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [18F]fluorodeoxyglucose PET scans from PD patients and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5 and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in PD patients imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. PMID:23671030

Characterization of disease-related covariance topographies with SSMPCA toolbox: effects of spatial normalization and PET scanners.

PubMed

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2014-05-01

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. Copyright © 2013 Wiley Periodicals, Inc.

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.

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

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.

Role of Gist and PHOG Features in Computer-Aided Diagnosis of Tuberculosis without Segmentation

PubMed Central

Chauhan, Arun; Chauhan, Devesh; Rout, Chittaranjan

2014-01-01

Purpose Effective diagnosis of tuberculosis (TB) relies on accurate interpretation of radiological patterns found in a chest radiograph (CXR). Lack of skilled radiologists and other resources, especially in developing countries, hinders its efficient diagnosis. Computer-aided diagnosis (CAD) methods provide second opinion to the radiologists for their findings and thereby assist in better diagnosis of cancer and other diseases including TB. However, existing CAD methods for TB are based on the extraction of textural features from manually or semi-automatically segmented CXRs. These methods are prone to errors and cannot be implemented in X-ray machines for automated classification. Methods Gabor, Gist, histogram of oriented gradients (HOG), and pyramid histogram of oriented gradients (PHOG) features extracted from the whole image can be implemented into existing X-ray machines to discriminate between TB and non-TB CXRs in an automated manner. Localized features were extracted for the above methods using various parameters, such as frequency range, blocks and region of interest. The performance of these features was evaluated against textural features. Two digital CXR image datasets (8-bit DA and 14-bit DB) were used for evaluating the performance of these features. Results Gist (accuracy 94.2% for DA, 86.0% for DB) and PHOG (accuracy 92.3% for DA, 92.0% for DB) features provided better results for both the datasets. These features were implemented to develop a MATLAB toolbox, TB-Xpredict, which is freely available for academic use at http://sourceforge.net/projects/tbxpredict/. This toolbox provides both automated training and prediction modules and does not require expertise in image processing for operation. Conclusion Since the features used in TB-Xpredict do not require segmentation, the toolbox can easily be implemented in X-ray machines. This toolbox can effectively be used for the mass screening of TB in high-burden areas with improved efficiency. PMID:25390291

Practical Approach for Hyperspectral Image Processing in Python

NASA Astrophysics Data System (ADS)

Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

2018-04-01

Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

The Hico Image Processing System: A Web-Accessible Hyperspectral Remote Sensing Toolbox

NASA Astrophysics Data System (ADS)

Harris, A. T., III; Goodman, J.; Justice, B.

2014-12-01

As the quantity of Earth-observation data increases, the use-case for hosting analytical tools in geospatial data centers becomes increasingly attractive. To address this need, HySpeed Computing and Exelis VIS have developed the HICO Image Processing System, a prototype cloud computing system that provides online, on-demand, scalable remote sensing image processing capabilities. The system provides a mechanism for delivering sophisticated image processing analytics and data visualization tools into the hands of a global user community, who will only need a browser and internet connection to perform analysis. Functionality of the HICO Image Processing System is demonstrated using imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), an imaging spectrometer located on the International Space Station (ISS) that is optimized for acquisition of aquatic targets. Example applications include a collection of coastal remote sensing algorithms that are directed at deriving critical information on water and habitat characteristics of our vulnerable coastal environment. The project leverages the ENVI Services Engine as the framework for all image processing tasks, and can readily accommodate the rapid integration of new algorithms, datasets and processing tools.

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.

An approach for traffic prohibition sign detection

NASA Astrophysics Data System (ADS)

Li, Qingquan; Xu, Dihong; Li, Bijun; Zeng, Zhe

2006-10-01

This paper presents an off-line traffic prohibition sign detection approach, whose core is based on combination with the color feature of traffic prohibition signs, shape feature and degree of circularity. Matlab-Image-processing toolbox is used for this purpose. In order to reduce the computational cost, a pre-processing of the image is applied before the core. Then, we employ the obvious redness attribute of prohibition signs to coarsely eliminate the non-redness image in the input data. Again, a edge-detection operator, Canny edge detector, is applied to extract the potential edge. Finally, Degree of circularity is used to verdict the traffic prohibition sign. Experimental results show that our systems offer satisfactory performance.

Despeckle filtering software toolbox for ultrasound imaging of the common carotid artery.

PubMed

Loizou, Christos P; Theofanous, Charoula; Pantziaris, Marios; Kasparis, Takis

2014-04-01

Ultrasound imaging of the common carotid artery (CCA) is a non-invasive tool used in medicine to assess the severity of atherosclerosis and monitor its progression through time. It is also used in border detection and texture characterization of the atherosclerotic carotid plaque in the CCA, the identification and measurement of the intima-media thickness (IMT) and the lumen diameter that all are very important in the assessment of cardiovascular disease (CVD). Visual perception, however, is hindered by speckle, a multiplicative noise, that degrades the quality of ultrasound B-mode imaging. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image segmentation of the IMT and the atherosclerotic carotid plaque in ultrasound images. In order to facilitate this preprocessing step, we have developed in MATLAB(®) a unified toolbox that integrates image despeckle filtering (IDF), texture analysis and image quality evaluation techniques to automate the pre-processing and complement the disease evaluation in ultrasound CCA images. The proposed software, is based on a graphical user interface (GUI) and incorporates image normalization, 10 different despeckle filtering techniques (DsFlsmv, DsFwiener, DsFlsminsc, DsFkuwahara, DsFgf, DsFmedian, DsFhmedian, DsFad, DsFnldif, DsFsrad), image intensity normalization, 65 texture features, 15 quantitative image quality metrics and objective image quality evaluation. The software is publicly available in an executable form, which can be downloaded from http://www.cs.ucy.ac.cy/medinfo/. It was validated on 100 ultrasound images of the CCA, by comparing its results with quantitative visual analysis performed by a medical expert. It was observed that the despeckle filters DsFlsmv, and DsFhmedian improved image quality perception (based on the expert's assessment and the image texture and quality metrics). It is anticipated that the system could help the physician in the assessment of cardiovascular image analysis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

ExoSOFT: Exoplanet Simple Orbit Fitting Toolbox

NASA Astrophysics Data System (ADS)

Mede, Kyle; Brandt, Timothy D.

2017-08-01

ExoSOFT provides orbital analysis of exoplanets and binary star systems. It fits any combination of astrometric and radial velocity data, and offers four parameter space exploration techniques, including MCMC. It is packaged with an automated set of post-processing and plotting routines to summarize results, and is suitable for performing orbital analysis during surveys with new radial velocity and direct imaging instruments.

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.

A Toolbox for Ab Initio 3-D Reconstructions in Single-particle Electron Microscopy

PubMed Central

Voss, Neil R; Lyumkis, Dmitry; Cheng, Anchi; Lau, Pick-Wei; Mulder, Anke; Lander, Gabriel C; Brignole, Edward J; Fellmann, Denis; Irving, Christopher; Jacovetty, Erica L; Leung, Albert; Pulokas, James; Quispe, Joel D; Winkler, Hanspeter; Yoshioka, Craig; Carragher, Bridget; Potter, Clinton S

2010-01-01

Structure determination of a novel macromolecular complex via single-particle electron microscopy depends upon overcoming the challenge of establishing a reliable 3-D reconstruction using only 2-D images. There are a variety of strategies that deal with this issue, but not all of them are readily accessible and straightforward to use. We have developed a “toolbox” of ab initio reconstruction techniques that provide several options for calculating 3-D volumes in an easily managed and tightly controlled work-flow that adheres to standard conventions and formats. This toolbox is designed to streamline the reconstruction process by removing the necessity for bookkeeping, while facilitating transparent data transfer between different software packages. It currently includes procedures for calculating ab initio reconstructions via random or orthogonal tilt geometry, tomograms, and common lines, all of which have been tested using the 50S ribosomal subunit. Our goal is that the accessibility of multiple independent reconstruction algorithms via this toolbox will improve the ease with which models can be generated, and provide a means of evaluating the confidence and reliability of the final reconstructed map. PMID:20018246

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.

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.

GUIDOS: tools for the assessment of pattern, connectivity, and fragmentation

NASA Astrophysics Data System (ADS)

Vogt, Peter

2013-04-01

Pattern, connectivity, and fragmentation can be considered as pillars for a quantitative analysis of digital landscape images. The free software toolbox GUIDOS (http://forest.jrc.ec.europa.eu/download/software/guidos) includes a variety of dedicated methodologies for the quantitative assessment of these features. Amongst others, Morphological Spatial Pattern Analysis (MSPA) is used for an intuitive description of image pattern structures and the automatic detection of connectivity pathways. GUIDOS includes tools for the detection and quantitative assessment of key nodes and links as well as to define connectedness in raster images and to setup appropriate input files for an enhanced network analysis using Conefor Sensinode. Finally, fragmentation is usually defined from a species point of view but a generic and quantifiable indicator is needed to measure fragmentation and its changes. Some preliminary results for different conceptual approaches will be shown for a sample dataset. Complemented by pre- and post-processing routines and a complete GIS environment the portable GUIDOS Toolbox may facilitate a holistic assessment in risk assessment studies, landscape planning, and conservation/restoration policies. Alternatively, individual analysis components may contribute to or enhance studies conducted with other software packages in landscape ecology.

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

An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave.

PubMed

Silva, Ikaro; Moody, George B

The WaveForm DataBase (WFDB) Toolbox for MATLAB/Octave enables integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox provides access over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by metadata such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

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.

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

Apte, A; Veeraraghavan, H; Oh, J

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

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

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.

The BRAT and GUT Couple: Broadview Radar Altimetry and GOCE User Toolboxes

NASA Astrophysics Data System (ADS)

Benveniste, J.; Restano, M.; Ambrózio, A.

2017-12-01

The Broadview Radar Altimetry Toolbox (BRAT) is a collection of tools designed to facilitate the processing of radar altimetry data from previous and current altimetry missions, including Sentinel-3A L1 and L2 products. A tutorial is included providing plenty of use cases. BRAT's next release (4.2.0) is planned for October 2017. Based on the community feedback, the front-end has been further improved and simplified whereas the capability to use BRAT in conjunction with MATLAB/IDL or C/C++/Python/Fortran, allowing users to obtain desired data bypassing the data-formatting hassle, remains unchanged. Several kinds of computations can be done within BRAT involving the combination of data fields, that can be saved for future uses, either by using embedded formulas including those from oceanographic altimetry, or by implementing ad-hoc Python modules created by users to meet their needs. BRAT can also be used to quickly visualise data, or to translate data into other formats, e.g. from NetCDF to raster images. The GOCE User Toolbox (GUT) is a compilation of tools for the use and the analysis of GOCE gravity field models. It facilitates using, viewing and post-processing GOCE L2 data and allows gravity field data, in conjunction and consistently with any other auxiliary data set, to be pre-processed by beginners in gravity field processing, for oceanographic and hydrologic as well as for solid earth applications at both regional and global scales. Hence, GUT facilitates the extensive use of data acquired during GRACE and GOCE missions. In the current 3.1 version, GUT has been outfitted with a graphical user interface allowing users to visually program data processing workflows. Further enhancements aiming at facilitating the use of gradients, the anisotropic diffusive filtering, and the computation of Bouguer and isostatic gravity anomalies have been introduced. Packaged with GUT is also GUT's Variance-Covariance Matrix tool (VCM). BRAT and GUT toolboxes can be freely downloaded, along with ancillary material, at https://earth.esa.int/brat and https://earth.esa.int/gut.

Threshold-based segmentation of fluorescent and chromogenic images of microglia, astrocytes and oligodendrocytes in FIJI.

PubMed

Healy, Sinead; McMahon, Jill; Owens, Peter; Dockery, Peter; FitzGerald, Una

2018-02-01

Image segmentation is often imperfect, particularly in complex image sets such z-stack micrographs of slice cultures and there is a need for sufficient details of parameters used in quantitative image analysis to allow independent repeatability and appraisal. For the first time, we have critically evaluated, quantified and validated the performance of different segmentation methodologies using z-stack images of ex vivo glial cells. The BioVoxxel toolbox plugin, available in FIJI, was used to measure the relative quality, accuracy, specificity and sensitivity of 16 global and 9 local threshold automatic thresholding algorithms. Automatic thresholding yields improved binary representation of glial cells compared with the conventional user-chosen single threshold approach for confocal z-stacks acquired from ex vivo slice cultures. The performance of threshold algorithms varies considerably in quality, specificity, accuracy and sensitivity with entropy-based thresholds scoring highest for fluorescent staining. We have used the BioVoxxel toolbox to correctly and consistently select the best automated threshold algorithm to segment z-projected images of ex vivo glial cells for downstream digital image analysis and to define segmentation quality. The automated OLIG2 cell count was validated using stereology. As image segmentation and feature extraction can quite critically affect the performance of successive steps in the image analysis workflow, it is becoming increasingly necessary to consider the quality of digital segmenting methodologies. Here, we have applied, validated and extended an existing performance-check methodology in the BioVoxxel toolbox to z-projected images of ex vivo glia cells. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Automatic tracking of labeled red blood cells in microchannels.

PubMed

Pinho, Diana; Lima, Rui; Pereira, Ana I; Gayubo, Fernando

2013-09-01

The current study proposes an automatic method for the segmentation and tracking of red blood cells flowing through a 100- μm glass capillary. The original images were obtained by means of a confocal system and then processed in MATLAB using the Image Processing Toolbox. The measurements obtained with the proposed automatic method were compared with the results determined by a manual tracking method. The comparison was performed by using both linear regressions and Bland-Altman analysis. The results have shown a good agreement between the two methods. Therefore, the proposed automatic method is a powerful way to provide rapid and accurate measurements for in vitro blood experiments in microchannels. Copyright © 2012 John Wiley & Sons, Ltd.

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

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.

Registration of in vivo MR to histology of rodent brains using blockface imaging

NASA Astrophysics Data System (ADS)

Uberti, Mariano; Liu, Yutong; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael

2009-02-01

Registration of MRI to histopathological sections can enhance bioimaging validation for use in pathobiologic, diagnostic, and therapeutic evaluations. However, commonly used registration methods fall short of this goal due to tissue shrinkage and tearing after brain extraction and preparation. In attempts to overcome these limitations we developed a software toolbox using 3D blockface imaging as the common space of reference. This toolbox includes a semi-automatic brain extraction technique using constraint level sets (CLS), 3D reconstruction methods for the blockface and MR volume, and a 2D warping technique using thin-plate splines with landmark optimization. Using this toolbox, the rodent brain volume is first extracted from the whole head MRI using CLS. The blockface volume is reconstructed followed by 3D brain MRI registration to the blockface volume to correct the global deformations due to brain extraction and fixation. Finally, registered MRI and histological slices are warped to corresponding blockface images to correct slice specific deformations. The CLS brain extraction technique was validated by comparing manual results showing 94% overlap. The image warping technique was validated by calculating target registration error (TRE). Results showed a registration accuracy of a TRE < 1 pixel. Lastly, the registration method and the software tools developed were used to validate cell migration in murine human immunodeficiency virus type one encephalitis.

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.

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.

Developing a Fluorescent Toolbox To Shed Light on the Mysteries of RNA.

PubMed

Alexander, Seth C; Devaraj, Neal K

2017-10-03

Technologies that detect and image RNA have illuminated the complex roles played by RNA, redefining the traditional and superficial role first outlined by the central dogma of biology. Because there is such a wide diversity of RNA structure arising from an assortment of functions within biology, a toolbox of approaches have emerged for investigation of this important class of biomolecules. These methods are necessary to detect and elucidate the localization and dynamics of specific RNAs and in doing so unlock our understanding of how RNA dysregulation leads to disease. Current methods for detecting and imaging RNA include in situ hybridization techniques, fluorescent aptamers, RNA binding proteins fused to fluorescent reporters, and covalent labeling strategies. Because of the inherent diversity of these methods, each approach comes with a set of strengths and limitations that leave room for future improvement. This perspective seeks to highlight the most recent advances and remaining challenges for the wide-ranging toolbox of technologies that illuminate RNA's contribution to cellular complexity.

A GUI visualization system for airborne lidar image data to reconstruct 3D city model

NASA Astrophysics Data System (ADS)

Kawata, Yoshiyuki; Koizumi, Kohei

2015-10-01

A visualization toolbox system with graphical user interfaces (GUIs) was developed for the analysis of LiDAR point cloud data, as a compound object oriented widget application in IDL (Interractive Data Language). The main features in our system include file input and output abilities, data conversion capability from ascii formatted LiDAR point cloud data to LiDAR image data whose pixel value corresponds the altitude measured by LiDAR, visualization of 2D/3D images in various processing steps and automatic reconstruction ability of 3D city model. The performance and advantages of our graphical user interface (GUI) visualization system for LiDAR data are demonstrated.

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.

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.

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

3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy

PubMed Central

Lerner, Thomas R.; Burden, Jemima J.; Nkwe, David O.; Pelchen-Matthews, Annegret; Domart, Marie-Charlotte; Durgan, Joanne; Weston, Anne; Jones, Martin L.; Peddie, Christopher J.; Carzaniga, Raffaella; Florey, Oliver; Marsh, Mark; Gutierrez, Maximiliano G.

2017-01-01

ABSTRACT The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research. PMID:27445312

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.

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.

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.

The Benefits of Comparing Grapefruits and Tangerines: A Toolbox for European Cross-Cultural Comparisons in Engineering Education--Using This Toolbox to Study Gendered Images of Engineering among Students

ERIC Educational Resources Information Center

Godfroy-Genin, Anne-Sophie; Pinault, Cloe

2006-01-01

The main objective of the WomEng European research project was to assess when, how and why women decide to or not to study engineering. This question was addressed through an international cross-comparison by an interdisciplinary research team in seven European countries. This article presents, in the first part, the methodological toolbox…

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.

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

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.

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.

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

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.

Programmable oligonucleotide probes design and applications for in situ and in vivo RNA imaging in cells

NASA Astrophysics Data System (ADS)

Cheglakov, Zoya

Unequal spreading of mRNA is a frequent experience observed in varied cell lines. The study of cellular processes dynamics and precise localization of mRNAs offers a vital toolbox to target specific proteins in precise cytoplasmic areas and provides a convenient instrument to uncover their mechanisms and functions. Latest methodological innovations have allowed imaging of a single mRNA molecule in situ and in vivo. Today, Fluorescent In Situ Hybridization (FISH) methods allow the studying of mRNA expression and offer a vital toolbox for accurate biological models. Studies enable analysis of the dynamics of an individual mRNA, have uncovered the multiplex RNA transport systems. With all current approaches, a single mRNA tracking in the mammalian cells is still challenging. This thesis describes mRNA detection methods based on programmable fluorophore-labeled DNA structures complimentary to native targets providing an accurate mRNA imaging in mammalian cells. First method represents beta-actin (ACTB) transcripts in situ detection in human cells, the technique strategy is based on programmable DNA probes, amplified by rolling circle amplification (RCA). The method reports precise localization of molecule of interest with an accuracy of a single-cell. Visualization and localization of specific endogenous mRNA molecules in real-time in vivo has the promising to innovate cellular biology studies, medical analysis and to provide a vital toolbox in drugs invention area. Second method described in this thesis represents miR-21 miRNA detection within a single live-cell resolution. The method using fluorophore-labeled short synthetic DNAs probes forming a stem-loop shape and generating Fluorescent Resonance Energy Transfer (FRET) as a result of target-probes hybridization. Catalytic nucleic acid (DNAzymes) probes are cooperative tool for precise detection of different mRNA targets. With assistance of a complementary fluorophore-quencher labeled substrate, the DNAzymes provide a beneficial strategy for simultaneous tracking readily accomplished by multicolor imaging with diverse fluorescent tags. The third method in this thesis will demonstrate the advantage of DNAzymes probes amplification, and offers potential strategy to monitor miRNAs in mammalian live cells.

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.

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.

Tinnitus Multimodal Imaging

DTIC Science & Technology

2016-12-01

images were segmented into gray and white matter images and spatially normalized to the MNI template (3 mm isotropic voxels) using the DARTEL toolbox in...AWARD NUMBER: W81XWH-13-1-0494 TITLE: Tinnitus Multimodal Imaging PRINCIPAL INVESTIGATOR: Steven Wan Cheung CONTRACTING ORGANIZATION... Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved for Public Release; Distribution Unlimited

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.

Reprocessing Close Range Terrestrial and Uav Photogrammetric Projects with the Dbat Toolbox for Independent Verification and Quality Control

NASA Astrophysics Data System (ADS)

Murtiyoso, A.; Grussenmeyer, P.; Börlin, N.

2017-11-01

Photogrammetry has recently seen a rapid increase in many applications, thanks to developments in computing power and algorithms. Furthermore with the democratisation of UAVs (Unmanned Aerial Vehicles), close range photogrammetry has seen more and more use due to the easier capability to acquire aerial close range images. In terms of photogrammetric processing, many commercial software solutions exist in the market that offer results from user-friendly environments. However, in most commercial solutions, a black-box approach to photogrammetric calculations is often used. This is understandable in light of the proprietary nature of the algorithms, but it may pose a problem if the results need to be validated in an independent manner. In this paper, the Damped Bundle Adjustment Toolbox (DBAT) developed for Matlab was used to reprocess some photogrammetric projects that were processed using the commercial software Agisoft Photoscan. Several scenarios were experimented on in order to see the performance of DBAT in reprocessing terrestrial and UAV close range photogrammetric projects in several configurations of self-calibration setting. Results show that DBAT managed to reprocess PS projects and generate metrics which can be useful for project verification.

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.

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.

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

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.

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.

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Cellular neural networks, the Navier-Stokes equation, and microarray image reconstruction.

PubMed

Zineddin, Bachar; Wang, Zidong; Liu, Xiaohui

2011-11-01

Although the last decade has witnessed a great deal of improvements achieved for the microarray technology, many major developments in all the main stages of this technology, including image processing, are still needed. Some hardware implementations of microarray image processing have been proposed in the literature and proved to be promising alternatives to the currently available software systems. However, the main drawback of those proposed approaches is the unsuitable addressing of the quantification of the gene spot in a realistic way without any assumption about the image surface. Our aim in this paper is to present a new image-reconstruction algorithm using the cellular neural network that solves the Navier-Stokes equation. This algorithm offers a robust method for estimating the background signal within the gene-spot region. The MATCNN toolbox for Matlab is used to test the proposed method. Quantitative comparisons are carried out, i.e., in terms of objective criteria, between our approach and some other available methods. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner within a remarkably efficient time.

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.

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.

GuidosToolbox: universal digital image object analysis

Treesearch

Peter Vogt; Kurt Riitters

2017-01-01

The increased availability of mapped environmental data calls for better tools to analyze the spatial characteristics and information contained in those maps. Publicly available, userfriendly and universal tools are needed to foster the interdisciplinary development and application of methodologies for the extraction of image object information properties contained in...

Image processing for improved eye-tracking accuracy

NASA Technical Reports Server (NTRS)

Mulligan, J. B.; Watson, A. B. (Principal Investigator)

1997-01-01

Video cameras provide a simple, noninvasive method for monitoring a subject's eye movements. An important concept is that of the resolution of the system, which is the smallest eye movement that can be reliably detected. While hardware systems are available that estimate direction of gaze in real-time from a video image of the pupil, such systems must limit image processing to attain real-time performance and are limited to a resolution of about 10 arc minutes. Two ways to improve resolution are discussed. The first is to improve the image processing algorithms that are used to derive an estimate. Off-line analysis of the data can improve resolution by at least one order of magnitude for images of the pupil. A second avenue by which to improve resolution is to increase the optical gain of the imaging setup (i.e., the amount of image motion produced by a given eye rotation). Ophthalmoscopic imaging of retinal blood vessels provides increased optical gain and improved immunity to small head movements but requires a highly sensitive camera. The large number of images involved in a typical experiment imposes great demands on the storage, handling, and processing of data. A major bottleneck had been the real-time digitization and storage of large amounts of video imagery, but recent developments in video compression hardware have made this problem tractable at a reasonable cost. Images of both the retina and the pupil can be analyzed successfully using a basic toolbox of image-processing routines (filtering, correlation, thresholding, etc.), which are, for the most part, well suited to implementation on vectorizing supercomputers.

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

PV_LIB Toolbox

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

2012-09-11

While an organized source of reference information on PV performance modeling is certainly valuable, there is nothing to match the availability of actual examples of modeling algorithms being used in practice. To meet this need, Sandia has developed a PV performance modeling toolbox (PV_LIB) for Matlab. It contains a set of well-documented, open source functions and example scripts showing the functions being used in practical examples. This toolbox is meant to help make the multi-step process of modeling a PV system more transparent and provide the means for model users to validate and understand the models they use and ormore » develop. It is fully integrated into Matlab's help and documentation utilities. The PV_LIB Toolbox provides more than 30 functions that are sorted into four categories« less

An artificial vision solution for reusing discarded parts resulted after a manufacturing process

NASA Astrophysics Data System (ADS)

Cohal, V.; Cohal, A.

2016-08-01

The profit of a factory can be improved by reusing the discarded components produced. This paper is based on the case of a manufacturing process where rectangular metallic sheets of different sizes are produced. Using an artificial vision system, the shapes and the sizes of the produced parts can be determined. Those sheets which do not respect the requirements imposed are labeled as discarded. Instead of throwing these parts, a decision algorithm can analyze if another metallic sheet with smaller dimensions can be obtained from these. Two methods of decision are presented in this paper, considering the restriction that the sides of the new sheet has to be parallel with the axis of the coordinate system. The coordinates of each new part obtained from a discarded sheet are computed in order to be delivered to a milling machine. Details about implementing these algorithms (image processing and decision respectively) in the MATLAB environment using Image Processing Toolbox are given.

Scaled Heavy-Ball Acceleration of the Richardson-Lucy Algorithm for 3D Microscopy Image Restoration.

