Green Chemistry Metrics with Special Reference to Green Analytical Chemistry.

PubMed

Tobiszewski, Marek; Marć, Mariusz; Gałuszka, Agnieszka; Namieśnik, Jacek

2015-06-12

The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

NASA Technical Reports Server (NTRS)

Gray, Justin; Chin, Jeffrey; Hearn, Tristan; Hendricks, Eric; Lavelle, Thomas; Martins, Joaquim R. R. A.

2016-01-01

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

In-flight Evaluation of Aerodynamic Predictions of an Air-launched Space Booster

NASA Technical Reports Server (NTRS)

Curry, Robert E.; Mendenhall, Michael R.; Moulton, Bryan

1992-01-01

Several analytical aerodynamic design tools that were applied to the Pegasus (registered trademark) air-launched space booster were evaluated using flight measurements. The study was limited to existing codes and was conducted with limited computational resources. The flight instrumentation was constrained to have minimal impact on the primary Pegasus missions. Where appropriate, the flight measurements were compared with computational data. Aerodynamic performance and trim data from the first two flights were correlated with predictions. Local measurements in the wing and wing-body interference region were correlated with analytical data. This complex flow region includes the effect of aerothermal heating magnification caused by the presence of a corner vortex and interaction of the wing leading edge shock and fuselage boundary layer. The operation of the first two missions indicates that the aerodynamic design approach for Pegasus was adequate, and data show that acceptable margins were available. Additionally, the correlations provide insight into the capabilities of these analytical tools for more complex vehicles in which the design margins may be more stringent.

In-flight evaluation of aerodynamic predictions of an air-launched space booster

NASA Technical Reports Server (NTRS)

Curry, Robert E.; Mendenhall, Michael R.; Moulton, Bryan

1993-01-01

Several analytical aerodynamic design tools that were applied to the Pegasus air-launched space booster were evaluated using flight measurements. The study was limited to existing codes and was conducted with limited computational resources. The flight instrumentation was constrained to have minimal impact on the primary Pegasus missions. Where appropriate, the flight measurements were compared with computational data. Aerodynamic performance and trim data from the first two flights were correlated with predictions. Local measurements in the wing and wing-body interference region were correlated with analytical data. This complex flow region includes the effect of aerothermal heating magnification caused by the presence of a corner vortex and interaction of the wing leading edge shock and fuselage boundary layer. The operation of the first two missions indicates that the aerodynamic design approach for Pegasus was adequate, and data show that acceptable margins were available. Additionally, the correlations provide insight into the capabilities of these analytical tools for more complex vehicles in which design margins may be more stringent.

Investigating Analytic Tools for e-Book Design in Early Literacy Learning

ERIC Educational Resources Information Center

Roskos, Kathleen; Brueck, Jeremy; Widman, Sarah

2009-01-01

Toward the goal of better e-book design to support early literacy learning, this study investigates analytic tools for examining design qualities of e-books for young children. Three research-based analytic tools related to e-book design were applied to a mixed genre collection of 50 e-books from popular online sites. Tool performance varied…

Ultra High-Resolution Electrospray Ionization/Ion Mobility Spectrometer System for In-Situ Detection of Organic Compounds

NASA Technical Reports Server (NTRS)

Kanik, I.; Beegle, L. W.; Hill, H. H.

2001-01-01

The potential of the high-resolution Electrospray Ionization/Ion Mobility Spectrometry (ESI/IMS) technique as analytical separation tool in analyzing bio-molecular mixtures in the search for the chemical signatures of life is demonstrated. Additional information is contained in the original extended abstract.

New Analytical Monographs on TCM Herbal Drugs for Quality Proof.

PubMed

Wagner, Hildebert; Bauer, Rudolf; Melchart, Dieter

2016-01-01

Regardless of specific national drug regulations there is an international consensus that all TCM drugs must meet stipulated high quality standards focusing on authentication, identification and chemical composition. In addition, safety of all TCM drugs prescribed by physicians has to be guaranteed. During the 25 years history of the TCM hospital Bad Kötzting, 171 TCM drugs underwent an analytical quality proof including thin layer as well as high pressure liquid chromatography. As from now mass spectroscopy will also be available as analytical tool. The findings are compiled and already published in three volumes of analytical monographs. One more volume will be published shortly, and a fifth volume is in preparation. The main issues of the analytical procedure in TCM drugs like authenticity, botanical nomenclature, variability of plant species and parts as well as processing are pointed out and possible ways to overcome them are sketched. © 2016 S. Karger GmbH, Freiburg.

Recombinant drugs-on-a-chip: The usage of capillary electrophoresis and trends in miniaturized systems - A review.

PubMed

Morbioli, Giorgio Gianini; Mazzu-Nascimento, Thiago; Aquino, Adriano; Cervantes, Cesar; Carrilho, Emanuel

2016-09-07

We present here a critical review covering conventional analytical tools of recombinant drug analysis and discuss their evolution towards miniaturized systems foreseeing a possible unique recombinant drug-on-a-chip device. Recombinant protein drugs and/or pro-drug analysis require sensitive and reproducible analytical techniques for quality control to ensure safety and efficacy of drugs according to regulatory agencies. The versatility of miniaturized systems combined with their low-cost could become a major trend in recombinant drugs and bioprocess analysis. Miniaturized systems are capable of performing conventional analytical and proteomic tasks, allowing for interfaces with other powerful techniques, such as mass spectrometry. Microdevices can be applied during the different stages of recombinant drug processing, such as gene isolation, DNA amplification, cell culture, protein expression, protein separation, and analysis. In addition, organs-on-chips have appeared as a viable alternative to testing biodrug pharmacokinetics and pharmacodynamics, demonstrating the capabilities of the miniaturized systems. The integration of individual established microfluidic operations and analytical tools in a single device is a challenge to be overcome to achieve a unique recombinant drug-on-a-chip device. Copyright © 2016 Elsevier B.V. All rights reserved.

33 CFR 385.33 - Revisions to models and analytical tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Management District, and other non-Federal sponsors shall rely on the best available science including models..., and assessment of projects. The selection of models and analytical tools shall be done in consultation... system-wide simulation models and analytical tools used in the evaluation and assessment of projects, and...

Developing Healthcare Data Analytics APPs with Open Data Science Tools.

PubMed

Hao, Bibo; Sun, Wen; Yu, Yiqin; Xie, Guotong

2017-01-01

Recent advances in big data analytics provide more flexible, efficient, and open tools for researchers to gain insight from healthcare data. Whilst many tools require researchers to develop programs with programming languages like Python, R and so on, which is not a skill set grasped by many researchers in the healthcare data analytics area. To make data science more approachable, we explored existing tools and developed a practice that can help data scientists convert existing analytics pipelines to user-friendly analytics APPs with rich interactions and features of real-time analysis. With this practice, data scientists can develop customized analytics pipelines as APPs in Jupyter Notebook and disseminate them to other researchers easily, and researchers can benefit from the shared notebook to perform analysis tasks or reproduce research results much more easily.

Factors Influencing Beliefs for Adoption of a Learning Analytics Tool: An Empirical Study

ERIC Educational Resources Information Center

Ali, Liaqat; Asadi, Mohsen; Gasevic, Dragan; Jovanovic, Jelena; Hatala, Marek

2013-01-01

Present research and development offer various learning analytics tools providing insights into different aspects of learning processes. Adoption of a specific tool for practice is based on how its learning analytics are perceived by educators to support their pedagogical and organizational goals. In this paper, we propose and empirically validate…

Hasse diagram as a green analytical metrics tool: ranking of methods for benzo[a]pyrene determination in sediments.

PubMed

Bigus, Paulina; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek; Tobiszewski, Marek

2016-05-01

This study presents an application of the Hasse diagram technique (HDT) as the assessment tool to select the most appropriate analytical procedures according to their greenness or the best analytical performance. The dataset consists of analytical procedures for benzo[a]pyrene determination in sediment samples, which were described by 11 variables concerning their greenness and analytical performance. Two analyses with the HDT were performed-the first one with metrological variables and the second one with "green" variables as input data. Both HDT analyses ranked different analytical procedures as the most valuable, suggesting that green analytical chemistry is not in accordance with metrology when benzo[a]pyrene in sediment samples is determined. The HDT can be used as a good decision support tool to choose the proper analytical procedure concerning green analytical chemistry principles and analytical performance merits.

75 FR 41173 - Call for Information: Information on Greenhouse Gas Emissions Associated With Bioenergy and Other...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-15

... oversimplify a complex issue. If this is the case, what alternative approaches or additional analytical tools... Information to solicit information and viewpoints from interested parties on approaches to accounting for... comment on developing an approach for such emissions under the Prevention of Significant Deterioration...

Scalable Visual Analytics of Massive Textual Datasets

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

Krishnan, Manoj Kumar; Bohn, Shawn J.; Cowley, Wendy E.

2007-04-01

This paper describes the first scalable implementation of text processing engine used in Visual Analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive dataset. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.

Deriving Earth Science Data Analytics Tools/Techniques Requirements

NASA Astrophysics Data System (ADS)

Kempler, S. J.

2015-12-01

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists. Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics tools/techniques requirements that would support specific ESDA type goals. Representative existing data analytics tools/techniques relevant to ESDA will also be addressed.

The generation of criteria for selecting analytical tools for landscape management

Treesearch

Marilyn Duffey-Armstrong

1979-01-01

This paper presents an approach to generating criteria for selecting the analytical tools used to assess visual resources for various landscape management tasks. The approach begins by first establishing the overall parameters for the visual assessment task, and follows by defining the primary requirements of the various sets of analytical tools to be used. Finally,...

An Analytic Tool to Investigate the Effect of Binder on the Sensitivity of HMX-Based Plastic Bonded Explosives in the Skid Test

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

Hayden, D. W.

This project will develop an analytical tool to calculate performance of HMX based PBXs in the skid test. The skid-test is used as a means to measure sensitivity for large charges in handling situations. Each series of skid tests requires dozens of drops of large billets. It is proposed that the reaction (or lack of one) of PBXs in the skid test is governed by the mechanical properties of the binder. If true, one might be able to develop an analytical tool to estimate skid test behavior for new PBX formulations. Others over the past 50 years have tried tomore » develop similar models. This project will research and summarize the works of others and couple the work of 3 into an analytical tool that can be run on a PC to calculate drop height of HMX based PBXs. Detonation due to dropping a billet is argued to be a dynamic thermal event. To avoid detonation, the heat created due to friction at impact, must be conducted into the charge or the target faster than the chemical kinetics can create additional energy. The methodology will involve numerically solving the Frank-Kamenetskii equation in one dimension. The analytical problem needs to be bounded in terms of how much heat is introduced to the billet and for how long. Assuming an inelastic collision with no rebound, the billet will be in contact with the target for a short duration determined by the equations of motion. For the purposes of the calculations, it will be assumed that if a detonation is to occur, it will transpire within that time. The surface temperature will be raised according to the friction created using the equations of motion of dropping the billet on a rigid surface. The study will connect the works of Charles Anderson, Alan Randolph, Larry Hatler, Alfonse Popolato, and Charles Mader into a single PC based analytic tool. Anderson's equations of motion will be used to calculate the temperature rise upon impact, the time this temperature is maintained (contact time) will be obtained from the work of Hatler et. al., and the reactive temperature rise will be obtained from Mader's work. Finally, the assessment of when a detonation occurs will be derived from Bowden and Yoffe's thermal explosion theory (hot spot).« less

Visual analytics for aviation safety: A collaborative approach to sensemaking

NASA Astrophysics Data System (ADS)

Wade, Andrew

Visual analytics, the "science of analytical reasoning facilitated by interactive visual interfaces", is more than just visualization. Understanding the human reasoning process is essential for designing effective visualization tools and providing correct analyses. This thesis describes the evolution, application and evaluation of a new method for studying analytical reasoning that we have labeled paired analysis. Paired analysis combines subject matter experts (SMEs) and tool experts (TE) in an analytic dyad, here used to investigate aircraft maintenance and safety data. The method was developed and evaluated using interviews, pilot studies and analytic sessions during an internship at the Boeing Company. By enabling a collaborative approach to sensemaking that can be captured by researchers, paired analysis yielded rich data on human analytical reasoning that can be used to support analytic tool development and analyst training. Keywords: visual analytics, paired analysis, sensemaking, boeing, collaborative analysis.

A Simplified Shuttle Payload Thermal Analyzer /SSPTA/ program

NASA Technical Reports Server (NTRS)

Bartoszek, J. T.; Huckins, B.; Coyle, M.

1979-01-01

A simple thermal analysis program for Space Shuttle payloads has been developed to accommodate the user who requires an easily understood but dependable analytical tool. The thermal analysis program includes several thermal subprograms traditionally employed in spacecraft thermal studies, a data management system for data generated by the subprograms, and a master program to coordinate the data files and thermal subprograms. The language and logic used to run the thermal analysis program are designed for the small user. In addition, analytical and storage techniques which conserve computer time and minimize core requirements are incorporated into the program.

Laboratory, Field, and Analytical Procedures for Using ...

EPA Pesticide Factsheets

Regardless of the remedial technology invoked to address contaminated sediments in the environment, there is a critical need to have tools for assessing the effectiveness of the remedy. In the past, these tools have included chemical and biomonitoring of the water column and sediments, toxicity testing and bioaccumulation studies performed on site sediments, and application of partitioning, transport and fate modeling. All of these tools served as lines of evidence for making informed environmental management decisions at contaminated sediment sites. In the last ten years, a new tool for assessing remedial effectiveness has gained a great deal of attention. Passive sampling offers a tool capable of measuring the freely dissolved concentration (Cfree) of legacy contaminants in water and sediments. In addition to assessing the effectiveness of the remedy, passive sampling can be applied for a variety of other contaminated sediments site purposes involved with performing the preliminary assessment and site inspection, conducting the remedial investigation and feasibility study, preparing the remedial design, and assessing the potential for contaminant bioaccumulation. While there is a distinct need for using passive sampling at contaminated sediments sites and several previous documents and research articles have discussed various aspects of passive sampling, there has not been definitive guidance on the laboratory, field and analytical procedures for using pas

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics

PubMed Central

2016-01-01

Background We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. Objective To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. Methods The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Results Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. Conclusions IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise. PMID:27729304

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics.

PubMed

Hoyt, Robert Eugene; Snider, Dallas; Thompson, Carla; Mantravadi, Sarita

2016-10-11

We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise.

75 FR 50017 - Self-Regulatory Organizations; EDGA Exchange, Inc.; Notice of Filing of Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-16

... the user. \\5\\ In addition to the boundary-level Exchange latency information, match level information... system which the Exchange operates or controls. In particular, the Exchange notes that it operates in a... users of the Exchange real-time analytical tools to measure the latency of orders to and from that...

Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

PubMed

Kangas, Michael J; Burks, Raychelle M; Atwater, Jordyn; Lukowicz, Rachel M; Garver, Billy; Holmes, Andrea E

2018-02-01

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. Colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10 M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study.

Spectrum simulation in DTSA-II.

PubMed

Ritchie, Nicholas W M

2009-10-01

Spectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on (rhoz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.

Functional Interfaces Constructed by Controlled/Living Radical Polymerization for Analytical Chemistry.

PubMed

Wang, Huai-Song; Song, Min; Hang, Tai-Jun

2016-02-10

The high-value applications of functional polymers in analytical science generally require well-defined interfaces, including precisely synthesized molecular architectures and compositions. Controlled/living radical polymerization (CRP) has been developed as a versatile and powerful tool for the preparation of polymers with narrow molecular weight distributions and predetermined molecular weights. Among the CRP system, atom transfer radical polymerization (ATRP) and reversible addition-fragmentation chain transfer (RAFT) are well-used to develop new materials for analytical science, such as surface-modified core-shell particles, monoliths, MIP micro- or nanospheres, fluorescent nanoparticles, and multifunctional materials. In this review, we summarize the emerging functional interfaces constructed by RAFT and ATRP for applications in analytical science. Various polymers with precisely controlled architectures including homopolymers, block copolymers, molecular imprinted copolymers, and grafted copolymers were synthesized by CRP methods for molecular separation, retention, or sensing. We expect that the CRP methods will become the most popular technique for preparing functional polymers that can be broadly applied in analytical chemistry.

Determining absolute protein numbers by quantitative fluorescence microscopy.

PubMed

Verdaasdonk, Jolien Suzanne; Lawrimore, Josh; Bloom, Kerry

2014-01-01

Biological questions are increasingly being addressed using a wide range of quantitative analytical tools to examine protein complex composition. Knowledge of the absolute number of proteins present provides insights into organization, function, and maintenance and is used in mathematical modeling of complex cellular dynamics. In this chapter, we outline and describe three microscopy-based methods for determining absolute protein numbers--fluorescence correlation spectroscopy, stepwise photobleaching, and ratiometric comparison of fluorescence intensity to known standards. In addition, we discuss the various fluorescently labeled proteins that have been used as standards for both stepwise photobleaching and ratiometric comparison analysis. A detailed procedure for determining absolute protein number by ratiometric comparison is outlined in the second half of this chapter. Counting proteins by quantitative microscopy is a relatively simple yet very powerful analytical tool that will increase our understanding of protein complex composition. © 2014 Elsevier Inc. All rights reserved.

WetDATA Hub: Democratizing Access to Water Data to Accelerate Innovation through Data Visualization, Predictive Analytics and Artificial Intelligence Applications

NASA Astrophysics Data System (ADS)

Sarni, W.

2017-12-01

Water scarcity and poor quality impacts economic development, business growth, and social well-being. Water has become, in our generation, the foremost critical local, regional, and global issue of our time. Despite these needs, there is no water hub or water technology accelerator solely dedicated to water data and tools. There is a need by the public and private sectors for vastly improved data management and visualization tools. This is the WetDATA opportunity - to develop a water data tech hub dedicated to water data acquisition, analytics, and visualization tools for informed policy and business decisions. WetDATA's tools will help incubate disruptive water data technologies and accelerate adoption of current water data solutions. WetDATA is a Colorado-based (501c3), global hub for water data analytics and technology innovation. WetDATA's vision is to be a global leader in water information, data technology innovation and collaborate with other US and global water technology hubs. ROADMAP * Portal (www.wetdata.org) to provide stakeholders with tools/resources to understand related water risks. * The initial activities will provide education, awareness and tools to stakeholders to support the implementation of the Colorado State Water Plan. * Leverage the Western States Water Council Water Data Exchange database. * Development of visualization, predictive analytics and AI tools to engage with stakeholders and provide actionable data and information. TOOLS Education: Provide information on water issues and risks at the local, state, national and global scale. Visualizations: Development of data analytics and visualization tools based upon the 2030 Water Resources Group methodology to support the implementation of the Colorado State Water Plan. Predictive Analytics: Accessing publically available water databases and using machine learning to develop water availability forecasting tools, and time lapse images to support city / urban planning.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle.

PubMed

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle

NASA Astrophysics Data System (ADS)

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

Rapid process development of chromatographic process using direct analysis in real time mass spectrometry as a process analytical technology tool.

PubMed

Yan, Binjun; Chen, Teng; Xu, Zhilin; Qu, Haibin

2014-06-01

The concept of quality by design (QbD) is widely applied in the process development of pharmaceuticals. However, the additional cost and time have caused some resistance about QbD implementation. To show a possible solution, this work proposed a rapid process development method, which used direct analysis in real time mass spectrometry (DART-MS) as a process analytical technology (PAT) tool for studying the chromatographic process of Ginkgo biloba L., as an example. The breakthrough curves were fast determined by DART-MS at-line. A high correlation coefficient of 0.9520 was found between the concentrations of ginkgolide A determined by DART-MS and HPLC. Based on the PAT tool, the impacts of process parameters on the adsorption capacity were discovered rapidly, which showed a decreased adsorption capacity with the increase of the flow rate. This work has shown the feasibility and advantages of integrating PAT into QbD implementation for rapid process development. Copyright © 2014 Elsevier B.V. All rights reserved.

Analytical Tools in School Finance Reform.

ERIC Educational Resources Information Center

Johns, R. L.

This paper discusses the problem of analyzing variations in the educational opportunities provided by different school districts and describes how to assess the impact of school finance alternatives through use of various analytical tools. The author first examines relatively simple analytical methods, including calculation of per-pupil…

Epilepsy analytic system with cloud computing.

PubMed

Shen, Chia-Ping; Zhou, Weizhi; Lin, Feng-Seng; Sung, Hsiao-Ya; Lam, Yan-Yu; Chen, Wei; Lin, Jeng-Wei; Pan, Ming-Kai; Chiu, Ming-Jang; Lai, Feipei

2013-01-01

Biomedical data analytic system has played an important role in doing the clinical diagnosis for several decades. Today, it is an emerging research area of analyzing these big data to make decision support for physicians. This paper presents a parallelized web-based tool with cloud computing service architecture to analyze the epilepsy. There are many modern analytic functions which are wavelet transform, genetic algorithm (GA), and support vector machine (SVM) cascaded in the system. To demonstrate the effectiveness of the system, it has been verified by two kinds of electroencephalography (EEG) data, which are short term EEG and long term EEG. The results reveal that our approach achieves the total classification accuracy higher than 90%. In addition, the entire training time accelerate about 4.66 times and prediction time is also meet requirements in real time.

Inspection of the Math Model Tools for On-Orbit Assessment of Impact Damage Report

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Raju, Ivatury S.; Piascik, Robert S> ; KramerWhite, Julie A.; KramerWhite, Julie A.; Labbe, Steve G.; Rotter, Hank A.

2007-01-01

In Spring of 2005, the NASA Engineering Safety Center (NESC) was engaged by the Space Shuttle Program (SSP) to peer review the suite of analytical tools being developed to support the determination of impact and damage tolerance of the Orbiter Thermal Protection Systems (TPS). The NESC formed an independent review team with the core disciplines of materials, flight sciences, structures, mechanical analysis and thermal analysis. The Math Model Tools reviewed included damage prediction and stress analysis, aeroheating analysis, and thermal analysis tools. Some tools are physics-based and other tools are empirically-derived. Each tool was created for a specific use and timeframe, including certification, real-time pre-launch assessments. In addition, the tools are used together in an integrated strategy for assessing the ramifications of impact damage to tile and RCC. The NESC teams conducted a peer review of the engineering data package for each Math Model Tool. This report contains the summary of the team observations and recommendations from these reviews.

Liquid chromatography/mass spectrometry and liquid chromatography/nuclear magnetic resonance as complementary analytical techniques for unambiguous identification of polymethoxylated flavones in residues from molecular distillation of orange peel oils (Citrus sinensis).

PubMed

Weber, Berthold; Hartmann, Beate; Stöckigt, Detlef; Schreiber, Klaus; Roloff, Michael; Bertram, Heinz-Jürgen; Schmidt, Claus O

2006-01-25

Liquid chromatography/mass spectrometry and liquid chromatography/nuclear magnetic resonance techniques with ultraviolet/diode array detection were used as complementary analytical tools for the reliable identification of polymethoxylated flavones in residues from molecular distillation of cold-pressed peel oils of Citrus sinensis. After development of a liquid chromatographic separation procedure, the presence of several polymethoxy flavones such as sinensetin, nobiletin, tangeretin, quercetogetin, heptamethoxyflavone, and other derivatives was unambiguously confirmed. In addition, proceranone, an acetylated tetranortriterpenoid with limonoid structure, was identified for the first time in citrus.

Harnessing scientific literature reports for pharmacovigilance. Prototype software analytical tool development and usability testing.

PubMed

Sorbello, Alfred; Ripple, Anna; Tonning, Joseph; Munoz, Monica; Hasan, Rashedul; Ly, Thomas; Francis, Henry; Bodenreider, Olivier

2017-03-22

We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers' capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. All usability test participants cited the tool's ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool's automated literature search relative to a manual 'all fields' PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction.

The Benefits and Complexities of Operating Geographic Information Systems (GIS) in a High Performance Computing (HPC) Environment

NASA Astrophysics Data System (ADS)

Shute, J.; Carriere, L.; Duffy, D.; Hoy, E.; Peters, J.; Shen, Y.; Kirschbaum, D.

2017-12-01

The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center is building and maintaining an Enterprise GIS capability for its stakeholders, to include NASA scientists, industry partners, and the public. This platform is powered by three GIS subsystems operating in a highly-available, virtualized environment: 1) the Spatial Analytics Platform is the primary NCCS GIS and provides users discoverability of the vast DigitalGlobe/NGA raster assets within the NCCS environment; 2) the Disaster Mapping Platform provides mapping and analytics services to NASA's Disaster Response Group; and 3) the internal (Advanced Data Analytics Platform/ADAPT) enterprise GIS provides users with the full suite of Esri and open source GIS software applications and services. All systems benefit from NCCS's cutting edge infrastructure, to include an InfiniBand network for high speed data transfers; a mixed/heterogeneous environment featuring seamless sharing of information between Linux and Windows subsystems; and in-depth system monitoring and warning systems. Due to its co-location with the NCCS Discover High Performance Computing (HPC) environment and the Advanced Data Analytics Platform (ADAPT), the GIS platform has direct access to several large NCCS datasets including DigitalGlobe/NGA, Landsat, MERRA, and MERRA2. Additionally, the NCCS ArcGIS Desktop Windows virtual machines utilize existing NetCDF and OPeNDAP assets for visualization, modelling, and analysis - thus eliminating the need for data duplication. With the advent of this platform, Earth scientists have full access to vast data repositories and the industry-leading tools required for successful management and analysis of these multi-petabyte, global datasets. The full system architecture and integration with scientific datasets will be presented. Additionally, key applications and scientific analyses will be explained, to include the NASA Global Landslide Catalog (GLC) Reporter crowdsourcing application, the NASA GLC Viewer discovery and analysis tool, the DigitalGlobe/NGA Data Discovery Tool, the NASA Disaster Response Group Mapping Platform (https://maps.disasters.nasa.gov), and support for NASA's Arctic - Boreal Vulnerability Experiment (ABoVE).

An Analysis of Earth Science Data Analytics Use Cases

NASA Technical Reports Server (NTRS)

Shie, Chung-Lin; Kempler, Steve

2014-01-01

The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https:earthdata.nasa.govaboutsystem-- performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co--analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task. Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.

The use of a quartz crystal microbalance as an analytical tool to monitor particle/surface and particle/particle interactions under dry ambient and pressurized conditions: a study using common inhaler components.

PubMed

Turner, N W; Bloxham, M; Piletsky, S A; Whitcombe, M J; Chianella, I

2016-12-19

Metered dose inhalers (MDI) and multidose powder inhalers (MPDI) are commonly used for the treatment of chronic obstructive pulmonary diseases and asthma. Currently, analytical tools to monitor particle/particle and particle/surface interaction within MDI and MPDI at the macro-scale do not exist. A simple tool capable of measuring such interactions would ultimately enable quality control of MDI and MDPI, producing remarkable benefits for the pharmaceutical industry and the users of inhalers. In this paper, we have investigated whether a quartz crystal microbalance (QCM) could become such a tool. A QCM was used to measure particle/particle and particle/surface interactions on the macroscale, by additions of small amounts of MDPI components, in the powder form into a gas stream. The subsequent interactions with materials on the surface of the QCM sensor were analyzed. Following this, the sensor was used to measure fluticasone propionate, a typical MDI active ingredient, in a pressurized gas system to assess its interactions with different surfaces under conditions mimicking the manufacturing process. In both types of experiments the QCM was capable of discriminating interactions of different components and surfaces. The results have demonstrated that the QCM is a suitable platform for monitoring macro-scale interactions and could possibly become a tool for quality control of inhalers.

Experimental and Numerical Optimization of a High-Lift System to Improve Low-Speed Performance, Stability, and Control of an Arrow-Wing Supersonic Transport

NASA Technical Reports Server (NTRS)

Hahne, David E.; Glaab, Louis J.

1999-01-01

An investigation was performed to evaluate leading-and trailing-edge flap deflections for optimal aerodynamic performance of a High-Speed Civil Transport concept during takeoff and approach-to-landing conditions. The configuration used for this study was designed by the Douglas Aircraft Company during the 1970's. A 0.1-scale model of this configuration was tested in the Langley 30- by 60-Foot Tunnel with both the original leading-edge flap system and a new leading-edge flap system, which was designed with modem computational flow analysis and optimization tools. Leading-and trailing-edge flap deflections were generated for the original and modified leading-edge flap systems with the computational flow analysis and optimization tools. Although wind tunnel data indicated improvements in aerodynamic performance for the analytically derived flap deflections for both leading-edge flap systems, perturbations of the analytically derived leading-edge flap deflections yielded significant additional improvements in aerodynamic performance. In addition to the aerodynamic performance optimization testing, stability and control data were also obtained. An evaluation of the crosswind landing capability of the aircraft configuration revealed that insufficient lateral control existed as a result of high levels of lateral stability. Deflection of the leading-and trailing-edge flaps improved the crosswind landing capability of the vehicle considerably; however, additional improvements are required.

A Model of Risk Analysis in Analytical Methodology for Biopharmaceutical Quality Control.

PubMed

Andrade, Cleyton Lage; Herrera, Miguel Angel De La O; Lemes, Elezer Monte Blanco

2018-01-01

One key quality control parameter for biopharmaceutical products is the analysis of residual cellular DNA. To determine small amounts of DNA (around 100 pg) that may be in a biologically derived drug substance, an analytical method should be sensitive, robust, reliable, and accurate. In principle, three techniques have the ability to measure residual cellular DNA: radioactive dot-blot, a type of hybridization; threshold analysis; and quantitative polymerase chain reaction. Quality risk management is a systematic process for evaluating, controlling, and reporting of risks that may affects method capabilities and supports a scientific and practical approach to decision making. This paper evaluates, by quality risk management, an alternative approach to assessing the performance risks associated with quality control methods used with biopharmaceuticals, using the tool hazard analysis and critical control points. This tool provides the possibility to find the steps in an analytical procedure with higher impact on method performance. By applying these principles to DNA analysis methods, we conclude that the radioactive dot-blot assay has the largest number of critical control points, followed by quantitative polymerase chain reaction, and threshold analysis. From the analysis of hazards (i.e., points of method failure) and the associated method procedure critical control points, we conclude that the analytical methodology with the lowest risk for performance failure for residual cellular DNA testing is quantitative polymerase chain reaction. LAY ABSTRACT: In order to mitigate the risk of adverse events by residual cellular DNA that is not completely cleared from downstream production processes, regulatory agencies have required the industry to guarantee a very low level of DNA in biologically derived pharmaceutical products. The technique historically used was radioactive blot hybridization. However, the technique is a challenging method to implement in a quality control laboratory: It is laborious, time consuming, semi-quantitative, and requires a radioisotope. Along with dot-blot hybridization, two alternatives techniques were evaluated: threshold analysis and quantitative polymerase chain reaction. Quality risk management tools were applied to compare the techniques, taking into account the uncertainties, the possibility of circumstances or future events, and their effects upon method performance. By illustrating the application of these tools with DNA methods, we provide an example of how they can be used to support a scientific and practical approach to decision making and can assess and manage method performance risk using such tools. This paper discusses, considering the principles of quality risk management, an additional approach to the development and selection of analytical quality control methods using the risk analysis tool hazard analysis and critical control points. This tool provides the possibility to find the method procedural steps with higher impact on method reliability (called critical control points). Our model concluded that the radioactive dot-blot assay has the larger number of critical control points, followed by quantitative polymerase chain reaction and threshold analysis. Quantitative polymerase chain reaction is shown to be the better alternative analytical methodology in residual cellular DNA analysis. © PDA, Inc. 2018.

A Progressive Approach to Teaching Analytics in the Marketing Curriculum

ERIC Educational Resources Information Center

Liu, Yiyuan; Levin, Michael A.

2018-01-01

With the emerging use of analytics tools and methodologies in marketing, marketing educators have provided students training and experiences beyond the soft skills associated with understanding consumer behavior. Previous studies have only discussed how to apply analytics in course designs, tools, and related practices. However, there is a lack of…

Median of patient results as a tool for assessment of analytical stability.

PubMed

Jørgensen, Lars Mønster; Hansen, Steen Ingemann; Petersen, Per Hyltoft; Sölétormos, György

2015-06-15

In spite of the well-established external quality assessment and proficiency testing surveys of analytical quality performance in laboratory medicine, a simple tool to monitor the long-term analytical stability as a supplement to the internal control procedures is often needed. Patient data from daily internal control schemes was used for monthly appraisal of the analytical stability. This was accomplished by using the monthly medians of patient results to disclose deviations from analytical stability, and by comparing divergences with the quality specifications for allowable analytical bias based on biological variation. Seventy five percent of the twenty analytes achieved on two COBASs INTEGRA 800 instruments performed in accordance with the optimum and with the desirable specifications for bias. Patient results applied in analytical quality performance control procedures are the most reliable sources of material as they represent the genuine substance of the measurements and therefore circumvent the problems associated with non-commutable materials in external assessment. Patient medians in the monthly monitoring of analytical stability in laboratory medicine are an inexpensive, simple and reliable tool to monitor the steadiness of the analytical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Targeted Analyte Detection by Standard Addition Improves Detection Limits in MALDI Mass Spectrometry

PubMed Central

Eshghi, Shadi Toghi; Li, Xingde; Zhang, Hui

2014-01-01

Matrix-assisted laser desorption/ionization has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications. PMID:22877355

Targeted analyte detection by standard addition improves detection limits in matrix-assisted laser desorption/ionization mass spectrometry.

PubMed

Toghi Eshghi, Shadi; Li, Xingde; Zhang, Hui

2012-09-18

Matrix-assisted laser desorption/ionization (MALDI) has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications.

Feature Geo Analytics and Big Data Processing: Hybrid Approaches for Earth Science and Real-Time Decision Support

NASA Astrophysics Data System (ADS)

Wright, D. J.; Raad, M.; Hoel, E.; Park, M.; Mollenkopf, A.; Trujillo, R.

2016-12-01

Introduced is a new approach for processing spatiotemporal big data by leveraging distributed analytics and storage. A suite of temporally-aware analysis tools summarizes data nearby or within variable windows, aggregates points (e.g., for various sensor observations or vessel positions), reconstructs time-enabled points into tracks (e.g., for mapping and visualizing storm tracks), joins features (e.g., to find associations between features based on attributes, spatial relationships, temporal relationships or all three simultaneously), calculates point densities, finds hot spots (e.g., in species distributions), and creates space-time slices and cubes (e.g., in microweather applications with temperature, humidity, and pressure, or within human mobility studies). These "feature geo analytics" tools run in both batch and streaming spatial analysis mode as distributed computations across a cluster of servers on typical "big" data sets, where static data exist in traditional geospatial formats (e.g., shapefile) locally on a disk or file share, attached as static spatiotemporal big data stores, or streamed in near-real-time. In other words, the approach registers large datasets or data stores with ArcGIS Server, then distributes analysis across a cluster of machines for parallel processing. Several brief use cases will be highlighted based on a 16-node server cluster at 14 Gb RAM per node, allowing, for example, the buffering of over 8 million points or thousands of polygons in 1 minute. The approach is "hybrid" in that ArcGIS Server integrates open-source big data frameworks such as Apache Hadoop and Apache Spark on the cluster in order to run the analytics. In addition, the user may devise and connect custom open-source interfaces and tools developed in Python or Python Notebooks; the common denominator being the familiar REST API.

A review of the analytical simulation of aircraft crash dynamics

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Carden, Huey D.; Boitnott, Richard L.; Hayduk, Robert J.

1990-01-01

A large number of full scale tests of general aviation aircraft, helicopters, and one unique air-to-ground controlled impact of a transport aircraft were performed. Additionally, research was also conducted on seat dynamic performance, load-limiting seats, load limiting subfloor designs, and emergency-locator-transmitters (ELTs). Computer programs were developed to provide designers with methods for predicting accelerations, velocities, and displacements of collapsing structure and for estimating the human response to crash loads. The results of full scale aircraft and component tests were used to verify and guide the development of analytical simulation tools and to demonstrate impact load attenuating concepts. Analytical simulation of metal and composite aircraft crash dynamics are addressed. Finite element models are examined to determine their degree of corroboration by experimental data and to reveal deficiencies requiring further development.

Analytical tools for the analysis of β-carotene and its degradation products

PubMed Central

Stutz, H.; Bresgen, N.; Eckl, P. M.

2015-01-01

Abstract β-Carotene, the precursor of vitamin A, possesses pronounced radical scavenging properties. This has centered the attention on β-carotene dietary supplementation in healthcare as well as in the therapy of degenerative disorders and several cancer types. However, two intervention trials with β-carotene have revealed adverse effects on two proband groups, that is, cigarette smokers and asbestos-exposed workers. Beside other causative reasons, the detrimental effects observed have been related to the oxidation products of β-carotene. Their generation originates in the polyene structure of β-carotene that is beneficial for radical scavenging, but is also prone to oxidation. Depending on the dominant degradation mechanism, bond cleavage might occur either randomly or at defined positions of the conjugated electron system, resulting in a diversity of cleavage products (CPs). Due to their instability and hydrophobicity, the handling of standards and real samples containing β-carotene and related CPs requires preventive measures during specimen preparation, analyte extraction, and final analysis, to avoid artificial degradation and to preserve the initial analyte portfolio. This review critically discusses different preparation strategies of standards and treatment solutions, and also addresses their protection from oxidation. Additionally, in vitro oxidation strategies for the generation of oxidative model compounds are surveyed. Extraction methods are discussed for volatile and non-volatile CPs individually. Gas chromatography (GC), (ultra)high performance liquid chromatography (U)HPLC, and capillary electrochromatography (CEC) are reviewed as analytical tools for final analyte analysis. For identity confirmation of analytes, mass spectrometry (MS) is indispensable, and the appropriate ionization principles are comprehensively discussed. The final sections cover analysis of real samples and aspects of quality assurance, namely matrix effects and method validation. PMID:25867077

Liquid chromatography-mass spectrometry in metabolomics research: mass analyzers in ultra high pressure liquid chromatography coupling.

PubMed

Forcisi, Sara; Moritz, Franco; Kanawati, Basem; Tziotis, Dimitrios; Lehmann, Rainer; Schmitt-Kopplin, Philippe

2013-05-31

The present review gives an introduction into the concept of metabolomics and provides an overview of the analytical tools applied in non-targeted metabolomics with a focus on liquid chromatography (LC). LC is a powerful analytical tool in the study of complex sample matrices. A further development and configuration employing Ultra-High Pressure Liquid Chromatography (UHPLC) is optimized to provide the largest known liquid chromatographic resolution and peak capacity. Reasonably UHPLC plays an important role in separation and consequent metabolite identification of complex molecular mixtures such as bio-fluids. The most sensitive detectors for these purposes are mass spectrometers. Almost any mass analyzer can be optimized to identify and quantify small pre-defined sets of targets; however, the number of analytes in metabolomics is far greater. Optimized protocols for quantification of large sets of targets may be rendered inapplicable. Results on small target set analyses on different sample matrices are easily comparable with each other. In non-targeted metabolomics there is almost no analytical method which is applicable to all different matrices due to limitations pertaining to mass analyzers and chromatographic tools. The specifications of the most important interfaces and mass analyzers are discussed. We additionally provide an exemplary application in order to demonstrate the level of complexity which remains intractable up to date. The potential of coupling a high field Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ICR-FT/MS), the mass analyzer with the largest known mass resolving power, to UHPLC is given with an example of one human pre-treated plasma sample. This experimental example illustrates one way of overcoming the necessity of faster scanning rates in the coupling with UHPLC. The experiment enabled the extraction of thousands of features (analytical signals). A small subset of this compositional space could be mapped into a mass difference network whose topology shows specificity toward putative metabolite classes and retention time. Copyright © 2013 Elsevier B.V. All rights reserved.

Stochastic modelling of the hydrologic operation of rainwater harvesting systems

NASA Astrophysics Data System (ADS)

Guo, Rui; Guo, Yiping

2018-07-01

Rainwater harvesting (RWH) systems are an effective low impact development practice that provides both water supply and runoff reduction benefits. A stochastic modelling approach is proposed in this paper to quantify the water supply reliability and stormwater capture efficiency of RWH systems. The input rainfall series is represented as a marked Poisson process and two typical water use patterns are analytically described. The stochastic mass balance equation is solved analytically, and based on this, explicit expressions relating system performance to system characteristics are derived. The performances of a wide variety of RWH systems located in five representative climatic regions of the United States are examined using the newly derived analytical equations. Close agreements between analytical and continuous simulation results are shown for all the compared cases. In addition, an analytical equation is obtained expressing the required storage size as a function of the desired water supply reliability, average water use rate, as well as rainfall and catchment characteristics. The equations developed herein constitute a convenient and effective tool for sizing RWH systems and evaluating their performances.

NASA transmission research and its probable effects on helicopter transmission design

NASA Technical Reports Server (NTRS)

Zaretsky, E. V.; Coy, J. J.; Townsend, D. P.

1983-01-01

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

NASA transmission research and its probable effects on helicopter transmission design

NASA Technical Reports Server (NTRS)

Zaretsky, E. V.; Coy, J. J.; Townsend, D. P.

1984-01-01

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

Experimental and analytical tools for evaluation of Stirling engine rod seal behavior

NASA Technical Reports Server (NTRS)

Krauter, A. I.; Cheng, H. S.

1979-01-01

The first year of a two year experimental and analytical program is reported. The program is directed at the elastohydrodynamic behavior of sliding elastomeric rod seals for the Stirling engine. During the year, experimental and analytical tools were developed for evaluating seal leakage, seal friction, and the fluid film thickness at the seal/cylinder interface.

Analytics for Cyber Network Defense

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

Plantenga, Todd.; Kolda, Tamara Gibson

2011-06-01

This report provides a brief survey of analytics tools considered relevant to cyber network defense (CND). Ideas and tools come from elds such as statistics, data mining, and knowledge discovery. Some analytics are considered standard mathematical or statistical techniques, while others re ect current research directions. In all cases the report attempts to explain the relevance to CND with brief examples.

Solar Data and Tools: Resources for Researchers, Industry, and Developers

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

2016-04-01

In partnership with the U.S. Department of Energy SunShot Initiative, the National Renewable Energy Laboratory (NREL) has created a suite of analytical tools and data that can inform decisions about implementing solar and that are increasingly forming the basis of private-sector tools and services to solar consumers. The following solar energy data sets and analytical tools are available free to the public.

Predictive Analytics for Identification of Patients at Risk for QT Interval Prolongation - A Systematic Review.

PubMed

Tomaselli Muensterman, Elena; Tisdale, James E

2018-06-08

Prolongation of the heart rate-corrected QT (QTc) interval increases the risk for torsades de pointes (TdP), a potentially fatal arrhythmia. The likelihood of TdP is higher in patients with risk factors, which include female sex, older age, heart failure with reduced ejection fraction, hypokalemia, hypomagnesemia, concomitant administration of ≥ 2 QTc interval-prolonging medications, among others. Assessment and quantification of risk factors may facilitate prediction of patients at highest risk for developing QTc interval prolongation and TdP. Investigators have utilized the field of predictive analytics, which generates predictions using techniques including data mining, modeling, machine learning, and others, to develop methods of risk quantification and prediction of QTc interval prolongation. Predictive analytics have also been incorporated into clinical decision support (CDS) tools to alert clinicians regarding patients at increased risk of developing QTc interval prolongation. The objectives of this paper are to assess the effectiveness of predictive analytics for identification of patients at risk of drug-induced QTc interval prolongation, and to discuss the efficacy of incorporation of predictive analytics into CDS tools in clinical practice. A systematic review of English language articles (human subjects only) was performed, yielding 57 articles, with an additional 4 articles identified from other sources; a total of 10 articles were included in this review. Risk scores for QTc interval prolongation have been developed in various patient populations including those in cardiac intensive care units (ICUs) and in broader populations of hospitalized or health system patients. One group developed a risk score that includes information regarding genetic polymorphisms; this score significantly predicted TdP. Development of QTc interval prolongation risk prediction models and incorporation of these models into CDS tools reduces the risk of QTc interval prolongation in cardiac ICUs and identifies health-system patients at increased risk for mortality. The impact of these QTc interval prolongation predictive analytics on overall patient safety outcomes, such as TdP and sudden cardiac death relative to the cost of development and implementation, requires further study. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Mining Mathematics in Textbook Lessons

ERIC Educational Resources Information Center

Ronda, Erlina; Adler, Jill

2017-01-01

In this paper, we propose an analytic tool for describing the mathematics made available to learn in a "textbook lesson". The tool is an adaptation of the Mathematics Discourse in Instruction (MDI) analytic tool that we developed to analyze what is made available to learn in teachers' lessons. Our motivation to adapt the use of the MDI…

Fire behavior modeling-a decision tool

Treesearch

Jack Cohen; Bill Bradshaw

1986-01-01

The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

Guidance for the Design and Adoption of Analytic Tools.

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

Bandlow, Alisa

2015-12-01

The goal is to make software developers aware of common issues that can impede the adoption of analytic tools. This paper provides a summary of guidelines, lessons learned and existing research to explain what is currently known about what analysts want and how to better understand what tools they do and don't need.

Revisiting the use of 'place' as an analytic tool for elucidating geographic issues central to Canadian rural palliative care.

PubMed

Giesbrecht, Melissa; Crooks, Valorie A; Castleden, Heather; Schuurman, Nadine; Skinner, Mark W; Williams, Allison M

2016-09-01

In 2010, Castleden and colleagues published a paper in this journal using the concept of 'place' as an analytic tool to understand the nature of palliative care provision in a rural region in British Columbia, Canada. This publication was based upon pilot data collected for a larger research project that has since been completed. With the addition of 40 semi-structured interviews with users and providers of palliative care in four other rural communities located across Canada, we revisit Castleden and colleagues' (2010) original framework. Applying the concept of place to the full dataset confirmed the previously published findings, but also revealed two new place-based dimensions related to experiences of rural palliative care in Canada: (1) borders and boundaries; and (2) 'making' place for palliative care progress. These new findings offer a refined understanding of the complex interconnections between various dimensions of place and palliative care in rural Canada. Copyright © 2016 Elsevier Ltd. All rights reserved.

Can we use high precision metal isotope analysis to improve our understanding of cancer?

PubMed

Larner, Fiona

2016-01-01

High precision natural isotope analyses are widely used in geosciences to trace elemental transport pathways. The use of this analytical tool is increasing in nutritional and disease-related research. In recent months, a number of groups have shown the potential this technique has in providing new observations for various cancers when applied to trace metal metabolism. The deconvolution of isotopic signatures, however, relies on mathematical models and geochemical data, which are not representative of the system under investigation. In addition to relevant biochemical studies of protein-metal isotopic interactions, technological development both in terms of sample throughput and detection sensitivity of these elements is now needed to translate this novel approach into a mainstream analytical tool. Following this, essential background healthy population studies must be performed, alongside observational, cross-sectional disease-based studies. Only then can the sensitivity and specificity of isotopic analyses be tested alongside currently employed methods, and important questions such as the influence of cancer heterogeneity and disease stage on isotopic signatures be addressed.

An analytical model to predict and minimize the residual stress of laser cladding process

NASA Astrophysics Data System (ADS)

Tamanna, N.; Crouch, R.; Kabir, I. R.; Naher, S.

2018-02-01

Laser cladding is one of the advanced thermal techniques used to repair or modify the surface properties of high-value components such as tools, military and aerospace parts. Unfortunately, tensile residual stresses generate in the thermally treated area of this process. This work focuses on to investigate the key factors for the formation of tensile residual stress and how to minimize it in the clad when using dissimilar substrate and clad materials. To predict the tensile residual stress, a one-dimensional analytical model has been adopted. Four cladding materials (Al2O3, TiC, TiO2, ZrO2) on the H13 tool steel substrate and a range of preheating temperatures of the substrate, from 300 to 1200 K, have been investigated. Thermal strain and Young's modulus are found to be the key factors of formation of tensile residual stresses. Additionally, it is found that using a preheating temperature of the substrate immediately before laser cladding showed the reduction of residual stress.

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

NASA Technical Reports Server (NTRS)

Patrick, M. Clinton; Cooper, Anita E.; Powers, W. T.

2004-01-01

Researchers are working on many konts to make possible high speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flow fields/plumes; the Optical Plume Anomaly Detection (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDIFIS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Additionally, efforts are being advanced to hardware encode components of the EDIFIS in order to address real-time operational requirements for health monitoring and management. This paper addresses the OPAD with its tool suite, and discusses what is considered a natural progression: a concept for migrating OPAD towards detection of high energy particles, including neutrons and gamma rays. The integration of these tools and capabilities will provide NASA with a systematic approach to monitor space vehicle internal and external environment.

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

SAM Radiochemical Methods Query

EPA Pesticide Factsheets

Laboratories measuring target radiochemical analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select radiochemical analytes.

