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…

The current preference for the immuno-analytical ELISA method for quantitation of steroid hormones (endocrine disruptor compounds) in wastewater in South Africa.

PubMed

Manickum, Thavrin; John, Wilson

2015-07-01

requirements for steroid hormone quantitation. Further optimization of the sensitivity of the chemical-analytical LC-tandem mass spectrometry methods, especially for wastewater screening, in South Africa is required. Risk assessment studies showed that it was not practical to propose standards or allowable limits for the steroid estrogens E1, E2, EE2, and E3; the use of predicted-no-effect concentration values of the steroid estrogens appears to be appropriate for use in their risk assessment in relation to aquatic organisms. For raw water sources, drinking water, raw and treated wastewater, the use of bioassays, with trigger values, is a useful screening tool option to decide whether further examination of specific endocrine activity may be warranted, or whether concentrations of such activity are of low priority, with respect to health concerns in the human population. The achievement of improved quantitation limits for immuno-analytical methods, like ELISA, used for compound quantitation, and standardization of the method for measuring E2 equivalents (EEQs) used for biological activity (endocrine: e.g., estrogenic) are some areas for future EDC research.

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,...

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.

Analytic and rule-based decision support tool for VDT workstation adjustment and computer accessories arrangement.

PubMed

Rurkhamet, Busagarin; Nanthavanij, Suebsak

2004-12-01

One important factor that leads to the development of musculoskeletal disorders (MSD) and cumulative trauma disorders (CTD) among visual display terminal (VDT) users is their work posture. While operating a VDT, a user's body posture is strongly influenced by the task, VDT workstation settings, and layout of computer accessories. This paper presents an analytic and rule-based decision support tool called EQ-DeX (an ergonomics and quantitative design expert system) that is developed to provide valid and practical recommendations regarding the adjustment of a VDT workstation and the arrangement of computer accessories. The paper explains the structure and components of EQ-DeX, input data, rules, and adjustment and arrangement algorithms. From input information such as gender, age, body height, task, etc., EQ-DeX uses analytic and rule-based algorithms to estimate quantitative settings of a computer table and a chair, as well as locations of computer accessories such as monitor, document holder, keyboard, and mouse. With the input and output screens that are designed using the concept of usability, the interactions between the user and EQ-DeX are convenient. Examples are also presented to demonstrate the recommendations generated by EQ-DeX.

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

Analytical aspects of hydrogen exchange mass spectrometry

PubMed Central

Engen, John R.; Wales, Thomas E.

2016-01-01

The analytical aspects of measuring hydrogen exchange by mass spectrometry are reviewed. The nature of analytical selectivity in hydrogen exchange is described followed by review of the analytical tools required to accomplish fragmentation, separation, and the mass spectrometry measurements under restrictive exchange quench conditions. In contrast to analytical quantitation that relies on measurements of peak intensity or area, quantitation in hydrogen exchange mass spectrometry depends on measuring a mass change with respect to an undeuterated or deuterated control, resulting in a value between zero and the maximum amount of deuterium that could be incorporated. Reliable quantitation is a function of experimental fidelity and to achieve high measurement reproducibility, a large number of experimental variables must be controlled during sample preparation and analysis. The method also reports on important qualitative aspects of the sample, including conformational heterogeneity and population dynamics. PMID:26048552

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.

Competing on analytics.

PubMed

Davenport, Thomas H

2006-01-01

We all know the power of the killer app. It's not just a support tool; it's a strategic weapon. Companies questing for killer apps generally focus all their firepower on the one area that promises to create the greatest competitive advantage. But a new breed of organization has upped the stakes: Amazon, Harrah's, Capital One, and the Boston Red Sox have all dominated their fields by deploying industrial-strength analytics across a wide variety of activities. At a time when firms in many industries offer similar products and use comparable technologies, business processes are among the few remaining points of differentiation--and analytics competitors wring every last drop of value from those processes. Employees hired for their expertise with numbers or trained to recognize their importance are armed with the best evidence and the best quantitative tools. As a result, they make the best decisions. In companies that compete on analytics, senior executives make it clear--from the top down--that analytics is central to strategy. Such organizations launch multiple initiatives involving complex data and statistical analysis, and quantitative activity is managed atthe enterprise (not departmental) level. In this article, professor Thomas H. Davenport lays out the characteristics and practices of these statistical masters and describes some of the very substantial changes other companies must undergo in order to compete on quantitative turf. As one would expect, the transformation requires a significant investment in technology, the accumulation of massive stores of data, and the formulation of company-wide strategies for managing the data. But, at least as important, it also requires executives' vocal, unswerving commitment and willingness to change the way employees think, work, and are treated.

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.

Evaluation methodology for comparing memory and communication of analytic processes in visual analytics

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

Ragan, Eric D; Goodall, John R

2014-01-01

Provenance tools can help capture and represent the history of analytic processes. In addition to supporting analytic performance, provenance tools can be used to support memory of the process and communication of the steps to others. Objective evaluation methods are needed to evaluate how well provenance tools support analyst s memory and communication of analytic processes. In this paper, we present several methods for the evaluation of process memory, and we discuss the advantages and limitations of each. We discuss methods for determining a baseline process for comparison, and we describe various methods that can be used to elicit processmore » recall, step ordering, and time estimations. Additionally, we discuss methods for conducting quantitative and qualitative analyses of process memory. By organizing possible memory evaluation methods and providing a meta-analysis of the potential benefits and drawbacks of different approaches, this paper can inform study design and encourage objective evaluation of process memory and communication.« less

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…

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.

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

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.

Correction for isotopic interferences between analyte and internal standard in quantitative mass spectrometry by a nonlinear calibration function.

PubMed

Rule, Geoffrey S; Clark, Zlatuse D; Yue, Bingfang; Rockwood, Alan L

2013-04-16

Stable isotope-labeled internal standards are of great utility in providing accurate quantitation in mass spectrometry (MS). An implicit assumption has been that there is no "cross talk" between signals of the internal standard and the target analyte. In some cases, however, naturally occurring isotopes of the analyte do contribute to the signal of the internal standard. This phenomenon becomes more pronounced for isotopically rich compounds, such as those containing sulfur, chlorine, or bromine, higher molecular weight compounds, and those at high analyte/internal standard concentration ratio. This can create nonlinear calibration behavior that may bias quantitative results. Here, we propose the use of a nonlinear but more accurate fitting of data for these situations that incorporates one or two constants determined experimentally for each analyte/internal standard combination and an adjustable calibration parameter. This fitting provides more accurate quantitation in MS-based assays where contributions from analyte to stable labeled internal standard signal exist. It can also correct for the reverse situation where an analyte is present in the internal standard as an impurity. The practical utility of this approach is described, and by using experimental data, the approach is compared to alternative fits.

Analytical insight into "breathing" crack-induced acoustic nonlinearity with an application to quantitative evaluation of contact cracks.

PubMed

Wang, Kai; Liu, Menglong; Su, Zhongqing; Yuan, Shenfang; Fan, Zheng

2018-08-01

To characterize fatigue cracks, in the undersized stage in particular, preferably in a quantitative and precise manner, a two-dimensional (2D) analytical model is developed for interpreting the modulation mechanism of a "breathing" crack on guided ultrasonic waves (GUWs). In conjunction with a modal decomposition method and a variational principle-based algorithm, the model is capable of analytically depicting the propagating and evanescent waves induced owing to the interaction of probing GUWs with a "breathing" crack, and further extracting linear and nonlinear wave features (e.g., reflection, transmission, mode conversion and contact acoustic nonlinearity (CAN)). With the model, a quantitative correlation between CAN embodied in acquired GUWs and crack parameters (e.g., location and severity) is obtained, whereby a set of damage indices is proposed via which the severity of the crack can be evaluated quantitatively. The evaluation, in principle, does not entail a benchmarking process against baseline signals. As validation, the results obtained from the analytical model are compared with those from finite element simulation, showing good consistency. This has demonstrated accuracy of the developed analytical model in interpreting contact crack-induced CAN, and spotlighted its application to quantitative evaluation of fatigue damage. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Calibrant-Free Analyte Quantitation via a Variable Velocity Flow Cell.

PubMed

Beck, Jason G; Skuratovsky, Aleksander; Granger, Michael C; Porter, Marc D

2017-01-17

In this paper, we describe a novel method for analyte quantitation that does not rely on calibrants, internal standards, or calibration curves but, rather, leverages the relationship between disparate and predictable surface-directed analyte flux to an array of sensing addresses and a measured resultant signal. To reduce this concept to practice, we fabricated two flow cells such that the mean linear fluid velocity, U, was varied systematically over an array of electrodes positioned along the flow axis. This resulted in a predictable variation of the address-directed flux of a redox analyte, ferrocenedimethanol (FDM). The resultant limiting currents measured at a series of these electrodes, and accurately described by a convective-diffusive transport model, provided a means to calculate an "unknown" concentration without the use of calibrants, internal standards, or a calibration curve. Furthermore, the experiment and concentration calculation only takes minutes to perform. Deviation in calculated FDM concentrations from true values was minimized to less than 0.5% when empirically derived values of U were employed.

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.

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…

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

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.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

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...

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

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

Cryogenic Propellant Feed System Analytical Tool Development

NASA Technical Reports Server (NTRS)

Lusby, Brian S.; Miranda, Bruno M.; Collins, Jacob A.

2011-01-01

The Propulsion Systems Branch at NASA s Lyndon B. Johnson Space Center (JSC) has developed a parametric analytical tool to address the need to rapidly predict heat leak into propellant distribution lines based on insulation type, installation technique, line supports, penetrations, and instrumentation. The Propellant Feed System Analytical Tool (PFSAT) will also determine the optimum orifice diameter for an optional thermodynamic vent system (TVS) to counteract heat leak into the feed line and ensure temperature constraints at the end of the feed line are met. PFSAT was developed primarily using Fortran 90 code because of its number crunching power and the capability to directly access real fluid property subroutines in the Reference Fluid Thermodynamic and Transport Properties (REFPROP) Database developed by NIST. A Microsoft Excel front end user interface was implemented to provide convenient portability of PFSAT among a wide variety of potential users and its ability to utilize a user-friendly graphical user interface (GUI) developed in Visual Basic for Applications (VBA). The focus of PFSAT is on-orbit reaction control systems and orbital maneuvering systems, but it may be used to predict heat leak into ground-based transfer lines as well. PFSAT is expected to be used for rapid initial design of cryogenic propellant distribution lines and thermodynamic vent systems. Once validated, PFSAT will support concept trades for a variety of cryogenic fluid transfer systems on spacecraft, including planetary landers, transfer vehicles, and propellant depots, as well as surface-based transfer systems. The details of the development of PFSAT, its user interface, and the program structure will be presented.

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

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.

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.

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Waltz, Ed

2016-05-01

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

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.

Tool independence for the Web Accessibility Quantitative Metric.

PubMed

Vigo, Markel; Brajnik, Giorgio; Arrue, Myriam; Abascal, Julio

2009-07-01

The Web Accessibility Quantitative Metric (WAQM) aims at accurately measuring the accessibility of web pages. One of the main features of WAQM among others is that it is evaluation tool independent for ranking and accessibility monitoring scenarios. This article proposes a method to attain evaluation tool independence for all foreseeable scenarios. After demonstrating that homepages have a more similar error profile than any other web page in a given web site, 15 homepages were measured with 10,000 different values of WAQM parameters using EvalAccess and LIFT, two automatic evaluation tools for accessibility. A similar procedure was followed with random pages and with several test files obtaining several tuples that minimise the difference between both tools. One thousand four hundred forty-nine web pages from 15 web sites were measured with these tuples and those values that minimised the difference between the tools were selected. Once the WAQM was tuned, the accessibility of 15 web sites was measured with two metrics for web sites, concluding that even if similar values can be produced, obtaining the same scores is undesirable since evaluation tools behave in a different way.

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.

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.

2D Hydrodynamic Based Logic Modeling Tool for River Restoration Decision Analysis: A Quantitative Approach to Project Prioritization

NASA Astrophysics Data System (ADS)

Bandrowski, D.; Lai, Y.; Bradley, N.; Gaeuman, D. A.; Murauskas, J.; Som, N. A.; Martin, A.; Goodman, D.; Alvarez, J.

2014-12-01

In the field of river restoration sciences there is a growing need for analytical modeling tools and quantitative processes to help identify and prioritize project sites. 2D hydraulic models have become more common in recent years and with the availability of robust data sets and computing technology, it is now possible to evaluate large river systems at the reach scale. The Trinity River Restoration Program is now analyzing a 40 mile segment of the Trinity River to determine priority and implementation sequencing for its Phase II rehabilitation projects. A comprehensive approach and quantitative tool has recently been developed to analyze this complex river system referred to as: 2D-Hydrodynamic Based Logic Modeling (2D-HBLM). This tool utilizes various hydraulic output parameters combined with biological, ecological, and physical metrics at user-defined spatial scales. These metrics and their associated algorithms are the underpinnings of the 2D-HBLM habitat module used to evaluate geomorphic characteristics, riverine processes, and habitat complexity. The habitat metrics are further integrated into a comprehensive Logic Model framework to perform statistical analyses to assess project prioritization. The Logic Model will analyze various potential project sites by evaluating connectivity using principal component methods. The 2D-HBLM tool will help inform management and decision makers by using a quantitative process to optimize desired response variables with balancing important limiting factors in determining the highest priority locations within the river corridor to implement restoration projects. Effective river restoration prioritization starts with well-crafted goals that identify the biological objectives, address underlying causes of habitat change, and recognizes that social, economic, and land use limiting factors may constrain restoration options (Bechie et. al. 2008). Applying natural resources management actions, like restoration prioritization, is

A results-based process for evaluation of diverse visual analytics tools

NASA Astrophysics Data System (ADS)

Rubin, Gary; Berger, David H.

2013-05-01

With the pervasiveness of still and full-motion imagery in commercial and military applications, the need to ingest and analyze these media has grown rapidly in recent years. Additionally, video hosting and live camera websites provide a near real-time view of our changing world with unprecedented spatial coverage. To take advantage of these controlled and crowd-sourced opportunities, sophisticated visual analytics (VA) tools are required to accurately and efficiently convert raw imagery into usable information. Whether investing in VA products or evaluating algorithms for potential development, it is important for stakeholders to understand the capabilities and limitations of visual analytics tools. Visual analytics algorithms are being applied to problems related to Intelligence, Surveillance, and Reconnaissance (ISR), facility security, and public safety monitoring, to name a few. The diversity of requirements means that a onesize- fits-all approach to performance assessment will not work. We present a process for evaluating the efficacy of algorithms in real-world conditions, thereby allowing users and developers of video analytics software to understand software capabilities and identify potential shortcomings. The results-based approach described in this paper uses an analysis of end-user requirements and Concept of Operations (CONOPS) to define Measures of Effectiveness (MOEs), test data requirements, and evaluation strategies. We define metrics that individually do not fully characterize a system, but when used together, are a powerful way to reveal both strengths and weaknesses. We provide examples of data products, such as heatmaps, performance maps, detection timelines, and rank-based probability-of-detection curves.

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…

Quantitative SIMS Imaging of Agar-Based Microbial Communities.

PubMed

Dunham, Sage J B; Ellis, Joseph F; Baig, Nameera F; Morales-Soto, Nydia; Cao, Tianyuan; Shrout, Joshua D; Bohn, Paul W; Sweedler, Jonathan V

2018-05-01

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

NASA Astrophysics Data System (ADS)

Mahgoub, Hend; Gilchrist, John R.; Fearn, Thomas; Strlič, Matija

2017-07-01

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the 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.

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

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.

Analytical method for the accurate determination of tricothecenes in grains using LC-MS/MS: a comparison between MRM transition and MS3 quantitation.

PubMed

Lim, Chee Wei; Tai, Siew Hoon; Lee, Lin Min; Chan, Sheot Harn

2012-07-01

The current food crisis demands unambiguous determination of mycotoxin contamination in staple foods to achieve safer food for consumption. This paper describes the first accurate LC-MS/MS method developed to analyze tricothecenes in grains by applying multiple reaction monitoring (MRM) transition and MS(3) quantitation strategies in tandem. The tricothecenes are nivalenol, deoxynivalenol, deoxynivalenol-3-glucoside, fusarenon X, 3-acetyl-deoxynivalenol, 15-acetyldeoxynivalenol, diacetoxyscirpenol, and HT-2 and T-2 toxins. Acetic acid and ammonium acetate were used to convert the analytes into their respective acetate adducts and ammonium adducts under negative and positive MS polarity conditions, respectively. The mycotoxins were separated by reversed-phase LC in a 13.5-min run, ionized using electrospray ionization, and detected by tandem mass spectrometry. Analyte-specific mass-to-charge (m/z) ratios were used to perform quantitation under MRM transition and MS(3) (linear ion trap) modes. Three experiments were made for each quantitation mode and matrix in batches over 6 days for recovery studies. The matrix effect was investigated at concentration levels of 20, 40, 80, 120, 160, and 200 μg kg(-1) (n = 3) in 5 g corn flour and rice flour. Extraction with acetonitrile provided a good overall recovery range of 90-108% (n = 3) at three levels of spiking concentration of 40, 80, and 120 μg kg(-1). A quantitation limit of 2-6 μg kg(-1) was achieved by applying an MRM transition quantitation strategy. Under MS(3) mode, a quantitation limit of 4-10 μg kg(-1) was achieved. Relative standard deviations of 2-10% and 2-11% were reported for MRM transition and MS(3) quantitation, respectively. The successful utilization of MS(3) enabled accurate analyte fragmentation pattern matching and its quantitation, leading to the development of analytical methods in fields that demand both analyte specificity and fragmentation fingerprint-matching capabilities that are

Investigating the Validity of Two Widely Used Quantitative Text Tools

ERIC Educational Resources Information Center

Cunningham, James W.; Hiebert, Elfrieda H.; Mesmer, Heidi Anne

2018-01-01

In recent years, readability formulas have gained new prominence as a basis for selecting texts for learning and assessment. Variables that quantitative tools count (e.g., word frequency, sentence length) provide valid measures of text complexity insofar as they accurately predict representative and high-quality criteria. The longstanding…

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.

Adequacy of surface analytical tools for studying the tribology of ceramics

NASA Technical Reports Server (NTRS)

Sliney, H. E.

1986-01-01

Surface analytical tools are very beneficial in tribological studies of ceramics. Traditional methods of optical microscopy, XRD, XRF, and SEM should be combined with newer surface sensitive techniques especially AES and XPS. ISS and SIMS can also be useful in providing additional compositon details. Tunneling microscopy and electron energy loss spectroscopy are less known techniques that may also prove useful.

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

DOE PAGES

Ercius, Peter; Alaidi, Osama; Rames, Matthew J.; ...