PubMed

Wang, Hongbin; Miller, Paul C

2014-02-01

The Richardson-Lucy algorithm is one of the most important in image deconvolution. However, a drawback is its slow convergence. A significant acceleration was obtained using the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the image processing MATLAB toolbox. The BA method was developed heuristically with no proof of convergence. In this paper, we introduce the heavy-ball (H-B) method for Poisson data optimization and extend it to a scaled H-B method, which includes the BA method as a special case. The method has a proof of the convergence rate of O(K(-2)), where k is the number of iterations. We demonstrate the superior convergence performance, by a speedup factor of five, of the scaled H-B method on both synthetic and real 3D images.

Quantitative imaging of heterogeneous dynamics in drying and aging paints

PubMed Central

van der Kooij, Hanne M.; Fokkink, Remco; van der Gucht, Jasper; Sprakel, Joris

2016-01-01

Drying and aging paint dispersions display a wealth of complex phenomena that make their study fascinating yet challenging. To meet the growing demand for sustainable, high-quality paints, it is essential to unravel the microscopic mechanisms underlying these phenomena. Visualising the governing dynamics is, however, intrinsically difficult because the dynamics are typically heterogeneous and span a wide range of time scales. Moreover, the high turbidity of paints precludes conventional imaging techniques from reaching deep inside the paint. To address these challenges, we apply a scattering technique, Laser Speckle Imaging, as a versatile and quantitative tool to elucidate the internal dynamics, with microscopic resolution and spanning seven decades of time. We present a toolbox of data analysis and image processing methods that allows a tailored investigation of virtually any turbid dispersion, regardless of the geometry and substrate. Using these tools we watch a variety of paints dry and age with unprecedented detail. PMID:27682840

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.

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore » the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.« less

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…

Image-based Analysis to Study Plant Infection with Human Pathogens

PubMed Central

Schikora, Marek; Schikora, Adam

2014-01-01

Our growing awareness that contaminated plants, fresh fruits and vegetables are responsible for a significant proportion of food poisoning with pathogenic microorganisms indorses the demand to understand the interactions between plants and human pathogens. Today we understand that those pathogens do not merely survive on or within plants, they actively infect plant organisms by suppressing their immune system. Studies on the infection process and disease development used mainly physiological, genetic, and molecular approaches, and image-based analysis provides yet another method for this toolbox. Employed as an observational tool, it bears the potential for objective and high throughput approaches, and together with other methods it will be very likely a part of data fusion approaches in the near future. PMID:25505501

Digital-image processing and image analysis of glacier ice

USGS Publications Warehouse

Fitzpatrick, Joan J.

2013-01-01

This document provides a methodology for extracting grain statistics from 8-bit color and grayscale images of thin sections of glacier ice—a subset of physical properties measurements typically performed on ice cores. This type of analysis is most commonly used to characterize the evolution of ice-crystal size, shape, and intercrystalline spatial relations within a large body of ice sampled by deep ice-coring projects from which paleoclimate records will be developed. However, such information is equally useful for investigating the stress state and physical responses of ice to stresses within a glacier. The methods of analysis presented here go hand-in-hand with the analysis of ice fabrics (aggregate crystal orientations) and, when combined with fabric analysis, provide a powerful method for investigating the dynamic recrystallization and deformation behaviors of bodies of ice in motion. The procedures described in this document compose a step-by-step handbook for a specific image acquisition and data reduction system built in support of U.S. Geological Survey ice analysis projects, but the general methodology can be used with any combination of image processing and analysis software. The specific approaches in this document use the FoveaPro 4 plug-in toolset to Adobe Photoshop CS5 Extended but it can be carried out equally well, though somewhat less conveniently, with software such as the image processing toolbox in MATLAB, Image-Pro Plus, or ImageJ.

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

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.

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.

The emerging molecular biology toolbox for the study of long noncoding RNA biology.

PubMed

Fok, Ezio T; Scholefield, Janine; Fanucchi, Stephanie; Mhlanga, Musa M

2017-10-01

Long noncoding RNAs (lncRNAs) have been implicated in many biological processes. However, due to the unique nature of lncRNAs and the consequential difficulties associated with their characterization, there is a growing disparity between the rate at which lncRNAs are being discovered and the assignment of biological function to these transcripts. Here we present a molecular biology toolbox equipped to help dissect aspects of lncRNA biology and reveal functionality. We outline an approach that begins with a broad survey of genome-wide, high-throughput datasets to identify potential lncRNA candidates and then narrow the focus on specific methods that are well suited to interrogate the transcripts of interest more closely. This involves the use of imaging-based strategies to validate these candidates and observe the behaviors of these transcripts at single molecule resolution in individual cells. We also describe the use of gene editing tools and interactome capture techniques to interrogate functionality and infer mechanism, respectively. With the emergence of lncRNAs as important molecules in healthy and diseased cellular function, it remains crucial to deepen our understanding of their biology.

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.

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

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.

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

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.

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.

Blood pulsation measurement using cameras operating in visible light: limitations.

PubMed

Koprowski, Robert

2016-10-03

The paper presents an automatic method for analysis and processing of images from a camera operating in visible light. This analysis applies to images containing the human facial area (body) and enables to measure the blood pulse rate. Special attention was paid to the limitations of this measurement method taking into account the possibility of using consumer cameras in real conditions (different types of lighting, different camera resolution, camera movement). The proposed new method of image analysis and processing was associated with three stages: (1) image pre-processing-allowing for the image filtration and stabilization (object location tracking); (2) main image processing-allowing for segmentation of human skin areas, acquisition of brightness changes; (3) signal analysis-filtration, FFT (Fast Fourier Transformation) analysis, pulse calculation. The presented algorithm and method for measuring the pulse rate has the following advantages: (1) it allows for non-contact and non-invasive measurement; (2) it can be carried out using almost any camera, including webcams; (3) it enables to track the object on the stage, which allows for the measurement of the heart rate when the patient is moving; (4) for a minimum of 40,000 pixels, it provides a measurement error of less than ±2 beats per minute for p < 0.01 and sunlight, or a slightly larger error (±3 beats per minute) for artificial lighting; (5) analysis of a single image takes about 40 ms in Matlab Version 7.11.0.584 (R2010b) with Image Processing Toolbox Version 7.1 (R2010b).

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

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.

Stereotaxic 18F-FDG PET and MRI templates with three-dimensional digital atlas for statistical parametric mapping analysis of tree shrew brain.

PubMed

Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci

2018-01-01

Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. 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

Distributed Aerodynamic Sensing and Processing Toolbox

NASA Technical Reports Server (NTRS)

Brenner, Martin; Jutte, Christine; Mangalam, Arun

2011-01-01

A Distributed Aerodynamic Sensing and Processing (DASP) toolbox was designed and fabricated for flight test applications with an Aerostructures Test Wing (ATW) mounted under the fuselage of an F-15B on the Flight Test Fixture (FTF). DASP monitors and processes the aerodynamics with the structural dynamics using nonintrusive, surface-mounted, hot-film sensing. This aerodynamic measurement tool benefits programs devoted to static/dynamic load alleviation, body freedom flutter suppression, buffet control, improvement of aerodynamic efficiency through cruise control, supersonic wave drag reduction through shock control, etc. This DASP toolbox measures local and global unsteady aerodynamic load distribution with distributed sensing. It determines correlation between aerodynamic observables (aero forces) and structural dynamics, and allows control authority increase through aeroelastic shaping and active flow control. It offers improvements in flutter suppression and, in particular, body freedom flutter suppression, as well as aerodynamic performance of wings for increased range/endurance of manned/ unmanned flight vehicles. Other improvements include inlet performance with closed-loop active flow control, and development and validation of advanced analytical and computational tools for unsteady aerodynamics.

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.

The universal toolbox thermal imager

NASA Astrophysics Data System (ADS)

Hollock, Steve; Jones, Graham; Usowicz, Paul

2003-09-01

The Introduction of Microsoft Pocket PC 2000/2002 has seen a standardisation of the operating systems used by the majority of PDA manufacturers. This, coupled with the recent price reductions associated with these devices, has led to a rapid increase in the sales of such units; their use is now common in industrial, commercial and domestic applications throughout the world. This paper describes the results of a programme to develop a thermal imager that will interface directly to all of these units so as to take advantage of the existing and future installed base of such devices. The imager currently interfaces with virtually any Pocket PC which provides the necessary processing, display and storage capability; as an alternative, the output of the unit can be visualised and processed in real time using a PC or laptop computer. In future, the open architecture employed by this imager will allow it to support all mobile computing devices, including phones and PDAs. The imager has been designed for one-handed or two-handed operation so that it may be pointed at awkward angles or used in confined spaces; this flexibility of use coupled with the extensive feature range and exceedingly low-cost of the imager, is extending the marketplace for thermal imaging from military and professional, through industrial to the commercial and domestic marketplaces.

Constructing and Classifying Email Networks from Raw Forensic Images

DTIC Science & Technology

2016-09-01

data mining for sequence and pattern mining ; in medical imaging for image segmentation; and in computer vision for object recognition” [28]. 2.3.1...machine learning and data mining suite that is written in Python. It provides a platform for experiment selection, recommendation systems, and...predictivemod- eling. The Orange library is a hierarchically-organized toolbox of data mining components. Data filtering and probability assessment are at the

KNIME4NGS: a comprehensive toolbox for next generation sequencing analysis.

PubMed

Hastreiter, Maximilian; Jeske, Tim; Hoser, Jonathan; Kluge, Michael; Ahomaa, Kaarin; Friedl, Marie-Sophie; Kopetzky, Sebastian J; Quell, Jan-Dominik; Mewes, H Werner; Küffner, Robert

2017-05-15

Analysis of Next Generation Sequencing (NGS) data requires the processing of large datasets by chaining various tools with complex input and output formats. In order to automate data analysis, we propose to standardize NGS tasks into modular workflows. This simplifies reliable handling and processing of NGS data, and corresponding solutions become substantially more reproducible and easier to maintain. Here, we present a documented, linux-based, toolbox of 42 processing modules that are combined to construct workflows facilitating a variety of tasks such as DNAseq and RNAseq analysis. We also describe important technical extensions. The high throughput executor (HTE) helps to increase the reliability and to reduce manual interventions when processing complex datasets. We also provide a dedicated binary manager that assists users in obtaining the modules' executables and keeping them up to date. As basis for this actively developed toolbox we use the workflow management software KNIME. See http://ibisngs.github.io/knime4ngs for nodes and user manual (GPLv3 license). robert.kueffner@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

GUIDANCE DOCUMENT ON IMPLEMENTATION OF THE ...

EPA Pesticide Factsheets

The Agreement in Principle for the Stage 2 M-DBP Federal Advisory Committee contains a list of treatment processes and management practices for water systems to use in meeting additional Cryptosporidium treatment requirements under the LT2ESWTR. This list, termed the microbial toolbox, includes watershed control programs, alternative intake locations, pretreatment processes, additional filtration barriers, inactivation technologies, and enhanced plant performance. The intent of the microbial toolbox is to provide water systems with broad flexibility in selecting cost-effective LT2ESWTR compliance strategies. Moreover, the toolbox allows systems that currently provide additional pathogen barriers or that can demonstrate enhanced performance to receive additional Cryptosporidium treatment credit. Provide guidance to utilities with surface water supplies and to state drinking water programs on the use of different treatment technologies to reduce the level of Cryptosporidium in drinking water. Technologies included in the guidance manual may be used to achieve compliance with the requirements of the LT2ESWTR.

General rigid motion correction for computed tomography imaging based on locally linear embedding

NASA Astrophysics Data System (ADS)

Chen, Mianyi; He, Peng; Feng, Peng; Liu, Baodong; Yang, Qingsong; Wei, Biao; Wang, Ge

2018-02-01

The patient motion can damage the quality of computed tomography images, which are typically acquired in cone-beam geometry. The rigid patient motion is characterized by six geometric parameters and are more challenging to correct than in fan-beam geometry. We extend our previous rigid patient motion correction method based on the principle of locally linear embedding (LLE) from fan-beam to cone-beam geometry and accelerate the computational procedure with the graphics processing unit (GPU)-based all scale tomographic reconstruction Antwerp toolbox. The major merit of our method is that we need neither fiducial markers nor motion-tracking devices. The numerical and experimental studies show that the LLE-based patient motion correction is capable of calibrating the six parameters of the patient motion simultaneously, reducing patient motion artifacts significantly.

Geocoding uncertainty analysis for the automated processing of Sentinel-1 data using Sentinel-1 Toolbox software

NASA Astrophysics Data System (ADS)

Dostálová, Alena; Naeimi, Vahid; Wagner, Wolfgang; Elefante, Stefano; Cao, Senmao; Persson, Henrik

2016-10-01

One of the major advantages of the Sentinel-1 data is its capability to provide very high spatio-temporal coverage allowing the mapping of large areas as well as creation of dense time-series of the Sentinel-1 acquisitions. The SGRT software developed at TU Wien aims at automated processing of Sentinel-1 data for global and regional products. The first step of the processing consists of the Sentinel-1 data geocoding with the help of S1TBX software and their resampling to a common grid. These resampled images serve as an input for the product derivation. Thus, it is very important to select the most reliable processing settings and assess the geocoding uncertainty for both backscatter and projected local incidence angle images. Within this study, selection of Sentinel-1 acquisitions over 3 test areas in Europe were processed manually in the S1TBX software, testing multiple software versions, processing settings and digital elevation models (DEM) and the accuracy of the resulting geocoded images were assessed. Secondly, all available Sentinel-1 data over the areas were processed using selected settings and detailed quality check was performed. Overall, strong influence of the used DEM on the geocoding quality was confirmed with differences up to 80 meters in areas with higher terrain variations. In flat areas, the geocoding accuracy of backscatter images was overall good, with observed shifts between 0 and 30m. Larger systematic shifts were identified in case of projected local incidence angle images. These results encourage the automated processing of large volumes of Sentinel-1 data.

GeoPAT: A toolbox for pattern-based information retrieval from large geospatial databases

NASA Astrophysics Data System (ADS)

Jasiewicz, Jarosław; Netzel, Paweł; Stepinski, Tomasz

2015-07-01

Geospatial Pattern Analysis Toolbox (GeoPAT) is a collection of GRASS GIS modules for carrying out pattern-based geospatial analysis of images and other spatial datasets. The need for pattern-based analysis arises when images/rasters contain rich spatial information either because of their very high resolution or their very large spatial extent. Elementary units of pattern-based analysis are scenes - patches of surface consisting of a complex arrangement of individual pixels (patterns). GeoPAT modules implement popular GIS algorithms, such as query, overlay, and segmentation, to operate on the grid of scenes. To achieve these capabilities GeoPAT includes a library of scene signatures - compact numerical descriptors of patterns, and a library of distance functions - providing numerical means of assessing dissimilarity between scenes. Ancillary GeoPAT modules use these functions to construct a grid of scenes or to assign signatures to individual scenes having regular or irregular geometries. Thus GeoPAT combines knowledge retrieval from patterns with mapping tasks within a single integrated GIS environment. GeoPAT is designed to identify and analyze complex, highly generalized classes in spatial datasets. Examples include distinguishing between different styles of urban settlements using VHR images, delineating different landscape types in land cover maps, and mapping physiographic units from DEM. The concept of pattern-based spatial analysis is explained and the roles of all modules and functions are described. A case study example pertaining to delineation of landscape types in a subregion of NLCD is given. Performance evaluation is included to highlight GeoPAT's applicability to very large datasets. The GeoPAT toolbox is available for download from

Semi-automated based ground-truthing GUI for airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan

2005-06-01

Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.

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.

Development of a Dependency Theory Toolbox for Database Design.

DTIC Science & Technology

1987-12-01

published algorithms and theorems , and hand simulating these algorithms can be a tedious and error prone chore. Additionally, since the process of...to design and study relational databases exists in the form of published algorithms and theorems . However, hand simulating these algorithms can be a...published algorithms and theorems . Hand simulating these algorithms can be a tedious and error prone chore. Therefore, a toolbox of algorithms and

ERPLAB: an open-source toolbox for the analysis of event-related potentials

PubMed Central

Lopez-Calderon, Javier; Luck, Steven J.

2014-01-01

ERPLAB toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB’s EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB’s tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user’s guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations. PMID:24782741

Optics Program Simplifies Analysis and Design

NASA Technical Reports Server (NTRS)

2007-01-01

Engineers at Goddard Space Flight Center partnered with software experts at Mide Technology Corporation, of Medford, Massachusetts, through a Small Business Innovation Research (SBIR) contract to design the Disturbance-Optics-Controls-Structures (DOCS) Toolbox, a software suite for performing integrated modeling for multidisciplinary analysis and design. The DOCS Toolbox integrates various discipline models into a coupled process math model that can then predict system performance as a function of subsystem design parameters. The system can be optimized for performance; design parameters can be traded; parameter uncertainties can be propagated through the math model to develop error bounds on system predictions; and the model can be updated, based on component, subsystem, or system level data. The Toolbox also allows the definition of process parameters as explicit functions of the coupled model and includes a number of functions that analyze the coupled system model and provide for redesign. The product is being sold commercially by Nightsky Systems Inc., of Raleigh, North Carolina, a spinoff company that was formed by Mide specifically to market the DOCS Toolbox. Commercial applications include use by any contractors developing large space-based optical systems, including Lockheed Martin Corporation, The Boeing Company, and Northrup Grumman Corporation, as well as companies providing technical audit services, like General Dynamics Corporation

ERPLAB: an open-source toolbox for the analysis of event-related potentials.

PubMed

Lopez-Calderon, Javier; Luck, Steven J

2014-01-01

ERPLAB toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB's EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB's tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user's guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations.

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.

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.

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.

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.

A Toolbox for Imaging Stellar Surfaces

NASA Astrophysics Data System (ADS)

Young, John

2018-04-01

In this talk I will review the available algorithms for synthesis imaging at visible and infrared wavelengths, including both gray and polychromatic methods. I will explain state-of-the-art approaches to constraining the ill-posed image reconstruction problem, and selecting an appropriate regularisation function and strength of regularisation. The reconstruction biases that can follow from non-optimal choices will be discussed, including their potential impact on the physical interpretation of the results. This discussion will be illustrated with example stellar surface imaging results from real VLTI and COAST datasets.

Application of COMSOL to Acoustic Imaging

DTIC Science & Technology

2010-10-01

Marquardt (LM) (2 epochs), followed by Broyden, Fletcher, Goldfarb, and Shannon (BFGS) (2 epochs) followed by scaled conjugate gradient ( SCG )(100...Use Matlab’s excellent Neural Network Toolbox  Optimization techniques considered:  Scaled‏Con jugate‏ Gradient‏ (“ SCG ”)‏ - fast  One‏Step

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.

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

Rangeland Brush Estimation Toolbox (RaBET): An Approach for Evaluating Brush Management Conservation Efforts in Western Grazing Lands

NASA Astrophysics Data System (ADS)

Holifield Collins, C.; Kautz, M. A.; Skirvin, S. M.; Metz, L. J.

2016-12-01

There are over 180 million hectares of rangelands and grazed forests in the central and western United States. Due to the loss of perennial grasses and subsequent increased runoff and erosion that can degrade the system, woody cover species cannot be allowed to proliferate unchecked. The USDA-Natural Resources Conservation Service (NRCS) has allocated extensive resources to employ brush management (removal) as a conservation practice to control woody species encroachment. The Rangeland-Conservation Effects Assessment Project (CEAP) has been tasked with determining how effective the practice has been, however their land managers lack a cost-effective means to conduct these assessments at the necessary scale. An ArcGIS toolbox for generating large-scale, Landsat-based, spatial maps of woody cover on grazing lands in the western United States was developed through a collaboration with NRCS Rangeland-CEAP. The toolbox contains two main components of operation, image generation and temporal analysis, and utilizes simple interfaces requiring minimum user inputs. The image generation tool utilizes geographically specific algorithms developed from combining moderate-resolution (30-m) Landsat imagery and high-resolution (1-m) National Agricultural Imagery Program (NAIP) aerial photography to produce the woody cover scenes at the Major Land Resource (MLRA) scale. The temporal analysis tool can be used on these scenes to assess treatment effectiveness and monitor woody cover reemergence. RaBET provides rangeland managers an operational, inexpensive decision support tool to aid in the application of brush removal treatments and assessing their effectiveness.

Visualizing flow fields using acoustic Doppler current profilers and the Velocity Mapping Toolbox

USGS Publications Warehouse

Jackson, P. Ryan

2013-01-01

The purpose of this fact sheet is to provide examples of how the U.S. Geological Survey is using acoustic Doppler current profilers for much more than routine discharge measurements. These instruments are capable of mapping complex three-dimensional flow fields within rivers, lakes, and estuaries. Using the Velocity Mapping Toolbox to process the ADCP data allows detailed visualization of the data, providing valuable information for a range of studies and applications.

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.

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.

A tool for NDVI time series extraction from wide-swath remotely sensed images

NASA Astrophysics Data System (ADS)

Li, Zhishan; Shi, Runhe; Zhou, Cong

2015-09-01

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

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).

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

DTIC Science & Technology

2015-09-29

initial amendment emplacement rather than longterm monitoring of bioremediation . A number of specific developments of cross- borehole ERT imaging...These substrates are commonly used for enhanced bioremediation and are readily available. For time-lapse ERT imaging, it is important that there is a...to remediation professionals and regulators. This includes the following LinkedIn groups: Bioremediation ; Contaminant Transport in Fractured Bedrock

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.

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.

Mimicking human expert interpretation of remotely sensed raster imagery by using a novel segmentation analysis within ArcGIS

NASA Astrophysics Data System (ADS)

Le Bas, Tim; Scarth, Anthony; Bunting, Peter

2015-04-01

Traditional computer based methods for the interpretation of remotely sensed imagery use each pixel individually or the average of a small window of pixels to calculate a class or thematic value, which provides an interpretation. However when a human expert interprets imagery, the human eye is excellent at finding coherent and homogenous areas and edge features. It may therefore be advantageous for computer analysis to mimic human interpretation. A new toolbox for ArcGIS 10.x will be presented that segments the data layers into a set of polygons. Each polygon is defined by a K-means clustering and region growing algorithm, thus finding areas, their edges and any lineations in the imagery. Attached to each polygon are the characteristics of the imagery such as mean and standard deviation of the pixel values, within the polygon. The segmentation of imagery into a jigsaw of polygons also has the advantage that the human interpreter does not need to spend hours digitising the boundaries. The segmentation process has been taken from the RSGIS library of analysis and classification routines (Bunting et al., 2014). These routines are freeware and have been modified to be available in the ArcToolbox under the Windows (v7) operating system. Input to the segmentation process is a multi-layered raster image, for example; a Landsat image, or a set of raster datasets made up from derivatives of topography. The size and number of polygons are set by the user and are dependent on the imagery used. Examples will be presented of data from the marine environment utilising bathymetric depth, slope, rugosity and backscatter from a multibeam system. Meaningful classification of the polygons using their numerical characteristics is the next goal. Object based image analysis (OBIA) should help this workflow. Fully calibrated imagery systems will allow numerical classification to be translated into more readily understandable terms. Peter Bunting, Daniel Clewley, Richard M. Lucas and Sam Gillingham. 2014. The Remote Sensing and GIS Software Library (RSGISLib), Computers & Geosciences. Volume 62, Pages 216-226 http://dx.doi.org/10.1016/j.cageo.2013.08.007.

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.

Retinal Image Quality Assessment for Spaceflight-Induced Vision Impairment Study

NASA Technical Reports Server (NTRS)

Vu, Amanda Cadao; Raghunandan, Sneha; Vyas, Ruchi; Radhakrishnan, Krishnan; Taibbi, Giovanni; Vizzeri, Gianmarco; Grant, Maria; Chalam, Kakarla; Parsons-Wingerter, Patricia

2015-01-01

Long-term exposure to space microgravity poses significant risks for visual impairment. Evidence suggests such vision changes are linked to cephalad fluid shifts, prompting a need to directly quantify microgravity-induced retinal vascular changes. The quality of retinal images used for such vascular remodeling analysis, however, is dependent on imaging methodology. For our exploratory study, we hypothesized that retinal images captured using fluorescein imaging methodologies would be of higher quality in comparison to images captured without fluorescein. A semi-automated image quality assessment was developed using Vessel Generation Analysis (VESGEN) software and MATLAB® image analysis toolboxes. An analysis of ten images found that the fluorescein imaging modality provided a 36% increase in overall image quality (two-tailed p=0.089) in comparison to nonfluorescein imaging techniques.

Measurement and image processing evaluation of surface modifications of dental implants G4 pure titanium created by different techniques

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

Bulutsuz, A. G., E-mail: asligunaya@gmail.com; Demircioglu, P., E-mail: pinar.demircioglu@adu.edu.tr; Bogrekci, I., E-mail: ismail.bogrekci@adu.edu.tr

Foreign substances and organic tissue interaction placed into the jaw in order to eliminate tooth loss involves a highly complex process. Many biological reactions take place as well as the biomechanical forces that influence this formation. Osseointegration denotes to the direct structural and functional association between the living bone and the load-bearing artificial implant's surface. Taking into consideration of the requirements in the manufacturing processes of the implants, surface characterizations with high precise measurement techniques are investigated and thus long-term success of dental implant is emphasized on the importance of these processes in this study. In this research, the detailedmore » surface characterization was performed to identify the dependence of the manufacturing techniques on the surface properties by using the image processing methods and using the scanning electron microscope (SEM) for morphological properties in 3D and Taylor Hobson stylus profilometer for roughness properties in 2D. Three implant surfaces fabricated by different manufacturing techniques were inspected, and a machined surface was included into the study as a reference specimen. The results indicated that different surface treatments were strongly influenced surface morphology. Thus 2D and 3D precise inspection techniques were highlighted on the importance for surface characterization. Different image analyses techniques such as Dark-light technique were used to verify the surface measurement results. The computational phase was performed using image processing toolbox in Matlab with precise evaluation of the roughness for the implant surfaces. The relationship between the number of black and white pixels and surface roughness is presented. FFT image processing and analyses results explicitly imply that the technique is useful in the determination of surface roughness. The results showed that the number of black pixels in the image increases with increase in surface roughness.« less

The Biopsychology-Toolbox: a free, open-source Matlab-toolbox for the control of behavioral experiments.