Coastal On-line Assessment and Synthesis Tool 2.0

NASA Technical Reports Server (NTRS)

Brown, Richard; Navard, Andrew; Nguyen, Beth

2011-01-01

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

A history of development in rotordynamics: A manufacturer's perspective

NASA Technical Reports Server (NTRS)

Shemeld, David E.

1987-01-01

The subject of rotordynamics and instability problems in high performance turbomachinery has been a topic of considerable industry discussion and debate over the last 15 or so years. This paper reviews an original equipment manufacturer's history of development of concepts and equipment as applicable to multistage centrifugal compressors. The variety of industry user compression requirements and resultant problematical situations tends to confound many of the theories and analytical techniques set forth. The experiences and examples described herein support the conclusion that the successful addressing of potential rotordynamics problems is best served by a fundamental knowledge of the specific equipment. This in addition to having the appropriate analytical tools. Also, that the final proof is in the doing.

Evaluation of analytical markers characterising different drying methods of parsley leaves (Petroselinum crispum L.).

PubMed

Lechtenberg, M; Zumdick, S; Gerhards, C; Schmidt, T J; Hensel, A

2007-12-01

Drying process of parsley leaves from Petroselinum crispum L. can influence the sensory qualities and aromatic taste of this herbal product. Beside oven-dried material, freeze-dried parsley is getting increasingly into the market. In the course of a search for analytical tools to differentiate oven-dried and lyophilised parsley, a HPLC determination of the 6"-O-malonylapiin to apiin ratio was shown to be a suitable marker system. While the ratio is high for fresh and lyophilised leave material, oven-drying leads to demalonylation and, subsequently, to a low malonylapiin--apiin ratio. Additionally, L*a*b colour measurement can be used for quality control to differentiate between different dried parsley raw materials.

Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data

NASA Astrophysics Data System (ADS)

Jern, Mikael

Recent advances in web-enabled graphics technologies have the potential to make a dramatic impact on developing collaborative geovisual analytics (GeoAnalytics). In this paper, tools are introduced that help establish progress initiatives at international and sub-national levels aimed at measuring and collaborating, through statistical indicators, economic, social and environmental developments and to engage both statisticians and the public in such activities. Given this global dimension of such a task, the “dream” of building a repository of progress indicators, where experts and public users can use GeoAnalytics collaborative tools to compare situations for two or more countries, regions or local communities, could be accomplished. While the benefits of GeoAnalytics tools are many, it remains a challenge to adapt these dynamic visual tools to the Internet. For example, dynamic web-enabled animation that enables statisticians to explore temporal, spatial and multivariate demographics data from multiple perspectives, discover interesting relationships, share their incremental discoveries with colleagues and finally communicate selected relevant knowledge to the public. These discoveries often emerge through the diverse backgrounds and experiences of expert domains and are precious in a creative analytics reasoning process. In this context, we introduce a demonstrator “OECD eXplorer”, a customized tool for interactively analyzing, and collaborating gained insights and discoveries based on a novel story mechanism that capture, re-use and share task-related explorative events.

Teaching Theory Construction With Initial Grounded Theory Tools: A Reflection on Lessons and Learning.

PubMed

Charmaz, Kathy

2015-12-01

This article addresses criticisms of qualitative research for spawning studies that lack analytic development and theoretical import. It focuses on teaching initial grounded theory tools while interviewing, coding, and writing memos for the purpose of scaling up the analytic level of students' research and advancing theory construction. Adopting these tools can improve teaching qualitative methods at all levels although doctoral education is emphasized here. What teachers cover in qualitative methods courses matters. The pedagogy presented here requires a supportive environment and relies on demonstration, collective participation, measured tasks, progressive analytic complexity, and accountability. Lessons learned from using initial grounded theory tools are exemplified in a doctoral student's coding and memo-writing excerpts that demonstrate progressive analytic development. The conclusion calls for increasing the number and depth of qualitative methods courses and for creating a cadre of expert qualitative methodologists. © The Author(s) 2015.

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2010 CFR

2010-07-01

... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life... empirical tools should be used to support the life safety equivalency evaluation? 102-80.120 Section 102-80...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2011 CFR

2011-01-01

... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life... empirical tools should be used to support the life safety equivalency evaluation? 102-80.120 Section 102-80...

Web Analytics

EPA Pesticide Factsheets

EPA’s Web Analytics Program collects, analyzes, and provides reports on traffic, quality assurance, and customer satisfaction metrics for EPA’s website. The program uses a variety of analytics tools, including Google Analytics and CrazyEgg.

A graph algebra for scalable visual analytics.

PubMed

Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

2012-01-01

Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

The design, analysis, and testing of a low-budget wind-tunnel flutter model with active aerodynamic controls

NASA Technical Reports Server (NTRS)

Bolding, R. M.; Stearman, R. O.

1976-01-01

A low budget flutter model incorporating active aerodynamic controls for flutter suppression studies was designed as both an educational and research tool to study the interfering lifting surface flutter phenomenon in the form of a swept wing-tail configuration. A flutter suppression mechanism was demonstrated on a simple semirigid three-degree-of-freedom flutter model of this configuration employing an active stabilator control, and was then verified analytically using a doublet lattice lifting surface code and the model's measured mass, mode shapes, and frequencies in a flutter analysis. Preliminary studies were significantly encouraging to extend the analysis to the larger degree of freedom AFFDL wing-tail flutter model where additional analytical flutter suppression studies indicated significant gains in flutter margins could be achieved. The analytical and experimental design of a flutter suppression system for the AFFDL model is presented along with the results of a preliminary passive flutter test.

EPA Tools and Resources Webinar: EPA’s Environmental Sampling and Analytical Methods for Environmental Remediation and Recovery

EPA Pesticide Factsheets

EPA’s Environmental Sampling and Analytical Methods (ESAM) is a website tool that supports the entire environmental characterization process from collection of samples all the way to their analyses.

An automated protocol for performance benchmarking a widefield fluorescence microscope.

PubMed

Halter, Michael; Bier, Elianna; DeRose, Paul C; Cooksey, Gregory A; Choquette, Steven J; Plant, Anne L; Elliott, John T

2014-11-01

Widefield fluorescence microscopy is a highly used tool for visually assessing biological samples and for quantifying cell responses. Despite its widespread use in high content analysis and other imaging applications, few published methods exist for evaluating and benchmarking the analytical performance of a microscope. Easy-to-use benchmarking methods would facilitate the use of fluorescence imaging as a quantitative analytical tool in research applications, and would aid the determination of instrumental method validation for commercial product development applications. We describe and evaluate an automated method to characterize a fluorescence imaging system's performance by benchmarking the detection threshold, saturation, and linear dynamic range to a reference material. The benchmarking procedure is demonstrated using two different materials as the reference material, uranyl-ion-doped glass and Schott 475 GG filter glass. Both are suitable candidate reference materials that are homogeneously fluorescent and highly photostable, and the Schott 475 GG filter glass is currently commercially available. In addition to benchmarking the analytical performance, we also demonstrate that the reference materials provide for accurate day to day intensity calibration. Published 2014 Wiley Periodicals Inc. Published 2014 Wiley Periodicals Inc. This article is a US government work and, as such, is in the public domain in the United States of America.

Analyte-Responsive Hydrogels: Intelligent Materials for Biosensing and Drug Delivery.

PubMed

Culver, Heidi R; Clegg, John R; Peppas, Nicholas A

2017-02-21

Nature has mastered the art of molecular recognition. For example, using synergistic non-covalent interactions, proteins can distinguish between molecules and bind a partner with incredible affinity and specificity. Scientists have developed, and continue to develop, techniques to investigate and better understand molecular recognition. As a consequence, analyte-responsive hydrogels that mimic these recognitive processes have emerged as a class of intelligent materials. These materials are unique not only in the type of analyte to which they respond but also in how molecular recognition is achieved and how the hydrogel responds to the analyte. Traditional intelligent hydrogels can respond to environmental cues such as pH, temperature, and ionic strength. The functional monomers used to make these hydrogels can be varied to achieve responsive behavior. For analyte-responsive hydrogels, molecular recognition can also be achieved by incorporating biomolecules with inherent molecular recognition properties (e.g., nucleic acids, peptides, enzymes, etc.) into the polymer network. Furthermore, in addition to typical swelling/syneresis responses, these materials exhibit unique responsive behaviors, such as gel assembly or disassembly, upon interaction with the target analyte. With the diverse tools available for molecular recognition and the ability to generate unique responsive behaviors, analyte-responsive hydrogels have found great utility in a wide range of applications. In this Account, we discuss strategies for making four different classes of analyte-responsive hydrogels, specifically, non-imprinted, molecularly imprinted, biomolecule-containing, and enzymatically responsive hydrogels. Then we explore how these materials have been incorporated into sensors and drug delivery systems, highlighting examples that demonstrate the versatility of these materials. For example, in addition to the molecular recognition properties of analyte-responsive hydrogels, the physicochemical changes that are induced upon analyte binding can be exploited to generate a detectable signal for sensing applications. As research in this area has grown, a number of creative approaches for improving the selectivity and sensitivity (i.e., detection limit) of these sensors have emerged. For applications in drug delivery systems, therapeutic release can be triggered by competitive molecular interactions or physicochemical changes in the network. Additionally, including degradable units within the network can enable sustained and responsive therapeutic release. Several exciting examples exploiting the analyte-responsive behavior of hydrogels for the treatment of cancer, diabetes, and irritable bowel syndrome are discussed in detail. We expect that creative and combinatorial approaches used in the design of analyte-responsive hydrogels will continue to yield materials with great potential in the fields of sensing and drug delivery.

Total Quality Management (TQM), an Overview

DTIC Science & Technology

1991-09-01

Quality Management (TQM). It discusses the reasons TQM is a current growth industry, what it is, and how one implements it. It describes the basic analytical tools, statistical process control, some advanced analytical tools, tools used by process improvement teams to enhance their own operations, and action plans for making improvements. The final sections discuss assessing quality efforts and measuring the quality to knowledge

Development of Advanced Life Prediction Tools for Elastic-Plastic Fatigue Crack Growth

NASA Technical Reports Server (NTRS)

Gregg, Wayne; McGill, Preston; Swanson, Greg; Wells, Doug; Throckmorton, D. A. (Technical Monitor)

2001-01-01

The objective of this viewgraph presentation is to develop a systematic approach to improving the fracture control process, including analytical tools, standards, guidelines, and awareness. Analytical tools specifically for elastic-plastic fracture analysis is a regime that is currently empirical for the Space Shuttle External Tank (ET) and is handled by simulated service testing of pre-cracked panels.

Development of a research ethics knowledge and analytical skills assessment tool.

PubMed

Taylor, Holly A; Kass, Nancy E; Ali, Joseph; Sisson, Stephen; Bertram, Amanda; Bhan, Anant

2012-04-01

The goal of this project was to develop and validate a new tool to evaluate learners' knowledge and skills related to research ethics. A core set of 50 questions from existing computer-based online teaching modules were identified, refined and supplemented to create a set of 74 multiple-choice, true/false and short answer questions. The questions were pilot-tested and item discrimination was calculated for each question. Poorly performing items were eliminated or refined. Two comparable assessment tools were created. These assessment tools were administered as a pre-test and post-test to a cohort of 58 Indian junior health research investigators before and after exposure to a new course on research ethics. Half of the investigators were exposed to the course online, the other half in person. Item discrimination was calculated for each question and Cronbach's α for each assessment tool. A final version of the assessment tool that incorporated the best questions from the pre-/post-test phase was used to assess retention of research ethics knowledge and skills 3 months after course delivery. The final version of the REKASA includes 41 items and had a Cronbach's α of 0.837. The results illustrate, in one sample of learners, the successful, systematic development and use of a knowledge and skills assessment tool in research ethics capable of not only measuring basic knowledge in research ethics and oversight but also assessing learners' ability to apply ethics knowledge to the analytical task of reasoning through research ethics cases, without reliance on essay or discussion-based examination. These promising preliminary findings should be confirmed with additional groups of learners.

Modeling and Predicting the Stress Relaxation of Composites with Short and Randomly Oriented Fibers

PubMed Central

Obaid, Numaira; Sain, Mohini

2017-01-01

The addition of short fibers has been experimentally observed to slow the stress relaxation of viscoelastic polymers, producing a change in the relaxation time constant. Our recent study attributed this effect of fibers on stress relaxation behavior to the interfacial shear stress transfer at the fiber-matrix interface. This model explained the effect of fiber addition on stress relaxation without the need to postulate structural changes at the interface. In our previous study, we developed an analytical model for the effect of fully aligned short fibers, and the model predictions were successfully compared to finite element simulations. However, in most industrial applications of short-fiber composites, fibers are not aligned, and hence it is necessary to examine the time dependence of viscoelastic polymers containing randomly oriented short fibers. In this study, we propose an analytical model to predict the stress relaxation behavior of short-fiber composites where the fibers are randomly oriented. The model predictions were compared to results obtained from Monte Carlo finite element simulations, and good agreement between the two was observed. The analytical model provides an excellent tool to accurately predict the stress relaxation behavior of randomly oriented short-fiber composites. PMID:29053601

Analytical framework and tool kit for SEA follow-up

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

Nilsson, Mans; Wiklund, Hans; Finnveden, Goeran

2009-04-15

Most Strategic Environmental Assessment (SEA) research and applications have so far neglected the ex post stages of the process, also called SEA follow-up. Tool kits and methodological frameworks for engaging effectively with SEA follow-up have been conspicuously missing. In particular, little has so far been learned from the much more mature evaluation literature although many aspects are similar. This paper provides an analytical framework and tool kit for SEA follow-up. It is based on insights and tools developed within programme evaluation and environmental systems analysis. It is also grounded in empirical studies into real planning and programming practices at themore » regional level, but should have relevance for SEA processes at all levels. The purpose of the framework is to promote a learning-oriented and integrated use of SEA follow-up in strategic decision making. It helps to identify appropriate tools and their use in the process, and to systematise the use of available data and knowledge across the planning organization and process. It distinguishes three stages in follow-up: scoping, analysis and learning, identifies the key functions and demonstrates the informational linkages to the strategic decision-making process. The associated tool kit includes specific analytical and deliberative tools. Many of these are applicable also ex ante, but are then used in a predictive mode rather than on the basis of real data. The analytical element of the framework is organized on the basis of programme theory and 'DPSIR' tools. The paper discusses three issues in the application of the framework: understanding the integration of organizations and knowledge; understanding planners' questions and analytical requirements; and understanding interests, incentives and reluctance to evaluate.« less

A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

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

Gillen, David S.

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less

A Modular GIS-Based Software Architecture for Model Parameter Estimation using the Method of Anchored Distributions (MAD)

NASA Astrophysics Data System (ADS)

Ames, D. P.; Osorio-Murillo, C.; Over, M. W.; Rubin, Y.

2012-12-01

The Method of Anchored Distributions (MAD) is an inverse modeling technique that is well-suited for estimation of spatially varying parameter fields using limited observations and Bayesian methods. This presentation will discuss the design, development, and testing of a free software implementation of the MAD technique using the open source DotSpatial geographic information system (GIS) framework, R statistical software, and the MODFLOW groundwater model. This new tool, dubbed MAD-GIS, is built using a modular architecture that supports the integration of external analytical tools and models for key computational processes including a forward model (e.g. MODFLOW, HYDRUS) and geostatistical analysis (e.g. R, GSLIB). The GIS-based graphical user interface provides a relatively simple way for new users of the technique to prepare the spatial domain, to identify observation and anchor points, to perform the MAD analysis using a selected forward model, and to view results. MAD-GIS uses the Managed Extensibility Framework (MEF) provided by the Microsoft .NET programming platform to support integration of different modeling and analytical tools at run-time through a custom "driver." Each driver establishes a connection with external programs through a programming interface, which provides the elements for communicating with core MAD software. This presentation gives an example of adapting the MODFLOW to serve as the external forward model in MAD-GIS for inferring the distribution functions of key MODFLOW parameters. Additional drivers for other models are being developed and it is expected that the open source nature of the project will engender the development of additional model drivers by 3rd party scientists.

Pilot testing of SHRP 2 reliability data and analytical products: Minnesota.

DOT National Transportation Integrated Search

2015-01-01

The Minnesota pilot site has undertaken an effort to test data and analytical tools developed through the Strategic Highway Research Program (SHRP) 2 Reliability focus area. The purpose of these tools is to facilitate the improvement of travel time r...

Freak oscillation in a dusty plasma.

PubMed

Zhang, Heng; Yang, Yang; Hong, Xue-Ren; Qi, Xin; Duan, Wen-Shan; Yang, Lei

2017-05-01

The freak oscillation in one-dimensional dusty plasma is studied numerically by particle-in-cell method. Using a perturbation method, the basic set of fluid equations is reduced to a nonlinear Schrödinger equation (NLSE). The rational solution of the NLSE is presented, which is proposed as an effective tool for studying the rogue waves in dusty plasma. Additionally, the application scope of the analytical solution of the rogue wave described by the NLSE is given.

The Empower project - a new way of assessing and monitoring test comparability and stability.

PubMed

De Grande, Linde A C; Goossens, Kenneth; Van Uytfanghe, Katleen; Stöckl, Dietmar; Thienpont, Linda M

2015-07-01

Manufacturers and laboratories might benefit from using a modern integrated tool for quality management/assurance. The tool should not be confounded by commutability issues and focus on the intrinsic analytical quality and comparability of assays as performed in routine laboratories. In addition, it should enable monitoring of long-term stability of performance, with the possibility to quasi "real-time" remedial action. Therefore, we developed the "Empower" project. The project comprises four pillars: (i) master comparisons with panels of frozen single-donation samples, (ii) monitoring of patient percentiles and (iii) internal quality control data, and (iv) conceptual and statistical education about analytical quality. In the pillars described here (i and ii), state-of-the-art as well as biologically derived specifications are used. In the 2014 master comparisons survey, 125 laboratories forming 8 peer groups participated. It showed not only good intrinsic analytical quality of assays but also assay biases/non-comparability. Although laboratory performance was mostly satisfactory, sometimes huge between-laboratory differences were observed. In patient percentile monitoring, currently, 100 laboratories participate with 182 devices. Particularly, laboratories with a high daily throughput and low patient population variation show a stable moving median in time with good between-instrument concordance. Shifts/drifts due to lot changes are sometimes revealed. There is evidence that outpatient medians mirror the calibration set-points shown in the master comparisons. The Empower project gives manufacturers and laboratories a realistic view on assay quality/comparability as well as stability of performance and/or the reasons for increased variation. Therefore, it is a modern tool for quality management/assurance toward improved patient care.

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

PubMed

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

SAM Methods Query

EPA Pesticide Factsheets

Laboratories measuring target chemical, radiochemical, pathogens, and biotoxin analytes in environmental samples can use this online query tool to identify analytical methods included in EPA's Selected Analytical Methods for Environmental Remediation

An introduction to joint research by the USEPA and USGS on ...

EPA Pesticide Factsheets

Improvements in analytical methodology have allowed low-level detection of an ever increasing number of pharmaceuticals, personal care products, hormones, pathogens and other contaminants of emerging concern (CECs). The use of these improved analytical tools has allowed researchers to document the global presence of CECs derived from a wide range of urban (e.g. wastewater treatment plants, onsite septic systems, landfills) and agricultural (e.g. livestock and crop production) sources. In addition, such research has documented that CECs are sufficiently mobile and persistent to be transported to all environmental compartments (e.g. surface water, stream bed sediment, groundwater, soil, tissue). This paper is an introduction to a series of papers being published in Science of the Total Environment

FPI: FM Success through Analytics

ERIC Educational Resources Information Center

Hickling, Duane

2013-01-01

The APPA Facilities Performance Indicators (FPI) is perhaps one of the most powerful analytical tools that institutional facilities professionals have at their disposal. It is a diagnostic facilities performance management tool that addresses the essential questions that facilities executives must answer to effectively perform their roles. It…

Experiments with Analytic Centers: A confluence of data, tools and help in using them.

NASA Astrophysics Data System (ADS)

Little, M. M.; Crichton, D. J.; Hines, K.; Cole, M.; Quam, B. M.

2017-12-01

Traditional repositories have been primarily focused on data stewardship. Over the past two decades, data scientists have attempted to overlay a superstructure to make these repositories more amenable to analysis tasks, with limited success. This poster will summarize lessons learned and some realizations regarding what it takes to create an analytic center. As the volume of Earth Science data grows and the sophistication of analytic tools improves, a pattern has emerged that indicates different science communities uniquely apply a selection of tools to the data to produce scientific results. Infrequently do the experiences of one group help steer other groups. How can the information technology community seed these domains with tools that conform to the thought processes and experiences of that particular science group? What types of succcessful technology infusions have occured and how does technology get adopted. AIST has been experimenting with the management of this analytic center process; this paper will summarize the results and indicate a direction for future infusion attempts.

Bibliometric mapping: eight decades of analytical chemistry, with special focus on the use of mass spectrometry.

PubMed

Waaijer, Cathelijn J F; Palmblad, Magnus

2015-01-01

In this Feature we use automatic bibliometric mapping tools to visualize the history of analytical chemistry from the 1920s until the present. In particular, we have focused on the application of mass spectrometry in different fields. The analysis shows major shifts in research focus and use of mass spectrometry. We conclude by discussing the application of bibliometric mapping and visualization tools in analytical chemists' research.

SAM Pathogen Methods Query

EPA Pesticide Factsheets

Laboratories measuring target pathogen analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select pathogens.

The role of analytical chemistry in Niger Delta petroleum exploration: a review.

PubMed

Akinlua, Akinsehinwa

2012-06-12

Petroleum and organic matter from which the petroleum is derived are composed of organic compounds with some trace elements. These compounds give an insight into the origin, thermal maturity and paleoenvironmental history of petroleum, which are essential elements in petroleum exploration. The main tool to acquire the geochemical data is analytical techniques. Due to progress in the development of new analytical techniques, many hitherto petroleum exploration problems have been resolved. Analytical chemistry has played a significant role in the development of petroleum resources of Niger Delta. Various analytical techniques that have aided the success of petroleum exploration in the Niger Delta are discussed. The analytical techniques that have helped to understand the petroleum system of the basin are also described. Recent and emerging analytical methodologies including green analytical methods as applicable to petroleum exploration particularly Niger Delta petroleum province are discussed in this paper. Analytical chemistry is an invaluable tool in finding the Niger Delta oils. Copyright © 2011 Elsevier B.V. All rights reserved.

Development of computer-based analytical tool for assessing physical protection system

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

Mardhi, Alim, E-mail: alim-m@batan.go.id; Chulalongkorn University, Faculty of Engineering, Nuclear Engineering Department, 254 Phayathai Road, Pathumwan, Bangkok Thailand. 10330; Pengvanich, Phongphaeth, E-mail: ppengvan@gmail.com

Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work,more » we have developed a computer–based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system’s detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.« less

Development of computer-based analytical tool for assessing physical protection system

NASA Astrophysics Data System (ADS)

Mardhi, Alim; Pengvanich, Phongphaeth

2016-01-01

Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work, we have developed a computer-based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system's detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.

Active controls: A look at analytical methods and associated tools

NASA Technical Reports Server (NTRS)

Newsom, J. R.; Adams, W. M., Jr.; Mukhopadhyay, V.; Tiffany, S. H.; Abel, I.

1984-01-01

A review of analytical methods and associated tools for active controls analysis and design problems is presented. Approaches employed to develop mathematical models suitable for control system analysis and/or design are discussed. Significant efforts have been expended to develop tools to generate the models from the standpoint of control system designers' needs and develop the tools necessary to analyze and design active control systems. Representative examples of these tools are discussed. Examples where results from the methods and tools have been compared with experimental data are also presented. Finally, a perspective on future trends in analysis and design methods is presented.

SAM Biotoxin Methods Query

EPA Pesticide Factsheets

Laboratories measuring target biotoxin analytes in environmental samples can use this online query tool to identify analytical methods included in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select biotoxins.

SAM Chemical Methods Query

EPA Pesticide Factsheets

Laboratories measuring target chemical, radiochemical, pathogens, and biotoxin analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery

Using Learning Analytics to Support Engagement in Collaborative Writing

ERIC Educational Resources Information Center

Liu, Ming; Pardo, Abelardo; Liu, Li

2017-01-01

Online collaborative writing tools provide an efficient way to complete a writing task. However, existing tools only focus on technological affordances and ignore the importance of social affordances in a collaborative learning environment. This article describes a learning analytic system that analyzes writing behaviors, and creates…

Application of Learning Analytics Using Clustering Data Mining for Students' Disposition Analysis

ERIC Educational Resources Information Center

Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay

2018-01-01

Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…

Seeing is believing: on the use of image databases for visually exploring plant organelle dynamics.

PubMed

Mano, Shoji; Miwa, Tomoki; Nishikawa, Shuh-ichi; Mimura, Tetsuro; Nishimura, Mikio

2009-12-01

Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

ERIC Educational Resources Information Center

Kelly, Nick; Thompson, Kate; Yeoman, Pippa

2015-01-01

This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…

[Progress in the application of laser ablation ICP-MS to surface microanalysis in material science].

PubMed

Zhang, Yong; Jia, Yun-hai; Chen, Ji-wen; Shen, Xue-jing; Liu, Ying; Zhao, Leiz; Li, Dong-ling; Hang, Peng-cheng; Zhao, Zhen; Fan, Wan-lun; Wang, Hai-zhou

2014-08-01

In the present paper, apparatus and theory of surface analysis is introduced, and the progress in the application of laser ablation ICP-MS to microanalysis in ferrous, nonferrous and semiconductor field is reviewed in detail. Compared with traditional surface analytical tools, such as SEM/EDS (scanning electron microscopy/energy dispersive spectrum), EPMA (electron probe microanalysis analysis), AES (auger energy spectrum), etc. the advantage is little or no sample preparation, adjustable spatial resolution according to analytical demand, multi-element analysis and high sensitivity. It is now a powerful complementary method to traditional surface analytical tool. With the development of LA-ICP-MS technology maturing, more and more analytical workers will use this powerful tool in the future, and LA-ICP-MS will be a super star in elemental analysis field just like LIBS (Laser-induced breakdown spectroscopy).

GenomicTools: a computational platform for developing high-throughput analytics in genomics.

PubMed

Tsirigos, Aristotelis; Haiminen, Niina; Bilal, Erhan; Utro, Filippo

2012-01-15

Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines. We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage. The GenomicTools platform (version 2.0.0) was implemented in C++. The source code, documentation, user manual, example datasets and scripts are available online at http://code.google.com/p/ibm-cbc-genomic-tools.

BIRCH: a user-oriented, locally-customizable, bioinformatics system.

PubMed

Fristensky, Brian

2007-02-09

Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. BIRCH (Biological Research Computing Hierarchy) is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment) graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere.

BIRCH: A user-oriented, locally-customizable, bioinformatics system

PubMed Central

Fristensky, Brian

2007-01-01

Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy) is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment) graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere. PMID:17291351

Parallel Aircraft Trajectory Optimization with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Falck, Robert D.; Gray, Justin S.; Naylor, Bret

2016-01-01

Trajectory optimization is an integral component for the design of aerospace vehicles, but emerging aircraft technologies have introduced new demands on trajectory analysis that current tools are not well suited to address. Designing aircraft with technologies such as hybrid electric propulsion and morphing wings requires consideration of the operational behavior as well as the physical design characteristics of the aircraft. The addition of operational variables can dramatically increase the number of design variables which motivates the use of gradient based optimization with analytic derivatives to solve the larger optimization problems. In this work we develop an aircraft trajectory analysis tool using a Legendre-Gauss-Lobatto based collocation scheme, providing analytic derivatives via the OpenMDAO multidisciplinary optimization framework. This collocation method uses an implicit time integration scheme that provides a high degree of sparsity and thus several potential options for parallelization. The performance of the new implementation was investigated via a series of single and multi-trajectory optimizations using a combination of parallel computing and constraint aggregation. The computational performance results show that in order to take full advantage of the sparsity in the problem it is vital to parallelize both the non-linear analysis evaluations and the derivative computations themselves. The constraint aggregation results showed a significant numerical challenge due to difficulty in achieving tight convergence tolerances. Overall, the results demonstrate the value of applying analytic derivatives to trajectory optimization problems and lay the foundation for future application of this collocation based method to the design of aircraft with where operational scheduling of technologies is key to achieving good performance.

Total analysis systems with Thermochromic Etching Discs technology.

PubMed

Avella-Oliver, Miquel; Morais, Sergi; Carrascosa, Javier; Puchades, Rosa; Maquieira, Ángel

2014-12-16

A new analytical system based on Thermochromic Etching Discs (TED) technology is presented. TED comprises a number of attractive features such as track independency, selective irradiation, a high power laser, and the capability to create useful assay platforms. The analytical versatility of this tool opens up a wide range of possibilities to design new compact disc-based total analysis systems applicable in chemistry and life sciences. In this paper, TED analytical implementation is described and discussed, and their analytical potential is supported by several applications. Microarray immunoassay, immunofiltration assay, solution measurement, and cell culture approaches are herein addressed in order to demonstrate the practical capacity of this system. The analytical usefulness of TED technology is herein demonstrated, describing how to exploit this tool for developing truly integrated analytical systems that provide solutions within the point of care framework.

Can the analyte-triggered asymmetric autocatalytic Soai reaction serve as a universal analytical tool for measuring enantiopurity and assigning absolute configuration?

PubMed

Welch, Christopher J; Zawatzky, Kerstin; Makarov, Alexey A; Fujiwara, Satoshi; Matsumoto, Arimasa; Soai, Kenso

2016-12-20

An investigation is reported on the use of the autocatalytic enantioselective Soai reaction, known to be influenced by the presence of a wide variety of chiral materials, as a generic tool for measuring the enantiopurity and absolute configuration of any substance. Good generality for the reaction across a small group of test analytes was observed, consistent with literature reports suggesting a diversity of compound types that can influence the stereochemical outcome of this reaction. Some trends in the absolute sense of stereochemical enrichment were noted, suggesting the possible utility of the approach for assigning absolute configuration to unknown compounds, by analogy to closely related species with known outcomes. Considerable variation was observed in the triggering strength of different enantiopure materials, an undesirable characteristic when dealing with mixtures containing minor impurities with strong triggering strength in the presence of major components with weak triggering strength. A strong tendency of the reaction toward an 'all or none' type of behavior makes the reaction most sensitive for detecting enantioenrichment close to zero. Consequently, the ability to discern modest from excellent enantioselectivity was relatively poor. While these properties limit the ability to obtain precise enantiopurity measurements in a simple single addition experiment, prospects may exist for more complex experimental setups that may potentially offer improved performance.

UV-Vis as quantification tool for solubilized lignin following a single-shot steam process.

PubMed

Lee, Roland A; Bédard, Charles; Berberi, Véronique; Beauchet, Romain; Lavoie, Jean-Michel

2013-09-01

In this short communication, UV/Vis was used as an analytical tool for the quantification of lignin concentrations in aqueous mediums. A significant correlation was determined between absorbance and concentration of lignin in solution. For this study, lignin was produced from different types of biomasses (willow, aspen, softwood, canary grass and hemp) using steam processes. Quantification was performed at 212, 225, 237, 270, 280 and 287 nm. UV-Vis quantification of lignin was found suitable for different types of biomass making this a timesaving analytical system that could lead to uses as Process Analytical Tool (PAT) in biorefineries utilizing steam processes or comparable approaches. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nucleic acid tool enzymes-aided signal amplification strategy for biochemical analysis: status and challenges.

PubMed

Qing, Taiping; He, Dinggeng; He, Xiaoxiao; Wang, Kemin; Xu, Fengzhou; Wen, Li; Shangguan, Jingfang; Mao, Zhengui; Lei, Yanli

2016-04-01

Owing to their highly efficient catalytic effects and substrate specificity, the nucleic acid tool enzymes are applied as 'nano-tools' for manipulating different nucleic acid substrates both in the test-tube and in living organisms. In addition to the function as molecular scissors and molecular glue in genetic engineering, the application of nucleic acid tool enzymes in biochemical analysis has also been extensively developed in the past few decades. Used as amplifying labels for biorecognition events, the nucleic acid tool enzymes are mainly applied in nucleic acids amplification sensing, as well as the amplification sensing of biorelated variations of nucleic acids. With the introduction of aptamers, which can bind different target molecules, the nucleic acid tool enzymes-aided signal amplification strategies can also be used to sense non-nucleic targets (e.g., ions, small molecules, proteins, and cells). This review describes and discusses the amplification strategies of nucleic acid tool enzymes-aided biosensors for biochemical analysis applications. Various analytes, including nucleic acids, ions, small molecules, proteins, and cells, are reviewed briefly. This work also addresses the future trends and outlooks for signal amplification in nucleic acid tool enzymes-aided biosensors.

Deriving Earth Science Data Analytics Requirements

NASA Technical Reports Server (NTRS)

Kempler, Steven J.

2015-01-01

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

Ultramicroelectrode Array Based Sensors: A Promising Analytical Tool for Environmental Monitoring

PubMed Central

Orozco, Jahir; Fernández-Sánchez, César; Jiménez-Jorquera, Cecilia

2010-01-01

The particular analytical performance of ultramicroelectrode arrays (UMEAs) has attracted a high interest by the research community and has led to the development of a variety of electroanalytical applications. UMEA-based approaches have demonstrated to be powerful, simple, rapid and cost-effective analytical tools for environmental analysis compared to available conventional electrodes and standardised analytical techniques. An overview of the fabrication processes of UMEAs, their characterization and applications carried out by the Spanish scientific community is presented. A brief explanation of theoretical aspects that highlight their electrochemical behavior is also given. Finally, the applications of this transducer platform in the environmental field are discussed. PMID:22315551

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2014 CFR

2014-01-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2013 CFR

2013-07-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2012 CFR

2012-01-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

(Re)braiding to Tell: Using "Trenzas" as a Metaphorical-Analytical Tool in Qualitative Research

ERIC Educational Resources Information Center

Quiñones, Sandra

2016-01-01

Metaphors can be used in qualitative research to illuminate the meanings of participant experiences and examine phenomena from insightful and creative perspectives. The purpose of this paper is to illustrate how I utilized "trenzas" (braids) as a metaphorical and analytical tool for understanding the experiences and perspectives of…

Feasibility model of a high reliability five-year tape transport. Volume 3: Appendices. [detailed drawing and analytical tools used in analyses

NASA Technical Reports Server (NTRS)

Meyers, A. P.; Davidson, W. A.; Gortowski, R. C.

1973-01-01

Detailed drawings of the five year tape transport are presented. Analytical tools used in the various analyses are described. These analyses include: tape guidance, tape stress over crowned rollers, tape pack stress program, response (computer) program, and control system electronics description.

Challenges and Opportunities in Analysing Students Modelling

ERIC Educational Resources Information Center

Blanco-Anaya, Paloma; Justi, Rosária; Díaz de Bustamante, Joaquín

2017-01-01

Modelling-based teaching activities have been designed and analysed from distinct theoretical perspectives. In this paper, we use one of them--the model of modelling diagram (MMD)--as an analytical tool in a regular classroom context. This paper examines the challenges that arise when the MMD is used as an analytical tool to characterise the…

Equity Analytics: A Methodological Approach for Quantifying Participation Patterns in Mathematics Classroom Discourse

ERIC Educational Resources Information Center

Reinholz, Daniel L.; Shah, Niral

2018-01-01

Equity in mathematics classroom discourse is a pressing concern, but analyzing issues of equity using observational tools remains a challenge. In this article, we propose equity analytics as a quantitative approach to analyzing aspects of equity and inequity in classrooms. We introduce a classroom observation tool that focuses on relatively…

Comprehensive data resources and analytical tools for pathological association of aminoacyl tRNA synthetases with cancer

PubMed Central

Lee, Ji-Hyun; You, Sungyong; Hyeon, Do Young; Kang, Byeongsoo; Kim, Hyerim; Park, Kyoung Mii; Han, Byungwoo; Hwang, Daehee; Kim, Sunghoon

2015-01-01

Mammalian cells have cytoplasmic and mitochondrial aminoacyl-tRNA synthetases (ARSs) that catalyze aminoacylation of tRNAs during protein synthesis. Despite their housekeeping functions in protein synthesis, recently, ARSs and ARS-interacting multifunctional proteins (AIMPs) have been shown to play important roles in disease pathogenesis through their interactions with disease-related molecules. However, there are lacks of data resources and analytical tools that can be used to examine disease associations of ARS/AIMPs. Here, we developed an Integrated Database for ARSs (IDA), a resource database including cancer genomic/proteomic and interaction data of ARS/AIMPs. IDA includes mRNA expression, somatic mutation, copy number variation and phosphorylation data of ARS/AIMPs and their interacting proteins in various cancers. IDA further includes an array of analytical tools for exploration of disease association of ARS/AIMPs, identification of disease-associated ARS/AIMP interactors and reconstruction of ARS-dependent disease-perturbed network models. Therefore, IDA provides both comprehensive data resources and analytical tools for understanding potential roles of ARS/AIMPs in cancers. Database URL: http://ida.biocon.re.kr/, http://ars.biocon.re.kr/ PMID:25824651

Analytical Web Tool for CERES Products

NASA Astrophysics Data System (ADS)

Mitrescu, C.; Chu, C.; Doelling, D.

2012-12-01

The CERES project provides the community climate quality observed TOA fluxes, consistent cloud properties, and computed profile and surface fluxes. The 11-year long data set proves invaluable for remote sensing and climate modeling communities for annual global mean energy, meridianal heat transport, consistent cloud and fluxes and climate trends studies. Moreover, a broader audience interested in Earth's radiative properties such as green energy, health and environmental companies have showed their interest in CERES derived products. A few years ago, the CERES team start developing a new web-based Ordering Tool tailored for this wide diversity of users. Recognizing the potential that web-2.0 technologies can offer to both Quality Control (QC) and scientific data visualization and manipulation, the CERES team began introducing a series of specialized functions that addresses the above. As such, displaying an attractive, easy to use modern web-based format, the Ordering Tool added the following analytical functions: i) 1-D Histograms to display the distribution of the data field to identify outliers that are useful for QC purposes; ii) an "Anomaly" map that shows the regional differences between the current month and the climatological monthly mean; iii) a 2-D Histogram that can identify either potential problems with the data (i.e. QC function) or provides a global view of trends and/or correlations between various CERES flux, cloud, aerosol, and atmospheric properties. The large volume and diversity of data, together with the on-the-fly execution were the main challenges that had to be tackle with. Depending on the application, the execution was done on either the browser side or the server side with the help of auxiliary files. Additional challenges came from the use of various open source applications, the multitude of CERES products and the seamless transition from previous development. For the future, we plan on expanding the analytical capabilities of the Ordering Tool and add/combine more CERES products to meet the growing data demand.

Entanglement and Wigner Function Negativity of Multimode Non-Gaussian States

NASA Astrophysics Data System (ADS)

Walschaers, Mattia; Fabre, Claude; Parigi, Valentina; Treps, Nicolas

2017-11-01

Non-Gaussian operations are essential to exploit the quantum advantages in optical continuous variable quantum information protocols. We focus on mode-selective photon addition and subtraction as experimentally promising processes to create multimode non-Gaussian states. Our approach is based on correlation functions, as is common in quantum statistical mechanics and condensed matter physics, mixed with quantum optics tools. We formulate an analytical expression of the Wigner function after the subtraction or addition of a single photon, for arbitrarily many modes. It is used to demonstrate entanglement properties specific to non-Gaussian states and also leads to a practical and elegant condition for Wigner function negativity. Finally, we analyze the potential of photon addition and subtraction for an experimentally generated multimode Gaussian state.

Entanglement and Wigner Function Negativity of Multimode Non-Gaussian States.

PubMed

Walschaers, Mattia; Fabre, Claude; Parigi, Valentina; Treps, Nicolas

2017-11-03

Non-Gaussian operations are essential to exploit the quantum advantages in optical continuous variable quantum information protocols. We focus on mode-selective photon addition and subtraction as experimentally promising processes to create multimode non-Gaussian states. Our approach is based on correlation functions, as is common in quantum statistical mechanics and condensed matter physics, mixed with quantum optics tools. We formulate an analytical expression of the Wigner function after the subtraction or addition of a single photon, for arbitrarily many modes. It is used to demonstrate entanglement properties specific to non-Gaussian states and also leads to a practical and elegant condition for Wigner function negativity. Finally, we analyze the potential of photon addition and subtraction for an experimentally generated multimode Gaussian state.

Database and Analytical Tool Development for the Management of Data Derived from US DOE (NETL) Funded Fine Particulate (PM2.5) Research

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

Robinson Khosah

2007-07-31

Advanced Technology Systems, Inc. (ATS) was contracted by the U. S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) to develop a state-of-the-art, scalable and robust web-accessible database application to manage the extensive data sets resulting from the DOE-NETL-sponsored ambient air monitoring programs in the upper Ohio River valley region. The data management system was designed to include a web-based user interface that will allow easy access to the data by the scientific community, policy- and decision-makers, and other interested stakeholders, while providing detailed information on sampling, analytical and quality control parameters. In addition, the system will provide graphical analyticalmore » tools for displaying, analyzing and interpreting the air quality data. The system will also provide multiple report generation capabilities and easy-to-understand visualization formats that can be utilized by the media and public outreach/educational institutions. The project was conducted in two phases. Phase One included the following tasks: (1) data inventory/benchmarking, including the establishment of an external stakeholder group; (2) development of a data management system; (3) population of the database; (4) development of a web-based data retrieval system, and (5) establishment of an internal quality assurance/quality control system on data management. Phase Two involved the development of a platform for on-line data analysis. Phase Two included the following tasks: (1) development of a sponsor and stakeholder/user website with extensive online analytical tools; (2) development of a public website; (3) incorporation of an extensive online help system into each website; and (4) incorporation of a graphical representation (mapping) system into each website. The project is now technically completed.« less

Estimation of the limit of detection using information theory measures.

PubMed

Fonollosa, Jordi; Vergara, Alexander; Huerta, Ramón; Marco, Santiago

2014-01-31

Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise. Copyright © 2013 Elsevier B.V. All rights reserved.

Quality Indicators for Learning Analytics

ERIC Educational Resources Information Center

Scheffel, Maren; Drachsler, Hendrik; Stoyanov, Slavi; Specht, Marcus

2014-01-01

This article proposes a framework of quality indicators for learning analytics that aims to standardise the evaluation of learning analytics tools and to provide a mean to capture evidence for the impact of learning analytics on educational practices in a standardised manner. The criteria of the framework and its quality indicators are based on…

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

NASA Technical Reports Server (NTRS)

Kempler, Steven; Barbieri, Lindsay

2016-01-01

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

Development of the Veritas plot and its application in cardiac surgery: an evidence-synthesis graphic tool for the clinician to assess multiple meta-analyses reporting on a common outcome.

PubMed

Panesar, Sukhmeet S; Rao, Christopher; Vecht, Joshua A; Mirza, Saqeb B; Netuveli, Gopalakrishnan; Morris, Richard; Rosenthal, Joe; Darzi, Ara; Athanasiou, Thanos

2009-10-01

Meta-analyses may be prone to generating misleading results because of a paucity of experimental studies (especially in surgery); publication bias; and heterogeneity in study design, intervention and the patient population of included studies. When investigating a specific clinical or scientific question on which several relevant meta-analyses may have been published, value judgments must be applied to determine which analysis represents the most robust evidence. These value judgments should be specifically acknowledged. We designed the Veritas plot to explicitly explore important elements of quality and to facilitate decision-making by highlighting specific areas in which meta-analyses are found to be deficient. Furthermore, as a graphic tool, it may be more intuitive than when similar data are presented in a tabular or text format. The Veritas plot is an adaption of the radar plot, a graphic tool for the description of multiattribute data. Key elements of meta-analytical quality such as heterogeneity, publication bias and study design are assessed. Existing qualitative methods such as the Assessment of Multiple Systematic Reviews (AMSTAR) tool have been incorporated in addition to important considerations when interpreting surgical meta-analyses such as the year of publication and population characteristics. To demonstrate the potential of the Veritas plot to inform clinical practice, we apply the Veritas plot to the meta-analytical literature comparing the incidence of 30-day stroke in off-pump coronary artery bypass surgery and conventional coronary artery bypass surgery. We demonstrate that a visually-stimulating and practical evidence-synthesis tool can direct the clinician and scientist to a particular meta-analytical study to inform clinical practice. The Veritas plot is also cumulative and allowed us to assess the quality of evidence over time. We have presented a practical graphic application for scientists and clinicians to identify and interpret variability in meta-analyses. Although further validation of the Veritas plot is required, it may have the potential to contribute to the implementation of evidence-based practice.

Chemometrics-based process analytical technology (PAT) tools: applications and adaptation in pharmaceutical and biopharmaceutical industries.

PubMed

Challa, Shruthi; Potumarthi, Ravichandra

2013-01-01

Process analytical technology (PAT) is used to monitor and control critical process parameters in raw materials and in-process products to maintain the critical quality attributes and build quality into the product. Process analytical technology can be successfully implemented in pharmaceutical and biopharmaceutical industries not only to impart quality into the products but also to prevent out-of-specifications and improve the productivity. PAT implementation eliminates the drawbacks of traditional methods which involves excessive sampling and facilitates rapid testing through direct sampling without any destruction of sample. However, to successfully adapt PAT tools into pharmaceutical and biopharmaceutical environment, thorough understanding of the process is needed along with mathematical and statistical tools to analyze large multidimensional spectral data generated by PAT tools. Chemometrics is a chemical discipline which incorporates both statistical and mathematical methods to obtain and analyze relevant information from PAT spectral tools. Applications of commonly used PAT tools in combination with appropriate chemometric method along with their advantages and working principle are discussed. Finally, systematic application of PAT tools in biopharmaceutical environment to control critical process parameters for achieving product quality is diagrammatically represented.

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

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

T.Rex

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

2016-06-08

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

Evaluating Business Intelligence/Business Analytics Software for Use in the Information Systems Curriculum

ERIC Educational Resources Information Center

Davis, Gary Alan; Woratschek, Charles R.

2015-01-01

Business Intelligence (BI) and Business Analytics (BA) Software has been included in many Information Systems (IS) curricula. This study surveyed current and past undergraduate and graduate students to evaluate various BI/BA tools. Specifically, this study compared several software tools from two of the major software providers in the BI/BA field.…

Analytical model for advective-dispersive transport involving flexible boundary inputs, initial distributions and zero-order productions

NASA Astrophysics Data System (ADS)

Chen, Jui-Sheng; Li, Loretta Y.; Lai, Keng-Hsin; Liang, Ching-Ping

2017-11-01

A novel solution method is presented which leads to an analytical model for the advective-dispersive transport in a semi-infinite domain involving a wide spectrum of boundary inputs, initial distributions, and zero-order productions. The novel solution method applies the Laplace transform in combination with the generalized integral transform technique (GITT) to obtain the generalized analytical solution. Based on this generalized analytical expression, we derive a comprehensive set of special-case solutions for some time-dependent boundary distributions and zero-order productions, described by the Dirac delta, constant, Heaviside, exponentially-decaying, or periodically sinusoidal functions as well as some position-dependent initial conditions and zero-order productions specified by the Dirac delta, constant, Heaviside, or exponentially-decaying functions. The developed solutions are tested against an analytical solution from the literature. The excellent agreement between the analytical solutions confirms that the new model can serve as an effective tool for investigating transport behaviors under different scenarios. Several examples of applications, are given to explore transport behaviors which are rarely noted in the literature. The results show that the concentration waves resulting from the periodically sinusoidal input are sensitive to dispersion coefficient. The implication of this new finding is that a tracer test with a periodic input may provide additional information when for identifying the dispersion coefficients. Moreover, the solution strategy presented in this study can be extended to derive analytical models for handling more complicated problems of solute transport in multi-dimensional media subjected to sequential decay chain reactions, for which analytical solutions are not currently available.

Ultra-sensitive chemical and biological analysis via specialty fibers with built-in microstructured optofluidic channels.

PubMed

Zhang, Nan; Li, Kaiwei; Cui, Ying; Wu, Zhifang; Shum, Perry Ping; Auguste, Jean-Louis; Dinh, Xuan Quyen; Humbert, Georges; Wei, Lei

2018-02-13

All-in-fiber optofluidics is an analytical tool that provides enhanced sensing performance with simplified analyzing system design. Currently, its advance is limited either by complicated liquid manipulation and light injection configuration or by low sensitivity resulting from inadequate light-matter interaction. In this work, we design and fabricate a side-channel photonic crystal fiber (SC-PCF) and exploit its versatile sensing capabilities in in-line optofluidic configurations. The built-in microfluidic channel of the SC-PCF enables strong light-matter interaction and easy lateral access of liquid samples in these analytical systems. In addition, the sensing performance of the SC-PCF is demonstrated with methylene blue for absorptive molecular detection and with human cardiac troponin T protein by utilizing a Sagnac interferometry configuration for ultra-sensitive and specific biomolecular specimen detection. Owing to the features of great flexibility and compactness, high-sensitivity to the analyte variation, and efficient liquid manipulation/replacement, the demonstrated SC-PCF offers a generic solution to be adapted to various fiber-waveguide sensors to detect a wide range of analytes in real time, especially for applications from environmental monitoring to biological diagnosis.