2015-06-18

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is amore » technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. Here, this review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. Electron tomography produces quantitative 3D reconstructions for biological and physical sciences from sets of 2D projections acquired at different tilting angles in a transmission electron microscope. Finally, state-of-the-art techniques capable of producing 3D representations such as Pt-Pd core-shell nanoparticles and IgG1 antibody molecules are reviewed.« less

Plant Aquaporins: Genome-Wide Identification, Transcriptomics, Proteomics, and Advanced Analytical Tools.

PubMed

Deshmukh, Rupesh K; Sonah, Humira; Bélanger, Richard R

2016-01-01

Aquaporins (AQPs) are channel-forming integral membrane proteins that facilitate the movement of water and many other small molecules. Compared to animals, plants contain a much higher number of AQPs in their genome. Homology-based identification of AQPs in sequenced species is feasible because of the high level of conservation of protein sequences across plant species. Genome-wide characterization of AQPs has highlighted several important aspects such as distribution, genetic organization, evolution and conserved features governing solute specificity. From a functional point of view, the understanding of AQP transport system has expanded rapidly with the help of transcriptomics and proteomics data. The efficient analysis of enormous amounts of data generated through omic scale studies has been facilitated through computational advancements. Prediction of protein tertiary structures, pore architecture, cavities, phosphorylation sites, heterodimerization, and co-expression networks has become more sophisticated and accurate with increasing computational tools and pipelines. However, the effectiveness of computational approaches is based on the understanding of physiological and biochemical properties, transport kinetics, solute specificity, molecular interactions, sequence variations, phylogeny and evolution of aquaporins. For this purpose, tools like Xenopus oocyte assays, yeast expression systems, artificial proteoliposomes, and lipid membranes have been efficiently exploited to study the many facets that influence solute transport by AQPs. In the present review, we discuss genome-wide identification of AQPs in plants in relation with recent advancements in analytical tools, and their availability and technological challenges as they apply to AQPs. An exhaustive review of omics resources available for AQP research is also provided in order to optimize their efficient utilization. Finally, a detailed catalog of computational tools and analytical pipelines is

Plant Aquaporins: Genome-Wide Identification, Transcriptomics, Proteomics, and Advanced Analytical Tools

PubMed Central

Deshmukh, Rupesh K.; Sonah, Humira; Bélanger, Richard R.

2016-01-01

Aquaporins (AQPs) are channel-forming integral membrane proteins that facilitate the movement of water and many other small molecules. Compared to animals, plants contain a much higher number of AQPs in their genome. Homology-based identification of AQPs in sequenced species is feasible because of the high level of conservation of protein sequences across plant species. Genome-wide characterization of AQPs has highlighted several important aspects such as distribution, genetic organization, evolution and conserved features governing solute specificity. From a functional point of view, the understanding of AQP transport system has expanded rapidly with the help of transcriptomics and proteomics data. The efficient analysis of enormous amounts of data generated through omic scale studies has been facilitated through computational advancements. Prediction of protein tertiary structures, pore architecture, cavities, phosphorylation sites, heterodimerization, and co-expression networks has become more sophisticated and accurate with increasing computational tools and pipelines. However, the effectiveness of computational approaches is based on the understanding of physiological and biochemical properties, transport kinetics, solute specificity, molecular interactions, sequence variations, phylogeny and evolution of aquaporins. For this purpose, tools like Xenopus oocyte assays, yeast expression systems, artificial proteoliposomes, and lipid membranes have been efficiently exploited to study the many facets that influence solute transport by AQPs. In the present review, we discuss genome-wide identification of AQPs in plants in relation with recent advancements in analytical tools, and their availability and technological challenges as they apply to AQPs. An exhaustive review of omics resources available for AQP research is also provided in order to optimize their efficient utilization. Finally, a detailed catalog of computational tools and analytical pipelines is

Sample normalization methods in quantitative metabolomics.

PubMed

Wu, Yiman; Li, Liang

2016-01-22

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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

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.

Metabolomics and Diabetes: Analytical and Computational Approaches

PubMed Central

Sas, Kelli M.; Karnovsky, Alla; Michailidis, George

2015-01-01

Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field. PMID:25713200

Tannin structural elucidation and quantitative ³¹P NMR analysis. 2. Hydrolyzable tannins and proanthocyanidins.

PubMed

Melone, Federica; Saladino, Raffaele; Lange, Heiko; Crestini, Claudia

2013-10-02

An unprecedented analytical method that allows simultaneous structural and quantitative characterization of all functional groups present in tannins is reported. In situ labeling of all labile H groups (aliphatic and phenolic hydroxyls and carboxylic acids) with a phosphorus-containing reagent (Cl-TMDP) followed by quantitative ³¹P NMR acquisition constitutes a novel fast and reliable analytical tool for the analysis of tannins and proanthocyanidins with significant implications for the fields of food and feed analyses, tannery, and the development of natural polyphenolics containing products.

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

INTRODUCTION TO ATTILA (ANALYTICAL TOOLS INTERFACE FOR LANDSCAPE ASSESSMENTS): AN ARCVIEW EXTENSION

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 indicators, which are quantitative measurements of the status or potential health of an area (e.g. ecological region, wat...

DAnTE: a statistical tool for quantitative analysis of –omics data

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

Polpitiya, Ashoka D.; Qian, Weijun; Jaitly, Navdeep

2008-05-03

DAnTE (Data Analysis Tool Extension) is a statistical tool designed to address challenges unique to quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide to protein rollup methods, an extensive array of plotting functions, and a comprehensive ANOVA scheme that can handle unbalanced data and random effects. The Graphical User Interface (GUI) is designed to be very intuitive and user friendly.

Analytical challenges for conducting rapid metabolism characterization for QIVIVE.

PubMed

Tolonen, Ari; Pelkonen, Olavi

2015-06-05

For quantitative in vitro-in vivo extrapolation (QIVIVE) of metabolism for the purposes of toxicokinetics prediction, a precise and robust analytical technique for identifying and measuring a chemical and its metabolites is an absolute prerequisite. Currently, high-resolution mass spectrometry (HR-MS) is a tool of choice for a majority of organic relatively lipophilic molecules, linked with a LC separation tool and simultaneous UV-detection. However, additional techniques such as gas chromatography, radiometric measurements and NMR, are required to cover the whole spectrum of chemical structures. To accumulate enough reliable and robust data for the validation of QIVIVE, there are some partially opposing needs: Detailed delineation of the in vitro test system to produce a reliable toxicokinetic measure for a studied chemical, and a throughput capacity of the in vitro set-up and the analytical tool as high as possible. We discuss current analytical challenges for the identification and quantification of chemicals and their metabolites, both stable and reactive, focusing especially on LC-MS techniques, but simultaneously attempting to pinpoint factors associated with sample preparation, testing conditions and strengths and weaknesses of a particular technique available for a particular task. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

PAUSE: Predictive Analytics Using SPARQL-Endpoints

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

Sukumar, Sreenivas R; Ainsworth, Keela; Bond, Nathaniel

2014-07-11

This invention relates to the medical industry and more specifically to methods of predicting risks. With the impetus towards personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledgebase, etc.) to predict diagnostic risks is fast emerging. We describe a software solution that leverages hardware for scalable in-memory analytics and applies next-generation semantic query tools on medical data.

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.

iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

PubMed Central

Chang, Hui-Yin; Chen, Ching-Tai; Lih, T. Mamie; Lynn, Ke-Shiuan; Juo, Chiun-Gung; Hsu, Wen-Lian; Sung, Ting-Yi

2016-01-01

Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤0.19) when quantifying the two internal standards and had higher abundance correlation (≥0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html. PMID:26784691

Quantitative phase imaging method based on an analytical nonparaxial partially coherent phase optical transfer function.

PubMed

Bao, Yijun; Gaylord, Thomas K

2016-11-01

Multifilter phase imaging with partially coherent light (MFPI-PC) is a promising new quantitative phase imaging method. However, the existing MFPI-PC method is based on the paraxial approximation. In the present work, an analytical nonparaxial partially coherent phase optical transfer function is derived. This enables the MFPI-PC to be extended to the realistic nonparaxial case. Simulations over a wide range of test phase objects as well as experimental measurements on a microlens array verify higher levels of imaging accuracy compared to the paraxial method. Unlike the paraxial version, the nonparaxial MFPI-PC with obliquity factor correction exhibits no systematic error. In addition, due to its analytical expression, the increase in computation time compared to the paraxial version is negligible.

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

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.

MsViz: A Graphical Software Tool for In-Depth Manual Validation and Quantitation of Post-translational Modifications.

PubMed

Martín-Campos, Trinidad; Mylonas, Roman; Masselot, Alexandre; Waridel, Patrice; Petricevic, Tanja; Xenarios, Ioannis; Quadroni, Manfredo

2017-08-04

Mass spectrometry (MS) has become the tool of choice for the large scale identification and quantitation of proteins and their post-translational modifications (PTMs). This development has been enabled by powerful software packages for the automated analysis of MS data. While data on PTMs of thousands of proteins can nowadays be readily obtained, fully deciphering the complexity and combinatorics of modification patterns even on a single protein often remains challenging. Moreover, functional investigation of PTMs on a protein of interest requires validation of the localization and the accurate quantitation of its changes across several conditions, tasks that often still require human evaluation. Software tools for large scale analyses are highly efficient but are rarely conceived for interactive, in-depth exploration of data on individual proteins. We here describe MsViz, a web-based and interactive software tool that supports manual validation of PTMs and their relative quantitation in small- and medium-size experiments. The tool displays sequence coverage information, peptide-spectrum matches, tandem MS spectra and extracted ion chromatograms through a single, highly intuitive interface. We found that MsViz greatly facilitates manual data inspection to validate PTM location and quantitate modified species across multiple samples.

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

Implementing a Quantitative Analysis Design Tool for Future Generation Interfaces

DTIC Science & Technology

2012-03-01

with Remotely Piloted Aircraft (RPA) has resulted in the need of a platform to evaluate interface design. The Vigilant Spirit Control Station ( VSCS ...Spirit interface. A modified version of the HCI Index was successfully applied to perform a quantitative analysis of the baseline VSCS interface and...time of the original VSCS interface. These results revealed the effectiveness of the tool and demonstrated in the design of future generation

The NIST Quantitative Infrared Database

PubMed Central

Chu, P. M.; Guenther, F. R.; Rhoderick, G. C.; Lafferty, W. J.

1999-01-01

With the recent developments in Fourier transform infrared (FTIR) spectrometers it is becoming more feasible to place these instruments in field environments. As a result, there has been enormous increase in the use of FTIR techniques for a variety of qualitative and quantitative chemical measurements. These methods offer the possibility of fully automated real-time quantitation of many analytes; therefore FTIR has great potential as an analytical tool. Recently, the U.S. Environmental Protection Agency (U.S.EPA) has developed protocol methods for emissions monitoring using both extractive and open-path FTIR measurements. Depending upon the analyte, the experimental conditions and the analyte matrix, approximately 100 of the hazardous air pollutants (HAPs) listed in the 1990 U.S.EPA Clean Air Act amendment (CAAA) can be measured. The National Institute of Standards and Technology (NIST) has initiated a program to provide quality-assured infrared absorption coefficient data based on NIST prepared primary gas standards. Currently, absorption coefficient data has been acquired for approximately 20 of the HAPs. For each compound, the absorption coefficient spectrum was calculated using nine transmittance spectra at 0.12 cm−1 resolution and the Beer’s law relationship. The uncertainties in the absorption coefficient data were estimated from the linear regressions of the transmittance data and considerations of other error sources such as the nonlinear detector response. For absorption coefficient values greater than 1 × 10−4 μmol/mol)−1 m−1 the average relative expanded uncertainty is 2.2 %. This quantitative infrared database is currently an ongoing project at NIST. Additional spectra will be added to the database as they are acquired. Our current plans include continued data acquisition of the compounds listed in the CAAA, as well as the compounds that contribute to global warming and ozone depletion.

Digital Holography, a metrological tool for quantitative analysis: Trends and future applications

NASA Astrophysics Data System (ADS)

Paturzo, Melania; Pagliarulo, Vito; Bianco, Vittorio; Memmolo, Pasquale; Miccio, Lisa; Merola, Francesco; Ferraro, Pietro

2018-05-01

A review on the last achievements of Digital Holography is reported in this paper, showing that this powerful method can be a key metrological tool for the quantitative analysis and non-invasive inspection of a variety of materials, devices and processes. Nowadays, its range of applications has been greatly extended, including the study of live biological matter and biomedical applications. This paper overviews the main progresses and future perspectives of digital holography, showing new optical configurations and investigating the numerical issues to be tackled for the processing and display of quantitative data.

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.

Kinetic Analysis of Amylase Using Quantitative Benedict's and Iodine Starch Reagents

ERIC Educational Resources Information Center

Cochran, Beverly; Lunday, Deborah; Miskevich, Frank

2008-01-01

Quantitative analysis of carbohydrates is a fundamental analytical tool used in many aspects of biology and chemistry. We have adapted a technique developed by Mathews et al. using an inexpensive scanner and open-source image analysis software to quantify amylase activity using both the breakdown of starch and the appearance of glucose. Breakdown…

MilQuant: a free, generic software tool for isobaric tagging-based quantitation.

PubMed

Zou, Xiao; Zhao, Minzhi; Shen, Hongyan; Zhao, Xuyang; Tong, Yuanpeng; Wang, Qingsong; Wei, Shicheng; Ji, Jianguo

2012-09-18

Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

(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…

Leadership Trust in Virtual Teams Using Communication Tools: A Quantitative Correlational Study

ERIC Educational Resources Information Center

Clark, Robert Lynn

2014-01-01

The purpose of this quantitative correlational study was to address leadership trust in virtual teams using communication tools in a small south-central, family-owned pharmaceutical organization, with multiple dispersed locations located in the United States. The results of the current research study could assist leaders to develop a communication…

New Tool Quantitatively Maps Minority-Carrier Lifetime of Multicrystalline Silicon Bricks (Fact Sheet)

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

Not Available

2011-11-01

NREL's new imaging tool could provide manufacturers with insight on their processes. Scientists at the National Renewable Energy Laboratory (NREL) have used capabilities within the Process Development and Integration Laboratory (PDIL) to generate quantitative minority-carrier lifetime maps of multicrystalline silicon (mc-Si) bricks. This feat has been accomplished by using the PDIL's photoluminescence (PL) imaging system in conjunction with transient lifetime measurements obtained using a custom NREL-designed resonance-coupled photoconductive decay (RCPCD) system. PL imaging can obtain rapid high-resolution images that provide a qualitative assessment of the material lifetime-with the lifetime proportional to the pixel intensity. In contrast, the RCPCD technique providesmore » a fast quantitative measure of the lifetime with a lower resolution and penetrates millimeters into the mc-Si brick, providing information on bulk lifetimes and material quality. This technique contrasts with commercially available minority-carrier lifetime mapping systems that use microwave conductivity measurements. Such measurements are dominated by surface recombination and lack information on the material quality within the bulk of the brick. By combining these two complementary techniques, we obtain high-resolution lifetime maps at very fast data acquisition times-attributes necessary for a production-based diagnostic tool. These bulk lifetime measurements provide manufacturers with invaluable feedback on their silicon ingot casting processes. NREL has been applying the PL images of lifetime in mc-Si bricks in collaboration with a U.S. photovoltaic industry partner through Recovery Act Funded Project ARRA T24. NREL developed a new tool to quantitatively map minority-carrier lifetime of multicrystalline silicon bricks by using photoluminescence imaging in conjunction with resonance-coupled photoconductive decay measurements. Researchers are not hindered by surface recombination and can

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.

Quantitative Evaluation of Heavy Duty Machine Tools Remanufacturing Based on Modified Catastrophe Progression Method

NASA Astrophysics Data System (ADS)

shunhe, Li; jianhua, Rao; lin, Gui; weimin, Zhang; degang, Liu

2017-11-01

The result of remanufacturing evaluation is the basis for judging whether the heavy duty machine tool can remanufacture in the EOL stage of the machine tool lifecycle management.The objectivity and accuracy of evaluation is the key to the evaluation method.In this paper, the catastrophe progression method is introduced into the quantitative evaluation of heavy duty machine tools’ remanufacturing,and the results are modified by the comprehensive adjustment method,which makes the evaluation results accord with the standard of human conventional thinking.Using the catastrophe progression method to establish the heavy duty machine tools’ quantitative evaluation model,to evaluate the retired TK6916 type CNC floor milling-boring machine’s remanufacturing.The evaluation process is simple,high quantification,the result is objective.

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Enabling analytical and Modeling Tools for Enhanced Disease Surveillance

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

Dawn K. Manley

2003-04-01

Early detection, identification, and warning are essential to minimize casualties from a biological attack. For covert attacks, sick people are likely to provide the first indication of an attack. An enhanced medical surveillance system that synthesizes distributed health indicator information and rapidly analyzes the information can dramatically increase the number of lives saved. Current surveillance methods to detect both biological attacks and natural outbreaks are hindered by factors such as distributed ownership of information, incompatible data storage and analysis programs, and patient privacy concerns. Moreover, because data are not widely shared, few data mining algorithms have been tested on andmore » applied to diverse health indicator data. This project addressed both integration of multiple data sources and development and integration of analytical tools for rapid detection of disease outbreaks. As a first prototype, we developed an application to query and display distributed patient records. This application incorporated need-to-know access control and incorporated data from standard commercial databases. We developed and tested two different algorithms for outbreak recognition. The first is a pattern recognition technique that searches for space-time data clusters that may signal a disease outbreak. The second is a genetic algorithm to design and train neural networks (GANN) that we applied toward disease forecasting. We tested these algorithms against influenza, respiratory illness, and Dengue Fever data. Through this LDRD in combination with other internal funding, we delivered a distributed simulation capability to synthesize disparate information and models for earlier recognition and improved decision-making in the event of a biological attack. The architecture incorporates user feedback and control so that a user's decision inputs can impact the scenario outcome as well as integrated security and role-based access-control for communicating

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

PubMed

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Quantitative tools link portfolio management with use of technology

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

Anderson, R.N.; Boulanger, A.; Amaefule, J.

1998-11-30

The exploration and production (E and P) business is in the midst of a major transformation from an emphasis on cost-cutting to more diverse portfolio management practices. The industry has found that it is not easy to simultaneously optimize net present value (NPV), return on investment (ROI), and long-term growth. The result has been the adaptation of quantitative business practices that rival their subsurface geological equivalents in sophistication and complexity. The computational tools assess the risk-reward tradeoffs inherent in the upstream linkages between (1) the application of advanced technologies to improve success in exploration and in exploitation (reservoir evaluation, drilling,more » producing, and delivery to market) and (2) the maximization of both short- and long-term profitability. Exploitation is a critical link to the industry`s E and P profitability, as can be seen from the correlation between earnings growth of the international majors and production growth. The paper discusses the use of tools to optimize exploitation.« less

Quantitative imaging with fluorescent biosensors.