PubMed

Rose, Jonas; Otto, Tobias; Dittrich, Lars

2008-10-30

The Biopsychology-Toolbox is a free, open-source Matlab-toolbox for the control of behavioral experiments. The major aim of the project was to provide a set of basic tools that allow programming novices to control basic hardware used for behavioral experimentation without limiting the power and flexibility of the underlying programming language. The modular design of the toolbox allows portation of parts as well as entire paradigms between different types of hardware. In addition to the toolbox, this project offers a platform for the exchange of functions, hardware solutions and complete behavioral paradigms.

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

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.

In-vivo segmentation and quantification of coronary lesions by optical coherence tomography images for a lesion type definition and stenosis grading.

PubMed

Celi, Simona; Berti, Sergio

2014-10-01

Optical coherence tomography (OCT) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels. This technique is particularly useful for studying coronary atherosclerosis. In this paper, we present a new framework that allows a segmentation and quantification of OCT images of coronary arteries to define the plaque type and stenosis grading. These analyses are usually carried out on-line on the OCT-workstation where measuring is mainly operator-dependent and mouse-based. The aim of this program is to simplify and improve the processing of OCT images for morphometric investigations and to present a fast procedure to obtain 3D geometrical models that can also be used for external purposes such as for finite element simulations. The main phases of our toolbox are the lumen segmentation and the identification of the main tissues in the artery wall. We validated the proposed method with identification and segmentation manually performed by expert OCT readers. The method was evaluated on ten datasets from clinical routine and the validation was performed on 210 images randomly extracted from the pullbacks. Our results show that automated segmentation of the vessel and of the tissue components are possible off-line with a precision that is comparable to manual segmentation for the tissue component and to the proprietary-OCT-console for the lumen segmentation. Several OCT sections have been processed to provide clinical outcome. Copyright © 2014 Elsevier B.V. All rights reserved.

GIXSGUI : a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films

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

Jiang, Zhang

GIXSGUIis a MATLAB toolbox that offers both a graphical user interface and script-based access to visualize and process grazing-incidence X-ray scattering data from nanostructures on surfaces and in thin films. It provides routine surface scattering data reduction methods such as geometric correction, one-dimensional intensity linecut, two-dimensional intensity reshapingetc. Three-dimensional indexing is also implemented to determine the space group and lattice parameters of buried organized nanoscopic structures in supported thin films.

EEGVIS: A MATLAB Toolbox for Browsing, Exploring, and Viewing Large Datasets.

PubMed

Robbins, Kay A

2012-01-01

Recent advances in data monitoring and sensor technology have accelerated the acquisition of very large data sets. Streaming data sets from instrumentation such as multi-channel EEG recording usually must undergo substantial pre-processing and artifact removal. Even when using automated procedures, most scientists engage in laborious manual examination and processing to assure high quality data and to indentify interesting or problematic data segments. Researchers also do not have a convenient method of method of visually assessing the effects of applying any stage in a processing pipeline. EEGVIS is a MATLAB toolbox that allows users to quickly explore multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. Customizable summary views reveal potentially interesting sections of data, which users can explore further by clicking to examine using detailed viewing components. The viewer and a companion browser are built on our MoBBED framework, which has a library of modular viewing components that can be mixed and matched to best reveal structure. Users can easily create new viewers for their specific data without any programming during the exploration process. These viewers automatically support pan, zoom, resizing of individual components, and cursor exploration. The toolbox can be used directly in MATLAB at any stage in a processing pipeline, as a plug-in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license at http://visual.cs.utsa.edu/eegvis.

Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.

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.

FZUImageReg: A toolbox for medical image registration and dose fusion in cervical cancer radiotherapy

PubMed Central

Bai, Penggang; Du, Min; Ni, Xiaolei; Ke, Dongzhong; Tong, Tong

2017-01-01

The combination external-beam radiotherapy and high-dose-rate brachytherapy is a standard form of treatment for patients with locally advanced uterine cervical cancer. Personalized radiotherapy in cervical cancer requires efficient and accurate dose planning and assessment across these types of treatment. To achieve radiation dose assessment, accurate mapping of the dose distribution from HDR-BT onto EBRT is extremely important. However, few systems can achieve robust dose fusion and determine the accumulated dose distribution during the entire course of treatment. We have therefore developed a toolbox (FZUImageReg), which is a user-friendly dose fusion system based on hybrid image registration for radiation dose assessment in cervical cancer radiotherapy. The main part of the software consists of a collection of medical image registration algorithms and a modular design with a user-friendly interface, which allows users to quickly configure, test, monitor, and compare different registration methods for a specific application. Owing to the large deformation, the direct application of conventional state-of-the-art image registration methods is not sufficient for the accurate alignment of EBRT and HDR-BT images. To solve this problem, a multi-phase non-rigid registration method using local landmark-based free-form deformation is proposed for locally large deformation between EBRT and HDR-BT images, followed by intensity-based free-form deformation. With the transformation, the software also provides a dose mapping function according to the deformation field. The total dose distribution during the entire course of treatment can then be presented. Experimental results clearly show that the proposed system can achieve accurate registration between EBRT and HDR-BT images and provide radiation dose warping and fusion results for dose assessment in cervical cancer radiotherapy in terms of high accuracy and efficiency. PMID:28388623

Advanced Thermoplastic Polymers and Additive Manufacturing Applied to ISS Columbus Toolbox: Lessons Learnt and Results

NASA Astrophysics Data System (ADS)

Ferrino, Marinella; Secondo, Ottaviano; Sabbagh, Amir; Della Sala, Emilio

2014-06-01

In the frame of the International Space Station (ISS) Exploitation Program a new toolbox has been realized by TAS-I to accommodate the tools currently in use on the ISS Columbus Module utilizing full-scale prototypes obtained with 3D rapid prototyping. The manufacturing of the flight hardware by means of advanced thermoplastic polymer UL TEM 9085 and additive manufacturing Fused Deposition Modelling (FDM) technology represent innovative elements. In this paper, the results achieved and the lessons learned are analyzed to promote future technology know-how. The acquired experience confirmed that the additive manufacturing process allows to save time/cost and to realize new shapes/features to introduce innovation in products and future design processes for space applications.

Accelerating Fibre Orientation Estimation from Diffusion Weighted Magnetic Resonance Imaging Using GPUs

PubMed Central

Hernández, Moisés; Guerrero, Ginés D.; Cecilia, José M.; García, José M.; Inuggi, Alberto; Jbabdi, Saad; Behrens, Timothy E. J.; Sotiropoulos, Stamatios N.

2013-01-01

With the performance of central processing units (CPUs) having effectively reached a limit, parallel processing offers an alternative for applications with high computational demands. Modern graphics processing units (GPUs) are massively parallel processors that can execute simultaneously thousands of light-weight processes. In this study, we propose and implement a parallel GPU-based design of a popular method that is used for the analysis of brain magnetic resonance imaging (MRI). More specifically, we are concerned with a model-based approach for extracting tissue structural information from diffusion-weighted (DW) MRI data. DW-MRI offers, through tractography approaches, the only way to study brain structural connectivity, non-invasively and in-vivo. We parallelise the Bayesian inference framework for the ball & stick model, as it is implemented in the tractography toolbox of the popular FSL software package (University of Oxford). For our implementation, we utilise the Compute Unified Device Architecture (CUDA) programming model. We show that the parameter estimation, performed through Markov Chain Monte Carlo (MCMC), is accelerated by at least two orders of magnitude, when comparing a single GPU with the respective sequential single-core CPU version. We also illustrate similar speed-up factors (up to 120x) when comparing a multi-GPU with a multi-CPU implementation. PMID:23658616

Operational SAR Data Processing in GIS Environments for Rapid Disaster Mapping

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2014-05-01

The use of SAR data has become increasingly popular in recent years and in a wide array of industries. Having access to SAR can be highly important and critical especially for public safety. Updating a GIS with contemporary information from SAR data allows to deliver a reliable set of geospatial information to advance civilian operations, e.g. search and rescue missions. SAR imaging offers the great advantage, over its optical counterparts, of not being affected by darkness, meteorological conditions such as clouds, fog, etc., or smoke and dust, frequently associated with disaster zones. In this paper we present the operational processing of SAR data within a GIS environment for rapid disaster mapping. For this technique we integrated the SARscape modules for ENVI with ArcGIS®, eliminating the need to switch between software packages. Thereby the premier algorithms for SAR image analysis can be directly accessed from ArcGIS desktop and server environments. They allow processing and analyzing SAR data in almost real time and with minimum user interaction. This is exemplified by the November 2010 flash flood in the Veneto region, Italy. The Bacchiglione River burst its banks on Nov. 2nd after two days of heavy rainfall throughout the northern Italian region. The community of Bovolenta, 22 km SSE of Padova, was covered by several meters of water. People were requested to stay in their homes; several roads, highways sections and railroads had to be closed. The extent of this flooding is documented by a series of Cosmo-SkyMed acquisitions with a GSD of 2.5 m (StripMap mode). Cosmo-SkyMed is a constellation of four Earth observation satellites, allowing a very frequent coverage, which enables monitoring using a very high temporal resolution. This data is processed in ArcGIS using a single-sensor, multi-mode, multi-temporal approach consisting of 3 steps: (1) The single images are filtered with a Gamma DE-MAP filter. (2) The filtered images are geocoded using a reference DEM without the need of ground control points. This step includes radiometric calibration. (3) A subsequent change detection analysis generates the final map showing the extent of the flash flood on Nov. 5th 2010. The underlying algorithms are provided by three different sources: Geocoding & radiometric calibration (2) is a standard functionality from the commercial SARscape Toolbox for ArcGIS. This toolbox is extended by the filter tool (1), which is called from the SARscape modules in ENVI. The change detection analysis (3) is based on ENVI processing routines and scripted with IDL. (2) and (3) are integrated with ArcGIS using a predefined Python interface. These 3 processing steps are combined using the ArcGIS ModelBuilder to create a new model for rapid disaster mapping in ArcGIS, based on SAR data. Moreover, this model can be dissolved from its desktop environment and published to users across the ArcGIS Server enterprise. Thus disaster zones, e.g. after severe flooding, can be automatically identified and mapped to support local task forces - using an operational workflow for SAR image analysis, which can be executed by the responsible operators without SAR expert knowledge.

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.

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.

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.

A toolbox for computing pebble shape and roundness indexes: experimental tests and recommendations for future applications.

NASA Astrophysics Data System (ADS)

Cassel, M.; Piegay, H.; Lave, J.

2016-12-01

Pebble rounding caused by attrition is, beside chemical dissolution, breakage, and grain size segregation, one of the key processes controlling bedload downstream fining in rivers. Downstream changes in pebble geometry is subject of consideration since Aristotle (Krynine, 1960) and its measurement represent a challenge since the end of 19th century, leading to a long standing debate (Blott and Pye, 2008). A toolbox developed by Roussillon et al. (2009) operate on automatic computation of several shape and roundness indexes from images of 2D projection plan of pebbles disposed on a one meter square red board. In order to promote the tool for future applications, we tested the effects of pebble position on board, of picture resolution and treatment on three shape and roundness indexes. We also compared the downstream patterns of these indexes on two pebble samples of the same lithology collected on the Progo River (Indonesia) based on field observations (i) and experimentation (ii). Shape and roundness were measured on (i) 8 sites distributed over a distance of 36 km along the river, and (ii) ten times on a set of particules collected on the Progo spring and transported in an annular flume over the same distance. This travel distance was monitored using passive low frequency RFID system. Results show that pebble position does not have a significant effect on shape and roundness indexes but these indexes are sensible to picture resolutions and treatments so that a clear protocol must be considered for avoiding any observer bias. Downstream changes in roundness indexes are very similar in field and experimental conditions, while abrasion environments are distinct. Discontinuities observed in downstream river pattern but not in experimental one underlined changes in Progo River pebble roundness are probably caused by sediment supplied from tributaries or bank erosion. These results highlight the toolbox potential for diagnosing river systems function.

Automatic Calibration of Stereo-Cameras Using Ordinary Chess-Board Patterns

NASA Astrophysics Data System (ADS)

Prokos, A.; Kalisperakis, I.; Petsa, E.; Karras, G.

2012-07-01

Automation of camera calibration is facilitated by recording coded 2D patterns. Our toolbox for automatic camera calibration using images of simple chess-board patterns is freely available on the Internet. But it is unsuitable for stereo-cameras whose calibration implies recovering camera geometry and their true-to-scale relative orientation. In contrast to all reported methods requiring additional specific coding to establish an object space coordinate system, a toolbox for automatic stereo-camera calibration relying on ordinary chess-board patterns is presented here. First, the camera calibration algorithm is applied to all image pairs of the pattern to extract nodes of known spacing, order them in rows and columns, and estimate two independent camera parameter sets. The actual node correspondences on stereo-pairs remain unknown. Image pairs of a textured 3D scene are exploited for finding the fundamental matrix of the stereo-camera by applying RANSAC to point matches established with the SIFT algorithm. A node is then selected near the centre of the left image; its match on the right image is assumed as the node closest to the corresponding epipolar line. This yields matches for all nodes (since these have already been ordered), which should also satisfy the 2D epipolar geometry. Measures for avoiding mismatching are taken. With automatically estimated initial orientation values, a bundle adjustment is performed constraining all pairs on a common (scaled) relative orientation. Ambiguities regarding the actual exterior orientations of the stereo-camera with respect to the pattern are irrelevant. Results from this automatic method show typical precisions not above 1/4 pixels for 640×480 web cameras.

ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox

NASA Technical Reports Server (NTRS)

Martin, Rodney A.; Santanu, Das; Janakiraman, Vijay Manikandan; Hosein, Stefan

2015-01-01

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we introduce a generic framework developed in MATLAB (sup registered mark) called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox). ACCEPT is an architectural framework designed to compare and contrast the performance of a variety of machine learning and early warning algorithms, and tests the capability of these algorithms to robustly predict the onset of adverse events in any time-series data generating systems or processes.

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

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.

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.

Data processing and analysis with the autoPROC toolbox.

PubMed

Vonrhein, Clemens; Flensburg, Claus; Keller, Peter; Sharff, Andrew; Smart, Oliver; Paciorek, Wlodek; Womack, Thomas; Bricogne, Gérard

2011-04-01

A typical diffraction experiment will generate many images and data sets from different crystals in a very short time. This creates a challenge for the high-throughput operation of modern synchrotron beamlines as well as for the subsequent data processing. Novice users in particular may feel overwhelmed by the tables, plots and numbers that the different data-processing programs and software packages present to them. Here, some of the more common problems that a user has to deal with when processing a set of images that will finally make up a processed data set are shown, concentrating on difficulties that may often show up during the first steps along the path of turning the experiment (i.e. data collection) into a model (i.e. interpreted electron density). Difficulties such as unexpected crystal forms, issues in crystal handling and suboptimal choices of data-collection strategies can often be dealt with, or at least diagnosed, by analysing specific data characteristics during processing. In the end, one wants to distinguish problems over which one has no immediate control once the experiment is finished from problems that can be remedied a posteriori. A new software package, autoPROC, is also presented that combines third-party processing programs with new tools and an automated workflow script that is intended to provide users with both guidance and insight into the offline processing of data affected by the difficulties mentioned above, with particular emphasis on the automated treatment of multi-sweep data sets collected on multi-axis goniostats.

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

The MONGOOSE Rational Arithmetic Toolbox.

PubMed

Le, Christopher; Chindelevitch, Leonid

2018-01-01

The modeling of metabolic networks has seen a rapid expansion following the complete sequencing of thousands of genomes. The constraint-based modeling framework has emerged as one of the most popular approaches to reconstructing and analyzing genome-scale metabolic models. Its main assumption is that of a quasi-steady-state, requiring that the production of each internal metabolite be balanced by its consumption. However, due to the multiscale nature of the models, the large number of reactions and metabolites, and the use of floating-point arithmetic for the stoichiometric coefficients, ensuring that this assumption holds can be challenging.The MONGOOSE toolbox addresses this problem by using rational arithmetic, thus ensuring that models are analyzed in a reproducible manner and consistently with modeling assumptions. In this chapter we present a protocol for the complete analysis of a metabolic network model using the MONGOOSE toolbox, via its newly developed GUI, and describe how it can be used as a model-checking platform both during and after the model construction process.

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.

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.

The Smithsonian-led Marine Global Earth Observatory (MarineGEO): Proposed Model for a Collaborative Network Linking Marine Biodiversity to Ecosystem Processes

NASA Astrophysics Data System (ADS)

Duffy, J. E.

2016-02-01

Biodiversity - the variety of functional types of organisms - is the engine of marine ecosystem processes, including productivity, nutrient cycling, and carbon sequestration. Biodiversity remains a black box in much of ocean science, despite wide recognition that effectively managing human interactions with marine ecosystems requires understanding both structure and functional consequences of biodiversity. Moreover, the inherent complexity of biological systems puts a premium on data-rich, comparative approaches, which are best met via collaborative networks. The Smithsonian Institution's MarineGEO program links a growing network of partners conducting parallel, comparative research to understand change in marine biodiversity and ecosystems, natural and anthropogenic drivers of that change, and the ecological processes mediating it. The focus is on nearshore, seabed-associated systems where biodiversity and human population are concentrated and interact most, yet which fall through the cracks of existing ocean observing programs. MarineGEO offers a standardized toolbox of research modules that efficiently capture key elements of biological diversity and its importance in ecological processes across a range of habitats. The toolbox integrates high-tech (DNA-based, imaging) and low-tech protocols (diver surveys, rapid assays of consumer activity) adaptable to differing institutional capacity and resources. The model for long-term sustainability involves leveraging in-kind support among partners, adoption of best practices wherever possible, engagement of students and citizen scientists, and benefits of training, networking, and global relevance as incentives for participation. Here I highlight several MarineGEO comparative research projects demonstrating the value of standardized, scalable assays and parallel experiments for measuring fish and invertebrate diversity, recruitment, benthic herbivory and generalist predation, decomposition, and carbon sequestration. Key remaining challenges include consensus on protocols; integration of historical data; data management and access; and informatics. These challenges are common to other fields and prospects for progress in the near future are good.

A quantitative framework for flower phenotyping in cultivated carnation (Dianthus caryophyllus L.).

PubMed

Chacón, Borja; Ballester, Roberto; Birlanga, Virginia; Rolland-Lagan, Anne-Gaëlle; Pérez-Pérez, José Manuel

2013-01-01

Most important breeding goals in ornamental crops are plant appearance and flower characteristics where selection is visually performed on direct offspring of crossings. We developed an image analysis toolbox for the acquisition of flower and petal images from cultivated carnation (Dianthus caryophyllus L.) that was validated by a detailed analysis of flower and petal size and shape in 78 commercial cultivars of D. caryophyllus, including 55 standard, 22 spray and 1 pot carnation cultivars. Correlation analyses allowed us to reduce the number of parameters accounting for the observed variation in flower and petal morphology. Convexity was used as a descriptor for the level of serration in flowers and petals. We used a landmark-based approach that allowed us to identify eight main principal components (PCs) accounting for most of the variance observed in petal shape. The effect and the strength of these PCs in standard and spray carnation cultivars are consistent with shared underlying mechanisms involved in the morphological diversification of petals in both subpopulations. Our results also indicate that neighbor-joining trees built with morphological data might infer certain phylogenetic relationships among carnation cultivars. Based on estimated broad-sense heritability values for some flower and petal features, different genetic determinants shall modulate the responses of flower and petal morphology to environmental cues in this species. We believe our image analysis toolbox could allow capturing flower variation in other species of high ornamental value.

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.

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

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

Chang, X; Yang, D

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was usedmore » to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.« less

Basic Radar Altimetry Toolbox: Tools to Use Radar Altimetry for Geodesy

NASA Astrophysics Data System (ADS)

Rosmorduc, V.; Benveniste, J. J.; Bronner, E.; Niejmeier, S.

2010-12-01

Radar altimetry is very much a technique expanding its applications and uses. If quite a lot of efforts have been made for oceanography users (including easy-to-use data), the use of those data for geodesy, especially combined witht ESA GOCE mission data is still somehow hard. ESA and CNES thus had the Basic Radar Altimetry Toolbox developed (as well as, on ESA side, the GOCE User Toolbox, both being linked). The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data. The software is able: - to read most distributed radar altimetry data, from ERS-1 & 2, Topex/Poseidon, Geosat Follow-on, Jason-1, Envisat, Jason- 2, CryoSat and the future Saral missions, - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways: - as a data reading tool, with APIs for C, Fortran, Matlab and IDL - as processing/extraction routines, through the on-line command mode - as an educational and a quick-look tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. It is an opportunity to teach remote sensing with practical training. It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. About 1200 people downloaded it (Summer 2010), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2. Others are ongoing, some are in discussion. Examples and Data use cases on geodesy will be presented. BRAT is developed under contract with ESA and CNES.

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...

ESP Toolbox: A Computational Framework for Precise, Scale-Independent Analysis of Bulk Elastic and Seismic Properties

NASA Astrophysics Data System (ADS)

Johnson, S. E.; Vel, S. S.; Cook, A. C.; Song, W. J.; Gerbi, C. C.; Okaya, D. A.

2014-12-01

Owing to the abundance of highly anisotropic minerals in the crust, the Voigt and Reuss bounds on the seismic velocities can be separated by more than 1 km/s. These bounds are determined by modal mineralogy and crystallographic preferred orientations (CPO) of the constituent minerals, but where the true velocities lie between these bounds is determined by other fabric parameters such as the shapes, shape-preferred orientations, and spatial arrangements of grains. Thus, the calculation of accurate bulk stiffness relies on explicitly treating the grain-scale heterogeneity, and the same principle applies at larger scales, for example calculating accurate bulk stiffness for a crustal volume with varying proportions and distributions of folds or shear zones. We have developed stand-alone GUI software - ESP Toolbox - for the calculation of 3D bulk elastic and seismic properties of heterogeneous and polycrystalline materials using image or EBSD data. The GUI includes a number of different homogenization techniques, including Voigt, Reuss, Hill, geometric mean, self-consistent and asymptotic expansion homogenization (AEH) methods. The AEH method, which uses a finite element mesh, is most accurate since it explicitly accounts for elastic interactions of constituent minerals/phases. The user need only specify the microstructure and material properties of the minerals/phases. We use the Toolbox to explore changes in bulk elasticity and related seismic anisotropy caused by specific variables, including: (a) the quartz alpha-beta phase change in rocks with varying proportions of quartz, (b) changes in modal mineralogy and CPO fabric that occur during progressive deformation and metamorphism, and (c) shear zones of varying thickness, abundance and geometry in continental crust. The Toolbox allows rapid sensitivity analysis around these and other variables, and the resulting bulk stiffness matrices can be used to populate volumes for synthetic wave propagation experiments that allow direct visualization of how variables of interest might affect propagation at a variety of scales. Sensitivity analyses also illustrate the value of the more precise AEH method. The ESP Toolbox can be downloaded here: http://umaine.edu/mecheng/faculty-and-staff/senthil-vel/software/

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.

Predictive Mining of Time Series Data

NASA Astrophysics Data System (ADS)

Java, A.; Perlman, E. S.

2002-05-01

All-sky monitors are a relatively new development in astronomy, and their data represent a largely untapped resource. Proper utilization of this resource could lead to important discoveries not only in the physics of variable objects, but in how one observes such objects. We discuss the development of a Java toolbox for astronomical time series data. Rather than using methods conventional in astronomy (e.g., power spectrum and cross-correlation analysis) we employ rule discovery techniques commonly used in analyzing stock-market data. By clustering patterns found within the data, rule discovery allows one to build predictive models, allowing one to forecast when a given event might occur or whether the occurrence of one event will trigger a second. We have tested the toolbox and accompanying display tool on datasets (representing several classes of objects) from the RXTE All Sky Monitor. We use these datasets to illustrate the methods and functionality of the toolbox. We have found predictive patterns in several ASM datasets. We also discuss problems faced in the development process, particularly the difficulties of dealing with discretized and irregularly sampled data. A possible application would be in scheduling target of opportunity observations where the astronomer wants to observe an object when a certain event or series of events occurs. By combining such a toolbox with an automatic, Java query tool which regularly gathers data on objects of interest, the astronomer or telescope operator could use the real-time datastream to efficiently predict the occurrence of (for example) a flare or other event. By combining the toolbox with dynamic time warping data-mining tools, one could predict events which may happen on variable time scales.

Renewable Energy Contract Development Best Practices

EPA Pesticide Factsheets

The Toolbox for Renewable Energy Project Development's Renewable Energy Contract Development Best Practices page provides an overview of the Request for Proposal (RFP) process as well as resources, such as contract templates.

Rural ITS toolbox

DOT National Transportation Integrated Search

2001-11-01

This document identifies successful rural Intelligent Transportation Systems (ITS) projects and statewide applications. These applications are referred to as "tools" and include those in the process of being tested prior to full deployment. The tools...

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/

Image fusion of Secondary Ion Mass Spectrometry and Energy-dispersive X-Ray Spectroscopy data for the characterization of uranium-molybdenum fuel foils

NASA Astrophysics Data System (ADS)

Willingham, David; Naes, Benjamin E.; Tarolli, Jay G.; Schemer-Kohrn, Alan; Rhodes, Mark; Dahl, Michael; Guzman, Anthony; Burkes, Douglas E.