MALDI-TOF MS identification of anaerobic bacteria: assessment of pre-analytical variables and specimen preparation techniques.

PubMed

Hsu, Yen-Michael S; Burnham, Carey-Ann D

2014-06-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a tool for identifying clinically relevant anaerobes. We evaluated the analytical performance characteristics of the Bruker Microflex with Biotyper 3.0 software system for identification of anaerobes and examined the impact of direct formic acid (FA) treatment and other pre-analytical factors on MALDI-TOF MS performance. A collection of 101 anaerobic bacteria were evaluated, including Clostridium spp., Propionibacterium spp., Fusobacterium spp., Bacteroides spp., and other anaerobic bacterial of clinical relevance. The results of our study indicate that an on-target extraction with 100% FA improves the rate of accurate identification without introducing misidentification (P<0.05). In addition, we modify the reporting cutoffs for the Biotyper "score" yielding acceptable identification. We found that a score of ≥1.700 can maximize the rate of identification. Of interest, MALDI-TOF MS can correctly identify anaerobes grown in suboptimal conditions, such as on selective culture media and following oxygen exposure. In conclusion, we report on a number of simple and cost-effective pre- and post-analytical modifications could enhance MALDI-TOF MS identification for anaerobic bacteria. Copyright © 2014 Elsevier Inc. All rights reserved.

Analytical methods in sphingolipidomics: Quantitative and profiling approaches in food analysis.

PubMed

Canela, Núria; Herrero, Pol; Mariné, Sílvia; Nadal, Pedro; Ras, Maria Rosa; Rodríguez, Miguel Ángel; Arola, Lluís

2016-01-08

In recent years, sphingolipidomics has emerged as an interesting omic science that encompasses the study of the full sphingolipidome characterization, content, structure and activity in cells, tissues or organisms. Like other omics, it has the potential to impact biomarker discovery, drug development and systems biology knowledge. Concretely, dietary food sphingolipids have gained considerable importance due to their extensively reported bioactivity. Because of the complexity of this lipid family and their diversity among foods, powerful analytical methodologies are needed for their study. The analytical tools developed in the past have been improved with the enormous advances made in recent years in mass spectrometry (MS) and chromatography, which allow the convenient and sensitive identification and quantitation of sphingolipid classes and form the basis of current sphingolipidomics methodologies. In addition, novel hyphenated nuclear magnetic resonance (NMR) strategies, new ionization strategies, and MS imaging are outlined as promising technologies to shape the future of sphingolipid analyses. This review traces the analytical methods of sphingolipidomics in food analysis concerning sample extraction, chromatographic separation, the identification and quantification of sphingolipids by MS and their structural elucidation by NMR. Copyright © 2015 Elsevier B.V. All rights reserved.

Look@NanoSIMS--a tool for the analysis of nanoSIMS data in environmental microbiology.

PubMed

Polerecky, Lubos; Adam, Birgit; Milucka, Jana; Musat, Niculina; Vagner, Tomas; Kuypers, Marcel M M

2012-04-01

We describe an open-source freeware programme for high throughput analysis of nanoSIMS (nanometre-scale secondary ion mass spectrometry) data. The programme implements basic data processing and analytical functions, including display and drift-corrected accumulation of scanned planes, interactive and semi-automated definition of regions of interest (ROIs), and export of the ROIs' elemental and isotopic composition in graphical and text-based formats. Additionally, the programme offers new functions that were custom-designed to address the needs of environmental microbiologists. Specifically, it allows manual and automated classification of ROIs based on the information that is derived either from the nanoSIMS dataset itself (e.g. from labelling achieved by halogen in situ hybridization) or is provided externally (e.g. as a fluorescence in situ hybridization image). Moreover, by implementing post-processing routines coupled to built-in statistical tools, the programme allows rapid synthesis and comparative analysis of results from many different datasets. After validation of the programme, we illustrate how these new processing and analytical functions increase flexibility, efficiency and depth of the nanoSIMS data analysis. Through its custom-made and open-source design, the programme provides an efficient, reliable and easily expandable tool that can help a growing community of environmental microbiologists and researchers from other disciplines process and analyse their nanoSIMS data. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Numerical modelling of orthogonal cutting: application to woodworking with a bench plane.

PubMed

Nairn, John A

2016-06-06

A numerical model for orthogonal cutting using the material point method was applied to woodcutting using a bench plane. The cutting process was modelled by accounting for surface energy associated with wood fracture toughness for crack growth parallel to the grain. By using damping to deal with dynamic crack propagation and modelling all contact between wood and the plane, simulations could initiate chip formation and proceed into steady-state chip propagation including chip curling. Once steady-state conditions were achieved, the cutting forces became constant and could be determined as a function of various simulation variables. The modelling details included a cutting tool, the tool's rake and grinding angles, a chip breaker, a base plate and a mouth opening between the base plate and the tool. The wood was modelled as an anisotropic elastic-plastic material. The simulations were verified by comparison to an analytical model and then used to conduct virtual experiments on wood planing. The virtual experiments showed interactions between depth of cut, chip breaker location and mouth opening. Additional simulations investigated the role of tool grinding angle, tool sharpness and friction.

IBM's Health Analytics and Clinical Decision Support.

PubMed

Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W

2014-08-15

This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.

Nanomaterial-Based Sensing and Biosensing of Phenolic Compounds and Related Antioxidant Capacity in Food.

PubMed

Della Pelle, Flavio; Compagnone, Dario

2018-02-04

Polyphenolic compounds (PCs) have received exceptional attention at the end of the past millennium and as much at the beginning of the new one. Undoubtedly, these compounds in foodstuffs provide added value for their well-known health benefits, for their technological role and also marketing. Many efforts have been made to provide simple, effective and user friendly analytical methods for the determination and antioxidant capacity (AOC) evaluation of food polyphenols. In a parallel track, over the last twenty years, nanomaterials (NMs) have made their entry in the analytical chemistry domain; NMs have, in fact, opened new paths for the development of analytical methods with the common aim to improve analytical performance and sustainability, becoming new tools in quality assurance of food and beverages. The aim of this review is to provide information on the most recent developments of new NMs-based tools and strategies for total polyphenols (TP) determination and AOC evaluation in food. In this review optical, electrochemical and bioelectrochemical approaches have been reviewed. The use of nanoparticles, quantum dots, carbon nanomaterials and hybrid materials for the detection of polyphenols is the main subject of the works reported. However, particular attention has been paid to the success of the application in real samples, in addition to the NMs. In particular, the discussion has been focused on methods/devices presenting, in the opinion of the authors, clear advancement in the fields, in terms of simplicity, rapidity and usability. This review aims to demonstrate how the NM-based approaches represent valid alternatives to classical methods for polyphenols analysis, and are mature to be integrated for the rapid quality assessment of food quality in lab or directly in the field.

Nanomaterial-Based Sensing and Biosensing of Phenolic Compounds and Related Antioxidant Capacity in Food

PubMed Central

2018-01-01

Polyphenolic compounds (PCs) have received exceptional attention at the end of the past millennium and as much at the beginning of the new one. Undoubtedly, these compounds in foodstuffs provide added value for their well-known health benefits, for their technological role and also marketing. Many efforts have been made to provide simple, effective and user friendly analytical methods for the determination and antioxidant capacity (AOC) evaluation of food polyphenols. In a parallel track, over the last twenty years, nanomaterials (NMs) have made their entry in the analytical chemistry domain; NMs have, in fact, opened new paths for the development of analytical methods with the common aim to improve analytical performance and sustainability, becoming new tools in quality assurance of food and beverages. The aim of this review is to provide information on the most recent developments of new NMs-based tools and strategies for total polyphenols (TP) determination and AOC evaluation in food. In this review optical, electrochemical and bioelectrochemical approaches have been reviewed. The use of nanoparticles, quantum dots, carbon nanomaterials and hybrid materials for the detection of polyphenols is the main subject of the works reported. However, particular attention has been paid to the success of the application in real samples, in addition to the NMs. In particular, the discussion has been focused on methods/devices presenting, in the opinion of the authors, clear advancement in the fields, in terms of simplicity, rapidity and usability. This review aims to demonstrate how the NM-based approaches represent valid alternatives to classical methods for polyphenols analysis, and are mature to be integrated for the rapid quality assessment of food quality in lab or directly in the field. PMID:29401719

Harnessing Scientific Literature Reports for Pharmacovigilance

PubMed Central

Ripple, Anna; Tonning, Joseph; Munoz, Monica; Hasan, Rashedul; Ly, Thomas; Francis, Henry; Bodenreider, Olivier

2017-01-01

Summary Objectives We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers’ capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. Methods A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. Results All usability test participants cited the tool’s ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool’s automated literature search relative to a manual ‘all fields’ PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. Conclusions Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction. PMID:28326432

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Understanding Emotions as Situated, Embodied, and Fissured: Thinking with Theory to Create an Analytical Tool

ERIC Educational Resources Information Center

Kuby, Candace R.

2014-01-01

An emerging theoretical perspective is that emotions are a verb or something we do in relation to others. Studies that demonstrate ways to analyze emotions from a performative stance are scarce. In this article, a new analytical tool is introduced; a critical performative analysis of emotion (CPAE) that draws upon three theoretical perspectives:…

Analytical Tools for Affordability Analysis

DTIC Science & Technology

2015-05-01

function (Womer)  Unit cost as a function of learning and rate  Learning with forgetting (Benkard)  Learning depreciates over time  Discretionary...Analytical Tools for Affordability Analysis David Tate Cost Analysis and Research Division Institute for Defense Analyses Report Documentation...ES) Institute for Defense Analyses, Cost Analysis and Research Division,4850 Mark Center Drive,Alexandria,VA,22311-1882 8. PERFORMING ORGANIZATION

Operational Analysis of Time-Optimal Maneuvering for Imaging Spacecraft

DTIC Science & Technology

2013-03-01

imaging spacecraft. The analysis is facilitated through the use of AGI’s Systems Tool Kit ( STK ) software. An Analytic Hierarchy Process (AHP)-based...the Singapore-developed X-SAT imaging spacecraft. The analysis is facilitated through the use of AGI’s Systems Tool Kit ( STK ) software. An Analytic...89  B.  FUTURE WORK................................................................................. 90  APPENDIX A. STK DATA AND BENEFIT

Social Capital: An Analytical Tool for Exploring Lifelong Learning and Community Development. CRLRA Discussion Paper.

ERIC Educational Resources Information Center

Kilpatrick, Sue; Field, John; Falk, Ian

The possibility of using the concept of social capital as an analytical tool for exploring lifelong learning and community development was examined. The following were among the topics considered: (1) differences between definitions of the concept of social capital that are based on collective benefit and those that define social capital as a…

The Metaphorical Department Head: Using Metaphors as Analytic Tools to Investigate the Role of Department Head

ERIC Educational Resources Information Center

Paranosic, Nikola; Riveros, Augusto

2017-01-01

This paper reports the results of a study that examined the ways a group of department heads in Ontario, Canada, describe their role. Despite their ubiquity and importance, department heads have been seldom investigated in the educational leadership literature. The study uses the metaphor as an analytic tool to examine the ways participants talked…

Analytical Tools for Behavioral Influences Operations

DTIC Science & Technology

2003-12-01

NASIC’s Investment in Analytical Capabilities ....................................................... 56 6.2 Study Limitations...get started. This project is envisioned as a foundation for future work by NASIC analysts. They will use the tools identified in this study to...capabilities Though this study took all three categories into account, most (90%) of the focus for the SRA team’s effort was on identifying and analyzing

Infrared Spectroscopy as a Chemical Fingerprinting Tool

NASA Technical Reports Server (NTRS)

Huff, Timothy L.

2003-01-01

Infrared (IR) spectroscopy is a powerful analytical tool in the chemical fingerprinting of materials. Any sample material that will interact with infrared light produces a spectrum and, although normally associated with organic materials, inorganic compounds may also be infrared active. The technique is rapid, reproducible and usually non-invasive to the sample. That it is non-invasive allows for additional characterization of the original material using other analytical techniques including thermal analysis and RAMAN spectroscopic techniques. With the appropriate accessories, the technique can be used to examine samples in liquid, solid or gas phase. Both aqueous and non-aqueous free-flowing solutions can be analyzed, as can viscous liquids such as heavy oils and greases. Solid samples of varying sizes and shapes may also be examined and with the addition of microscopic IR (microspectroscopy) capabilities, minute materials such as single fibers and threads may be analyzed. With the addition of appropriate software, microspectroscopy can be used for automated discrete point or compositional surface area mapping, with the latter providing a means to record changes in the chemical composition of a material surface over a defined area. Due to the ability to characterize gaseous samples, IR spectroscopy can also be coupled with thermal processes such as thermogravimetric (TG) analyses to provide both thermal and chemical data in a single run. In this configuration, solids (or liquids) heated in a TG analyzer undergo decomposition, with the evolving gases directed into the IR spectrometer. Thus, information is provided on the thermal properties of a material and the order in which its chemical constituents are broken down during incremental heating. Specific examples of these varied applications will be cited, with data interpretation and method limitations further discussed.

Use of the MATRIXx Integrated Toolkit on the Microwave Anisotropy Probe Attitude Control System

NASA Technical Reports Server (NTRS)

Ward, David K.; Andrews, Stephen F.; McComas, David C.; ODonnell, James R., Jr.

1999-01-01

Recent advances in analytical software tools allow the analysis, simulation, flight code, and documentation of an algorithm to be generated from a single source, all within one integrated analytical design package. NASA's Microwave Anisotropy Probe project has used one such package, Integrated Systems' MATRIXx suite, in the design of the spacecraft's Attitude Control System. The project's experience with the linear analysis, simulation, code generation, and documentation tools will be presented and compared with more traditional development tools. In particular, the quality of the flight software generated will be examined in detail. Finally, lessons learned on each of the tools will be shared.

Summary of NDE of Additive Manufacturing Efforts in NASA

NASA Technical Reports Server (NTRS)

Waller, Jess; Saulsberry, Regor; Parker, Bradford; Hodges, Kenneth; Burke, Eric; Taminger, Karen

2014-01-01

(1) General Rationale for Additive Manufacturing (AM): (a) Operate under a 'design-to-constraint' paradigm, make parts too complicated to fabricate otherwise, (b) Reduce weight by 20 percent with monolithic parts, (c) Reduce waste (green manufacturing), (e) Eliminate reliance on Original Equipment Manufacturers for critical spares, and (f) Extend life of in-service parts by innovative repair methods; (2) NASA OSMA NDE of AM State-of-the-Discipline Report; (3) Overview of NASA AM Efforts at Various Centers: (a) Analytical Tools, (b) Ground-Based Fabrication (c) Space-Based Fabrication; and (d) Center Activity Summaries; (4) Overview of NASA NDE data to date on AM parts; and (5) Gap Analysis/Recommendations for NDE of AM.

Versatile electrophoresis-based self-test platform.

PubMed

Guijt, Rosanne M

2015-03-01

Lab on a Chip technology offers the possibility to extract chemical information from a complex sample in a simple, automated way without the need for a laboratory setting. In the health care sector, this chemical information could be used as a diagnostic tool for example to inform dosing. In this issue, the research underpinning a family of electrophoresis-based point-of-care devices for self-testing of ionic analytes in various sample matrices is described [Electrophoresis 2015, 36, 712-721.]. Hardware, software, and methodological chances made to improve the overall analytical performance in terms of accuracy, precision, detection limit, and reliability are discussed. In addition to the main focus of lithium monitoring, new applications including the use of the platform for veterinary purposes, sodium, and for creatinine measurements are included. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of "At Risk" Students Using Learning Analytics: The Ethical Dilemmas of Intervention Strategies in a Higher Education Institution

ERIC Educational Resources Information Center

Lawson, Celeste; Beer, Colin; Rossi, Dolene; Moore, Teresa; Fleming, Julie

2016-01-01

Learning analytics is an emerging field in which sophisticated analytic tools are used to inform and improve learning and teaching. Researchers within a regional university in Australia identified an association between interaction and student success in online courses and subsequently developed a learning analytics system aimed at informing…

Pegasus hypersonic flight research

NASA Technical Reports Server (NTRS)

Curry, Robert E.; Meyer, Robert R., Jr.; Budd, Gerald D.

1992-01-01

Hypersonic aeronautics research using the Pegasus air-launched space booster is described. Two areas are discussed in the paper: previously obtained results from Pegasus flights 1 and 2, and plans for future programs. Proposed future research includes boundary-layer transition studies on the airplane-like first stage and also use of the complete Pegasus launch system to boost a research vehicle to hypersonic speeds. Pegasus flight 1 and 2 measurements were used to evaluate the results of several analytical aerodynamic design tools applied during the development of the vehicle as well as to develop hypersonic flight-test techniques. These data indicated that the aerodynamic design approach for Pegasus was adequate and showed that acceptable margins were available. Additionally, the correlations provide insight into the capabilities of these analytical tools for more complex vehicles in which design margins may be more stringent. Near-term plans to conduct hypersonic boundary-layer transition studies are discussed. These plans involve the use of a smooth metallic glove at about the mid-span of the wing. Longer-term opportunities are proposed which identify advantages of the Pegasus launch system to boost large-scale research vehicles to the real-gas hypersonic flight regime.

A graphical approach to radio frequency quadrupole design

NASA Astrophysics Data System (ADS)

Turemen, G.; Unel, G.; Yasatekin, B.

2015-07-01

The design of a radio frequency quadrupole, an important section of all ion accelerators, and the calculation of its beam dynamics properties can be achieved using the existing computational tools. These programs, originally designed in 1980s, show effects of aging in their user interfaces and in their output. The authors believe there is room for improvement in both design techniques using a graphical approach and in the amount of analytical calculations before going into CPU burning finite element analysis techniques. Additionally an emphasis on the graphical method of controlling the evolution of the relevant parameters using the drag-to-change paradigm is bound to be beneficial to the designer. A computer code, named DEMIRCI, has been written in C++ to demonstrate these ideas. This tool has been used in the design of Turkish Atomic Energy Authority (TAEK)'s 1.5 MeV proton beamline at Saraykoy Nuclear Research and Training Center (SANAEM). DEMIRCI starts with a simple analytical model, calculates the RFQ behavior and produces 3D design files that can be fed to a milling machine. The paper discusses the experience gained during design process of SANAEM Project Prometheus (SPP) RFQ and underlines some of DEMIRCI's capabilities.

Detection of anabolic androgenic steroid abuse in doping control using mammalian reporter gene bioassays.

PubMed

Houtman, Corine J; Sterk, Saskia S; van de Heijning, Monique P M; Brouwer, Abraham; Stephany, Rainer W; van der Burg, Bart; Sonneveld, Edwin

2009-04-01

Anabolic androgenic steroids (AAS) are a class of steroid hormones related to the male hormone testosterone. They are frequently detected as drugs in sport doping control. Being similar to or derived from natural male hormones, AAS share the activation of the androgen receptor (AR) as common mechanism of action. The mammalian androgen responsive reporter gene assay (AR CALUX bioassay), measuring compounds interacting with the AR can be used for the analysis of AAS without the necessity of knowing their chemical structure beforehand, whereas current chemical-analytical approaches may have difficulty in detecting compounds with unknown structures, such as designer steroids. This study demonstrated that AAS prohibited in sports and potential designer AAS can be detected with this AR reporter gene assay, but that also additional steroid activities of AAS could be found using additional mammalian bioassays for other types of steroid hormones. Mixtures of AAS were found to behave additively in the AR reporter gene assay showing that it is possible to use this method for complex mixtures as are found in doping control samples, including mixtures that are a result of multi drug use. To test if mammalian reporter gene assays could be used for the detection of AAS in urine samples, background steroidal activities were measured. AAS-spiked urine samples, mimicking doping positive samples, showed significantly higher androgenic activities than unspiked samples. GC-MS analysis of endogenous androgens and AR reporter gene assay analysis of urine samples showed how a combined chemical-analytical and bioassay approach can be used to identify samples containing AAS. The results indicate that the AR reporter gene assay, in addition to chemical-analytical methods, can be a valuable tool for the analysis of AAS for doping control purposes.

Tools for studying dry-cured ham processing by using computed tomography.

PubMed

Santos-Garcés, Eva; Muñoz, Israel; Gou, Pere; Sala, Xavier; Fulladosa, Elena

2012-01-11

An accurate knowledge and optimization of dry-cured ham elaboration processes could help to reduce operating costs and maximize product quality. The development of nondestructive tools to characterize chemical parameters such as salt and water contents and a(w) during processing is of special interest. In this paper, predictive models for salt content (R(2) = 0.960 and RMSECV = 0.393), water content (R(2) = 0.912 and RMSECV = 1.751), and a(w) (R(2) = 0.906 and RMSECV = 0.008), which comprise the whole elaboration process, were developed. These predictive models were used to develop analytical tools such as distribution diagrams, line profiles, and regions of interest (ROIs) from the acquired computed tomography (CT) scans. These CT analytical tools provided quantitative information on salt, water, and a(w) in terms of content but also distribution throughout the process. The information obtained was applied to two industrial case studies. The main drawback of the predictive models and CT analytical tools is the disturbance that fat produces in water content and a(w) predictions.

Development of Multi-slice Analytical Tool to Support BIM-based Design Process

NASA Astrophysics Data System (ADS)

Atmodiwirjo, P.; Johanes, M.; Yatmo, Y. A.

2017-03-01

This paper describes the on-going development of computational tool to analyse architecture and interior space based on multi-slice representation approach that is integrated with Building Information Modelling (BIM). Architecture and interior space is experienced as a dynamic entity, which have the spatial properties that might be variable from one part of space to another, therefore the representation of space through standard architectural drawings is sometimes not sufficient. The representation of space as a series of slices with certain properties in each slice becomes important, so that the different characteristics in each part of space could inform the design process. The analytical tool is developed for use as a stand-alone application that utilises the data exported from generic BIM modelling tool. The tool would be useful to assist design development process that applies BIM, particularly for the design of architecture and interior spaces that are experienced as continuous spaces. The tool allows the identification of how the spatial properties change dynamically throughout the space and allows the prediction of the potential design problems. Integrating the multi-slice analytical tool in BIM-based design process thereby could assist the architects to generate better design and to avoid unnecessary costs that are often caused by failure to identify problems during design development stages.

Sustainability Tools Inventory Initial Gap Analysis

EPA Science Inventory

This report identifies a suite of tools that address a comprehensive set of community sustainability concerns. The objective is to discover whether "gaps" exist in the tool suite’s analytic capabilities. These tools address activities that significantly influence resource consu...

New Tools to Prepare ACE Cross-section Files for MCNP Analytic Test Problems

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

Brown, Forrest B.

Monte Carlo calculations using one-group cross sections, multigroup cross sections, or simple continuous energy cross sections are often used to: (1) verify production codes against known analytical solutions, (2) verify new methods and algorithms that do not involve detailed collision physics, (3) compare Monte Carlo calculation methods with deterministic methods, and (4) teach fundamentals to students. In this work we describe 2 new tools for preparing the ACE cross-section files to be used by MCNP ® for these analytic test problems, simple_ace.pl and simple_ace_mg.pl.

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Learner Dashboards a Double-Edged Sword? Students' Sense-Making of a Collaborative Critical Reading and Learning Analytics Environment for Fostering 21st-Century Literacies

ERIC Educational Resources Information Center

Pei-Ling Tan, Jennifer; Koh, Elizabeth; Jonathan, Christin; Yang, Simon

2017-01-01

The affordances of learning analytics (LA) tools and solutions are being increasingly harnessed for enhancing 21st century pedagogical and learning strategies and outcomes. However, use cases and empirical understandings of students' experiences with LA tools and environments aimed at fostering 21st century literacies, especially in the K-12…

Visual Information for the Desktop, version 1.0

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

2006-03-29

VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.

Commentary on "Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning"

ERIC Educational Resources Information Center

Teplovs, Chris

2015-01-01

This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…

Search Analytics: Automated Learning, Analysis, and Search with Open Source

NASA Astrophysics Data System (ADS)

Hundman, K.; Mattmann, C. A.; Hyon, J.; Ramirez, P.

2016-12-01

The sheer volume of unstructured scientific data makes comprehensive human analysis impossible, resulting in missed opportunities to identify relationships, trends, gaps, and outliers. As the open source community continues to grow, tools like Apache Tika, Apache Solr, Stanford's DeepDive, and Data-Driven Documents (D3) can help address this challenge. With a focus on journal publications and conference abstracts often in the form of PDF and Microsoft Office documents, we've initiated an exploratory NASA Advanced Concepts project aiming to use the aforementioned open source text analytics tools to build a data-driven justification for the HyspIRI Decadal Survey mission. We call this capability Search Analytics, and it fuses and augments these open source tools to enable the automatic discovery and extraction of salient information. In the case of HyspIRI, a hyperspectral infrared imager mission, key findings resulted from the extractions and visualizations of relationships from thousands of unstructured scientific documents. The relationships include links between satellites (e.g. Landsat 8), domain-specific measurements (e.g. spectral coverage) and subjects (e.g. invasive species). Using the above open source tools, Search Analytics mined and characterized a corpus of information that would be infeasible for a human to process. More broadly, Search Analytics offers insights into various scientific and commercial applications enabled through missions and instrumentation with specific technical capabilities. For example, the following phrases were extracted in close proximity within a publication: "In this study, hyperspectral images…with high spatial resolution (1 m) were analyzed to detect cutleaf teasel in two areas. …Classification of cutleaf teasel reached a users accuracy of 82 to 84%." Without reading a single paper we can use Search Analytics to automatically identify that a 1 m spatial resolution provides a cutleaf teasel detection users accuracy of 82-84%, which could have tangible, direct downstream implications for crop protection. Automatically assimilating this information expedites and supplements human analysis, and, ultimately, Search Analytics and its foundation of open source tools will result in more efficient scientific investment and research.

From Theory Use to Theory Building in Learning Analytics: A Commentary on "Learning Analytics to Support Teachers during Synchronous CSCL"

ERIC Educational Resources Information Center

Chen, Bodong

2015-01-01

In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…

Microgenetic Learning Analytics Methods: Workshop Report

ERIC Educational Resources Information Center

Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin

2016-01-01

Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

2014-01-01

Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

Observations, Ideas, and Opinions: Systems Engineering and Integration for Return to Flight

NASA Technical Reports Server (NTRS)

Gafka, George K.

2006-01-01

This presentation addresses project management and systems engineering and integration challenges for return to flight, focusing on the Thermal Protection System Tile Repair Project (TRP). The program documentation philosophy, communication with program requirements flow and philosophy and planned deliverables and documentation are outlined. The development of TRP 'use-as-is' analytical tools is also highlighted and emphasis is placed on the use flight history to assess pre-flight and real-time risk. Additionally, an overview is provided of the repair procedure, including an outline of the logistics deployment chart.

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

PubMed

Kumar, Sudhir; Stecher, Glen; Li, Michael; Knyaz, Christina; Tamura, Koichiro

2018-06-01

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

Introduction to the special section "Big'er' Data": Scaling up psychotherapy research in counseling psychology.

PubMed

Owen, Jesse; Imel, Zac E

2016-04-01

This article introduces the special section on utilizing large data sets to explore psychotherapy processes and outcomes. The increased use of technology has provided new opportunities for psychotherapy researchers. In particular, there is a rise in large databases of tens of thousands clients. Additionally, there are new ways to pool valuable resources for meta-analytic processes. At the same time, these tools also come with limitations. These issues are introduced as well as brief overview of the articles. (c) 2016 APA, all rights reserved).

Lobed Mixer Optimization for Advanced Ejector Geometries

NASA Technical Reports Server (NTRS)

Waitz, Ian A.

1996-01-01

The overall objectives are: 1) to pursue analytical, computational, and experimental studies that enhance basic understanding of forced mixing phenomena relevant to supersonic jet noise reduction, and 2) to integrate this enhanced understanding (analytical, computational, and empirical) into a design-oriented model of a mixer-ejector noise suppression system. The work is focused on ejector geometries and flow conditions typical of those being investigated in the NASA High Speed Research Program (HSRP). The research will be carried out in collaboration with the NASA HSRP Nozzle Integrated Technology Development (ITD) Team, and will both contribute to, and benefit from, the results of other HSRP research. The noise suppressor system model that is being developed under this grant is distinct from analytical tools developed by industry because it directly links details of lobe geometry to mixer-ejector performance. In addition, the model provides a 'technology road map to define gaps in the current understanding of various phenomena related to mixer-ejector design and to help prioritize research areas. This report describes research completed in the past year, as well as work proposed for the following year.

TLD efficiency calculations for heavy ions: an analytical approach

DOE PAGES

Boscolo, Daria; Scifoni, Emanuele; Carlino, Antonio; ...

2015-12-18

The use of thermoluminescent dosimeters (TLDs) in heavy charged particles’ dosimetry is limited by their non-linear dose response curve and by their response dependence on the radiation quality. Thus, in order to use TLDs with particle beams, a model that can reproduce the behavior of these detectors under different conditions is needed. Here a new, simple and completely analytical algorithm for the calculation of the relative TL-efficiency depending on the ion charge Z and energy E is presented. In addition, the detector response is evaluated starting from the single ion case, where the computed effectiveness values have been compared withmore » experimental data as well as with predictions from a different method. The main advantage of this approach is that, being fully analytical, it is computationally fast and can be efficiently integrated into treatment planning verification tools. In conclusion, the calculated efficiency values have been then implemented in the treatment planning code TRiP98 and dose calculations on a macroscopic target irradiated with an extended carbon ion field have been performed and verified against experimental data.« less

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

PubMed

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.

Simultaneous Spectrophotometric Determination of Rifampicin, Isoniazid and Pyrazinamide in a Single Step

PubMed Central

Asadpour-Zeynali, Karim; Saeb, Elhameh

2016-01-01

Three antituberculosis medications are investigated in this work consist of rifampicin, isoniazid and pyrazinamide. The ultra violet (UV) spectra of these compounds are overlapped, thus use of suitable chemometric methods are helpful for simultaneous spectrophotometric determination of them. A generalized version of net analyte signal standard addition method (GNASSAM) was used for determination of three antituberculosis medications as a model system. In generalized net analyte signal standard addition method only one standard solution was prepared for all analytes. This standard solution contains a mixture of all analytes of interest, and the addition of such solution to sample, causes increases in net analyte signal of each analyte which are proportional to the concentrations of analytes in added standards solution. For determination of concentration of each analyte in some synthetic mixtures, the UV spectra of pure analytes and each sample were recorded in the range of 210 nm-550 nm. The standard addition procedure was performed for each sample and the UV spectrum was recorded after each addition and finally the results were analyzed by net analyte signal method. Obtained concentrations show acceptable performance of GNASSAM in these cases. PMID:28243267

Data Intensive Computing on Amazon Web Services

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

Magana-Zook, S. A.

The Geophysical Monitoring Program (GMP) has spent the past few years building up the capability to perform data intensive computing using what have been referred to as “big data” tools. These big data tools would be used against massive archives of seismic signals (>300 TB) to conduct research not previously possible. Examples of such tools include Hadoop (HDFS, MapReduce), HBase, Hive, Storm, Spark, Solr, and many more by the day. These tools are useful for performing data analytics on datasets that exceed the resources of traditional analytic approaches. To this end, a research big data cluster (“Cluster A”) was setmore » up as a collaboration between GMP and Livermore Computing (LC).« less

Rapid Quantification of Melamine in Different Brands/Types of Milk Powders Using Standard Addition Net Analyte Signal and Near-Infrared Spectroscopy

PubMed Central

2016-01-01

Multivariate calibration (MVC) and near-infrared (NIR) spectroscopy have demonstrated potential for rapid analysis of melamine in various dairy products. However, the practical application of ordinary MVC can be largely restricted because the prediction of a new sample from an uncalibrated batch would be subject to a significant bias due to matrix effect. In this study, the feasibility of using NIR spectroscopy and the standard addition (SA) net analyte signal (NAS) method (SANAS) for rapid quantification of melamine in different brands/types of milk powders was investigated. In SANAS, the NAS vector of melamine in an unknown sample as well as in a series of samples added with melamine standards was calculated and then the Euclidean norms of series standards were used to build a straightforward univariate regression model. The analysis results of 10 different brands/types of milk powders with melamine levels 0~0.12% (w/w) indicate that SANAS obtained accurate results with the root mean squared error of prediction (RMSEP) values ranging from 0.0012 to 0.0029. An additional advantage of NAS is to visualize and control the possible unwanted variations during standard addition. The proposed method will provide a practically useful tool for rapid and nondestructive quantification of melamine in different brands/types of milk powders. PMID:27525154

Haze Gray Paint and the U.S. Navy: A Procurement Process Review

DTIC Science & Technology

2017-12-01

support of the fleet. The research encompasses both qualitative and quantitative analytical tools utilizing historical demand data for Silicone Alkyd...inventory level of 1K Polysiloxane in support of the fleet. The research encompasses both qualitative and quantitative analytical tools utilizing...Chapter I. C. CONCLUSIONS As discussed in the Summary section, this research used a qualitative and a quantitative approach to analyze the Polysiloxane

Enterprise Systems Value-Based R&D Portfolio Analytics: Methods, Processes, and Tools

DTIC Science & Technology

2014-01-14

Enterprise Systems Value-Based R&D Portfolio Analytics: Methods, Processes, and Tools Final Technical Report SERC -2014-TR-041-1 January 14...by the U.S. Department of Defense through the Systems Engineering Research Center ( SERC ) under Contract H98230-08-D-0171 (Task Order 0026, RT 51... SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology Any opinions, findings and

Visualization and Analytics Software Tools for Peregrine System |

Science.gov Websites

R is a language and environment for statistical computing and graphics. Go to the R web site for System Visualization and Analytics Software Tools for Peregrine System Learn about the available visualization for OpenGL-based applications. For more information, please go to the FastX page. ParaView An open

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

Analytical Tools for the Application of Operational Culture: A Case Study in the Trans-Sahel

DTIC Science & Technology

2011-03-28

Study Team Working Paper 3: Research Methods Discussion for the Study Team Methods229 Generating Empirical Materials In grounded theory ... research I have conducted using these methods . UNCLASSIFIED Analytical Tools for the Application of Operational Culture: A Case Study in the...Survey and a Case Study ,‖ Kjeller, Norway: FFI Glaser, B. G. & Strauss, A. L. (1967). ―The discovery of grounded theory

Demonstrating Success: Web Analytics and Continuous Improvement

ERIC Educational Resources Information Center

Loftus, Wayne

2012-01-01

As free and low-cost Web analytics tools become more sophisticated, libraries' approach to user analysis can become more nuanced and precise. Tracking appropriate metrics with a well-formulated analytics program can inform design decisions, demonstrate the degree to which those decisions have succeeded, and thereby inform the next iteration in the…

Understanding Education Involving Geovisual Analytics

ERIC Educational Resources Information Center

Stenliden, Linnea

2013-01-01

Handling the vast amounts of data and information available in contemporary society is a challenge. Geovisual Analytics provides technology designed to increase the effectiveness of information interpretation and analytical task solving. To date, little attention has been paid to the role such tools can play in education and to the extent to which…

Development of analytical cell support for vitrification at the West Valley Demonstration Project. Topical report

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

Barber, F.H.; Borek, T.T.; Christopher, J.Z.

1997-12-01

Analytical and Process Chemistry (A&PC) support is essential to the high-level waste vitrification campaign at the West Valley Demonstration Project (WVDP). A&PC characterizes the waste, providing information necessary to formulate the recipe for the target radioactive glass product. High-level waste (HLW) samples are prepared and analyzed in the analytical cells (ACs) and Sample Storage Cell (SSC) on the third floor of the main plant. The high levels of radioactivity in the samples require handling them in the shielded cells with remote manipulators. The analytical hot cells and third floor laboratories were refurbished to ensure optimal uninterrupted operation during the vitrificationmore » campaign. New and modified instrumentation, tools, sample preparation and analysis techniques, and equipment and training were required for A&PC to support vitrification. Analytical Cell Mockup Units (ACMUs) were designed to facilitate method development, scientist and technician training, and planning for analytical process flow. The ACMUs were fabricated and installed to simulate the analytical cell environment and dimensions. New techniques, equipment, and tools could be evaluated m in the ACMUs without the consequences of generating or handling radioactive waste. Tools were fabricated, handling and disposal of wastes was addressed, and spatial arrangements for equipment were refined. As a result of the work at the ACMUs the remote preparation and analysis methods and the equipment and tools were ready for installation into the ACs and SSC m in July 1995. Before use m in the hot cells, all remote methods had been validated and four to eight technicians were trained on each. Fine tuning of the procedures has been ongoing at the ACs based on input from A&PC technicians. Working at the ACs presents greater challenges than had development at the ACMUs. The ACMU work and further refinements m in the ACs have resulted m in a reduction m in analysis turnaround time (TAT).« less

Distributed Generation Interconnection Collaborative | NREL

Science.gov Websites

, reduce paperwork, and improve customer service. Analytical Methods for Interconnection Many utilities and jurisdictions are seeking the right screening and analytical methods and tools to meet their reliability

Toward high value sensing: monolayer-protected metal nanoparticles in multivariable gas and vapor sensors.

PubMed

Potyrailo, Radislav A

2017-08-29

For detection of gases and vapors in complex backgrounds, "classic" analytical instruments are an unavoidable alternative to existing sensors. Recently a new generation of sensors, known as multivariable sensors, emerged with a fundamentally different perspective for sensing to eliminate limitations of existing sensors. In multivariable sensors, a sensing material is designed to have diverse responses to different gases and vapors and is coupled to a multivariable transducer that provides independent outputs to recognize these diverse responses. Data analytics tools provide rejection of interferences and multi-analyte quantitation. This review critically analyses advances of multivariable sensors based on ligand-functionalized metal nanoparticles also known as monolayer-protected nanoparticles (MPNs). These MPN sensing materials distinctively stand out from other sensing materials for multivariable sensors due to their diversity of gas- and vapor-response mechanisms as provided by organic and biological ligands, applicability of these sensing materials for broad classes of gas-phase compounds such as condensable vapors and non-condensable gases, and for several principles of signal transduction in multivariable sensors that result in non-resonant and resonant electrical sensors as well as material- and structure-based photonic sensors. Such features should allow MPN multivariable sensors to be an attractive high value addition to existing analytical instrumentation.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

Chemical and biological threat-agent detection using electrophoresis-based lab-on-a-chip devices.

PubMed

Borowsky, Joseph; Collins, Greg E

2007-10-01

The ability to separate complex mixtures of analytes has made capillary electrophoresis (CE) a powerful analytical tool since its modern configuration was first introduced over 25 years ago. The technique found new utility with its application to the microfluidics based lab-on-a-chip platform (i.e., microchip), which resulted in ever smaller footprints, sample volumes, and analysis times. These features, coupled with the technique's potential for portability, have prompted recent interest in the development of novel analyzers for chemical and biological threat agents. This article will comment on three main areas of microchip CE as applied to the separation and detection of threat agents: detection techniques and their corresponding limits of detection, sampling protocol and preparation time, and system portability. These three areas typify the broad utility of lab-on-a-chip for meeting critical, present-day security, in addition to illustrating areas wherein advances are necessary.

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

PubMed

Shen, Zeqian; Ma, Kwan-Liu; Eliassi-Rad, Tina

2006-01-01

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

BIOCHEMISTRY OF MOBILE ZINC AND NITRIC OXIDE REVEALED BY FLUORESCENT SENSORS

PubMed Central

Pluth, Michael D.; Tomat, Elisa; Lippard, Stephen J.

2010-01-01

Biologically mobile zinc and nitric oxide (NO) are two prominent examples of inorganic compounds involved in numerous signaling pathways in living systems. In the past decade, a synergy of regulation, signaling, and translocation of these two species has emerged in several areas of human physiology, providing additional incentive for developing adequate detection systems for Zn(II) ions and NO in biological specimens. Fluorescent probes for both of these bioinorganic analytes provide excellent tools for their detection, with high spatial and temporal resolution. We review the most widely used fluorescent sensors for biological zinc and nitric oxide, together with promising new developments and unmet needs of contemporary Zn(II) and NO biological imaging. The interplay between zinc and nitric oxide in the nervous, cardiovascular, and immune systems is highlighted to illustrate the contributions of selective fluorescent probes to the study of these two important bioinorganic analytes. PMID:21675918

Ethane-Bridged Bisporphyrin Conformational Changes As an Effective Analytical Tool for Nonenzymatic Detection of Urea in the Physiological Range.

PubMed

Buccolieri, Alessandro; Hasan, Mohammed; Bettini, Simona; Bonfrate, Valentina; Salvatore, Luca; Santino, Angelo; Borovkov, Victor; Giancane, Gabriele

2018-06-05

Conformational switching induced in ethane-bridged bisporphyrins was used as a sensitive transduction method for revealing the presence of urea dissolved in water via nonenzymatic approach. Bisporphyrins were deposited on solid quartz slides by means of the spin-coating method. Molecular conformations of Zn and Ni monometalated bis-porphyrins were influenced by water solvated urea molecules and their fluorescence emission was modulated by the urea concentration. Absorption, fluorescence and Raman spectroscopies allowed the identification of supramolecular processes, which are responsible for host-guest interaction between the active layers and urea molecules. A high selectivity of the sensing mechanism was highlighted upon testing the spectroscopic responses of bis-porphyrin films to citrulline and glutamine used as interfering agents. Additionally, potential applicability was demonstrated by quantifying the urea concentration in real physiological samples proposing this new approach as a valuable alternative analytical procedure to the traditionally used enzymatic methods.

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Solution of the exact equations for three-dimensional atmospheric entry using directly matched asymptotic expansions

NASA Technical Reports Server (NTRS)

Busemann, A.; Vinh, N. X.; Culp, R. D.

1976-01-01

The problem of determining the trajectories, partially or wholly contained in the atmosphere of a spherical, nonrotating planet, is considered. The exact equations of motion for three-dimensional, aerodynamically affected flight are derived. Modified Chapman variables are introduced and the equations are transformed into a set suitable for analytic integration using asymptotic expansions. The trajectory is solved in two regions: the outer region, where the force may be considered a gravitational field with aerodynamic perturbations, and the inner region, where the force is predominantly aerodynamic, with gravity as a perturbation. The two solutions are matched directly. A composite solution, valid everywhere, is constructed by additive composition. This approach of directly matched asymptotic expansions applied to the exact equations of motion couched in terms of modified Chapman variables yields an analytical solution which should prove to be a powerful tool for aerodynamic orbit calculations.

Simultaneous quantitative analysis of olmesartan, amlodipine and hydrochlorothiazide in their combined dosage form utilizing classical and alternating least squares based chemometric methods.

PubMed

Darwish, Hany W; Bakheit, Ahmed H; Abdelhameed, Ali S

2016-03-01

Simultaneous spectrophotometric analysis of a multi-component dosage form of olmesartan, amlodipine and hydrochlorothiazide used for the treatment of hypertension has been carried out using various chemometric methods. Multivariate calibration methods include classical least squares (CLS) executed by net analyte processing (NAP-CLS), orthogonal signal correction (OSC-CLS) and direct orthogonal signal correction (DOSC-CLS) in addition to multivariate curve resolution-alternating least squares (MCR-ALS). Results demonstrated the efficiency of the proposed methods as quantitative tools of analysis as well as their qualitative capability. The three analytes were determined precisely using the aforementioned methods in an external data set and in a dosage form after optimization of experimental conditions. Finally, the efficiency of the models was validated via comparison with the partial least squares (PLS) method in terms of accuracy and precision.

Consistent approach to describing aircraft HIRF protection

NASA Technical Reports Server (NTRS)

Rimbey, P. R.; Walen, D. B.

1995-01-01

The high intensity radiated fields (HIRF) certification process as currently implemented is comprised of an inconsistent combination of factors that tend to emphasize worst case scenarios in assessing commercial airplane certification requirements. By examining these factors which include the process definition, the external HIRF environment, the aircraft coupling and corresponding internal fields, and methods of measuring equipment susceptibilities, activities leading to an approach to appraising airplane vulnerability to HIRF are proposed. This approach utilizes technically based criteria to evaluate the nature of the threat, including the probability of encountering the external HIRF environment. No single test or analytic method comprehensively addresses the full HIRF threat frequency spectrum. Additional tools such as statistical methods must be adopted to arrive at more realistic requirements to reflect commercial aircraft vulnerability to the HIRF threat. Test and analytic data are provided to support the conclusions of this report. This work was performed under NASA contract NAS1-19360, Task 52.

Multicriteria decision analysis in ranking of analytical procedures for aldrin determination in water.

PubMed

Tobiszewski, Marek; Orłowski, Aleksander

2015-03-27

The study presents the possibility of multi-criteria decision analysis (MCDA) application when choosing analytical procedures with low environmental impact. A type of MCDA, Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), was chosen as versatile tool that meets all the analytical chemists--decision makers requirements. Twenty five analytical procedures for aldrin determination in water samples (as an example) were selected as input alternatives to MCDA analysis. Nine different criteria describing the alternatives were chosen from different groups--metrological, economical and the most importantly--environmental impact. The weights for each criterion were obtained from questionnaires that were sent to experts, giving three different scenarios for MCDA results. The results of analysis show that PROMETHEE is very promising tool to choose the analytical procedure with respect to its greenness. The rankings for all three scenarios placed solid phase microextraction and liquid phase microextraction--based procedures high, while liquid-liquid extraction, solid phase extraction and stir bar sorptive extraction--based procedures were placed low in the ranking. The results show that although some of the experts do not intentionally choose green analytical chemistry procedures, their MCDA choice is in accordance with green chemistry principles. The PROMETHEE ranking results were compared with more widely accepted green analytical chemistry tools--NEMI and Eco-Scale. As PROMETHEE involved more different factors than NEMI, the assessment results were only weakly correlated. Oppositely, the results of Eco-Scale assessment were well-correlated as both methodologies involved similar criteria of assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

Pyrolysis-gas chromatography-isotope ratio mass spectrometry for monitoring natural additives in polylactic acid active food packages.

PubMed

Llana-Ruíz-Cabello, M; Pichardo, S; Jiménez-Morillo, N T; González-Vila, F J; Guillamón, E; Bermúdez, J M; Aucejo, S; Camean, A M; González-Pérez, J A

2017-11-24

Compound-specific isotope analysis (CSIA) usually requires preparative steps (pretreatments, extraction, derivatization) to get amenable chromatographic analytes from bulk geological, biological or synthetic materials. Analytical pyrolysis (Py-GC/MS) can help to overcome such sample manipulation. This communication describe the results obtained by hyphenating analytical pyrolysis (Py-GC) with carbon isotope-ratio mass spectrometry (IRMS) for the analysis of a polylactic acid (PLA) a based bio-plastic extruded with variable quantities of a natural plant extract or oregano essential oil. The chemical structural information of pyrolysates was first determined by conventional analytical pyrolysis and the measure of δ 13 C in specific compounds was done by coupling a pyrolysis unit to a gas chromatograph connected to a continuous flow IRMS unit (Py-GC-C-IRMS). Using this Py-CSIA device it was possible to trace natural additives with depleted δ 13 C values produced by C3 photosystem vegetation (cymene: -26.7‰±2.52; terpinene: -27.1‰±0.13 and carvacrol: -27.5‰±1.80 from oregano and two unknown structures: -23.3‰±3.32 and -24.4‰±1.70 and butyl valerate: -24.1‰±3.55 from Allium spp.), within the naturally isotopically enriched bio-plastic backbone derived from corn (C4 vegetation) starch (cyclopentanones: -14.2‰±2.11; lactide enantiomers: -9.2‰±1.56 and larger polymeric units: -17.2‰±1.71). This is the first application of Py-CSIA to characterize a bio-plastic and is shown as a promising tool to study such materials, providing not only a fingerprinting, but also valuable information about the origin of the materials, allowing the traceability of additives and minimizing sample preparation. Copyright © 2017 Elsevier B.V. All rights reserved.

A Comprehensive Tool and Analytical Pathway for Differential Molecular Profiling and Biomarker Discovery

DTIC Science & Technology

2014-10-20

three possiblities: AKR , B6, and BALB_B) and MUP Protein (containing two possibilities: Intact and Denatured), then you can view a plot of the Strain...the tags for the last two labels. Again, if the attribute Strain has three tags: AKR , B6, 74 Distribution A . Approved for public release...AFRL-RH-WP-TR-2014-0131 A COMPREHENSIVE TOOL AND ANALYTICAL PATHWAY FOR DIFFERENTIAL MOLECULAR PROFILING AND BIOMARKER DISCOVERY

Development of a Suite of Analytical Tools for Energy and Water Infrastructure Knowledge Discovery

NASA Astrophysics Data System (ADS)

Morton, A.; Piburn, J.; Stewart, R.; Chandola, V.