PubMed

Okumoto, Sakiko; Jones, Alexander; Frommer, Wolf B

2012-01-01

Molecular activities are highly dynamic and can occur locally in subcellular domains or compartments. Neighboring cells in the same tissue can exist in different states. Therefore, quantitative information on the cellular and subcellular dynamics of ions, signaling molecules, and metabolites is critical for functional understanding of organisms. Mass spectrometry is generally used for monitoring ions and metabolites; however, its temporal and spatial resolution are limited. Fluorescent proteins have revolutionized many areas of biology-e.g., fluorescent proteins can report on gene expression or protein localization in real time-yet promoter-based reporters are often slow to report physiologically relevant changes such as calcium oscillations. Therefore, novel tools are required that can be deployed in specific cells and targeted to subcellular compartments in order to quantify target molecule dynamics directly. We require tools that can measure enzyme activities, protein dynamics, and biophysical processes (e.g., membrane potential or molecular tension) with subcellular resolution. Today, we have an extensive suite of tools at our disposal to address these challenges, including translocation sensors, fluorescence-intensity sensors, and Förster resonance energy transfer sensors. This review summarizes sensor design principles, provides a database of sensors for more than 70 different analytes/processes, and gives examples of applications in quantitative live cell imaging.

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.

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.

Harmonization of strategies for the validation of quantitative analytical procedures. A SFSTP proposal--Part I.

PubMed

Hubert, Ph; Nguyen-Huu, J-J; Boulanger, B; Chapuzet, E; Chiap, P; Cohen, N; Compagnon, P-A; Dewé, W; Feinberg, M; Lallier, M; Laurentie, M; Mercier, N; Muzard, G; Nivet, C; Valat, L

2004-11-15

This paper is the first part of a summary report of a new commission of the Société Française des Sciences et Techniques Pharmaceutiques (SFSTP). The main objective of this commission was the harmonization of approaches for the validation of quantitative analytical procedures. Indeed, the principle of the validation of theses procedures is today widely spread in all the domains of activities where measurements are made. Nevertheless, this simple question of acceptability or not of an analytical procedure for a given application, remains incompletely determined in several cases despite the various regulations relating to the good practices (GLP, GMP, ...) and other documents of normative character (ISO, ICH, FDA, ...). There are many official documents describing the criteria of validation to be tested, but they do not propose any experimental protocol and limit themselves most often to the general concepts. For those reasons, two previous SFSTP commissions elaborated validation guides to concretely help the industrial scientists in charge of drug development to apply those regulatory recommendations. If these two first guides widely contributed to the use and progress of analytical validations, they present, nevertheless, weaknesses regarding the conclusions of the performed statistical tests and the decisions to be made with respect to the acceptance limits defined by the use of an analytical procedure. The present paper proposes to review even the bases of the analytical validation for developing harmonized approach, by distinguishing notably the diagnosis rules and the decision rules. This latter rule is based on the use of the accuracy profile, uses the notion of total error and allows to simplify the approach of the validation of an analytical procedure while checking the associated risk to its usage. Thanks to this novel validation approach, it is possible to unambiguously demonstrate the fitness for purpose of a new method as stated in all regulatory

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

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 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.

Quantitative proteomics in the field of microbiology.

PubMed

Otto, Andreas; Becher, Dörte; Schmidt, Frank

2014-03-01

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Targeted Quantitation of Proteins by Mass Spectrometry

PubMed Central

2013-01-01

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement. PMID:23517332

Targeted quantitation of proteins by mass spectrometry.

PubMed

Liebler, Daniel C; Zimmerman, Lisa J

2013-06-04

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement.

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.

Qualitative and Quantitative Management Tools Used by Financial Officers in Public Research Universities

ERIC Educational Resources Information Center

Trexler, Grant Lewis

2012-01-01

This dissertation set out to identify effective qualitative and quantitative management tools used by financial officers (CFOs) in carrying out their management functions of planning, decision making, organizing, staffing, communicating, motivating, leading and controlling at a public research university. In addition, impediments to the use of…

Challenges in Higher Education Research: The Use of Quantitative Tools in Comparative Analyses

ERIC Educational Resources Information Center

Reale, Emanuela

2014-01-01

Despite the value of the comparative perspective for the study of higher education is widely recognised, there is little consensus about the specific methodological approaches. Quantitative tools outlined their relevance for addressing comparative analyses since they are supposed to reducing the complexity, finding out and graduating similarities…

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

NASA Astrophysics Data System (ADS)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

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.

Thin silica shell coated Ag assembled nanostructures for expanding generality of SERS analytes

PubMed Central

Kang, Yoo-Lee; Lee, Minwoo; Kang, Homan; Kim, Jaehi; Pham, Xuan-Hung; Kim, Tae Han; Hahm, Eunil; Lee, Yoon-Sik; Jeong, Dae Hong

2017-01-01

Surface-enhanced Raman scattering (SERS) provides a unique non-destructive spectroscopic fingerprint for chemical detection. However, intrinsic differences in affinity of analyte molecules to metal surface hinder SERS as a universal quantitative detection tool for various analyte molecules simultaneously. This must be overcome while keeping close proximity of analyte molecules to the metal surface. Moreover, assembled metal nanoparticles (NPs) structures might be beneficial for sensitive and reliable detection of chemicals than single NP structures. For this purpose, here we introduce thin silica-coated and assembled Ag NPs (SiO2@Ag@SiO2 NPs) for simultaneous and quantitative detection of chemicals that have different intrinsic affinities to silver metal. These SiO2@Ag@SiO2 NPs could detect each SERS peak of aniline or 4-aminothiophenol (4-ATP) from the mixture with limits of detection (LOD) of 93 ppm and 54 ppb, respectively. E-field distribution based on interparticle distance was simulated using discrete dipole approximation (DDA) calculation to gain insight into enhanced scattering of these thin silica coated Ag NP assemblies. These NPs were successfully applied to detect aniline in river water and tap water. Results suggest that SiO2@Ag@SiO2 NP-based SERS detection systems can be used as a simple and universal detection tool for environment pollutants and food safety. PMID:28570633

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...

Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities.

PubMed

Ramanujan, Devarajan; Bernstein, William Z; Chandrasegaran, Senthil K; Ramani, Karthik

2017-01-01

The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sense-making in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human-experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages-design, manufacturing, distribution & supply chain, use-phase, end-of-life, as well as life cycle assessment. Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

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…

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.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma*

PubMed Central

Abbatiello, Susan E.; Schilling, Birgit; Mani, D. R.; Zimmerman, Lisa J.; Hall, Steven C.; MacLean, Brendan; Albertolle, Matthew; Allen, Simon; Burgess, Michael; Cusack, Michael P.; Gosh, Mousumi; Hedrick, Victoria; Held, Jason M.; Inerowicz, H. Dorota; Jackson, Angela; Keshishian, Hasmik; Kinsinger, Christopher R.; Lyssand, John; Makowski, Lee; Mesri, Mehdi; Rodriguez, Henry; Rudnick, Paul; Sadowski, Pawel; Sedransk, Nell; Shaddox, Kent; Skates, Stephen J.; Kuhn, Eric; Smith, Derek; Whiteaker, Jeffery R.; Whitwell, Corbin; Zhang, Shucha; Borchers, Christoph H.; Fisher, Susan J.; Gibson, Bradford W.; Liebler, Daniel C.; MacCoss, Michael J.; Neubert, Thomas A.; Paulovich, Amanda G.; Regnier, Fred E.; Tempst, Paul; Carr, Steven A.

2015-01-01

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC

Analytical Tools for Cloudscope Ice Measurement

NASA Technical Reports Server (NTRS)

Arnott, W. Patrick

1998-01-01

The cloudscope is a ground or aircraft instrument for viewing ice crystals impacted on a sapphire window. It is essentially a simple optical microscope with an attached compact CCD video camera whose output is recorded on a Hi-8 mm video cassette recorder equipped with digital time and date recording capability. In aircraft operation the window is at a stagnation point of the flow so adiabatic compression heats the window to sublimate the ice crystals so that later impacting crystals can be imaged as well. A film heater is used for ground based operation to provide sublimation, and it can also be used to provide extra heat for aircraft operation. The compact video camera can be focused manually by the operator, and a beam splitter - miniature bulb combination provide illumination for night operation. Several shutter speeds are available to accommodate daytime illumination conditions by direct sunlight. The video images can be directly used to qualitatively assess the crystal content of cirrus clouds and contrails. Quantitative size spectra are obtained with the tools described in this report. Selected portions of the video images are digitized using a PCI bus frame grabber to form a short movie segment or stack using NIH (National Institute of Health) Image software with custom macros developed at DRI. The stack can be Fourier transform filtered with custom, easy to design filters to reduce most objectionable video artifacts. Particle quantification of each slice of the stack is performed using digital image analysis. Data recorded for each particle include particle number and centroid, frame number in the stack, particle area, perimeter, equivalent ellipse maximum and minimum radii, ellipse angle, and pixel number. Each valid particle in the stack is stamped with a unique number. This output can be used to obtain a semiquantitative appreciation of the crystal content. The particle information becomes the raw input for a subsequent program (FORTRAN) that

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:…

Edesign: Primer and Enhanced Internal Probe Design Tool for Quantitative PCR Experiments and Genotyping Assays.

PubMed

Kimura, Yasumasa; Soma, Takahiro; Kasahara, Naoko; Delobel, Diane; Hanami, Takeshi; Tanaka, Yuki; de Hoon, Michiel J L; Hayashizaki, Yoshihide; Usui, Kengo; Harbers, Matthias

2016-01-01

Analytical PCR experiments preferably use internal probes for monitoring the amplification reaction and specific detection of the amplicon. Such internal probes have to be designed in close context with the amplification primers, and may require additional considerations for the detection of genetic variations. Here we describe Edesign, a new online and stand-alone tool for designing sets of PCR primers together with an internal probe for conducting quantitative real-time PCR (qPCR) and genotypic experiments. Edesign can be used for selecting standard DNA oligonucleotides like for instance TaqMan probes, but has been further extended with new functions and enhanced design features for Eprobes. Eprobes, with their single thiazole orange-labelled nucleotide, allow for highly sensitive genotypic assays because of their higher DNA binding affinity as compared to standard DNA oligonucleotides. Using new thermodynamic parameters, Edesign considers unique features of Eprobes during primer and probe design for establishing qPCR experiments and genotyping by melting curve analysis. Additional functions in Edesign allow probe design for effective discrimination between wild-type sequences and genetic variations either using standard DNA oligonucleotides or Eprobes. Edesign can be freely accessed online at http://www.dnaform.com/edesign2/, and the source code is available for download.

Edesign: Primer and Enhanced Internal Probe Design Tool for Quantitative PCR Experiments and Genotyping Assays

PubMed Central

Kasahara, Naoko; Delobel, Diane; Hanami, Takeshi; Tanaka, Yuki; de Hoon, Michiel J. L.; Hayashizaki, Yoshihide; Usui, Kengo; Harbers, Matthias

2016-01-01

Analytical PCR experiments preferably use internal probes for monitoring the amplification reaction and specific detection of the amplicon. Such internal probes have to be designed in close context with the amplification primers, and may require additional considerations for the detection of genetic variations. Here we describe Edesign, a new online and stand-alone tool for designing sets of PCR primers together with an internal probe for conducting quantitative real-time PCR (qPCR) and genotypic experiments. Edesign can be used for selecting standard DNA oligonucleotides like for instance TaqMan probes, but has been further extended with new functions and enhanced design features for Eprobes. Eprobes, with their single thiazole orange-labelled nucleotide, allow for highly sensitive genotypic assays because of their higher DNA binding affinity as compared to standard DNA oligonucleotides. Using new thermodynamic parameters, Edesign considers unique features of Eprobes during primer and probe design for establishing qPCR experiments and genotyping by melting curve analysis. Additional functions in Edesign allow probe design for effective discrimination between wild-type sequences and genetic variations either using standard DNA oligonucleotides or Eprobes. Edesign can be freely accessed online at http://www.dnaform.com/edesign2/, and the source code is available for download. PMID:26863543

Analytical validation of quantitative immunohistochemical assays of tumor infiltrating lymphocyte biomarkers.

PubMed

Singh, U; Cui, Y; Dimaano, N; Mehta, S; Pruitt, S K; Yearley, J; Laterza, O F; Juco, J W; Dogdas, B

2018-06-04

Tumor infiltrating lymphocytes (TIL), especially T-cells, have both prognostic and therapeutic applications. The presence of CD8+ effector T-cells and the ratio of CD8+ cells to FOXP3+ regulatory T-cells have been used as biomarkers of disease prognosis to predict response to various immunotherapies. Blocking the interaction between inhibitory receptors on T-cells and their ligands with therapeutic antibodies including atezolizumab, nivolumab, pembrolizumab and tremelimumab increases the immune response against cancer cells and has shown significant improvement in clinical benefits and survival in several different tumor types. The improved clinical outcome is presumed to be associated with a higher tumor infiltration; therefore, it is thought that more accurate methods for measuring the amount of TIL could assist prognosis and predict treatment response. We have developed and validated quantitative immunohistochemistry (IHC) assays for CD3, CD8 and FOXP3 for immunophenotyping T-lymphocytes in tumor tissue. Various types of formalin fixed, paraffin embedded (FFPE) tumor tissues were immunolabeled with anti-CD3, anti-CD8 and anti-FOXP3 antibodies using an IHC autostainer. The tumor area of stained tissues, including the invasive margin of the tumor, was scored by a pathologist (visual scoring) and by computer-based quantitative image analysis. Two image analysis scores were obtained for the staining of each biomarker: the percent positive cells in the tumor area and positive cells/mm 2 tumor area. Comparison of visual vs. image analysis scoring methods using regression analysis showed high correlation and indicated that quantitative image analysis can be used to score the number of positive cells in IHC stained slides. To demonstrate that the IHC assays produce consistent results in normal daily testing, we evaluated the specificity, sensitivity and reproducibility of the IHC assays using both visual and image analysis scoring methods. We found that CD3, CD8 and

Information Technology Tools Analysis in Quantitative Courses of IT-Management (Case Study: M.Sc.-Tehran University)

ERIC Educational Resources Information Center

Eshlaghy, Abbas Toloie; Kaveh, Haydeh

2009-01-01

The purpose of this study was to determine the most suitable ICT-based education and define the most suitable e-content creation tools for quantitative courses in the IT-management Masters program. ICT-based tools and technologies are divided in to three categories: the creation of e-content, the offering of e-content, and access to e-content. In…

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.

Development and Validation of a Quantitative Framework and Management Expectation Tool for the Selection of Bioremediation Approaches at Chlorinated Ethene Sites

DTIC Science & Technology

2015-12-01

FINAL REPORT Development and Validation of a Quantitative Framework and Management Expectation Tool for the Selection of Bioremediation ...TITLE AND SUBTITLE Development and Validation of a Quantitative Framework and Management Expectation Tool for the Selection of Bioremediation ...project ER-201129 was to develop and validate a framework used to make bioremediation decisions based on site-specific physical and biogeochemical

Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance.

PubMed

Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W

2015-08-01

This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck. © The Author(s) 2014.

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

On the accuracy of analytical models of impurity segregation during directional melt crystallization and their applicability for quantitative calculations

NASA Astrophysics Data System (ADS)

Voloshin, A. E.; Prostomolotov, A. I.; Verezub, N. A.

2016-11-01

The paper deals with the analysis of the accuracy of some one-dimensional (1D) analytical models of the axial distribution of impurities in the crystal grown from a melt. The models proposed by Burton-Prim-Slichter, Ostrogorsky-Muller and Garandet with co-authors are considered, these models are compared to the results of a two-dimensional (2D) numerical simulation. Stationary solutions as well as solutions for the initial transient regime obtained using these models are considered. The sources of errors are analyzed, a conclusion is made about the applicability of 1D analytical models for quantitative estimates of impurity incorporation into the crystal sample as well as for the solution of the inverse problems.

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.

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…

Effects of fecal sampling on preanalytical and analytical phases in quantitative fecal immunochemical tests for hemoglobin.

PubMed

Rapi, Stefano; Berardi, Margherita; Cellai, Filippo; Ciattini, Samuele; Chelazzi, Laura; Ognibene, Agostino; Rubeca, Tiziana

2017-07-24

Information on preanalytical variability is mandatory to bring laboratories up to ISO 15189 requirements. Fecal sampling is greatly affected by lack of harmonization in laboratory medicine. The aims of this study were to obtain information on the devices used for fecal sampling and to explore the effect of different amounts of feces on the results from the fecal immunochemical test for hemoglobin (FIT-Hb). Four commercial sample collection devices for quantitative FIT-Hb measurements were investigated. The volume of interest (VOI) of the probes was measured from diameter and geometry. Quantitative measurements of the mass of feces were carried out by gravimetry. The effects of an increased amount of feces on the analytical environment were investigated measuring the Hb values with a single analytical method. VOI was 8.22, 7.1 and 9.44 mm3 for probes that collected a target of 10 mg of feces, and 3.08 mm3 for one probe that targeted 2 mg of feces. The ratio between recovered and target amounts of devices ranged from 56% to 121%. Different changes in the measured Hb values were observed, in adding increasing amounts of feces in commercial buffers. The amounts of collected materials are related to the design of probes. Three out 4 manufacturers declare the same target amount using different sampling volumes and obtaining different amounts of collected materials. The introduction of a standard probes to reduce preanalytical variability could be an useful step for fecal test harmonization and to fulfill the ISO 15189 requirements.

A survey of tools for the analysis of quantitative PCR (qPCR) data.

PubMed

Pabinger, Stephan; Rödiger, Stefan; Kriegner, Albert; Vierlinger, Klemens; Weinhäusel, Andreas

2014-09-01

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Use of quantitative pharmacology tools to improve malaria treatments.

PubMed

Davis, Timothy M E; Moore, Brioni R; Salman, Sam; Page-Sharp, Madhu; Batty, Kevin T; Manning, Laurens

2016-01-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) data to inform antimalarial treatment regimens has accelerated in the past few decades, due in no small part to the stimulus provided by progressive development of parasite resistance to most of the currently available drugs. An understanding of the disposition, interactions, efficacy and toxicity of the mainstay of contemporary antimalarial treatment, artemisinin combination therapy (ACT), has been facilitated by PK/PD studies which have been used to refine treatment regimens across the spectrum of disease, especially in special groups including young children and pregnant women. The present review highlights recent clinically-important examples of the ways in which these quantitative pharmacology tools have been applied to improve ACT, as well as 8-aminoquinoline use and the characterisation of novel antimalarial therapies such as the spiroindolones.

Challenges and perspectives in quantitative NMR.

PubMed

Giraudeau, Patrick

2017-01-01

This perspective article summarizes, from the author's point of view at the beginning of 2016, the major challenges and perspectives in the field of quantitative NMR. The key concepts in quantitative NMR are first summarized; then, the most recent evolutions in terms of resolution and sensitivity are discussed, as well as some potential future research directions in this field. A particular focus is made on methodologies capable of boosting the resolution and sensitivity of quantitative NMR, which could open application perspectives in fields where the sample complexity and the analyte concentrations are particularly challenging. These include multi-dimensional quantitative NMR and hyperpolarization techniques such as para-hydrogen-induced polarization or dynamic nuclear polarization. Because quantitative NMR cannot be dissociated from the key concepts of analytical chemistry, i.e. trueness and precision, the methodological developments are systematically described together with their level of analytical performance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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…

Evaluation and performance of desorption electrospray ionization using a triple quadrupole mass spectrometer for quantitation of pharmaceuticals in plasma.