2018-01-01

Uranium-molybdenum (U-Mo) monolithic fuels represent one option for converting civilian research and test reactors operating with high enriched uranium (HEU) to low enriched uranium (LEU), effectively reducing the threat of nuclear proliferation world-wide. However, processes associated with fabrication of U-Mo monolithic fuels result in regions of elemental heterogeneity, observed as bands traversing the cross-section of representative samples. Isotopic variations (e.g., 235U and 238U) could also be introduced because of associated processing steps, particularly since HEU feedstock is melted with natural or depleted uranium diluent to produce LEU. This study demonstrates the utility of correlative analysis of Energy-Dispersive X-ray Spectroscopy (EDS) and Secondary Ion Mass Spectrometry (SIMS) with their image data streams using image fusion, resulting in a comprehensive microanalytical characterization toolbox. Elemental and isotopic measurements were made on a sample from the Advanced Test Reactor (ATR) Full-sized plate In-center flux trap Position (AFIP)-7 experiment and compared to previous optical and electron microscopy results. The image fusion results are characteristic of SIMS isotopic maps, but with the spatial resolution of EDS images and, therefore, can be used to increase the effective spatial resolution of the SIMS imaging results to better understand homogeneity or heterogeneity that persists because of processing selections. Visual inspection using the image fusion methodology indicated slight variations in the 235U/238U ratio and quantitative analysis using the image intensities across several FoVs revealed an average 235U atom percent value of 17.9 ± 2.4%, which was indicative of a non-uniform U isotopic distribution in the area sampled. Further development of this capability is useful for understanding the connections between the properties of LEU fuel alternatives and the ability to predict performance under irradiation.

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

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.

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

IV. NIH Toolbox Cognition Battery (CB): measuring language (vocabulary comprehension and reading decoding).

PubMed

Gershon, Richard C; Slotkin, Jerry; Manly, Jennifer J; Blitz, David L; Beaumont, Jennifer L; Schnipke, Deborah; Wallner-Allen, Kathleen; Golinkoff, Roberta Michnick; Gleason, Jean Berko; Hirsh-Pasek, Kathy; Adams, Marilyn Jager; Weintraub, Sandra

2013-08-01

Mastery of language skills is an important predictor of daily functioning and health. Vocabulary comprehension and reading decoding are relatively quick and easy to measure and correlate highly with overall cognitive functioning, as well as with success in school and work. New measures of vocabulary comprehension and reading decoding (in both English and Spanish) were developed for the NIH Toolbox Cognition Battery (CB). In the Toolbox Picture Vocabulary Test (TPVT), participants hear a spoken word while viewing four pictures, and then must choose the picture that best represents the word. This approach tests receptive vocabulary knowledge without the need to read or write, removing the literacy load for children who are developing literacy and for adults who struggle with reading and writing. In the Toolbox Oral Reading Recognition Test (TORRT), participants see a letter or word onscreen and must pronounce or identify it. The examiner determines whether it was pronounced correctly by comparing the response to the pronunciation guide on a separate computer screen. In this chapter, we discuss the importance of language during childhood and the relation of language and brain function. We also review the development of the TPVT and TORRT, including information about the item calibration process and results from a validation study. Finally, the strengths and weaknesses of the measures are discussed. © 2013 The Society for Research in Child Development, Inc.

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

NASA Technical Reports Server (NTRS)

Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

2001-01-01

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Proceedings of the Annual Meeting of the Association for Education in Journalism and Mass Communication (79th, Anaheim, CA, August 10-13, 1996). Visual Communication and Science and Health Communication Division.

ERIC Educational Resources Information Center

Association for Education in Journalism and Mass Communication.

The Visual Communication and Science and Health Communication section of the proceedings contains the following 12 papers: "The Designers' Toolbox: Newsroom Experience and Ideal Characteristics of Newspaper Designers" (Wayne Wanta and Lauren Danner); "Patterned Image of the Homeless: Discourse Analysis of Television News…

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

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.

Fractal-dimension analysis detects cerebral changes in preterm infants with and without intrauterine growth restriction.

PubMed

Esteban, Francisco J; Padilla, Nelly; Sanz-Cortés, Magdalena; de Miras, Juan Ruiz; Bargalló, Núria; Villoslada, Pablo; Gratacós, Eduard

2010-12-01

In the search for a useful parameter to detect and quantify subtle brain abnormalities in infants with intrauterine growth restriction (IUGR), we hypothesised that the analysis of the structural complexity of grey matter (GM) and white matter (WM) using the fractal dimension (FD), a measurement of the topological complexity of an object, could be established as a useful tool for quantitative studies of infant brain morphology. We studied a sample of 18 singleton IUGR premature infants, (12.72 months corrected age (CA), range: 12 months-14 months), 15 preterm infants matched one-to-one for gestational age (GA) at delivery (12.6 months; range: 12 months-14 months), and 15 neonates born at term (12.4 months; range: 11 months-14 months). The neurodevelopmental outcome was assessed in all subjects at 18 months CA according to the Bayley Scale for Infant and Toddler Development - Third edition (BSID-III). For MRI acquisition and processing, the infants were scanned at 12 months CA, in a TIM TRIO 3T scanner, sleeping naturally. Images were pre-processed using the SPM5 toolbox, the GM and WM segmented under the VBM5 toolbox, and the box-counting method was applied for FD calculation of normal and skeletonized segmented images. The results showed a significant decrease of the FD of the brain GM and WM in the IUGR group when compared to the preterm or at-term controls. We also identified a significant linear tendency of both GM and WM FD from IUGR to preterm and term groups. Finally, multiple linear analyses between the FD of the GM or WM and the neurodevelopmental scales showed a significant regression of the language and motor scales with the FD of the GM. In conclusion, a decreased FD of the GM and WM in IUGR infants could be a sensitive indicator for the investigation of structural brain abnormalities in the IUGR population at 12 months of age, which can also be related to functional disorders. Copyright © 2010 Elsevier Inc. All rights reserved.

Semi-automated Digital Imaging and Processing System for Measuring Lake Ice Thickness

NASA Astrophysics Data System (ADS)

Singh, Preetpal

Canada is home to thousands of freshwater lakes and rivers. Apart from being sources of infinite natural beauty, rivers and lakes are an important source of water, food and transportation. The northern hemisphere of Canada experiences extreme cold temperatures in the winter resulting in a freeze up of regional lakes and rivers. Frozen lakes and rivers tend to offer unique opportunities in terms of wildlife harvesting and winter transportation. Ice roads built on frozen rivers and lakes are vital supply lines for industrial operations in the remote north. Monitoring the ice freeze-up and break-up dates annually can help predict regional climatic changes. Lake ice impacts a variety of physical, ecological and economic processes. The construction and maintenance of a winter road can cost millions of dollars annually. A good understanding of ice mechanics is required to build and deem an ice road safe. A crucial factor in calculating load bearing capacity of ice sheets is the thickness of ice. Construction costs are mainly attributed to producing and maintaining a specific thickness and density of ice that can support different loads. Climate change is leading to warmer temperatures causing the ice to thin faster. At a certain point, a winter road may not be thick enough to support travel and transportation. There is considerable interest in monitoring winter road conditions given the high construction and maintenance costs involved. Remote sensing technologies such as Synthetic Aperture Radar have been successfully utilized to study the extent of ice covers and record freeze-up and break-up dates of ice on lakes and rivers across the north. Ice road builders often used Ultrasound equipment to measure ice thickness. However, an automated monitoring system, based on machine vision and image processing technology, which can measure ice thickness on lakes has not been thought of. Machine vision and image processing techniques have successfully been used in manufacturing to detect equipment failure and identify defective products at the assembly line. The research work in this thesis combines machine vision and image processing technology to build a digital imaging and processing system for monitoring and measuring lake ice thickness in real time. An ultra-compact USB camera is programmed to acquire and transmit high resolution imagery for processing with MATLAB Image Processing toolbox. The image acquisition and transmission process is fully automated; image analysis is semi-automated and requires limited user input. Potential design changes to the prototype and ideas on fully automating the imaging and processing procedure are presented to conclude this research work.

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.

An automatic alignment tool to improve repeatability of left ventricular function and dyssynchrony parameters in serial gated myocardial perfusion SPECT studies

PubMed Central

Zhou, Yanli; Faber, Tracy L.; Patel, Zenic; Folks, Russell D.; Cheung, Alice A.; Garcia, Ernest V.; Soman, Prem; Li, Dianfu; Cao, Kejiang; Chen, Ji

2013-01-01

Objective Left ventricular (LV) function and dyssynchrony parameters measured from serial gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) using blinded processing had a poorer repeatability than when manual side-by-side processing was used. The objective of this study was to validate whether an automatic alignment tool can reduce the variability of LV function and dyssynchrony parameters in serial gated SPECT MPI. Methods Thirty patients who had undergone serial gated SPECT MPI were prospectively enrolled in this study. Thirty minutes after the first acquisition, each patient was repositioned and a gated SPECT MPI image was reacquired. The two data sets were first processed blinded from each other by the same technologist in different weeks. These processed data were then realigned by the automatic tool, and manual side-by-side processing was carried out. All processing methods used standard iterative reconstruction and Butterworth filtering. The Emory Cardiac Toolbox was used to measure the LV function and dyssynchrony parameters. Results The automatic tool failed in one patient, who had a large, severe scar in the inferobasal wall. In the remaining 29 patients, the repeatability of the LV function and dyssynchrony parameters after automatic alignment was significantly improved from blinded processing and was comparable to manual side-by-side processing. Conclusion The automatic alignment tool can be an alternative method to manual side-by-side processing to improve the repeatability of LV function and dyssynchrony measurements by serial gated SPECT MPI. PMID:23211996

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.

A broadband toolbox for scanning microwave microscopy transmission measurements

NASA Astrophysics Data System (ADS)

Lucibello, Andrea; Sardi, Giovanni Maria; Capoccia, Giovanni; Proietti, Emanuela; Marcelli, Romolo; Kasper, Manuel; Gramse, Georg; Kienberger, Ferry

2016-05-01

In this paper, we present in detail the design, both electromagnetic and mechanical, the fabrication, and the test of the first prototype of a Scanning Microwave Microscope (SMM) suitable for a two-port transmission measurement, recording, and processing the high frequency transmission scattering parameter S21 passing through the investigated sample. The S21 toolbox is composed by a microwave emitter, placed below the sample, which excites an electromagnetic wave passing through the sample under test, and is collected by the cantilever used as the detector, electrically matched for high frequency measurements. This prototype enhances the actual capability of the instrument for a sub-surface imaging at the nanoscale. Moreover, it allows the study of the electromagnetic properties of the material under test obtained through the measurement of the reflection (S11) and transmission (S21) parameters at the same time. The SMM operates between 1 GHz and 20 GHz, current limit for the microwave matching of the cantilever, and the high frequency signal is recorded by means of a two-port Vector Network Analyzer, using both contact and no-contact modes of operation, the latter, especially minded for a fully nondestructive and topography-free characterization. This tool is an upgrade of the already established setup for the reflection mode S11 measurement. Actually, the proposed setup is able to give richer information in terms of scattering parameters, including amplitude and phase measurements, by means of the two-port arrangement.

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

Current and future trends in marine image annotation software

NASA Astrophysics Data System (ADS)

Gomes-Pereira, Jose Nuno; Auger, Vincent; Beisiegel, Kolja; Benjamin, Robert; Bergmann, Melanie; Bowden, David; Buhl-Mortensen, Pal; De Leo, Fabio C.; Dionísio, Gisela; Durden, Jennifer M.; Edwards, Luke; Friedman, Ariell; Greinert, Jens; Jacobsen-Stout, Nancy; Lerner, Steve; Leslie, Murray; Nattkemper, Tim W.; Sameoto, Jessica A.; Schoening, Timm; Schouten, Ronald; Seager, James; Singh, Hanumant; Soubigou, Olivier; Tojeira, Inês; van den Beld, Inge; Dias, Frederico; Tempera, Fernando; Santos, Ricardo S.

2016-12-01

Given the need to describe, analyze and index large quantities of marine imagery data for exploration and monitoring activities, a range of specialized image annotation tools have been developed worldwide. Image annotation - the process of transposing objects or events represented in a video or still image to the semantic level, may involve human interactions and computer-assisted solutions. Marine image annotation software (MIAS) have enabled over 500 publications to date. We review the functioning, application trends and developments, by comparing general and advanced features of 23 different tools utilized in underwater image analysis. MIAS requiring human input are basically a graphical user interface, with a video player or image browser that recognizes a specific time code or image code, allowing to log events in a time-stamped (and/or geo-referenced) manner. MIAS differ from similar software by the capability of integrating data associated to video collection, the most simple being the position coordinates of the video recording platform. MIAS have three main characteristics: annotating events in real time, posteriorly to annotation and interact with a database. These range from simple annotation interfaces, to full onboard data management systems, with a variety of toolboxes. Advanced packages allow to input and display data from multiple sensors or multiple annotators via intranet or internet. Posterior human-mediated annotation often include tools for data display and image analysis, e.g. length, area, image segmentation, point count; and in a few cases the possibility of browsing and editing previous dive logs or to analyze the annotations. The interaction with a database allows the automatic integration of annotations from different surveys, repeated annotation and collaborative annotation of shared datasets, browsing and querying of data. Progress in the field of automated annotation is mostly in post processing, for stable platforms or still images. Integration into available MIAS is currently limited to semi-automated processes of pixel recognition through computer-vision modules that compile expert-based knowledge. Important topics aiding the choice of a specific software are outlined, the ideal software is discussed and future trends are presented.

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...

Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) User's Guide

NASA Technical Reports Server (NTRS)

Chapman, Jeffryes W.; Lavelle, Thomas M.; May, Ryan D.; Litt, Jonathan S.; Guo, Ten-Huei

2014-01-01

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) software package is an open source, MATLABSimulink toolbox (plug in) that can be used by industry professionals and academics for the development of thermodynamic and controls simulations.

CFS MATLAB toolbox: An experiment builder for continuous flash suppression (CFS) task.

PubMed

Nuutinen, Mikko; Mustonen, Terhi; Häkkinen, Jukka

2017-09-15

CFS toolbox is an open-source collection of MATLAB functions that utilizes PsychToolbox-3 (PTB-3). It is designed to allow a researcher to create and run continuous flash suppression experiments using a variety of experimental parameters (i.e., stimulus types and locations, noise characteristics, and experiment window settings). In a CFS experiment, one of the eyes at a time is presented with a dynamically changing noise pattern, while the other eye is concurrently presented with a static target stimulus, such as a Gabor patch. Due to the strong interocular suppression created by the dominant noise pattern mask, the target stimulus is rendered invisible for an extended duration. Very little knowledge of MATLAB is required for using the toolbox; experiments are generated by modifying csv files with the required parameters, and result data are output to text files for further analysis. The open-source code is available on the project page under a Creative Commons License ( http://www.mikkonuutinen.arkku.net/CFS_toolbox/ and https://bitbucket.org/mikkonuutinen/cfs_toolbox ).

Efficient estimation and large-scale evaluation of lateral chromatic aberration for digital image forensics

NASA Astrophysics Data System (ADS)

Gloe, Thomas; Borowka, Karsten; Winkler, Antje

2010-01-01

The analysis of lateral chromatic aberration forms another ingredient for a well equipped toolbox of an image forensic investigator. Previous work proposed its application to forgery detection1 and image source identification.2 This paper takes a closer look on the current state-of-the-art method to analyse lateral chromatic aberration and presents a new approach to estimate lateral chromatic aberration in a runtime-efficient way. Employing a set of 11 different camera models including 43 devices, the characteristic of lateral chromatic aberration is investigated in a large-scale. The reported results point to general difficulties that have to be considered in real world investigations.

Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Marchuk, V. I.; Fedosov, V. P.; Stradanchenko, S. G.; Ruslyakov, D. V.

2015-05-01

This work aimed to study computationally simple method of saliency map calculation. Research in this field received increasing interest for the use of complex techniques in portable devices. A saliency map allows increasing the speed of many subsequent algorithms and reducing the computational complexity. The proposed method of saliency map detection based on both image and frequency space analysis. Several examples of test image from the Kodak dataset with different detalisation considered in this paper demonstrate the effectiveness of the proposed approach. We present experiments which show that the proposed method providing better results than the framework Salience Toolbox in terms of accuracy and speed.

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.

An interactive toolbox for atlas-based segmentation and coding of volumetric images

NASA Astrophysics Data System (ADS)

Menegaz, G.; Luti, S.; Duay, V.; Thiran, J.-Ph.

2007-03-01

Medical imaging poses the great challenge of having compression algorithms that are lossless for diagnostic and legal reasons and yet provide high compression rates for reduced storage and transmission time. The images usually consist of a region of interest representing the part of the body under investigation surrounded by a "background", which is often noisy and not of diagnostic interest. In this paper, we propose a ROI-based 3D coding system integrating both the segmentation and the compression tools. The ROI is extracted by an atlas based 3D segmentation method combining active contours with information theoretic principles, and the resulting segmentation map is exploited for ROI based coding. The system is equipped with a GUI allowing the medical doctors to supervise the segmentation process and eventually reshape the detected contours at any point. The process is initiated by the user through the selection of either one pre-de.ned reference image or one image of the volume to be used as the 2D "atlas". The object contour is successively propagated from one frame to the next where it is used as the initial border estimation. In this way, the entire volume is segmented based on a unique 2D atlas. The resulting 3D segmentation map is exploited for adaptive coding of the different image regions. Two coding systems were considered: the JPEG3D standard and the 3D-SPITH. The evaluation of the performance with respect to both segmentation and coding proved the high potential of the proposed system in providing an integrated, low-cost and computationally effective solution for CAD and PAC systems.

Data processing and analysis with the autoPROC toolbox

PubMed Central

Vonrhein, Clemens; Flensburg, Claus; Keller, Peter; Sharff, Andrew; Smart, Oliver; Paciorek, Wlodek; Womack, Thomas; Bricogne, Gérard

2011-01-01

A typical diffraction experiment will generate many images and data sets from different crystals in a very short time. This creates a challenge for the high-throughput operation of modern synchrotron beamlines as well as for the subsequent data processing. Novice users in particular may feel overwhelmed by the tables, plots and numbers that the different data-processing programs and software packages present to them. Here, some of the more common problems that a user has to deal with when processing a set of images that will finally make up a processed data set are shown, concentrating on difficulties that may often show up during the first steps along the path of turning the experiment (i.e. data collection) into a model (i.e. interpreted electron density). Difficulties such as unexpected crystal forms, issues in crystal handling and suboptimal choices of data-collection strategies can often be dealt with, or at least diagnosed, by analysing specific data characteristics during processing. In the end, one wants to distinguish problems over which one has no immediate control once the experiment is finished from problems that can be remedied a posteriori. A new software package, autoPROC, is also presented that combines third-party processing programs with new tools and an automated workflow script that is intended to provide users with both guidance and insight into the offline processing of data affected by the difficulties mentioned above, with particular emphasis on the automated treatment of multi-sweep data sets collected on multi-axis goniostats. PMID:21460447

A Quantitative Framework for Flower Phenotyping in Cultivated Carnation (Dianthus caryophyllus L.)

PubMed Central

Chacón, Borja; Ballester, Roberto; Birlanga, Virginia; Rolland-Lagan, Anne-Gaëlle; Pérez-Pérez, José Manuel

2013-01-01

Most important breeding goals in ornamental crops are plant appearance and flower characteristics where selection is visually performed on direct offspring of crossings. We developed an image analysis toolbox for the acquisition of flower and petal images from cultivated carnation (Dianthus caryophyllus L.) that was validated by a detailed analysis of flower and petal size and shape in 78 commercial cultivars of D. caryophyllus, including 55 standard, 22 spray and 1 pot carnation cultivars. Correlation analyses allowed us to reduce the number of parameters accounting for the observed variation in flower and petal morphology. Convexity was used as a descriptor for the level of serration in flowers and petals. We used a landmark-based approach that allowed us to identify eight main principal components (PCs) accounting for most of the variance observed in petal shape. The effect and the strength of these PCs in standard and spray carnation cultivars are consistent with shared underlying mechanisms involved in the morphological diversification of petals in both subpopulations. Our results also indicate that neighbor-joining trees built with morphological data might infer certain phylogenetic relationships among carnation cultivars. Based on estimated broad-sense heritability values for some flower and petal features, different genetic determinants shall modulate the responses of flower and petal morphology to environmental cues in this species. We believe our image analysis toolbox could allow capturing flower variation in other species of high ornamental value. PMID:24349209

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

Tomopy is a Python toolbox to perform x-ray data processing, image reconstruction and data exchange tasks at synchrotron facilities. The dependencies of the software are currently as follows: -Python related python standard library (http://docs.python.org/2/library/) numpy (http://www.numpy.org/) scipy (http://scipy.org/) matplotlib (http://matplotlip.org/) sphinx (http://sphinx-doc.org) pil (http://www.pythonware.com/products/pil/) pyhdf (http://pysclint.sourceforge.net/pyhdf/) h5py (http://www.h5py.org) pywt (http://www.pybytes.com/pywavelets/) file.py (https://pyspec.svn.sourceforge.net/svnroot/pyspec/trunk/pyspec/ccd/files.py) -C/C++ related: gridec (anonymous?? C-code written back in 1997 that uses standard C library) fftw (http://www.fftw.org/) tomoRecon (multi-threaded C++ verion of gridrec. Author: Mark Rivers from APS. http://cars9.uchicago.edu/software/epics/tomoRecon.html) epics (http://www.aps.anl.gov/epics/)

Strong Functional Connectivity among Homotopic Brain Areas Is Vital for Motor Control in Unilateral Limb Movement.

PubMed

Wei, Pengxu; Zhang, Zuting; Lv, Zeping; Jing, Bin

2017-01-01

The mechanism underlying brain region organization for motor control in humans remains poorly understood. In this functional magnetic resonance imaging (fMRI) study, right-handed volunteers were tasked to maintain unilateral foot movements on the right and left sides as consistently as possible. We aimed to identify the similarities and differences between brain motor networks of the two conditions. We recruited 18 right-handed healthy volunteers aged 25 ± 2.3 years and used a whole-body 3T system for magnetic resonance (MR) scanning. Image analysis was performed using SPM8, Conn toolbox and Brain Connectivity Toolbox. We determined a craniocaudally distributed, mirror-symmetrical modular structure. The functional connectivity between homotopic brain areas was generally stronger than the intrahemispheric connections, and such strong connectivity led to the abovementioned modular structure. Our findings indicated that the interhemispheric functional interaction between homotopic brain areas is more intensive than the interaction along the conventional top-down and bottom-up pathways within the brain during unilateral limb movement. The detected strong interhemispheric horizontal functional interaction is an important aspect of motor control but often neglected or underestimated. The strong interhemispheric connectivity may explain the physiological phenomena and effects of promising therapeutic approaches. Further accurate and effective therapeutic methods may be developed on the basis of our findings.

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.

CERENA: ChEmical REaction Network Analyzer--A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics.

PubMed

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/.

CERENA: ChEmical REaction Network Analyzer—A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics

PubMed Central

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J.; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/. PMID:26807911

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…

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.

Wind wave analysis in depth limited water using OCEANLYZ, A MATLAB toolbox

NASA Astrophysics Data System (ADS)

Karimpour, Arash; Chen, Qin

2017-09-01

There are a number of well established methods in the literature describing how to assess and analyze measured wind wave data. However, obtaining reliable results from these methods requires adequate knowledge on their behavior, strengths and weaknesses. A proper implementation of these methods requires a series of procedures including a pretreatment of the raw measurements, and adjustment and refinement of the processed data to provide quality assurance of the outcomes, otherwise it can lead to untrustworthy results. This paper discusses potential issues in these procedures, explains what parameters are influential for the outcomes and suggests practical solutions to avoid and minimize the errors in the wave results. The procedure of converting the water pressure data into the water surface elevation data, treating the high frequency data with a low signal-to-noise ratio, partitioning swell energy from wind sea, and estimating the peak wave frequency from the weighted integral of the wave power spectrum are described. Conversion and recovery of the data acquired by a pressure transducer, particularly in depth-limited water like estuaries and lakes, are explained in detail. To provide researchers with tools for a reliable estimation of wind wave parameters, the Ocean Wave Analyzing toolbox, OCEANLYZ, is introduced. The toolbox contains a number of MATLAB functions for estimation of the wave properties in time and frequency domains. The toolbox has been developed and examined during a number of the field study projects in Louisiana's estuaries.

An integrated toolbox for processing and analysis of remote sensing data of inland and coastal waters - atmospheric correction

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

Haan, J.F. de; Kokke, J.M.M.; Hoogenboom, H.J.

1997-06-01

Deriving thematic maps of water quality parameters from a remote sensing image requires a number of processing steps, such as calibration, atmospheric correction, air-water interface correction, and application of water quality algorithms. A prototype version of an integrated software environment has recently been developed that enables the user to perform and control these processing steps. Major parts of this environment are: (i) access to the MODTRAN 3 radiative transfer code, (ii) a database of water quality algorithms, and (iii) a spectral library of Dutch coastal and inland waters, containing subsurface irradiance reflectance spectra and associated water quality parameters. The atmosphericmore » correction part of this environment is discussed here. It is shown that this part can be used to accurately retrieve spectral signatures of inland water for wavelengths between 450 and 750 nm, provided in situ measurements are used to determine atmospheric model parameters. Assessment of the usefulness of the completely integrated software system in an operational environment requires a revised version that is presently being developed.« less

SiGe BiCMOS manufacturing platform for mmWave applications

NASA Astrophysics Data System (ADS)

Kar-Roy, Arjun; Howard, David; Preisler, Edward; Racanelli, Marco; Chaudhry, Samir; Blaschke, Volker

2010-10-01

TowerJazz offers high volume manufacturable commercial SiGe BiCMOS technology platforms to address the mmWave market. In this paper, first, the SiGe BiCMOS process technology platforms such as SBC18 and SBC13 are described. These manufacturing platforms integrate 200 GHz fT/fMAX SiGe NPN with deep trench isolation into 0.18μm and 0.13μm node CMOS processes along with high density 5.6fF/μm2 stacked MIM capacitors, high value polysilicon resistors, high-Q metal resistors, lateral PNP transistors, and triple well isolation using deep n-well for mixed-signal integration, and, multiple varactors and compact high-Q inductors for RF needs. Second, design enablement tools that maximize performance and lowers costs and time to market such as scalable PSP and HICUM models, statistical and Xsigma models, reliability modeling tools, process control model tools, inductor toolbox and transmission line models are described. Finally, demonstrations in silicon for mmWave applications in the areas of optical networking, mobile broadband, phased array radar, collision avoidance radar and W-band imaging are listed.

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.