2017-12-01

Energy and water generation and delivery systems are inherently interconnected. With demand for energy growing, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic, and demographic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This also requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. To address this need, we've developed a suite of analytical tools to support an integrated data driven modeling, analysis, and visualization capability for understanding, designing, and developing efficient local and regional practices related to the energy-water nexus. This work reviews the analytical capabilities available along with a series of case studies designed to demonstrate the potential of these tools for illuminating energy-water nexus solutions and supporting strategic (federal) policy decisions.

Student use of Web 2.0 tools to support argumentation in a high school science classroom

NASA Astrophysics Data System (ADS)

Weible, Jennifer L.

This ethnographic study is an investigation into how two classes of chemistry students (n=35) from a low-income high school with a one-to-one laptop initiative used Web 2.0 tools to support participation in the science practice of argumentation (i.e., sensemaking, articulating understandings, and persuading an audience) during a unit on alternative energy. The science curriculum utilized the Technology-Enhanced Inquiry Tools for Science Education as a pedagogical framework (Kim, Hannafin, & Bryan, 2007). Video recordings of the classroom work, small group discussions, and focus group interviews, documents, screen shots, wiki evidence, and student produced multi-media artifacts were the data analyzed for this study. Open and focused coding techniques, counts of social tags and wiki moves, and interpretive analyses were used to find patterns in the data. The study found that the tools of social bookmarking, wiki, and persuasive multimedia artifacts supported participation in argumentation. In addition, students utilized the affordances of the technologies in multiple ways to communicate, collaborate, manage the work of others, and efficiently complete their science project. This study also found that technologically enhanced science curriculum can bridge students' everyday and scientific understandings of making meaning, articulating understandings, and persuading others of their point of view. As a result, implications from this work include a set of design principles for science inquiry learning that utilize technology. This study suggests new consideration of analytical methodology that blends wiki data analytics and video data. It also suggests that utilizing technology as a bridging strategy serves two roles within classrooms: (a) deepening students' understanding of alternative energy science content and (b) supporting students as they learn to participate in the practices of argumentation.

Modeling of the Global Water Cycle - Analytical Models

Treesearch

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

Database and Analytical Tool Development for the Management of Data Derived from US DOE (NETL) Funded Fine Particulate (PM2.5) Research

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

Robinson P. Khosah; Frank T. Alex

2007-02-11

Advanced Technology Systems, Inc. (ATS) was contracted by the U. S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) to develop a state-of-the-art, scalable and robust web-accessible database application to manage the extensive data sets resulting from the DOE-NETL-sponsored ambient air monitoring programs in the upper Ohio River valley region. The data management system was designed to include a web-based user interface that will allow easy access to the data by the scientific community, policy- and decision-makers, and other interested stakeholders, while providing detailed information on sampling, analytical and quality control parameters. In addition, the system will provide graphical analyticalmore » tools for displaying, analyzing and interpreting the air quality data. The system will also provide multiple report generation capabilities and easy-to-understand visualization formats that can be utilized by the media and public outreach/educational institutions. The project is being conducted in two phases. Phase One includes the following tasks: (1) data inventory/benchmarking, including the establishment of an external stakeholder group; (2) development of a data management system; (3) population of the database; (4) development of a web-based data retrieval system, and (5) establishment of an internal quality assurance/quality control system on data management. Phase Two, which is currently underway, involves the development of a platform for on-line data analysis. Phase Two includes the following tasks: (1) development of a sponsor and stakeholder/user website with extensive online analytical tools; (2) development of a public website; (3) incorporation of an extensive online help system into each website; and (4) incorporation of a graphical representation (mapping) system into each website. The project is now into its forty-eighth month of development activities.« less

DATABASE AND ANALYTICAL TOOL DEVELOPMENT FOR THE MANAGEMENT OF DATA DERIVED FROM US DOE (NETL) FUNDED FINE PARTICULATE (PM 2.5) RESEARCH

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

Robinson P. Khosah; Charles G. Crawford

2006-02-11

Advanced Technology Systems, Inc. (ATS) was contracted by the U. S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) to develop a state-of-the-art, scalable and robust web-accessible database application to manage the extensive data sets resulting from the DOE-NETL-sponsored ambient air monitoring programs in the upper Ohio River valley region. The data management system was designed to include a web-based user interface that will allow easy access to the data by the scientific community, policy- and decision-makers, and other interested stakeholders, while providing detailed information on sampling, analytical and quality control parameters. In addition, the system will provide graphical analyticalmore » tools for displaying, analyzing and interpreting the air quality data. The system will also provide multiple report generation capabilities and easy-to-understand visualization formats that can be utilized by the media and public outreach/educational institutions. The project is being conducted in two phases. Phase One includes the following tasks: (1) data inventory/benchmarking, including the establishment of an external stakeholder group; (2) development of a data management system; (3) population of the database; (4) development of a web-based data retrieval system, and (5) establishment of an internal quality assurance/quality control system on data management. Phase Two, which is currently underway, involves the development of a platform for on-line data analysis. Phase Two includes the following tasks: (1) development of a sponsor and stakeholder/user website with extensive online analytical tools; (2) development of a public website; (3) incorporation of an extensive online help system into each website; and (4) incorporation of a graphical representation (mapping) system into each website. The project is now into its forty-second month of development activities.« less

A Lean Six Sigma approach to the improvement of the selenium analysis method.

PubMed

Cloete, Bronwyn C; Bester, André

2012-11-02

Reliable results represent the pinnacle assessment of quality of an analytical laboratory, and therefore variability is considered to be a critical quality problem associated with the selenium analysis method executed at Western Cape Provincial Veterinary Laboratory (WCPVL). The elimination and control of variability is undoubtedly of significant importance because of the narrow margin of safety between toxic and deficient doses of the trace element for good animal health. A quality methodology known as Lean Six Sigma was believed to present the most feasible solution for overcoming the adverse effect of variation, through steps towards analytical process improvement. Lean Six Sigma represents a form of scientific method type, which is empirical, inductive and deductive, and systematic, which relies on data, and is fact-based. The Lean Six Sigma methodology comprises five macro-phases, namely Define, Measure, Analyse, Improve and Control (DMAIC). Both qualitative and quantitative laboratory data were collected in terms of these phases. Qualitative data were collected by using quality-tools, namely an Ishikawa diagram, a Pareto chart, Kaizen analysis and a Failure Mode Effect analysis tool. Quantitative laboratory data, based on the analytical chemistry test method, were collected through a controlled experiment. The controlled experiment entailed 13 replicated runs of the selenium test method, whereby 11 samples were repetitively analysed, whilst Certified Reference Material (CRM) was also included in 6 of the runs. Laboratory results obtained from the controlled experiment was analysed by using statistical methods, commonly associated with quality validation of chemistry procedures. Analysis of both sets of data yielded an improved selenium analysis method, believed to provide greater reliability of results, in addition to a greatly reduced cycle time and superior control features. Lean Six Sigma may therefore be regarded as a valuable tool in any laboratory, and represents both a management discipline, and a standardised approach to problem solving and process optimisation.

DATABASE AND ANALYTICAL TOOL DEVELOPMENT FOR THE MANAGEMENT OF DATA DERIVED FROM US DOE (NETL) FUNDED FINE PARTICULATE (PM2.5) RESEARCH

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

Robinson P. Khosah; Charles G. Crawford

Advanced Technology Systems, Inc. (ATS) was contracted by the U. S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) to develop a state-of-the-art, scalable and robust web-accessible database application to manage the extensive data sets resulting from the DOE-NETL-sponsored ambient air monitoring programs in the upper Ohio River valley region. The data management system was designed to include a web-based user interface that will allow easy access to the data by the scientific community, policy- and decision-makers, and other interested stakeholders, while providing detailed information on sampling, analytical and quality control parameters. In addition, the system will provide graphical analyticalmore » tools for displaying, analyzing and interpreting the air quality data. The system will also provide multiple report generation capabilities and easy-to-understand visualization formats that can be utilized by the media and public outreach/educational institutions. The project is being conducted in two phases. Phase 1, which is currently in progress and will take twelve months to complete, will include the following tasks: (1) data inventory/benchmarking, including the establishment of an external stakeholder group; (2) development of a data management system; (3) population of the database; (4) development of a web-based data retrieval system, and (5) establishment of an internal quality assurance/quality control system on data management. In Phase 2, which will be completed in the second year of the project, a platform for on-line data analysis will be developed. Phase 2 will include the following tasks: (1) development of a sponsor and stakeholder/user website with extensive online analytical tools; (2) development of a public website; (3) incorporation of an extensive online help system into each website; and (4) incorporation of a graphical representation (mapping) system into each website. The project is now into its eleventh month of Phase 1 development activities.« less

Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data.

PubMed

Dunn, Joshua G; Weissman, Jonathan S

2016-11-22

Next-generation sequencing (NGS) informs many biological questions with unprecedented depth and nucleotide resolution. These assays have created a need for analytical tools that enable users to manipulate data nucleotide-by-nucleotide robustly and easily. Furthermore, because many NGS assays encode information jointly within multiple properties of read alignments - for example, in ribosome profiling, the locations of ribosomes are jointly encoded in alignment coordinates and length - analytical tools are often required to extract the biological meaning from the alignments before analysis. Many assay-specific pipelines exist for this purpose, but there remains a need for user-friendly, generalized, nucleotide-resolution tools that are not limited to specific experimental regimes or analytical workflows. Plastid is a Python library designed specifically for nucleotide-resolution analysis of genomics and NGS data. As such, Plastid is designed to extract assay-specific information from read alignments while retaining generality and extensibility to novel NGS assays. Plastid represents NGS and other biological data as arrays of values associated with genomic or transcriptomic positions, and contains configurable tools to convert data from a variety of sources to such arrays. Plastid also includes numerous tools to manipulate even discontinuous genomic features, such as spliced transcripts, with nucleotide precision. Plastid automatically handles conversion between genomic and feature-centric coordinates, accounting for splicing and strand, freeing users of burdensome accounting. Finally, Plastid's data models use consistent and familiar biological idioms, enabling even beginners to develop sophisticated analytical workflows with minimal effort. Plastid is a versatile toolkit that has been used to analyze data from multiple NGS assays, including RNA-seq, ribosome profiling, and DMS-seq. It forms the genomic engine of our ORF annotation tool, ORF-RATER, and is readily adapted to novel NGS assays. Examples, tutorials, and extensive documentation can be found at https://plastid.readthedocs.io .

Google Analytics – Index of Resources

EPA Pesticide Factsheets

Find how-to and best practice resources and training for accessing and understanding EPA's Google Analytics (GA) tools, including how to create reports that will help you improve and maintain the web areas you manage.

Environmental corrections of a dual-induction logging while drilling tool in vertical wells

NASA Astrophysics Data System (ADS)

Kang, Zhengming; Ke, Shizhen; Jiang, Ming; Yin, Chengfang; Li, Anzong; Li, Junjian

2018-04-01

With the development of Logging While Drilling (LWD) technology, dual-induction LWD logging is not only widely applied in deviated wells and horizontal wells, but it is used commonly in vertical wells. Accordingly, it is necessary to simulate the response of LWD tools in vertical wells for logging interpretation. In this paper, the investigation characteristics, the effects of the tool structure, skin effect and drilling environment of a dual-induction LWD tool are simulated by the three-dimensional (3D) finite element method (FEM). In order to closely simulate the actual situation, real structure of the tool is taking into account. The results demonstrate that the influence of the background value of the tool structure can be eliminated. The values of deducting the background of a tool structure and analytical solution have a quantitative agreement in homogeneous formations. The effect of measurement frequency could be effectively eliminated by chart of skin effect correction. In addition, the measurement environment, borehole size, mud resistivity, shoulder bed, layer thickness and invasion, have an effect on the true resistivity. To eliminate these effects, borehole correction charts, shoulder bed correction charts and tornado charts are computed based on real tool structure. Based on correction charts, well logging data can be corrected automatically by a suitable interpolation method, which is convenient and fast. Verified with actual logging data in vertical wells, this method could obtain the true resistivity of formation.

Investigating the causes of low detectability of pesticides in fruits and vegetables analysed by high-performance liquid chromatography - Time-of-flight.

PubMed

Muehlwald, S; Buchner, N; Kroh, L W

2018-03-23

Because of the high number of possible pesticide residues and their chemical complexity, it is necessary to develop methods which cover a broad range of pesticides. In this work, a qualitative multi-screening method for pesticides was developed by use of HPLC-ESI-Q-TOF. 110 pesticides were chosen for the creation of a personal compound database and library (PCDL). The MassHunter Qualitative Analysis software from Agilent Technologies was used to identify the analytes. The software parameter settings were optimised to produce a low number of false positive as well as false negative results. The method was validated for 78 selected pesticides. However, the validation criteria were not fulfilled for 45 analytes. Due to this result, investigations were started to elucidate reasons for the low detectability. It could be demonstrated that the three main causes of the signal suppression were the co-eluting matrix (matrix effect), the low sensitivity of the analyte in standard solution and the fragmentation of the analyte in the ion source (in-source collision-induced dissociation). In this paper different examples are discussed showing that the impact of these three causes is different for each analyte. For example, it is possible that an analyte with low signal intensity and an intense fragmentation in the ion source is detectable in a difficult matrix, whereas an analyte with a high sensitivity and a low fragmentation is not detectable in a simple matrix. Additionally, it could be shown that in-source fragments are a helpful tool for an unambiguous identification. Copyright © 2018 Elsevier B.V. All rights reserved.

Rethinking Visual Analytics for Streaming Data Applications

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

Crouser, R. Jordan; Franklin, Lyndsey; Cook, Kris

In the age of data science, the use of interactive information visualization techniques has become increasingly ubiquitous. From online scientific journals to the New York Times graphics desk, the utility of interactive visualization for both storytelling and analysis has become ever more apparent. As these techniques have become more readily accessible, the appeal of combining interactive visualization with computational analysis continues to grow. Arising out of a need for scalable, human-driven analysis, primary objective of visual analytics systems is to capitalize on the complementary strengths of human and machine analysis, using interactive visualization as a medium for communication between themore » two. These systems leverage developments from the fields of information visualization, computer graphics, machine learning, and human-computer interaction to support insight generation in areas where purely computational analyses fall short. Over the past decade, visual analytics systems have generated remarkable advances in many historically challenging analytical contexts. These include areas such as modeling political systems [Crouser et al. 2012], detecting financial fraud [Chang et al. 2008], and cybersecurity [Harrison et al. 2012]. In each of these contexts, domain expertise and human intuition is a necessary component of the analysis. This intuition is essential to building trust in the analytical products, as well as supporting the translation of evidence into actionable insight. In addition, each of these examples also highlights the need for scalable analysis. In each case, it is infeasible for a human analyst to manually assess the raw information unaided, and the communication overhead to divide the task between a large number of analysts makes simple parallelism intractable. Regardless of the domain, visual analytics tools strive to optimize the allocation of human analytical resources, and to streamline the sensemaking process on data that is massive, complex, incomplete, and uncertain in scenarios requiring human judgment.« less

A multi-purpose tool for food inspection: Simultaneous determination of various classes of preservatives and biogenic amines in meat and fish products by LC-MS.

PubMed

Molognoni, Luciano; Daguer, Heitor; de Sá Ploêncio, Leandro Antunes; De Dea Lindner, Juliano

2018-02-01

This paper describes an innovative fast and multipurpose method for the chemical inspection of meat and fish products by liquid chromatography-tandem mass spectrometry. Solid-liquid extraction and low temperature partitioning were applied to 17 analytes, which included large bacteriocins (3.5kDa) and small molecules (organic acids, heterocyclic compounds, polyene macrolides, alkyl esters of the p-hydroxybenzoic acid, aromatic, and aliphatic biogenic amines and polyamines). Chromatographic separation was achieved in 10min, using stationary phase of di-isopropyl-3-aminopropyl silane bound to hydroxylated silica. Method validation was in accordance to Commission Decision 657/2002/CE. Linear ranges were among 1.25-10.0mgkg -1 (natamycin and parabens), 2.50-10.0mgkg -1 (sorbate and nisin), 25.0-200mgkg -1 (biogenic amines, hexamethylenetetramine, benzoic and lactic acids), and 50.0-400mgkg -1 (citric acid). Expanded measurement uncertainty (U) was estimated by single laboratory validation combined to modeling in two calculation approaches: internal (U = 5%) and external standardization (U = 24%). Method applicability was checked on 89 real samples among raw, cooked, dry fermented and cured products, yielding acceptable recoveries. Many regulatory issues were revealed, corroborating the need for enhancement of the current analytical methods. This simple execution method dispenses the use of additional procedures of extraction and, therefore, reduces costs over time. It is suitable for routine analysis as a screening or confirmatory tool for both qualitative and quantitative results, replacing many time consuming analytical procedures. Copyright © 2017 Elsevier B.V. All rights reserved.

Bacterial discrimination by means of a universal array approach mediated by LDR (ligase detection reaction)

PubMed Central

Busti, Elena; Bordoni, Roberta; Castiglioni, Bianca; Monciardini, Paolo; Sosio, Margherita; Donadio, Stefano; Consolandi, Clarissa; Rossi Bernardi, Luigi; Battaglia, Cristina; De Bellis, Gianluca

2002-01-01

Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode) which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene) contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria. PMID:12243651

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform

PubMed Central

Poucke, Sven Van; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; Deyne, Cathy De

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner’s Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research. PMID:26731286

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

PubMed

Van Poucke, Sven; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; De Deyne, Cathy

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

Analytical and Empirical Modeling of Wear and Forces of CBN Tool in Hard Turning - A Review

NASA Astrophysics Data System (ADS)

Patel, Vallabh Dahyabhai; Gandhi, Anishkumar Hasmukhlal

2017-08-01

Machining of steel material having hardness above 45 HRC (Hardness-Rockwell C) is referred as a hard turning. There are numerous models which should be scrutinized and implemented to gain optimum performance of hard turning. Various models in hard turning by cubic boron nitride tool have been reviewed, in attempt to utilize appropriate empirical and analytical models. Validation of steady state flank and crater wear model, Usui's wear model, forces due to oblique cutting theory, extended Lee and Shaffer's force model, chip formation and progressive flank wear have been depicted in this review paper. Effort has been made to understand the relationship between tool wear and tool force based on the different cutting conditions and tool geometries so that appropriate model can be used according to user requirement in hard turning.

Net analyte signal standard addition method (NASSAM) as a novel spectrofluorimetric and spectrophotometric technique for simultaneous determination, application to assay of melatonin and pyridoxine

NASA Astrophysics Data System (ADS)

Asadpour-Zeynali, Karim; Bastami, Mohammad

2010-02-01

In this work a new modification of the standard addition method called "net analyte signal standard addition method (NASSAM)" is presented for the simultaneous spectrofluorimetric and spectrophotometric analysis. The proposed method combines the advantages of standard addition method with those of net analyte signal concept. The method can be applied for the determination of analyte in the presence of known interferents. The accuracy of the predictions against H-point standard addition method is not dependent on the shape of the analyte and interferent spectra. The method was successfully applied to simultaneous spectrofluorimetric and spectrophotometric determination of pyridoxine (PY) and melatonin (MT) in synthetic mixtures and in a pharmaceutical formulation.

A Tool Supporting Collaborative Data Analytics Workflow Design and Management

NASA Astrophysics Data System (ADS)

Zhang, J.; Bao, Q.; Lee, T. J.

2016-12-01

Collaborative experiment design could significantly enhance the sharing and adoption of the data analytics algorithms and models emerged in Earth science. Existing data-oriented workflow tools, however, are not suitable to support collaborative design of such a workflow, to name a few, to support real-time co-design; to track how a workflow evolves over time based on changing designs contributed by multiple Earth scientists; and to capture and retrieve collaboration knowledge on workflow design (discussions that lead to a design). To address the aforementioned challenges, we have designed and developed a technique supporting collaborative data-oriented workflow composition and management, as a key component toward supporting big data collaboration through the Internet. Reproducibility and scalability are two major targets demanding fundamental infrastructural support. One outcome of the project os a software tool, supporting an elastic number of groups of Earth scientists to collaboratively design and compose data analytics workflows through the Internet. Instead of recreating the wheel, we have extended an existing workflow tool VisTrails into an online collaborative environment as a proof of concept.

Interactive entity resolution in relational data: a visual analytic tool and its evaluation.

PubMed

Kang, Hyunmo; Getoor, Lise; Shneiderman, Ben; Bilgic, Mustafa; Licamele, Louis

2008-01-01

Databases often contain uncertain and imprecise references to real-world entities. Entity resolution, the process of reconciling multiple references to underlying real-world entities, is an important data cleaning process required before accurate visualization or analysis of the data is possible. In many cases, in addition to noisy data describing entities, there is data describing the relationships among the entities. This relational data is important during the entity resolution process; it is useful both for the algorithms which determine likely database references to be resolved and for visual analytic tools which support the entity resolution process. In this paper, we introduce a novel user interface, D-Dupe, for interactive entity resolution in relational data. D-Dupe effectively combines relational entity resolution algorithms with a novel network visualization that enables users to make use of an entity's relational context for making resolution decisions. Since resolution decisions often are interdependent, D-Dupe facilitates understanding this complex process through animations which highlight combined inferences and a history mechanism which allows users to inspect chains of resolution decisions. An empirical study with 12 users confirmed the benefits of the relational context visualization on the performance of entity resolution tasks in relational data in terms of time as well as users' confidence and satisfaction.

In-Line Detection and Measurement of Molecular Contamination in Semiconductor Process Solutions

NASA Astrophysics Data System (ADS)

Wang, Jason; West, Michael; Han, Ye; McDonald, Robert C.; Yang, Wenjing; Ormond, Bob; Saini, Harmesh

2005-09-01

This paper discusses a fully automated metrology tool for detection and quantitative measurement of contamination, including cationic, anionic, metallic, organic, and molecular species present in semiconductor process solutions. The instrument is based on an electrospray ionization time-of-flight mass spectrometer (ESI-TOF/MS) platform. The tool can be used in diagnostic or analytical modes to understand process problems in addition to enabling routine metrology functions. Metrology functions include in-line contamination measurement with near real-time trend analysis. This paper discusses representative organic and molecular contamination measurement results in production process problem solving efforts. The examples include the analysis and identification of organic compounds in SC-1 pre-gate clean solution; urea, NMP (N-Methyl-2-pyrrolidone) and phosphoric acid contamination in UPW; and plasticizer and an organic sulfur-containing compound found in isopropyl alcohol (IPA). It is expected that these unique analytical and metrology capabilities will improve the understanding of the effect of organic and molecular contamination on device performance and yield. This will permit the development of quantitative correlations between contamination levels and process degradation. It is also expected that the ability to perform routine process chemistry metrology will lead to corresponding improvements in manufacturing process control and yield, the ability to avoid excursions and will improve the overall cost effectiveness of the semiconductor manufacturing process.

Toxicological importance of human biomonitoring of metallic and metalloid elements in different biological samples.

PubMed

Gil, F; Hernández, A F

2015-06-01

Human biomonitoring has become an important tool for the assessment of internal doses of metallic and metalloid elements. These elements are of great significance because of their toxic properties and wide distribution in environmental compartments. Although blood and urine are the most used and accepted matrices for human biomonitoring, other non-conventional samples (saliva, placenta, meconium, hair, nails, teeth, breast milk) may have practical advantages and would provide additional information on health risk. Nevertheless, the analysis of these compounds in biological matrices other than blood and urine has not yet been accepted as a useful tool for biomonitoring. The validation of analytical procedures is absolutely necessary for a proper implementation of non-conventional samples in biomonitoring programs. However, the lack of reliable and useful analytical methodologies to assess exposure to metallic elements, and the potential interference of external contamination and variation in biological features of non-conventional samples are important limitations for setting health-based reference values. The influence of potential confounding factors on metallic concentration should always be considered. More research is needed to ascertain whether or not non-conventional matrices offer definitive advantages over the traditional samples and to broaden the available database for establishing worldwide accepted reference values in non-exposed populations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Applying Pragmatics Principles for Interaction with Visual Analytics.

PubMed

Hoque, Enamul; Setlur, Vidya; Tory, Melanie; Dykeman, Isaac

2018-01-01

Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.

A Semi-Analytical Method for Determining the Energy Release Rate of Cracks in Adhesively-Bonded Single-Lap Composite Joints

NASA Technical Reports Server (NTRS)

Yang, Charles; Sun, Wenjun; Tomblin, John S.; Smeltzer, Stanley S., III

2007-01-01

A semi-analytical method for determining the strain energy release rate due to a prescribed interface crack in an adhesively-bonded, single-lap composite joint subjected to axial tension is presented. The field equations in terms of displacements within the joint are formulated by using first-order shear deformable, laminated plate theory together with kinematic relations and force equilibrium conditions. The stress distributions for the adherends and adhesive are determined after the appropriate boundary and loading conditions are applied and the equations for the field displacements are solved. Based on the adhesive stress distributions, the forces at the crack tip are obtained and the strain energy release rate of the crack is determined by using the virtual crack closure technique (VCCT). Additionally, the test specimen geometry from both the ASTM D3165 and D1002 test standards are utilized during the derivation of the field equations in order to correlate analytical models with future test results. The system of second-order differential field equations is solved to provide the adherend and adhesive stress response using the symbolic computation tool, Maple 9. Finite element analyses using J-integral as well as VCCT were performed to verify the developed analytical model. The finite element analyses were conducted using the commercial finite element analysis software ABAQUS. The results determined using the analytical method correlated well with the results from the finite element analyses.

Long-term urine biobanking: storage stability of clinical chemical parameters under moderate freezing conditions without use of preservatives.

PubMed

Remer, Thomas; Montenegro-Bethancourt, Gabriela; Shi, Lijie

2014-12-01

To examine the long-term stability and validity of analyte concentrations of 21 clinical biochemistry parameters in 24-h urine samples stored for 12 or 15 yr at -22°C and preservative free. Healthy children's 24-h urine samples in which the respective analytes had been measured shortly after sample collection (baseline) were reanalyzed. Second measurement was performed after 12 yr (organic acids) and 15 yr (creatinine, urea, osmolality, iodine, nitrogen, anions, cations, acid-base parameters) with the same analytical methodology. Paired comparisons and correlations between the baseline and repeated measurements were done. Recovery rates were calculated. More than half of the analytes (creatinine, urea, iodine, nitrogen, sodium, potassium, magnesium, calcium, ammonium, bicarbonate, citric & uric acid) showed measurement values after >10 yr of storage not significantly different from baseline. 15 of the 21 parameters were highly correlated (r=0.99) between baseline and second measurement. Poorest correlation was r=0.77 for oxalate. Recovery ranged from 73% (oxalate) to 105% (phosphate). Our results suggest high long-term stability and measurement validity for numerous clinical chemistry parameters stored at -22°C without addition of any urine preservative. Prospective storage of urine aliquots at -22°C for periods even exceeding 10 yr, appears to be an acceptable and valid tool in epidemiological settings for later quantification of several urine analytes. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Semi-Analytical Models of CO2 Injection into Deep Saline Aquifers: Evaluation of the Area of Review and Leakage through Abandoned Wells

EPA Science Inventory

This presentation will provide a conceptual preview of an Area of Review (AoR) tool being developed by EPA’s Office of Research and Development that applies analytic and semi-analytical mathematical solutions to elucidate potential risks associated with geologic sequestration of ...

The Broad Application of Data Science and Analytics: Essential Tools for the Liberal Arts Graduate

ERIC Educational Resources Information Center

Cárdenas-Navia, Isabel; Fitzgerald, Brian K.

2015-01-01

New technologies and data science are transforming a wide range of organizations into analytics-intensive enterprises. Despite the resulting demand for graduates with experience in the application of analytics, though, undergraduate education has been slow to change. The academic and policy communities have engaged in a decade-long conversation…

Analytic Shielding Optimization to Reduce Crew Exposure to Ionizing Radiation Inside Space Vehicles

NASA Technical Reports Server (NTRS)

Gaza, Razvan; Cooper, Tim P.; Hanzo, Arthur; Hussein, Hesham; Jarvis, Kandy S.; Kimble, Ryan; Lee, Kerry T.; Patel, Chirag; Reddell, Brandon D.; Stoffle, Nicholas;

Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory.

PubMed

Kumar, B Vinodh; Mohan, Thuthi

2018-01-01

Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes.

Headspace-Solid-Phase Microextraction-Gas Chromatography as Analytical Methodology for the Determination of Volatiles in Wild Mushrooms and Evaluation of Modifications Occurring during Storage

PubMed Central

Costa, Rosaria; De Grazia, Selenia; Grasso, Elisa; Trozzi, Alessandra

2015-01-01

Mushrooms are sources of food, medicines, and agricultural means. Not much is reported in the literature about wild species of the Mediterranean flora, although many of them are traditionally collected for human consumption. The knowledge of their chemical constituents could represent a valid tool for both taxonomic and physiological characterizations. In this work, a headspace-solid-phase microextraction (HS-SPME) method coupled with GC-MS and GC-FID was developed to evaluate the volatile profiles of ten wild mushroom species collected in South Italy. In addition, in order to evaluate the potential of this analytical methodology for true quantitation of volatiles, samples of the cultivated species Agaricus bisporus were analyzed. The choice of this mushroom was dictated by its ease of availability in the food market, due to the consistent amounts required for SPME method development. For calibration of the main volatile compounds, the standard addition method was chosen. Finally, the assessed volatile composition of A. bisporus was monitored in order to evaluate compositional changes occurring during storage, which represents a relevant issue for such a wide consumption edible product. PMID:25945282

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

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

Franklin, Lyndsey; Pirrung, Megan A.; Blaha, Leslie M.

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat modelsmore » that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.« less

Bayesian variable selection for post-analytic interrogation of susceptibility loci.

PubMed

Chen, Siying; Nunez, Sara; Reilly, Muredach P; Foulkes, Andrea S

2017-06-01

Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material. © 2016, The International Biometric Society.

Interpretation of biomonitoring data in clinical medicine and the exposure sciences

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

Williams, Bryan L.; Barr, Dana B.; Wright, J. Michael

2008-11-15

Biomonitoring has become a fundamental tool in both exposure science and clinical medicine. Despite significant analytical advances, the clinical use of environmental biomarkers remains in its infancy. Clinical use of environmental biomarkers poses some complex scientific and ethical challenges. The purpose of this paper is compare how the clinical and exposure sciences differ with respect to their interpretation and use of biological data. Additionally, the clinical use of environmental biomonitoring data is discussed. A case study is used to illustrate the complexities of conducting biomonitoring research on highly vulnerable populations in a clinical setting.

Simplex-stochastic collocation method with improved scalability

NASA Astrophysics Data System (ADS)

Edeling, W. N.; Dwight, R. P.; Cinnella, P.

2016-04-01

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

Science & Technology Review September 2005

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

Aufderheide III, M B

2005-07-19

This month's issue has the following articles: (1) The Pursuit of Fusion Energy--Commentary by William H. Goldstein; (2) A Dynamo of a Plasma--The self-organizing magnetized plasmas in a Livermore fusion energy experiment are akin to solar flares and galactic jets; (3) How One Equation Changed the World--A three-page paper by Albert Einstein revolutionized physics by linking mass and energy; (4) Recycled Equations Help Verify Livermore Codes--New analytic solutions for imploding spherical shells give scientists additional tools for verifying codes; and (5) Dust That.s Worth Keeping--Scientists have solved the mystery of an astronomical spectral feature in interplanetary dust particles.

Accelerated bridge construction (ABC) decision making and economic modeling tool.

DOT National Transportation Integrated Search

2011-12-01

In this FHWA-sponsored pool funded study, a set of decision making tools, based on the Analytic Hierarchy Process (AHP) was developed. This tool set is prepared for transportation specialists and decision-makers to determine if ABC is more effective ...

17 CFR 49.17 - Access to SDR data.

Code of Federal Regulations, 2013 CFR

2013-04-01

... legal and statutory responsibilities under the Act and related regulations. (2) Monitoring tools. A registered swap data repository is required to provide the Commission with proper tools for the monitoring... data structure and content. These monitoring tools shall be substantially similar in analytical...

17 CFR 49.17 - Access to SDR data.

Code of Federal Regulations, 2014 CFR

2014-04-01

... legal and statutory responsibilities under the Act and related regulations. (2) Monitoring tools. A registered swap data repository is required to provide the Commission with proper tools for the monitoring... data structure and content. These monitoring tools shall be substantially similar in analytical...

Assessment Tools' Indicators for Sustainability in Universities: An Analytical Overview

ERIC Educational Resources Information Center

Alghamdi, Naif; den Heijer, Alexandra; de Jonge, Hans

2017-01-01

Purpose: The purpose of this paper is to analyse 12 assessment tools of sustainability in universities and develop the structure and the contents of these tools to be more intelligible. The configuration of the tools reviewed highlight indicators that clearly communicate only the essential information. This paper explores how the theoretical…

MRMPlus: an open source quality control and assessment tool for SRM/MRM assay development.

PubMed

Aiyetan, Paul; Thomas, Stefani N; Zhang, Zhen; Zhang, Hui

2015-12-12

Selected and multiple reaction monitoring involves monitoring a multiplexed assay of proteotypic peptides and associated transitions in mass spectrometry runs. To describe peptide and associated transitions as stable, quantifiable, and reproducible representatives of proteins of interest, experimental and analytical validation is required. However, inadequate and disparate analytical tools and validation methods predispose assay performance measures to errors and inconsistencies. Implemented as a freely available, open-source tool in the platform independent Java programing language, MRMPlus computes analytical measures as recommended recently by the Clinical Proteomics Tumor Analysis Consortium Assay Development Working Group for "Tier 2" assays - that is, non-clinical assays sufficient enough to measure changes due to both biological and experimental perturbations. Computed measures include; limit of detection, lower limit of quantification, linearity, carry-over, partial validation of specificity, and upper limit of quantification. MRMPlus streamlines assay development analytical workflow and therefore minimizes error predisposition. MRMPlus may also be used for performance estimation for targeted assays not described by the Assay Development Working Group. MRMPlus' source codes and compiled binaries can be freely downloaded from https://bitbucket.org/paiyetan/mrmplusgui and https://bitbucket.org/paiyetan/mrmplusgui/downloads respectively.

Big data analytics in immunology: a knowledge-based approach.

PubMed

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Big data analytics workflow management for eScience

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Palazzo, Cosimo; Elia, Donatello; Mariello, Andrea; Nassisi, Paola; Aloisio, Giovanni

2015-04-01

In many domains such as climate and astrophysics, scientific data is often n-dimensional and requires tools that support specialized data types and primitives if it is to be properly stored, accessed, analysed and visualized. Currently, scientific data analytics relies on domain-specific software and libraries providing a huge set of operators and functionalities. However, most of these software fail at large scale since they: (i) are desktop based, rely on local computing capabilities and need the data locally; (ii) cannot benefit from available multicore/parallel machines since they are based on sequential codes; (iii) do not provide declarative languages to express scientific data analysis tasks, and (iv) do not provide newer or more scalable storage models to better support the data multidimensionality. Additionally, most of them: (v) are domain-specific, which also means they support a limited set of data formats, and (vi) do not provide a workflow support, to enable the construction, execution and monitoring of more complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides several parallel operators to manipulate large datasets. Some relevant examples include: (i) data sub-setting (slicing and dicing), (ii) data aggregation, (iii) array-based primitives (the same operator applies to all the implemented UDF extensions), (iv) data cube duplication, (v) data cube pivoting, (vi) NetCDF-import and export. Metadata operators are available too. Additionally, the Ophidia framework provides array-based primitives to perform data sub-setting, data aggregation (i.e. max, min, avg), array concatenation, algebraic expressions and predicate evaluation on large arrays of scientific data. Bit-oriented plugins have also been implemented to manage binary data cubes. Defining processing chains and workflows with tens, hundreds of data analytics operators is the real challenge in many practical scientific use cases. This talk will specifically address the main needs, requirements and challenges regarding data analytics workflow management applied to large scientific datasets. Three real use cases concerning analytics workflows for sea situational awareness, fire danger prevention, climate change and biodiversity will be discussed in detail.

Update on SLD Engineering Tools Development

NASA Technical Reports Server (NTRS)

Miller, Dean R.; Potapczuk, Mark G.; Bond, Thomas H.

2004-01-01

The airworthiness authorities (FAA, JAA, Transport Canada) will be releasing a draft rule in the 2006 timeframe concerning the operation of aircraft in a Supercooled Large Droplet (SLD) environment aloft. The draft rule will require aircraft manufacturers to demonstrate that their aircraft can operate safely in an SLD environment for a period of time to facilitate a safe exit from the condition. It is anticipated that aircraft manufacturers will require a capability to demonstrate compliance with this rule via experimental means (icing tunnels or tankers) and by analytical means (ice prediction codes). Since existing icing research facilities and analytical codes were not developed to account for SLD conditions, current engineering tools are not adequate to support compliance activities in SLD conditions. Therefore, existing capabilities need to be augmented to include SLD conditions. In response to this need, NASA and its partners conceived a strategy or Roadmap for developing experimental and analytical SLD simulation tools. Following review and refinement by the airworthiness authorities and other international research partners, this technical strategy has been crystallized into a project plan to guide the SLD Engineering Tool Development effort. This paper will provide a brief overview of the latest version of the project plan and technical rationale, and provide a status of selected SLD Engineering Tool Development research tasks which are currently underway.

76 FR 70517 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-14

... requested. These systems generally also provide analytics, spreadsheets, and other tools designed to enable funds to analyze the data presented, as well as communication tools to process fund instructions...

The Rack-Gear Tool Generation Modelling. Non-Analytical Method Developed in CATIA, Using the Relative Generating Trajectories Method

NASA Astrophysics Data System (ADS)

Teodor, V. G.; Baroiu, N.; Susac, F.; Oancea, N.

2016-11-01

The modelling of a curl of surfaces associated with a pair of rolling centrodes, when it is known the profile of the rack-gear's teeth profile, by direct measuring, as a coordinate matrix, has as goal the determining of the generating quality for an imposed kinematics of the relative motion of tool regarding the blank. In this way, it is possible to determine the generating geometrical error, as a base of the total error. The generation modelling allows highlighting the potential errors of the generating tool, in order to correct its profile, previously to use the tool in machining process. A method developed in CATIA is proposed, based on a new method, namely the method of “relative generating trajectories”. They are presented the analytical foundation, as so as some application for knows models of rack-gear type tools used on Maag teething machines.

SU-C-204-01: A Fast Analytical Approach for Prompt Gamma and PET Predictions in a TPS for Proton Range Verification

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

Kroniger, K; Herzog, M; Landry, G

2015-06-15

Purpose: We describe and demonstrate a fast analytical tool for prompt-gamma emission prediction based on filter functions applied on the depth dose profile. We present the implementation in a treatment planning system (TPS) of the same algorithm for positron emitter distributions. Methods: The prediction of the desired observable is based on the convolution of filter functions with the depth dose profile. For both prompt-gammas and positron emitters, the results of Monte Carlo simulations (MC) are compared with those of the analytical tool. For prompt-gamma emission from inelastic proton-induced reactions, homogeneous and inhomogeneous phantoms alongside with patient data are used asmore » irradiation targets of mono-energetic proton pencil beams. The accuracy of the tool is assessed in terms of the shape of the analytically calculated depth profiles and their absolute yields, compared to MC. For the positron emitters, the method is implemented in a research RayStation TPS and compared to MC predictions. Digital phantoms and patient data are used and positron emitter spatial density distributions are analyzed. Results: Calculated prompt-gamma profiles agree with MC within 3 % in terms of absolute yield and reproduce the correct shape. Based on an arbitrary reference material and by means of 6 filter functions (one per chemical element), profiles in any other material composed of those elements can be predicted. The TPS implemented algorithm is accurate enough to enable, via the analytically calculated positron emitters profiles, detection of range differences between the TPS and MC with errors of the order of 1–2 mm. Conclusion: The proposed analytical method predicts prompt-gamma and positron emitter profiles which generally agree with the distributions obtained by a full MC. The implementation of the tool in a TPS shows that reliable profiles can be obtained directly from the dose calculated by the TPS, without the need of full MC simulation.« less

Progress in the Modeling of NiAl-Based Alloys Using the BFS Method

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Noebe, Ronald D.; Ferrante, John; Garg, Anita

1997-01-01

The BFS method has been applied to the study of NiAl-based materials to assess the effect of alloying additions on structure. Ternary, quaternary and even pent-alloys based on Ni-rich NiAl with additions of Ti, Cr and Cu were studied. Two approaches were used, Monte Carlo simulations to determine ground state structures and analytical calculations of high symmetry configurations which give physical insight into preferred bonding. Site occupancy energetics for ternary and the more complicated case of quaternary additions were determined, and solubility limits and precipitate formation with corresponding information concerning structure and lattice parameter were also 'observed' computationally. The method was also applied to determine the composition of alloy surfaces and interfaces. Overall, the results demonstrate that the BFS method for alloys is a powerful tool for alloy design and with its simplicity and obvious advantages can be used to complement any experimental alloy design program.

Synthesis of Feedback Controller for Chaotic Systems by Means of Evolutionary Techniques

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Oplatkova, Zuzana; Zelinka, Ivan; Davendra, Donald; Jasek, Roman

2011-06-01

This research deals with a synthesis of control law for three selected discrete chaotic systems by means of analytic programming. The novality of the approach is that a tool for symbolic regression—analytic programming—is used for such kind of difficult problem. The paper consists of the descriptions of analytic programming as well as chaotic systems and used cost function. For experimentation, Self-Organizing Migrating Algorithm (SOMA) with analytic programming was used.

Value-informed space systems design and acquisition

NASA Astrophysics Data System (ADS)

Brathwaite, Joy

Investments in space systems are substantial, indivisible, and irreversible, characteristics that make them high-risk, especially when coupled with an uncertain demand environment. Traditional approaches to system design and acquisition, derived from a performance- or cost-centric mindset, incorporate little information about the spacecraft in relation to its environment and its value to its stakeholders. These traditional approaches, while appropriate in stable environments, are ill-suited for the current, distinctly uncertain, and rapidly changing technical and economic conditions; as such, they have to be revisited and adapted to the present context. This thesis proposes that in uncertain environments, decision-making with respect to space system design and acquisition should be value-based, or at a minimum value-informed. This research advances the value-centric paradigm by providing the theoretical basis, foundational frameworks, and supporting analytical tools for value assessment of priced and unpriced space systems. For priced systems, stochastic models of the market environment and financial models of stakeholder preferences are developed and integrated with a spacecraft-sizing tool to assess the system's net present value. The analytical framework is applied to a case study of a communications satellite, with market, financial, and technical data obtained from the satellite operator, Intelsat. The case study investigates the implications of the value-centric versus the cost-centric design and acquisition choices. Results identify the ways in which value-optimal spacecraft design choices are contingent on both technical and market conditions, and that larger spacecraft for example, which reap economies of scale benefits, as reflected by their decreasing cost-per-transponder, are not always the best (most valuable) choices. Market conditions and technical constraints for which convergence occurs between design choices under a cost-centric and a value-centric approach are identified and discussed. In addition, an innovative approach for characterizing value uncertainty through partial moments, a technique used in finance, is adapted to an engineering context and applied to priced space systems. Partial moments disaggregate uncertainty into upside potential and downside risk, and as such, they provide the decision-maker with additional insights for value-uncertainty management in design and acquisition. For unpriced space systems, this research first posits that their value derives from, and can be assessed through, the value of information they provide. To this effect, a Bayesian framework is created to assess system value in which the system is viewed as an information provider and the stakeholder an information recipient. Information has value to stakeholders as it changes their rational beliefs enabling them to yield higher expected pay-offs. Based on this marginal increase in expected pay-offs, a new metric, Value-of-Design (VoD), is introduced to quantify the unpriced system’s value. The Bayesian framework is applied to the case of an Earth Science satellite that provides hurricane information to oil rig operators using nested Monte Carlo modeling and simulation. Probability models of stakeholders’ beliefs, and economic models of pay-offs are developed and integrated with a spacecraft payload generation tool. The case study investigates the information value generated by each payload, with results pointing to clusters of payload instruments that yielded higher information value, and minimum information thresholds below which it is difficult to justify the acquisition of the system. In addition, an analytical decision tool, probabilistic Pareto fronts, is developed in the Cost-VoD trade space to provide the decision-maker with additional insights into the coupling of a system's probable value generation and its associated cost risk.

Nutritional Lipidomics: Molecular Metabolism, Analytics, and Diagnostics

PubMed Central

Smilowitz, Jennifer T.; Zivkovic, Angela M.; Wan, Yu-Jui Yvonne; Watkins, Steve M.; Nording, Malin L.; Hammock, Bruce D.; German, J. Bruce

2013-01-01

The field of lipidomics is providing nutritional science a more comprehensive view of lipid intermediates. Lipidomics research takes advantage of the increase in accuracy and sensitivity of mass detection of mass spectrometry with new bioinformatics toolsets to characterize the structures and abundances of complex lipids. Yet, translating lipidomics to practice via nutritional interventions is still in its infancy. No single instrumentation platform is able to solve the varying analytical challenges of the different molecular lipid species. Biochemical pathways of lipid metabolism remain incomplete and the tools to map lipid compositional data to pathways are still being assembled. Biology itself is dauntingly complex and simply separating biological structures remains a key challenge to lipidomics. Nonetheless, the strategy of combining tandem analytical methods to perform the sensitive, high-throughput, quantitative and comprehensive analysis of lipid metabolites of very large numbers of molecules is poised to drive the field forward rapidly. Among the next steps for nutrition to understand the changes in structures, compositions and function of lipid biomolecules in response to diet is to describe their distribution within discrete functional compartments-lipoproteins. Additionally, lipidomics must tackle the task of assigning the functions of lipids as signaling molecules, nutrient sensors, and intermediates of metabolic pathways. PMID:23818328

THE FUTURE OF SUSTAINABLE MANAGEMENT APPROACHES AND REVITALIZATION TOOLS-ELECTRONIC (SMARTE): 2006-2010

EPA Science Inventory

SMARTe is being developed to give stakeholders information resources, analytical tools, communication strategies, and a decision analysis approach to be able to make better decisions regarding future uses of property. The development of the communication tools and decision analys...

High-density fuel effects. Final report, September 1985-April 1988

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

Rizk, N.K.; Oechsie, V.L.; Ross, P.T.

1988-08-18

The purpose of this program was to determine, by combustor rig tests and data evaluation, the effects of the high-density fuel properties on the performance and durability of the Allison T56-A-15 combustion system. Four high-density fuels in addition to baseline JP4 were evaluated in the effort. The rig-test program included: nozzle-flow bench testing, aerothermal performance and wall temperature, flame stability and ignition, injector coking and plugging, and flow-transient effect. The data-evaluation effort involved the utilization of empirical correlations in addition to analytical multidimensional tools to analyze the performance of the combustor. The modifications required to optimize the performance with high-densitymore » fuels were suggested and the expected improvement in performance was evaluated.« less

Characterization of hydraulic fracturing flowback water in Colorado: Implications for water treatment

USGS Publications Warehouse

Lester, Yaal; Ferrer, Imma; Thurman, E. Michael; Sitterley, Kurban A.; Korak, Julie A.; Aiken, George R.; Linden, Karl G.

2015-01-01

A suite of analytical tools was applied to thoroughly analyze the chemical composition of an oil/gas well flowback water from the Denver–Julesburg (DJ) basin in Colorado, and the water quality data was translated to propose effective treatment solutions tailored to specific reuse goals. Analysis included bulk quality parameters, trace organic and inorganic constituents, and organic matter characterization. The flowback sample contained salts (TDS = 22,500 mg/L), metals (e.g., iron at 81.4 mg/L) and high concentration of dissolved organic matter (DOC = 590 mgC/L). The organic matter comprised fracturing fluid additives such as surfactants (e.g., linear alkyl ethoxylates) and high levels of acetic acid (an additives' degradation product), indicating the anthropogenic impact on this wastewater. Based on the water quality results and preliminary treatability tests, the removal of suspended solids and iron by aeration/precipitation (and/or filtration) followed by disinfection was identified as appropriate for flowback recycling in future fracturing operations. In addition to these treatments, a biological treatment (to remove dissolved organic matter) followed by reverse osmosis desalination was determined to be necessary to attain water quality standards appropriate for other water reuse options (e.g., crop irrigation). The study provides a framework for evaluating site-specific hydraulic fracturing wastewaters, proposing a suite of analytical methods for characterization, and a process for guiding the choice of a tailored treatment approach.

Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays

PubMed Central

Hsieh, Helen V.; Dantzler, Jeffrey L.; Weigl, Bernhard H.