PubMed

Kennedy, Joseph H; Wiseman, Justin M

2010-02-01

The present work describes the methodology and investigates the performance of desorption electrospray ionization (DESI) combined with a triple quadrupole mass spectrometer for the quantitation of small drug molecules in human plasma. Amoxepine, atenolol, carbamazepine, clozapine, prazosin, propranolol and verapamil were selected as target analytes while terfenadine was selected as the internal standard common to each of the analytes. Protein precipitation of human plasma using acetonitrile was utilized for all samples. Limits of detection were determined for all analytes in plasma and shown to be in the range 0.2-40 ng/mL. Quantitative analysis of amoxepine, prazosin and verapamil was performed over the range 20-7400 ng/mL and shown to be linear in all cases with R(2) >0.99. In most cases, the precision (relative standard deviation) and accuracy (relative error) of each method were less than or equal to 20%, respectively. The performance of the combined techniques made it possible to analyze each sample in 15 s illustrating DESI tandem mass spectrometry (MS/MS) as powerful tool for the quantitation of analytes in deproteinized human plasma. Copyright 2010 John Wiley & Sons, Ltd.

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...

Analytical Tools for Space Suit Design

NASA Technical Reports Server (NTRS)

Aitchison, Lindsay

2011-01-01

As indicated by the implementation of multiple small project teams within the agency, NASA is adopting a lean approach to hardware development that emphasizes quick product realization and rapid response to shifting program and agency goals. Over the past two decades, space suit design has been evolutionary in approach with emphasis on building prototypes then testing with the largest practical range of subjects possible. The results of these efforts show continuous improvement but make scaled design and performance predictions almost impossible with limited budgets and little time. Thus, in an effort to start changing the way NASA approaches space suit design and analysis, the Advanced Space Suit group has initiated the development of an integrated design and analysis tool. It is a multi-year-if not decadal-development effort that, when fully implemented, is envisioned to generate analysis of any given space suit architecture or, conversely, predictions of ideal space suit architectures given specific mission parameters. The master tool will exchange information to and from a set of five sub-tool groups in order to generate the desired output. The basic functions of each sub-tool group, the initial relationships between the sub-tools, and a comparison to state of the art software and tools are discussed.

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells.

PubMed

Andrews, J O; Conway, W; Cho, W -K; Narayanan, A; Spille, J -H; Jayanth, N; Inoue, T; Mullen, S; Thaler, J; Cissé, I I

2018-05-09

We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.

Affinity for Quantitative Tools: Undergraduate Marketing Students Moving beyond Quantitative Anxiety

ERIC Educational Resources Information Center

Tarasi, Crina O.; Wilson, J. Holton; Puri, Cheenu; Divine, Richard L.

2013-01-01

Marketing students are known as less likely to have an affinity for the quantitative aspects of the marketing discipline. In this article, we study the reasons why this might be true and develop a parsimonious 20-item scale for measuring quantitative affinity in undergraduate marketing students. The scale was administered to a sample of business…

Studying Behaviors Among Neurosurgery Residents Using Web 2.0 Analytic Tools.

PubMed

Davidson, Benjamin; Alotaibi, Naif M; Guha, Daipayan; Amaral, Sandi; Kulkarni, Abhaya V; Lozano, Andres M

Web 2.0 technologies (e.g., blogs, social networks, and wikis) are increasingly being used by medical schools and postgraduate training programs as tools for information dissemination. These technologies offer the unique opportunity to track metrics of user engagement and interaction. Here, we employ Web 2.0 tools to assess academic behaviors among neurosurgery residents. We performed a retrospective review of all educational lectures, part of the core Neurosurgery Residency curriculum at the University of Toronto, posted on our teaching website (www.TheBrainSchool.net). Our website was developed using publicly available Web 2.0 platforms. Lecture usage was assessed by the number of clicks, and associations were explored with lecturer academic position, timing of examinations, and lecture/subspecialty topic. The overall number of clicks on 77 lectures was 1079. Most of these clicks were occurring during the in-training examination month (43%). Click numbers were significantly higher on lectures presented by faculty (mean = 18.6, standard deviation ± 4.1) compared to those delivered by residents (mean = 8.4, standard deviation ± 2.1) (p = 0.031). Lectures covering topics in functional neurosurgery received the most clicks (47%), followed by pediatric neurosurgery (22%). This study demonstrates the value of Web 2.0 analytic tools in examining resident study behavior. Residents tend to "cram" by downloading lectures in the same month of training examinations and display a preference for faculty-delivered lectures. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Oxygen octahedra picker: A software tool to extract quantitative information from STEM images.

PubMed

Wang, Yi; Salzberger, Ute; Sigle, Wilfried; Eren Suyolcu, Y; van Aken, Peter A

2016-09-01

In perovskite oxide based materials and hetero-structures there are often strong correlations between oxygen octahedral distortions and functionality. Thus, atomistic understanding of the octahedral distortion, which requires accurate measurements of atomic column positions, will greatly help to engineer their properties. Here, we report the development of a software tool to extract quantitative information of the lattice and of BO6 octahedral distortions from STEM images. Center-of-mass and 2D Gaussian fitting methods are implemented to locate positions of individual atom columns. The precision of atomic column distance measurements is evaluated on both simulated and experimental images. The application of the software tool is demonstrated using practical examples. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

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.

Process analytical technology in the pharmaceutical industry: a toolkit for continuous improvement.

PubMed

Scott, Bradley; Wilcock, Anne

2006-01-01

Process analytical technology (PAT) refers to a series of tools used to ensure that quality is built into products while at the same time improving the understanding of processes, increasing efficiency, and decreasing costs. It has not been widely adopted by the pharmaceutical industry. As the setting for this paper, the current pharmaceutical manufacturing paradigm and PAT guidance to date are discussed prior to the review of PAT principles and tools, benefits, and challenges. The PAT toolkit contains process analyzers, multivariate analysis tools, process control tools, and continuous improvement/knowledge management/information technology systems. The integration and implementation of these tools is complex, and has resulted in uncertainty with respect to both regulation and validation. The paucity of staff knowledgeable in this area may complicate adoption. Studies to quantitate the benefits resulting from the adoption of PAT within the pharmaceutical industry would be a valuable addition to the qualitative studies that are currently available.

Confocal Raman Microscopy for pH-Gradient Preconcentration and Quantitative Analyte Detection in Optically Trapped Phospholipid Vesicles.

PubMed

Hardcastle, Chris D; Harris, Joel M

2015-08-04

The ability of a vesicle membrane to preserve a pH gradient, while allowing for diffusion of neutral molecules across the phospholipid bilayer, can provide the isolation and preconcentration of ionizable compounds within the vesicle interior. In this work, confocal Raman microscopy is used to observe (in situ) the pH-gradient preconcentration of compounds into individual optically trapped vesicles that provide sub-femtoliter collectors for small-volume samples. The concentration of analyte accumulated in the vesicle interior is determined relative to a perchlorate-ion internal standard, preloaded into the vesicle along with a high-concentration buffer. As a guide to the experiments, a model for the transfer of analyte into the vesicle based on acid-base equilibria is developed to predict the concentration enrichment as a function of source-phase pH and analyte concentration. To test the concept, the accumulation of benzyldimethylamine (BDMA) was measured within individual 1 μm phospholipid vesicles having a stable initial pH that is 7 units lower than the source phase. For low analyte concentrations in the source phase (100 nM), a concentration enrichment into the vesicle interior of (5.2 ± 0.4) × 10(5) was observed, in agreement with the model predictions. Detection of BDMA from a 25 nM source-phase sample was demonstrated, a noteworthy result for an unenhanced Raman scattering measurement. The developed model accurately predicts the falloff of enrichment (and measurement sensitivity) at higher analyte concentrations, where the transfer of greater amounts of BDMA into the vesicle titrates the internal buffer and decreases the pH gradient. The predictable calibration response over 4 orders of magnitude in source-phase concentration makes it suitable for quantitative analysis of ionizable compounds from small-volume samples. The kinetics of analyte accumulation are relatively fast (∼15 min) and are consistent with the rate of transfer of a polar aromatic

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.

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...

Multiplexed and Microparticle-based Analyses: Quantitative Tools for the Large-Scale Analysis of Biological Systems

PubMed Central

Nolan, John P.; Mandy, Francis

2008-01-01

While the term flow cytometry refers to the measurement of cells, the approach of making sensitive multiparameter optical measurements in a flowing sample stream is a very general analytical approach. The past few years have seen an explosion in the application of flow cytometry technology for molecular analysis and measurements using micro-particles as solid supports. While microsphere-based molecular analyses using flow cytometry date back three decades, the need for highly parallel quantitative molecular measurements that has arisen from various genomic and proteomic advances has driven the development in particle encoding technology to enable highly multiplexed assays. Multiplexed particle-based immunoassays are now common place, and new assays to study genes, protein function, and molecular assembly. Numerous efforts are underway to extend the multiplexing capabilities of microparticle-based assays through new approaches to particle encoding and analyte reporting. The impact of these developments will be seen in the basic research and clinical laboratories, as well as in drug development. PMID:16604537

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3-D reconstruction.

PubMed

Hein, L R

2001-10-01

A set of NIH Image macro programs was developed to make qualitative and quantitative analyses from digital stereo pictures produced by scanning electron microscopes. These tools were designed for image alignment, anaglyph representation, animation, reconstruction of true elevation surfaces, reconstruction of elevation profiles, true-scale elevation mapping and, for the quantitative approach, surface area and roughness calculations. Limitations on time processing, scanning techniques and programming concepts are also discussed.

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

PubMed

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

2014-05-30

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

DISQOVER the Landcover - R based tools for quantitative vegetation reconstruction

NASA Astrophysics Data System (ADS)

Theuerkauf, Martin; Couwenberg, John; Kuparinen, Anna; Liebscher, Volkmar

2016-04-01

Quantitative methods have gained increasing attention in the field of vegetation reconstruction over the past decade. The DISQOVER package implements key tools in the R programming environment for statistical computing. This implementation has three main goals: 1) Provide a user-friendly, transparent, and open implementation of the methods 2) Provide full flexibility in all parameters (including the underlying pollen dispersal model) 3) Provide a sandbox for testing the sensitivity of the methods. We illustrate the possibilities of the package with tests of the REVEALS model and of the extended downscaling approach (EDA). REVEALS (Sugita 2007) is designed to translate pollen data from large lakes into regional vegetation composition. We applied REVEALSinR on pollen data from Lake Tiefer See (NE-Germany) and validated the results with historic landcover data. The results clearly show that REVEALS is sensitive to the underlying pollen dispersal model; REVEALS performs best when applied with the state of the art Lagrangian stochastic dispersal model. REVEALS applications with the conventional Gauss model can produce realistic results, but only if unrealistic pollen productivity estimates are used. The EDA (Theuerkauf et al. 2014) employs pollen data from many sites across a landscape to explore whether species distributions in the past were related to know stable patterns in the landscape, e.g. the distribution of soil types. The approach had so far only been implemented in simple settings with few taxa. Tests with EDAinR show that it produces sharp results in complex settings with many taxa as well. The DISQOVER package is open source software, available from disqover.uni-greifswald.de. This website can be used as a platform to discuss and improve quantitative methods in vegetation reconstruction. To introduce the tool we plan a short course in autumn of this year. This study is a contribution to the Virtual Institute of Integrated Climate and Landscape Evolution

Validity of a quantitative clinical measurement tool of trunk posture in idiopathic scoliosis.

PubMed

Fortin, Carole; Feldman, Debbie E; Cheriet, Farida; Labelle, Hubert

2010-09-01

Concurrent validity between postural indices obtained from digital photographs (two-dimensional [2D]), surface topography imaging (three-dimensional [3D]), and radiographs. To assess the validity of a quantitative clinical postural assessment tool of the trunk based on photographs (2D) as compared to a surface topography system (3D) as well as indices calculated from radiographs. To monitor progression of scoliosis or change in posture over time in young persons with idiopathic scoliosis (IS), noninvasive and nonionizing methods are recommended. In a clinical setting, posture can be quite easily assessed by calculating key postural indices from photographs. Quantitative postural indices of 70 subjects aged 10 to 20 years old with IS (Cobb angle, 15 degrees -60 degrees) were measured from photographs and from 3D trunk surface images taken in the standing position. Shoulder, scapula, trunk list, pelvis, scoliosis, and waist angles indices were calculated with specially designed software. Frontal and sagittal Cobb angles and trunk list were also calculated on radiographs. The Pearson correlation coefficients (r) was used to estimate concurrent validity of the 2D clinical postural tool of the trunk with indices extracted from the 3D system and with those obtained from radiographs. The correlation between 2D and 3D indices was good to excellent for shoulder, pelvis, trunk list, and thoracic scoliosis (0.81>r<0.97; P<0.01) but fair to moderate for thoracic kyphosis, lumbar lordosis, and thoracolumbar or lumbar scoliosis (0.30>r<0.56; P<0.05). The correlation between 2D and radiograph spinal indices was fair to good (-0.33 to -0.80 with Cobb angles and 0.76 for trunk list; P<0.05). This tool will facilitate clinical practice by monitoring trunk posture among persons with IS. Further, it may contribute to a reduction in the use of radiographs to monitor scoliosis progression.

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

Assessing analytical comparability of biosimilars: GCSF as a case study.

PubMed

Nupur, Neh; Singh, Sumit Kumar; Narula, Gunjan; Rathore, Anurag S

2016-10-01

The biosimilar industry is witnessing an unprecedented growth with the newer therapeutics increasing in complexity over time. A key step towards development of a biosimilar is to establish analytical comparability with the innovator product, which would otherwise affect the safety/efficacy profile of the product. Choosing appropriate analytical tools that can fulfil this objective by qualitatively and/or quantitatively assessing the critical quality attributes (CQAs) of the product is highly critical for establishing equivalence. These CQAs cover the primary and higher order structures of the product, product related variants and impurities, as well as process related impurities, and host cell related impurities. In the present work, we use such an analytical platform for assessing comparability of five approved Granulocyte Colony Stimulating Factor (GCSF) biosimilars (Emgrast, Lupifil, Colstim, Neukine and Grafeel) to the innovator product, Neupogen(®). The comparability studies involve assessing structural homogeneity, identity, secondary structure, and product related modifications. Physicochemical analytical tools include peptide mapping with mass determination, circular dichroism (CD) spectroscopy, reverse phase chromatography (RPC) and size exclusion chromatography (SEC) have been used in this exercise. Bioactivity assessment include comparison of relative potency through in vitro cell proliferation assays. The results from extensive analytical examination offer robust evidence of structural and biological similarity of the products under consideration with the pertinent innovator product. For the most part, the biosimilar drugs were found to be comparable to the innovator drug anomaly that was identified was that three of the biosimilars had a typical variant which was reported as an oxidized species in the literature. But, upon further investigation using RPC-FLD and ESI-MS we found that this is likely a conformational variant of the biotherapeutic been

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

Quantitative assessment of prevalence of pre-analytical variables and their effect on coagulation assay. Can intervention improve patient safety?

PubMed

Bhushan, Ravi; Sen, Arijit

2017-04-01

Very few Indian studies exist on evaluation of pre-analytical variables affecting "Prothrombin Time" the commonest coagulation assay performed. The study was performed in an Indian tertiary care setting with an aim to assess quantitatively the prevalence of pre-analytical variables and their effects on the results (patient safety), for Prothrombin time test. The study also evaluated their effects on the result and whether intervention, did correct the results. The firstly evaluated the prevalence for various pre-analytical variables detected in samples sent for Prothrombin Time testing. These samples with the detected variables wherever possible were tested and result noted. The samples from the same patients were repeated and retested ensuring that no pre-analytical variable is present. The results were again noted to check for difference the intervention produced. The study evaluated 9989 samples received for PT/INR over a period of 18 months. The prevalence of different pre-analytical variables was found to be 862 (8.63%). The proportion of various pre-analytical variables detected were haemolysed samples 515 (5.16%), over filled vacutainers 62 (0.62%), under filled vacutainers 39 (0.39%), low values 205 (2.05%), clotted samples 11 (0.11%), wrong labeling 4 (0.04%), wrong vacutainer use 2 (0.02%), chylous samples 7 (0.07%) and samples with more than one variable 17 (0.17%). The comparison of percentage of samples showing errors were noted for the first variables since they could be tested with and without the variable in place. The reduction in error percentage was 91.5%, 69.2%, 81.5% and 95.4% post intervention for haemolysed, overfilled, under filled and samples collected with excess pressure at phlebotomy respectively. Correcting the variables did reduce the error percentage to a great extent in these four variables and hence the variables are found to affect "Prothrombin Time" testing and can hamper patient safety.

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

PubMed

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Energy-dispersive X-ray fluorescence systems as analytical tool for assessment of contaminated soils.

PubMed

Vanhoof, Chris; Corthouts, Valère; Tirez, Kristof

2004-04-01

To determine the heavy metal content in soil samples at contaminated locations, a static and time consuming procedure is used in most cases. Soil samples are collected and analyzed in the laboratory at high quality and high analytical costs. The demand by government and consultants for a more dynamic approach and by customers requiring performances in which analyses are performed in the field with immediate feedback of the analytical results, is growing. Especially during the follow-up of remediation projects or during the determination of the sampling strategy, field analyses are advisable. For this purpose four types of ED-XRF systems, ranging from portable up to high performance laboratory systems, have been evaluated. The evaluation criteria are based on the performance characteristics for all the ED-XRF systems such as limit of detection, accuracy and the measurement uncertainty on one hand, and also the influence of the sample pretreatment on the obtained results on the other hand. The study proved that the field portable system and the bench top system, placed in a mobile van, can be applied as field techniques, resulting in semi-quantitative analytical results. A limited homogenization of the analyzed sample significantly increases the representativeness of the soil sample. The ED-XRF systems can be differentiated by their limits of detection which are a factor of 10 to 20 higher for the portable system. The accuracy of the results and the measurement uncertainty also improved using the bench top system. Therefore, the selection criteria for applicability of both field systems are based on the required detection level and also the required accuracy of the results.

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

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.

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…

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2017-12-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2018-04-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

Proteomics Is Analytical Chemistry: Fitness-for-Purpose in the Application of Top-Down and Bottom-Up Analyses.