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

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

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...

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...

Experimental validation of 2D uncertainty quantification for digital image correlation.

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

Reu, Phillip L.

Because digital image correlation (DIC) has become such an important and standard tool in the toolbox of experimental mechanicists, a complete uncertainty quantification of the method is needed. It should be remembered that each DIC setup and series of images will have a unique uncertainty based on the calibration quality and the image and speckle quality of the analyzed images. Any pretest work done with a calibrated DIC stereo-rig to quantify the errors using known shapes and translations, while useful, do not necessarily reveal the uncertainty of a later test. This is particularly true with high-speed applications where actual testmore » images are often less than ideal. Work has previously been completed on the mathematical underpinnings of DIC uncertainty quantification and is already published, this paper will present corresponding experimental work used to check the validity of the uncertainty equations.« less

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation

PubMed Central

Wilke, Marko; Altaye, Mekibib; Holland, Scott K.

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating “unusual” populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php. PMID:28275348

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation.

PubMed

Wilke, Marko; Altaye, Mekibib; Holland, Scott K

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php.

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.

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

Effect of absorbable gelatin sponge in the middle ear: in vitro and in vivo animal model.

PubMed

Goncalves, Stefania; Chiossone-Kerdel, Juan Armando; Bianco, Andrea S; Ercolino, Jose M; Hernandez-Rojas, Jorge

2015-01-01

GelitaSpon gelatin sponge (GS) showed faster reabsorption than gelfoam (GF) in vitro, and GS-packed middle ears resulted in a faster hearing recovery and less inflammation than the ears packed with GF soaked in saline. Soaking GF sponges with boric acid (BA) appeared to offset the inflammatory response of saline-soaked GF, making this inflammatory response comparable to that of GS-packed ears. To describe the reabsorption and inflammatory effects of absorbable gelatin sponge in the middle ear. For in vitro evaluation, GF and GS were used as disks immersed in saline solution or 3% BA and placed in gel. Images were captured with a microscope and processed using image processing Toolbox. For in vivo tests, 16 female albino Sprague Dawley rats were divided into four groups: bulla opening; GF + 0.9% saline; GF + BA; and GS + 0.9% saline. An anterior approach to the right bulla was used for surgery. Preoperative and postoperative auditory brainstem response thresholds were measured. In vitro, there was marked degradation of GF by day 14, while GS showed complete degradation by the third day. In vivo, hearing recovery occurred by day 21. GF produced a more severe inflammatory response, which could be reduced by treating the GF with BA.

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.

BLINKER: Automated Extraction of Ocular Indices from EEG Enabling Large-Scale Analysis.

PubMed

Kleifges, Kelly; Bigdely-Shamlo, Nima; Kerick, Scott E; Robbins, Kay A

2017-01-01

Electroencephalography (EEG) offers a platform for studying the relationships between behavioral measures, such as blink rate and duration, with neural correlates of fatigue and attention, such as theta and alpha band power. Further, the existence of EEG studies covering a variety of subjects and tasks provides opportunities for the community to better characterize variability of these measures across tasks and subjects. We have implemented an automated pipeline (BLINKER) for extracting ocular indices such as blink rate, blink duration, and blink velocity-amplitude ratios from EEG channels, EOG channels, and/or independent components (ICs). To illustrate the use of our approach, we have applied the pipeline to a large corpus of EEG data (comprising more than 2000 datasets acquired at eight different laboratories) in order to characterize variability of certain ocular indicators across subjects. We also investigate dependence of ocular indices on task in a shooter study. We have implemented our algorithms in a freely available MATLAB toolbox called BLINKER. The toolbox, which is easy to use and can be applied to collections of data without user intervention, can automatically discover which channels or ICs capture blinks. The tools extract blinks, calculate common ocular indices, generate a report for each dataset, dump labeled images of the individual blinks, and provide summary statistics across collections. Users can run BLINKER as a script or as a plugin for EEGLAB. The toolbox is available at https://github.com/VisLab/EEG-Blinks. User documentation and examples appear at http://vislab.github.io/EEG-Blinks/.

SemVisM: semantic visualizer for medical image

NASA Astrophysics Data System (ADS)

Landaeta, Luis; La Cruz, Alexandra; Baranya, Alexander; Vidal, María.-Esther

2015-01-01

SemVisM is a toolbox that combines medical informatics and computer graphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a novel strategy for visualizing medical data annotated semantically, combining rendering techniques, and segmentation algorithms. SemVisM comprises two main components: i) AMORE (A Modest vOlume REgister) to handle input data (RAW, DAT or DICOM) and to initially annotate the images using terms defined on medical ontologies (e.g., MesH, FMA or RadLex), and ii) VOLPROB (VOlume PRObability Builder) for generating the annotated volumetric data containing the classified voxels that belong to a particular tissue. SemVisM is built on top of the semantic visualizer ANISE.1

Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues.

PubMed

Del Valle, José C; Gallardo-López, Antonio; Buide, Mª Luisa; Whittall, Justen B; Narbona, Eduardo

2018-03-01

Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio, anthocyanin content-chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.

CMGTooL user's manual

USGS Publications Warehouse

Xu, Jingping; Lightsom, Fran; Noble, Marlene A.; Denham, Charles

2002-01-01

During the past several years, the sediment transport group in the Coastal and Marine Geology Program (CMGP) of the U. S. Geological Survey has made major revisions to its methodology of processing, analyzing, and maintaining the variety of oceanographic time-series data. First, CMGP completed the transition of the its oceanographic time-series database to a self-documenting NetCDF (Rew et al., 1997) data format. Second, CMGP’s oceanographic data variety and complexity have been greatly expanded from traditional 2-dimensional, single-point time-series measurements (e.g., Electro-magnetic current meters, transmissometers) to more advanced 3-dimensional and profiling time-series measurements due to many new acquisitions of modern instruments such as Acoustic Doppler Current Profiler (RDI, 1996), Acoustic Doppler Velocitimeter, Pulse-Coherence Acoustic Doppler Profiler (SonTek, 2001), Acoustic Bacscatter Sensor (Aquatec, 1001001001001001001). In order to accommodate the NetCDF format of data from the new instruments, a software package of processing, analyzing, and visualizing time-series oceanographic data was developed. It is named CMGTooL. The CMGTooL package contains two basic components: a user-friendly GUI for NetCDF file analysis, processing and manipulation; and a data analyzing program library. Most of the routines in the library are stand-alone programs suitable for batch processing. CMGTooL is written in MATLAB computing language (The Mathworks, 1997), therefore users must have MATLAB installed on their computer in order to use this software package. In addition, MATLAB’s Signal Processing Toolbox is also required by some CMGTooL’s routines. Like most MATLAB programs, all CMGTooL codes are compatible with different computing platforms including PC, MAC, and UNIX machines (Note: CMGTooL has been tested on different platforms that run MATLAB 5.2 (Release 10) or lower versions. Some of the commands related to MAC may not be compatible with later releases of MATLAB). The GUI and some of the library routines call low-level NetCDF file I/O, variable and attribute functions. These NetCDF exclusive functions are supported by a MATLAB toolbox named NetCDF, created by Dr. Charles Denham . This toolbox has to be installed in order to use the CMGTooL GUI. The CMGTooL GUI calls several routines that were initially developed by others. The authors would like to acknowledge the following scientists for their ideas and codes: Dr. Rich Signell (USGS), Dr. Chris Sherwood (USGS), and Dr. Bob Beardsley (WHOI). Many special terms that carry special meanings in either MATLAB or the NetCDF Toolbox are used in this manual. Users are encouraged to read the documents of MATLAB and NetCDF for references.

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.

MagPy: A Python toolbox for controlling Magstim transcranial magnetic stimulators.

PubMed

McNair, Nicolas A

2017-01-30

To date, transcranial magnetic stimulation (TMS) studies manipulating stimulation parameters have largely used blocked paradigms. However, altering these parameters on a trial-by-trial basis in Magstim stimulators is complicated by the need to send regular (1Hz) commands to the stimulator. Additionally, effecting such control interferes with the ability to send TMS pulses or simultaneously present stimuli with high-temporal precision. This manuscript presents the MagPy toolbox, a Python software package that provides full control over Magstim stimulators via the serial port. It is able to maintain this control with no impact on concurrent processing, such as stimulus delivery. In addition, a specially-designed "QuickFire" serial cable is specified that allows MagPy to trigger TMS pulses with very low-latency. In a series of experimental simulations, MagPy was able to maintain uninterrupted remote control over the connected Magstim stimulator across all testing sessions. In addition, having MagPy enabled had no effect on stimulus timing - all stimuli were presented for precisely the duration specified. Finally, using the QuickFire cable, MagPy was able to elicit TMS pulses with sub-millisecond latencies. The MagPy toolbox allows for experiments that require manipulating stimulation parameters from trial to trial. Furthermore, it can achieve this in contexts that require tight control over timing, such as those seeking to combine TMS with fMRI or EEG. Together, the MagPy toolbox and QuickFire serial cable provide an effective means for controlling Magstim stimulators during experiments while ensuring high-precision timing. Copyright © 2016 Elsevier B.V. All rights reserved.

Language Measures of the NIH Toolbox Cognition Battery

PubMed Central

Gershon, Richard C.; Cook, Karon F.; Mungas, Dan; Manly, Jennifer J.; Slotkin, Jerry; Beaumont, Jennifer L.; Weintraub, Sandra

2015-01-01

Language facilitates communication and efficient encoding of thought and experience. Because of its essential role in early childhood development, in educational achievement and in subsequent life adaptation, language was included as one of the subdomains in the NIH Toolbox for the Assessment of Neurological and Behavioral Function Cognition Battery (NIHTB-CB). There are many different components of language functioning, including syntactic processing (i.e., morphology and grammar) and lexical semantics. For purposes of the NIHTB-CB, two tests of language—a picture vocabulary test and a reading recognition test—were selected by consensus based on literature reviews, iterative expert input, and a desire to assess in English and Spanish. NIHTB-CB’s picture vocabulary and reading recognition tests are administered using computer adaptive testing and scored using item response theory. Data are presented from the validation of the English versions in a sample of adults ages 20–85 years (Spanish results will be presented in a future publication). Both tests demonstrated high test–retest reliability and good construct validity compared to corresponding gold-standard measures. Scores on the NIH Toolbox measures were consistent with age-related expectations, namely, growth in language during early development, with relative stabilization into late adulthood. PMID:24960128

[Study on the 3D mathematical mode of the muscle groups applied to human mandible by a linear programming method].

PubMed

Wang, Dongmei; Yu, Liniu; Zhou, Xianlian; Wang, Chengtao

2004-02-01

Four types of 3D mathematical mode of the muscle groups applied to the human mandible have been developed. One is based on electromyography (EMG) and the others are based on linear programming with different objective function. Each model contains 26 muscle forces and two joint forces, allowing simulation of static bite forces and concomitant joint reaction forces for various bite point locations and mandibular positions. In this paper, the method of image processing to measure the position and direction of muscle forces according to 3D CAD model was built with CT data. Matlab optimization toolbox is applied to solve the three modes based on linear programming. Results show that the model with an objective function requiring a minimum sum of the tensions in the muscles is reasonable and agrees very well with the normal physiology activity.

SIRTF Tools for DIRT

NASA Astrophysics Data System (ADS)

Pound, M. W.; Wolfire, M. G.; Amarnath, N. S.

2003-12-01

The Dust InfraRed ToolBox (DIRT - a part of the Web Infrared ToolShed, or WITS, located at http://dustem.astro.umd.edu) is a Java applet for modeling astrophysical processes in circumstellar shells around young and evolved stars. DIRT has been used by the astrophysics community for about 5 years. Users can automatically and efficiently search grids of pre-calculated models to fit their data. A large set of physical parameters and dust types are included in the model database, which contains over 500,000 models. We are adding new functionality to DIRT to support new missions like SIRTF and SOFIA. A new Instrument module allows for plotting of the model points convolved with the spatial and spectral responses of the selected instrument. This lets users better fit data from specific instruments. Currently, we have implemented modules for the Infrared Array Camera (IRAC) and Multiband Imaging Photometer (MIPS) on SIRTF.

Experimental validation of 2D uncertainty quantification for DIC.

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

Reu, Phillip L.

Because digital image correlation (DIC) has become such an important and standard tool in the toolbox of experimental mechanicists, a complete uncertainty quantification of the method is needed. It should be remembered that each DIC setup and series of images will have a unique uncertainty based on the calibration quality and the image and speckle quality of the analyzed images. Any pretest work done with a calibrated DIC stereo-rig to quantify the errors using known shapes and translations, while useful, do not necessarily reveal the uncertainty of a later test. This is particularly true with high-speed applications where actual testmore » images are often less than ideal. Work has previously been completed on the mathematical underpinnings of DIC uncertainty quantification and is already published, this paper will present corresponding experimental work used to check the validity of the uncertainty equations.« less

Neurochemistry of Drug Action: Insights from Proton Magnetic Resonance Spectroscopic Imaging And Their Relevance to Addiction

PubMed Central

Licata, Stephanie C.; Renshaw, Perry F.

2011-01-01

Proton magnetic resonance spectroscopy (1H MRS) is a non-invasive imaging technique that permits measurement of particular compounds or metabolites within the tissue of interest. In the brain, 1H MRS provides a snapshot of the neurochemical environment within a defined volume of interest. A search of the literature demonstrates the widespread utility of this technique for characterizing tumors, tracking the progress of neurodegenerative disease, and for understanding the neurobiological basis of psychiatric disorders. As of relatively recently, 1H MRS has found its way into substance abuse research, and it is beginning to become recognized as a valuable complement in the brain imaging toolbox that also contains positron emission tomography (PET), single photon emission computed tomography (SPECT), and functional magnetic resonance imaging (fMRI). Drug abuse studies employing 1H MRS have identified a number biochemical changes in the brain. The most consistent alterations across drug class were reductions in N-acetylaspartate and elevations in myo-inositol, while changes in choline, creatine, and amino acid transmitters also were abundant. Together, the studies discussed herein provide evidence that drugs of abuse may have a profound impact on neuronal health, energy metabolism and maintenance, inflammatory processes, cell membrane turnover, and neurotransmission, and these biochemical changes may underlie the neuropathology within brain tissue that subsequently gives rise to the cognitive and behavioral impairments associated with drug addiction. PMID:20201852

Neurochemistry of drug action: insights from proton magnetic resonance spectroscopic imaging and their relevance to addiction.

PubMed

Licata, Stephanie C; Renshaw, Perry F

2010-02-01

Proton magnetic resonance spectroscopy ((1)H MRS) is a noninvasive imaging technique that permits measurement of particular compounds or metabolites within the tissue of interest. In the brain, (1)H MRS provides a snapshot of the neurochemical environment within a defined volume of interest. A search of the literature demonstrates the widespread utility of this technique for characterizing tumors, tracking the progress of neurodegenerative disease, and for understanding the neurobiological basis of psychiatric disorders. As of relatively recently, (1)H MRS has found its way into substance abuse research, and it is beginning to become recognized as a valuable complement in the brain imaging toolbox that also contains positron emission tomography, single-photon-emission computed tomography, and functional magnetic resonance imaging. Drug abuse studies using (1)H MRS have identified several biochemical changes in the brain. The most consistent alterations across drug class were reductions in N-acetylaspartate and elevations in myo-inositol, whereas changes in choline, creatine, and amino acid transmitters also were abundant. Together, the studies discussed herein provide evidence that drugs of abuse may have a profound effect on neuronal health, energy metabolism and maintenance, inflammatory processes, cell membrane turnover, and neurotransmission, and these biochemical changes may underlie the neuropathology within brain tissue that subsequently gives rise to the cognitive and behavioral impairments associated with drug addiction.

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

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

Jiang, S; Dolly, S; Cai, B

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deepmore » modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.« less

Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

NASA Astrophysics Data System (ADS)

Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

2001-07-01

Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

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.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

Principles and Algorithms for Natural and Engineered Systems

DTIC Science & Technology

2014-12-16

Toolbox for MATLAB into C/C++. The target for the calibration is a 2D black and white checkerboard pattern. In a typical set of calibration images...errors the dynamic clusters typically contain entangled trajectories i.e. links form between two different dynamic clusters (see Figures 8 and 9). To...all dynamic clusters is L, and the average number of trajectories a given dynamic cluster are entangled with for its entire length is known as the

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.

Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.

PubMed

Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel

2017-01-01

The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images. Copyright © 2016 Elsevier B.V. All rights reserved.

The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis

NASA Astrophysics Data System (ADS)

Veatch, W.; Friedman, D.; Baker, B.; Mueller, C.

2017-12-01

The vast majority of data analyzed by climate researchers are repeated observations of physical process or time series data. This data lends itself of a common set of statistical techniques and models designed to determine trends and variability (e.g., seasonality) of these repeated observations. Often, these same techniques and models can be applied to a wide variety of different time series data. The Timeseries Toolbox is a web application designed to standardize and streamline these common approaches to time series analysis and modeling with particular attention to hydrologic time series used in climate preparedness and resilience planning and design by the U. S. Army Corps of Engineers. The application performs much of the pre-processing of time series data necessary for more complex techniques (e.g. interpolation, aggregation). With this tool, users can upload any dataset that conforms to a standard template and immediately begin applying these techniques to analyze their time series data.

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.

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).

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.

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.

Operational monitoring of turbidity in rivers: how satellites can contribute

NASA Astrophysics Data System (ADS)

Hucke, Dorothee; Hillebrand, Gudrun; Winterscheid, Axel; Kranz, Susanne; Baschek, Björn

2016-10-01

The applications of remote sensing in hydrology are diverse and offer significant benefits for water monitoring. Up to now, operational river monitoring and sediment management in Germany mainly rely on in-situ measurements and on results obtained from numerical modelling. Remote sensing by satellites has a great potential to supplement existing data with two-dimensional information on near-surface turbidity distributions at greater spatial scales than in-situ measurements can offer. Within the project WasMon-CT (WaterMonitoring-Chlorophyll/Turbidity), the Federal Institute of Hydrology (BfG) aims at the implementation of an operational monitoring of turbidity distributions based on satellite images (esp. Sentinel-2, Landsat7 and 8). Initially, selected federal inland and estuarine waterways will be addressed: Rhine, Elbe, Ems, Weser. WasMon-CT is funded within the German Copernicus activities. Within the project, a database of atmospherically corrected, geo-referenced turbidity data will be assembled. The collected corresponding meta-data will include aspects of satellite data as well as hydrological data, e.g. cloud cover and river run-off. Based on this catalogue of spatially linked meta-data, the satellite data will be selected by e.g. cloud cover or run-off. The permanently updated database will include past as well as recent satellite images. It is designed with a long-term perspective to optimize the existing in-situ measurement network, which will serve partly for calibration and partly as validation data set. The aim is to extend, but not to substitute, the existing frequent point measurements with spatially extensive, satellite-derived data from the near surface part of the water column. Here, turbidity is used as proxy for corresponding suspended sediment concentrations. For this, the relationship between turbidity and suspended sediment concentrations will be investigated. Products as e.g. longitudinal profiles or virtual measurement stations will be developed from an application toolbox to specifically match requirements of operational monitoring tasks and to allow for a better integration into the existing monitoring system. The toolbox demonstrates the benefits of remote sensing by applying the established processing chain to diverse hydrological questions, such as for the investigation of tidal-affected sediment loads or mixing processes at river confluences. This new application will be of great value to assess, evaluate and monitor the status or the change of large-scale sediment processes at the system level. Accordingly, the satellite-derived turbidity data will strongly enhance federal consulting activities and thus ensure a modern river monitoring of Germany's federal water ways.

BLINKER: Automated Extraction of Ocular Indices from EEG Enabling Large-Scale Analysis

PubMed Central

Kleifges, Kelly; Bigdely-Shamlo, Nima; Kerick, Scott E.; Robbins, Kay A.

2017-01-01

Electroencephalography (EEG) offers a platform for studying the relationships between behavioral measures, such as blink rate and duration, with neural correlates of fatigue and attention, such as theta and alpha band power. Further, the existence of EEG studies covering a variety of subjects and tasks provides opportunities for the community to better characterize variability of these measures across tasks and subjects. We have implemented an automated pipeline (BLINKER) for extracting ocular indices such as blink rate, blink duration, and blink velocity-amplitude ratios from EEG channels, EOG channels, and/or independent components (ICs). To illustrate the use of our approach, we have applied the pipeline to a large corpus of EEG data (comprising more than 2000 datasets acquired at eight different laboratories) in order to characterize variability of certain ocular indicators across subjects. We also investigate dependence of ocular indices on task in a shooter study. We have implemented our algorithms in a freely available MATLAB toolbox called BLINKER. The toolbox, which is easy to use and can be applied to collections of data without user intervention, can automatically discover which channels or ICs capture blinks. The tools extract blinks, calculate common ocular indices, generate a report for each dataset, dump labeled images of the individual blinks, and provide summary statistics across collections. Users can run BLINKER as a script or as a plugin for EEGLAB. The toolbox is available at https://github.com/VisLab/EEG-Blinks. User documentation and examples appear at http://vislab.github.io/EEG-Blinks/. PMID:28217081

BrainNet Viewer: a network visualization tool for human brain connectomics.

PubMed

Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

Investigation of a Graphical CONOPS Development Environment for Agile Systems Engineering - Phase 2

DTIC Science & Technology

2010-05-31

Westerman, Crawshaw , Hockey, and Sauer, 1998) for practitioners. Thus, CTA extends research by providing a toolbox of methods for understanding teams...drive process and performance. Washington, DC: American Psychological Association. pp. 3-8. Shrayne, N. M., Westerman, S. J., Crawshaw , C. M

TRIAC II. A MatLab code for track measurements from SSNT detectors

NASA Astrophysics Data System (ADS)

Patiris, D. L.; Blekas, K.; Ioannides, K. G.

2007-08-01

A computer program named TRIAC II written in MATLAB and running with a friendly GUI has been developed for recognition and parameters measurements of particles' tracks from images of Solid State Nuclear Track Detectors. The program, using image analysis tools, counts the number of tracks and depending on the current working mode classifies them according to their radii (Mode I—circular tracks) or their axis (Mode II—elliptical tracks), their mean intensity value (brightness) and their orientation. Images of the detectors' surfaces are input to the code, which generates text files as output, including the number of counted tracks with the associated track parameters. Hough transform techniques are used for the estimation of the number of tracks and their parameters, providing results even in cases of overlapping tracks. Finally, it is possible for the user to obtain informative histograms as well as output files for each image and/or group of images. Program summaryTitle of program:TRIAC II Catalogue identifier:ADZC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZC_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer: Pentium III, 600 MHz Installations: MATLAB 7.0 Operating system under which the program has been tested: Windows XP Programming language used:MATLAB Memory required to execute with typical data:256 MB No. of bits in a word:32 No. of processors used:one Has the code been vectorized or parallelized?:no No. of lines in distributed program, including test data, etc.:25 964 No. of bytes in distributed program including test data, etc.: 4 354 510 Distribution format:tar.gz Additional comments: This program requires the MatLab Statistical toolbox and the Image Processing Toolbox to be installed. Nature of physical problem: Following the passage of a charged particle (protons and heavier) through a Solid State Nuclear Track Detector (SSNTD), a damage region is created, usually named latent track. After the chemical etching of the detectors in aqueous NaOH or KOH solutions, latent tracks can be sufficiently enlarged (with diameters of 1 μm or more) to become visible under an optical microscope. Using the appropriate apparatus, one can record images of the SSNTD's surface. The shapes of the particle's tracks are strongly dependent on their charge, energy and the angle of incidence. Generally, they have elliptical shapes and in the special case of vertical incidence, they are circular. The manual counting of tracks is a tedious and time-consuming task. An automatic system is needed to speed up the process and to increase the accuracy of the results. Method of solution: TRIAC II is based on a segmentation method that groups image pixels according to their intensity value (brightness) in a number of grey level groups. After the segmentation of pixels, the program recognizes and separates the track from the background, subsequently performing image morphology, where oversized objects or objects smaller than a threshold value are removed. Finally, using the appropriate Hough transform technique, the program counts the tracks, even those which overlap and classifies them according to their shape parameters and brightness. Typical running time: The analysis of an image with a PC (Intel Pentium III processor running at 600 MHz) requires 2 to 10 minutes, depending on the number of observed tracks and the digital resolution of the image. Unusual features of the program: This program has been tested with images of CR-39 detectors exposed to alpha particles. Also, in low contrast images with few or small tracks, background pixels can be recognized as track pixels. To avoid this problem the brightness of the background pixels should be sufficiently higher than that of the track pixels.

SHynergie: Development of a virtual project laboratory for monitoring hydraulic stimulations

NASA Astrophysics Data System (ADS)

Renner, Jörg; Friederich, Wolfgang; Meschke, Günther; Müller, Thomas; Steeb, Holger

2016-04-01

Hydraulic stimulations are the primary means of developing subsurface reservoirs regarding the extent of fluid transport in them. The associated creation or conditioning of a system of hydraulic conduits involves a range of hydraulic and mechanical processes but also chemical reactions, such as dissolution and precipitation, may affect the stimulation result on time scales as short as hours. In the light of the extent and complexity of these processes, the steering potential for the operator of a stimulation critically depends on the ability to integrate the maximum amount of site-specific information with profound process understanding and a large spectrum of experience. We report on the development of a virtual project laboratory for monitoring hydraulic stimulations within the project SHynergie (http://www.ruhr-uni-bochum.de/shynergie/). The concept of the laboratory envisioned product that constitutes a preparing and accompanying rather than post-processing instrument ultimately accessible to persons responsible for a project over a web-repository. The virtual laboratory consists of a data base, a toolbox, and a model-building environment. Entries in the data base are of two categories. On the one hand, selected mineral and rock properties are provided from the literature. On the other hand, project-specific entries of any format can be made that are assigned attributes regarding their use in a stimulation problem at hand. The toolbox is interactive and allows the user to perform calculations of effective properties and simulations of different types (e.g., wave propagation in a reservoir, hydraulic test). The model component is also hybrid. The laboratory provides a library of models reflecting a range of scenarios but also allows the user to develop a site-specific model constituting the basis for simulations. The laboratory offers the option to use its components following the typical workflow of a stimulation project. The toolbox incorporates simulation instruments developed in the course of the SHynergie project that account for the experimental and modeling results of the various sub-projects.