2017-01-01

Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness. PMID:28555034

User`s and reference guide to the INEL RML/analytical radiochemistry sample tracking database version 1.00

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

Femec, D.A.

This report discusses the sample tracking database in use at the Idaho National Engineering Laboratory (INEL) by the Radiation Measurements Laboratory (RML) and Analytical Radiochemistry. The database was designed in-house to meet the specific needs of the RML and Analytical Radiochemistry. The report consists of two parts, a user`s guide and a reference guide. The user`s guide presents some of the fundamentals needed by anyone who will be using the database via its user interface. The reference guide describes the design of both the database and the user interface. Briefly mentioned in the reference guide are the code-generating tools, CREATE-SCHEMAmore » and BUILD-SCREEN, written to automatically generate code for the database and its user interface. The appendices contain the input files used by the these tools to create code for the sample tracking database. The output files generated by these tools are also included in the appendices.« less

Exhaled breath condensate – from an analytical point of view

PubMed Central

Dodig, Slavica; Čepelak, Ivana

2013-01-01

Over the past three decades, the goal of many researchers is analysis of exhaled breath condensate (EBC) as noninvasively obtained sample. A total quality in laboratory diagnostic processes in EBC analysis was investigated: pre-analytical (formation, collection, storage of EBC), analytical (sensitivity of applied methods, standardization) and post-analytical (interpretation of results) phases. EBC analysis is still used as a research tool. Limitations referred to pre-analytical, analytical, and post-analytical phases of EBC analysis are numerous, e.g. low concentrations of EBC constituents, single-analyte methods lack in sensitivity, and multi-analyte has not been fully explored, and reference values are not established. When all, pre-analytical, analytical and post-analytical requirements are met, EBC biomarkers as well as biomarker patterns can be selected and EBC analysis can hopefully be used in clinical practice, in both, the diagnosis and in the longitudinal follow-up of patients, resulting in better outcome of disease. PMID:24266297

An improved multiple flame photometric detector for gas chromatography.

PubMed

Clark, Adrian G; Thurbide, Kevin B

2015-11-20

An improved multiple flame photometric detector (mFPD) is introduced, based upon interconnecting fluidic channels within a planar stainless steel (SS) plate. Relative to the previous quartz tube mFPD prototype, the SS mFPD provides a 50% reduction in background emission levels, an orthogonal analytical flame, and easier more sensitive operation. As a result, sulfur response in the SS mFPD spans 4 orders of magnitude, yields a minimum detectable limit near 9×10(-12)gS/s, and has a selectivity approaching 10(4) over carbon. The device also exhibits exceptionally large resistance to hydrocarbon response quenching. Additionally, the SS mFPD uniquely allows analyte emission monitoring in the multiple worker flames for the first time. The findings suggest that this mode can potentially further improve upon the analytical flame response of sulfur (both linear HSO, and quadratic S2) and also phosphorus. Of note, the latter is nearly 20-fold stronger in S/N in the collective worker flames response and provides 6 orders of linearity with a detection limit of about 2.0×10(-13)gP/s. Overall, the results indicate that this new SS design notably improves the analytical performance of the mFPD and can provide a versatile and beneficial monitoring tool for gas chromatography. Copyright © 2015 Elsevier B.V. All rights reserved.

Software Tools on the Peregrine System | High-Performance Computing | NREL

Science.gov Websites

Debugger or performance analysis Tool for understanding the behavior of MPI applications. Intel VTune environment for statistical computing and graphics. VirtualGL/TurboVNC Visualization and analytics Remote Tools on the Peregrine System Software Tools on the Peregrine System NREL has a variety of

Mass spectrometry as a quantitative tool in plant metabolomics

PubMed Central

Jorge, Tiago F.; Mata, Ana T.

2016-01-01

Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644967

The NASA Reanalysis Ensemble Service - Advanced Capabilities for Integrated Reanalysis Access and Intercomparison

NASA Astrophysics Data System (ADS)

Tamkin, G.; Schnase, J. L.; Duffy, D.; Li, J.; Strong, S.; Thompson, J. H.

2017-12-01

NASA's efforts to advance climate analytics-as-a-service are making new capabilities available to the research community: (1) A full-featured Reanalysis Ensemble Service (RES) comprising monthly means data from multiple reanalysis data sets, accessible through an enhanced set of extraction, analytic, arithmetic, and intercomparison operations. The operations are made accessible through NASA's climate data analytics Web services and our client-side Climate Data Services Python library, CDSlib; (2) A cloud-based, high-performance Virtual Real-Time Analytics Testbed supporting a select set of climate variables. This near real-time capability enables advanced technologies like Spark and Hadoop-based MapReduce analytics over native NetCDF files; and (3) A WPS-compliant Web service interface to our climate data analytics service that will enable greater interoperability with next-generation systems such as ESGF. The Reanalysis Ensemble Service includes the following: - New API that supports full temporal, spatial, and grid-based resolution services with sample queries - A Docker-ready RES application to deploy across platforms - Extended capabilities that enable single- and multiple reanalysis area average, vertical average, re-gridding, standard deviation, and ensemble averages - Convenient, one-stop shopping for commonly used data products from multiple reanalyses including basic sub-setting and arithmetic operations (e.g., avg, sum, max, min, var, count, anomaly) - Full support for the MERRA-2 reanalysis dataset in addition to, ECMWF ERA-Interim, NCEP CFSR, JMA JRA-55 and NOAA/ESRL 20CR… - A Jupyter notebook-based distribution mechanism designed for client use cases that combines CDSlib documentation with interactive scenarios and personalized project management - Supporting analytic services for NASA GMAO Forward Processing datasets - Basic uncertainty quantification services that combine heterogeneous ensemble products with comparative observational products (e.g., reanalysis, observational, visualization) - The ability to compute and visualize multiple reanalysis for ease of inter-comparisons - Automated tools to retrieve and prepare data collections for analytic processing

NASTRAN as an analytical research tool for composite mechanics and composite structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Sinclair, J. H.; Sullivan, T. L.

1976-01-01

Selected examples are described in which NASTRAN is used as an analysis research tool for composite mechanics and for composite structural components. The examples were selected to illustrate the importance of using NASTRAN as an analysis tool in this rapidly advancing field.

Modeling Biodegradation and Reactive Transport: Analytical and Numerical Models

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

Sun, Y; Glascoe, L

The computational modeling of the biodegradation of contaminated groundwater systems accounting for biochemical reactions coupled to contaminant transport is a valuable tool for both the field engineer/planner with limited computational resources and the expert computational researcher less constrained by time and computer power. There exists several analytical and numerical computer models that have been and are being developed to cover the practical needs put forth by users to fulfill this spectrum of computational demands. Generally, analytical models provide rapid and convenient screening tools running on very limited computational power, while numerical models can provide more detailed information with consequent requirementsmore » of greater computational time and effort. While these analytical and numerical computer models can provide accurate and adequate information to produce defensible remediation strategies, decisions based on inadequate modeling output or on over-analysis can have costly and risky consequences. In this chapter we consider both analytical and numerical modeling approaches to biodegradation and reactive transport. Both approaches are discussed and analyzed in terms of achieving bioremediation goals, recognizing that there is always a tradeoff between computational cost and the resolution of simulated systems.« less

Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.

PubMed

Fan Du; Shneiderman, Ben; Plaisant, Catherine; Malik, Sana; Perer, Adam

2017-06-01

The growing volume and variety of data presents both opportunities and challenges for visual analytics. Addressing these challenges is needed for big data to provide valuable insights and novel solutions for business, security, social media, and healthcare. In the case of temporal event sequence analytics it is the number of events in the data and variety of temporal sequence patterns that challenges users of visual analytic tools. This paper describes 15 strategies for sharpening analytic focus that analysts can use to reduce the data volume and pattern variety. Four groups of strategies are proposed: (1) extraction strategies, (2) temporal folding, (3) pattern simplification strategies, and (4) iterative strategies. For each strategy, we provide examples of the use and impact of this strategy on volume and/or variety. Examples are selected from 20 case studies gathered from either our own work, the literature, or based on email interviews with individuals who conducted the analyses and developers who observed analysts using the tools. Finally, we discuss how these strategies might be combined and report on the feedback from 10 senior event sequence analysts.

Differentiation of organic and non-organic winter wheat cultivars from a controlled field trial by crystallization patterns.

PubMed

Kahl, Johannes; Busscher, Nicolaas; Mergardt, Gaby; Mäder, Paul; Torp, Torfinn; Ploeger, Angelika

2015-01-01

There is a need for authentication tools in order to verify the existing certification system. Recently, markers for analytical authentication of organic products were evaluated. Herein, crystallization with additives was described as an interesting fingerprint approach which needs further evidence, based on a standardized method and well-documented sample origin. The fingerprint of wheat cultivars from a controlled field trial is generated from structure analysis variables of crystal patterns. Method performance was tested on factors such as crystallization chamber, day of experiment and region of interest of the patterns. Two different organic treatments and two different treatments of the non-organic regime can be grouped together in each of three consecutive seasons. When the k-nearest-neighbor classification method was applied, approximately 84% of Runal samples and 95% of Titlis samples were classified correctly into organic and non-organic origin using cross-validation. Crystallization with additive offers an interesting complementary fingerprint method for organic wheat samples. When the method is applied to winter wheat from the DOK trial, organic and non-organic treated samples can be differentiated significantly based on pattern recognition. Therefore crystallization with additives seems to be a promising tool in organic wheat authentication. © 2014 Society of Chemical Industry.

Diving deeper into Zebrafish development of social behavior: analyzing high resolution data.

PubMed

Buske, Christine; Gerlai, Robert

2014-08-30

Vertebrate model organisms have been utilized in high throughput screening but only with substantial cost and human capital investment. The zebrafish is a vertebrate model species that is a promising and cost effective candidate for efficient high throughput screening. Larval zebrafish have already been successfully employed in this regard (Lessman, 2011), but adult zebrafish also show great promise. High throughput screening requires the use of a large number of subjects and collection of substantial amount of data. Collection of data is only one of the demanding aspects of screening. However, in most screening approaches that involve behavioral data the main bottleneck that slows throughput is the time consuming aspect of analysis of the collected data. Some automated analytical tools do exist, but often they only work for one subject at a time, eliminating the possibility of fully utilizing zebrafish as a screening tool. This is a particularly important limitation for such complex phenotypes as social behavior. Testing multiple fish at a time can reveal complex social interactions but it may also allow the identification of outliers from a group of mutagenized or pharmacologically treated fish. Here, we describe a novel method using a custom software tool developed within our laboratory, which enables tracking multiple fish, in combination with a sophisticated analytical approach for summarizing and analyzing high resolution behavioral data. This paper focuses on the latter, the analytic tool, which we have developed using the R programming language and environment for statistical computing. We argue that combining sophisticated data collection methods with appropriate analytical tools will propel zebrafish into the future of neurobehavioral genetic research. Copyright © 2014. Published by Elsevier B.V.

ANALYTICAL TOOLS FOR GROUNDWATER POLLUTION ASSESSMENT

EPA Science Inventory

This paper deals with the development of analytical screening-exposure models (indices) and their potential application to regulate the use of hazardous chemicals and the design of groundwater buffer strips. The indices describe the leaching of solutes below the root zone (mass f...

Structuring modeling and simulation analysis for evacuation planning and operations.

DOT National Transportation Integrated Search

2009-06-01

This document is intended to provide guidance to decision-makers at agencies and jurisdictions considering the role of analytical tools in evacuation planning and operations. It is often unclear what kind of analytical approach may be of most value, ...

3D-MICE: integration of cross-sectional and longitudinal imputation for multi-analyte longitudinal clinical data.

PubMed

Luo, Yuan; Szolovits, Peter; Dighe, Anand S; Baron, Jason M

2018-06-01

A key challenge in clinical data mining is that most clinical datasets contain missing data. Since many commonly used machine learning algorithms require complete datasets (no missing data), clinical analytic approaches often entail an imputation procedure to "fill in" missing data. However, although most clinical datasets contain a temporal component, most commonly used imputation methods do not adequately accommodate longitudinal time-based data. We sought to develop a new imputation algorithm, 3-dimensional multiple imputation with chained equations (3D-MICE), that can perform accurate imputation of missing clinical time series data. We extracted clinical laboratory test results for 13 commonly measured analytes (clinical laboratory tests). We imputed missing test results for the 13 analytes using 3 imputation methods: multiple imputation with chained equations (MICE), Gaussian process (GP), and 3D-MICE. 3D-MICE utilizes both MICE and GP imputation to integrate cross-sectional and longitudinal information. To evaluate imputation method performance, we randomly masked selected test results and imputed these masked results alongside results missing from our original data. We compared predicted results to measured results for masked data points. 3D-MICE performed significantly better than MICE and GP-based imputation in a composite of all 13 analytes, predicting missing results with a normalized root-mean-square error of 0.342, compared to 0.373 for MICE alone and 0.358 for GP alone. 3D-MICE offers a novel and practical approach to imputing clinical laboratory time series data. 3D-MICE may provide an additional tool for use as a foundation in clinical predictive analytics and intelligent clinical decision support.

Moving standard deviation and moving sum of outliers as quality tools for monitoring analytical precision.

PubMed

Liu, Jiakai; Tan, Chin Hon; Badrick, Tony; Loh, Tze Ping

2018-02-01

An increase in analytical imprecision (expressed as CV a ) can introduce additional variability (i.e. noise) to the patient results, which poses a challenge to the optimal management of patients. Relatively little work has been done to address the need for continuous monitoring of analytical imprecision. Through numerical simulations, we describe the use of moving standard deviation (movSD) and a recently described moving sum of outlier (movSO) patient results as means for detecting increased analytical imprecision, and compare their performances against internal quality control (QC) and the average of normal (AoN) approaches. The power of detecting an increase in CV a is suboptimal under routine internal QC procedures. The AoN technique almost always had the highest average number of patient results affected before error detection (ANPed), indicating that it had generally the worst capability for detecting an increased CV a . On the other hand, the movSD and movSO approaches were able to detect an increased CV a at significantly lower ANPed, particularly for measurands that displayed a relatively small ratio of biological variation to CV a. CONCLUSION: The movSD and movSO approaches are effective in detecting an increase in CV a for high-risk measurands with small biological variation. Their performance is relatively poor when the biological variation is large. However, the clinical risks of an increase in analytical imprecision is attenuated for these measurands as an increased analytical imprecision will only add marginally to the total variation and less likely to impact on the clinical care. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Chemometrics in analytical chemistry-part I: history, experimental design and data analysis tools.

PubMed

Brereton, Richard G; Jansen, Jeroen; Lopes, João; Marini, Federico; Pomerantsev, Alexey; Rodionova, Oxana; Roger, Jean Michel; Walczak, Beata; Tauler, Romà

2017-10-01

Chemometrics has achieved major recognition and progress in the analytical chemistry field. In the first part of this tutorial, major achievements and contributions of chemometrics to some of the more important stages of the analytical process, like experimental design, sampling, and data analysis (including data pretreatment and fusion), are summarised. The tutorial is intended to give a general updated overview of the chemometrics field to further contribute to its dissemination and promotion in analytical chemistry.

SU-F-BRB-16: A Spreadsheet Based Automatic Trajectory GEnerator (SAGE): An Open Source Tool for Automatic Creation of TrueBeam Developer Mode Robotic Trajectories

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

Etmektzoglou, A; Mishra, P; Svatos, M

Purpose: To automate creation and delivery of robotic linac trajectories with TrueBeam Developer Mode, an open source spreadsheet-based trajectory generation tool has been developed, tested and made freely available. The computing power inherent in a spreadsheet environment plus additional functions programmed into the tool insulate users from the underlying schema tedium and allow easy calculation, parameterization, graphical visualization, validation and finally automatic generation of Developer Mode XML scripts which are directly loadable on a TrueBeam linac. Methods: The robotic control system platform that allows total coordination of potentially all linac moving axes with beam (continuous, step-and-shoot, or combination thereof) becomesmore » available in TrueBeam Developer Mode. Many complex trajectories are either geometric or can be described in analytical form, making the computational power, graphing and programmability available in a spreadsheet environment an easy and ideal vehicle for automatic trajectory generation. The spreadsheet environment allows also for parameterization of trajectories thus enabling the creation of entire families of trajectories using only a few variables. Standard spreadsheet functionality has been extended for powerful movie-like dynamic graphic visualization of the gantry, table, MLC, room, lasers, 3D observer placement and beam centerline all as a function of MU or time, for analysis of the motions before requiring actual linac time. Results: We used the tool to generate and deliver extended SAD “virtual isocenter” trajectories of various shapes such as parameterized circles and ellipses. We also demonstrated use of the tool in generating linac couch motions that simulate respiratory motion using analytical parameterized functions. Conclusion: The SAGE tool is a valuable resource to experiment with families of complex geometric trajectories for a TrueBeam Linac. It makes Developer Mode more accessible as a vehicle to quickly translate research ideas into machine readable scripts without programming knowledge. As an open source initiative, it also enables researcher collaboration on future developments. I am a full time employee at Varian Medical Systems, Palo Alto, California.« less

Critical Appraisal Toolkit (CAT) for assessing multiple types of evidence

PubMed Central

Moralejo, D; Ogunremi, T; Dunn, K

2017-01-01

Healthcare professionals are often expected to critically appraise research evidence in order to make recommendations for practice and policy development. Here we describe the Critical Appraisal Toolkit (CAT) currently used by the Public Health Agency of Canada. The CAT consists of: algorithms to identify the type of study design, three separate tools (for appraisal of analytic studies, descriptive studies and literature reviews), additional tools to support the appraisal process, and guidance for summarizing evidence and drawing conclusions about a body of evidence. Although the toolkit was created to assist in the development of national guidelines related to infection prevention and control, clinicians, policy makers and students can use it to guide appraisal of any health-related quantitative research. Participants in a pilot test completed a total of 101 critical appraisals and found that the CAT was user-friendly and helpful in the process of critical appraisal. Feedback from participants of the pilot test of the CAT informed further revisions prior to its release. The CAT adds to the arsenal of available tools and can be especially useful when the best available evidence comes from non-clinical trials and/or studies with weak designs, where other tools may not be easily applied. PMID:29770086

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland.

PubMed

Muellner, Ulrich J; Vial, Flavie; Wohlfender, Franziska; Hadorn, Daniela; Reist, Martin; Muellner, Petra

2015-01-01

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Open-source Software for Demand Forecasting of Clinical Laboratory Test Volumes Using Time-series Analysis.

PubMed

Mohammed, Emad A; Naugler, Christopher

2017-01-01

Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. This tool will allow anyone with historic test volume data to model future demand.

Open-source Software for Demand Forecasting of Clinical Laboratory Test Volumes Using Time-series Analysis

PubMed Central

Mohammed, Emad A.; Naugler, Christopher

2017-01-01

Background: Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. Method: In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. Results: This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. Conclusion: This tool will allow anyone with historic test volume data to model future demand. PMID:28400996

Analytical Tools Interface for Landscape Assessments

EPA Science Inventory

Environmental management practices are trending away from simple, local-scale assessments toward complex, multiple-stressor regional assessments. Landscape ecology provides the theory behind these assessments while geographic information systems (GIS) supply the tools to implemen...

SolarPILOT | Concentrating Solar Power | NREL

Science.gov Websites

tools. Unlike exclusively ray-tracing tools, SolarPILOT runs the analytical simulation engine that uses engine alongside a ray-tracing core for more detailed simulations. The SolTrace simulation engine is

Nuclear magnetic resonance magnet actively cooled by pulse tube refrigerator

NASA Astrophysics Data System (ADS)

Kirichek, Oleg; Carr, Philip; Johnson, Chris; Atrey, Milind

2005-05-01

High field NMR spectrometers have been an essential tool for biomolecular scientists for many years. They have been instrumental in the pursuit of understanding of the structure, function and dynamics of proteins and other biological molecules. In addition, NMR is increasingly used for small molecule applications such as metabonomics, providing capabilities that aid drug discovery, as well as general organic and inorganic chemistry [M. Pellecchia et al., Nature Reviews Drug Discovery 1, 211 (2002)]. However, access to these systems is restricted due to the requirement to periodically refill them with liquid cryogens. This is both logistically demanding and expensive. A new system combining NMR spectrometry and Pulse Tube Refrigeration (PTR) has been developed and successfully tested. This approach eliminates the dependence on liquid cryogens, reduces spectrometer downtime, and also significantly reduces the size of the system. In the near future this new type of analytical tool may become ubiquitous in biomedical and chemical laboratories.

Metabonomics and drug development.

PubMed

Ramana, Pranov; Adams, Erwin; Augustijns, Patrick; Van Schepdael, Ann

2015-01-01

Metabolites as an end product of metabolism possess a wealth of information about altered metabolic control and homeostasis that is dependent on numerous variables including age, sex, and environment. Studying significant changes in the metabolite patterns has been recognized as a tool to understand crucial aspects in drug development like drug efficacy and toxicity. The inclusion of metabonomics into the OMICS study platform brings us closer to define the phenotype and allows us to look at alternatives to improve the diagnosis of diseases. Advancements in the analytical strategies and statistical tools used to study metabonomics allow us to prevent drug failures at early stages of drug development and reduce financial losses during expensive phase II and III clinical trials. This chapter introduces metabonomics along with the instruments used in the study; in addition relevant examples of the usage of metabonomics in the drug development process are discussed along with an emphasis on future directions and the challenges it faces.

A reversible fluorescent probe for real-time live-cell imaging and quantification of endogenous hydropolysulfides.

PubMed

Umezawa, Keitaro; Kamiya, Mako; Urano, Yasuteru

2018-05-23

The chemical biology of reactive sulfur species, including hydropolysulfides, has been a subject undergoing intense study in recent years, but further understanding of their 'intact' function in living cells has been limited due to a lack of appropriate analytical tools. In order to overcome this limitation, we developed a new type of fluorescent probe which reversibly and selectively reacts to hydropolysulfides. The probe enables live-cell visualization and quantification of endogenous hydropolysulfides without interference from intrinsic thiol species such as glutathione. Additionally, real-time reversible monitoring of oxidative-stress-induced fluctuation of intrinsic hydropolysulfides has been achieved with a temporal resolution in the order of seconds, a result which has not yet been realized using conventional methods. These results reveal the probe's versatility as a new fluorescence imaging tool to understand the function of intracellular hydropolysulfides. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Preliminary design methods for fiber reinforced composite structures employing a personal computer

NASA Technical Reports Server (NTRS)

Eastlake, C. N.

1986-01-01

The objective of this project was to develop a user-friendly interactive computer program to be used as an analytical tool by structural designers. Its intent was to do preliminary, approximate stress analysis to help select or verify sizing choices for composite structural members. The approach to the project was to provide a subroutine which uses classical lamination theory to predict an effective elastic modulus for a laminate of arbitrary material and ply orientation. This effective elastic modulus can then be used in a family of other subroutines which employ the familiar basic structural analysis methods for isotropic materials. This method is simple and convenient to use but only approximate, as is appropriate for a preliminary design tool which will be subsequently verified by more sophisticated analysis. Additional subroutines have been provided to calculate laminate coefficient of thermal expansion and to calculate ply-by-ply strains within a laminate.

Program for establishing long-time flight service performance of composite materials in the center wing structure of C-130 aircraft. Phase 4: Ground/flight acceptance tests

NASA Technical Reports Server (NTRS)

Harvill, W. E.; Kizer, J. A.

1976-01-01

The advantageous structural uses of advanced filamentary composites are demonstrated by design, fabrication, and test of three boron-epoxy reinforced C-130 center wing boxes. The advanced development work necessary to support detailed design of a composite reinforced C-130 center wing box was conducted. Activities included the development of a basis for structural design, selection and verification of materials and processes, manufacturing and tooling development, and fabrication and test of full-scale portions of the center wing box. Detailed design drawings, and necessary analytical structural substantiation including static strength, fatigue endurance, flutter, and weight analyses are considered. Some additional component testing was conducted to verify the design for panel buckling, and to evaluate specific local design areas. Development of the cool tool restraint concept was completed, and bonding capabilities were evaluated using full-length skin panel and stringer specimens.

The Geochemical Databases GEOROC and GeoReM - What's New?

NASA Astrophysics Data System (ADS)

Sarbas, B.; Jochum, K. P.; Nohl, U.; Weis, U.

2017-12-01

The geochemical databases GEOROC (http: georoc.mpch-mainz.gwdg.de) and GeoReM (http: georem.mpch-mainz.gwdg.de) are maintained by the Max Planck Institute for Chemistry in Mainz, Germany. Both online databases became crucial tools for geoscientists from different research areas. They are regularly upgraded by new tools and new data from recent publications obtained from a wide range of international journals. GEOROC is a collection of published analyses of volcanic rocks and mantle xenoliths. Since recently, data for plutonic rocks are added. The analyses include major and trace element concentrations, radiogenic and non-radiogenic isotope ratios as well as analytical ages for whole rocks, glasses, minerals and inclusions. Samples come from eleven geological settings and span the whole geological age scale from Archean to Recent. Metadata include, among others, geographic location, rock class and rock type, geological age, degree of alteration, analytical method, laboratory, and reference. The GEOROC web page allows selection of samples by geological setting, geography, chemical criteria, rock or sample name, and bibliographic criteria. In addition, it provides a large number of precompiled files for individual locations, minerals and rock classes. GeoReM is a database collecting information about reference materials of geological and environmental interest, such as rock powders, synthetic and natural glasses as well as mineral, isotopic, biological, river water and seawater reference materials. It contains published data and compilation values (major and trace element concentrations and mass fractions, radiogenic and stable isotope ratios). Metadata comprise, among others, uncertainty, analytical method and laboratory. Reference materials are important for calibration, method validation, quality control and to establish metrological traceability. GeoReM offers six different search strategies: samples or materials (published values), samples (GeoReM preferred values), chemical criteria, chemical criteria based on bibliography, bibliography, as well as methods and institutions.

Modification and validation of an analytical source model for external beam radiotherapy Monte Carlo dose calculations.

PubMed

Davidson, Scott E; Cui, Jing; Kry, Stephen; Deasy, Joseph O; Ibbott, Geoffrey S; Vicic, Milos; White, R Allen; Followill, David S

2016-08-01

A dose calculation tool, which combines the accuracy of the dose planning method (DPM) Monte Carlo code and the versatility of a practical analytical multisource model, which was previously reported has been improved and validated for the Varian 6 and 10 MV linear accelerators (linacs). The calculation tool can be used to calculate doses in advanced clinical application studies. One shortcoming of current clinical trials that report dose from patient plans is the lack of a standardized dose calculation methodology. Because commercial treatment planning systems (TPSs) have their own dose calculation algorithms and the clinical trial participant who uses these systems is responsible for commissioning the beam model, variation exists in the reported calculated dose distributions. Today's modern linac is manufactured to tight specifications so that variability within a linac model is quite low. The expectation is that a single dose calculation tool for a specific linac model can be used to accurately recalculate dose from patient plans that have been submitted to the clinical trial community from any institution. The calculation tool would provide for a more meaningful outcome analysis. The analytical source model was described by a primary point source, a secondary extra-focal source, and a contaminant electron source. Off-axis energy softening and fluence effects were also included. The additions of hyperbolic functions have been incorporated into the model to correct for the changes in output and in electron contamination with field size. A multileaf collimator (MLC) model is included to facilitate phantom and patient dose calculations. An offset to the MLC leaf positions was used to correct for the rudimentary assumed primary point source. Dose calculations of the depth dose and profiles for field sizes 4 × 4 to 40 × 40 cm agree with measurement within 2% of the maximum dose or 2 mm distance to agreement (DTA) for 95% of the data points tested. The model was capable of predicting the depth of the maximum dose within 1 mm. Anthropomorphic phantom benchmark testing of modulated and patterned MLCs treatment plans showed agreement to measurement within 3% in target regions using thermoluminescent dosimeters (TLD). Using radiochromic film normalized to TLD, a gamma criteria of 3% of maximum dose and 2 mm DTA was applied with a pass rate of least 85% in the high dose, high gradient, and low dose regions. Finally, recalculations of patient plans using DPM showed good agreement relative to a commercial TPS when comparing dose volume histograms and 2D dose distributions. A unique analytical source model coupled to the dose planning method Monte Carlo dose calculation code has been modified and validated using basic beam data and anthropomorphic phantom measurement. While this tool can be applied in general use for a particular linac model, specifically it was developed to provide a singular methodology to independently assess treatment plan dose distributions from those clinical institutions participating in National Cancer Institute trials.

Next-Generation Tools For Next-Generation Surveys

NASA Astrophysics Data System (ADS)

Murray, S. G.

2017-04-01

The next generation of large-scale galaxy surveys, across the electromagnetic spectrum, loom on the horizon as explosively game-changing datasets, in terms of our understanding of cosmology and structure formation. We are on the brink of a torrent of data that is set to both confirm and constrain current theories to an unprecedented level, and potentially overturn many of our conceptions. One of the great challenges of this forthcoming deluge is to extract maximal scientific content from the vast array of raw data. This challenge requires not only well-understood and robust physical models, but a commensurate network of software implementations with which to efficiently apply them. The halo model, a semi-analytic treatment of cosmological spatial statistics down to nonlinear scales, provides an excellent mathematical framework for exploring the nature of dark matter. This thesis presents a next-generation toolkit based on the halo model formalism, intended to fulfil the requirements of next-generation surveys. Our toolkit comprises three tools: (i) hmf, a comprehensive and flexible calculator for halo mass functions (HMFs) within extended Press-Schechter theory, (ii) the MRP distribution for extremely efficient analytic characterisation of HMFs, and (iii) halomod, an extension of hmf which provides support for the full range of halo model components. In addition to the development and technical presentation of these tools, we apply each to the task of physical modelling. With hmf, we determine the precision of our knowledge of the HMF, due to uncertainty in our knowledge of the cosmological parameters, over the past decade of cosmic microwave background (CMB) experiments. We place rule-of-thumb uncertainties on the predicted HMF for the Planck cosmology, and find that current limits on the precision are driven by modeling uncertainties rather than those from cosmological parameters. With the MRP, we create and test a method for robustly fitting the HMF to observed masses with arbitrary measurement uncertainties on a per-object basis. We find that our method reduces estimation uncertainty on parameters by over 50%, and correctly accounts for Eddington bias even in extremely poorly measured data. Additionally, we use the analytical properties of the MRP to obtain asymptotically correct forms for the stellar-mass halo-mass relation, in the subhalo abundance matching scheme. Finally, with halomod, we explore the viability of the halo model as a test of warm dark matter (WDM) via galaxy clustering. Examining three distinct scale regimes, we find that the clustering of galaxies at the smallest resolvable scales may provide a valuable independent probe in the coming era.

Bio-TDS: bioscience query tool discovery system.

PubMed

Gnimpieba, Etienne Z; VanDiermen, Menno S; Gustafson, Shayla M; Conn, Bill; Lushbough, Carol M

2017-01-04

Bioinformatics and computational biology play a critical role in bioscience and biomedical research. As researchers design their experimental projects, one major challenge is to find the most relevant bioinformatics toolkits that will lead to new knowledge discovery from their data. The Bio-TDS (Bioscience Query Tool Discovery Systems, http://biotds.org/) has been developed to assist researchers in retrieving the most applicable analytic tools by allowing them to formulate their questions as free text. The Bio-TDS is a flexible retrieval system that affords users from multiple bioscience domains (e.g. genomic, proteomic, bio-imaging) the ability to query over 12 000 analytic tool descriptions integrated from well-established, community repositories. One of the primary components of the Bio-TDS is the ontology and natural language processing workflow for annotation, curation, query processing, and evaluation. The Bio-TDS's scientific impact was evaluated using sample questions posed by researchers retrieved from Biostars, a site focusing on BIOLOGICAL DATA ANALYSIS: The Bio-TDS was compared to five similar bioscience analytic tool retrieval systems with the Bio-TDS outperforming the others in terms of relevance and completeness. The Bio-TDS offers researchers the capacity to associate their bioscience question with the most relevant computational toolsets required for the data analysis in their knowledge discovery process. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Manipulability, force, and compliance analysis for planar continuum manipulators

NASA Technical Reports Server (NTRS)

Gravagne, Ian A.; Walker, Ian D.

2002-01-01

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Hearn, Tristan; Hendricks, Eric; Chin, Jeffrey; Gray, Justin; Moore, Kenneth T.

2016-01-01

A new engine cycle analysis tool, called Pycycle, was recently built using the OpenMDAO framework. This tool uses equilibrium chemistry based thermodynamics, and provides analytic derivatives. This allows for stable and efficient use of gradient-based optimization and sensitivity analysis methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a multi-point turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Manipulability, force, and compliance analysis for planar continuum manipulators.

PubMed

Gravagne, Ian A; Walker, Ian D

2002-06-01

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

Evaluation of a recent product to remove lipids and other matrix co-extractives in the analysis of pesticide residues and environmental contaminants in foods.

PubMed

Han, Lijun; Matarrita, Jessie; Sapozhnikova, Yelena; Lehotay, Steven J

2016-06-03

This study demonstrates the application of a novel lipid removal product to the residue analysis of 65 pesticides and 52 environmental contaminants in kale, pork, salmon, and avocado by fast, low pressure gas chromatography - tandem mass spectrometry (LPGC-MS/MS). Sample preparation involves QuEChERS extraction followed by use of EMR-Lipid ("enhanced matrix removal of lipids") and an additional salting out step for cleanup. The optimal amount of EMR-Lipid was determined to be 500mg for 2.5mL extracts for most of the analytes. The co-extractive removal efficiency by the EMR-Lipid cleanup step was 83-98% for fatty samples and 79% for kale, including 76% removal of chlorophyll. Matrix effects were typically less than ±20%, in part because analyte protectants were used in the LPGC-MS/MS analysis. The recoveries of polycyclic aromatic hydrocarbons and diverse pesticides were mostly 70-120%, whereas recoveries of nonpolar polybrominated diphenyl ethers and polychlorinated biphenyls were mostly lower than 70% through the cleanup procedure. With the use of internal standards, method validation results showed that 76-85 of the 117 analytes achieved satisfactory results (recoveries of 70-120% and RSD≤20%) in pork, avocado, and kale, while 53 analytes had satisfactory results in salmon. Detection limits were 5-10ng/g for all but a few analytes. EMR-Lipid is a new sample preparation tool that serves as another useful option for cleanup in multiresidue analysis, particularly of fatty foods. Published by Elsevier B.V.

Nondestructive quantification of analyte diffusion in cornea and sclera using optical coherence tomography.

PubMed

Ghosn, Mohamad G; Tuchin, Valery V; Larin, Kirill V

2007-06-01

Noninvasive functional imaging, monitoring, and quantification of analytes transport in epithelial ocular tissues are extremely important for therapy and diagnostics of many eye diseases. In this study the authors investigated the capability of optical coherence tomography (OCT) for noninvasive monitoring and quantification of diffusion of different analytes in sclera and cornea of rabbit eyes. A portable time-domain OCT system with wavelength of 1310 +/- 15 nm, output power of 3.5 mW, and resolution of 25 mum was used in this study. Diffusion of different analytes was monitored and quantified in rabbit cornea and sclera of whole eyeballs. Diffusion of water, metronidazole (0.5%), dexamethasone (0.2%), ciprofloxacin (0.3%), mannitol (20%), and glucose solution (20%) were examined, and their permeability coefficients were calculated by using OCT signal slope and depth-resolved amplitude methods. Permeability coefficients were calculated as a function of time and tissue depth. For instance, mannitol was found to have a permeability coefficient of (8.99 +/- 1.43) x 10(-6) cm/s in cornea and (6.18 +/- 1.08) x 10(-6) cm/s in sclera. The permeability coefficient of drugs with small concentrations (where water was the major solvent) was found to be in the range of that of water in the same tissue type, whereas permeability coefficients of higher concentrated solutions varied significantly. Results suggest that the OCT technique might be a powerful tool for noninvasive diffusion studies of different analytes in ocular tissues. However, additional methods of OCT signal acquisition and processing are required to study the diffusion of agents of small concentrations.

Can cloud point-based enrichment, preservation, and detection methods help to bridge gaps in aquatic nanometrology?

PubMed

Duester, Lars; Fabricius, Anne-Lena; Jakobtorweihen, Sven; Philippe, Allan; Weigl, Florian; Wimmer, Andreas; Schuster, Michael; Nazar, Muhammad Faizan

2016-11-01

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

Exploring the Potential of Predictive Analytics and Big Data in Emergency Care.

PubMed

Janke, Alexander T; Overbeek, Daniel L; Kocher, Keith E; Levy, Phillip D

2016-02-01

Clinical research often focuses on resource-intensive causal inference, whereas the potential of predictive analytics with constantly increasing big data sources remains largely unexplored. Basic prediction, divorced from causal inference, is much easier with big data. Emergency care may benefit from this simpler application of big data. Historically, predictive analytics have played an important role in emergency care as simple heuristics for risk stratification. These tools generally follow a standard approach: parsimonious criteria, easy computability, and independent validation with distinct populations. Simplicity in a prediction tool is valuable, but technological advances make it no longer a necessity. Emergency care could benefit from clinical predictions built using data science tools with abundant potential input variables available in electronic medical records. Patients' risks could be stratified more precisely with large pools of data and lower resource requirements for comparing each clinical encounter to those that came before it, benefiting clinical decisionmaking and health systems operations. The largest value of predictive analytics comes early in the clinical encounter, in which diagnostic and prognostic uncertainty are high and resource-committing decisions need to be made. We propose an agenda for widening the application of predictive analytics in emergency care. Throughout, we express cautious optimism because there are myriad challenges related to database infrastructure, practitioner uptake, and patient acceptance. The quality of routinely compiled clinical data will remain an important limitation. Complementing big data sources with prospective data may be necessary if predictive analytics are to achieve their full potential to improve care quality in the emergency department. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Data and Tools | Concentrating Solar Power | NREL

Science.gov Websites

download. Solar Power tower Integrated Layout and Optimization Tool (SolarPILOT(tm)) The SolarPILOT is code rapid layout and optimization capability of the analytical DELSOL3 program with the accuracy and

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

RapidIO as a multi-purpose interconnect

NASA Astrophysics Data System (ADS)

Baymani, Simaolhoda; Alexopoulos, Konstantinos; Valat, Sébastien

2017-10-01

RapidIO (http://rapidio.org/) technology is a packet-switched high-performance fabric, which has been under active development since 1997. Originally meant to be a front side bus, it developed into a system level interconnect which is today used in all 4G/LTE base stations world wide. RapidIO is often used in embedded systems that require high reliability, low latency and scalability in a heterogeneous environment - features that are highly interesting for several use cases, such as data analytics and data acquisition (DAQ) networks. We will present the results of evaluating RapidIO in a data analytics environment, from setup to benchmark. Specifically, we will share the experience of running ROOT and Hadoop on top of RapidIO. To demonstrate the multi-purpose characteristics of RapidIO, we will also present the results of investigating RapidIO as a technology for high-speed DAQ networks using a generic multi-protocol event-building emulation tool. In addition we will present lessons learned from implementing native ports of CERN applications to RapidIO.

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies.

PubMed

Haller, Toomas; Leitsalu, Liis; Fischer, Krista; Nuotio, Marja-Liisa; Esko, Tõnu; Boomsma, Dorothea Irene; Kyvik, Kirsten Ohm; Spector, Tim D; Perola, Markus; Metspalu, Andres

2017-01-01

Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

Convergence in full motion video processing, exploitation, and dissemination and activity based intelligence

NASA Astrophysics Data System (ADS)

Phipps, Marja; Lewis, Gina

2012-06-01

Over the last decade, intelligence capabilities within the Department of Defense/Intelligence Community (DoD/IC) have evolved from ad hoc, single source, just-in-time, analog processing; to multi source, digitally integrated, real-time analytics; to multi-INT, predictive Processing, Exploitation and Dissemination (PED). Full Motion Video (FMV) technology and motion imagery tradecraft advancements have greatly contributed to Intelligence, Surveillance and Reconnaissance (ISR) capabilities during this timeframe. Imagery analysts have exploited events, missions and high value targets, generating and disseminating critical intelligence reports within seconds of occurrence across operationally significant PED cells. Now, we go beyond FMV, enabling All-Source Analysts to effectively deliver ISR information in a multi-INT sensor rich environment. In this paper, we explore the operational benefits and technical challenges of an Activity Based Intelligence (ABI) approach to FMV PED. Existing and emerging ABI features within FMV PED frameworks are discussed, to include refined motion imagery tools, additional intelligence sources, activity relevant content management techniques and automated analytics.

Integrity, standards, and QC-related issues with big data in pre-clinical drug discovery.

PubMed

Brothers, John F; Ung, Matthew; Escalante-Chong, Renan; Ross, Jermaine; Zhang, Jenny; Cha, Yoonjeong; Lysaght, Andrew; Funt, Jason; Kusko, Rebecca

2018-06-01

The tremendous expansion of data analytics and public and private big datasets presents an important opportunity for pre-clinical drug discovery and development. In the field of life sciences, the growth of genetic, genomic, transcriptomic and proteomic data is partly driven by a rapid decline in experimental costs as biotechnology improves throughput, scalability, and speed. Yet far too many researchers tend to underestimate the challenges and consequences involving data integrity and quality standards. Given the effect of data integrity on scientific interpretation, these issues have significant implications during preclinical drug development. We describe standardized approaches for maximizing the utility of publicly available or privately generated biological data and address some of the common pitfalls. We also discuss the increasing interest to integrate and interpret cross-platform data. Principles outlined here should serve as a useful broad guide for existing analytical practices and pipelines and as a tool for developing additional insights into therapeutics using big data. Copyright © 2018 Elsevier Inc. All rights reserved.

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Biosensors and their applications in detection of organophosphorus pesticides in the environment.

PubMed

Hassani, Shokoufeh; Momtaz, Saeideh; Vakhshiteh, Faezeh; Maghsoudi, Armin Salek; Ganjali, Mohammad Reza; Norouzi, Parviz; Abdollahi, Mohammad

2017-01-01

This review discusses the past and recent advancements of biosensors focusing on detection of organophosphorus pesticides (OPs) due to their exceptional use during the last decades. Apart from agricultural benefits, OPs also impose adverse toxicological effects on animal and human population. Conventional approaches such as chromatographic techniques used for pesticide detection are associated with several limitations. A biosensor technology is unique due to the detection sensitivity, selectivity, remarkable performance capabilities, simplicity and on-site operation, fabrication and incorporation with nanomaterials. This study also provided specifications of the most OPs biosensors reported until today based on their transducer system. In addition, we highlighted the application of advanced complementary materials and analysis techniques in OPs detection systems. The availability of these new materials associated with new sensing techniques has led to introduction of easy-to-use analytical tools of high sensitivity and specificity in the design and construction of OPs biosensors. In this review, we elaborated the achievements in sensing systems concerning innovative nanomaterials and analytical techniques with emphasis on OPs.

Training the next generation analyst using red cell analytics

NASA Astrophysics Data System (ADS)

Graham, Meghan N.; Graham, Jacob L.

2016-05-01

We have seen significant change in the study and practice of human reasoning in recent years from both a theoretical and methodological perspective. Ubiquitous communication coupled with advances in computing and a plethora of analytic support tools have created a push for instantaneous reporting and analysis. This notion is particularly prevalent in law enforcement, emergency services and the intelligence community (IC), where commanders (and their civilian leadership) expect not only a birds' eye view of operations as they occur, but a play-by-play analysis of operational effectiveness. This paper explores the use of Red Cell Analytics (RCA) as pedagogy to train the next-gen analyst. A group of Penn State students in the College of Information Sciences and Technology at the University Park campus of The Pennsylvania State University have been practicing Red Team Analysis since 2008. RCA draws heavily from the military application of the same concept, except student RCA problems are typically on non-military in nature. RCA students utilize a suite of analytic tools and methods to explore and develop red-cell tactics, techniques and procedures (TTPs), and apply their tradecraft across a broad threat spectrum, from student-life issues to threats to national security. The strength of RCA is not always realized by the solution but by the exploration of the analytic pathway. This paper describes the concept and use of red cell analytics to teach and promote the use of structured analytic techniques, analytic writing and critical thinking in the area of security and risk and intelligence training.

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

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

Cook, Kristin A.; Cramer, Nicholas O.; Israel, David

2015-12-07

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying modelsmore » of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.« less

ATTIRE (analytical tools for thermal infrared engineering): A sensor simulation and modeling package

NASA Astrophysics Data System (ADS)

Jaggi, S.

1993-02-01

The Advanced Sensor Development Laboratory (ASDL) at the Stennis Space Center develops, maintains and calibrates remote sensing instruments for the National Aeronautics & Space Administration (NASA). To perform system design trade-offs, analysis, and establish system parameters, ASDL has developed a software package for analytical simulation of sensor systems. This package called 'Analytical Tools for Thermal InfraRed Engineering' - ATTIRE, simulates the various components of a sensor system. The software allows each subsystem of the sensor to be analyzed independently for its performance. These performance parameters are then integrated to obtain system level information such as Signal-to-Noise Ratio (SNR), Noise Equivalent Radiance (NER), Noise Equivalent Temperature Difference (NETD) etc. This paper describes the uses of the package and the physics that were used to derive the performance parameters.

Earth Science Data Analytics: Bridging Tools and Techniques with the Co-Analysis of Large, Heterogeneous Datasets

NASA Technical Reports Server (NTRS)

Kempler, Steve; Mathews, Tiffany

2016-01-01

The continuum of ever-evolving data management systems affords great opportunities to the enhancement of knowledge and facilitation of science research. To take advantage of these opportunities, it is essential to understand and develop methods that enable data relationships to be examined and the information to be manipulated. This presentation describes the efforts of the Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster to understand, define, and facilitate the implementation of ESDA to advance science research. As a result of the void of Earth science data analytics publication material, the cluster has defined ESDA along with 10 goals to set the framework for a common understanding of tools and techniques that are available and still needed to support ESDA.

Advancements in nano-enabled therapeutics for neuroHIV management.

PubMed

Kaushik, Ajeet; Jayant, Rahul Dev; Nair, Madhavan

This viewpoint is a global call to promote fundamental and applied research aiming toward designing smart nanocarriers of desired properties, novel noninvasive strategies to open the blood-brain barrier (BBB), delivery/release of single/multiple therapeutic agents across the BBB to eradicate neurohuman immunodeficiency virus (HIV), strategies for on-demand site-specific release of antiretroviral therapy, developing novel nanoformulations capable to recognize and eradicate latently infected HIV reservoirs, and developing novel smart analytical diagnostic tools to detect and monitor HIV infection. Thus, investigation of novel nanoformulations, methodologies for site-specific delivery/release, analytical methods, and diagnostic tools would be of high significance to eradicate and monitor neuroacquired immunodeficiency syndrome. Overall, these developments will certainly help to develop personalized nanomedicines to cure HIV and to develop smart HIV-monitoring analytical systems for disease management.

Physics of cosmological cascades and observable properties

NASA Astrophysics Data System (ADS)

Fitoussi, T.; Belmont, R.; Malzac, J.; Marcowith, A.; Cohen-Tanugi, J.; Jean, P.

2017-04-01

TeV photons from extragalactic sources are absorbed in the intergalactic medium and initiate electromagnetic cascades. These cascades offer a unique tool to probe the properties of the universe at cosmological scales. We present a new Monte Carlo code dedicated to the physics of such cascades. This code has been tested against both published results and analytical approximations, and is made publicly available. Using this numerical tool, we investigate the main cascade properties (spectrum, halo extension and time delays), and study in detail their dependence on the physical parameters (extragalactic magnetic field, extragalactic background light, source redshift, source spectrum and beaming emission). The limitations of analytical solutions are emphasized. In particular, analytical approximations account only for the first generation of photons and higher branches of the cascade tree are neglected.

NeedATool: A Needlet Analysis Tool for Cosmological Data Processing

NASA Astrophysics Data System (ADS)

Pietrobon, Davide; Balbi, Amedeo; Cabella, Paolo; Gorski, Krzysztof M.

2010-11-01

We introduce NeedATool (Needlet Analysis Tool), a software for data analysis based on needlets, a wavelet rendition which is powerful for the analysis of fields defined on a sphere. Needlets have been applied successfully to the treatment of astrophysical and cosmological observations, and in particular to the analysis of cosmic microwave background (CMB) data. Usually, such analyses are performed in real space as well as in its dual domain, the harmonic one. Both spaces have advantages and disadvantages: for example, in pixel space it is easier to deal with partial sky coverage and experimental noise; in the harmonic domain, beam treatment and comparison with theoretical predictions are more effective. During the last decade, however, wavelets have emerged as a useful tool for CMB data analysis, since they allow us to combine most of the advantages of the two spaces, one of the main reasons being their sharp localization. In this paper, we outline the analytical properties of needlets and discuss the main features of the numerical code, which should be a valuable addition to the CMB analyst's toolbox.