PubMed

Coorssen, Jens R; Yergey, Alfred L

2015-12-03

Molecular mechanisms underlying health and disease function at least in part based on the flexibility and fine-tuning afforded by protein isoforms and post-translational modifications. The ability to effectively and consistently resolve these protein species or proteoforms, as well as assess quantitative changes is therefore central to proteomic analyses. Here we discuss the pros and cons of currently available and developing analytical techniques from the perspective of the full spectrum of available tools and their current applications, emphasizing the concept of fitness-for-purpose in experimental design based on consideration of sample size and complexity; this necessarily also addresses analytical reproducibility and its variance. Data quality is considered the primary criterion, and we thus emphasize that the standards of Analytical Chemistry must apply throughout any proteomic analysis.

The combined use of analytical tools for exploring tetanus toxin and tetanus toxoid structures.

PubMed

Bayart, Caroline; Peronin, Sébastien; Jean, Elisa; Paladino, Joseph; Talaga, Philippe; Borgne, Marc Le

2017-06-01

Aldehyde detoxification is a process used to convert toxin into toxoid for vaccine applications. In the case of tetanus toxin (TT), formaldehyde is used to obtain the tetanus toxoid (TTd), which is used either for the tetanus vaccine or as carrier protein in conjugate vaccines. Several studies have already been conducted to better understand the exact mechanism of this detoxification. Those studies led to the identification of a number of formaldehyde-induced modifications on lab scale TTd samples. To obtain greater insights of the changes induced by formaldehyde, we used three industrial TTd batches to identify repeatable modifications in the detoxification process. Our strategy was to combine seven analytical tools to map these changes. Mass spectrometry (MS), colorimetric test and amino acid analysis (AAA) were used to study modifications on amino acids. SDS-PAGE, asymmetric flow field flow fractionation (AF4), fluorescence spectroscopy and circular dichroism (CD) were used to study formaldehyde modifications on the whole protein structure. We identified 41 formaldehyde-induced modifications across the 1315 amino acid primary sequence of TT. Of these, five modifications on lysine residues were repeatable across TTd batches. Changes in protein conformation were also observed using SDS-PAGE, AF4 and CD techniques. Each analytical tool brought a piece of information regarding formaldehyde induced-modifications, and all together, these methods provided a comprehensive overview of the structural changes that occurred with detoxification. These results could be the first step leading to site-directed TT mutagenesis studies that may enable the production of a non-toxic equivalent protein without using formaldehyde. Copyright © 2017 Elsevier B.V. All rights reserved.

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

PubMed

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

PubMed Central

Alaidi, Osama; Rames, Matthew J.

2016-01-01

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. PMID:26087941

Quantitative determination of a-Arbutin, ß-Arbutin, Kojic acid, nicotinamide, hydroquinone, resorcinol, 4-methoxyphenol, 4-ethoxyphenol and ascorbic acid from skin whitening Products by HPLC-UV

USDA-ARS?s Scientific Manuscript database

Development of an analytical method for the simultaneous determination of multifarious skin whitening agents will provide an efficient tool to analyze skin whitening cosmetics. An HPLC-UV method was developed for quantitative analysis of six commonly used whitening agents, a-arbutin, ß-arbutin, koji...

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.

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.

Development of a new analytical tool for assessing the mutagen 2-methyl-1,4-dinitro-pyrrole in meat products by LC-ESI-MS/MS.

PubMed

Molognoni, Luciano; Daguer, Heitor; de Sá Ploêncio, Leandro Antunes; Yotsuyanagi, Suzana Eri; da Silva Correa Lemos, Ana Lucia; Joussef, Antonio Carlos; De Dea Lindner, Juliano

2018-08-01

The use of sorbate and nitrite in meat processing may lead to the formation of 2-methyl-1,4-dinitro-pyrrole (DNMP), a mutagenic compound. This work was aimed at developing and validating an analytical method for the quantitation of DNMP by liquid chromatography-tandem mass spectrometry. Full validation was performed in accordance to Commission Decision 2002/657/EC and method applicability was checked in several samples of meat products. A simple procedure, with low temperature partitioning solid-liquid extraction, was developed. The nitrosation during the extraction was monitored by the N-nitroso-DL-pipecolic acid content. Chromatographic separation was achieved in 8 min with di-isopropyl-3-aminopropyl silane bound to hydroxylated silica as stationary phase. Samples of bacon and cooked sausage yielded the highest concentrations of DNMP (68 ± 3 and 50 ± 3 μg kg -1 , respectively). The developed method proved to be a reliable, selective, and sensitive tool for DNMP measurements in meat products. Copyright © 2018 Elsevier B.V. All rights reserved.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-03-01

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy.

PubMed

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-01-18

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in

Reverse transcription-polymerase chain reaction molecular testing of cytology specimens: Pre-analytic and analytic factors.

PubMed

Bridge, Julia A

2017-01-01

The introduction of molecular testing into cytopathology laboratory practice has expanded the types of samples considered feasible for identifying genetic alterations that play an essential role in cancer diagnosis and treatment. Reverse transcription-polymerase chain reaction (RT-PCR), a sensitive and specific technical approach for amplifying a defined segment of RNA after it has been reverse-transcribed into its DNA complement, is commonly used in clinical practice for the identification of recurrent or tumor-specific fusion gene events. Real-time RT-PCR (quantitative RT-PCR), a technical variation, also permits the quantitation of products generated during each cycle of the polymerase chain reaction process. This review addresses qualitative and quantitative pre-analytic and analytic considerations of RT-PCR as they relate to various cytologic specimens. An understanding of these aspects of genetic testing is central to attaining optimal results in the face of the challenges that cytology specimens may present. Cancer Cytopathol 2017;125:11-19. © 2016 American Cancer Society. © 2016 American Cancer Society.

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.

More Analytical Tools for Fluids Management in Space

NASA Astrophysics Data System (ADS)

Weislogel, Mark

Continued advances during the 2000-2010 decade in the analysis of a class of capillary-driven flows relevant to materials processing and fluids management aboard spacecraft have been made. The class of flows addressed concern combined forced and spontaneous capillary flows in complex containers with interior edges. Such flows are commonplace in space-based fluid systems and arise from the particular container geometry and wetting properties of the system. Important applications for this work include low-g liquid fill and/or purge operations and passive fluid phase separation operations, where the container (i.e. fuel tank, water processer, etc.) geometry possesses interior edges, and where quantitative information of fluid location, transients, flow rates, and stability is critical. Examples include the storage and handling of liquid propellants and cryogens, water conditioning for life support, fluid phase-change thermal systems, materials processing in the liquid state, on-orbit biofluids processing, among others. For a growing number of important problems, closed-form expressions to transient three-dimensional flows are possible that, as design tools, replace difficult, time-consuming, and rarely performed numerical calculations. An overview of a selection of solutions in-hand is presented with example problems solved. NASA drop tower, low-g aircraft, and ISS flight ex-periment results are employed where practical to buttress the theoretical findings. The current review builds on a similar review presented at COSPAR, 2002, for the approximate decade 1990-2000.

An analytical approach based on ESI-MS, LC-MS and PCA for the quali-quantitative analysis of cycloartane derivatives in Astragalus spp.

PubMed

Napolitano, Assunta; Akay, Seref; Mari, Angela; Bedir, Erdal; Pizza, Cosimo; Piacente, Sonia

2013-11-01

Astragalus species are widely used as health foods and dietary supplements, as well as drugs in traditional medicine. To rapidly evaluate metabolite similarities and differences among the EtOH extracts of the roots of eight commercial Astragalus spp., an approach based on direct analyses by ESI-MS followed by PCA of ESI-MS data, was carried out. Successively, quali-quantitative analyses of cycloartane derivatives in the eight Astragalus spp. by LC-ESI-MS(n) and PCA of LC-ESI-MS data were performed. This approach allowed to promptly highlighting metabolite similarities and differences among the various Astragalus spp. PCA results from LC-ESI-MS data of Astragalus samples were in reasonable agreement with both PCA results of ESI-MS data and quantitative results. This study affords an analytical method for the quali-quantitative determination of cycloartane derivatives in herbal preparations used as health and food supplements. Copyright © 2013 Elsevier B.V. All rights reserved.

Network Analytical Tool for Monitoring Global Food Safety Highlights China

PubMed Central

Nepusz, Tamás; Petróczi, Andrea; Naughton, Declan P.

2009-01-01

Background The Beijing Declaration on food safety and security was signed by over fifty countries with the aim of developing comprehensive programs for monitoring food safety and security on behalf of their citizens. Currently, comprehensive systems for food safety and security are absent in many countries, and the systems that are in place have been developed on different principles allowing poor opportunities for integration. Methodology/Principal Findings We have developed a user-friendly analytical tool based on network approaches for instant customized analysis of food alert patterns in the European dataset from the Rapid Alert System for Food and Feed. Data taken from alert logs between January 2003 – August 2008 were processed using network analysis to i) capture complexity, ii) analyze trends, and iii) predict possible effects of interventions by identifying patterns of reporting activities between countries. The detector and transgressor relationships are readily identifiable between countries which are ranked using i) Google's PageRank algorithm and ii) the HITS algorithm of Kleinberg. The program identifies Iran, China and Turkey as the transgressors with the largest number of alerts. However, when characterized by impact, counting the transgressor index and the number of countries involved, China predominates as a transgressor country. Conclusions/Significance This study reports the first development of a network analysis approach to inform countries on their transgressor and detector profiles as a user-friendly aid for the adoption of the Beijing Declaration. The ability to instantly access the country-specific components of the several thousand annual reports will enable each country to identify the major transgressors and detectors within its trading network. Moreover, the tool can be used to monitor trading countries for improved detector/transgressor ratios. PMID:19688088

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

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.

Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics.

PubMed

Marchand, Jérémy; Martineau, Estelle; Guitton, Yann; Dervilly-Pinel, Gaud; Giraudeau, Patrick

2017-02-01

Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

A miniaturized optoelectronic system for rapid quantitative label-free detection of harmful species in food

NASA Astrophysics Data System (ADS)

Raptis, Ioannis; Misiakos, Konstantinos; Makarona, Eleni; Salapatas, Alexandros; Petrou, Panagiota; Kakabakos, Sotirios; Botsialas, Athanasios; Jobst, Gerhard; Haasnoot, Willem; Fernandez-Alba, Amadeo; Lees, Michelle; Valamontes, Evangelos

2016-03-01

Optical biosensors have emerged in the past decade as the most promising candidates for portable, highly-sensitive bioanalytical systems that can be employed for in-situ measurements. In this work, a miniaturized optoelectronic system for rapid, quantitative, label-free detection of harmful species in food is presented. The proposed system has four distinctive features that can render to a powerful tool for the next generation of Point-of-Need applications, namely it accommodates the light sources and ten interferometric biosensors on a single silicon chip of a less-than-40mm2 footprint, each sensor can be individually functionalized for a specific target analyte, the encapsulation can be performed at the wafer-scale, and finally it exploits a new operation principle, Broad-band Mach-Zehnder Interferometry to ameliorate its analytical capabilities. Multi-analyte evaluation schemes for the simultaneous detection of harmful contaminants, such as mycotoxins, allergens and pesticides, proved that the proposed system is capable of detecting within short time these substances at concentrations below the limits imposed by regulatory authorities, rendering it to a novel tool for the near-future food safety applications.

Enhanced analytical sensitivity of a quantitative PCR for CMV using a modified nucleic-acid extraction procedure.

PubMed

Ferreira-Gonzalez, A; Yanovich, S; Langley, M R; Weymouth, L A; Wilkinson, D S; Garrett, C T

2000-01-01

Accurate and rapid diagnosis of CMV disease in immunocompromised individuals remains a challenge. Quantitative polymerase chain reaction (QPCR) methods for detection of CMV in peripheral blood mononuclear cells (PBMC) have improved the positive and negative predictive value of PCR for diagnosis of CMV disease. However, detection of CMV in plasma has demonstrated a lower negative predictive value for plasma as compared with PBMC. To enhance the sensitivity of the QPCR assay for plasma specimens, plasma samples were centrifuged before nucleic-acid extraction and the extracted DNA resolubilized in reduced volume. Optimization of the nucleic-acid extraction focused on decreasing or eliminating the presence of inhibitors in the pelleted plasma. Quantitation was achieved by co-amplifying an internal quantitative standard (IS) with the same primer sequences as CMV. PCR products were detected by hybridization in a 96-well microtiter plate coated with a CMV or IS specific probe. The precision of the QPCR assay for samples prepared from untreated and from pelleted plasma was then assessed. The coefficient of variation for both types of samples was almost identical and the magnitude of the coefficient of variations was reduced by a factor of ten if the data were log transformed. Linearity of the QPCR assay extended over a 3.3-log range for both types of samples but the range of linearity for pelleted plasma was 20 to 40,000 viral copies/ml (vc/ml) in contrast to 300 to 400,000 vc/ml for plasma. Thus, centrifugation of plasma before nucleic-acid extraction and resuspension of extracted CMV DNA in reduced volume enhanced the analytical sensitivity approximately tenfold over the dynamic range of the assay. Copyright 2000 Wiley-Liss, Inc.

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research.

PubMed

Ercius, Peter; Alaidi, Osama; Rames, Matthew J; Ren, Gang

2015-10-14

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. This review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis.

PubMed

Zhao, Xiaoyan; Qureshi, Ferhan; Eastman, P Scott; Manning, William C; Alexander, Claire; Robinson, William H; Hesterberg, Lyndal K

2012-04-30

Variability in pre-analytical blood sampling and handling can significantly impact results obtained in quantitative immunoassays. Understanding the impact of these variables is critical for accurate quantification and validation of biomarker measurements. Particularly, in the design and execution of large clinical trials, even small differences in sample processing and handling can have dramatic effects in analytical reliability, results interpretation, trial management and outcome. The effects of two common blood sampling methods (serum vs. plasma) and two widely-used serum handling methods (on the clot with ambient temperature shipping, "traditional", vs. centrifuged with cold chain shipping, "protocol") on protein and autoantibody concentrations were examined. Matched serum and plasma samples were collected from 32 rheumatoid arthritis (RA) patients representing a wide range of disease activity status. Additionally, a set of matched serum samples with two sample handling methods was collected. One tube was processed per manufacturer's instructions and shipped overnight on cold packs (protocol). The matched tube, without prior centrifugation, was simultaneously shipped overnight at ambient temperatures (traditional). Upon delivery, the traditional tube was centrifuged. All samples were subsequently aliquoted and frozen prior to analysis of protein and autoantibody biomarkers. Median correlation between paired serum and plasma across all autoantibody assays was 0.99 (0.98-1.00) with a median % difference of -3.3 (-7.5 to 6.0). In contrast, observed protein biomarker concentrations were significantly affected by sample types, with median correlation of 0.99 (0.33-1.00) and a median % difference of -10 (-55 to 23). When the two serum collection/handling methods were compared, the median correlation between paired samples for autoantibodies was 0.99 (0.91-1.00) with a median difference of 4%. In contrast, significant increases were observed in protein biomarker

SearchLight: a freely available web-based quantitative spectral analysis tool (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prabhat, Prashant; Peet, Michael; Erdogan, Turan

2016-03-01

In order to design a fluorescence experiment, typically the spectra of a fluorophore and of a filter set are overlaid on a single graph and the spectral overlap is evaluated intuitively. However, in a typical fluorescence imaging system the fluorophores and optical filters are not the only wavelength dependent variables - even the excitation light sources have been changing. For example, LED Light Engines may have a significantly different spectral response compared to the traditional metal-halide lamps. Therefore, for a more accurate assessment of fluorophore-to-filter-set compatibility, all sources of spectral variation should be taken into account simultaneously. Additionally, intuitive or qualitative evaluation of many spectra does not necessarily provide a realistic assessment of the system performance. "SearchLight" is a freely available web-based spectral plotting and analysis tool that can be used to address the need for accurate, quantitative spectral evaluation of fluorescence measurement systems. This tool is available at: http://searchlight.semrock.com/. Based on a detailed mathematical framework [1], SearchLight calculates signal, noise, and signal-to-noise ratio for multiple combinations of fluorophores, filter sets, light sources and detectors. SearchLight allows for qualitative and quantitative evaluation of the compatibility of filter sets with fluorophores, analysis of bleed-through, identification of optimized spectral edge locations for a set of filters under specific experimental conditions, and guidance regarding labeling protocols in multiplexing imaging assays. Entire SearchLight sessions can be shared with colleagues and collaborators and saved for future reference. [1] Anderson, N., Prabhat, P. and Erdogan, T., Spectral Modeling in Fluorescence Microscopy, http://www.semrock.com (2010).

A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics.

PubMed

Van Oudenhove, Laurence; Devreese, Bart

2013-06-01

Proteomics has evolved substantially since its early days, some 20 years ago. In this mini-review, we aim to provide an overview of general methodologies and more recent developments in mass spectrometric approaches used for relative and absolute quantitation of proteins. Enhancement of sensitivity of the mass spectrometers as well as improved sample preparation and protein fractionation methods are resulting in a more comprehensive analysis of proteomes. We also document some upcoming trends for quantitative proteomics such as the use of label-free quantification methods. Hopefully, microbiologists will continue to explore proteomics as a tool in their research to understand the adaptation of microorganisms to their ever changing environment. We encourage them to incorporate some of the described new developments in mass spectrometry to facilitate their analyses and improve the general knowledge of the fascinating world of microorganisms.

A quantitative, comprehensive analytical model for ``fast'' magnetic reconnection in Hall MHD

NASA Astrophysics Data System (ADS)

Simakov, Andrei N.

2008-11-01

Magnetic reconnection in nature usually happens on fast (e.g. dissipation independent) time scales. While such scales have been observed computationally [1], a fundamental analytical model capable of explaining them has been lacking. Here, we propose such a quantitative model for 2D Hall MHD reconnection without a guide field. The model recovers the Sweet-Parker and the electron MHD [2] results in the appropriate limits of the ion inertial length, di, and is valid everywhere in between [3]. The model predicts the dissipation region aspect ratio and the reconnection rate Ez in terms of dissipation and inertial parameters, and has been found to be in excellent agreement with non-linear simulations. It confirms a number of long-standing empirical results and resolves several controversies. In particular, we find that both open X-point and elongated dissipation regions allow ``fast'' reconnection and that Ez depends on di. Moreover, when applied to electron-positron plasmas, the model demonstrates that fast dispersive waves are not instrumental for ``fast'' reconnection [4]. [1] J. Birn et al., J. Geophys. Res. 106, 3715 (2001). [2] L. Chac'on, A. N. Simakov, and A. Zocco, Phys. Rev. Lett. 99, 235001 (2007). [3] A. N. Simakov and L. Chac'on, submitted to Phys. Rev. Lett. [4] L. Chac'on, A. N. Simakov, V. Lukin, and A. Zocco, Phys. Rev. Lett. 101, 025003 (2008).

Application of the correlation constrained multivariate curve resolution alternating least-squares method for analyte quantitation in the presence of unexpected interferences using first-order instrumental data.