Wide-area mapping of resting state hemodynamic correlations at microvascular resolution with multi-contrast optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Senarathna, Janaka; Hadjiabadi, Darian; Gil, Stacy; Thakor, Nitish V.; Pathak, Arvind P.

2017-02-01

Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their `resting state connectivity'. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for `microvascular scale' imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.

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

The conservation physiology toolbox: status and opportunities

PubMed Central

Love, Oliver P; Hultine, Kevin R

2018-01-01

Abstract For over a century, physiological tools and techniques have been allowing researchers to characterize how organisms respond to changes in their natural environment and how they interact with human activities or infrastructure. Over time, many of these techniques have become part of the conservation physiology toolbox, which is used to monitor, predict, conserve, and restore plant and animal populations under threat. Here, we provide a summary of the tools that currently comprise the conservation physiology toolbox. By assessing patterns in articles that have been published in ‘Conservation Physiology’ over the past 5 years that focus on introducing, refining and validating tools, we provide an overview of where researchers are placing emphasis in terms of taxa and physiological sub-disciplines. Although there is certainly diversity across the toolbox, metrics of stress physiology (particularly glucocorticoids) and studies focusing on mammals have garnered the greatest attention, with both comprising the majority of publications (>45%). We also summarize the types of validations that are actively being completed, including those related to logistics (sample collection, storage and processing), interpretation of variation in physiological traits and relevance for conservation science. Finally, we provide recommendations for future tool refinement, with suggestions for: (i) improving our understanding of the applicability of glucocorticoid physiology; (ii) linking multiple physiological and non-physiological tools; (iii) establishing a framework for plant conservation physiology; (iv) assessing links between environmental disturbance, physiology and fitness; (v) appreciating opportunities for validations in under-represented taxa; and (vi) emphasizing tool validation as a core component of research programmes. Overall, we are confident that conservation physiology will continue to increase its applicability to more taxa, develop more non-invasive techniques, delineate where limitations exist, and identify the contexts necessary for interpretation in captivity and the wild. PMID:29942517

Basic Radar Altimetry Toolbox: tools to teach altimetry for ocean

NASA Astrophysics Data System (ADS)

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

2013-04-01

The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data, including the next mission to be launched, CryoSat. It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. More than 2000 people downloaded it (January 2013), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 and 3. Others are in discussion for the future, including addition of the future Sentinel-3. The Basic Radar Altimetry Toolbox is able: - to read most distributed radar altimetry data, including the one from future missions like Saral, - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways, including as an educational tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. Example from education uses will be presented, and feedback from those who used it as such will be most welcome. BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/

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.

An online database for plant image analysis software tools.

PubMed

Lobet, Guillaume; Draye, Xavier; Périlleux, Claire

2013-10-09

Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research. We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions. The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.

Imaging the square of the correlated two-electron wave function of a hydrogen molecule

DOE PAGES

Waitz, M.; Bello, R. Y.; Metz, D.; ...

2017-12-22

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in whichmore » electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.« less

Imaging the square of the correlated two-electron wave function of a hydrogen molecule.

PubMed

Waitz, M; Bello, R Y; Metz, D; Lower, J; Trinter, F; Schober, C; Keiling, M; Lenz, U; Pitzer, M; Mertens, K; Martins, M; Viefhaus, J; Klumpp, S; Weber, T; Schmidt, L Ph H; Williams, J B; Schöffler, M S; Serov, V V; Kheifets, A S; Argenti, L; Palacios, A; Martín, F; Jahnke, T; Dörner, R

2017-12-22

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in which electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.

Imaging the square of the correlated two-electron wave function of a hydrogen molecule

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

Waitz, M.; Bello, R. Y.; Metz, D.

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in whichmore » electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.« less

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.

Advanced Multimission Operations System (ATMO)

NASA Technical Reports Server (NTRS)

Mandrake, Lucas; Thompson, David R.

2013-01-01

The HiiHat toolbox developed for CAT/ENVI provides principal investigators direct, immediate, flexible, and seamless interaction with their instruments and data from any location. Offering segmentation and neutral region division, it facilitates the discovery of key endmembers and regions of interest larger than a single pixel. Crucial to the analysis of hyperspectral data from Mars or Earth is the removal of unwanted atmospheric signatures. For Mars and the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), residual atmospheric CO2 absorption is both directly problematic and indicative of processing errors with implications to the scientific utility of any particular image region. Estimating this residual error becomes key both in selecting regions of low distortion, and also to select mitigating methods, such as neutral region division. This innovation, the ATMO estimator, provides a simple, 0-1 normalized scalar that estimates this distortion (see figure). The metric is defined as the coefficient of determination of a quadratic fit in the region of distorting atmospheric absorption (approx 2 micron). This mimics the behavior of existing CRISM team mineralogical indices to estimate the presence of known, interesting mineral signatures. This facilitates the ATMO metric's assimilation into existing planetary geology workflows.

MCR Container Tools

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

Haas, Nicholas Q; Gillen, Robert E; Karnowski, Thomas P

MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting frommore » them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.« less

40 CFR 141.719 - Additional filtration toolbox components.

Code of Federal Regulations, 2011 CFR

2011-07-01

... establish a quality control release value (QCRV) for a non-destructive performance test that demonstrates... Detection Limit) (5) Challenge testing must be conducted at the maximum design flow rate for the filter as... representative hydraulic conditions at the maximum design flux and maximum design process recovery specified by...

40 CFR 141.719 - Additional filtration toolbox components.

Code of Federal Regulations, 2010 CFR

2010-07-01

... establish a quality control release value (QCRV) for a non-destructive performance test that demonstrates... Detection Limit) (5) Challenge testing must be conducted at the maximum design flow rate for the filter as... representative hydraulic conditions at the maximum design flux and maximum design process recovery specified by...

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.

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

PubMed

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

2002-05-30

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

A finite-element toolbox for the stationary Gross-Pitaevskii equation with rotation

NASA Astrophysics Data System (ADS)

Vergez, Guillaume; Danaila, Ionut; Auliac, Sylvain; Hecht, Frédéric

2016-12-01

We present a new numerical system using classical finite elements with mesh adaptivity for computing stationary solutions of the Gross-Pitaevskii equation. The programs are written as a toolbox for FreeFem++ (www.freefem.org), a free finite-element software available for all existing operating systems. This offers the advantage to hide all technical issues related to the implementation of the finite element method, allowing to easily code various numerical algorithms. Two robust and optimized numerical methods were implemented to minimize the Gross-Pitaevskii energy: a steepest descent method based on Sobolev gradients and a minimization algorithm based on the state-of-the-art optimization library Ipopt. For both methods, mesh adaptivity strategies are used to reduce the computational time and increase the local spatial accuracy when vortices are present. Different run cases are made available for 2D and 3D configurations of Bose-Einstein condensates in rotation. An optional graphical user interface is also provided, allowing to easily run predefined cases or with user-defined parameter files. We also provide several post-processing tools (like the identification of quantized vortices) that could help in extracting physical features from the simulations. The toolbox is extremely versatile and can be easily adapted to deal with different physical models.

MACCS : Multi-Mission Atmospheric Correction and Cloud Screening tool for high-frequency revisit data processing

NASA Astrophysics Data System (ADS)

Petrucci, B.; Huc, M.; Feuvrier, T.; Ruffel, C.; Hagolle, O.; Lonjou, V.; Desjardins, C.

2015-10-01

For the production of Level2A products during Sentinel-2 commissioning in the Technical Expertise Center Sentinel-2 in CNES, CESBIO proposed to adapt the Venus Level-2 , taking advantage of the similarities between the two missions: image acquisition at a high frequency (2 days for Venus, 5 days with the two Sentinel-2), high resolution (5m for Venus, 10, 20 and 60m for Sentinel-2), images acquisition under constant viewing conditions. The Multi-Mission Atmospheric Correction and Cloud Screening (MACCS) tool was born: based on CNES Orfeo Toolbox Library, Venμs processor which was already able to process Formosat2 and VENμS data, was adapted to process Sentinel-2 and Landsat5-7 data; since then, a great effort has been made reviewing MACCS software architecture in order to ease the add-on of new missions that have also the peculiarity of acquiring images at high resolution, high revisit and under constant viewing angles, such as Spot4/Take5 and Landsat8. The recursive and multi-temporal algorithm is implemented in a core that is the same for all the sensors and that combines several processing steps: estimation of cloud cover, cloud shadow, water, snow and shadows masks, of water vapor content, aerosol optical thickness, atmospheric correction. This core is accessed via a number of plug-ins where the specificity of the sensor and of the user project are taken into account: products format, algorithmic processing chaining and parameters. After a presentation of MACCS architecture and functionalities, the paper will give an overview of the production facilities integrating MACCS and the associated specificities: the interest for this tool has grown worldwide and MACCS will be used for extensive production within the THEIA land data center and Agri-S2 project. Finally the paper will zoom on the use of MACCS during Sentinel-2 In Orbit Test phase showing the first Level-2A products.

ERP Reliability Analysis (ERA) Toolbox: An open-source toolbox for analyzing the reliability of event-related brain potentials.

PubMed

Clayson, Peter E; Miller, Gregory A

2017-01-01

Generalizability theory (G theory) provides a flexible, multifaceted approach to estimating score reliability. G theory's approach to estimating score reliability has important advantages over classical test theory that are relevant for research using event-related brain potentials (ERPs). For example, G theory does not require parallel forms (i.e., equal means, variances, and covariances), can handle unbalanced designs, and provides a single reliability estimate for designs with multiple sources of error. This monograph provides a detailed description of the conceptual framework of G theory using examples relevant to ERP researchers, presents the algorithms needed to estimate ERP score reliability, and provides a detailed walkthrough of newly-developed software, the ERP Reliability Analysis (ERA) Toolbox, that calculates score reliability using G theory. The ERA Toolbox is open-source, Matlab software that uses G theory to estimate the contribution of the number of trials retained for averaging, group, and/or event types on ERP score reliability. The toolbox facilitates the rigorous evaluation of psychometric properties of ERP scores recommended elsewhere in this special issue. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

MATLAB tools for improved characterization and quantification of volcanic incandescence in Webcam imagery; applications at Kilauea Volcano, Hawai'i

USGS Publications Warehouse

Patrick, Matthew R.; Kauahikaua, James P.; Antolik, Loren

2010-01-01

Webcams are now standard tools for volcano monitoring and are used at observatories in Alaska, the Cascades, Kamchatka, Hawai'i, Italy, and Japan, among other locations. Webcam images allow invaluable documentation of activity and provide a powerful comparative tool for interpreting other monitoring datastreams, such as seismicity and deformation. Automated image processing can improve the time efficiency and rigor of Webcam image interpretation, and potentially extract more information on eruptive activity. For instance, Lovick and others (2008) provided a suite of processing tools that performed such tasks as noise reduction, eliminating uninteresting images from an image collection, and detecting incandescence, with an application to dome activity at Mount St. Helens during 2007. In this paper, we present two very simple automated approaches for improved characterization and quantification of volcanic incandescence in Webcam images at Kilauea Volcano, Hawai`i. The techniques are implemented in MATLAB (version 2009b, Copyright: The Mathworks, Inc.) to take advantage of the ease of matrix operations. Incandescence is a useful indictor of the location and extent of active lava flows and also a potentially powerful proxy for activity levels at open vents. We apply our techniques to a period covering both summit and east rift zone activity at Kilauea during 2008?2009 and compare the results to complementary datasets (seismicity, tilt) to demonstrate their integrative potential. A great strength of this study is the demonstrated success of these tools in an operational setting at the Hawaiian Volcano Observatory (HVO) over the course of more than a year. Although applied only to Webcam images here, the techniques could be applied to any type of sequential images, such as time-lapse photography. We expect that these tools are applicable to many other volcano monitoring scenarios, and the two MATLAB scripts, as they are implemented at HVO, are included in the appendixes. These scripts would require minor to moderate modifications for use elsewhere, primarily to customize directory navigation. If the user has some familiarity with MATLAB, or programming in general, these modifications should be easy. Although we originally anticipated needing the Image Processing Toolbox, the scripts in the appendixes do not require it. Thus, only the base installation of MATLAB is needed. Because fairly basic MATLAB functions are used, we expect that the script can be run successfully by versions earlier than 2009b.

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

Real time wind farm emulation using SimWindFarm toolbox

NASA Astrophysics Data System (ADS)

Topor, Marcel

2016-06-01

This paper presents a wind farm emulation solution using an open source Matlab/Simulink toolbox and the National Instruments cRIO platform. This work is based on the Aeolus SimWindFarm (SWF) toolbox models developed at Aalborg university, Denmark. Using the Matlab Simulink models developed in SWF, the modeling code can be exported to a real time model using the NI Veristand model framework and the resulting code is integrated as a hardware in the loop control on the NI 9068 platform.

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.

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/

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

Automatic detection and classification of EOL-concrete and resulting recovered products by hyperspectral imaging

NASA Astrophysics Data System (ADS)

Palmieri, Roberta; Bonifazi, Giuseppe; Serranti, Silvia

2014-05-01

The recovery of materials from Demolition Waste (DW) represents one of the main target of the recycling industry and the its characterization is important in order to set up efficient sorting and/or quality control systems. End-Of-Life (EOL) concrete materials identification is necessary to maximize DW conversion into useful secondary raw materials, so it is fundamental to develop strategies for the implementation of an automatic recognition system of the recovered products. In this paper, HyperSpectral Imaging (HSI) technique was applied in order to detect DW composition. Hyperspectral images were acquired by a laboratory device equipped with a HSI sensing device working in the near infrared range (1000-1700 nm): NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Acquired spectral data were analyzed adopting the PLS_Toolbox (Version 7.5, Eigenvector Research, Inc.) under Matlab® environment (Version 7.11.1, The Mathworks, Inc.), applying different chemometric methods: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials, distinguishing recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood, foam, etc.). The developed procedure is cheap, fast and non-destructive: it could be used to make some steps of the recycling process more efficient and less expensive.

Radionuclide Myocardial Perfusion Imaging for the Evaluation of Patients With Known or Suspected Coronary Artery Disease in the Era of Multimodality Cardiovascular Imaging

PubMed Central

Taqueti, Viviany R.; Di Carli, Marcelo F.

2018-01-01

Over the last several decades, radionuclide myocardial perfusion imaging (MPI) with single photon emission tomography and positron emission tomography has been a mainstay for the evaluation of patients with known or suspected coronary artery disease (CAD). More recently, technical advances in separate and complementary imaging modalities including coronary computed tomography angiography, computed tomography perfusion, cardiac magnetic resonance imaging, and contrast stress echocardiography have expanded the toolbox of diagnostic testing for cardiac patients. While the growth of available technologies has heralded an exciting era of multimodality cardiovascular imaging, coordinated and dispassionate utilization of these techniques is needed to implement the right test for the right patient at the right time, a promise of “precision medicine.” In this article, we review the maturing role of MPI in the current era of multimodality cardiovascular imaging, particularly in the context of recent advances in myocardial blood flow quantitation, and as applied to the evaluation of patients with known or suspected CAD. PMID:25770849

40 CFR 141.720 - Inactivation toolbox components.

Code of Federal Regulations, 2014 CFR

2014-07-01

... treatment unit process with a measurable disinfectant residual level and a liquid volume. Under this... through reactor validation testing, as described in paragraph (d)(2) of this section. The UV dose values....0 12 11 143 (vii) 3.5 15 15 163 (viii) 4.0 22 22 186 (2) Reactor validation testing. Systems must...

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB's Toolbox

PubMed Central

Mahmoodabadi, M. J.; Taherkhorsandi, M.; Bagheri, A.

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. PMID:24616619

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.

Electronic audit and feedback intervention with action implementation toolbox to improve pain management in intensive care: protocol for a laboratory experiment and cluster randomised trial.

PubMed

Gude, Wouter T; Roos-Blom, Marie-José; van der Veer, Sabine N; de Jonge, Evert; Peek, Niels; Dongelmans, Dave A; de Keizer, Nicolette F

2017-05-25

Audit and feedback is often used as a strategy to improve quality of care, however, its effects are variable and often marginal. In order to learn how to design and deliver effective feedback, we need to understand their mechanisms of action. This theory-informed study will investigate how electronic audit and feedback affects improvement intentions (i.e. information-intention gap), and whether an action implementation toolbox with suggested actions and materials helps translating those intentions into action (i.e. intention-behaviour gap). The study will be executed in Dutch intensive care units (ICUs) and will be focused on pain management. We will conduct a laboratory experiment with individual ICU professionals to assess the impact of feedback on their intentions to improve practice. Next, we will conduct a cluster randomised controlled trial with ICUs allocated to feedback without or feedback with action implementation toolbox group. Participants will not be told explicitly what aspect of the intervention is randomised; they will only be aware that there are two variations of providing feedback. ICUs are eligible for participation if they submit indicator data to the Dutch National Intensive Care Evaluation (NICE) quality registry and agree to allocate a quality improvement team that spends 4 h per month on the intervention. All participating ICUs will receive access to an online quality dashboard that provides two functionalities: gaining insight into clinical performance on pain management indicators and developing action plans. ICUs with access to the toolbox can develop their action plans guided by a list of potential barriers in the care process, associated suggested actions, and supporting materials to facilitate implementation of the actions. The primary outcome measure for the laboratory experiment is the proportion of improvement intentions set by participants that are consistent with recommendations based on peer comparisons; for the randomised trial it is the proportion of patient shifts during which pain has been adequately managed. We will also conduct a process evaluation to understand how the intervention is implemented and used in clinical practice, and how implementation and use affect the intervention's impact. The results of this study will inform care providers and managers in ICU and other clinical settings how to use indicator-based performance feedback in conjunction with an action implementation toolbox to improve quality of care. Within the ICU context, this study will produce concrete and directly applicable knowledge with respect to what is or is not effective for improving pain management, and under which circumstances. The results will further guide future research that aims to understand the mechanisms behind audit and feedback and contribute to identifying the active ingredients of successful interventions. ClinicalTrials.gov NCT02922101 . Registered 26 September 2016.

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.

Methodology for heritage conservation in Belgium based on multi-temporal interferometry

NASA Astrophysics Data System (ADS)

Bejarano-Urrego, L.; Verstrynge, E.; Shimoni, M.; Lopez, J.; Walstra, J.; Declercq, P.-Y.; Derauw, D.; Hayen, R.; Van Balen, K.

2017-09-01

Soil differential settlements that cause structural damage to heritage buildings are precipitating cultural and economic value losses. Adequate damage assessment as well as protection and preservation of the built patrimony are priorities at national and local levels, so they require advanced integration and analysis of environmental, architectural and historical parameters. The GEPATAR project (GEotechnical and Patrimonial Archives Toolbox for ARchitectural conservation in Belgium) aims to create an online interactive geo-information tool that allows the user to view and to be informed about the Belgian heritage buildings at risk due to differential soil settlements. Multi-temporal interferometry techniques (MTI) have been proven to be a powerful technique for analyzing earth surface deformation patterns through time series of Synthetic Aperture Radar (SAR) images. These techniques allow to measure ground movements over wide areas at high precision and relatively low cost. In this project, Persistent Scatterer Synthetic Aperture Radar Interferometry (PS-InSAR) and Multidimensional Small Baseline Subsets (MSBAS) are used to measure and monitor the temporal evolution of surface deformations across Belgium. This information is integrated with the Belgian heritage data by means of an interactive toolbox in a GIS environment in order to identify the level of risk. At country scale, the toolbox includes ground deformation hazard maps, geological information, location of patrimony buildings and land use; while at local scale, it includes settlement rates, photographic and historical surveys as well as architectural and geotechnical information. Some case studies are investigated by means of on-site monitoring techniques and stability analysis to evaluate the applied approaches. This paper presents a description of the methodology being implemented in the project together with the case study of the Saint Vincent's church which is located on a former colliery zone. For this building, damage is assessed by means of PSInSAR.

SU-C-201-04: Quantification of Perfusion Heterogeneity Based On Texture Analysis for Fully Automatic Detection of Ischemic Deficits From Myocardial Perfusion Imaging

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

Fang, Y; Huang, H; Su, T

Purpose: Texture-based quantification of image heterogeneity has been a popular topic for imaging studies in recent years. As previous studies mainly focus on oncological applications, we report our recent efforts of applying such techniques on cardiac perfusion imaging. A fully automated procedure has been developed to perform texture analysis for measuring the image heterogeneity. Clinical data were used to evaluate the preliminary performance of such methods. Methods: Myocardial perfusion images of Thallium-201 scans were collected from 293 patients with suspected coronary artery disease. Each subject underwent a Tl-201 scan and a percutaneous coronary intervention (PCI) within three months. The PCImore » Result was used as the gold standard of coronary ischemia of more than 70% stenosis. Each Tl-201 scan was spatially normalized to an image template for fully automatic segmentation of the LV. The segmented voxel intensities were then carried into the texture analysis with our open-source software Chang Gung Image Texture Analysis toolbox (CGITA). To evaluate the clinical performance of the image heterogeneity for detecting the coronary stenosis, receiver operating characteristic (ROC) analysis was used to compute the overall accuracy, sensitivity and specificity as well as the area under curve (AUC). Those indices were compared to those obtained from the commercially available semi-automatic software QPS. Results: With the fully automatic procedure to quantify heterogeneity from Tl-201 scans, we were able to achieve a good discrimination with good accuracy (74%), sensitivity (73%), specificity (77%) and AUC of 0.82. Such performance is similar to those obtained from the semi-automatic QPS software that gives a sensitivity of 71% and specificity of 77%. Conclusion: Based on fully automatic procedures of data processing, our preliminary data indicate that the image heterogeneity of myocardial perfusion imaging can provide useful information for automatic determination of the myocardial ischemia.« less

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

Evolutionary process development towards next generation crystalline silicon solar cells : a semiconductor process toolbox application

NASA Astrophysics Data System (ADS)

John, J.; Prajapati, V.; Vermang, B.; Lorenz, A.; Allebe, C.; Rothschild, A.; Tous, L.; Uruena, A.; Baert, K.; Poortmans, J.

2012-08-01

Bulk crystalline Silicon solar cells are covering more than 85% of the world's roof top module installation in 2010. With a growth rate of over 30% in the last 10 years this technology remains the working horse of solar cell industry. The full Aluminum back-side field (Al BSF) technology has been developed in the 90's and provides a production learning curve on module price of constant 20% in average. The main reason for the decrease of module prices with increasing production capacity is due to the effect of up scaling industrial production. For further decreasing of the price per wattpeak silicon consumption has to be reduced and efficiency has to be improved. In this paper we describe a successive efficiency improving process development starting from the existing full Al BSF cell concept. We propose an evolutionary development includes all parts of the solar cell process: optical enhancement (texturing, polishing, anti-reflection coating), junction formation and contacting. Novel processes are benchmarked on industrial like baseline flows using high-efficiency cell concepts like i-PERC (Passivated Emitter and Rear Cell). While the full Al BSF crystalline silicon solar cell technology provides efficiencies of up to 18% (on cz-Si) in production, we are achieving up to 19.4% conversion efficiency for industrial fabricated, large area solar cells with copper based front side metallization and local Al BSF applying the semiconductor toolbox.

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.

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.

A multiplexed microfluidic toolbox for the rapid optimization of affinity-driven partition in aqueous two phase systems.

PubMed

Bras, Eduardo J S; Soares, Ruben R G; Azevedo, Ana M; Fernandes, Pedro; Arévalo-Rodríguez, Miguel; Chu, Virginia; Conde, João P; Aires-Barros, M Raquel

2017-09-15

Antibodies and other protein products such as interferons and cytokines are biopharmaceuticals of critical importance which, in order to be safely administered, have to be thoroughly purified in a cost effective and efficient manner. The use of aqueous two-phase extraction (ATPE) is a viable option for this purification, but these systems are difficult to model and optimization procedures require lengthy and expensive screening processes. Here, a methodology for the rapid screening of antibody extraction conditions using a microfluidic channel-based toolbox is presented. A first microfluidic structure allows a simple negative-pressure driven rapid screening of up to 8 extraction conditions simultaneously, using less than 20μL of each phase-forming solution per experiment, while a second microfluidic structure allows the integration of multi-step extraction protocols based on the results obtained with the first device. In this paper, this microfluidic toolbox was used to demonstrate the potential of LYTAG fusion proteins used as affinity tags to optimize the partitioning of antibodies in ATPE processes, where a maximum partition coefficient (K) of 9.2 in a PEG 3350/phosphate system was obtained for the antibody extraction in the presence of the LYTAG-Z dual ligand. This represents an increase of approx. 3.7 fold when compared with the same conditions without the affinity molecule (K=2.5). Overall, this miniaturized and versatile approach allowed the rapid optimization of molecule partition followed by a proof-of-concept demonstration of an integrated back extraction procedure, both of which are critical procedures towards obtaining high purity biopharmaceuticals using ATPE. Copyright © 2017 Elsevier B.V. All rights reserved.

Optical performance assessment under environmental and mechanical perturbations in large, deployable telescopes

NASA Astrophysics Data System (ADS)

Folley, Christopher; Bronowicki, Allen

2005-09-01

Prediction of optical performance for large, deployable telescopes under environmental conditions and mechanical disturbances is a crucial part of the design verification process of such instruments for all phases of design and operation: ground testing, commissioning, and on-orbit operation. A Structural-Thermal-Optical-Performance (STOP) analysis methodology is often created that integrates the output of one analysis with the input of another. The integration of thermal environment predictions with structural models is relatively well understood, while the integration of structural deformation results into optical analysis/design software is less straightforward. A Matlab toolbox has been created that effectively integrates the predictions of mechanical deformations on optical elements generated by, for example, finite element analysis, and computes optical path differences for the distorted prescription. The engine of the toolbox is the real ray-tracing algorithm that allows the optical surfaces to be defined in a single, global coordinate system thereby allowing automatic alignment of the mechanical coordinate system with the optical coordinate system. Therefore, the physical location of the optical surfaces is identical in the optical prescription and the finite element model. The application of rigid body displacements to optical surfaces, however, is more general than for use solely in STOP analysis, such as the analysis of misalignments during the commissioning process. Furthermore, all the functionality of Matlab is available for optimization and control. Since this is a new tool for use on flight programs, it has been verified against CODE V. The toolbox' functionality, to date, is described, verification results are presented, and, as an example of its utility, results of a thermal distortion analysis are presented using the James Webb Space Telescope (JWST) prescription.