KNIME for reproducible cross-domain analysis of life science data.

PubMed

Fillbrunn, Alexander; Dietz, Christian; Pfeuffer, Julianus; Rahn, René; Landrum, Gregory A; Berthold, Michael R

2017-11-10

Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing. Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis. Such scripts are not only prone to be platform dependent, they also tend to grow as the experiment progresses and are seldomly well documented, a fact that hinders the reproducibility of the experiment. Workflow systems such as KNIME Analytics Platform aim to solve these problems by providing a platform for connecting tools graphically and guaranteeing the same results on different operating systems. As an open source software, KNIME allows scientists and programmers to provide their own extensions to the scientific community. In this review paper we present selected extensions from the life sciences that simplify data exploration, analysis, and visualization and are interoperable due to KNIME's unified data model. Additionally, we name other workflow systems that are commonly used in the life sciences and highlight their similarities and differences to KNIME. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Numerical simulation of tunneling through arbitrary potential barriers applied on MIM and MIIM rectenna diodes

NASA Astrophysics Data System (ADS)

Abdolkader, Tarek M.; Shaker, Ahmed; Alahmadi, A. N. M.

2018-07-01

With the continuous miniaturization of electronic devices, quantum-mechanical effects such as tunneling become more effective in many device applications. In this paper, a numerical simulation tool is developed under a MATLAB environment to calculate the tunneling probability and current through an arbitrary potential barrier comparing three different numerical techniques: the finite difference method, transfer matrix method, and transmission line method. For benchmarking, the tool is applied to many case studies such as the rectangular single barrier, rectangular double barrier, and continuous bell-shaped potential barrier, each compared to analytical solutions and giving the dependence of the error on the number of mesh points. In addition, a thorough study of the J ‑ V characteristics of MIM and MIIM diodes, used as rectifiers for rectenna solar cells, is presented and simulations are compared to experimental results showing satisfactory agreement. On the undergraduate level, the tool provides a deeper insight for students to compare numerical techniques used to solve various tunneling problems and helps students to choose a suitable technique for a certain application.

PAVA: Physiological and Anatomical Visual Analytics for Mapping of Tissue-Specific Concentration and Time-Course Data

EPA Science Inventory

We describe the development and implementation of a Physiological and Anatomical Visual Analytics tool (PAVA), a web browser-based application, used to visualize experimental/simulated chemical time-course data (dosimetry), epidemiological data and Physiologically-Annotated Data ...

Analysis of the Image of Scientists Portrayed in the Lebanese National Science Textbooks

NASA Astrophysics Data System (ADS)

Yacoubian, Hagop A.; Al-Khatib, Layan; Mardirossian, Taline

2017-07-01

This article presents an analysis of how scientists are portrayed in the Lebanese national science textbooks. The purpose of this study was twofold. First, to develop a comprehensive analytical framework that can serve as a tool to analyze the image of scientists portrayed in educational resources. Second, to analyze the image of scientists portrayed in the Lebanese national science textbooks that are used in Basic Education. An analytical framework, based on an extensive review of the relevant literature, was constructed that served as a tool for analyzing the textbooks. Based on evidence-based stereotypes, the framework focused on the individual and work-related characteristics of scientists. Fifteen science textbooks were analyzed using both quantitative and qualitative measures. Our analysis of the textbooks showed the presence of a number of stereotypical images. The scientists are predominantly white males of European descent. Non-Western scientists, including Lebanese and/or Arab scientists are mostly absent in the textbooks. In addition, the scientists are portrayed as rational individuals who work alone, who conduct experiments in their labs by following the scientific method, and by operating within Eurocentric paradigms. External factors do not influence their work. They are engaged in an enterprise which is objective, which aims for discovering the truth out there, and which involves dealing with direct evidence. Implications for science education are discussed.

Analytical Model-Based Design Optimization of a Transverse Flux Machine

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

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

Reducing the barriers against analytical epidemiological studies in investigations of local foodborne disease outbreaks in Germany - a starter kit for local health authorities.

PubMed

Werber, D; Bernard, H

2014-02-27

Thousands of infectious food-borne disease outbreaks (FBDO) are reported annually to the European Food Safety Authority within the framework of the zoonoses Directive (2003/99/EC). Most recognised FBDO occur locally following point source exposure, but only few are investigated using analytical epidemiological studies. In Germany, and probably also in other countries of the European Union, this seems to be particularly true for those investigated by local health authorities. Analytical studies, usually cohort studies or case–control studies, are a powerful tool to identify suspect food vehicles. Therefore, from a public health and food safety perspective, their more frequent usage is highly desirable. We have developed a small toolbox consisting of a strategic concept and a simple software tool for data entry and analysis, with the objective to increase the use of analytical studies in the investigation of local point source FBDO in Germany.

Electrochemical Enzyme Biosensors Revisited: Old Solutions for New Problems.

PubMed

Monteiro, Tiago; Almeida, Maria Gabriela

2018-05-14

Worldwide legislation is driving the development of novel and highly efficient analytical tools for assessing the composition of every material that interacts with Consumers or Nature. The biosensor technology is one of the most active R&D domains of Analytical Sciences focused on the challenge of taking analytical chemistry to the field. Electrochemical biosensors based on redox enzymes, in particular, are highly appealing due to their usual quick response, high selectivity and sensitivity, low cost and portable dimensions. This review paper aims to provide an overview of the most important advances made in the field since the proposal of the first biosensor, the well-known hand-held glucose meter. The first section addresses the current needs and challenges for novel analytical tools, followed by a brief description of the different components and configurations of biosensing devices, and the fundamentals of enzyme kinetics and amperometry. The following sections emphasize on enzyme-based amperometric biosensors and the different stages of their development.

Multivariable Hermite polynomials and phase-space dynamics

NASA Technical Reports Server (NTRS)

Dattoli, G.; Torre, Amalia; Lorenzutta, S.; Maino, G.; Chiccoli, C.

1994-01-01

The phase-space approach to classical and quantum systems demands for advanced analytical tools. Such an approach characterizes the evolution of a physical system through a set of variables, reducing to the canonically conjugate variables in the classical limit. It often happens that phase-space distributions can be written in terms of quadratic forms involving the above quoted variables. A significant analytical tool to treat these problems may come from the generalized many-variables Hermite polynomials, defined on quadratic forms in R(exp n). They form an orthonormal system in many dimensions and seem the natural tool to treat the harmonic oscillator dynamics in phase-space. In this contribution we discuss the properties of these polynomials and present some applications to physical problems.

CONSTRAINTS FROM ASYMMETRIC HEATING: INVESTIGATING THE EPSILON AURIGAE DISK

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

Pearson, Richard L. III; Stencel, Robert E., E-mail: richard.pearson@du.edu, E-mail: robert.stencel@du.edu

2015-01-01

Epsilon Aurigae is a long-period eclipsing binary that likely contains an F0Ia star and a circumstellar disk enshrouding a hidden companion, assumed to be a main-sequence B star. High uncertainty in its parallax has kept the evolutionary status of the system in question and, hence, the true nature of each component. This unknown, as well as the absence of solid state spectral features in the infrared, requires an investigation of a wide parameter space by means of both analytic and Monte Carlo radiative transfer (MCRT) methods. The first MCRT models of epsilon Aurigae that include all three system components aremore » presented here. We seek additional system parameter constraints by melding analytic approximations with MCRT outputs (e.g., dust temperatures) on a first-order level. The MCRT models investigate the effects of various parameters on the disk-edge temperatures; these include two distances, three particle size distributions, three compositions, and two disk masses, resulting in 36 independent models. Specifically, the MCRT temperatures permit analytic calculations of effective heating and cooling curves along the disk edge. These are used to calculate representative observed fluxes and corresponding temperatures. This novel application of thermal properties provides the basis for utilization of other binary systems containing disks. We find degeneracies in the model fits for the various parameter sets. However, the results show a preference for a carbon disk with particle size distributions ≥10 μm. Additionally, a linear correlation between the MCRT noon and basal temperatures serves as a tool for effectively eliminating portions of the parameter space.« less

The H4IIE cell bioassay as an indicator of dioxin-like chemicals in wildlife and the environment

USGS Publications Warehouse

White, J.J.; Schmitt, C.J.; Tillitt, D. E.

2004-01-01

The H4IIE cell bioassay has proven utility as a screening tool for planar halogenated hydrocarbons (PHHs) and structurally similar chemicals accumulated in organisms from the wild. This bioassay has additional applications in hazard assessment of PHH exposed populations. In this review, the toxicological principles, current protocols, performance criteria, and field applications for the assay are described. The H4IIE cell bioassay has several advantages over the analytical measurement of PHHs in environmental samples, but conclusions from studies can be strengthened when both bioassay and analytical chemistry data are presented together. Often, the bioassay results concur with biological effects in organisms and support direct measures of PHHs. For biomonitoring purposes and prioritization of PHH-contaminated environments, the H4IIE bioassay may be faster and less expensive than analytical measurements. The H4IIE cell bioassay can be used in combination with other biomarkers such as in vivo measurements of CYP1A1 induction to help pinpoint the sources and identities of dioxin-like chemicals. The number of studies that measure H4IIE-derived TCDD-EQs continues to increase, resulting in subtle improvements over time. Further experiments are required to determine if TCDD-EQs derived from mammalian cells are adequate predictors of toxicity to non-mammalian species. The H4IIE cell bioassay has been used in over 300 published studies, and its combination of speed, simplicity, and ability to integrate the effects of complex containment mixtures makes it a valuable addition to hazard assessment and biomonitoring studies.

Capillary electrophoresis for the analysis of contaminants in emerging food safety issues and food traceability.

PubMed

Vallejo-Cordoba, Belinda; González-Córdova, Aarón F

2010-07-01

This review presents an overview of the applicability of CE in the analysis of chemical and biological contaminants involved in emerging food safety issues. Additionally, CE-based genetic analyzers' usefulness as a unique tool in food traceability verification systems was presented. First, analytical approaches for the determination of melamine and specific food allergens in different foods were discussed. Second, natural toxin analysis by CE was updated from the last review reported in 2008. Finally, the analysis of prion proteins associated with the "mad cow" crises and the application of CE-based genetic analyzers for meat traceability were summarized.

Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory

PubMed Central

Kumar, B. Vinodh; Mohan, Thuthi

2018-01-01

OBJECTIVE: Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. MATERIALS AND METHODS: This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. RESULTS: For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. CONCLUSION: This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes. PMID:29692587

Tool to Prioritize Energy Efficiency Investments

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

Farese, P.; Gelman, R.; Hendron, R.

2012-08-01

To provide analytic support of the U.S. Department of Energy's Office of the Building Technology Program (BTP), NREL developed a Microsoft Excel-based tool to provide an open and objective comparison of the hundreds of investment opportunities available to BTP. This tool uses established methodologies to evaluate the energy savings and cost of those savings.

Tools for Educational Data Mining: A Review

ERIC Educational Resources Information Center

Slater, Stefan; Joksimovic, Srecko; Kovanovic, Vitomir; Baker, Ryan S.; Gasevic, Dragan

2017-01-01

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

Development of a Computer-based Benchmarking and Analytical Tool. Benchmarking and Energy & Water Savings Tool in Dairy Plants (BEST-Dairy)

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

Xu, Tengfang; Flapper, Joris; Ke, Jing

The overall goal of the project is to develop a computer-based benchmarking and energy and water savings tool (BEST-Dairy) for use in the California dairy industry – including four dairy processes – cheese, fluid milk, butter, and milk powder.

Predictive Data Tools Find Uses in Schools

ERIC Educational Resources Information Center

Sparks, Sarah D.

2011-01-01

The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

A consumer guide: tools to manage vegetation and fuels.

Treesearch

David L. Peterson; Louisa Evers; Rebecca A. Gravenmier; Ellen Eberhardt

2007-01-01

Current efforts to improve the scientific basis for fire management on public lands will benefit from more efficient transfer of technical information and tools that support planning, implementation, and effectiveness of vegetation and hazardous fuel treatments. The technical scope, complexity, and relevant spatial scale of analytical and decision support tools differ...

A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

PubMed

Jones, Stephen; Cournane, Seán; Sheehy, Niall; Hederman, Lucy

2016-12-01

Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

Extreme Pressure Synergistic Mechanism of Bismuth Naphthenate and Sulfurized Isobutene Additives

NASA Astrophysics Data System (ADS)

Xu, Xin; Hu, Jianqiang; Yang, Shizhao; Xie, Feng; Guo, Li

A four-ball tester was used to evaluate the tribological performances of bismuth naphthenate (BiNap), sulfurized isobutene (VSB), and their combinations. The results show that the antiwear properties of BiNap and VSB are not very visible, but they possess good extreme pressure (EP) properties, particularly sulfur containing bismuth additives. Synergistic EP properties of BiNap with various sulfur-containing additives were investigated. The results indicate that BiNap exhibits good EP synergism with sulfur-containing additives. The surface analytical tools, such as X-ray photoelectron spectrometer (XPS) scanning electron microscope (SEM) and energy dispersive X-ray (EDX), were used to investigate the topography, composition contents, and depth profile of some typical elements on the rubbing surface. Smooth topography of wear scar further confirms that the additive showed good EP capacities, and XPS and EDX analyzes indicate that tribochemical mixed protective films composed of bismuth, bismuth oxides, sulfides, and sulfates are formed on the rubbing surface, which improves the tribological properties of lubricants. In particular, a large number of bismuth atoms and bismuth sulfides play an important role in improving the EP properties of oils.

Assessment of Trading Partners for China's Rare Earth Exports Using a Decision Analytic Approach

PubMed Central

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies. PMID:25051534

Assessment of trading partners for China's rare earth exports using a decision analytic approach.

PubMed

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.

Comparison of Left Ventricular Hypertrophy by Electrocardiography and Echocardiography in Children Using Analytics Tool.

PubMed

Tague, Lauren; Wiggs, Justin; Li, Qianxi; McCarter, Robert; Sherwin, Elizabeth; Weinberg, Jacqueline; Sable, Craig

2018-05-17

Left ventricular hypertrophy (LVH) is a common finding on pediatric electrocardiography (ECG) leading to many referrals for echocardiography (echo). This study utilizes a novel analytics tool that combines ECG and echo databases to evaluate ECG as a screening tool for LVH. SQL Server 2012 data warehouse incorporated ECG and echo databases for all patients from a single institution from 2006 to 2016. Customized queries identified patients 0-18 years old with LVH on ECG and an echo performed within 24 h. Using data visualization (Tableau) and analytic (Stata 14) software, ECG and echo findings were compared. Of 437,699 encounters, 4637 met inclusion criteria. ECG had high sensitivity (≥ 90%) but poor specificity (43%), and low positive predictive value (< 20%) for echo abnormalities. ECG performed only 11-22% better than chance (AROC = 0.50). 83% of subjects with LVH on ECG had normal left ventricle (LV) structure and size on echo. African-Americans with LVH were least likely to have an abnormal echo. There was a low correlation between V 6 R on ECG and echo-derived Z score of left ventricle diastolic diameter (r = 0.14) and LV mass index (r = 0.24). The data analytics client was able to mine a database of ECG and echo reports, comparing LVH by ECG and LV measurements and qualitative findings by echo, identifying an abnormal LV by echo in only 17% of cases with LVH on ECG. This novel tool is useful for rapid data mining for both clinical and research endeavors.

A tool for selective inline quantification of co-eluting proteins in chromatography using spectral analysis and partial least squares regression.

PubMed

Brestrich, Nina; Briskot, Till; Osberghaus, Anna; Hubbuch, Jürgen

2014-07-01

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities. © 2014 Wiley Periodicals, Inc.

Recent Methodology in Ginseng Analysis

PubMed Central

Baek, Seung-Hoon; Bae, Ok-Nam; Park, Jeong Hill

2012-01-01

As much as the popularity of ginseng in herbal prescriptions or remedies, ginseng has become the focus of research in many scientific fields. Analytical methodologies for ginseng, referred to as ginseng analysis hereafter, have been developed for bioactive component discovery, phytochemical profiling, quality control, and pharmacokinetic studies. This review summarizes the most recent advances in ginseng analysis in the past half-decade including emerging techniques and analytical trends. Ginseng analysis includes all of the leading analytical tools and serves as a representative model for the analytical research of herbal medicines. PMID:23717112

ANAlyte: A modular image analysis tool for ANA testing with indirect immunofluorescence.

PubMed

Di Cataldo, Santa; Tonti, Simone; Bottino, Andrea; Ficarra, Elisa

2016-05-01

The automated analysis of indirect immunofluorescence images for Anti-Nuclear Autoantibody (ANA) testing is a fairly recent field that is receiving ever-growing interest from the research community. ANA testing leverages on the categorization of intensity level and fluorescent pattern of IIF images of HEp-2 cells to perform a differential diagnosis of important autoimmune diseases. Nevertheless, it suffers from tremendous lack of repeatability due to subjectivity in the visual interpretation of the images. The automatization of the analysis is seen as the only valid solution to this problem. Several works in literature address individual steps of the work-flow, nonetheless integrating such steps and assessing their effectiveness as a whole is still an open challenge. We present a modular tool, ANAlyte, able to characterize a IIF image in terms of fluorescent intensity level and fluorescent pattern without any user-interactions. For this purpose, ANAlyte integrates the following: (i) Intensity Classifier module, that categorizes the intensity level of the input slide based on multi-scale contrast assessment; (ii) Cell Segmenter module, that splits the input slide into individual HEp-2 cells; (iii) Pattern Classifier module, that determines the fluorescent pattern of the slide based on the pattern of the individual cells. To demonstrate the accuracy and robustness of our tool, we experimentally validated ANAlyte on two different public benchmarks of IIF HEp-2 images with rigorous leave-one-out cross-validation strategy. We obtained overall accuracy of fluorescent intensity and pattern classification respectively around 85% and above 90%. We assessed all results by comparisons with some of the most representative state of the art works. Unlike most of the other works in the recent literature, ANAlyte aims at the automatization of all the major steps of ANA image analysis. Results on public benchmarks demonstrate that the tool can characterize HEp-2 slides in terms of intensity and fluorescent pattern with accuracy better or comparable with the state of the art techniques, even when such techniques are run on manually segmented cells. Hence, ANAlyte can be proposed as a valid solution to the problem of ANA testing automatization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Standard addition method for the determination of pharmaceutical residues in drinking water by SPE-LC-MS/MS.

PubMed

Cimetiere, Nicolas; Soutrel, Isabelle; Lemasle, Marguerite; Laplanche, Alain; Crocq, André

2013-01-01

The study of the occurrence and fate of pharmaceutical compounds in drinking or waste water processes has become very popular in recent years. Liquid chromatography with tandem mass spectrometry is a powerful analytical tool often used to determine pharmaceutical residues at trace level in water. However, many steps may disrupt the analytical procedure and bias the results. A list of 27 environmentally relevant molecules, including various therapeutic classes and (cardiovascular, veterinary and human antibiotics, neuroleptics, non-steroidal anti-inflammatory drugs, hormones and other miscellaneous pharmaceutical compounds), was selected. In this work, a method was developed using ultra performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) and solid-phase extraction to determine the concentration of the 27 targeted pharmaceutical compounds at the nanogram per litre level. The matrix effect was evaluated from water sampled at different treatment stages. Conventional methods with external calibration and internal standard correction were compared with the standard addition method (SAM). An accurate determination of pharmaceutical compounds in drinking water was obtained by the SAM associated with UPLC-MS/MS. The developed method was used to evaluate the occurrence and fate of pharmaceutical compounds in some drinking water treatment plants in the west of France.

Analytical dose modeling for preclinical proton irradiation of millimetric targets.

PubMed

Vanstalle, Marie; Constanzo, Julie; Karakaya, Yusuf; Finck, Christian; Rousseau, Marc; Brasse, David

2018-01-01

Due to the considerable development of proton radiotherapy, several proton platforms have emerged to irradiate small animals in order to study the biological effectiveness of proton radiation. A dedicated analytical treatment planning tool was developed in this study to accurately calculate the delivered dose given the specific constraints imposed by the small dimensions of the irradiated areas. The treatment planning system (TPS) developed in this study is based on an analytical formulation of the Bragg peak and uses experimental range values of protons. The method was validated after comparison with experimental data from the literature and then compared to Monte Carlo simulations conducted using Geant4. Three examples of treatment planning, performed with phantoms made of water targets and bone-slab insert, were generated with the analytical formulation and Geant4. Each treatment planning was evaluated using dose-volume histograms and gamma index maps. We demonstrate the value of the analytical function for mouse irradiation, which requires a targeting accuracy of 0.1 mm. Using the appropriate database, the analytical modeling limits the errors caused by misestimating the stopping power. For example, 99% of a 1-mm tumor irradiated with a 24-MeV beam receives the prescribed dose. The analytical dose deviations from the prescribed dose remain within the dose tolerances stated by report 62 of the International Commission on Radiation Units and Measurements for all tested configurations. In addition, the gamma index maps show that the highly constrained targeting accuracy of 0.1 mm for mouse irradiation leads to a significant disagreement between Geant4 and the reference. This simulated treatment planning is nevertheless compatible with a targeting accuracy exceeding 0.2 mm, corresponding to rat and rabbit irradiations. Good dose accuracy for millimetric tumors is achieved with the analytical calculation used in this work. These volume sizes are typical in mouse models for radiation studies. Our results demonstrate that the choice of analytical rather than simulated treatment planning depends on the animal model under consideration. © 2017 American Association of Physicists in Medicine.

Comparison of analytical tools appropriate for identification of proteinaceous additives in historical mortars.

PubMed

Krizova, Iva; Schultz, Julia; Nemec, Ivan; Cabala, Radomir; Hynek, Radovan; Kuckova, Stepanka

2018-01-01

Natural organic additives such as eggs, lard, resins, and oils have been added to mortars since ancient times, because the ancient builders knew of their positive effect on the mortar quality. The tradition of adding organic materials to mortars was commonly handed down only verbally for thousands years. However, this practice disappeared in the nineteenth century, when the usage of modern materials started. Today, one of the most recent topics in the industry of building materials is the reusing of natural organic materials and searching for the forgotten ancient recipes. The research of the old technological approaches involves currently the most advanced analytical techniques and methods. This paper is focussed on testing the possibility of identification of proteinaceous additives in historical mortars and model mortar samples containing blood, bone glue, curd, eggs and gelatine, by Fourier transform infrared (FTIR) and Raman spectroscopy, gas chromatography - mass spectrometry (GC-MS), matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI-TOF MS), liquid chromatography-electrospray ionisation-quadrupole-time of flight mass spectrometry (LC-ESI-Q-TOF MS) and enzyme-linked immunosorbent assay (ELISA). All these methods were applied to the mortar sample taken from the interior of the medieval (sixteenth century) castle in Namest nad Oslavou in the Czech Republic and their comparison contributed to the rough estimation of the protein additive content in the mortar. The obtained results demonstrate that only LC-ESI-Q-TOF MS, MALDI-TOF MS and ELISA have the sufficiently low detection limits that enable the reliable identification of collagens in historical mortars. Graphical abstract Proteomics analyses of historical mortars.

Pre-analytical issues in the haemostasis laboratory: guidance for the clinical laboratories.

PubMed

Magnette, A; Chatelain, M; Chatelain, B; Ten Cate, H; Mullier, F

2016-01-01

Ensuring quality has become a daily requirement in laboratories. In haemostasis, even more than in other disciplines of biology, quality is determined by a pre-analytical step that encompasses all procedures, starting with the formulation of the medical question, and includes patient preparation, sample collection, handling, transportation, processing, and storage until time of analysis. This step, based on a variety of manual activities, is the most vulnerable part of the total testing process and is a major component of the reliability and validity of results in haemostasis and constitutes the most important source of erroneous or un-interpretable results. Pre-analytical errors may occur throughout the testing process and arise from unsuitable, inappropriate or wrongly handled procedures. Problems may arise during the collection of blood specimens such as misidentification of the sample, use of inadequate devices or needles, incorrect order of draw, prolonged tourniquet placing, unsuccessful attempts to locate the vein, incorrect use of additive tubes, collection of unsuitable samples for quality or quantity, inappropriate mixing of a sample, etc. Some factors can alter the result of a sample constituent after collection during transportation, preparation and storage. Laboratory errors can often have serious adverse consequences. Lack of standardized procedures for sample collection accounts for most of the errors encountered within the total testing process. They can also have clinical consequences as well as a significant impact on patient care, especially those related to specialized tests as these are often considered as "diagnostic". Controlling pre-analytical variables is critical since this has a direct influence on the quality of results and on their clinical reliability. The accurate standardization of the pre-analytical phase is of pivotal importance for achieving reliable results of coagulation tests and should reduce the side effects of the influence factors. This review is a summary of the most important recommendations regarding the importance of pre-analytical factors for coagulation testing and should be a tool to increase awareness about the importance of pre-analytical factors for coagulation testing.

Constraint-Referenced Analytics of Algebra Learning

ERIC Educational Resources Information Center

Sutherland, Scot M.; White, Tobin F.

2016-01-01

The development of the constraint-referenced analytics tool for monitoring algebra learning activities presented here came from the desire to firstly, take a more quantitative look at student responses in collaborative algebra activities, and secondly, to situate those activities in a more traditional introductory algebra setting focusing on…

Towards an Analytic Foundation for Network Architecture

DTIC Science & Technology

2010-12-31

SUPPLEMENTARY NOTES N/A 14. ABSTRACT In this project, we develop the analytic tools of stochastic optimization for wireless network design and apply them...and Mung Chiang, “ DaVinci : Dynamically Adaptive Virtual Networks for a Customized Internet,” in Proc. ACM SIGCOMM CoNext Conference, December 2008

University Macro Analytic Simulation Model.

ERIC Educational Resources Information Center

Baron, Robert; Gulko, Warren

The University Macro Analytic Simulation System (UMASS) has been designed as a forecasting tool to help university administrators budgeting decisions. Alternative budgeting strategies can be tested on a computer model and then an operational alternative can be selected on the basis of the most desirable projected outcome. UMASS uses readily…

Advancements in Large-Scale Data/Metadata Management for Scientific Data.

NASA Astrophysics Data System (ADS)

Guntupally, K.; Devarakonda, R.; Palanisamy, G.; Frame, M. T.

2017-12-01

Scientific data often comes with complex and diverse metadata which are critical for data discovery and users. The Online Metadata Editor (OME) tool, which was developed by an Oak Ridge National Laboratory team, effectively manages diverse scientific datasets across several federal data centers, such as DOE's Atmospheric Radiation Measurement (ARM) Data Center and USGS's Core Science Analytics, Synthesis, and Libraries (CSAS&L) project. This presentation will focus mainly on recent developments and future strategies for refining OME tool within these centers. The ARM OME is a standard based tool (https://www.archive.arm.gov/armome) that allows scientists to create and maintain metadata about their data products. The tool has been improved with new workflows that help metadata coordinators and submitting investigators to submit and review their data more efficiently. The ARM Data Center's newly upgraded Data Discovery Tool (http://www.archive.arm.gov/discovery) uses rich metadata generated by the OME to enable search and discovery of thousands of datasets, while also providing a citation generator and modern order-delivery techniques like Globus (using GridFTP), Dropbox and THREDDS. The Data Discovery Tool also supports incremental indexing, which allows users to find new data as and when they are added. The USGS CSAS&L search catalog employs a custom version of the OME (https://www1.usgs.gov/csas/ome), which has been upgraded with high-level Federal Geographic Data Committee (FGDC) validations and the ability to reserve and mint Digital Object Identifiers (DOIs). The USGS's Science Data Catalog (SDC) (https://data.usgs.gov/datacatalog) allows users to discover a myriad of science data holdings through a web portal. Recent major upgrades to the SDC and ARM Data Discovery Tool include improved harvesting performance and migration using new search software, such as Apache Solr 6.0 for serving up data/metadata to scientific communities. Our presentation will highlight the future enhancements of these tools which enable users to retrieve fast search results, along with parallelizing the retrieval process from online and High Performance Storage Systems. In addition, these improvements to the tools will support additional metadata formats like the Large-Eddy Simulation (LES) ARM Symbiotic and Observation (LASSO) bundle data.

Initiating an Online Reputation Monitoring System with Open Source Analytics Tools

NASA Astrophysics Data System (ADS)

Shuhud, Mohd Ilias M.; Alwi, Najwa Hayaati Md; Halim, Azni Haslizan Abd

2018-05-01

Online reputation is an invaluable asset for modern organizations as it can help in business performance especially in sales and profit. However, if we are not aware of our reputation, it is difficult to maintain it. Thus, social media analytics is a new tool that can provide online reputation monitoring in various ways such as sentiment analysis. As a result, numerous large-scale organizations have implemented Online Reputation Monitoring (ORM) systems. However, this solution is not supposed to be exclusively for high-income organizations, as many organizations regardless sizes and types are now online. This research attempts to propose an affordable and reliable ORM system using combination of open source analytics tools for both novice practitioners and academicians. We also evaluate its prediction accuracy and we discovered that the system provides acceptable predictions (sixty percent accuracy) and demonstrate a tally prediction of major polarity by human annotation. The proposed system can help in supporting business decisions with flexible monitoring strategies especially for organization that want to initiate and administrate ORM themselves at low cost.

Updates in metabolomics tools and resources: 2014-2015.

PubMed

Misra, Biswapriya B; van der Hooft, Justin J J

2016-01-01

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Free web-based modelling platform for managed aquifer recharge (MAR) applications

NASA Astrophysics Data System (ADS)

Stefan, Catalin; Junghanns, Ralf; Glaß, Jana; Sallwey, Jana; Fatkhutdinov, Aybulat; Fichtner, Thomas; Barquero, Felix; Moreno, Miguel; Bonilla, José; Kwoyiga, Lydia

2017-04-01

Managed aquifer recharge represents a valuable instrument for sustainable water resources management. The concept implies purposeful infiltration of surface water into underground for later recovery or environmental benefits. Over decades, MAR schemes were successfully installed worldwide for a variety of reasons: to maximize the natural storage capacity of aquifers, physical aquifer management, water quality management, and ecological benefits. The INOWAS-DSS platform provides a collection of free web-based tools for planning, management and optimization of main components of MAR schemes. The tools are grouped into 13 specific applications that cover most relevant challenges encountered at MAR sites, both from quantitative and qualitative perspectives. The applications include among others the optimization of MAR site location, the assessment of saltwater intrusion, the restoration of groundwater levels in overexploited aquifers, the maximization of natural storage capacity of aquifers, the improvement of water quality, the design and operational optimization of MAR schemes, clogging development and risk assessment. The platform contains a collection of about 35 web-based tools of various degrees of complexity, which are either included in application specific workflows or used as standalone modelling instruments. Among them are simple tools derived from data mining and empirical equations, analytical groundwater related equations, as well as complex numerical flow and transport models (MODFLOW, MT3DMS and SEAWAT). Up to now, the simulation core of the INOWAS-DSS, which is based on the finite differences groundwater flow model MODFLOW, is implemented and runs on the web. A scenario analyser helps to easily set up and evaluate new management options as well as future development such as land use and climate change and compare them to previous scenarios. Additionally simple tools such as analytical equations to assess saltwater intrusion are already running online. Besides the simulation tools, a web-based data base is under development where geospatial and time series data can be stored, managed, and processed. Furthermore, a web-based information system containing user guides for the various developed tools and applications as well as basic information on MAR and related topics is published and will be regularly expanded as new tools are getting implemented. The INOWAS-DSS including its simulation tools, data base and information system provides an extensive framework to manage, plan and optimize MAR facilities. As the INOWAS-DSS is an open-source software accessible via the internet using standard web browsers, it offers new ways for data sharing and collaboration among various partners and decision makers.

3D FEM Simulation of Flank Wear in Turning

NASA Astrophysics Data System (ADS)

Attanasio, Aldo; Ceretti, Elisabetta; Giardini, Claudio

2011-05-01

This work deals with tool wear simulation. Studying the influence of tool wear on tool life, tool substitution policy and influence on final part quality, surface integrity, cutting forces and power consumption it is important to reduce the global process costs. Adhesion, abrasion, erosion, diffusion, corrosion and fracture are some of the phenomena responsible of the tool wear depending on the selected cutting parameters: cutting velocity, feed rate, depth of cut, …. In some cases these wear mechanisms are described by analytical models as a function of process variables (temperature, pressure and sliding velocity along the cutting surface). These analytical models are suitable to be implemented in FEM codes and they can be utilized to simulate the tool wear. In the present paper a commercial 3D FEM software has been customized to simulate the tool wear during turning operations when cutting AISI 1045 carbon steel with uncoated tungsten carbide tip. The FEM software was improved by means of a suitable subroutine able to modify the tool geometry on the basis of the estimated tool wear as the simulation goes on. Since for the considered couple of tool-workpiece material the main phenomena generating wear are the abrasive and the diffusive ones, the tool wear model implemented into the subroutine was obtained as combination between the Usui's and the Takeyama and Murata's models. A comparison between experimental and simulated flank tool wear curves is reported demonstrating that it is possible to simulate the tool wear development.

Using social autopsy to understand maternal, newborn, and child mortality in low-resource settings: a systematic review of the literature

PubMed Central

Moyer, Cheryl A.; Johnson, Cassidy; Kaselitz, Elizabeth; Aborigo, Raymond

2017-01-01

ABSTRACT Background: Social, cultural, and behavioral factors are often potent upstream contributors to maternal, neonatal, and child mortality, especially in low- and middle-income countries (LMICs). Social autopsy is one method of identifying the impact of such factors, yet it is unclear how social autopsy methods are being used in LMICs. Objective: This study aimed to identify the most common social autopsy instruments, describe overarching findings across populations and geography, and identify gaps in the existing social autopsy literature. Methods: A systematic search of the peer-reviewed literature from 2005 to 2016 was conducted. Studies were included if they were conducted in an LMIC, focused on maternal/neonatal/infant/child health, reported on the results of original research, and explicitly mentioned the use of a social autopsy tool. Results: Sixteen articles out of 1950 citations were included, representing research conducted in 11 countries. Five different tools were described, with two primary conceptual frameworks used to guide analysis: Pathway to Survival and Three Delays models. Studies varied in methods for identifying deaths, and recall periods for respondents ranged from 6 weeks to 5+ years. Across studies, recognition of danger signs appeared to be high, while subsequent care-seeking was inconsistent. Cost, distance to facility, and transportation issues were frequently cited barriers to care-seeking, however, additional barriers were reported that varied by location. Gaps in the social autopsy literature include the lack of: harmonized tools and analytical methods that allow for cross-study comparisons, discussion of complexity of decision making for care seeking, qualitative narratives that address inconsistencies in responses, and the explicit inclusion of perspectives from husbands and fathers. Conclusion: Despite the nascence of the field, research across 11 countries has included social autopsy methods, using a variety of tools, sampling methods, and analytical frameworks to determine how social factors impact maternal, neonatal, and child health outcomes. PMID:29261449

Weathering the Storm: Developing a Spatial Data Infrastructure and Online Research Platform for Oil Spill Preparedness

NASA Astrophysics Data System (ADS)

Bauer, J. R.; Rose, K.; Romeo, L.; Barkhurst, A.; Nelson, J.; Duran-Sesin, R.; Vielma, J.

2016-12-01

Efforts to prepare for and reduce the risk of hazards, from both natural and anthropogenic sources, which threaten our oceans and coasts requires an understanding of the dynamics and interactions between the physical, ecological, and socio-economic systems. Understanding these coupled dynamics are essential as offshore oil & gas exploration and production continues to push into harsher, more extreme environments where risks and uncertainty increase. However, working with these large, complex data from various sources and scales to assess risks and potential impacts associated with offshore energy exploration and production poses several challenges to research. In order to address these challenges, an integrated assessment model (IAM) was developed at the Department of Energy's (DOE) National Energy Technology Laboratory (NETL) that combines spatial data infrastructure and an online research platform to manage, process, analyze, and share these large, multidimensional datasets, research products, and the tools and models used to evaluate risk and reduce uncertainty for the entire offshore system, from the subsurface, through the water column, to coastal ecosystems and communities. Here, we will discuss the spatial data infrastructure and online research platform, NETL's Energy Data eXchange (EDX), that underpin the offshore IAM, providing information on how the framework combines multidimensional spatial data and spatio-temporal tools to evaluate risks to the complex matrix of potential environmental, social, and economic impacts stemming from modeled offshore hazard scenarios, such as oil spills or hurricanes. In addition, we will discuss the online analytics, tools, and visualization methods integrated into this framework that support availability and access to data, as well as allow for the rapid analysis and effective communication of analytical results to aid a range of decision-making needs.

Development and Validation of a Hypersonic Vehicle Design Tool Based On Waverider Design Technique

NASA Astrophysics Data System (ADS)

Dasque, Nastassja

Methodologies for a tool capable of assisting design initiatives for practical waverider based hypersonic vehicles were developed and validated. The design space for vehicle surfaces was formed using an algorithm that coupled directional derivatives with the conservation laws to determine a flow field defined by a set of post-shock streamlines. The design space is used to construct an ideal waverider with a sharp leading edge. A blunting method was developed to modify the ideal shapes to a more practical geometry for real-world application. Empirical and analytical relations were then systematically applied to the resulting geometries to determine local pressure, skin-friction and heat flux. For the ideal portion of the geometry, flat plate relations for compressible flow were applied. For the blunted portion of the geometry modified Newtonian theory, Fay-Riddell theory and Modified Reynolds analogy were applied. The design and analysis methods were validated using analytical solutions as well as empirical and numerical data. The streamline solution for the flow field generation technique was compared with a Taylor-Maccoll solution and showed very good agreement. The relationship between the local Stanton number and skin friction coefficient with local Reynolds number along the ideal portion of the body showed good agreement with experimental data. In addition, an automated grid generation routine was formulated to construct a structured mesh around resulting geometries in preparation for Computational Fluid Dynamics analysis. The overall analysis of the waverider body using the tool was then compared to CFD studies. The CFD flow field showed very good agreement with the design space. However, the distribution of the surface properties was near CFD results but did not have great agreement.

Average of delta: a new quality control tool for clinical laboratories.

PubMed

Jones, Graham R D

2016-01-01

Average of normals is a tool used to control assay performance using the average of a series of results from patients' samples. Delta checking is a process of identifying errors in individual patient results by reviewing the difference from previous results of the same patient. This paper introduces a novel alternate approach, average of delta, which combines these concepts to use the average of a number of sequential delta values to identify changes in assay performance. Models for average of delta and average of normals were developed in a spreadsheet application. The model assessed the expected scatter of average of delta and average of normals functions and the effect of assay bias for different values of analytical imprecision and within- and between-subject biological variation and the number of samples included in the calculations. The final assessment was the number of patients' samples required to identify an added bias with 90% certainty. The model demonstrated that with larger numbers of delta values, the average of delta function was tighter (lower coefficient of variation). The optimal number of samples for bias detection with average of delta was likely to be between 5 and 20 for most settings and that average of delta outperformed average of normals when the within-subject biological variation was small relative to the between-subject variation. Average of delta provides a possible additional assay quality control tool which theoretical modelling predicts may be more valuable than average of normals for analytes where the group biological variation is wide compared with within-subject variation and where there is a high rate of repeat testing in the laboratory patient population. © The Author(s) 2015.

Stream Lifetimes Against Planetary Encounters

NASA Technical Reports Server (NTRS)

Valsecchi, G. B.; Lega, E.; Froeschle, Cl.

2011-01-01

We study, both analytically and numerically, the perturbation induced by an encounter with a planet on a meteoroid stream. Our analytical tool is the extension of pik s theory of close encounters, that we apply to streams described by geocentric variables. The resulting formulae are used to compute the rate at which a stream is dispersed by planetary encounters into the sporadic background. We have verified the accuracy of the analytical model using a numerical test.

Comparative analytics of infusion pump data across multiple hospital systems.

PubMed

Catlin, Ann Christine; Malloy, William X; Arthur, Karen J; Gaston, Cindy; Young, James; Fernando, Sudheera; Fernando, Ruchith

2015-02-15

A Web-based analytics system for conducting inhouse evaluations and cross-facility comparisons of alert data generated by smart infusion pumps is described. The Infusion Pump Informatics (IPI) project, a collaborative effort led by research scientists at Purdue University, was launched in 2009 to provide advanced analytics and tools for workflow analyses to assist hospitals in determining the significance of smart-pump alerts and reducing nuisance alerts. The IPI system allows facility-specific analyses of alert patterns and trends, as well as cross-facility comparisons of alert data uploaded by more than 55 participating institutions using different types of smart pumps. Tools accessible through the IPI portal include (1) charts displaying aggregated or breakout data on the top drugs associated with alerts, numbers of alerts per device or care area, and override-to-alert ratios, (2) investigative reports that can be used to characterize and analyze pump-programming errors in a variety of ways (e.g., by drug, by infusion type, by time of day), and (3) "drill-down" workflow analytics enabling users to evaluate alert patterns—both internally and in relation to patterns at other hospitals—in a quick and efficient stepwise fashion. The formation of the IPI analytics system to support a community of hospitals has been successful in providing sophisticated tools for member facilities to review, investigate, and efficiently analyze smart-pump alert data, not only within a member facility but also across other member facilities, to further enhance smart pump drug library design. Copyright © 2015 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...

LATUX: An Iterative Workflow for Designing, Validating, and Deploying Learning Analytics Visualizations

ERIC Educational Resources Information Center

Martinez-Maldonado, Roberto; Pardo, Abelardo; Mirriahi, Negin; Yacef, Kalina; Kay, Judy; Clayphan, Andrew

2015-01-01

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…

Microprocessor Based Temperature Control of Liquid Delivery with Flow Disturbances.

ERIC Educational Resources Information Center

Kaya, Azmi

1982-01-01

Discusses analytical design and experimental verification of a PID control value for a temperature controlled liquid delivery system, demonstrating that the analytical design techniques can be experimentally verified by using digital controls as a tool. Digital control instrumentation and implementation are also demonstrated and documented for…

Advances in analytical technologies for environmental protection and public safety.

PubMed

Sadik, O A; Wanekaya, A K; Andreescu, S

2004-06-01

Due to the increased threats of chemical and biological agents of injury by terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat chemical and biochemical toxins. In addition to the right mix of policies and training of medical personnel on how to recognize symptoms of biochemical warfare agents, the major success in combating terrorism still lies in the prevention, early detection and the efficient and timely response using reliable analytical technologies and powerful therapies for minimizing the effects in the event of an attack. The public and regulatory agencies expect reliable methodologies and devices for public security. Today's systems are too bulky or slow to meet the "detect-to-warn" needs for first responders such as soldiers and medical personnel. This paper presents the challenges in monitoring technologies for warfare agents and other toxins. It provides an overview of how advances in environmental analytical methodologies could be adapted to design reliable sensors for public safety and environmental surveillance. The paths to designing sensors that meet the needs of today's measurement challenges are analyzed using examples of novel sensors, autonomous cell-based toxicity monitoring, 'Lab-on-a-Chip' devices and conventional environmental analytical techniques. Finally, in order to ensure that the public and legal authorities are provided with quality data to make informed decisions, guidelines are provided for assessing data quality and quality assurance using the United States Environmental Protection Agency (US-EPA) methodologies.

Transcutaneous Measurement of Blood Analyte Concentration Using Raman Spectroscopy

NASA Astrophysics Data System (ADS)

Barman, Ishan; Singh, Gajendra P.; Dasari, Ramachandra R.; Feld, Michael S.

2008-11-01

Diabetes mellitus is a chronic disorder, affecting nearly 200 million people worldwide. Acute complications, such as hypoglycemia, cardiovascular disease and retinal damage, may occur if the disease is not adequately controlled. As diabetes has no known cure, tight control of glucose levels is critical for the prevention of such complications. Given the necessity for regular monitoring of blood glucose, development of non-invasive glucose detection devices is essential to improve the quality of life in diabetic patients. The commercially available glucose sensors measure the interstitial fluid glucose by electrochemical detection. However, these sensors have severe limitations, primarily related to their invasive nature and lack of stability. This necessitates the development of a truly non-invasive glucose detection technique. NIR Raman Spectroscopy, which combines the substantial penetration depth of NIR light with the excellent chemical specificity of Raman spectroscopy, provides an excellent tool to meet the challenges involved. Additionally, it enables simultaneous determination of multiple blood analytes. Our laboratory has pioneered the use of Raman spectroscopy for blood analytes' detection in biological media. The preliminary success of our non-invasive glucose measurements both in vitro (such as in serum and blood) and in vivo has provided the foundation for the development of feasible clinical systems. However, successful application of this technology still faces a few hurdles, highlighted by the problems of tissue luminescence and selection of appropriate reference concentration. In this article we explore possible avenues to overcome these challenges so that prospective prediction accuracy of blood analytes can be brought to clinically acceptable levels.

Cascaded analysis of signal and noise propagation through a heterogeneous breast model.

PubMed

Mainprize, James G; Yaffe, Martin J

2010-10-01

The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the "power law" filter used to generate the texture of the tissue distribution. A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

A thermal biosensor based on enzyme reaction.

PubMed

Zheng, Yi-Hua; Hua, Tse-Chao; Xu, Fei

2005-01-01

Application of the thermal biosensor as analytical tool is promising due to advantages as universal, simplicity and quick response. A novel thermal biosensor based on enzyme reaction has been developed. This biosensor is a flow injection analysis system and consists of two channels with enzyme reaction column and reference column. The reference column, which is set for eliminating the unspecific heat, is inactived on special enzyme reaction of the ingredient to be detected. The special enzyme reaction takes places in the enzyme reaction column at a constant temperature realizing by a thermoelectric thermostat. Thermal sensor based on the thermoelectric module containing 127 serial BiTe-thermocouples is used to monitor the temperature difference between two streams from the enzyme reaction column and the reference column. The analytical example for dichlorvos shows that this biosensor can be used as analytical tool in medicine and biology.

Optical Drug Monitoring: Photoacoustic Imaging of Nanosensors to Monitor Therapeutic Lithium In Vivo

PubMed Central

Cash, Kevin J.; Li, Chiye; Xia, Jun; Wang, Lihong V.; Clark, Heather A.

2015-01-01

Personalized medicine could revolutionize how primary care physicians treat chronic disease and how researchers study fundamental biological questions. To realize this goal we need to develop more robust, modular tools and imaging approaches for in vivo monitoring of analytes. In this report, we demonstrate that synthetic nanosensors can measure physiologic parameters with photoacoustic contrast, and we apply that platform to continuously track lithium levels in vivo. Photoacoustic imaging achieves imaging depths that are unattainable with fluorescence or multiphoton microscopy. We validated the photoacoustic results that illustrate the superior imaging depth and quality of photoacoustic imaging with optical measurements. This powerful combination of techniques will unlock the ability to measure analyte changes in deep tissue and will open up photoacoustic imaging as a diagnostic tool for continuous physiological tracking of a wide range of analytes. PMID:25588028

Optical drug monitoring: photoacoustic imaging of nanosensors to monitor therapeutic lithium in vivo.

PubMed

Cash, Kevin J; Li, Chiye; Xia, Jun; Wang, Lihong V; Clark, Heather A

2015-02-24

Personalized medicine could revolutionize how primary care physicians treat chronic disease and how researchers study fundamental biological questions. To realize this goal, we need to develop more robust, modular tools and imaging approaches for in vivo monitoring of analytes. In this report, we demonstrate that synthetic nanosensors can measure physiologic parameters with photoacoustic contrast, and we apply that platform to continuously track lithium levels in vivo. Photoacoustic imaging achieves imaging depths that are unattainable with fluorescence or multiphoton microscopy. We validated the photoacoustic results that illustrate the superior imaging depth and quality of photoacoustic imaging with optical measurements. This powerful combination of techniques will unlock the ability to measure analyte changes in deep tissue and will open up photoacoustic imaging as a diagnostic tool for continuous physiological tracking of a wide range of analytes.

Chemical Functionalization of Plasmonic Surface Biosensors: A Tutorial Review on Issues, Strategies, and Costs

PubMed Central

2017-01-01

In an ideal plasmonic surface sensor, the bioactive area, where analytes are recognized by specific biomolecules, is surrounded by an area that is generally composed of a different material. The latter, often the surface of the supporting chip, is generally hard to be selectively functionalized, with respect to the active area. As a result, cross talks between the active area and the surrounding one may occur. In designing a plasmonic sensor, various issues must be addressed: the specificity of analyte recognition, the orientation of the immobilized biomolecule that acts as the analyte receptor, and the selectivity of surface coverage. The objective of this tutorial review is to introduce the main rational tools required for a correct and complete approach to chemically functionalize plasmonic surface biosensors. After a short introduction, the review discusses, in detail, the most common strategies for achieving effective surface functionalization. The most important issues, such as the orientation of active molecules and spatial and chemical selectivity, are considered. A list of well-defined protocols is suggested for the most common practical situations. Importantly, for the reported protocols, we also present direct comparisons in term of costs, labor demand, and risk vs benefit balance. In addition, a survey of the most used characterization techniques necessary to validate the chemical protocols is reported. PMID:28796479

Helicase-dependent isothermal amplification: a novel tool in the development of molecular-based analytical systems for rapid pathogen detection.