PubMed

Goicoechea, Héctor C; Olivieri, Alejandro C; Tauler, Romà

2010-03-01

Correlation constrained multivariate curve resolution-alternating least-squares is shown to be a feasible method for processing first-order instrumental data and achieve analyte quantitation in the presence of unexpected interferences. Both for simulated and experimental data sets, the proposed method could correctly retrieve the analyte and interference spectral profiles and perform accurate estimations of analyte concentrations in test samples. Since no information concerning the interferences was present in calibration samples, the proposed multivariate calibration approach including the correlation constraint facilitates the achievement of the so-called second-order advantage for the analyte of interest, which is known to be present for more complex higher-order richer instrumental data. The proposed method is tested using a simulated data set and two experimental data systems, one for the determination of ascorbic acid in powder juices using UV-visible absorption spectral data, and another for the determination of tetracycline in serum samples using fluorescence emission spectroscopy.

A Quantitative Study of a Software Tool that Supports a Part-Complete Solution Method on Learning Outcomes

ERIC Educational Resources Information Center

Garner, Stuart

2009-01-01

This paper reports on the findings from a quantitative research study into the use of a software tool that was built to support a part-complete solution method (PCSM) for the learning of computer programming. The use of part-complete solutions to programming problems is one of the methods that can be used to reduce the cognitive load that students…

Development of a BK virus real-time quantitative assay using the bioMérieux analyte-specific reagents in plasma specimens.

PubMed

Rennert, Hanna; Fernandes, Helen; Gilani, Zahid; Sipley, John

2015-12-01

Viral load testing for BK virus (BKV) has become the standard of care for diagnosing BKV infection and monitoring therapy in kidney transplant patients. However, there are currently no US Food and Drug Administration-approved assays and no standardization among available tests. This study evaluated the performance of the analyte-specific reagent (ASR) BKV primers r-gene and probe r-gene reagents (bioMérieux, Marcy l'Étoile, France) soon to become available on the US market for accuracy, linearity, precision, analytical sensitivity, specificity, and correlation with the Qiagen (Germantown, MD) BKV ASR test using commercial material and patient plasma samples. The assay was linear from 204 to 3.92 million (2.31-6.6 log10) DNA copies/mL (coefficient of determination: R(2) =0.999). A dilution series demonstrated limits of detection and quantitation of 2.14 log10 and 2.30 log10 copies/mL (95% hit rate detection), respectively. Interrun precision was highly reproducible, with coefficients of variance ranging from 2.2% to 6.0%. A comparison of 34 matched samples showed a good agreement (R(2) = 0.87) between the bioMérieux BKV laboratory test and the Qiagen BKV ASR assay results, with an average negative bias (-0.28 log10 copies/mL). The laboratory-developed test with bioMérieux BKV reagents is a reliable and sensitive assay for BKV DNA quantitation compared with the Qiagen ASR test. Copyright© by the American Society for Clinical Pathology.

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…

Advances in analytical chemistry

NASA Technical Reports Server (NTRS)

Arendale, W. F.; Congo, Richard T.; Nielsen, Bruce J.

1991-01-01

Implementation of computer programs based on multivariate statistical algorithms makes possible obtaining reliable information from long data vectors that contain large amounts of extraneous information, for example, noise and/or analytes that we do not wish to control. Three examples are described. Each of these applications requires the use of techniques characteristic of modern analytical chemistry. The first example, using a quantitative or analytical model, describes the determination of the acid dissociation constant for 2,2'-pyridyl thiophene using archived data. The second example describes an investigation to determine the active biocidal species of iodine in aqueous solutions. The third example is taken from a research program directed toward advanced fiber-optic chemical sensors. The second and third examples require heuristic or empirical models.

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...

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.

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.

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…

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

A Quantitative ADME-base Tool for Exploring Human ...

EPA Pesticide Factsheets

Exposure to a wide range of chemicals through our daily habits and routines is ubiquitous and largely unavoidable within modern society. The potential for human exposure, however, has not been quantified for the vast majority of chemicals with wide commercial use. Creative advances in exposure science are needed to support efficient and effective evaluation and management of chemical risks, particularly for chemicals in consumer products. The U.S. Environmental Protection Agency Office of Research and Development is developing, or collaborating in the development of, scientifically-defensible methods for making quantitative or semi-quantitative exposure predictions. The Exposure Prioritization (Ex Priori) model is a simplified, quantitative visual dashboard that provides a rank-ordered internalized dose metric to simultaneously explore exposures across chemical space (not chemical by chemical). Diverse data streams are integrated within the interface such that different exposure scenarios for “individual,” “population,” or “professional” time-use profiles can be interchanged to tailor exposure and quantitatively explore multi-chemical signatures of exposure, internalized dose (uptake), body burden, and elimination. Ex Priori has been designed as an adaptable systems framework that synthesizes knowledge from various domains and is amenable to new knowledge/information. As such, it algorithmically captures the totality of exposure across pathways. It

FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

PubMed

Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

2015-10-01

Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

Quantitative Glycomics Strategies*

PubMed Central

Mechref, Yehia; Hu, Yunli; Desantos-Garcia, Janie L.; Hussein, Ahmed; Tang, Haixu

2013-01-01

The correlations between protein glycosylation and many biological processes and diseases are increasing the demand for quantitative glycomics strategies enabling sensitive monitoring of changes in the abundance and structure of glycans. This is currently attained through multiple strategies employing several analytical techniques such as capillary electrophoresis, liquid chromatography, and mass spectrometry. The detection and quantification of glycans often involve labeling with ionic and/or hydrophobic reagents. This step is needed in order to enhance detection in spectroscopic and mass spectrometric measurements. Recently, labeling with stable isotopic reagents has also been presented as a very viable strategy enabling relative quantitation. The different strategies available for reliable and sensitive quantitative glycomics are herein described and discussed. PMID:23325767

Quantitative study of protein-protein interactions by quartz nanopipettes

NASA Astrophysics Data System (ADS)

Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

2014-08-01

In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Selection of reference standard during method development using the analytical hierarchy process.

PubMed

Sun, Wan-yang; Tong, Ling; Li, Dong-xiang; Huang, Jing-yi; Zhou, Shui-ping; Sun, Henry; Bi, Kai-shun

2015-03-25

Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development. Copyright © 2015 Elsevier B.V. All rights reserved.

Analytical Chemistry and the Microchip.

ERIC Educational Resources Information Center

Lowry, Robert K.

1986-01-01

Analytical techniques used at various points in making microchips are described. They include: Fourier transform infrared spectrometry (silicon purity); optical emission spectroscopy (quantitative thin-film composition); X-ray photoelectron spectroscopy (chemical changes in thin films); wet chemistry, instrumental analysis (process chemicals);…

Distributed Engine Control Empirical/Analytical Verification Tools

NASA Technical Reports Server (NTRS)

DeCastro, Jonathan; Hettler, Eric; Yedavalli, Rama; Mitra, Sayan

2013-01-01

NASA's vision for an intelligent engine will be realized with the development of a truly distributed control system featuring highly reliable, modular, and dependable components capable of both surviving the harsh engine operating environment and decentralized functionality. A set of control system verification tools was developed and applied to a C-MAPSS40K engine model, and metrics were established to assess the stability and performance of these control systems on the same platform. A software tool was developed that allows designers to assemble easily a distributed control system in software and immediately assess the overall impacts of the system on the target (simulated) platform, allowing control system designers to converge rapidly on acceptable architectures with consideration to all required hardware elements. The software developed in this program will be installed on a distributed hardware-in-the-loop (DHIL) simulation tool to assist NASA and the Distributed Engine Control Working Group (DECWG) in integrating DCS (distributed engine control systems) components onto existing and next-generation engines.The distributed engine control simulator blockset for MATLAB/Simulink and hardware simulator provides the capability to simulate virtual subcomponents, as well as swap actual subcomponents for hardware-in-the-loop (HIL) analysis. Subcomponents can be the communication network, smart sensor or actuator nodes, or a centralized control system. The distributed engine control blockset for MATLAB/Simulink is a software development tool. The software includes an engine simulation, a communication network simulation, control algorithms, and analysis algorithms set up in a modular environment for rapid simulation of different network architectures; the hardware consists of an embedded device running parts of the CMAPSS engine simulator and controlled through Simulink. The distributed engine control simulation, evaluation, and analysis technology provides unique

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…

Progressing towards more quantitative analytical pyrolysis of soil organic matter using molecular beam mass spectroscopy of whole soils and added standards

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

Haddix, Michelle L.; Magrini-Bair, Kim; Evans, Robert J.

Soil organic matter (SOM) is extremely complex. It is composed of hundreds of different organic substances and it has been difficult to quantify these diverse substances in a dynamic-ecosystem functioning standpoint. Analytical pyrolysis has been used to compare chemical differences between soils, but its ability to measure the absolute amount of a specific compound in the soil is still in question. Our objective was to assess whether utilizing pyrolysis-molecular beam mass spectroscopy (py-MBMS) to define the signature of known reference compounds (adenine, indole, palmitic acid, etc.) and biological samples (chitin, fungi, cellulose, etc.) separately and when added to whole soilsmore » it was possible to make py-MBMS more quantitative. Reference compounds, spanning a wide variety of compound categories, and biological samples, expected to be present in SOM, were added to three soils from Colorado, Ohio, and Massachusetts that have varying total C, % clay, and clay type. Py-MBMS, a rapid analysis technique originally developed to analyze complex biomolecules, flash pyrolyzes soil organic matter to form products that are often considered characteristic of the original molecular structure. Samples were pyrolyzed at 550 degrees C by py-MBMS. All samples were weighed and %C and %N determined both before and after pyrolysis to evaluate mass loss, C loss, and N loss for the samples.An average relationship of r2 = 0.76 (P = 0.005) was found for the amount of cellulose added to soil at 25, 50, and 100% of soil C relative to the ion intensity of select mass/charge of the compound.There was a relationship of r2 = 0.93 (P < 0.001) for the amount of indole added to soil at 25, 50, and 100% of soil C and the ion intensity of the associated mass variables (mass/charge). Comparing spectra of pure compounds with the spectra of the compounds added to soil and isolated clay showed that interference could occur based on soil type and compound with the Massachusetts soil with high

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…

Training in motivational interviewing in obstetrics: a quantitative analytical tool.

PubMed

Lindhardt, Christina L; Rubak, Sune; Mogensen, Ole; Hansen, Helle P; Lamont, Ronald F; Jørgensen, Jan S

2014-07-01

To examine whether a 3-day training course in motivational interviewing, which is an approach to helping people to change, could improve the communication skills of obstetric healthcare professionals in their interaction with obese pregnant women. Intervention study. The Region of Southern Denmark. Eleven obstetric healthcare professionals working with obese pregnant women underwent a 3-day course in motivational interviewing techniques and were assessed before and after training to measure the impact on their overall performance as well as the effect on specific behavioral techniques observed during interviews. With a few exceptions, the participants changed their behavior appropriate to the motivational interviewing technique. The participants made more interventions towards the principles of motivational interviewing (adherent and nonadherent interventions). Furthermore, the participants asked fewer closed and more open questions before training in motivational interview. In the assessment of proficiency and competency, most of the participants scored higher after the training in motivational interviewing. Training in motivational interviewing improves healthcare professionals' proficiency and competency when communicating with obese pregnant women, albeit that the effect was not universal. © 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

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.

Concurrence of big data analytics and healthcare: A systematic review.

PubMed

Mehta, Nishita; Pandit, Anil

2018-06-01

The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. This review study unveils that there is a paucity of information on evidence of real-world use of

Extended internal standard method for quantitative 1H NMR assisted by chromatography (EIC) for analyte overlapping impurity on 1H NMR spectra.

PubMed

Saito, Naoki; Kitamaki, Yuko; Otsuka, Satoko; Yamanaka, Noriko; Nishizaki, Yuzo; Sugimoto, Naoki; Imura, Hisanori; Ihara, Toshihide

2018-07-01

We devised a novel extended internal standard method of quantitative 1 H NMR (qNMR) assisted by chromatography (EIC) that accurately quantifies 1 H signal areas of analytes, even when the chemical shifts of the impurity and analyte signals overlap completely. When impurity and analyte signals overlap in the 1 H NMR spectrum but can be separated in a chromatogram, the response ratio of the impurity and an internal standard (IS) can be obtained from the chromatogram. If the response ratio can be converted into the 1 H signal area ratio of the impurity and the IS, the 1 H signal area of the analyte can be evaluated accurately by mathematically correcting the contributions of the 1 H signal area of the impurity overlapping the analyte in the 1 H NMR spectrum. In this study, gas chromatography and liquid chromatography were used. We used 2-chlorophenol and 4-chlorophenol containing phenol as an impurity as examples in which impurity and analyte signals overlap to validate and demonstrate the EIC, respectively. Because the 1 H signals of 2-chlorophenol and phenol can be separated in specific alkaline solutions, 2-chlorophenol is suitable to validate the EIC by comparing analytical value obtained by the EIC with that by only qNMR under the alkaline condition. By the EIC, the purity of 2-chlorophenol was obtained with a relative expanded uncertainty (k = 2) of 0.24%. The purity matched that obtained under the alkaline condition. Furthermore, the EIC was also validated by evaluating the phenol content with the absolute calibration curve method by gas chromatography. Finally, we demonstrated that the EIC was possible to evaluate the purity of 4-chlorophenol, with a relative expanded uncertainty (k = 2) of 0.22%, which was not able to be separated from the 1 H signal of phenol under any condition. Copyright © 2018 Elsevier B.V. All rights reserved.

Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America☆

PubMed Central

Pepin, K.M.; Spackman, E.; Brown, J.D.; Pabilonia, K.L.; Garber, L.P.; Weaver, J.T.; Kennedy, D.A.; Patyk, K.A.; Huyvaert, K.P.; Miller, R.S.; Franklin, A.B.; Pedersen, K.; Bogich, T.L.; Rohani, P.; Shriner, S.A.; Webb, C.T.; Riley, S.

2014-01-01

Wild birds are the primary source of genetic diversity for influenza A viruses that eventually emerge in poultry and humans. Much progress has been made in the descriptive ecology of avian influenza viruses (AIVs), but contributions are less evident from quantitative studies (e.g., those including disease dynamic models). Transmission between host species, individuals and flocks has not been measured with sufficient accuracy to allow robust quantitative evaluation of alternate control protocols. We focused on the United States of America (USA) as a case study for determining the state of our quantitative knowledge of potential AIV emergence processes from wild hosts to poultry. We identified priorities for quantitative research that would build on existing tools for responding to AIV in poultry and concluded that the following knowledge gaps can be addressed with current empirical data: (1) quantification of the spatio-temporal relationships between AIV prevalence in wild hosts and poultry populations, (2) understanding how the structure of different poultry sectors impacts within-flock transmission, (3) determining mechanisms and rates of between-farm spread, and (4) validating current policy-decision tools with data. The modeling studies we recommend will improve our mechanistic understanding of potential AIV transmission patterns in USA poultry, leading to improved measures of accuracy and reduced uncertainty when evaluating alternative control strategies. PMID:24462191

Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America.

PubMed

Pepin, K M; Spackman, E; Brown, J D; Pabilonia, K L; Garber, L P; Weaver, J T; Kennedy, D A; Patyk, K A; Huyvaert, K P; Miller, R S; Franklin, A B; Pedersen, K; Bogich, T L; Rohani, P; Shriner, S A; Webb, C T; Riley, S

2014-03-01

Wild birds are the primary source of genetic diversity for influenza A viruses that eventually emerge in poultry and humans. Much progress has been made in the descriptive ecology of avian influenza viruses (AIVs), but contributions are less evident from quantitative studies (e.g., those including disease dynamic models). Transmission between host species, individuals and flocks has not been measured with sufficient accuracy to allow robust quantitative evaluation of alternate control protocols. We focused on the United States of America (USA) as a case study for determining the state of our quantitative knowledge of potential AIV emergence processes from wild hosts to poultry. We identified priorities for quantitative research that would build on existing tools for responding to AIV in poultry and concluded that the following knowledge gaps can be addressed with current empirical data: (1) quantification of the spatio-temporal relationships between AIV prevalence in wild hosts and poultry populations, (2) understanding how the structure of different poultry sectors impacts within-flock transmission, (3) determining mechanisms and rates of between-farm spread, and (4) validating current policy-decision tools with data. The modeling studies we recommend will improve our mechanistic understanding of potential AIV transmission patterns in USA poultry, leading to improved measures of accuracy and reduced uncertainty when evaluating alternative control strategies. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Mapping healthcare systems: a policy relevant analytic tool

PubMed Central

Sekhri Feachem, Neelam; Afshar, Ariana; Pruett, Cristina; Avanceña, Anton L.V.

2017-01-01

Abstract Background In the past decade, an international consensus on the value of well-functioning systems has driven considerable health systems research. This research falls into two broad categories. The first provides conceptual frameworks that take complex healthcare systems and create simplified constructs of interactions and functions. The second focuses on granular inputs and outputs. This paper presents a novel translational mapping tool – the University of California, San Francisco mapping tool (the Tool) - which bridges the gap between these two areas of research, creating a platform for multi-country comparative analysis. Methods Using the Murray-Frenk framework, we create a macro-level representation of a country's structure, focusing on how it finances and delivers healthcare. The map visually depicts the fundamental policy questions in healthcare system design: funding sources and amount spent through each source, purchasers, populations covered, provider categories; and the relationship between these entities. Results We use the Tool to provide a macro-level comparative analysis of the structure of India's and Thailand's healthcare systems. Conclusions As part of the systems strengthening arsenal, the Tool can stimulate debate about the merits and consequences of different healthcare systems structural designs, using a common framework that fosters multi-country comparative analyses. PMID:28541518

Mapping healthcare systems: a policy relevant analytic tool.

PubMed

Sekhri Feachem, Neelam; Afshar, Ariana; Pruett, Cristina; Avanceña, Anton L V

2017-07-01

In the past decade, an international consensus on the value of well-functioning systems has driven considerable health systems research. This research falls into two broad categories. The first provides conceptual frameworks that take complex healthcare systems and create simplified constructs of interactions and functions. The second focuses on granular inputs and outputs. This paper presents a novel translational mapping tool - the University of California, San Francisco mapping tool (the Tool) - which bridges the gap between these two areas of research, creating a platform for multi-country comparative analysis. Using the Murray-Frenk framework, we create a macro-level representation of a country's structure, focusing on how it finances and delivers healthcare. The map visually depicts the fundamental policy questions in healthcare system design: funding sources and amount spent through each source, purchasers, populations covered, provider categories; and the relationship between these entities. We use the Tool to provide a macro-level comparative analysis of the structure of India's and Thailand's healthcare systems. As part of the systems strengthening arsenal, the Tool can stimulate debate about the merits and consequences of different healthcare systems structural designs, using a common framework that fosters multi-country comparative analyses. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

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.

Rhodobase, a meta-analytical tool for reconstructing gene regulatory networks in a model photosynthetic bacterium.