From magic to technology: materials integration by wafer bonding

NASA Astrophysics Data System (ADS)

Dragoi, Viorel

2006-02-01

Wafer bonding became in the last decade a very powerful technology for MEMS/MOEMS manufacturing. Being able to offer a solution to overcome some problems of the standard processes used for materials integration (e.g. epitaxy, thin films deposition), wafer bonding is nowadays considered an important item in the MEMS engineer toolbox. Different principles governing the wafer bonding processes will be reviewed in this paper. Various types of applications will be presented as examples.

FPGA-based real-time swept-source OCT systems for B-scan live-streaming or volumetric imaging

NASA Astrophysics Data System (ADS)

Bandi, Vinzenz; Goette, Josef; Jacomet, Marcel; von Niederhäusern, Tim; Bachmann, Adrian H.; Duelk, Marcus

2013-03-01

We have developed a Swept-Source Optical Coherence Tomography (Ss-OCT) system with high-speed, real-time signal processing on a commercially available Data-Acquisition (DAQ) board with a Field-Programmable Gate Array (FPGA). The Ss-OCT system simultaneously acquires OCT and k-clock reference signals at 500MS/s. From the k-clock signal of each A-scan we extract a remap vector for the k-space linearization of the OCT signal. The linear but oversampled interpolation is followed by a 2048-point FFT, additional auxiliary computations, and a data transfer to a host computer for real-time, live-streaming of B-scan or volumetric C-scan OCT visualization. We achieve a 100 kHz A-scan rate by parallelization of our hardware algorithms, which run on standard and affordable, commercially available DAQ boards. Our main development tool for signal analysis as well as for hardware synthesis is MATLAB® with add-on toolboxes and 3rd-party tools.

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.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

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.

ZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis

PubMed Central

Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas

2016-01-01

Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/. PMID:26882475

The Radiology Resident iPad Toolbox: an educational and clinical tool for radiology residents.

PubMed

Sharpe, Emerson E; Kendrick, Michael; Strickland, Colin; Dodd, Gerald D

2013-07-01

Tablet computing and mobile resources are the hot topics in technology today, with that interest spilling into the medical field. To improve resident education, a fully configured iPad, referred to as the "Radiology Resident iPad Toolbox," was created and implemented at the University of Colorado. The goal was to create a portable device with comprehensive educational, clinical, and communication tools that would contain all necessary resources for an entire 4-year radiology residency. The device was distributed to a total of 34 radiology residents (8 first-year residents, 8 second-year residents, 9 third-year residents, and 9 fourth-year residents). This article describes the process used to develop and deploy the device, provides a distillation of useful applications and resources decided upon after extensive evaluation, and assesses the impact this device had on resident education. The Radiology Resident iPad Toolbox is a cost-effective, portable, educational instrument that has increased studying efficiency; improved access to study materials such as books, radiology cases, lectures, and web-based resources; and increased interactivity in educational conferences and lectures through the use of audience-response software, with questions geared toward the new ABR board format. This preconfigured tablet fully embraces the technology shift into mobile computing and represents a paradigm shift in educational strategy. Copyright © 2013 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Vectorized data acquisition and fast triple-correlation integrals for Fluorescence Triple Correlation Spectroscopy

PubMed Central

Ridgeway, William K; Millar, David P; Williamson, James R

2013-01-01

Fluorescence Correlation Spectroscopy (FCS) is widely used to quantitate reaction rates and concentrations of molecules in vitro and in vivo. We recently reported Fluorescence Triple Correlation Spectroscopy (F3CS), which correlates three signals together instead of two. F3CS can analyze the stoichiometries of complex mixtures and detect irreversible processes by identifying time-reversal asymmetries. Here we report the computational developments that were required for the realization of F3CS and present the results as the Triple Correlation Toolbox suite of programs. Triple Correlation Toolbox is a complete data analysis pipeline capable of acquiring, correlating and fitting large data sets. Each segment of the pipeline handles error estimates for accurate error-weighted global fitting. Data acquisition was accelerated with a combination of off-the-shelf counter-timer chips and vectorized operations on 128-bit registers. This allows desktop computers with inexpensive data acquisition cards to acquire hours of multiple-channel data with sub-microsecond time resolution. Off-line correlation integrals were implemented as a two delay time multiple-tau scheme that scales efficiently with multiple processors and provides an unprecedented view of linked dynamics. Global fitting routines are provided to fit FCS and F3CS data to models containing up to ten species. Triple Correlation Toolbox is a complete package that enables F3CS to be performed on existing microscopes. PMID:23525193

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Determination of sub-daily glacier uplift and horizontal flow velocity with time-lapse images using ImGRAFT

NASA Astrophysics Data System (ADS)

Egli, Pascal; Mankoff, Ken; Mettra, François; Lane, Stuart

2017-04-01

This study investigates the application of feature tracking algorithms to monitoring of glacier uplift. Several publications have confirmed the occurrence of an uplift of the glacier surface in the late morning hours of the mid to late ablation season. This uplift is thought to be caused by high sub-glacial water pressures at the onset of melt caused by overnight-deposited sediment that blocks subglacial channels. We use time-lapse images from a camera mounted in front of the glacier tongue of Haut Glacier d'Arolla during August 2016 in combination with a Digital Elevation Model and GPS measurements in order to investigate the phenomenon of glacier uplift using the feature tracking toolbox ImGRAFT. Camera position is corrected for all images and the images are geo-rectified using Ground Control Points visible in every image. Changing lighting conditions due to different sun angles create substantial noise and complicate the image analysis. A small glacier uplift of the order of 5 cm over a time span of 3 hours may be observed on certain days, confirming previous research.

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...

Shaping the Future with Math, Science, and Technology: Solutions and Lesson Plans to Prepare Tomorrow's Innovators

ERIC Educational Resources Information Center

Adams, Dennis; Hamm, Mary

2011-01-01

"Shaping the Future with Math, Science, and Technology" examines how ingenuity, creativity, and teamwork skills are part of an intellectual toolbox associated with math, science, and technology. The book provides new ideas, proven processes, practical tools, and examples useful to educators who want to encourage students to solve problems and…

Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Pohl, Rudiger F.

2009-01-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

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…

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.

Basic Radar Altimetry Toolbox: Tools and Tutorial To Use Radar Altimetry For Cryosphere

NASA Astrophysics Data System (ADS)

Benveniste, J. J.; Bronner, E.; Dinardo, S.; Lucas, B. M.; Rosmorduc, V.; Earith, D.

2010-12-01

Radar altimetry is very much a technique expanding its applications. If quite a lot of efforts have been made for oceanography users (including easy-to-use data), the use of those data for cryosphere application, especially with the new ESA CryoSat-2 mission data is still somehow tedious, especially for new Altimetry data products users. ESA and CNES thus had the Basic Radar Altimetry Toolbox developed a few years ago, and are improving and upgrading it to fit new missions and the growing number of altimetry uses. The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data. The software is able: - to read most distributed radar altimetry data, from ERS-1 & 2, Topex/Poseidon, Geosat Follow-on, Jason-1, Envisat, Jason- 2, CryoSat and the future Saral missions, - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways: - as a data reading tool, with APIs for C, Fortran, Matlab and IDL - as processing/extraction routines, through the on-line command mode - as an educational and a quick-look tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. It is an opportunity to teach remote sensing with practical training. It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. About 1200 people downloaded it (Summer 2010), with many "newcomers" to altimetry among them, including teachers and professors. Users' feedback, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2. Others are under development, some are in discussion for the future. Data use cases on cryosphere applications will be presented. BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/

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.

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

Wyrm: A Brain-Computer Interface Toolbox in Python.

PubMed

Venthur, Bastian; Dähne, Sven; Höhne, Johannes; Heller, Hendrik; Blankertz, Benjamin

2015-10-01

In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm ( https://github.com/bbci/wyrm ), an open source BCI toolbox in Python. Wyrm is applicable to a broad range of neuroscientific problems. It can be used as a toolbox for analysis and visualization of neurophysiological data and in real-time settings, like an online BCI application. In order to prevent software defects, Wyrm makes extensive use of unit testing. We will explain the key aspects of Wyrm's software architecture and design decisions for its data structure, and demonstrate and validate the use of our toolbox by presenting our approach to the classification tasks of two different data sets from the BCI Competition III. Furthermore, we will give a brief analysis of the data sets using our toolbox, and demonstrate how we implemented an online experiment using Wyrm. With Wyrm we add the final piece to our ongoing effort to provide a complete, free and open source BCI system in Python.

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

Sauter, Nicholas K., E-mail: nksauter@lbl.gov; Hattne, Johan; Grosse-Kunstleve, Ralf W.

The Computational Crystallography Toolbox (cctbx) is a flexible software platform that has been used to develop high-throughput crystal-screening tools for both synchrotron sources and X-ray free-electron lasers. Plans for data-processing and visualization applications are discussed, and the benefits and limitations of using graphics-processing units are evaluated. Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h{sup −1}) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in realmore » time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units.« less

Basic Radar Altimetry Toolbox and Radar Altimetry Tutorial: Tools for all Altimetry Users

NASA Astrophysics Data System (ADS)

Rosmorduc, Vinca; Benveniste, J.; Breebaart, L.; Bronner, E.; Dinardo, S.; Earith, D.; Lucas, B. M.; Maheu, C.; Niejmeier, S.; Picot, N.

2013-09-01

The Basic Radar Altimetry Toolbox is an "all- altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data, including the next mission to be launched, Saral.It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. Nearly 2000 people downloaded it (January 2012), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 to 4. Others are under development, some are in discussion for the future.The Basic Radar Altimetry Toolbox is able:- to read most distributed radar altimetry data, including the one from future missions like Saral, Jason-3- to perform some processing, data editing and statistic, - and to visualize the results.It can be used at several levels/several ways, including as an educational tool, with the graphical user interface.As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data.BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. More than 2000 people downloaded it (as of end of September 2012), with many "newcomers" to altimetry among them, and teachers/students. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 and 3. Others are envisioned, some are in discussion.

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.

Processing methods for differential analysis of LC/MS profile data

PubMed Central

Katajamaa, Mikko; Orešič, Matej

2005-01-01

Background Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. Results We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. Conclusion The software is freely available under the GNU General Public License and it can be obtained from the project web page at: . PMID:16026613

Processing methods for differential analysis of LC/MS profile data.

PubMed

Katajamaa, Mikko; Oresic, Matej

2005-07-18

Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. The software is freely available under the GNU General Public License and it can be obtained from the project web page at: http://mzmine.sourceforge.net/.

Creating Qungasvik (a Yup'ik intervention "toolbox"): case examples from a community-developed and culturally-driven intervention.

PubMed

Rasmus, Stacy M; Charles, Billy; Mohatt, Gerald V

2014-09-01

This paper describes the development of a Yup'ik Alaska Native approach to suicide and alcohol abuse prevention that resulted in the creation of the Qungasvik, a toolbox promoting reasons for life and sobriety among youth. The Qungasvik is made up of thirty-six modules that function as cultural scripts for creating experiences in Yup'ik communities that build strengths and protection against suicide and alcohol abuse. The Qungasvik manual represents the results of a community based participatory research intervention development process grounded in culture and local process, and nurtured through a syncretic blending of Indigenous and Western theories and practices. This paper will provide a description of the collaborative steps taken at the community-level to develop the intervention modules. This process involved university researchers and community members coming together and drawing from multiple sources of data and knowledge to inform the development of prevention activities addressing youth suicide and alcohol abuse. We will present case examples describing the development of three keystone modules; Qasgiq (The Men's House), Yup'ik Kinship Terms, and Surviving Your Feelings. These modules each are representative of the process that the community co-researcher team took to develop and implement protective experiences that: (1) create supportive community, (2) strengthen families, and (3) give individuals tools to be healthy and strong.

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.

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).

The Application of Support Vector Machine (svm) Using Cielab Color Model, Color Intensity and Color Constancy as Features for Ortho Image Classification of Benthic Habitats in Hinatuan, Surigao del Sur, Philippines

NASA Astrophysics Data System (ADS)

Cubillas, J. E.; Japitana, M.

2016-06-01

This study demonstrates the application of CIELAB, Color intensity, and One Dimensional Scalar Constancy as features for image recognition and classifying benthic habitats in an image with the coastal areas of Hinatuan, Surigao Del Sur, Philippines as the study area. The study area is composed of four datasets, namely: (a) Blk66L005, (b) Blk66L021, (c) Blk66L024, and (d) Blk66L0114. SVM optimization was performed in Matlab® software with the help of Parallel Computing Toolbox to hasten the SVM computing speed. The image used for collecting samples for SVM procedure was Blk66L0114 in which a total of 134,516 sample objects of mangrove, possible coral existence with rocks, sand, sea, fish pens and sea grasses were collected and processed. The collected samples were then used as training sets for the supervised learning algorithm and for the creation of class definitions. The learned hyper-planes separating one class from another in the multi-dimensional feature space can be thought of as a super feature which will then be used in developing the C (classifier) rule set in eCognition® software. The classification results of the sampling site yielded an accuracy of 98.85% which confirms the reliability of remote sensing techniques and analysis employed to orthophotos like the CIELAB, Color Intensity and One dimensional scalar constancy and the use of SVM classification algorithm in classifying benthic habitats.

The Diffusion Tensor Imaging Toolbox

PubMed Central

Alger, Jeffry R.

2012-01-01

During the past few years, the Journal of Neuroscience has published over 30 articles that describe investigations that used Diffusion Tensor Imaging (DTI) and related techniques as a primary observation method. This illustrates a growing interest in DTI within the basic and clinical neuroscience communities. This article summarizes DTI methodology in terms that can be immediately understood by the neuroscientist who has little previous exposure to DTI. It describes the fundamentals of water molecular diffusion coefficient measurement in brain tissue and illustrates how these fundamentals can be used to form vivid and useful depictions of white matter macroscopic and microscopic anatomy. It also describes current research applications and the technique’s attributes and limitations. It is hoped that this article will help the readers of this Journal to more effectively evaluate neuroscience studies that use DTI. PMID:22649222

Topologically preserving straightening of spinal cord MRI.

PubMed

De Leener, Benjamin; Mangeat, Gabriel; Dupont, Sara; Martin, Allan R; Callot, Virginie; Stikov, Nikola; Fehlings, Michael G; Cohen-Adad, Julien

2017-10-01

To propose a robust and accurate method for straightening magnetic resonance (MR) images of the spinal cord, based on spinal cord segmentation, that preserves spinal cord topology and that works for any MRI contrast, in a context of spinal cord template-based analysis. The spinal cord curvature was computed using an iterative Non-Uniform Rational B-Spline (NURBS) approximation. Forward and inverse deformation fields for straightening were computed by solving analytically the straightening equations for each image voxel. Computational speed-up was accomplished by solving all voxel equation systems as one single system. Straightening accuracy (mean and maximum distance from straight line), computational time, and robustness to spinal cord length was evaluated using the proposed and the standard straightening method (label-based spline deformation) on 3T T 2 - and T 1 -weighted images from 57 healthy subjects and 33 patients with spinal cord compression due to degenerative cervical myelopathy (DCM). The proposed algorithm was more accurate, more robust, and faster than the standard method (mean distance = 0.80 vs. 0.83 mm, maximum distance = 1.49 vs. 1.78 mm, time = 71 vs. 174 sec for the healthy population and mean distance = 0.65 vs. 0.68 mm, maximum distance = 1.28 vs. 1.55 mm, time = 32 vs. 60 sec for the DCM population). A novel image straightening method that enables template-based analysis of quantitative spinal cord MRI data is introduced. This algorithm works for any MRI contrast and was validated on healthy and patient populations. The presented method is implemented in the Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1209-1219. © 2017 International Society for Magnetic Resonance in Medicine.

Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers.

PubMed

Shu, Jie; Dolman, G E; Duan, Jiang; Qiu, Guoping; Ilyas, Mohammad

2016-04-27

Colour is the most important feature used in quantitative immunohistochemistry (IHC) image analysis; IHC is used to provide information relating to aetiology and to confirm malignancy. Statistical modelling is a technique widely used for colour detection in computer vision. We have developed a statistical model of colour detection applicable to detection of stain colour in digital IHC images. Model was first trained by massive colour pixels collected semi-automatically. To speed up the training and detection processes, we removed luminance channel, Y channel of YCbCr colour space and chose 128 histogram bins which is the optimal number. A maximum likelihood classifier is used to classify pixels in digital slides into positively or negatively stained pixels automatically. The model-based tool was developed within ImageJ to quantify targets identified using IHC and histochemistry. The purpose of evaluation was to compare the computer model with human evaluation. Several large datasets were prepared and obtained from human oesophageal cancer, colon cancer and liver cirrhosis with different colour stains. Experimental results have demonstrated the model-based tool achieves more accurate results than colour deconvolution and CMYK model in the detection of brown colour, and is comparable to colour deconvolution in the detection of pink colour. We have also demostrated the proposed model has little inter-dataset variations. A robust and effective statistical model is introduced in this paper. The model-based interactive tool in ImageJ, which can create a visual representation of the statistical model and detect a specified colour automatically, is easy to use and available freely at http://rsb.info.nih.gov/ij/plugins/ihc-toolbox/index.html . Testing to the tool by different users showed only minor inter-observer variations in results.

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...

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

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

Fully Automated Atlas-Based Hippocampus Volumetry for Clinical Routine: Validation in Subjects with Mild Cognitive Impairment from the ADNI Cohort.

PubMed

Suppa, Per; Hampel, Harald; Spies, Lothar; Fiebach, Jochen B; Dubois, Bruno; Buchert, Ralph

2015-01-01

Hippocampus volumetry based on magnetic resonance imaging (MRI) has not yet been translated into everyday clinical diagnostic patient care, at least in part due to limited availability of appropriate software tools. In the present study, we evaluate a fully-automated and computationally efficient processing pipeline for atlas based hippocampal volumetry using freely available Statistical Parametric Mapping (SPM) software in 198 amnestic mild cognitive impairment (MCI) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI1). Subjects were grouped into MCI stable and MCI to probable Alzheimer's disease (AD) converters according to follow-up diagnoses at 12, 24, and 36 months. Hippocampal grey matter volume (HGMV) was obtained from baseline T1-weighted MRI and then corrected for total intracranial volume and age. Average processing time per subject was less than 4 minutes on a standard PC. The area under the receiver operator characteristic curve of the corrected HGMV for identification of MCI to probable AD converters within 12, 24, and 36 months was 0.78, 0.72, and 0.71, respectively. Thus, hippocampal volume computed with the fully-automated processing pipeline provides similar power for prediction of MCI to probable AD conversion as computationally more expensive methods. The whole processing pipeline has been made freely available as an SPM8 toolbox. It is easily set up and integrated into everyday clinical patient care.

Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

PubMed

Hu, Xiaotang; Li, Hongbin

2014-10-01

Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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.

SBEToolbox: A Matlab Toolbox for Biological Network Analysis

PubMed Central

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J.

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases. PMID:24027418

SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

PubMed

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.

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...

N-Way FRET Microscopy of Multiple Protein-Protein Interactions in Live Cells

PubMed Central

Hoppe, Adam D.; Scott, Brandon L.; Welliver, Timothy P.; Straight, Samuel W.; Swanson, Joel A.

2013-01-01

Fluorescence Resonance Energy Transfer (FRET) microscopy has emerged as a powerful tool to visualize nanoscale protein-protein interactions while capturing their microscale organization and millisecond dynamics. Recently, FRET microscopy was extended to imaging of multiple donor-acceptor pairs, thereby enabling visualization of multiple biochemical events within a single living cell. These methods require numerous equations that must be defined on a case-by-case basis. Here, we present a universal multispectral microscopy method (N-Way FRET) to enable quantitative imaging for any number of interacting and non-interacting FRET pairs. This approach redefines linear unmixing to incorporate the excitation and emission couplings created by FRET, which cannot be accounted for in conventional linear unmixing. Experiments on a three-fluorophore system using blue, yellow and red fluorescent proteins validate the method in living cells. In addition, we propose a simple linear algebra scheme for error propagation from input data to estimate the uncertainty in the computed FRET images. We demonstrate the strength of this approach by monitoring the oligomerization of three FP-tagged HIV Gag proteins whose tight association in the viral capsid is readily observed. Replacement of one FP-Gag molecule with a lipid raft-targeted FP allowed direct observation of Gag oligomerization with no association between FP-Gag and raft-targeted FP. The N-Way FRET method provides a new toolbox for capturing multiple molecular processes with high spatial and temporal resolution in living cells. PMID:23762252

Optimal reproducibility of gated sestamibi and thallium myocardial perfusion study left ventricular ejection fractions obtained on a solid-state CZT cardiac camera requires operator input.

PubMed

Cherk, Martin H; Ky, Jason; Yap, Kenneth S K; Campbell, Patrina; McGrath, Catherine; Bailey, Michael; Kalff, Victor

2012-08-01

To evaluate the reproducibility of serial re-acquisitions of gated Tl-201 and Tc-99m sestamibi left ventricular ejection fraction (LVEF) measurements obtained on a new generation solid-state cardiac camera system during myocardial perfusion imaging and the importance of manual operator optimization of left ventricular wall tracking. Resting blinded automated (auto) and manual operator optimized (opt) LVEF measurements were measured using ECT toolbox (ECT) and Cedars-Sinai QGS software in two separate cohorts of 55 Tc-99m sestamibi (MIBI) and 50 thallium (Tl-201) myocardial perfusion studies (MPS) acquired in both supine and prone positions on a cadmium zinc telluride (CZT) solid-state camera system. Resting supine and prone automated LVEF measurements were similarly obtained in a further separate cohort of 52 gated cardiac blood pool scans (GCBPS) for validation of methodology and comparison. Appropriate use of Bland-Altman, chi-squared and Levene's equality of variance tests was used to analyse the resultant data comparisons. For all radiotracer and software combinations, manual checking and optimization of valve planes (+/- centre radius with ECT software) resulted in significant improvement in MPS LVEF reproducibility that approached that of planar GCBPS. No difference was demonstrated between optimized MIBI/Tl-201 QGS and planar GCBPS LVEF reproducibility (P = .17 and P = .48, respectively). ECT required significantly more manual optimization compared to QGS software in both supine and prone positions independent of radiotracer used (P < .02). Reproducibility of gated sestamibi and Tl-201 LVEF measurements obtained during myocardial perfusion imaging with ECT toolbox or QGS software packages using a new generation solid-state cardiac camera with improved image quality approaches that of planar GCBPS however requires visual quality control and operator optimization of left ventricular wall tracking for best results. Using this superior cardiac technology, Tl-201 reproducibility also appears at least equivalent to sestamibi for measuring LVEF.

Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration

PubMed Central

Klein, Arno; Andersson, Jesper; Ardekani, Babak A.; Ashburner, John; Avants, Brian; Chiang, Ming-Chang; Christensen, Gary E.; Collins, D. Louis; Gee, James; Hellier, Pierre; Song, Joo Hyun; Jenkinson, Mark; Lepage, Claude; Rueckert, Daniel; Thompson, Paul; Vercauteren, Tom; Woods, Roger P.; Mann, J. John; Parsey, Ramin V.

2009-01-01

All fields of neuroscience that employ brain imaging need to communicate their results with reference to anatomical regions. In particular, comparative morphometry and group analysis of functional and physiological data require coregistration of brains to establish correspondences across brain structures. It is well established that linear registration of one brain to another is inadequate for aligning brain structures, so numerous algorithms have emerged to nonlinearly register brains to one another. This study is the largest evaluation of nonlinear deformation algorithms applied to brain image registration ever conducted. Fourteen algorithms from laboratories around the world are evaluated using 8 different error measures. More than 45,000 registrations between 80 manually labeled brains were performed by algorithms including: AIR, ANIMAL, ART, Diffeomorphic Demons, FNIRT, IRTK, JRD-fluid, ROMEO, SICLE, SyN, and four different SPM5 algorithms (“SPM2-type” and regular Normalization, Unified Segmentation, and the DARTEL Toolbox). All of these registrations were preceded by linear registration between the same image pairs using FLIRT. One of the most significant findings of this study is that the relative performances of the registration methods under comparison appear to be little affected by the choice of subject population, labeling protocol, and type of overlap measure. This is important because it suggests that the findings are generalizable to new subject populations that are labeled or evaluated using different labeling protocols. Furthermore, we ranked the 14 methods according to three completely independent analyses (permutation tests, one-way ANOVA tests, and indifference-zone ranking) and derived three almost identical top rankings of the methods. ART, SyN, IRTK, and SPM's DARTEL Toolbox gave the best results according to overlap and distance measures, with ART and SyN delivering the most consistently high accuracy across subjects and label sets. Updates will be published on the http://www.mindboggle.info/papers/ website. PMID:19195496

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.

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...

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...

Integrating model behavior, optimization, and sensitivity/uncertainty analysis: overview and application of the MOUSE software toolbox

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) software application, an open-source, Java-based toolbox of visual and numerical analysis components for the evaluation of environmental models. MOUSE is based on the OPTAS model calibration syst...