PubMed

Barreda-García, Susana; Miranda-Castro, Rebeca; de-Los-Santos-Álvarez, Noemí; Miranda-Ordieres, Arturo J; Lobo-Castañón, María Jesús

2018-01-01

Highly sensitive testing of nucleic acids is essential to improve the detection of pathogens, which pose a major threat for public health worldwide. Currently available molecular assays, mainly based on PCR, have a limited utility in point-of-need control or resource-limited settings. Consequently, there is a strong interest in developing cost-effective, robust, and portable platforms for early detection of these harmful microorganisms. Since its description in 2004, isothermal helicase-dependent amplification (HDA) has been successfully applied in the development of novel molecular-based technologies for rapid, sensitive, and selective detection of viruses and bacteria. In this review, we highlight relevant analytical systems using this simple nucleic acid amplification methodology that takes place at a constant temperature and that is readily compatible with microfluidic technologies. Different strategies for monitoring HDA amplification products are described. In addition, we present technological advances for integrating sample preparation, HDA amplification, and detection. Future perspectives and challenges toward point-of-need use not only for clinical diagnosis but also in food safety testing and environmental monitoring are also discussed. Graphical Abstract Expanding the analytical toolbox for the detection of DNA sequences specific of pathogens with isothermal helicase dependent amplification (HDA).

Screening and selection of artificial riboswitches.

PubMed

Harbaugh, Svetlana V; Martin, Jennifer; Weinstein, Jenna; Ingram, Grant; Kelley-Loughnane, Nancy

2018-05-17

Synthetic riboswitches are engineered to regulate gene expression in response to a variety of non-endogenous small molecules, and a challenge to select this engineered response requires robust screening tools. A new synthetic riboswitch can be created by linking an in vitro-selected aptamer library with a randomized expression platform followed by in vivo selection and screening. In order to determine response to analyte, we developed a dual-color reporter comprising elements of the E. coli fimbriae phase variation system: recombinase FimE controlled by a synthetic riboswitch and an invertible DNA segment (fimS) containing a constitutively active promoter placed between two fluorescent protein genes. Without an analyte, the fluorescent reporter constitutively expressed green fluorescent protein (GFPa1). Addition of the analyte initiated translation of fimE causing unidirectional inversion of the fimS segment and constitutive expression of red fluorescent protein (mKate2). The dual color reporter system can be used to select and to optimize artificial riboswitches in E. coli cells. In this work, the enriched library of aptamers incorporated into the riboswitch architecture reduces the sequence search space by offering a higher percentage of potential ligand binders. The study was designed to produce structure switching aptamers, a necessary feature for riboswitch function and efficiently quantify this function using the dual color reporter system. Copyright © 2018. Published by Elsevier Inc.

SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations.

PubMed

Liu, Dongyu; Weng, Di; Li, Yuhong; Bao, Jie; Zheng, Yu; Qu, Huamin; Wu, Yingcai

2017-01-01

The problem of formulating solutions immediately and comparing them rapidly for billboard placements has plagued advertising planners for a long time, owing to the lack of efficient tools for in-depth analyses to make informed decisions. In this study, we attempt to employ visual analytics that combines the state-of-the-art mining and visualization techniques to tackle this problem using large-scale GPS trajectory data. In particular, we present SmartAdP, an interactive visual analytics system that deals with the two major challenges including finding good solutions in a huge solution space and comparing the solutions in a visual and intuitive manner. An interactive framework that integrates a novel visualization-driven data mining model enables advertising planners to effectively and efficiently formulate good candidate solutions. In addition, we propose a set of coupled visualizations: a solution view with metaphor-based glyphs to visualize the correlation between different solutions; a location view to display billboard locations in a compact manner; and a ranking view to present multi-typed rankings of the solutions. This system has been demonstrated using case studies with a real-world dataset and domain-expert interviews. Our approach can be adapted for other location selection problems such as selecting locations of retail stores or restaurants using trajectory data.

Final Technical Report - SciDAC Cooperative Agreement: Center for Wave Interactions with Magnetohydrodynamics

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

Schnack, Dalton D.

Final technical report for research performed by Dr. Thomas G. Jenkins in collaboration with Professor Dalton D. Schnack on SciDAC Cooperative Agreement: Center for Wave Interactions with Magnetohydrodyanics, DE-FC02-06ER54899, for the period of 8/15/06 - 8/14/11. This report centers on the Slow MHD physics campaign work performed by Dr. Jenkins while at UW-Madison and then at Tech-X Corporation. To make progress on the problem of RF induced currents affect magnetic island evolution in toroidal plasmas, a set of research approaches are outlined. Three approaches can be addressed in parallel. These are: (1) Analytically prescribed additional term in Ohm's law tomore » model the effect of localized ECCD current drive; (2) Introduce an additional evolution equation for the Ohm's law source term. Establish a RF source 'box' where information from the RF code couples to the fluid evolution; and (3) Carry out a more rigorous analytic calculation treating the additional RF terms in a closure problem. These approaches rely on the necessity of reinvigorating the computation modeling efforts of resistive and neoclassical tearing modes with present day versions of the numerical tools. For the RF community, the relevant action item is - RF ray tracing codes need to be modified so that general three-dimensional spatial information can be obtained. Further, interface efforts between the two codes require work as well as an assessment as to the numerical stability properties of the procedures to be used.« less

Optimization of the β-Elimination/Michael Addition Chemistry on Reversed-Phase Supports for Mass Spectrometry Analysis of O-Linked Protein Modifications

PubMed Central

Nika, Heinz; Nieves, Edward; Hawke, David H.; Angeletti, Ruth Hogue

2013-01-01

We previously adapted the β-elimination/Michael addition chemistry to solid-phase derivatization on reversed-phase supports, and demonstrated the utility of this reaction format to prepare phosphoseryl peptides in unfractionated protein digests for mass spectrometric identification and facile phosphorylation-site determination. Here, we have expanded the use of this technique to β-N-acetylglucosamine peptides, modified at serine/threonine, phosphothreonyl peptides, and phosphoseryl/phosphothreonyl peptides, followed in sequence by proline. The consecutive β-elimination with Michael addition was adapted to optimize the solid-phase reaction conditions for throughput and completeness of derivatization. The analyte remained intact during derivatization and was recovered efficiently from the silica-based, reversed-phase support with minimal sample loss. The general use of the solid-phase approach for enzymatic dephosphorylation was demonstrated with phosphoseryl and phosphothreonyl peptides and was used as an orthogonal method to confirm the identity of phosphopeptides in proteolytic mixtures. The solid-phase approach proved highly suitable to prepare substrates from low-level amounts of protein digests for phosphorylation-site determination by chemical-targeted proteolysis. The solid-phase protocol provides for a simple, robust, and efficient tool to prepare samples for phosphopeptide identification in MALDI mass maps of unfractionated protein digests, using standard equipment available in most biological laboratories. The use of a solid-phase analytical platform is expected to be readily expanded to prepare digest from O-glycosylated- and O-sulfonated proteins for mass spectrometry-based structural characterization. PMID:23997661

Characterization of hydraulic fracturing flowback water in Colorado: implications for water treatment.

PubMed

Lester, Yaal; Ferrer, Imma; Thurman, E Michael; Sitterley, Kurban A; Korak, Julie A; Aiken, George; Linden, Karl G

2015-04-15

A suite of analytical tools was applied to thoroughly analyze the chemical composition of an oil/gas well flowback water from the Denver-Julesburg (DJ) basin in Colorado, and the water quality data was translated to propose effective treatment solutions tailored to specific reuse goals. Analysis included bulk quality parameters, trace organic and inorganic constituents, and organic matter characterization. The flowback sample contained salts (TDS=22,500 mg/L), metals (e.g., iron at 81.4 mg/L) and high concentration of dissolved organic matter (DOC=590 mgC/L). The organic matter comprised fracturing fluid additives such as surfactants (e.g., linear alkyl ethoxylates) and high levels of acetic acid (an additives' degradation product), indicating the anthropogenic impact on this wastewater. Based on the water quality results and preliminary treatability tests, the removal of suspended solids and iron by aeration/precipitation (and/or filtration) followed by disinfection was identified as appropriate for flowback recycling in future fracturing operations. In addition to these treatments, a biological treatment (to remove dissolved organic matter) followed by reverse osmosis desalination was determined to be necessary to attain water quality standards appropriate for other water reuse options (e.g., crop irrigation). The study provides a framework for evaluating site-specific hydraulic fracturing wastewaters, proposing a suite of analytical methods for characterization, and a process for guiding the choice of a tailored treatment approach. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving a complex finite-difference ground water flow model through the use of an analytic element screening model

USGS Publications Warehouse

Hunt, R.J.; Anderson, M.P.; Kelson, V.A.

1998-01-01

This paper demonstrates that analytic element models have potential as powerful screening tools that can facilitate or improve calibration of more complicated finite-difference and finite-element models. We demonstrate how a two-dimensional analytic element model was used to identify errors in a complex three-dimensional finite-difference model caused by incorrect specification of boundary conditions. An improved finite-difference model was developed using boundary conditions developed from a far-field analytic element model. Calibration of a revised finite-difference model was achieved using fewer zones of hydraulic conductivity and lake bed conductance than the original finite-difference model. Calibration statistics were also improved in that simulated base-flows were much closer to measured values. The improved calibration is due mainly to improved specification of the boundary conditions made possible by first solving the far-field problem with an analytic element model.This paper demonstrates that analytic element models have potential as powerful screening tools that can facilitate or improve calibration of more complicated finite-difference and finite-element models. We demonstrate how a two-dimensional analytic element model was used to identify errors in a complex three-dimensional finite-difference model caused by incorrect specification of boundary conditions. An improved finite-difference model was developed using boundary conditions developed from a far-field analytic element model. Calibration of a revised finite-difference model was achieved using fewer zones of hydraulic conductivity and lake bed conductance than the original finite-difference model. Calibration statistics were also improved in that simulated base-flows were much closer to measured values. The improved calibration is due mainly to improved specification of the boundary conditions made possible by first solving the far-field problem with an analytic element model.

The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

ERIC Educational Resources Information Center

Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

2010-01-01

Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

Data Visualization: An Exploratory Study into the Software Tools Used by Businesses

ERIC Educational Resources Information Center

Diamond, Michael; Mattia, Angela

2017-01-01

Data visualization is a key component to business and data analytics, allowing analysts in businesses to create tools such as dashboards for business executives. Various software packages allow businesses to create these tools in order to manipulate data for making informed business decisions. The focus is to examine what skills employers are…

Data Visualization: An Exploratory Study into the Software Tools Used by Businesses

ERIC Educational Resources Information Center

Diamond, Michael; Mattia, Angela

2015-01-01

Data visualization is a key component to business and data analytics, allowing analysts in businesses to create tools such as dashboards for business executives. Various software packages allow businesses to create these tools in order to manipulate data for making informed business decisions. The focus is to examine what skills employers are…

Process monitoring and visualization solutions for hot-melt extrusion: a review.

PubMed

Saerens, Lien; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

2014-02-01

Hot-melt extrusion (HME) is applied as a continuous pharmaceutical manufacturing process for the production of a variety of dosage forms and formulations. To ensure the continuity of this process, the quality of the extrudates must be assessed continuously during manufacturing. The objective of this review is to provide an overview and evaluation of the available process analytical techniques which can be applied in hot-melt extrusion. Pharmaceutical extruders are equipped with traditional (univariate) process monitoring tools, observing barrel and die temperatures, throughput, screw speed, torque, drive amperage, melt pressure and melt temperature. The relevance of several spectroscopic process analytical techniques for monitoring and control of pharmaceutical HME has been explored recently. Nevertheless, many other sensors visualizing HME and measuring diverse critical product and process parameters with potential use in pharmaceutical extrusion are available, and were thoroughly studied in polymer extrusion. The implementation of process analytical tools in HME serves two purposes: (1) improving process understanding by monitoring and visualizing the material behaviour and (2) monitoring and analysing critical product and process parameters for process control, allowing to maintain a desired process state and guaranteeing the quality of the end product. This review is the first to provide an evaluation of the process analytical tools applied for pharmaceutical HME monitoring and control, and discusses techniques that have been used in polymer extrusion having potential for monitoring and control of pharmaceutical HME. © 2013 Royal Pharmaceutical Society.

METABOLOMICS AS A DIAGNOSTIC TOOL FOR SMALL FISH TOXICOLOGY RESEARCH

EPA Science Inventory

Metabolomics involves the application of advanced analytical and statistical tools to profile changes in levels of endogenous metabolites in tissues and biofluids resulting from disease onset or stress. While certain metabolites are being specifically targeted in these studies, w...

Analytical tools for identifying bicycle route suitability, coverage, and continuity.

DOT National Transportation Integrated Search

2012-05-01

This report presents new tools created to assess bicycle suitability using geographic information systems (GIS). Bicycle suitability is a rating of how appropriate a roadway is for bicycle travel based on attributes of the roadway, such as vehi...

An Integrated Multivariable Visualization Tool for Marine Sanctuary Climate Assessments

NASA Astrophysics Data System (ADS)

Shein, K. A.; Johnston, S.; Stachniewicz, J.; Duncan, B.; Cecil, D.; Ansari, S.; Urzen, M.

2012-12-01

The comprehensive development and use of ecological climate impact assessments by ecosystem managers can be limited by data access and visualization methods that require a priori knowledge about the various large and complex climate data products necessary to those impact assessments. In addition, it can be difficult to geographically and temporally integrate climate and ecological data to fully characterize climate-driven ecological impacts. To address these considerations, we have enhanced and extended the functionality of the NOAA National Climatic Data Center's Weather and Climate Toolkit (WCT). The WCT is a freely available Java-based tool designed to access and display NCDC's georeferenced climate data products (e.g., satellite, radar, and reanalysis gridded data). However, the WCT requires users already know how to obtain the data products, which products are preferred for a given variable, and which products are most relevant to their needs. Developed in cooperation with research and management customers at the Gulf of the Farallones National Marine Sanctuary, the Integrated Marine Protected Area Climate Tools (IMPACT) modification to the WCT simplifies or eliminates these requirements, while simultaneously adding core analytical functionality to the tool. Designed for use by marine ecosystem managers, WCT-IMPACT accesses a suite of data products that have been identified as relevant to marine ecosystem climate impact assessments, such as NOAA's Climate Data Records. WCT-IMPACT regularly crops these products to the geographic boundaries of each included marine protected area (MPA), and those clipped regions are processed to produce MPA-specific analytics. The tool retrieves the most appropriate data files based on the user selection of MPA, environmental variable(s), and time frame. Once the data are loaded, they may be visualized, explored, analyzed, and exported to other formats (e.g., Google KML). Multiple variables may be simultaneously visualized using a 4-panel display and compared via a variety of statistics such as difference, probability, or correlation maps.; NCDC's Weather and Climate Toolkit image of NARR-A non-convective cloud cover (%) over the Pacific Coast on June 17, 2012 at 09:00 GMT.

Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions.

PubMed

Rong, Y; Padron, A V; Hagerty, K J; Nelson, N; Chi, S; Keyhani, N O; Katz, J; Datta, S P A; Gomes, C; McLamore, E S

2018-04-30

Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Protein-ligand binding sensors have enormous potential for biosensing, but achieving accuracy in complex solutions is a major challenge. There is a need for simple post hoc analytical tools that are not computationally expensive, yet provide near real time feedback on data derived from impedance spectra. Here, we show the use of a simple, open source support vector machine learning algorithm for analyzing impedimetric data in lieu of using equivalent circuit analysis. We demonstrate two different protein-based biosensors to show that the tool can be used for various applications. We conclude with a mobile phone-based demonstration focused on the measurement of acetone, an important biomarker related to the onset of diabetic ketoacidosis. In all conditions tested, the open source classifier was capable of performing as well as, or better, than the equivalent circuit analysis for characterizing weak/transient interactions between a model ligand (acetone) and a small chemosensory protein derived from the tsetse fly. In addition, the tool has a low computational requirement, facilitating use for mobile acquisition systems such as mobile phones. The protocol is deployed through Jupyter notebook (an open source computing environment available for mobile phone, tablet or computer use) and the code was written in Python. For each of the applications, we provide step-by-step instructions in English, Spanish, Mandarin and Portuguese to facilitate widespread use. All codes were based on scikit-learn, an open source software machine learning library in the Python language, and were processed in Jupyter notebook, an open-source web application for Python. The tool can easily be integrated with the mobile biosensor equipment for rapid detection, facilitating use by a broad range of impedimetric biosensor users. This post hoc analysis tool can serve as a launchpad for the convergence of nanobiosensors in planetary health monitoring applications based on mobile phone hardware.

Surrogate matrix and surrogate analyte approaches for definitive quantitation of endogenous biomolecules.

PubMed

Jones, Barry R; Schultz, Gary A; Eckstein, James A; Ackermann, Bradley L

2012-10-01

Quantitation of biomarkers by LC-MS/MS is complicated by the presence of endogenous analytes. This challenge is most commonly overcome by calibration using an authentic standard spiked into a surrogate matrix devoid of the target analyte. A second approach involves use of a stable-isotope-labeled standard as a surrogate analyte to allow calibration in the actual biological matrix. For both methods, parallelism between calibration standards and the target analyte in biological matrix must be demonstrated in order to ensure accurate quantitation. In this communication, the surrogate matrix and surrogate analyte approaches are compared for the analysis of five amino acids in human plasma: alanine, valine, methionine, leucine and isoleucine. In addition, methodology based on standard addition is introduced, which enables a robust examination of parallelism in both surrogate analyte and surrogate matrix methods prior to formal validation. Results from additional assays are presented to introduce the standard-addition methodology and to highlight the strengths and weaknesses of each approach. For the analysis of amino acids in human plasma, comparable precision and accuracy were obtained by the surrogate matrix and surrogate analyte methods. Both assays were well within tolerances prescribed by regulatory guidance for validation of xenobiotic assays. When stable-isotope-labeled standards are readily available, the surrogate analyte approach allows for facile method development. By comparison, the surrogate matrix method requires greater up-front method development; however, this deficit is offset by the long-term advantage of simplified sample analysis.

New procedure of quantitative mapping of Ti and Al released from dental implant and Mg, Ca, Fe, Zn, Cu, Mn as physiological elements in oral mucosa by LA-ICP-MS.

PubMed

Sajnóg, Adam; Hanć, Anetta; Koczorowski, Ryszard; Barałkiewicz, Danuta

2017-12-01

A new procedure for determination of elements derived from titanium implants and physiological elements in soft tissues by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is presented. The analytical procedure was developed which involved preparation of in-house matrix matched solid standards with analyte addition based on certified reference material (CRM) MODAS-4 Cormorant Tissue. Addition of gelatin, serving as a binding agent, essentially improved physical properties of standards. Performance of the analytical method was assayed and validated by calculating parameters like precision, detection limits, trueness and recovery of analyte addition using additional CRM - ERM-BB184 Bovine Muscle. Analyte addition was additionally confirmed by microwave digestion of solid standards and analysis by solution nebulization ICP-MS. The detection limits are in range 1.8μgg -1 to 450μgg -1 for Mn and Ca respectively. The precision values range from 7.3% to 42% for Al and Zn respectively. The estimated recoveries of analyte addition line within scope of 83%-153% for Mn and Cu respectively. Oral mucosa samples taken from patients treated with titanium dental implants were examined using developed analytical method. Standards and tissue samples were cryocut into 30µm thin sections. LA-ICP-MS allowed to obtain two-dimensional maps of distribution of elements in tested samples which revealed high content of Ti and Al derived from implants. Photographs from optical microscope displayed numerous particles with µm size in oral mucosa samples which suggests that they are residues from implantation procedure. Copyright © 2017 Elsevier B.V. All rights reserved.

Analytics to Better Interpret and Use Large Amounts of Heterogeneous Data

NASA Astrophysics Data System (ADS)

Mathews, T. J.; Baskin, W. E.; Rinsland, P. L.

2014-12-01

Data scientists at NASA's Atmospheric Science Data Center (ASDC) are seasoned software application developers who have worked with the creation, archival, and distribution of large datasets (multiple terabytes and larger). In order for ASDC data scientists to effectively implement the most efficient processes for cataloging and organizing data access applications, they must be intimately familiar with data contained in the datasets with which they are working. Key technologies that are critical components to the background of ASDC data scientists include: large RBMSs (relational database management systems) and NoSQL databases; web services; service-oriented architectures; structured and unstructured data access; as well as processing algorithms. However, as prices of data storage and processing decrease, sources of data increase, and technologies advance - granting more people to access to data at real or near-real time - data scientists are being pressured to accelerate their ability to identify and analyze vast amounts of data. With existing tools this is becoming exceedingly more challenging to accomplish. For example, NASA Earth Science Data and Information System (ESDIS) alone grew from having just over 4PBs of data in 2009 to nearly 6PBs of data in 2011. This amount then increased to roughly10PBs of data in 2013. With data from at least ten new missions to be added to the ESDIS holdings by 2017, the current volume will continue to grow exponentially and drive the need to be able to analyze more data even faster. Though there are many highly efficient, off-the-shelf analytics tools available, these tools mainly cater towards business data, which is predominantly unstructured. Inadvertently, there are very few known analytics tools that interface well to archived Earth science data, which is predominantly heterogeneous and structured. This presentation will identify use cases for data analytics from an Earth science perspective in order to begin to identify specific tools that may be able to address those challenges.

Benefits and limitations of using decision analytic tools to assess uncertainty and prioritize Landscape Conservation Cooperative information needs

USGS Publications Warehouse

Post van der Burg, Max; Cullinane Thomas, Catherine; Holcombe, Tracy R.; Nelson, Richard D.

2016-01-01

The Landscape Conservation Cooperatives (LCCs) are a network of partnerships throughout North America that are tasked with integrating science and management to support more effective delivery of conservation at a landscape scale. In order to achieve this integration, some LCCs have adopted the approach of providing their partners with better scientific information in an effort to facilitate more effective and coordinated conservation decisions. Taking this approach has led many LCCs to begin funding research to provide the information for improved decision making. To ensure that funding goes to research projects with the highest likelihood of leading to more integrated broad scale conservation, some LCCs have also developed approaches for prioritizing which information needs will be of most benefit to their partnerships. We describe two case studies in which decision analytic tools were used to quantitatively assess the relative importance of information for decisions made by partners in the Plains and Prairie Potholes LCC. The results of the case studies point toward a few valuable lessons in terms of using these tools with LCCs. Decision analytic tools tend to help shift focus away from research oriented discussions and toward discussions about how information is used in making better decisions. However, many technical experts do not have enough knowledge about decision making contexts to fully inform the latter type of discussion. When assessed in the right decision context, however, decision analyses can point out where uncertainties actually affect optimal decisions and where they do not. This helps technical experts understand that not all research is valuable in improving decision making. But perhaps most importantly, our results suggest that decision analytic tools may be more useful for LCCs as way of developing integrated objectives for coordinating partner decisions across the landscape, rather than simply ranking research priorities.

An overview of city analytics

PubMed Central

Higham, Desmond J.; Batty, Michael; Bettencourt, Luís M. A.; Greetham, Danica Vukadinović; Grindrod, Peter

2017-01-01

We introduce the 14 articles in the Royal Society Open Science themed issue on City Analytics. To provide a high-level, strategic, overview, we summarize the topics addressed and the analytical tools deployed. We then give a more detailed account of the individual contributions. Our overall aims are (i) to highlight exciting advances in this emerging, interdisciplinary field, (ii) to encourage further activity and (iii) to emphasize the variety of new, public-domain, datasets that are available to researchers. PMID:28386454

The MCNP6 Analytic Criticality Benchmark Suite

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

Brown, Forrest B.

2016-06-16

Analytical benchmarks provide an invaluable tool for verifying computer codes used to simulate neutron transport. Several collections of analytical benchmark problems [1-4] are used routinely in the verification of production Monte Carlo codes such as MCNP® [5,6]. Verification of a computer code is a necessary prerequisite to the more complex validation process. The verification process confirms that a code performs its intended functions correctly. The validation process involves determining the absolute accuracy of code results vs. nature. In typical validations, results are computed for a set of benchmark experiments using a particular methodology (code, cross-section data with uncertainties, and modeling)more » and compared to the measured results from the set of benchmark experiments. The validation process determines bias, bias uncertainty, and possibly additional margins. Verification is generally performed by the code developers, while validation is generally performed by code users for a particular application space. The VERIFICATION_KEFF suite of criticality problems [1,2] was originally a set of 75 criticality problems found in the literature for which exact analytical solutions are available. Even though the spatial and energy detail is necessarily limited in analytical benchmarks, typically to a few regions or energy groups, the exact solutions obtained can be used to verify that the basic algorithms, mathematics, and methods used in complex production codes perform correctly. The present work has focused on revisiting this benchmark suite. A thorough review of the problems resulted in discarding some of them as not suitable for MCNP benchmarking. For the remaining problems, many of them were reformulated to permit execution in either multigroup mode or in the normal continuous-energy mode for MCNP. Execution of the benchmarks in continuous-energy mode provides a significant advance to MCNP verification methods.« less

Surface-enhanced Raman spectroscopy for the detection of pathogenic DNA and protein in foods

NASA Astrophysics Data System (ADS)

Chowdhury, Mustafa H.; Atkinson, Brad; Good, Theresa; Cote, Gerard L.

2003-07-01

Traditional Raman spectroscopy while extremely sensitive to structure and conformation, is an ineffective tool for the detection of bioanalytes at the sub milimolar level. Surface Enhanced Raman Spectroscopy (SERS) is a technique developed more recently that has been used with applaudable success to enhance the Raman cross-section of a molecule by factors of 106 to 1014. This technique can be exploited in a nanoscale biosensor for the detection of pathogenic proteins and DNA in foods by using a biorecognition molecule to bring a target analyte in close proximity to the mental surface. This is expected to produce a SERS signal of the target analyte, thus making it possible to easily discriminate between the target analyte and possible confounders. In order for the sensor to be effective, the Raman spectra of the target analyte would have to be distinct from that of the biorecognition molecule, as both would be in close proximity to the metal surface and thus be subjected to the SERS effect. In our preliminary studies we have successfully used citrate reduced silver colloidal particles to obtain unique SERS spectra of α-helical and β-sheet bovine serum albumin (BSA) that served as models of an α helical antiobiody (biorecognition element) and a β-sheet target protein (pathogenic prion). In addition, the unique SERS spectra of double stranded and single stranded DNA were also obtained where the single stranded DNA served as the model for the biorecognition element and the double stranded DNA served as themodel for the DNA probe/target hybrid. This provides a confirmation of the feasibility of the method which opens opportunities for potentially wide spread applications in the detection of food pathogens, biowarefare agents, andother bio-analytes.

Applications of surface analytical techniques in Earth Sciences

NASA Astrophysics Data System (ADS)

Qian, Gujie; Li, Yubiao; Gerson, Andrea R.

2015-03-01

This review covers a wide range of surface analytical techniques: X-ray photoelectron spectroscopy (XPS), scanning photoelectron microscopy (SPEM), photoemission electron microscopy (PEEM), dynamic and static secondary ion mass spectroscopy (SIMS), electron backscatter diffraction (EBSD), atomic force microscopy (AFM). Others that are relatively less widely used but are also important to the Earth Sciences are also included: Auger electron spectroscopy (AES), low energy electron diffraction (LEED) and scanning tunnelling microscopy (STM). All these techniques probe only the very top sample surface layers (sub-nm to several tens of nm). In addition, we also present several other techniques i.e. Raman microspectroscopy, reflection infrared (IR) microspectroscopy and quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) that penetrate deeper into the sample, up to several μm, as all of them are fundamental analytical tools for the Earth Sciences. Grazing incidence synchrotron techniques, sensitive to surface measurements, are also briefly introduced at the end of this review. (Scanning) transmission electron microscopy (TEM/STEM) is a special case that can be applied to characterisation of mineralogical and geological sample surfaces. Since TEM/STEM is such an important technique for Earth Scientists, we have also included it to draw attention to the capability of TEM/STEM applied as a surface-equivalent tool. While this review presents most of the important techniques for the Earth Sciences, it is not an all-inclusive bibliography of those analytical techniques. Instead, for each technique that is discussed, we first give a very brief introduction about its principle and background, followed by a short section on approaches to sample preparation that are important for researchers to appreciate prior to the actual sample analysis. We then use examples from publications (and also some of our known unpublished results) within the Earth Sciences to show how each technique is applied and used to obtain specific information and to resolve real problems, which forms the central theme of this review. Although this review focuses on applications of these techniques to study mineralogical and geological samples, we also anticipate that researchers from other research areas such as Material and Environmental Sciences may benefit from this review.

Analytic Simulation of the Elastic Waves Propagation in the Neighborhood of Fluid Filled Wells with Monopole Sources

NASA Astrophysics Data System (ADS)

Ávila-Carrera, R.; Sánchez-Sesma, F. J.; Spurlin, James H.; Valle-Molina, C.; Rodríguez-Castellanos, A.

2014-09-01

An analytic formulation to understand the scattering, diffraction and attenuation of elastic waves at the neighborhood of fluid filled wells is presented. An important, and not widely exploited, technique to carefully investigate the wave propagation in exploration wells is the logging of sonic waveforms. Fundamental decisions and production planning in petroleum reservoirs are made by interpretation of such recordings. Nowadays, geophysicists and engineers face problems related to the acquisition and interpretation under complex conditions associated with conducting open-hole measurements. A crucial problem that directly affects the response of sonic logs is the eccentricity of the measuring tool with respect to the center of the borehole. Even with the employment of centralizers, this simple variation, dramatically changes the physical conditions on the wave propagation around the well. Recent works in the numerical field reported advanced studies in modeling and simulation of acoustic wave propagation around wells, including complex heterogeneities and anisotropy. However, no analytical efforts have been made to formally understand the wireline sonic logging measurements acquired with borehole-eccentered tools. In this paper, the Graf's addition theorem was used to describe monopole sources in terms of solutions of the wave equation. The formulation was developed from the three-dimensional discrete wave-number method in the frequency domain. The cylindrical Bessel functions of the third kind and order zero were re-derived to obtain a simplified set of equations projected into a bi-dimensional plane-space for displacements and stresses. This new and condensed analytic formulation allows the straightforward calculation of all converted modes and their visualization in the time domain via Fourier synthesis. The main aim was to obtain spectral surfaces of transfer functions and synthetic seismograms that might be useful to understand the wave motion produced by the eccentricity of the source and explain in detail the new arising borehole propagation modes. Finally, time histories and amplitude spectra for relevant examples are presented and the validation of time traces using the spectral element method is reported.

Sigma Metrics Across the Total Testing Process.

PubMed

Charuruks, Navapun

2017-03-01

Laboratory quality control has been developed for several decades to ensure patients' safety, from a statistical quality control focus on the analytical phase to total laboratory processes. The sigma concept provides a convenient way to quantify the number of errors in extra-analytical and analytical phases through the defect per million and sigma metric equation. Participation in a sigma verification program can be a convenient way to monitor analytical performance continuous quality improvement. Improvement of sigma-scale performance has been shown from our data. New tools and techniques for integration are needed. Copyright © 2016 Elsevier Inc. All rights reserved.

Light aircraft crash safety program

NASA Technical Reports Server (NTRS)

Thomson, R. G.; Hayduk, R. J.

1974-01-01

NASA is embarked upon research and development tasks aimed at providing the general aviation industry with a reliable crashworthy airframe design technology. The goals of the NASA program are: reliable analytical techniques for predicting the nonlinear behavior of structures; significant design improvements of airframes; and simulated full-scale crash test data. The analytical tools will include both simplified procedures for estimating energy absorption characteristics and more complex computer programs for analysis of general airframe structures under crash loading conditions. The analytical techniques being developed both in-house and under contract are described, and a comparison of some analytical predictions with experimental results is shown.

Patent databases and analytical tools for space technology commercialization (Part 2)

NASA Astrophysics Data System (ADS)

Hulsey, William N., III

2002-07-01

A shift in the space industry has occurred that requires technology developers to understand the basics of the intellectual property laws; Global harmonization facilitates this understanding; internet-based tools enable knowledge of these rights and the facts affecting them.

Geospatial methods and data analysis for assessing distribution of grazing livestock

USDA-ARS?s Scientific Manuscript database

Free-ranging livestock research must begin with a well conceived problem statement and employ appropriate data acquisition tools and analytical techniques to accomplish the research objective. These requirements are especially critical in addressing animal distribution. Tools and statistics used t...

Integration of bus stop counts data with census data for improving bus service.

DOT National Transportation Integrated Search

2016-04-01

This research project produced an open source transit market data visualization and analysis tool suite, : The Bus Transit Market Analyst (BTMA), which contains user-friendly GIS mapping and data : analytics tools, and state-of-the-art transit demand...

Applicability of bioanalysis of multiple analytes in drug discovery and development: review of select case studies including assay development considerations.

PubMed

Srinivas, Nuggehally R

2006-05-01

The development of sound bioanalytical method(s) is of paramount importance during the process of drug discovery and development culminating in a marketing approval. Although the bioanalytical procedure(s) originally developed during the discovery stage may not necessarily be fit to support the drug development scenario, they may be suitably modified and validated, as deemed necessary. Several reviews have appeared over the years describing analytical approaches including various techniques, detection systems, automation tools that are available for an effective separation, enhanced selectivity and sensitivity for quantitation of many analytes. The intention of this review is to cover various key areas where analytical method development becomes necessary during different stages of drug discovery research and development process. The key areas covered in this article with relevant case studies include: (a) simultaneous assay for parent compound and metabolites that are purported to display pharmacological activity; (b) bioanalytical procedures for determination of multiple drugs in combating a disease; (c) analytical measurement of chirality aspects in the pharmacokinetics, metabolism and biotransformation investigations; (d) drug monitoring for therapeutic benefits and/or occupational hazard; (e) analysis of drugs from complex and/or less frequently used matrices; (f) analytical determination during in vitro experiments (metabolism and permeability related) and in situ intestinal perfusion experiments; (g) determination of a major metabolite as a surrogate for the parent molecule; (h) analytical approaches for universal determination of CYP450 probe substrates and metabolites; (i) analytical applicability to prodrug evaluations-simultaneous determination of prodrug, parent and metabolites; (j) quantitative determination of parent compound and/or phase II metabolite(s) via direct or indirect approaches; (k) applicability in analysis of multiple compounds in select disease areas and/or in clinically important drug-drug interaction studies. A tabular representation of select examples of analysis is provided covering areas of separation conditions, validation aspects and applicable conclusion. A limited discussion is provided on relevant aspects of the need for developing bioanalytical procedures for speedy drug discovery and development. Additionally, some key elements such as internal standard selection, likely issues of mass detection, matrix effect, chiral aspects etc. are provided for consideration during method development.

Let's Talk Learning Analytics: A Framework for Implementation in Relation to Student Retention

ERIC Educational Resources Information Center

West, Deborah; Heath, David; Huijser, Henk

2016-01-01

This paper presents a dialogical tool for the advancement of learning analytics implementation for student retention in Higher Education institutions. The framework was developed as an outcome of a project commissioned and funded by the Australian Government's "Office for Learning and Teaching". The project took a mixed-method approach…

Making Sense of Game-Based User Data: Learning Analytics in Applied Games

ERIC Educational Resources Information Center

Steiner, Christina M.; Kickmeier-Rus, Michael D.; Albert, Dietrich

2015-01-01

Digital learning games are useful educational tools with high motivational potential. With the application of games for instruction there comes the need of acknowledging learning game experiences also in the context of educational assessment. Learning analytics provides new opportunities for supporting assessment in and of educational games. We…

Gear Spline Coupling Program

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

Guo, Yi; Errichello, Robert

2013-08-29

An analytical model is developed to evaluate the design of a spline coupling. For a given torque and shaft misalignment, the model calculates the number of teeth in contact, tooth loads, stiffnesses, stresses, and safety factors. The analytic model provides essential spline coupling design and modeling information and could be easily integrated into gearbox design and simulation tools.

Challenges of Using Learning Analytics Techniques to Support Mobile Learning

ERIC Educational Resources Information Center

Arrigo, Marco; Fulantelli, Giovanni; Taibi, Davide

2015-01-01

Evaluation of Mobile Learning remains an open research issue, especially as regards the activities that take place outside the classroom. In this context, Learning Analytics can provide answers, and offer the appropriate tools to enhance Mobile Learning experiences. In this poster we introduce a task-interaction framework, using learning analytics…

A Simpli ed, General Approach to Simulating from Multivariate Copula Functions

Treesearch

Barry Goodwin

2012-01-01

Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses \\probability{...

Design and Implementation of a Learning Analytics Toolkit for Teachers

ERIC Educational Resources Information Center

Dyckhoff, Anna Lea; Zielke, Dennis; Bultmann, Mareike; Chatti, Mohamed Amine; Schroeder, Ulrik

2012-01-01

Learning Analytics can provide powerful tools for teachers in order to support them in the iterative process of improving the effectiveness of their courses and to collaterally enhance their students' performance. In this paper, we present the theoretical background, design, implementation, and evaluation details of eLAT, a Learning Analytics…

An introduction to joint research by the USEPA and USGS on contaminants of emerging concern in source and treated drinking waters of the United States

EPA Science Inventory

Improvements in analytical methodology have allowed low-level detection of an ever increasing number of pharmaceuticals, personal care products, hormones, pathogens and other contaminants of emerging concern (CECs). The use of these improved analytical tools has allowed researche...

Evaluating the Development of Science Research Skills in Work-Integrated Learning through the Use of Workplace Science Tools

ERIC Educational Resources Information Center

McCurdy, Susan M.; Zegwaard, Karsten E.; Dalgety, Jacinta

2013-01-01

Concept understanding, the development of analytical skills and a research mind set are explored through the use of academic tools common in a tertiary science education and relevant work-integrated learning (WIL) experiences. The use and development of the tools; laboratory book, technical report, and literature review are examined by way of…

Survey of Network Visualization Tools

DTIC Science & Technology

2007-12-01

Dimensionality • 2D Comments: Deployment Type: • Components for tool building • Standalone Tool OS: • Windows Extensibility • ActiveX ...Visual Basic Comments: Interoperability Daisy is fully compliant with Microsoft’s ActiveX , therefore, other Windows based programs can...other functions that improve analytic decision making. Available in ActiveX , C++, Java, and .NET editions. • Tom Sawyer Visualization: Enables you to

Analytical Design Package (ADP2): A computer aided engineering tool for aircraft transparency design

NASA Technical Reports Server (NTRS)

Wuerer, J. E.; Gran, M.; Held, T. W.

1994-01-01

The Analytical Design Package (ADP2) is being developed as a part of the Air Force Frameless Transparency Program (FTP). ADP2 is an integrated design tool consisting of existing analysis codes and Computer Aided Engineering (CAE) software. The objective of the ADP2 is to develop and confirm an integrated design methodology for frameless transparencies, related aircraft interfaces, and their corresponding tooling. The application of this methodology will generate high confidence for achieving a qualified part prior to mold fabrication. ADP2 is a customized integration of analysis codes, CAE software, and material databases. The primary CAE integration tool for the ADP2 is P3/PATRAN, a commercial-off-the-shelf (COTS) software tool. The open architecture of P3/PATRAN allows customized installations with different applications modules for specific site requirements. Integration of material databases allows the engineer to select a material, and those material properties are automatically called into the relevant analysis code. The ADP2 materials database will be composed of four independent schemas: CAE Design, Processing, Testing, and Logistics Support. The design of ADP2 places major emphasis on the seamless integration of CAE and analysis modules with a single intuitive graphical interface. This tool is being designed to serve and be used by an entire project team, i.e., analysts, designers, materials experts, and managers. The final version of the software will be delivered to the Air Force in Jan. 1994. The Analytical Design Package (ADP2) will then be ready for transfer to industry. The package will be capable of a wide range of design and manufacturing applications.

Modification and validation of an analytical source model for external beam radiotherapy Monte Carlo dose calculations

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

Davidson, Scott E., E-mail: sedavids@utmb.edu

Purpose: A dose calculation tool, which combines the accuracy of the dose planning method (DPM) Monte Carlo code and the versatility of a practical analytical multisource model, which was previously reported has been improved and validated for the Varian 6 and 10 MV linear accelerators (linacs). The calculation tool can be used to calculate doses in advanced clinical application studies. One shortcoming of current clinical trials that report dose from patient plans is the lack of a standardized dose calculation methodology. Because commercial treatment planning systems (TPSs) have their own dose calculation algorithms and the clinical trial participant who usesmore » these systems is responsible for commissioning the beam model, variation exists in the reported calculated dose distributions. Today’s modern linac is manufactured to tight specifications so that variability within a linac model is quite low. The expectation is that a single dose calculation tool for a specific linac model can be used to accurately recalculate dose from patient plans that have been submitted to the clinical trial community from any institution. The calculation tool would provide for a more meaningful outcome analysis. Methods: The analytical source model was described by a primary point source, a secondary extra-focal source, and a contaminant electron source. Off-axis energy softening and fluence effects were also included. The additions of hyperbolic functions have been incorporated into the model to correct for the changes in output and in electron contamination with field size. A multileaf collimator (MLC) model is included to facilitate phantom and patient dose calculations. An offset to the MLC leaf positions was used to correct for the rudimentary assumed primary point source. Results: Dose calculations of the depth dose and profiles for field sizes 4 × 4 to 40 × 40 cm agree with measurement within 2% of the maximum dose or 2 mm distance to agreement (DTA) for 95% of the data points tested. The model was capable of predicting the depth of the maximum dose within 1 mm. Anthropomorphic phantom benchmark testing of modulated and patterned MLCs treatment plans showed agreement to measurement within 3% in target regions using thermoluminescent dosimeters (TLD). Using radiochromic film normalized to TLD, a gamma criteria of 3% of maximum dose and 2 mm DTA was applied with a pass rate of least 85% in the high dose, high gradient, and low dose regions. Finally, recalculations of patient plans using DPM showed good agreement relative to a commercial TPS when comparing dose volume histograms and 2D dose distributions. Conclusions: A unique analytical source model coupled to the dose planning method Monte Carlo dose calculation code has been modified and validated using basic beam data and anthropomorphic phantom measurement. While this tool can be applied in general use for a particular linac model, specifically it was developed to provide a singular methodology to independently assess treatment plan dose distributions from those clinical institutions participating in National Cancer Institute trials.« less

Platform for Automated Real-Time High Performance Analytics on Medical Image Data.

PubMed

Allen, William J; Gabr, Refaat E; Tefera, Getaneh B; Pednekar, Amol S; Vaughn, Matthew W; Narayana, Ponnada A

2018-03-01

Biomedical data are quickly growing in volume and in variety, providing clinicians an opportunity for better clinical decision support. Here, we demonstrate a robust platform that uses software automation and high performance computing (HPC) resources to achieve real-time analytics of clinical data, specifically magnetic resonance imaging (MRI) data. We used the Agave application programming interface to facilitate communication, data transfer, and job control between an MRI scanner and an off-site HPC resource. In this use case, Agave executed the graphical pipeline tool GRAphical Pipeline Environment (GRAPE) to perform automated, real-time, quantitative analysis of MRI scans. Same-session image processing will open the door for adaptive scanning and real-time quality control, potentially accelerating the discovery of pathologies and minimizing patient callbacks. We envision this platform can be adapted to other medical instruments, HPC resources, and analytics tools.

Moscow Test Well, INEL Oversight Program: Aqueous geochemistry

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

McCurry, M.; Fromm, J.; Welhan, J.

1992-09-29

This report presents a summary and interpretation of data gathered during sampling of the Moscow Test Well at Moscow, Idaho during April and May of 1992. The principal objectives of this chemical survey were to validate sampling procedures with a new straddle packer sampling tool in a previously hydrologically well characterized and simple sampling environment, and to compare analytical results from two independent labs for reproducibility of analytical results. Analytes included a wide range of metals, anions, nutrients, BNA`s, and VOC`s. Secondary objectives included analyzing of waters from a large distilled water tank (utilized for all field laboratory purposes asmore » ``pure`` stock water), of water which passed through a steamer used to clean the packer, and of rinsates from the packer tool itself before it was lowered into the test well. Analyses were also obtained of blanks and spikes for data validation purposes.« less

Analytical Chemistry in the Regulatory Science of Medical Devices.

PubMed

Wang, Yi; Guan, Allan; Wickramasekara, Samanthi; Phillips, K Scott

2018-06-12

In the United States, regulatory science is the science of developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of all Food and Drug Administration-regulated products. Good regulatory science facilitates consumer access to innovative medical devices that are safe and effective throughout the Total Product Life Cycle (TPLC). Because the need to measure things is fundamental to the regulatory science of medical devices, analytical chemistry plays an important role, contributing to medical device technology in two ways: It can be an integral part of an innovative medical device (e.g., diagnostic devices), and it can be used to support medical device development throughout the TPLC. In this review, we focus on analytical chemistry as a tool for the regulatory science of medical devices. We highlight recent progress in companion diagnostics, medical devices on chips for preclinical testing, mass spectrometry for postmarket monitoring, and detection/characterization of bacterial biofilm to prevent infections.

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

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

MASS SPECTROMETRY-BASED METABOLOMICS

PubMed Central

Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D.

2007-01-01

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. PMID:16921475

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

PubMed

Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E; Mandl, René C; Almasy, Laura; Booth, Tom; Brouwer, Rachel M; Curran, Joanne E; de Zubicaray, Greig I; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T; Hong, L Elliot; Landman, Bennett A; Lemaitre, Hervé; Lopez, Lorna M; Martin, Nicholas G; McMahon, Katie L; Mitchell, Braxton D; Olvera, Rene L; Peterson, Charles P; Starr, John M; Sussmann, Jessika E; Toga, Arthur W; Wardlaw, Joanna M; Wright, Margaret J; Wright, Susan N; Bastin, Mark E; McIntosh, Andrew M; Boomsma, Dorret I; Kahn, René S; den Braber, Anouk; de Geus, Eco J C; Deary, Ian J; Hulshoff Pol, Hilleke E; Williamson, Douglas E; Blangero, John; van 't Ent, Dennis; Thompson, Paul M; Glahn, David C

2014-07-15

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. Copyright © 2014 Elsevier Inc. All rights reserved.

Newer developments on self-modeling curve resolution implementing equality and unimodality constraints.

PubMed

Beyramysoltan, Samira; Abdollahi, Hamid; Rajkó, Róbert

2014-05-27

Analytical self-modeling curve resolution (SMCR) methods resolve data sets to a range of feasible solutions using only non-negative constraints. The Lawton-Sylvestre method was the first direct method to analyze a two-component system. It was generalized as a Borgen plot for determining the feasible regions in three-component systems. It seems that a geometrical view is required for considering curve resolution methods, because the complicated (only algebraic) conceptions caused a stop in the general study of Borgen's work for 20 years. Rajkó and István revised and elucidated the principles of existing theory in SMCR methods and subsequently introduced computational geometry tools for developing an algorithm to draw Borgen plots in three-component systems. These developments are theoretical inventions and the formulations are not always able to be given in close form or regularized formalism, especially for geometric descriptions, that is why several algorithms should have been developed and provided for even the theoretical deductions and determinations. In this study, analytical SMCR methods are revised and described using simple concepts. The details of a drawing algorithm for a developmental type of Borgen plot are given. Additionally, for the first time in the literature, equality and unimodality constraints are successfully implemented in the Lawton-Sylvestre method. To this end, a new state-of-the-art procedure is proposed to impose equality constraint in Borgen plots. Two- and three-component HPLC-DAD data set were simulated and analyzed by the new analytical curve resolution methods with and without additional constraints. Detailed descriptions and explanations are given based on the obtained abstract spaces. Copyright © 2014 Elsevier B.V. All rights reserved.

Preliminary Validation of Direct Detection of Foot-And-Mouth Disease Virus within Clinical Samples Using Reverse Transcription Loop-Mediated Isothermal Amplification Coupled with a Simple Lateral Flow Device for Detection

PubMed Central

Waters, Ryan A.; Fowler, Veronica L.; Armson, Bryony; Nelson, Noel; Gloster, John; Paton, David J.; King, Donald P.