PubMed

Moskvin, Oleg V; Bolotin, Dmitry; Wang, Andrew; Ivanov, Pavel S; Gomelsky, Mark

2011-02-01

We present Rhodobase, a web-based meta-analytical tool for analysis of transcriptional regulation in a model anoxygenic photosynthetic bacterium, Rhodobacter sphaeroides. The gene association meta-analysis is based on the pooled data from 100 of R. sphaeroides whole-genome DNA microarrays. Gene-centric regulatory networks were visualized using the StarNet approach (Jupiter, D.C., VanBuren, V., 2008. A visual data mining tool that facilitates reconstruction of transcription regulatory networks. PLoS ONE 3, e1717) with several modifications. We developed a means to identify and visualize operons and superoperons. We designed a framework for the cross-genome search for transcription factor binding sites that takes into account high GC-content and oligonucleotide usage profile characteristic of the R. sphaeroides genome. To facilitate reconstruction of directional relationships between co-regulated genes, we screened upstream sequences (-400 to +20bp from start codons) of all genes for putative binding sites of bacterial transcription factors using a self-optimizing search method developed here. To test performance of the meta-analysis tools and transcription factor site predictions, we reconstructed selected nodes of the R. sphaeroides transcription factor-centric regulatory matrix. The test revealed regulatory relationships that correlate well with the experimentally derived data. The database of transcriptional profile correlations, the network visualization engine and the optimized search engine for transcription factor binding sites analysis are available at http://rhodobase.org. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Stable isotope ratio analysis: A potential analytical tool for the authentication of South African lamb meat.

PubMed

Erasmus, Sara Wilhelmina; Muller, Magdalena; van der Rijst, Marieta; Hoffman, Louwrens Christiaan

2016-02-01

Stable isotope ratios ((13)C/(12)C and (15)N/(14)N) of South African Dorper lambs from farms with different vegetation types were measured by isotope ratio mass spectrometry (IRMS), to evaluate it as a tool for the authentication of origin and feeding regime. Homogenised and defatted meat of the Longissimus lumborum (LL) muscle of lambs from seven different farms was assessed. The δ(13)C values were affected by the origin of the meat, mainly reflecting the diet. The Rûens and Free State farms had the lowest (p ⩽ 0.05) δ(15)N values, followed by the Northern Cape farms, with Hantam Karoo/Calvinia having the highest δ(15)N values. Discriminant analysis showed δ(13)C and δ(15)N differences as promising results for the use of IRMS as a reliable analytical tool for lamb meat authentication. The results suggest that diet, linked to origin, is an important factor to consider regarding region of origin classification for South African lamb. Copyright © 2015 Elsevier Ltd. All rights reserved.

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…

Analytical Tools for Functional Assessment of Architectural Layouts

NASA Astrophysics Data System (ADS)

Bąkowski, Jarosław

2017-10-01

defects. This approach, supplemented by the method of reverse engineering means that already in the design phase there is essential knowledge about the functioning of the facility. It is far beyond intuitive knowledge, based on the standards and specifications. In the scope of reverse engineering methods, the subject of the research is an audit of the product (i.e. architectural design, especially the built spatial layout) in order to determine exactly how it works. Information gained in this way is to help building a system for supporting decisions for preparing design solutions for future investments as well as the functional analysis itself becomes an essential part of the setting up building information process. The data are presented with graphical methods as networks of different factors between rooms. The direct analytical method for the setting is to determine the functional collision between users’ tracks, finding or indication of the shortest paths connecting analyzed rooms and finally to identify the optimal location of these rooms (each according to different factor). The measurement data are supplemented by the results of surveys conducted among users of hospitals, statistics and quantitative medical procedures performed in the test section of the hospital. The results of research are transferred and integrated with BIM system (building information modelling system), and included in the specifications of the IFC (Industry Foundation Classes), especially at the level of information on the relationship between the individual properties associated with elements (in the case of hospitals it may be information about the necessary connections with other rooms, access times from or to specific rooms, rooms utilization conditions, fire safety protection and conditions and many other). At the level of the BIM specification the model data are integrated at the BIM 6D (an extension of the model data with a range of functional analysis) or even BIM 7D (additional

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.

Surrogate analyte approach for quantitation of endogenous NAD(+) in human acidified blood samples using liquid chromatography coupled with electrospray ionization tandem mass spectrometry.

PubMed

Liu, Liling; Cui, Zhiyi; Deng, Yuzhong; Dean, Brian; Hop, Cornelis E C A; Liang, Xiaorong

2016-02-01

A high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS) assay for the quantitative determination of NAD(+) in human whole blood using a surrogate analyte approach was developed and validated. Human whole blood was acidified using 0.5N perchloric acid at a ratio of 1:3 (v:v, blood:perchloric acid) during sample collection. 25μL of acidified blood was extracted using a protein precipitation method and the resulting extracts were analyzed using reverse-phase chromatography and positive electrospray ionization mass spectrometry. (13)C5-NAD(+) was used as the surrogate analyte for authentic analyte, NAD(+). The standard curve ranging from 0.250 to 25.0μg/mL in acidified human blood for (13)C5-NAD(+) was fitted to a 1/x(2) weighted linear regression model. The LC-MS/MS response between surrogate analyte and authentic analyte at the same concentration was obtained before and after the batch run. This response factor was not applied when determining the NAD(+) concentration from the (13)C5-NAD(+) standard curve since the percent difference was less than 5%. The precision and accuracy of the LC-MS/MS assay based on the five analytical QC levels were well within the acceptance criteria from both FDA and EMA guidance for bioanalytical method validation. Average extraction recovery of (13)C5-NAD(+) was 94.6% across the curve range. Matrix factor was 0.99 for both high and low QC indicating minimal ion suppression or enhancement. The validated assay was used to measure the baseline level of NAD(+) in 29 male and 21 female human subjects. This assay was also used to study the circadian effect of endogenous level of NAD(+) in 10 human subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative imaging for discovery and assembly of the metabo-regulome

PubMed Central

Okumoto, Sakiko; Takanaga, Hitomi; Frommer, Wolf B.

2009-01-01

Summary Little is known about regulatory networks that control metabolic flux in plant cells. Detailed understanding of regulation is crucial for synthetic biology. The difficulty of measuring metabolites with cellular and subcellular precision is a major roadblock. New tools have been developed for monitoring extracellular, cytosolic, organellar and vacuolar ion and metabolite concentrations with a time resolution of milliseconds to hours. Genetically encoded sensors allow quantitative measurement of steady-state concentrations of ions, signaling molecules and metabolites and their respective changes over time. Fluorescence resonance energy transfer (FRET) sensors exploit conformational changes in polypeptides as a proxy for analyte concentrations. Subtle effects of analyte binding on the conformation of the recognition element are translated into a FRET change between two fused green fluorescent protein (GFP) variants, enabling simple monitoring of analyte concentrations using fluorimetry or fluorescence microscopy. Fluorimetry provides information averaged over cell populations, while microscopy detects differences between cells or populations of cells. The genetically encoded sensors can be targeted to subcellular compartments or the cell surface. Confocal microscopy ultimately permits observation of gradients or local differences within a compartment. The FRET assays can be adapted to high-throughput analysis to screen mutant populations in order to systematically identify signaling networks that control individual steps in metabolic flux. PMID:19138219

Quantitative Decision Making.

ERIC Educational Resources Information Center

Baldwin, Grover H.

The use of quantitative decision making tools provides the decision maker with a range of alternatives among which to decide, permits acceptance and use of the optimal solution, and decreases risk. Training line administrators in the use of these tools can help school business officials obtain reliable information upon which to base district…

QUANTITATIVE DECISION TOOLS AND MANAGEMENT DEVELOPMENT PROGRAMS.

ERIC Educational Resources Information Center

BYARS, LLOYD L.; NUNN, GEOFFREY E.

THIS ARTICLE OUTLINED THE CURRENT STATUS OF QUANTITATIVE METHODS AND OPERATIONS RESEARCH (OR), SKETCHED THE STRENGTHS OF TRAINING EFFORTS AND ISOLATED WEAKNESSES, AND FORMULATED WORKABLE CRITERIA FOR EVALUATING SUCCESS OF OPERATIONS RESEARCH TRAINING PROGRAMS. A SURVEY OF 105 COMPANIES REVEALED THAT PERT, INVENTORY CONTROL THEORY AND LINEAR…

Biological Matrix Effects in Quantitative Tandem Mass Spectrometry-Based Analytical Methods: Advancing Biomonitoring

PubMed Central

Panuwet, Parinya; Hunter, Ronald E.; D’Souza, Priya E.; Chen, Xianyu; Radford, Samantha A.; Cohen, Jordan R.; Marder, M. Elizabeth; Kartavenka, Kostya; Ryan, P. Barry; Barr, Dana Boyd

2015-01-01

The ability to quantify levels of target analytes in biological samples accurately and precisely, in biomonitoring, involves the use of highly sensitive and selective instrumentation such as tandem mass spectrometers and a thorough understanding of highly variable matrix effects. Typically, matrix effects are caused by co-eluting matrix components that alter the ionization of target analytes as well as the chromatographic response of target analytes, leading to reduced or increased sensitivity of the analysis. Thus, before the desired accuracy and precision standards of laboratory data are achieved, these effects must be characterized and controlled. Here we present our review and observations of matrix effects encountered during the validation and implementation of tandem mass spectrometry-based analytical methods. We also provide systematic, comprehensive laboratory strategies needed to control challenges posed by matrix effects in order to ensure delivery of the most accurate data for biomonitoring studies assessing exposure to environmental toxicants. PMID:25562585

Evaluating analytic and risk assessment tools to estimate sediment and nutrients losses from agricultural lands in the southern region of the USA

USDA-ARS?s Scientific Manuscript database

Non-point source pollution from agricultural fields is a critical problem associated with water quality impairment in the USA and a low-oxygen environment in the Gulf of Mexico. The use, development and enhancement of qualitative and quantitative models or tools for assessing agricultural runoff qua...

Using learning analytics to evaluate a video-based lecture series.

PubMed

Lau, K H Vincent; Farooque, Pue; Leydon, Gary; Schwartz, Michael L; Sadler, R Mark; Moeller, Jeremy J

2018-01-01

The video-based lecture (VBL), an important component of the flipped classroom (FC) and massive open online course (MOOC) approaches to medical education, has primarily been evaluated through direct learner feedback. Evaluation may be enhanced through learner analytics (LA) - analysis of quantitative audience usage data generated by video-sharing platforms. We applied LA to an experimental series of ten VBLs on electroencephalography (EEG) interpretation, uploaded to YouTube in the model of a publicly accessible MOOC. Trends in view count; total percentage of video viewed and audience retention (AR) (percentage of viewers watching at a time point compared to the initial total) were examined. The pattern of average AR decline was characterized using regression analysis, revealing a uniform linear decline in viewership for each video, with no evidence of an optimal VBL length. Segments with transient increases in AR corresponded to those focused on core concepts, indicative of content requiring more detailed evaluation. We propose a model for applying LA at four levels: global, series, video, and feedback. LA may be a useful tool in evaluating a VBL series. Our proposed model combines analytics data and learner self-report for comprehensive evaluation.

Control/structure interaction conceptual design tool

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1990-01-01

The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

Comparative Application of PLS and PCR Methods to Simultaneous Quantitative Estimation and Simultaneous Dissolution Test of Zidovudine - Lamivudine Tablets.

PubMed

Üstündağ, Özgür; Dinç, Erdal; Özdemir, Nurten; Tilkan, M Günseli

2015-01-01

In the development strategies of new drug products and generic drug products, the simultaneous in-vitro dissolution behavior of oral dosage formulations is the most important indication for the quantitative estimation of efficiency and biopharmaceutical characteristics of drug substances. This is to force the related field's scientists to improve very powerful analytical methods to get more reliable, precise and accurate results in the quantitative analysis and dissolution testing of drug formulations. In this context, two new chemometric tools, partial least squares (PLS) and principal component regression (PCR) were improved for the simultaneous quantitative estimation and dissolution testing of zidovudine (ZID) and lamivudine (LAM) in a tablet dosage form. The results obtained in this study strongly encourage us to use them for the quality control, the routine analysis and the dissolution test of the marketing tablets containing ZID and LAM drugs.

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...

Lowering the Barrier to Reproducible Research by Publishing Provenance from Common Analytical Tools

NASA Astrophysics Data System (ADS)

Jones, M. B.; Slaughter, P.; Walker, L.; Jones, C. S.; Missier, P.; Ludäscher, B.; Cao, Y.; McPhillips, T.; Schildhauer, M.

2015-12-01

Scientific provenance describes the authenticity, origin, and processing history of research products and promotes scientific transparency by detailing the steps in computational workflows that produce derived products. These products include papers, findings, input data, software products to perform computations, and derived data and visualizations. The geosciences community values this type of information, and, at least theoretically, strives to base conclusions on computationally replicable findings. In practice, capturing detailed provenance is laborious and thus has been a low priority; beyond a lab notebook describing methods and results, few researchers capture and preserve detailed records of scientific provenance. We have built tools for capturing and publishing provenance that integrate into analytical environments that are in widespread use by geoscientists (R and Matlab). These tools lower the barrier to provenance generation by automating capture of critical information as researchers prepare data for analysis, develop, test, and execute models, and create visualizations. The 'recordr' library in R and the `matlab-dataone` library in Matlab provide shared functions to capture provenance with minimal changes to normal working procedures. Researchers can capture both scripted and interactive sessions, tag and manage these executions as they iterate over analyses, and then prune and publish provenance metadata and derived products to the DataONE federation of archival repositories. Provenance traces conform to the ProvONE model extension of W3C PROV, enabling interoperability across tools and languages. The capture system supports fine-grained versioning of science products and provenance traces. By assigning global identifiers such as DOIs, reseachers can cite the computational processes used to reach findings. And, finally, DataONE has built a web portal to search, browse, and clearly display provenance relationships between input data, the software

Identifying problems and generating recommendations for enhancing complex systems: applying the abstraction hierarchy framework as an analytical tool.

PubMed

Xu, Wei

2007-12-01

This study adopts J. Rasmussen's (1985) abstraction hierarchy (AH) framework as an analytical tool to identify problems and pinpoint opportunities to enhance complex systems. The process of identifying problems and generating recommendations for complex systems using conventional methods is usually conducted based on incompletely defined work requirements. As the complexity of systems rises, the sheer mass of data generated from these methods becomes unwieldy to manage in a coherent, systematic form for analysis. There is little known work on adopting a broader perspective to fill these gaps. AH was used to analyze an aircraft-automation system in order to further identify breakdowns in pilot-automation interactions. Four steps follow: developing an AH model for the system, mapping the data generated by various methods onto the AH, identifying problems based on the mapped data, and presenting recommendations. The breakdowns lay primarily with automation operations that were more goal directed. Identified root causes include incomplete knowledge content and ineffective knowledge structure in pilots' mental models, lack of effective higher-order functional domain information displayed in the interface, and lack of sufficient automation procedures for pilots to effectively cope with unfamiliar situations. The AH is a valuable analytical tool to systematically identify problems and suggest opportunities for enhancing complex systems. It helps further examine the automation awareness problems and identify improvement areas from a work domain perspective. Applications include the identification of problems and generation of recommendations for complex systems as well as specific recommendations regarding pilot training, flight deck interfaces, and automation procedures.

An Overview of Learning Analytics

ERIC Educational Resources Information Center

Clow, Doug

2013-01-01

Learning analytics, the analysis and representation of data about learners in order to improve learning, is a new lens through which teachers can understand education. It is rooted in the dramatic increase in the quantity of data about learners and linked to management approaches that focus on quantitative metrics, which are sometimes antithetical…

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

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool.

PubMed

Wu, Q; Zhao, X; You, H

2017-05-18

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool

PubMed Central

Wu, Q.; Zhao, X.; You, H.

2017-01-01

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver

The Quantitative Evaluation of the Clinical and Translational Science Awards (CTSA) Program Based on Science Mapping and Scientometric Analysis

PubMed Central

Zhang, Yin; Wang, Lei

2013-01-01

Abstract The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. PMID:24330689

The quantitative evaluation of the Clinical and Translational Science Awards (CTSA) program based on science mapping and scientometric analysis.

PubMed

Zhang, Yin; Wang, Lei; Diao, Tianxi

2013-12-01

The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. © 2013 Wiley Periodicals, Inc.

Development of TIF based figuring algorithm for deterministic pitch tool polishing

NASA Astrophysics Data System (ADS)

Yi, Hyun-Su; Kim, Sug-Whan; Yang, Ho-Soon; Lee, Yun-Woo

2007-12-01

Pitch is perhaps the oldest material used for optical polishing, leaving superior surface texture, and has been used widely in the optics shop floor. However, for its unpredictable controllability of removal characteristics, the pitch tool polishing has been rarely analysed quantitatively and many optics shops rely heavily on optician's "feel" even today. In order to bring a degree of process controllability to the pitch tool polishing, we added motorized tool motions to the conventional Draper type polishing machine and modelled the tool path in the absolute machine coordinate. We then produced a number of Tool Influence Function (TIF) both from an analytical model and a series of experimental polishing runs using the pitch tool. The theoretical TIFs agreed well with the experimental TIFs to the profile accuracy of 79 % in terms of its shape. The surface figuring algorithm was then developed in-house utilizing both theoretical and experimental TIFs. We are currently undertaking a series of trial figuring experiments to prove the performance of the polishing algorithm, and the early results indicate that the highly deterministic material removal control with the pitch tool can be achieved to a certain level of form error. The machine renovation, TIF theory and experimental confirmation, figuring simulation results are reported together with implications to deterministic polishing.

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…

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.

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…

Quantitative methylene blue decolourisation assays as rapid screening tools for assessing the efficiency of catalytic reactions.

PubMed

Kruid, Jan; Fogel, Ronen; Limson, Janice Leigh

2017-05-01

Identifying the most efficient oxidation process to achieve maximum removal of a target pollutant compound forms the subject of much research. There exists a need to develop rapid screening tools to support research in this area. In this work we report on the development of a quantitative assay as a means for identifying catalysts capable of decolourising methylene blue through the generation of oxidising species from hydrogen peroxide. Here, a previously described methylene blue test strip method was repurposed as a quantitative, aqueous-based spectrophotometric assay. From amongst a selection of metal salts and metallophthalocyanine complexes, monitoring of the decolourisation of the cationic dye methylene blue (via Fenton-like and non-Fenton oxidation reactions) by the assay identified the following to be suitable oxidation catalysts: CuSO 4 (a Fenton-like catalyst), iron(II)phthalocyanine (a non-Fenton oxidation catalyst), as well as manganese(II) phthalocyanine. The applicability of the method was examined for the removal of bisphenol A (BPA), as measured by HPLC, during parallel oxidation experiments. The order of catalytic activity was identified as FePc > MnPc > CuSO 4 for both BPA and MB. The quantitative MB decolourisation assay may offer a rapid method for screening a wide range of potential catalysts for oxidation processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools.