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…

WE-G-18C-07: Accelerated Water/fat Separation in MRI for Radiotherapy Planning Using Multi-Band Imaging Techniques

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

Crijns, S; Stemkens, B; Sbrizzi, A

Purpose: Dixon sequences are used to characterize disease processes, obtain good fat or water separation in cases where fat suppression fails and to obtain pseudo-CT datasets. Dixon's method uses at least two images acquired with different echo times and thus requires prolonged acquisition times. To overcome associated problems (e.g., for DCE/cine-MRI), we propose to use a method for water/fat separation based on spectrally selective RF pulses. Methods: Two alternating RF pulses were used, that imposes a fat selective phase cycling over the phase encoding lines, which results in a spatial shift for fat in the reconstructed image, identical to thatmore » in CAIPIRINHA. Associated aliasing artefacts were resolved using the encoding power of a multi-element receiver array, analogous to SENSE. In vivo measurements were performed on a 1.5T clinical MR-scanner in a healthy volunteer's legs, using a four channel receiver coil. Gradient echo images were acquired with TE/TR = 2.3/4.7ms, flip angle 20°, FOV 45×22.5cm{sup 2}, matrix 480×216, slice thickness 5mm. Dixon images were acquired with TE,1/TE,2/TR=2.2/4.6/7ms. All image reconstructions were done in Matlab using the ReconFrame toolbox (Gyrotools, Zurich, CH). Results: RF pulse alternation yields a fat image offset from the water image. Hence the water and fat images fold over, which is resolved using in-plane SENSE reconstruction. Using the proposed technique, we achieved excellent water/fat separation comparable to Dixon images, while acquiring images at only one echo time. Conclusion: The proposed technique yields both inphase water and fat images at arbitrary echo times and requires only one measurement, thereby shortening the acquisition time by a factor 2. In future work the technique may be extended to a multi-band water/fat separation sequence that is able to achieve single point water/fat separation in multiple slices at once and hence yields higher speed-up factors.« less

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.

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

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

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.

Silk fibroin as biomaterial for bone tissue engineering.

PubMed

Melke, Johanna; Midha, Swati; Ghosh, Sourabh; Ito, Keita; Hofmann, Sandra

2016-02-01

Silk fibroin (SF) is a fibrous protein which is produced mainly by silkworms and spiders. Its unique mechanical properties, tunable biodegradation rate and the ability to support the differentiation of mesenchymal stem cells along the osteogenic lineage, have made SF a favorable scaffold material for bone tissue engineering. SF can be processed into various scaffold forms, combined synergistically with other biomaterials to form composites and chemically modified, which provides an impressive toolbox and allows SF scaffolds to be tailored to specific applications. This review discusses and summarizes recent advancements in processing SF, focusing on different fabrication and functionalization methods and their application to grow bone tissue in vitro and in vivo. Potential areas for future research, current challenges, uncertainties and gaps in knowledge are highlighted. Silk fibroin is a natural biomaterial with remarkable biomedical and mechanical properties which make it favorable for a broad range of bone tissue engineering applications. It can be processed into different scaffold forms, combined synergistically with other biomaterials to form composites and chemically modified which provides a unique toolbox and allows silk fibroin scaffolds to be tailored to specific applications. This review discusses and summarizes recent advancements in processing silk fibroin, focusing on different fabrication and functionalization methods and their application to grow bone tissue in vitro and in vivo. Potential areas for future research, current challenges, uncertainties and gaps in knowledge are highlighted. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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…

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

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

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.

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.

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.

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.

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.

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.

Reconstruction and downscaling of Eastern Mediterranean OSCAR satellite surface current data using DINEOF

NASA Astrophysics Data System (ADS)

Nikolaidis, Andreas; Stylianou, Stavros; Georgiou, Georgios; Hajimitsis, Diofantos; Gravanis, Elias; Akylas, Evangelos

2015-04-01

During the last decade, Rixen (2005) and Alvera-Azkarate (2010) presented the DINEOF (Data Interpolating Empirical Orthogonal Functions) method, a EOF-based technique to reconstruct missing data in satellite images. The application of DINEOF method, proved to provide relative success in various experimental trials (Wang and Liu, 2013; Nikolaidis et al., 2013;2014), and tends to be an effective and computationally affordable solution, on the problem of data reconstruction, for missing data from geophysical fields, such as chlorophyll-a, sea surface temperatures or salinity and geophysical fields derived from satellite data. Implementation of this method in a GIS system will provide with a more complete, integrated approach, permitting the expansion of the applicability over various aspects. This may be especially useful in studies where various data of different kind, have to be examined. For this purpose, in this study we have implemented and present a GIS toolbox that aims to automate the usage of the algorithm, incorporating the DINEOF codes provided by GHER (GeoHydrodynamics and Environment Research Group of University of Liege) into the ArcGIS®. ArcGIS® is a well known standard on Geographical Information Systems, used over the years for various remote sensing procedures, in sea and land environment alike. A case-study of filling the missing satellite derived current data in the Eastern Mediterranean Sea area, for a monthly period is analyzed, as an example for the effectiveness and simplicity of the usage of this toolbox. The specific study focuses to OSCAR satellite data (http://www.oscar.noaa.gov/) collected by NOAA/NESDIS Operational Surface Current Processing and Data Center, from the respective products of OSCAR Project Office Earth and Space Research organization, that provides free online access to unfiltered (1/3 degree) resolution. All the 5-day mean products data coverage were successfully reconstructed. KEY WORDS: Remote Sensing, Cyprus, Mediterranean, DINEOF, ArcGIS, data reconstruction.

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.

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).

Basic Radar Altimetry Toolbox: Tools and Tutorial to Use Cryosat Data

NASA Astrophysics Data System (ADS)

Benveniste, J.; Bronner, E.; Dinardo, S.; Lucas, B. M.; Rosmorduc, V.; Earith, D.; Niemeijer, S.

2011-12-01

Radar altimetry is very much a technique expanding its applications. Even If quite a lot of effort has been invested for oceanography users, the use of Altimetry data for cryosphere application, especially with the new ESA CryoSat-2 mission data is still somehow tedious for new Altimetry data products users. ESA and CNES therfore developed the Basic Radar Altimetry Toolbox a few years ago, and are improving and upgrading it to fit new missions and the growing number of altimetry uses. The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data. The software is able: - to read most distributed radar altimetry data, from ERS-1 & 2, Topex/Poseidon, Geosat Follow-on, Jason-1, Envisat, Jason- 2, CryoSat, the future Saral missions and is ready for adaptation to Sentinel-3 products - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways: - as a data reading tool, with APIs for C, Fortran, Matlab and IDL - as processing/extraction routines, through the on-line command mode - as an educational and a quick-look tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. It is an opportunity to teach remote sensing with practical training. It has been available since April 2007, and had been demonstrated during training courses and scientific meetings. About 2000 people downloaded it (Summer 2011), with many "newcomers" to altimetry among them, including teachers and professors, worldwide. Users' feedback, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in the recent version release (v3.0.1). Others are in discussion for future development. Data use cases on CryoSat data use will be presented. BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/

Dust Tsunamis, Blackouts and 50 deg C: Teaching MATLAB in East Africa

NASA Astrophysics Data System (ADS)

Trauth, M. H.

2016-12-01

MATLAB is the tool of choice when analyzing earth and environmental data from East Africa. The software and companion toolboxes helps to process satellite images and digital elevation models, to detect trends, cycles, and recurrent, characteristic types of climate transitions in climate time series, and to model the hydrological balance of ancient lakes. The advantage of MATLAB is that the user can do many different types of analyses with the same software, making the software very attractive for young scientists at African universities. Since 2009 we are organizing summer schools on the subject of data analysis with various tools including MATLAB in Ethiopia, Kenya and Tanzania. Throughout the summerschool, participants are instructed by teams of senior researchers, together with young scientists, some of which were participants of an earlier summerschool. The participants are themselves integrated in teaching, depending on previous knowledge, so that the boundary between teachers and learners constantly shifts or even dissolves. From the extraordinarily positive experience, but also the difficulties in teaching data analysis methods with MATLAB in East Africa is reported.

The Study of Imperfection in Rough Set on the Field of Engineering and Education

NASA Astrophysics Data System (ADS)

Sheu, Tian-Wei; Liang, Jung-Chin; You, Mei-Li; Wen, Kun-Li

Based on the characteristic of rough set, rough set theory overlaps with many other theories, especially with fuzzy set theory, evidence theory and Boolean reasoning methods. And the rough set methodology has found many real-life applications, such as medical data analysis, finance, banking, engineering, voice recognition, image processing and others. Till now, there is rare research associating to this issue in the imperfection of rough set. Hence, the main purpose of this paper is to study the imperfection of rough set in the field of engineering and education. First of all, we preview the mathematics model of rough set, and a given two examples to enhance our approach, which one is the weighting of influence factor in muzzle noise suppressor, and the other is the weighting of evaluation factor in English learning. Third, we also apply Matlab to develop a complete human-machine interface type of toolbox in order to support the complex calculation and verification the huge data. Finally, some further suggestions are indicated for the research in the future.

Indexing amyloid peptide diffraction from serial femtosecond crystallography: New algorithms for sparse patterns

DOE PAGES

Brewster, Aaron S.; Sawaya, Michael R.; Rodriguez, Jose; ...

2015-01-23

Still diffraction patterns from peptide nanocrystals with small unit cells are challenging to index using conventional methods owing to the limited number of spots and the lack of crystal orientation information for individual images. New indexing algorithms have been developed as part of the Computational Crystallography Toolbox( cctbx) to overcome these challenges. Accurate unit-cell information derived from an aggregate data set from thousands of diffraction patterns can be used to determine a crystal orientation matrix for individual images with as few as five reflections. These algorithms are potentially applicable not only to amyloid peptides but also to any set ofmore » diffraction patterns with sparse properties, such as low-resolution virus structures or high-throughput screening of still images captured by raster-scanning at synchrotron sources. As a proof of concept for this technique, successful integration of X-ray free-electron laser (XFEL) data to 2.5 Å resolution for the amyloid segment GNNQQNY from the Sup35 yeast prion is presented.« less

Far-field nanoscopy on a semiconductor quantum dot via a rapid-adiabatic-passage-based switch

NASA Astrophysics Data System (ADS)

Kaldewey, Timo; Kuhlmann, Andreas V.; Valentin, Sascha R.; Ludwig, Arne; Wieck, Andreas D.; Warburton, Richard J.

2018-02-01

The diffraction limit prevents a conventional optical microscope from imaging at the nanoscale. However, nanoscale imaging of molecules is possible by exploiting an intensity-dependent molecular switch1-3. This switch is translated into a microscopy scheme, stimulated emission depletion microscopy4-7. Variants on this scheme exist3,8-13, yet all exploit an incoherent response to the lasers. We present a scheme that relies on a coherent response to a laser. Quantum control of a two-level system proceeds via rapid adiabatic passage, an ideal molecular switch. We implement this scheme on an ensemble of quantum dots. Each quantum dot results in a bright spot in the image with extent down to 30 nm (λ/31). There is no significant loss of intensity with respect to confocal microscopy, resulting in a factor of 10 improvement in emitter position determination. The experiments establish rapid adiabatic passage as a versatile tool in the super-resolution toolbox.

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.

Reliability and Validity of Composite Scores from the NIH Toolbox Cognition Battery in Adults

PubMed Central

Heaton, Robert K.; Akshoomoff, Natacha; Tulsky, David; Mungas, Dan; Weintraub, Sandra; Dikmen, Sureyya; Beaumont, Jennifer; Casaletto, Kaitlin B.; Conway, Kevin; Slotkin, Jerry; Gershon, Richard

2014-01-01

This study describes psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) Composite Scores in an adult sample. The NIHTB-CB was designed for use in epidemiologic studies and clinical trials for ages 3 to 85. A total of 268 self-described healthy adults were recruited at four university-based sites, using stratified sampling guidelines to target demographic variability for age (20–85 years), gender, education, and ethnicity. The NIHTB-CB contains seven computer-based instruments assessing five cognitive sub-domains: Language, Executive Function, Episodic Memory, Processing Speed, and Working Memory. Participants completed the NIHTB-CB, corresponding gold standard validation measures selected to tap the same cognitive abilities, and sociodemographic questionnaires. Three Composite Scores were derived for both the NIHTB-CB and gold standard batteries: “Crystallized Cognition Composite,” “Fluid Cognition Composite,” and “Total Cognition Composite” scores. NIHTB Composite Scores showed acceptable internal consistency (Cronbach’s alphas = 0.84 Crystallized, 0.83 Fluid, 0.77 Total), excellent test–retest reliability (r: 0.86–0.92), strong convergent (r: 0.78–0.90) and discriminant (r: 0.19–0.39) validities versus gold standard composites, and expected age effects (r = 0.18 crystallized, r = − 0.68 fluid, r = − 0.26 total). Significant relationships with self-reported prior school difficulties and current health status, employment, and presence of a disability provided evidence of external validity. The NIH Toolbox Cognition Battery Composite Scores have excellent reliability and validity, suggesting they can be used effectively in epidemiologic and clinical studies. PMID:24960398

MTpy: A Python toolbox for magnetotellurics

USGS Publications Warehouse

Krieger, Lars; Peacock, Jared R.

2014-01-01

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.

DIRT: Dust InfraRed Toolbox

NASA Astrophysics Data System (ADS)

Pound, Marc W.; Wolfire, Mark G.; Mundy, Lee G.; Teuben, Peter; Lord, Steve

2011-02-01

DIRT is a Java applet for modelling astrophysical processes in circumstellar dust shells around young and evolved stars. With DIRT, you can: select and display over 500,000 pre-run model spectral energy distributions (SEDs) find the best-fit model to your data set account for beam size in model fitting manipulate data and models with an interactive viewer display gas and dust density and temperature profiles display model intensity profiles at various wavelengths

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.

Super-resolution photoacoustic microscopy using a localized near-field of a plasmonic nanoaperture: a three-dimensional simulation study

NASA Astrophysics Data System (ADS)

Park, Byullee; Lee, Hongki; Upputuri, Paul Kumar; Pramanik, Manojit; Kim, Donghyun; Kim, Chulhong

2018-02-01

Super-resolution microscopy has been increasingly important to delineate nanoscale biological structures or nanoparticles. With these increasing demands, several imaging modalities, including super-resolution fluorescence microscope (SRFM) and electron microscope (EM), have been developed and commercialized. These modalities achieve nanoscale resolution, however, SRFM cannot image without fluorescence, and sample preparation of EM is not suitable for biological specimens. To overcome those disadvantages, we have numerically studied the possibility of superresolution photoacoustic microscopy (SR-PAM) based on near-field localization of light. Photoacoustic (PA) signal is generally acquired based on optical absorption contrast; thus it requires no agents or pre-processing for the samples. The lateral resolution of the conventional photoacoustic microscopy is limited to 200 nm by diffraction limit, therefore reducing the lateral resolution is a major research impetus. Our approach to breaking resolution limit is to use laser pulses of extremely small spot size as a light source. In this research, we simulated the PA signal by constructing the three dimensional SR-PAM system environment using the k-Wave toolbox. As the light source, we simulated ultrashort light pulses using geometrical nanoaperture with near-field localization of surface plasmons. Through the PA simulation, we have successfully distinguish cuboids spaced 3 nm apart. In the near future, we will develop the SR-PAM and it will contribute to biomedical and material sciences.

Motion artifacts in MRI: A complex problem with many partial solutions.

PubMed

Zaitsev, Maxim; Maclaren, Julian; Herbst, Michael

2015-10-01

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations. © 2015 Wiley Periodicals, Inc.

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.

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),

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.

A sigma factor toolbox for orthogonal gene expression in Escherichia coli

PubMed Central

Van Brempt, Maarten; Van Nerom, Katleen; Van Hove, Bob; Maertens, Jo; De Mey, Marjan; Charlier, Daniel

2018-01-01

Abstract Synthetic genetic sensors and circuits enable programmable control over timing and conditions of gene expression and, as a result, are increasingly incorporated into the control of complex and multi-gene pathways. Size and complexity of genetic circuits are growing, but stay limited by a shortage of regulatory parts that can be used without interference. Therefore, orthogonal expression and regulation systems are needed to minimize undesired crosstalk and allow for dynamic control of separate modules. This work presents a set of orthogonal expression systems for use in Escherichia coli based on heterologous sigma factors from Bacillus subtilis that recognize specific promoter sequences. Up to four of the analyzed sigma factors can be combined to function orthogonally between each other and toward the host. Additionally, the toolbox is expanded by creating promoter libraries for three sigma factors without loss of their orthogonal nature. As this set covers a wide range of transcription initiation frequencies, it enables tuning of multiple outputs of the circuit in response to different sensory signals in an orthogonal manner. This sigma factor toolbox constitutes an interesting expansion of the synthetic biology toolbox and may contribute to the assembly of more complex synthetic genetic systems in the future. PMID:29361130

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.

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

From black box to toolbox: Outlining device functionality, engagement activities, and the pervasive information architecture of mHealth interventions.

PubMed

Danaher, Brian G; Brendryen, Håvar; Seeley, John R; Tyler, Milagra S; Woolley, Tim

2015-03-01

mHealth interventions that deliver content via mobile phones represent a burgeoning area of health behavior change. The current paper examines two themes that can inform the underlying design of mHealth interventions: (1) mobile device functionality, which represents the technological toolbox available to intervention developers; and (2) the pervasive information architecture of mHealth interventions, which determines how intervention content can be delivered concurrently using mobile phones, personal computers, and other devices. We posit that developers of mHealth interventions will be better able to achieve the promise of this burgeoning arena by leveraging the toolbox and functionality of mobile devices in order to engage participants and encourage meaningful behavior change within the context of a carefully designed pervasive information architecture.

Near Real Time Ship Detection Experiments

NASA Astrophysics Data System (ADS)

Brusch, S.; Lehner, S.; Schwarz, E.; Fritz, T.

2010-04-01

A new Near Real Time (NRT) ship detection processor SAINT (SAR AIS Integrated Toolbox) was developed in the framework of the ESA project MARISS. Data are received at DLRs ground segment DLR-BN (Neustrelitz, Germany). Results of the ship detection are available on ftp server within 30 min after the acquisition started. The detectability of ships on Synthetic Aperture Radar (SAR) ERS-2, ENVISAT ASAR and TerraSAR-X (TS-X) images is validated by coastal (live) AIS and space AIS. The monitoring areas chosen for surveillance are the North-, Baltic Sea, and Cape Town. The detectability in respect to environmental parameters like wind field, sea state, currents and changing coastlines due to tidal effects is investigated. In the South Atlantic a tracking experiment of the German research vessel Polarstern has been performed. Issues of piracy in particular in respect to ships hijacked at the Somali coast are discussed. Some examples using high resolution images from TerraSAR-X are given.

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

Applications of a morphological scene change detection (MSCD) for visual leak and failure identification in process and chemical engineering

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Harvey, Paul K.; Smith, Jeremy S.

2010-10-01

Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. The additional ability to set up the system in virtually any location due to the FPGA makes it ideal for insertion into an autonomous mobile robot for patrol duties. However, security is not the only potential of this robust algorithm. This paper details how such a system can be used for the detection of leaks in piping for use in the process and chemical industries and could be deployed as stated in the above manner. The test substance in this work was water, which was pumped either as a liquid or as low pressure steam through a simple pipe configuration with holes at set points to simulate the leaks. These holes were situated randomly at either the center of a pipe (in order to simulate an impact to it) or at a joint or corner (to simulate a failed weld). Imagery of the resultant leaks, which were visualised as drips or the accumulation of steam, which where analysed using MATLAB to determine their pixel volume in order to calibrate the trigger for the MSCD. The triggering mechanism is adaptive to make it possible in theory for the type of leak to be determined by the number of pixels in the threshold of the image and a numerical output signal to state which of the leak situations is being observed. The system was designed using the DSP Builder package from Altera so that its graphical nature is easily comprehensible to the non-embedded system designer. Furthermore, all the data from the DSP Builder simulation underwent verification against MATLAB comparisons using the image processing toolbox in order to validate the results.

Novel 1:1 labeling and purification process for C-terminal thioester and single cysteine recombinant proteins using generic peptidic toolbox reagents.

PubMed

Portal, Christophe F; Seifert, Jan-Marcus; Buehler, Christof; Meisner-Kober, Nicole-Claudia; Auer, Manfred

2014-07-16

We developed a versatile set of chemical labeling reagents which allow dye ligation to the C-terminus of a protein or a single internal cysteine and target purification in a simple two-step process. This simple process results in a fully 1:1 labeled conjugate suitable for all quantitative fluorescence spectroscopy and imaging experiments. We refer to a "generic labeling toolbox" because of the flexibility to choose one of many available dyes, spacers of different lengths and compositions which increase the target solubility, a variety of affinity purification tags, and different cleavage chemistries to release the 1:1 labeled proteins. Studying protein function in vitro or in the context of live cells and organisms is of vital importance in biological research. Although label free detection technologies gain increasing interest in molecular recognition science, fluorescence spectroscopy is still the most often used detection technique for assays and screens both in academic as well as in industrial groups. For generations, fluorescence spectroscopists have labeled their proteins of interest with small fluorescent dyes by random chemical linking on the proteins' exposed lysines and cysteines. Chemical reactions with a certain excess of activated esters or maleimides of longer wavelength dyes hardly ever result in quantitative labeling of the target protein. Most of the time, more than one exposed amino acid side chain reacts. This results in a mixture of dye-protein complexes of different labeling stoichiometries and labeling sites. Only mass spectrometry allows resolving the precise chemical composition of the conjugates. In "classical" ensemble averaging fluorescent experiments, these labeled proteins are still useful, and quantification of, e.g., ligand binding experiments, is achieved via knowledge of the overall protein concentration and a fluorescent signal change which is proportional to the amount of complex formed. With the development of fluorescence fluctuation analysis techniques working at single molecule resolution, like fluorescence correlation spectroscopy (FCS), fluorescence cross correlation spectroscopy (FCCS), fluorescence intensity diffusion analysis (FIDA), etc., it became important to work with homogeneously labeled target proteins. Each molecule participating in a binding equilibrium should be detectable when it freely fluctuates through the confocal focus of a microscope. The measured photon burst for each transition contains information about the size and the stoichiometry of a protein complex. Therefore, it is important to work with reagents that contain an exact number of tracers per protein at identical positions. The ideal fluorescent tracer-protein complex stoichiometry is 1:1. While genetic tags such as fluorescent proteins (FPs) are widely used to detect proteins, FPs have several limitations compared to chemical tags. For example, FPs cannot easily compete with organic dyes in the flexibility of modification and spectral range; moreover, FPs have disadvantages in brightness and photostability and are therefore not ideal for most biochemical single molecule studies. We present the synthesis of a series of exemplaric toolbox reagents and labeling results on three target proteins which were needed for high throughput screening experiments using fluorescence fluctuation analysis at single molecule resolution. On one target, Hu-antigen R (HuR), we demonstrated the activity of the 1:1 labeled protein in ribonucleic acid (RNA) binding, and the ease of resolving the stoichiometry of an RNA-HuR complex using the same dye on protein and RNA by Fluorescence Intensity Multiple Distribution Analysis (FIMDA) detection.

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.

Morphological spot counting from stacked images for automated analysis of gene copy numbers by fluorescence in situ hybridization.

PubMed

Grigoryan, Artyom M; Dougherty, Edward R; Kononen, Juha; Bubendorf, Lukas; Hostetter, Galen; Kallioniemi, Olli

2002-01-01

Fluorescence in situ hybridization (FISH) is a molecular diagnostic technique in which a fluorescent labeled probe hybridizes to a target nucleotide sequence of deoxyribose nucleic acid. Upon excitation, each chromosome containing the target sequence produces a fluorescent signal (spot). Because fluorescent spot counting is tedious and often subjective, automated digital algorithms to count spots are desirable. New technology provides a stack of images on multiple focal planes throughout a tissue sample. Multiple-focal-plane imaging helps overcome the biases and imprecision inherent in single-focal-plane methods. This paper proposes an algorithm for global spot counting in stacked three-dimensional slice FISH images without the necessity of nuclei segmentation. It is designed to work in complex backgrounds, when there are agglomerated nuclei, and in the presence of illumination gradients. It is based on the morphological top-hat transform, which locates intensity spikes on irregular backgrounds. After finding signals in the slice images, the algorithm groups these together to form three-dimensional spots. Filters are employed to separate legitimate spots from fluorescent noise. The algorithm is set in a comprehensive toolbox that provides visualization and analytic facilities. It includes simulation software that allows examination of algorithm performance for various image and algorithm parameter settings, including signal size, signal density, and the number of slices.

Synthesis and Live-Cell Imaging of Fluorescent Sterols for Analysis of Intracellular Cholesterol Transport.

PubMed

Modzel, Maciej; Lund, Frederik W; Wüstner, Daniel

2017-01-01

Cellular cholesterol homeostasis relies on precise control of the sterol content of organelle membranes. Obtaining insight into cholesterol trafficking pathways and kinetics by live-cell imaging relies on two conditions. First, one needs to develop suitable analogs that resemble cholesterol as closely as possible with respect to their biophysical and biochemical properties. Second, the cholesterol analogs should have good fluorescence properties. This interferes, however, often with the first requirement, such that the imaging instrumentation must be optimized to collect photons from suboptimal fluorophores, but good cholesterol mimics, such as the intrinsically fluorescent sterols, cholestatrienol (CTL) or dehydroergosterol (DHE). CTL differs from cholesterol only in having two additional double bonds in the ring system, which is why it is slightly fluorescent in the ultraviolet (UV). In the first part of this protocol, we describe how to synthesize and image CTL in living cells relative to caveolin, a structural component of caveolae. In the second part, we explain in detail how to perform time-lapse experiments of commercially available BODIPY-tagged cholesterol (TopFluor-cholesterol ® ; TF-Chol) in comparison to DHE. Finally, using two-photon time-lapse imaging data of TF-Chol, we demonstrate how to use our imaging toolbox SpatTrack for tracking sterol rich vesicles in living cells over time.

Toolbox No. 2: Expanding the Role of Foster Parents in Achieving Permanency. Toolboxes for Permanency.

ERIC Educational Resources Information Center

Dougherty, Susan

Noting that over the last decade, the role of a foster parent has evolved from temporary caregiver to essential part of a professional team in determining the best long-term plan for children in their care, this guide focuses on practical ways in which best child welfare practice can be incorporated into the recruitment, training, and support of…

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.