2014-01-01

Rapid, field-based diagnostic assays are desirable tools for the control of foot-and-mouth disease (FMD). Current approaches involve either; 1) Detection of FMD virus (FMDV) with immuochromatographic antigen lateral flow devices (LFD), which have relatively low analytical sensitivity, or 2) portable RT-qPCR that has high analytical sensitivity but is expensive. Loop-mediated isothermal amplification (LAMP) may provide a platform upon which to develop field based assays without these drawbacks. The objective of this study was to modify an FMDV-specific reverse transcription–LAMP (RT-LAMP) assay to enable detection of dual-labelled LAMP products with an LFD, and to evaluate simple sample processing protocols without nucleic acid extraction. The limit of detection of this assay was demonstrated to be equivalent to that of a laboratory based real-time RT-qPCR assay and to have a 10,000 fold higher analytical sensitivity than the FMDV-specific antigen LFD currently used in the field. Importantly, this study demonstrated that FMDV RNA could be detected from epithelial suspensions without the need for prior RNA extraction, utilising a rudimentary heat source for amplification. Once optimised, this RT-LAMP-LFD protocol was able to detect multiple serotypes from field epithelial samples, in addition to detecting FMDV in the air surrounding infected cattle, pigs and sheep, including pre-clinical detection. This study describes the development and evaluation of an assay format, which may be used as a future basis for rapid and low cost detection of FMDV. In addition it provides providing “proof of concept” for the future use of LAMP assays to tackle other challenging diagnostic scenarios encompassing veterinary and human health. PMID:25165973

Potential of Near-Infrared Chemical Imaging as Process Analytical Technology Tool for Continuous Freeze-Drying.

PubMed

Brouckaert, Davinia; De Meyer, Laurens; Vanbillemont, Brecht; Van Bockstal, Pieter-Jan; Lammens, Joris; Mortier, Séverine; Corver, Jos; Vervaet, Chris; Nopens, Ingmar; De Beer, Thomas

2018-04-03

Near-infrared chemical imaging (NIR-CI) is an emerging tool for process monitoring because it combines the chemical selectivity of vibrational spectroscopy with spatial information. Whereas traditional near-infrared spectroscopy is an attractive technique for water content determination and solid-state investigation of lyophilized products, chemical imaging opens up possibilities for assessing the homogeneity of these critical quality attributes (CQAs) throughout the entire product. In this contribution, we aim to evaluate NIR-CI as a process analytical technology (PAT) tool for at-line inspection of continuously freeze-dried pharmaceutical unit doses based on spin freezing. The chemical images of freeze-dried mannitol samples were resolved via multivariate curve resolution, allowing us to visualize the distribution of mannitol solid forms throughout the entire cake. Second, a mannitol-sucrose formulation was lyophilized with variable drying times for inducing changes in water content. Analyzing the corresponding chemical images via principal component analysis, vial-to-vial variations as well as within-vial inhomogeneity in water content could be detected. Furthermore, a partial least-squares regression model was constructed for quantifying the water content in each pixel of the chemical images. It was hence concluded that NIR-CI is inherently a most promising PAT tool for continuously monitoring freeze-dried samples. Although some practicalities are still to be solved, this analytical technique could be applied in-line for CQA evaluation and for detecting the drying end point.

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

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

Granderson, Jessica; Bonvini, Marco; Piette, Mary Ann

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and buildingmore » behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.« less

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark J.

1991-01-01

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

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

Steed, Chad A

Interactive data visualization leverages human visual perception and cognition to improve the accuracy and effectiveness of data analysis. When combined with automated data analytics, data visualization systems orchestrate the strengths of humans with the computational power of machines to solve problems neither approach can manage in isolation. In the intelligent transportation system domain, such systems are necessary to support decision making in large and complex data streams. In this chapter, we provide an introduction to several key topics related to the design of data visualization systems. In addition to an overview of key techniques and strategies, we will describe practicalmore » design principles. The chapter is concluded with a detailed case study involving the design of a multivariate visualization tool.« less

Advances in Mid-Infrared Spectroscopy for Chemical Analysis

NASA Astrophysics Data System (ADS)

Haas, Julian; Mizaikoff, Boris

2016-06-01

Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

Affect induction through musical sounds: an ethological perspective

PubMed Central

Huron, David

2015-01-01

How does music induce or evoke feeling states in listeners? A number of mechanisms have been proposed for how sounds induce emotions, including innate auditory responses, learned associations and mirror neuron processes. Inspired by ethology, it is suggested that the ethological concepts of signals, cues and indices offer additional analytic tools for better understanding induced affect. It is proposed that ethological concepts help explain why music is able to induce only certain emotions, why some induced emotions are similar to the displayed emotion (whereas other induced emotions differ considerably from the displayed emotion), why listeners often report feeling mixed emotions and why only some musical expressions evoke similar responses across cultures. PMID:25646521

Assessment of SOAP note evaluation tools in colleges and schools of pharmacy.

PubMed

Sando, Karen R; Skoy, Elizabeth; Bradley, Courtney; Frenzel, Jeanne; Kirwin, Jennifer; Urteaga, Elizabeth

2017-07-01

To describe current methods used to assess SOAP notes in colleges and schools of pharmacy. Members of the American Association of Colleges of Pharmacy Laboratory Instructors Special Interest Group were invited to share assessment tools for SOAP notes. Content of submissions was evaluated to characterize overall qualities and how the tools assessed subjective, objective, assessment, and plan information. Thirty-nine assessment tools from 25 schools were evaluated. Twenty-nine (74%) of the tools were rubrics and ten (26%) were checklists. All rubrics included analytic scoring elements, while two (7%) were mixed with holistic and analytic scoring elements. A majority of the rubrics (35%) used a four-item rating scale. Substantial variability existed in how tools evaluated subjective and objective sections. All tools included problem identification in the assessment section. Other assessment items included goals (82%) and rationale (69%). Seventy-seven percent assessed drug therapy; however, only 33% assessed non-drug therapy. Other plan items included education (59%) and follow-up (90%). There is a great deal of variation in the specific elements used to evaluate SOAP notes in colleges and schools of pharmacy. Improved consistency in assessment methods to evaluate SOAP notes may better prepare students to produce standardized documentation when entering practice. Copyright © 2017 Elsevier Inc. All rights reserved.

ESIP Earth Sciences Data Analytics (ESDA) Cluster - Work in Progress

NASA Technical Reports Server (NTRS)

Kempler, Steven

2015-01-01

The purpose of this poster is to promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations to better understand the cross usage of heterogeneous datasets and to provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities. Objectives Provide a forum for Academic discussions that provides ESIP members a better understanding of the various aspects of Earth Science Data Analytics Bring in guest speakers to describe external efforts, and further teach us about the broader use of Data Analytics. Perform activities that:- Compile use cases generated from specific community needs to cross analyze heterogeneous data- Compile sources of analytics tools, in particular, to satisfy the needs of the above data users- Examine gaps between needs and sources- Examine gaps between needs and community expertise- Document specific data analytics expertise needed to perform Earth science data analytics Seek graduate data analytics Data Science student internship opportunities.

Machine Learning Technologies Translates Vigilant Surveillance Satellite Big Data into Predictive Alerts for Environmental Stressors

NASA Astrophysics Data System (ADS)

Johnson, S. P.; Rohrer, M. E.

2017-12-01

The application of scientific research pertaining to satellite imaging and data processing has facilitated the development of dynamic methodologies and tools that utilize nanosatellites and analytical platforms to address the increasing scope, scale, and intensity of emerging environmental threats to national security. While the use of remotely sensed data to monitor the environment at local and global scales is not a novel proposition, the application of advances in nanosatellites and analytical platforms are capable of overcoming the data availability and accessibility barriers that have historically impeded the timely detection, identification, and monitoring of these stressors. Commercial and university-based applications of these technologies were used to identify and evaluate their capacity as security-motivated environmental monitoring tools. Presently, nanosatellites can provide consumers with 1-meter resolution imaging, frequent revisits, and customizable tasking, allowing users to define an appropriate temporal scale for high resolution data collection that meets their operational needs. Analytical platforms are capable of ingesting increasingly large and diverse volumes of data, delivering complex analyses in the form of interpretation-ready data products and solutions. The synchronous advancement of these technologies creates the capability of analytical platforms to deliver interpretable products from persistently collected high-resolution data that meet varying temporal and geographic scale requirements. In terms of emerging environmental threats, these advances translate into customizable and flexible tools that can respond to and accommodate the evolving nature of environmental stressors. This presentation will demonstrate the capability of nanosatellites and analytical platforms to provide timely, relevant, and actionable information that enables environmental analysts and stakeholders to make informed decisions regarding the prevention, intervention, and prediction of emerging environmental threats.

ANALYTICAL TOOLS INTERFACE FOR LANDSCAPE ASSESSMENTS (ATTILA) ARCVIEW EXTENTION

EPA Science Inventory

Geographic Information Systems (GIS) have become a powerful tool in the field of landscape ecology. A common application of GIS is the generation of landscape metrics, which are quantitative measurements of the status or potential health of an area (e.g. ecological region, waters...

Analytical tool for measuring emissions impact of acceleration and deceleration lanes : final report.

DOT National Transportation Integrated Search

2001-04-01

Air quality has become one of the important factors to be considered in making transportation improvement : decisions. Thus, tools are expected to help such decision-makings. On the other hand, MOBILE5 model, which : has been widely used in evaluatin...

Visualizing Qualitative Information

ERIC Educational Resources Information Center

Slone, Debra J.

2009-01-01

The abundance of qualitative data in today's society and the need to easily scrutinize, digest, and share this information calls for effective visualization and analysis tools. Yet, no existing qualitative tools have the analytic power, visual effectiveness, and universality of familiar quantitative instruments like bar charts, scatter-plots, and…

Visualizing the Geography of the Diseases of China: Western Disease Maps from Analytical Tools to Tools of Empire, Sovereignty, and Public Health Propaganda, 1878-1929.

PubMed

Hanson, Marta

2017-09-01

Argument This article analyzes for the first time the earliest western maps of diseases in China spanning fifty years from the late 1870s to the end of the 1920s. The 24 featured disease maps present a visual history of the major transformations in modern medicine from medical geography to laboratory medicine wrought on Chinese soil. These medical transformations occurred within new political formations from the Qing dynasty (1644-1911) to colonialism in East Asia (Hong Kong, Taiwan, Manchuria, Korea) and hypercolonialism within China (Tianjin, Shanghai, Amoy) as well as the new Republican Chinese nation state (1912-49). As a subgenre of persuasive graphics, physicians marshaled disease maps for various rhetorical functions within these different political contexts. Disease maps in China changed from being mostly analytical tools to functioning as tools of empire, national sovereignty, and public health propaganda legitimating new medical concepts, public health interventions, and political structures governing over human and non-human populations.

The National energy modeling system

NASA Astrophysics Data System (ADS)

The DOE uses a variety of energy and economic models to forecast energy supply and demand. It also uses a variety of more narrowly focussed analytical tools to examine energy policy options. For the purpose of the scope of this work, this set of models and analytical tools is called the National Energy Modeling System (NEMS). The NEMS is the result of many years of development of energy modeling and analysis tools, many of which were developed for different applications and under different assumptions. As such, NEMS is believed to be less than satisfactory in certain areas. For example, NEMS is difficult to keep updated and expensive to use. Various outputs are often difficult to reconcile. Products were not required to interface, but were designed to stand alone. Because different developers were involved, the inner workings of the NEMS are often not easily or fully understood. Even with these difficulties, however, NEMS comprises the best tools currently identified to deal with our global, national and regional energy modeling, and energy analysis needs.

Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

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

Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

2008-07-30

As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

Impact and Penetration Simulations for Composite Wing-like Structures

NASA Technical Reports Server (NTRS)

Knight, Norman F.

1998-01-01

The goal of this research project was to develop methodologies for the analysis of wing-like structures subjected to impact loadings. Low-speed impact causing either no damage or only minimal damage and high-speed impact causing severe laminate damage and possible penetration of the structure were to be considered during this research effort. To address this goal, an assessment of current analytical tools for impact analysis was performed. Assessment of the analytical tools for impact and penetration simulations with regard to accuracy, modeling, and damage modeling was considered as well as robustness, efficient, and usage in a wing design environment. Following a qualitative assessment, selected quantitative evaluations will be performed using the leading simulation tools. Based on this assessment, future research thrusts for impact and penetration simulation of composite wing-like structures were identified.

Shouting in the Jungle - The SETI Transmission Debate

NASA Astrophysics Data System (ADS)

Schuch, H. P.; Almar, I.

The prudence of transmitting deliberate messages from Earth into interstellar space remains controversial. Reasoned risk- benefit analysis is needed, to inform policy recommendations by such bodies as the International Academy of Astronautics SETI Permanent Study Group. As a first step, at the 2005 International Astronautical Congress in Fukuoka, we discussed the San Marino Scale, a new analytical tool for assessing transmission risk. That Scale was updated, and a revised version presented at the 2006 IAC in Valencia. We are now in a position to recommend specific improvements to the scale we proposed for quantifying terrestrial transmissions. Our intent is to make this tool better reflect the detectability and potential impact of recent and proposed messages beamed from Earth. We believe the changes proposed herein strengthen the San Marino Scale as an analytical tool, and bring us closer to its eventual adoption.

Social Web mining and exploitation for serious applications: Technosocial Predictive Analytics and related technologies for public health, environmental and national security surveillance.

PubMed

Kamel Boulos, Maged N; Sanfilippo, Antonio P; Corley, Courtney D; Wheeler, Steve

2010-10-01

This paper explores Technosocial Predictive Analytics (TPA) and related methods for Web "data mining" where users' posts and queries are garnered from Social Web ("Web 2.0") tools such as blogs, micro-blogging and social networking sites to form coherent representations of real-time health events. The paper includes a brief introduction to commonly used Social Web tools such as mashups and aggregators, and maps their exponential growth as an open architecture of participation for the masses and an emerging way to gain insight about people's collective health status of whole populations. Several health related tool examples are described and demonstrated as practical means through which health professionals might create clear location specific pictures of epidemiological data such as flu outbreaks. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Analytical quality by design: a tool for regulatory flexibility and robust analytics.

PubMed

Peraman, Ramalingam; Bhadraya, Kalva; Padmanabha Reddy, Yiragamreddy

2015-01-01

Very recently, Food and Drug Administration (FDA) has approved a few new drug applications (NDA) with regulatory flexibility for quality by design (QbD) based analytical approach. The concept of QbD applied to analytical method development is known now as AQbD (analytical quality by design). It allows the analytical method for movement within method operable design region (MODR). Unlike current methods, analytical method developed using analytical quality by design (AQbD) approach reduces the number of out-of-trend (OOT) results and out-of-specification (OOS) results due to the robustness of the method within the region. It is a current trend among pharmaceutical industry to implement analytical quality by design (AQbD) in method development process as a part of risk management, pharmaceutical development, and pharmaceutical quality system (ICH Q10). Owing to the lack explanatory reviews, this paper has been communicated to discuss different views of analytical scientists about implementation of AQbD in pharmaceutical quality system and also to correlate with product quality by design and pharmaceutical analytical technology (PAT).

Analytical Quality by Design: A Tool for Regulatory Flexibility and Robust Analytics

PubMed Central

Bhadraya, Kalva; Padmanabha Reddy, Yiragamreddy

2015-01-01

Very recently, Food and Drug Administration (FDA) has approved a few new drug applications (NDA) with regulatory flexibility for quality by design (QbD) based analytical approach. The concept of QbD applied to analytical method development is known now as AQbD (analytical quality by design). It allows the analytical method for movement within method operable design region (MODR). Unlike current methods, analytical method developed using analytical quality by design (AQbD) approach reduces the number of out-of-trend (OOT) results and out-of-specification (OOS) results due to the robustness of the method within the region. It is a current trend among pharmaceutical industry to implement analytical quality by design (AQbD) in method development process as a part of risk management, pharmaceutical development, and pharmaceutical quality system (ICH Q10). Owing to the lack explanatory reviews, this paper has been communicated to discuss different views of analytical scientists about implementation of AQbD in pharmaceutical quality system and also to correlate with product quality by design and pharmaceutical analytical technology (PAT). PMID:25722723

Geovisualization applications to examine and explore high-density and hierarchical critical infrastructure data

NASA Astrophysics Data System (ADS)

Edsall, Robert; Hembree, Harvey

2018-05-01

The geospatial research and development team in the National and Homeland Security Division at Idaho National Laboratory was tasked with providing tools to derive insight from the substantial amount of data currently available - and continuously being produced - associated with the critical infrastructure of the US. This effort is in support of the Department of Homeland Security, whose mission includes the protection of this infrastructure and the enhancement of its resilience to hazards, both natural and human. We present geovisual-analytics-based approaches for analysis of vulnerabilities and resilience of critical infrastructure, designed so that decision makers, analysts, and infrastructure owners and managers can manage risk, prepare for hazards, and direct resources before and after an incident that might result in an interruption in service. Our designs are based on iterative discussions with DHS leadership and analysts, who in turn will use these tools to explore and communicate data in partnership with utility providers, law enforcement, and emergency response and recovery organizations, among others. In most cases these partners desire summaries of large amounts of data, but increasingly, our users seek the additional capability of focusing on, for example, a specific infrastructure sector, a particular geographic region, or time period, or of examining data in a variety of generalization or aggregation levels. These needs align well with tenets of in-formation-visualization design; in this paper, selected applications among those that we have designed are described and positioned within geovisualization, geovisual analytical, and information visualization frameworks.

Fabrication of Protein Microparticles and Microcapsules with Biomolecular Tools

NASA Astrophysics Data System (ADS)

Cheung, Kwan Yee; Lai, Kwok Kei; Mak, Wing Cheung

2018-05-01

Microparticles have attracted much attention for medical, analytical and biological applications. Calcium carbonate (CaCO3) templating method with the advantages of having narrow size distribution, controlled morphology and good biocompatibility that has been widely used for the synthesis of various protein-based microparticles. Despite CaCO3 template is biocompatible, most of the conventional methods to create stable protein microparticles are mainly driven by chemical crosslink reagents which may induce potential harmful effect and remains undesirable especially for biomedical or clinical applications. In this article, we demonstrate the fabrication of protein microparticles and microcapsules with an innovative method using biomolecular tools such as enzymes and affinity molecules to trigger the assembling of protein molecules within a porous CaCO3 template followed by a template removal step. We demonstrated the enzyme-assisted fabrication of collagen microparticles triggered by transglutaminase, as well as the affinity-assisted fabrication of BSA-biotin avidin microcapsules triggered by biotin-avidin affinity interaction, respectively. Based on the different protein assemble mechanisms, the collagen microparticles appeared as a solid-structured particles, while the BSA-biotin avidin microcapsules appeared as hollow-structured morphology. The fabrication procedures are simple and robust that allows producing protein microparticles or microcapsules under mild conditions at physiological pH and temperature. In addition, the microparticle morphologies, protein compositions and the assemble mechanisms were studied. Our technology provides a facile approach to design and fabricate protein microparticles and microcapsules that are useful in the area of biomaterials, pharmaceuticals and analytical chemistry.

Surveillance of emerging drugs of abuse in Hong Kong: validation of an analytical tool.

PubMed

Tang, Magdalene H Y; Ching, C K; Tse, M L; Ng, Carol; Lee, Caroline; Chong, Y K; Wong, Watson; Mak, Tony W L

2015-04-01

To validate a locally developed chromatography-based method to monitor emerging drugs of abuse whilst performing regular drug testing in abusers. Cross-sectional study. Eleven regional hospitals, seven social service units, and a tertiary level clinical toxicology laboratory in Hong Kong. A total of 972 drug abusers and high-risk individuals were recruited from acute, rehabilitation, and high-risk settings between 1 November 2011 and 31 July 2013. A subset of the participants was of South Asian ethnicity. In total, 2000 urine or hair specimens were collected. Proof of concept that surveillance of emerging drugs of abuse can be performed whilst conducting routine drug of abuse testing in patients. The method was successfully applied to 2000 samples with three emerging drugs of abuse detected in five samples: PMMA (paramethoxymethamphetamine), TFMPP [1-(3-trifluoromethylphenyl)piperazine], and methcathinone. The method also detected conventional drugs of abuse, with codeine, methadone, heroin, methamphetamine, and ketamine being the most frequently detected drugs. Other findings included the observation that South Asians had significantly higher rates of using opiates such as heroin, methadone, and codeine; and that ketamine and cocaine had significantly higher detection rates in acute subjects compared with the rehabilitation population. This locally developed analytical method is a valid tool for simultaneous surveillance of emerging drugs of abuse and routine drug monitoring of patients at minimal additional cost and effort. Continued, proactive surveillance and early identification of emerging drugs will facilitate prompt clinical, social, and legislative management.

Experimental and Numerical Studies on Isothermal and Non-isothermal Deep Drawing of IS 513 CR3 Steel Sheets

NASA Astrophysics Data System (ADS)

Mayavan, T.; Karthikeyan, L.; Senthilkumar, V. S.

2016-11-01

The present work aims to investigate the effects of the temperature gradient developed within the tool profiles on the formability of IS 513 CR3-grade steel sheets using the cup drawing test. The deformation characteristics of steel sheets were analyzed by comparing the thicknesses in various regions of the formed cup and also the limiting drawing ratios (LDR). Finite element simulations were carried out to predict the behavior of the steel sheets in isothermal and non-isothermal forming using Abaqus/Standard 6.12-1. An analytical model created by Kim was used to validate the experimental and finite element analysis (FEA) results on identical process parameters. Both the FEA and analytical modeling results showed that formability improvement is possible in warm forming; the findings are in good agreement with the experimental results in determining the locations and values of excessive thinning. The results also indicated that formability improvement cannot be achieved by keeping the tooling temperature at the same level. The LDR increased by around 9.5% in isothermal forming and by 19% in non-isothermal forming (with the punch maintained at a lower temperature compared with the die and blank holder). In addition, the fractured surfaces of unsuccessfully formed samples were analyzed using scanning electron microscopy. Metallographic investigations confirmed that the fracture mechanism during the forming of IS 513 CR3-grade steel sheets depends on the brittleness, strain hardening value, forming temperature, and magnitude of stresses developed.

Analytical tools and isolation of TOF events

NASA Technical Reports Server (NTRS)

Wolf, H.

1974-01-01

Analytical tools are presented in two reports. The first is a probability analysis of the orbital distribution of events in relation to dust flux density observed in Pioneer 8 and 9 distributions. A distinction is drawn between asymmetries caused by random fluctuations and systematic variations, by calculating the probability of any particular asymmetry. The second article discusses particle trajectories for a repulsive force field. The force on a particle due to solar radiation pressure is directed along the particle's radius vector, from the sun, and is inversely proportional to its distance from the sun. Equations of motion which describe both solar radiation pressure and gravitational attraction are presented.

RNA "traffic lights": an analytical tool to monitor siRNA integrity.

PubMed

Holzhauser, Carolin; Liebl, Renate; Goepferich, Achim; Wagenknecht, Hans-Achim; Breunig, Miriam

2013-05-17

The combination of thiazole orange and thiazole red as an internal energy transfer-based fluorophore pair in oligonucleotides provides an outstanding analytical tool to follow DNA/RNA hybridization through a distinct fluorescence color change from red to green. Herein, we demonstrate that this concept can be applied to small interfering RNA (siRNA) to monitor RNA integrity in living cells in real time with a remarkable dynamic range and excellent contrast ratios in cellular media. Furthermore, we show that our siRNA-sensors still possess their gene silencing function toward the knockdown of enhanced green fluorescent protein in CHO-K1 cells.

T.Rex Visual Analytics for Transactional Exploration

ScienceCinema

None

2018-01-16

T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate to each other.

T.Rex Visual Analytics for Transactional Exploration

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

None

2014-07-01

T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate tomore » each other.« less

Determining GPS average performance metrics

NASA Technical Reports Server (NTRS)

Moore, G. V.

1995-01-01

Analytic and semi-analytic methods are used to show that users of the GPS constellation can expect performance variations based on their location. Specifically, performance is shown to be a function of both altitude and latitude. These results stem from the fact that the GPS constellation is itself non-uniform. For example, GPS satellites are over four times as likely to be directly over Tierra del Fuego than over Hawaii or Singapore. Inevitable performance variations due to user location occur for ground, sea, air and space GPS users. These performance variations can be studied in an average relative sense. A semi-analytic tool which symmetrically allocates GPS satellite latitude belt dwell times among longitude points is used to compute average performance metrics. These metrics include average number of GPS vehicles visible, relative average accuracies in the radial, intrack and crosstrack (or radial, north/south, east/west) directions, and relative average PDOP or GDOP. The tool can be quickly changed to incorporate various user antenna obscuration models and various GPS constellation designs. Among other applications, tool results can be used in studies to: predict locations and geometries of best/worst case performance, design GPS constellations, determine optimal user antenna location and understand performance trends among various users.

PREPARE: innovative integrated tools and platforms for radiological emergency preparedness and post-accident response in Europe.

PubMed

Raskob, Wolfgang; Schneider, Thierry; Gering, Florian; Charron, Sylvie; Zhelezniak, Mark; Andronopoulos, Spyros; Heriard-Dubreuil, Gilles; Camps, Johan

2015-04-01

The PREPARE project that started in February 2013 and will end at the beginning of 2016 aims to close gaps that have been identified in nuclear and radiological preparedness in Europe following the first evaluation of the Fukushima disaster. Among others, the project will address the review of existing operational procedures for dealing with long-lasting releases and cross-border problems in radiation monitoring and food safety and further develop missing functionalities in decision support systems (DSS) ranging from improved source-term estimation and dispersion modelling to the inclusion of hydrological pathways for European water bodies. In addition, a so-called Analytical Platform will be developed exploring the scientific and operational means to improve information collection, information exchange and the evaluation of such types of disasters. The tools developed within the project will be partly integrated into the two DSS ARGOS and RODOS. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Configurational entropy as a tool to select a physical thick brane model

NASA Astrophysics Data System (ADS)

Chinaglia, M.; Cruz, W. T.; Correa, R. A. C.; de Paula, W.; Moraes, P. H. R. S.

2018-04-01

We analize braneworld scenarios via a configurational entropy (CE) formalism. Braneworld scenarios have drawn attention mainly due to the fact that they can explain the hierarchy problem and unify the fundamental forces through a symmetry breaking procedure. Those scenarios localize matter in a (3 + 1) hypersurface, the brane, which is inserted in a higher dimensional space, the bulk. Novel analytical braneworld models, in which the warp factor depends on a free parameter n, were recently released in the literature. In this article we will provide a way to constrain this parameter through the relation between information and dynamics of a system described by the CE. We demonstrate that in some cases the CE is an important tool in order to provide the most probable physical system among all the possibilities. In addition, we show that the highest CE is correlated to a tachyonic sector of the configuration, where the solutions for the corresponding model are dynamically unstable.

Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree-Fock.

PubMed

Tamayo-Mendoza, Teresa; Kreisbeck, Christoph; Lindh, Roland; Aspuru-Guzik, Alán

2018-05-23

Automatic differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions. Thus, AD has great potential in quantum chemistry, where gradients are omnipresent but also difficult to obtain, and researchers typically spend a considerable amount of time finding suitable analytical forms when implementing derivatives. Here, we demonstrate that AD can be used to compute gradients with respect to any parameter throughout a complete quantum chemistry method. We present DiffiQult , a Hartree-Fock implementation, entirely differentiated with the use of AD tools. DiffiQult is a software package written in plain Python with minimal deviation from standard code which illustrates the capability of AD to save human effort and time in implementations of exact gradients in quantum chemistry. We leverage the obtained gradients to optimize the parameters of one-particle basis sets in the context of the floating Gaussian framework.

Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree–Fock

PubMed Central

2018-01-01

Automatic differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions. Thus, AD has great potential in quantum chemistry, where gradients are omnipresent but also difficult to obtain, and researchers typically spend a considerable amount of time finding suitable analytical forms when implementing derivatives. Here, we demonstrate that AD can be used to compute gradients with respect to any parameter throughout a complete quantum chemistry method. We present DiffiQult, a Hartree–Fock implementation, entirely differentiated with the use of AD tools. DiffiQult is a software package written in plain Python with minimal deviation from standard code which illustrates the capability of AD to save human effort and time in implementations of exact gradients in quantum chemistry. We leverage the obtained gradients to optimize the parameters of one-particle basis sets in the context of the floating Gaussian framework.

Improving the fatigue performance of porous metallic biomaterials produced by Selective Laser Melting.

PubMed

Van Hooreweder, Brecht; Apers, Yanni; Lietaert, Karel; Kruth, Jean-Pierre

2017-01-01

This paper provides new insights into the fatigue properties of porous metallic biomaterials produced by additive manufacturing. Cylindrical porous samples with diamond unit cells were produced from Ti6Al4V powder using Selective Laser Melting (SLM). After measuring all morphological and quasi-static properties, compression-compression fatigue tests were performed to determine fatigue strength and to identify important fatigue influencing factors. In a next step, post-SLM treatments were used to improve the fatigue life of these biomaterials by changing the microstructure and by reducing stress concentrators and surface roughness. In particular, the influence of stress relieving, hot isostatic pressing and chemical etching was studied. Analytical and numerical techniques were developed to calculate the maximum local tensile stress in the struts as function of the strut diameter and load. With this method, the variability in the relative density between all samples was taken into account. The local stress in the struts was then used to quantify the exact influence of the applied post-SLM treatments on the fatigue life. A significant improvement of the fatigue life was achieved. Also, the post-SLM treatments, procedures and calculation methods can be applied to different types of porous metallic structures and hence this paper provides useful tools for improving fatigue performance of metallic biomaterials. Additive Manufacturing (AM) techniques such as Selective Laser Melting (SLM) are increasingly being used for producing customized porous metallic biomaterials. These biomaterials are regularly used for biomedical implants and hence a long lifetime is required. In this paper, a set of post-built surface and heat treatments is presented that can be used to significantly improve the fatigue life of porous SLM-Ti6Al4V samples. In addition, a novel and efficient analytical local stress method was developed to accurately quantify the influence of the post-built treatments on the fatigue life. Also numerical simulation techniques were used for validation. The developed methods and techniques can be applied to other types of porous biomaterials and hence provide new and useful tools for improving and predicting the fatigue life of porous biomaterials. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments

PubMed Central

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-01-01

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. PMID:27827849

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments.

PubMed

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-11-02

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio ( m / z ) values and retention times) that serves as a reference, the tool recognizes both m / z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m / z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley.

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.

Focused and Steady-State Characteristics of Shaped Sonic Boom Signatures: Prediction and Analysis

NASA Technical Reports Server (NTRS)

Maglieri, Domenic J.; Bobbitt, Percy J.; Massey, Steven J.; Plotkin, Kenneth J.; Kandil, Osama A.; Zheng, Xudong

2011-01-01

The objective of this study is to examine the effect of flight, at off-design conditions, on the propagated sonic boom pressure signatures of a small "low-boom" supersonic aircraft. The amplification, or focusing, of the low magnitude "shaped" signatures produced by maneuvers such as the accelerations from transonic to supersonic speeds, climbs, turns, pull-up and pushovers is the concern. To analyze these effects, new and/or improved theoretical tools have been developed, in addition to the use of existing methodology. Several shaped signatures are considered in the application of these tools to the study of selected maneuvers and off-design conditions. The results of these applications are reported in this paper as well as the details of the new analytical tools. Finally, the magnitude of the focused boom problem for "low boom" supersonic aircraft designs has been more accurately quantified and potential "mitigations" suggested. In general, "shaped boom" signatures, designed for cruise flight, such as asymmetric and symmetric flat-top and initial-shock ramp waveforms retain their basic shape during transition flight. Complex and asymmetric and symmetric initial shock ramp waveforms provide lower magnitude focus boom levels than N-waves or asymmetric and symmetric flat-top signatures.

Monitoring of antisolvent crystallization of sodium scutellarein by combined FBRM-PVM-NIR.

PubMed

Liu, Xuesong; Sun, Di; Wang, Feng; Wu, Yongjiang; Chen, Yong; Wang, Longhu

2011-06-01

Antisolvent crystallization can be used as an alternative to cooling or evaporation for the separation and purification of solid product in the pharmaceutical industry. To improve the process understanding of antisolvent crystallization, the use of in-line tools is vital. In this study, the process analytical technology (PAT) tools including focused beam reflectance measurement (FBRM), particle video microscope (PVM), and near-infrared spectroscopy (NIRS) were utilized to monitor antisolvent crystallization of sodium scutellarein. FBRM was used to monitor chord count and chord length distribution of sodium scutellarein particles in the crystallizer, and PVM, as an in-line video camera, provided pictures imaging particle shape and dimension. In addition, a quantitative model of PLS was established by in-line NIRS to detect the concentration of sodium scutellarein in the solvent and good calibration statistics were obtained (r(2) = 0.976) with the residual predictive deviation value of 11.3. The discussion over sensitivities, strengths, and weaknesses of the PAT tools may be helpful in selection of suitable PAT techniques. These in-line techniques eliminate the need for sample preparation and offer a time-saving approach to understand and monitor antisolvent crystallization process. Copyright © 2011 Wiley-Liss, Inc.

ANALYTICAL TOOL INTERFACE FOR LANDSCAPE ASSESSMENTS (ATIILA): AN ARCVIEW EXTENSION FOR THE ANALYSIS OF LANDSCAPE PATTERNS, COMPOSITION, AND STRUCTURE

EPA Science Inventory

Environmental management practices are trending away from simple, local- scale assessments toward complex, multiple-stressor regional assessments. Landscape ecology provides the theory behind these assessments while geographic information systems (GIS) supply the tools to impleme...

WebMeV | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Web MeV (Multiple-experiment Viewer) is a web/cloud-based tool for genomic data analysis. Web MeV is being built to meet the challenge of exploring large public genomic data set with intuitive graphical interface providing access to state-of-the-art analytical tools.

Simple, rapid, and environmentally friendly method for the separation of isoflavones using ultra-high performance supercritical fluid chromatography.

PubMed

Wu, Wenjie; Zhang, Yuan; Wu, Hanqiu; Zhou, Weie; Cheng, Yan; Li, Hongna; Zhang, Chuanbin; Li, Lulu; Huang, Ying; Zhang, Feng

2017-07-01

Isoflavones are natural substances that exhibit hormone-like pharmacological activities. The separation of isoflavones remains an analytical challenge because of their similar structures. We show that ultra-high performance supercritical fluid chromatography can be an appropriate tool to achieve the fast separation of 12 common dietary isoflavones. Among the five tested columns the Torus DEA column was found to be the most effective column for the separation of these isoflavones. The impact of individual parameters on the retention time and separation factor was evaluated. These parameters were optimized to develop a simple, rapid, and green method for the separation of the 12 target analytes. It only took 12.91 min using gradient elution with methanol as an organic modifier and formic acid as an additive. These isoflavones were determined with limit of quantitation ranging from 0.10 to 0.50 μg/mL, which was sufficient for reliable determination of various matrixes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In-line and Real-time Monitoring of Resonant Acoustic Mixing by Near-infrared Spectroscopy Combined with Chemometric Technology for Process Analytical Technology Applications in Pharmaceutical Powder Blending Systems.

PubMed

Tanaka, Ryoma; Takahashi, Naoyuki; Nakamura, Yasuaki; Hattori, Yusuke; Ashizawa, Kazuhide; Otsuka, Makoto

2017-01-01

Resonant acoustic ® mixing (RAM) technology is a system that performs high-speed mixing by vibration through the control of acceleration and frequency. In recent years, real-time process monitoring and prediction has become of increasing interest, and process analytical technology (PAT) systems will be increasingly introduced into actual manufacturing processes. This study examined the application of PAT with the combination of RAM, near-infrared spectroscopy, and chemometric technology as a set of PAT tools for introduction into actual pharmaceutical powder blending processes. Content uniformity was based on a robust partial least squares regression (PLSR) model constructed to manage the RAM configuration parameters and the changing concentration of the components. As a result, real-time monitoring may be possible and could be successfully demonstrated for in-line real-time prediction of active pharmaceutical ingredients and other additives using chemometric technology. This system is expected to be applicable to the RAM method for the risk management of quality.

Polymers imprinted with PAH mixtures--comparing fluorescence and QCM sensors.

PubMed

Lieberzeit, Peter A; Halikias, Konstantin; Afzal, Adeel; Dickert, Franz L

2008-12-01

Molecular imprinting with binary mixtures of different polycyclic aromatic hydrocarbons (PAH) is a tool for design of chemically highly sensitive layers for detection of these analytes. Sensor responses increase by one order of magnitude compared with layers imprinted with one type of template. Detection limits, e.g. for pyrene, reach down to 30 ng L(-1) in water, as could be observed with a naphthalene and pyrene-imprinted polyurethane. Comparing sensor characteristics obtained by QCM and fluorescence reveals different saturation behaviours indicating that, first, single PAH molecules occupy the interaction centres followed by gradual excimer incorporation at higher concentrations finally leading to substantial quenching, when all accessible cavities are occupied. The plateau in the mass-sensitive measurements suggests that up to 80% of the cavities generated in the MIP are re-occupied. Displacement measurements between chrysene and pyrene revealed that for imprinted layers with very high pyrene sensitivities the signals of both PAH are additive, whereas in materials with lower pyrene uptake the two analytes replace each other in the interaction sites of the polymer.

Orbital Signature Analyzer (OSA): A spacecraft health/safety monitoring and analysis tool

NASA Technical Reports Server (NTRS)

Weaver, Steven; Degeorges, Charles; Bush, Joy; Shendock, Robert; Mandl, Daniel

1993-01-01

Fixed or static limit sensing is employed in control centers to ensure that spacecraft parameters remain within a nominal range. However, many critical parameters, such as power system telemetry, are time-varying and, as such, their 'nominal' range is necessarily time-varying as well. Predicted data, manual limits checking, and widened limit-checking ranges are often employed in an attempt to monitor these parameters without generating excessive limits violations. Generating predicted data and manual limits checking are both resource intensive, while broadening limit ranges for time-varying parameters is clearly inadequate to detect all but catastrophic problems. OSA provides a low-cost solution by using analytically selected data as a reference upon which to base its limits. These limits are always defined relative to the time-varying reference data, rather than as fixed upper and lower limits. In effect, OSA provides individual limits tailored to each value throughout all the data. A side benefit of using relative limits is that they automatically adjust to new reference data. In addition, OSA provides a wealth of analytical by-products in its execution.

Structural stiffness and Coulomb damping in compliant foil journal bearings: Theoretical considerations

NASA Astrophysics Data System (ADS)

Ku, C.-P. Roger; Heshmat, Hooshang

1994-07-01

Compliant foil bearings operate on either gas or liquid, which makes them very attractive for use in extreme environments such as in high-temperature aircraft turbine engines and cryogenic turbopumps. However, a lack of analytical models to predict the dynamic characteristics of foil bearings forces the bearing designer to rely on prototype testing, which is time-consuming and expensive. In this paper, the authors present a theoretical model to predict the structural stiffness and damping coefficients of the bump foil strip in a journal bearing or damper. Stiffness is calculated based on the perturbation of the journal center with respect to its static equilibrium position. The equivalent viscous damping coefficients are determined based on the area of a closed hysteresis loop of the journal center motion. The authors found, theoretically, that the energy dissipated from this loop was mostly contributed by the frictional motion between contact surfaces. In addition, the source and mechanism of the nonlinear behavior of the bump foil strips were examined. With the introduction of this enhanced model, the analytical tools are now available for the design of compliant foil bearings.

Reducing post analytical error: perspectives on new formats for the blood sciences pathology report.

PubMed

O'Connor, John D

2015-02-01

Little has changed in the way we report pathology results from blood sciences over the last 50 years other than moving to electronic display from paper. In part, this is aspiration to preserve the format of a paper report in electronic format. It is also due to the limitations of electronic media to display the data. The advancement of web-based technologies and functionality of hand-held devices together with wireless and other technologies afford the opportunity to rethink data presentation with the aim of emphasising the message in the data, thereby modifying clinical behaviours and potentially reducing post-analytical error. This article takes the form of a commentary which explores new developments in the field of infographics and, together with examples, suggests some new approaches to communicating what is currently just data into information. The combination of graphics and a new approach to provocative interpretative commenting offers a powerful tool in improving pathology utilisation. An additional challenge is the requirement to consider how pathology reports may be issued directly to patients.

Reducing Post Analytical Error: Perspectives on New Formats for the Blood Sciences Pathology Report

PubMed Central

O’Connor, John D

2015-01-01

Little has changed in the way we report pathology results from blood sciences over the last 50 years other than moving to electronic display from paper. In part, this is aspiration to preserve the format of a paper report in electronic format. It is also due to the limitations of electronic media to display the data. The advancement of web-based technologies and functionality of hand-held devices together with wireless and other technologies afford the opportunity to rethink data presentation with the aim of emphasising the message in the data, thereby modifying clinical behaviours and potentially reducing post-analytical error. This article takes the form of a commentary which explores new developments in the field of infographics and, together with examples, suggests some new approaches to communicating what is currently just data into information. The combination of graphics and a new approach to provocative interpretative commenting offers a powerful tool in improving pathology utilisation. An additional challenge is the requirement to consider how pathology reports may be issued directly to patients. PMID:25944968

Solvent signal suppression for high-resolution MAS-DNP

NASA Astrophysics Data System (ADS)

Lee, Daniel; Chaudhari, Sachin R.; De Paëpe, Gaël

2017-05-01

Dynamic nuclear polarization (DNP) has become a powerful tool to substantially increase the sensitivity of high-field magic angle spinning (MAS) solid-state NMR experiments. The addition of dissolved hyperpolarizing agents usually results in the presence of solvent signals that can overlap and obscure those of interest from the analyte. Here, two methods are proposed to suppress DNP solvent signals: a Forced Echo Dephasing experiment (FEDex) and TRAnsfer of Populations in DOuble Resonance Echo Dephasing (TRAPDORED) NMR. These methods reintroduce a heteronuclear dipolar interaction that is specific to the solvent, thereby forcing a dephasing of recoupled solvent spins and leaving acquired NMR spectra free of associated resonance overlap with the analyte. The potency of these methods is demonstrated on sample types common to MAS-DNP experiments, namely a frozen solution (of L-proline) and a powdered solid (progesterone), both containing deuterated glycerol as a DNP solvent. The proposed methods are efficient, simple to implement, compatible with other NMR experiments, and extendable past spectral editing for just DNP solvents. The sensitivity gains from MAS-DNP in conjunction with FEDex or TRAPDORED then permits rapid and uninterrupted sample analysis.

Pods: a Powder Delivery System for Mars In-situ Organic, Mineralogic and Isotopic Analysis Instruments

NASA Technical Reports Server (NTRS)

Saha, C. P.; Bryson, C. E.; Sarrazin, P.; Blake, D. F.

2005-01-01

Many Mars in situ instruments require fine-grained high-fidelity samples of rocks or soil. Included are instruments for the determination of mineralogy as well as organic and isotopic chemistry. Powder can be obtained as a primary objective of a sample collection system (e.g., by collecting powder as a surface is abraded by a rotary abrasion tool (RAT)), or as a secondary objective (e.g, by collecting drill powder as a core is drilled). In the latter case, a properly designed system could be used to monitor drilling in real time as well as to deliver powder to analytical instruments which would perform complementary analyses to those later performed on the intact core. In addition, once a core or other sample is collected, a system that could transfer intelligently collected subsamples of power from the intact core to a suite of analytical instruments would be highly desirable. We have conceptualized, developed and tested a breadboard Powder Delivery System (PoDS) intended to satisfy the collection, processing and distribution requirements of powder samples for Mars in-situ mineralogic, organic and isotopic measurement instruments.

Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: Meta-analysis with a joint model.

PubMed

Emura, Takeshi; Nakatochi, Masahiro; Matsui, Shigeyuki; Michimae, Hirofumi; Rondeau, Virginie

2017-01-01

Developing a personalized risk prediction model of death is fundamental for improving patient care and touches on the realm of personalized medicine. The increasing availability of genomic information and large-scale meta-analytic data sets for clinicians has motivated the extension of traditional survival prediction based on the Cox proportional hazards model. The aim of our paper is to develop a personalized risk prediction formula for death according to genetic factors and dynamic tumour progression status based on meta-analytic data. To this end, we extend the existing joint frailty-copula model to a model allowing for high-dimensional genetic factors. In addition, we propose a dynamic prediction formula to predict death given tumour progression events possibly occurring after treatment or surgery. For clinical use, we implement the computation software of the prediction formula in the joint.Cox R package. We also develop a tool to validate the performance of the prediction formula by assessing the prediction error. We illustrate the method with the meta-analysis of individual patient data on ovarian cancer patients.

Commented review of the Colombian legislation regarding the ethics of health research.

PubMed

Lopera, Mónica María

2017-12-01

The scope of ethics in health research transcends its legal framework and the regulations established in Resolution 8430 of 1993. These norms represent a fundamental tool to determine the minimum protection standards for research subjects, and, therefore, they should be known, applied properly, and reflect upon by all researchers in the field.Here I present and discuss from an analytical point of view the regulations that guide research in health. In this framework, health is understood as a multidimensional process, and research in health as a multidisciplinary exercise involving basic, clinical and public health research, collective health, and other related sciences.The main analytical categories are related to the principles and actors involved in research (regulatory authorities, ethical committees, and special or vulnerable subjects and populations), and to professional ethics codes, in addition to informed consents and data management.Despite the contribution of this legislation to the qualification of health research, my conclusion is that the national legislation in ethics for health research requires updating regarding technological and scientific developments, as well as specifications from the multiple types of health studies.

High Bandwidth Rotary Fast Tool Servos and a Hybrid Rotary/Linear Electromagnetic Actuator

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

Montesanti, Richard Clement

2005-09-01

This thesis describes the development of two high bandwidth short-stroke rotary fast tool servos and the hybrid rotary/linear electromagnetic actuator developed for one of them. Design insights, trade-o® methodologies, and analytical tools are developed for precision mechanical systems, power and signal electronic systems, control systems, normal-stress electromagnetic actuators, and the dynamics of the combined systems.

The Blooming Anatomy Tool (BAT): A Discipline-Specific Rubric for Utilizing Bloom's Taxonomy in the Design and Evaluation of Assessments in the Anatomical Sciences

ERIC Educational Resources Information Center

Thompson, Andrew R.; O'Loughlin, Valerie D.

2015-01-01

Bloom's taxonomy is a resource commonly used to assess the cognitive level associated with course assignments and examination questions. Although widely utilized in educational research, Bloom's taxonomy has received limited attention as an analytical tool in the anatomical sciences. Building on previous research, the Blooming Anatomy Tool (BAT)…

The Blackbird Whistling or Just After? Vygotsky's Tool and Sign as an Analytic for Writing

ERIC Educational Resources Information Center

Imbrenda, Jon-Philip

2016-01-01

Based on Vygotsky's theory of the interplay of the tool and sign functions of language, this study presents a textual analysis of a corpus of student-authored texts to illuminate aspects of development evidenced through the dialectical tension of tool and sign. Data were drawn from a series of reflective memos I authored during a seminar for new…

Linguistics and the Study of Literature. Linguistics in the Undergraduate Curriculum, Appendix 4-D.

ERIC Educational Resources Information Center

Steward, Ann Harleman

Linguistics gives the student of literature an analytical tool whose sole purpose is to describe faithfully the workings of language. It provides a theoretical framework, an analytical method, and a vocabulary for communicating its insights--all designed to serve concerns other than literary interpretation and evaluation, but all useful for…

Required, Practical, or Unnecessary? An Examination and Demonstration of Propensity Score Matching Using Longitudinal Secondary Data

ERIC Educational Resources Information Center

Padgett, Ryan D.; Salisbury, Mark H.; An, Brian P.; Pascarella, Ernest T.

2010-01-01

The sophisticated analytical techniques available to institutional researchers give them an array of procedures to estimate a causal effect using observational data. But as many quantitative researchers have discovered, access to a wider selection of statistical tools does not necessarily ensure construction of a better analytical model. Moreover,…

Using Data Mining for Predicting Relationships between Online Question Theme and Final Grade

ERIC Educational Resources Information Center

Abdous, M'hammed; He, Wu; Yen, Cherng-Jyh

2012-01-01

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students' learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped…

Using Functional Analytic Therapy to Train Therapists in Acceptance and Commitment Therapy, a Conceptual and Practical Framework

ERIC Educational Resources Information Center

Schoendorff, Benjamin; Steinwachs, Joanne

2012-01-01

How can therapists be effectively trained in clinical functional contextualism? In this conceptual article we propose a new way of training therapists in Acceptance and Commitment Therapy skills using tools from Functional Analytic Psychotherapy in a training context functionally similar to the therapeutic relationship. FAP has been successfully…

Effects of Learning Analytics Dashboard: Analyzing the Relations among Dashboard Utilization, Satisfaction, and Learning Achievement

ERIC Educational Resources Information Center

Kim, Jeonghyun; Jo, Il-Hyun; Park, Yeonjeong

2016-01-01

The learning analytics dashboard (LAD) is a newly developed learning support tool for virtual classrooms that is believed to allow students to review their online learning behavior patterns intuitively through the provision of visual information. The purpose of this study was to empirically validate the effects of LAD. An experimental study was…