PubMed

Blattmann, Peter; Heusel, Moritz; Aebersold, Ruedi

2016-01-01

SWATH-MS is an acquisition and analysis technique of targeted proteomics that enables measuring several thousand proteins with high reproducibility and accuracy across many samples. OpenSWATH is popular open-source software for peptide identification and quantification from SWATH-MS data. For downstream statistical and quantitative analysis there exist different tools such as MSstats, mapDIA and aLFQ. However, the transfer of data from OpenSWATH to the downstream statistical tools is currently technically challenging. Here we introduce the R/Bioconductor package SWATH2stats, which allows convenient processing of the data into a format directly readable by the downstream analysis tools. In addition, SWATH2stats allows annotation, analyzing the variation and the reproducibility of the measurements, FDR estimation, and advanced filtering before submitting the processed data to downstream tools. These functionalities are important to quickly analyze the quality of the SWATH-MS data. Hence, SWATH2stats is a new open-source tool that summarizes several practical functionalities for analyzing, processing, and converting SWATH-MS data and thus facilitates the efficient analysis of large-scale SWATH/DIA datasets.

Quantitative study of protein-protein interactions by quartz nanopipettes.

PubMed

Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

2014-09-07

In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.

Time-resolved fluorescence microscopy (FLIM) as an analytical tool in skin nanomedicine.

PubMed

Alexiev, Ulrike; Volz, Pierre; Boreham, Alexander; Brodwolf, Robert

2017-07-01

The emerging field of nanomedicine provides new approaches for the diagnosis and treatment of diseases, for symptom relief, and for monitoring of disease progression. Topical application of drug-loaded nanoparticles for the treatment of skin disorders is a promising strategy to overcome the stratum corneum, the upper layer of the skin, which represents an effective physical and biochemical barrier. The understanding of drug penetration into skin and enhanced penetration into skin facilitated by nanocarriers requires analytical tools that ideally allow to visualize the skin, its morphology, the drug carriers, drugs, their transport across the skin and possible interactions, as well as effects of the nanocarriers within the different skin layers. Here, we review some recent developments in the field of fluorescence microscopy, namely Fluorescence Lifetime Imaging Microscopy (FLIM)), for improved characterization of nanocarriers, their interactions and penetration into skin. In particular, FLIM allows for the discrimination of target molecules, e.g. fluorescently tagged nanocarriers, against the autofluorescent tissue background and, due to the environmental sensitivity of the fluorescence lifetime, also offers insights into the local environment of the nanoparticle and its interactions with other biomolecules. Thus, FLIM shows the potential to overcome several limits of intensity based microscopy. Copyright © 2017 Elsevier B.V. All rights reserved.

Common plants as alternative analytical tools to monitor heavy metals in soil

PubMed Central

2012-01-01

Background Herbaceous plants are common vegetal species generally exposed, for a limited period of time, to bioavailable environmental pollutants. Heavy metals contamination is the most common form of environmental pollution. Herbaceous plants have never been used as natural bioindicators of environmental pollution, in particular to monitor the amount of heavy metals in soil. In this study, we aimed at assessing the usefulness of using three herbaceous plants (Plantago major L., Taraxacum officinale L. and Urtica dioica L.) and one leguminous (Trifolium pratense L.) as alternative indicators to evaluate soil pollution by heavy metals. Results We employed Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) to assess the concentration of selected heavy metals (Cu, Zn, Mn, Pb, Cr and Pd) in soil and plants and we employed statistical analyses to describe the linear correlation between the accumulation of some heavy metals and selected vegetal species. We found that the leaves of Taraxacum officinale L. and Trifolium pratense L. can accumulate Cu in a linearly dependent manner with Urtica dioica L. representing the vegetal species accumulating the highest fraction of Pb. Conclusions In this study we demonstrated that common plants can be used as an alternative analytical tool for monitoring selected heavy metals in soil. PMID:22594441

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images.

PubMed

Haass-Koffler, Carolina L; Naeemuddin, Mohammad; Bartlett, Selena E

2012-08-31

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology even in complex tissue sections. Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic

SedCT: MATLAB™ tools for standardized and quantitative processing of sediment core computed tomography (CT) data collected using a medical CT scanner

NASA Astrophysics Data System (ADS)

Reilly, B. T.; Stoner, J. S.; Wiest, J.

2017-08-01

Computed tomography (CT) of sediment cores allows for high-resolution images, three-dimensional volumes, and down core profiles. These quantitative data are generated through the attenuation of X-rays, which are sensitive to sediment density and atomic number, and are stored in pixels as relative gray scale values or Hounsfield units (HU). We present a suite of MATLAB™ tools specifically designed for routine sediment core analysis as a means to standardize and better quantify the products of CT data collected on medical CT scanners. SedCT uses a graphical interface to process Digital Imaging and Communications in Medicine (DICOM) files, stitch overlapping scanned intervals, and create down core HU profiles in a manner robust to normal coring imperfections. Utilizing a random sampling technique, SedCT reduces data size and allows for quick processing on typical laptop computers. SedCTimage uses a graphical interface to create quality tiff files of CT slices that are scaled to a user-defined HU range, preserving the quantitative nature of CT images and easily allowing for comparison between sediment cores with different HU means and variance. These tools are presented along with examples from lacustrine and marine sediment cores to highlight the robustness and quantitative nature of this method.

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.

Electronic tongue: An analytical gustatory tool

PubMed Central

Latha, Rewanthwar Swathi; Lakshmi, P. K.

2012-01-01

Taste is an important organoleptic property governing acceptance of products for administration through mouth. But majority of drugs available are bitter in taste. For patient acceptability and compliance, bitter taste drugs are masked by adding several flavoring agents. Thus, taste assessment is one important quality control parameter for evaluating taste-masked formulations. The primary method for the taste measurement of drug substances and formulations is by human panelists. The use of sensory panelists is very difficult and problematic in industry and this is due to the potential toxicity of drugs and subjectivity of taste panelists, problems in recruiting taste panelists, motivation and panel maintenance are significantly difficult when working with unpleasant products. Furthermore, Food and Drug Administration (FDA)-unapproved molecules cannot be tested. Therefore, analytical taste-sensing multichannel sensory system called as electronic tongue (e-tongue or artificial tongue) which can assess taste have been replacing the sensory panelists. Thus, e-tongue includes benefits like reducing reliance on human panel. The present review focuses on the electrochemical concepts in instrumentation, performance qualification of E-tongue, and applications in various fields. PMID:22470887

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

Contamination-Free Manufacturing: Tool Component Qualification, Verification and Correlation with Wafers

NASA Astrophysics Data System (ADS)

Tan, Samantha H.; Chen, Ning; Liu, Shi; Wang, Kefei

2003-09-01

As part of the semiconductor industry "contamination-free manufacturing" effort, significant emphasis has been placed on reducing potential sources of contamination from process equipment and process equipment components. Process tools contain process chambers and components that are exposed to the process environment or process chemistry and in some cases are in direct contact with production wafers. Any contamination from these sources must be controlled or eliminated in order to maintain high process yields, device performance, and device reliability. This paper discusses new nondestructive analytical methods for quantitative measurement of the cleanliness of metal, quartz, polysilicon and ceramic components that are used in process equipment tools. The goal of these new procedures is to measure the effectiveness of cleaning procedures and to verify whether a tool component part is sufficiently clean for installation and subsequent routine use in the manufacturing line. These procedures provide a reliable "qualification method" for tool component certification and also provide a routine quality control method for reliable operation of cleaning facilities. Cost advantages to wafer manufacturing include higher yields due to improved process cleanliness and elimination of yield loss and downtime resulting from the installation of "bad" components in process tools. We also discuss a representative example of wafer contamination having been linked to a specific process tool component.

Algorithms for optimized maximum entropy and diagnostic tools for analytic continuation.

PubMed

Bergeron, Dominic; Tremblay, A-M S

2016-08-01

Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem. The maximum-entropy approach, based on Bayesian inference, is the most widely used method to tackle that problem. Although the approach is well established and among the most reliable and efficient ones, useful developments of the method and of its implementation are still possible. In addition, while a few free software implementations are available, a well-documented, optimized, general purpose, and user-friendly software dedicated to that specific task is still lacking. Here we analyze all aspects of the implementation that are critical for accuracy and speed and present a highly optimized approach to maximum entropy. Original algorithmic and conceptual contributions include (1) numerical approximations that yield a computational complexity that is almost independent of temperature and spectrum shape (including sharp Drude peaks in broad background, for example) while ensuring quantitative accuracy of the result whenever precision of the data is sufficient, (2) a robust method of choosing the entropy weight α that follows from a simple consistency condition of the approach and the observation that information- and noise-fitting regimes can be identified clearly from the behavior of χ^{2} with respect to α, and (3) several diagnostics to assess the reliability of the result. Benchmarks with test spectral functions of different complexity and an example with an actual physical simulation are presented. Our implementation, which covers most typical cases for fermions, bosons, and response functions, is available as an open source, user-friendly software.

Algorithms for optimized maximum entropy and diagnostic tools for analytic continuation

NASA Astrophysics Data System (ADS)

Bergeron, Dominic; Tremblay, A.-M. S.

2016-08-01

Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem. The maximum-entropy approach, based on Bayesian inference, is the most widely used method to tackle that problem. Although the approach is well established and among the most reliable and efficient ones, useful developments of the method and of its implementation are still possible. In addition, while a few free software implementations are available, a well-documented, optimized, general purpose, and user-friendly software dedicated to that specific task is still lacking. Here we analyze all aspects of the implementation that are critical for accuracy and speed and present a highly optimized approach to maximum entropy. Original algorithmic and conceptual contributions include (1) numerical approximations that yield a computational complexity that is almost independent of temperature and spectrum shape (including sharp Drude peaks in broad background, for example) while ensuring quantitative accuracy of the result whenever precision of the data is sufficient, (2) a robust method of choosing the entropy weight α that follows from a simple consistency condition of the approach and the observation that information- and noise-fitting regimes can be identified clearly from the behavior of χ2 with respect to α , and (3) several diagnostics to assess the reliability of the result. Benchmarks with test spectral functions of different complexity and an example with an actual physical simulation are presented. Our implementation, which covers most typical cases for fermions, bosons, and response functions, is available as an open source, user-friendly software.

A Systematic Approach for Quantitative Analysis of Multidisciplinary Design Optimization Framework

NASA Astrophysics Data System (ADS)

Kim, Sangho; Park, Jungkeun; Lee, Jeong-Oog; Lee, Jae-Woo

An efficient Multidisciplinary Design and Optimization (MDO) framework for an aerospace engineering system should use and integrate distributed resources such as various analysis codes, optimization codes, Computer Aided Design (CAD) tools, Data Base Management Systems (DBMS), etc. in a heterogeneous environment, and need to provide user-friendly graphical user interfaces. In this paper, we propose a systematic approach for determining a reference MDO framework and for evaluating MDO frameworks. The proposed approach incorporates two well-known methods, Analytic Hierarchy Process (AHP) and Quality Function Deployment (QFD), in order to provide a quantitative analysis of the qualitative criteria of MDO frameworks. Identification and hierarchy of the framework requirements and the corresponding solutions for the reference MDO frameworks, the general one and the aircraft oriented one were carefully investigated. The reference frameworks were also quantitatively identified using AHP and QFD. An assessment of three in-house frameworks was then performed. The results produced clear and useful guidelines for improvement of the in-house MDO frameworks and showed the feasibility of the proposed approach for evaluating an MDO framework without a human interference.

Mining Health-Related Issues in Consumer Product Reviews by Using Scalable Text Analytics

PubMed Central

Torii, Manabu; Tilak, Sameer S.; Doan, Son; Zisook, Daniel S.; Fan, Jung-wei

2016-01-01

In an era when most of our life activities are digitized and recorded, opportunities abound to gain insights about population health. Online product reviews present a unique data source that is currently underexplored. Health-related information, although scarce, can be systematically mined in online product reviews. Leveraging natural language processing and machine learning tools, we were able to mine 1.3 million grocery product reviews for health-related information. The objectives of the study were as follows: (1) conduct quantitative and qualitative analysis on the types of health issues found in consumer product reviews; (2) develop a machine learning classifier to detect reviews that contain health-related issues; and (3) gain insights about the task characteristics and challenges for text analytics to guide future research. PMID:27375358

Mining Health-Related Issues in Consumer Product Reviews by Using Scalable Text Analytics.

PubMed

Torii, Manabu; Tilak, Sameer S; Doan, Son; Zisook, Daniel S; Fan, Jung-Wei

2016-01-01

In an era when most of our life activities are digitized and recorded, opportunities abound to gain insights about population health. Online product reviews present a unique data source that is currently underexplored. Health-related information, although scarce, can be systematically mined in online product reviews. Leveraging natural language processing and machine learning tools, we were able to mine 1.3 million grocery product reviews for health-related information. The objectives of the study were as follows: (1) conduct quantitative and qualitative analysis on the types of health issues found in consumer product reviews; (2) develop a machine learning classifier to detect reviews that contain health-related issues; and (3) gain insights about the task characteristics and challenges for text analytics to guide future research.

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence.

PubMed

Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

2018-03-05

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Semi-quantitative analysis of salivary gland scintigraphy in Sjögren's syndrome diagnosis: a first-line tool.

PubMed

Angusti, Tiziana; Pilati, Emanuela; Parente, Antonella; Carignola, Renato; Manfredi, Matteo; Cauda, Simona; Pizzigati, Elena; Dubreuil, Julien; Giammarile, Francesco; Podio, Valerio; Skanjeti, Andrea

2017-09-01

The aim of this study was the assessment of semi-quantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to predict primary Sjögren's syndrome (pSS). Forty-six consecutive patients (41 females; age 61 ± 11 years) with sicca syndrome were studied by SGdS after injection of 200 MBq of pertechnetate. In sixteen patients, pSS was diagnosed, according to American-European Consensus Group criteria (AECGc). Semi-quantitative parameters (uptake (UP) and excretion fraction (EF)) were obtained for each gland. ROC curves were used to determine the best cut-off value. The area under the curve (AUC) was used to estimate the accuracy of each semi-quantitative analysis. To assess the correlation between scintigraphic results and disease severity, semi-quantitative parameters were plotted versus Sjögren's syndrome disease activity index (ESSDAI). A nomogram was built to perform an integrated evaluation of all the scintigraphic semi-quantitative data. Both UP and EF of salivary glands were significantly lower in pSS patients compared to those in non-pSS (p < 0.001). ROC curve showed significantly large AUC for both the parameters (p < 0.05). Parotid UP and submandibular EF, assessed by univariated and multivariate logistic regression, showed a significant and independent correlation with pSS diagnosis (p value <0.05). No correlation was found between SGdS semi-quantitative parameters and ESSDAI. The proposed nomogram accuracy was 87%. SGdS is an accurate and reproducible tool for the diagnosis of pSS. ESSDAI was not shown to be correlated with SGdS data. SGdS should be the first-line imaging technique in patients with suspected pSS.

The Quantitative Analgesic Questionnaire: A Tool to Capture Patient-Reported Chronic Pain Medication Use.

PubMed

Robinson-Papp, Jessica; George, Mary Catherine; Wongmek, Arada; Nmashie, Alexandra; Merlin, Jessica S; Ali, Yousaf; Epstein, Lawrence; Green, Mark; Serban, Stelian; Sheth, Parag; Simpson, David M

2015-09-01

The extent to which patients take chronic pain medications as prescribed is not well studied, and there are no generally agreed-upon measures. The Quantitative Analgesic Questionnaire (QAQ) is a new instrument designed to comprehensively document patient-reported medication use, generate scores to quantify it (by individual drug, class, and/or overall), and compare it (qualitatively and/or quantitatively) to the regimen as prescribed. The aim of this study was to describe the development and preliminary validation of the QAQ. The QAQ was studied in a convenience sample of 149 HIV-infected participants. We found that the QAQ scores computed for participants' chronic pain medication regimens were valid based on their correlation with 1) patient-reported pain intensity (r = 0.38; P < 0.001) and 2) experienced pain management physicians' independent quantification of the regimens (r = 0.89; P < 0.001). The QAQ also demonstrated high interrater reliability (r = 0.957; P < 0.001). Detailed examination of the QAQ data in a subset of 34 participants demonstrated that the QAQ revealed suboptimal adherence in 44% of participants and contained information that would not have been gleaned from review of the medical record alone in 94%, including use of over-the-counter medications and quantification of "as needed" dosing. The QAQ also was found to be useful in quantifying change in the medication regimen over time, capturing a change in 50% of the participants from baseline to eight week follow-up. The QAQ is a simple tool that can facilitate understanding of patient-reported chronic pain medication regimens, including calculation of percent adherence and generation of quantitative scores suitable for estimating and tracking change in medication use over time. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

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…

Analytical tools for characterizing biopharmaceuticals and the implications for biosimilars

PubMed Central

Berkowitz, Steven A.; Engen, John R.; Mazzeo, Jeffrey R.; Jones, Graham B.

2013-01-01

Biologics such as monoclonal antibodies are much more complex than small-molecule drugs, which raises challenging questions for the development and regulatory evaluation of follow-on versions of such biopharmaceutical products (also known as biosimilars) and their clinical use once patent protection for the pioneering biologic has expired. With the recent introduction of regulatory pathways for follow-on versions of complex biologics, the role of analytical technologies in comparing biosimilars with the corresponding reference product is attracting substantial interest in establishing the development requirements for biosimilars. Here, we discuss the current state of the art in analytical technologies to assess three characteristics of protein biopharmaceuticals that regulatory authorities have identified as being important in development strategies for biosimilars: post-translational modifications, three-dimensional structures and protein aggregation. PMID:22743980

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.

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

The Xeno-glycomics database (XDB): a relational database of qualitative and quantitative pig glycome repertoire.

PubMed

Park, Hae-Min; Park, Ju-Hyeong; Kim, Yoon-Woo; Kim, Kyoung-Jin; Jeong, Hee-Jin; Jang, Kyoung-Soon; Kim, Byung-Gee; Kim, Yun-Gon

2013-11-15

In recent years, the improvement of mass spectrometry-based glycomics techniques (i.e. highly sensitive, quantitative and high-throughput analytical tools) has enabled us to obtain a large dataset of glycans. Here we present a database named Xeno-glycomics database (XDB) that contains cell- or tissue-specific pig glycomes analyzed with mass spectrometry-based techniques, including a comprehensive pig glycan information on chemical structures, mass values, types and relative quantities. It was designed as a user-friendly web-based interface that allows users to query the database according to pig tissue/cell types or glycan masses. This database will contribute in providing qualitative and quantitative information on glycomes characterized from various pig cells/organs in xenotransplantation and might eventually provide new targets in the α1,3-galactosyltransferase gene-knock out pigs era. The database can be accessed on the web at http://bioinformatics.snu.ac.kr/xdb.

Quantitative determination of BAF312, a S1P-R modulator, in human urine by LC-MS/MS: prevention and recovery of lost analyte due to container surface adsorption.

PubMed

Li, Wenkui; Luo, Suyi; Smith, Harold T; Tse, Francis L S

2010-02-15

Analyte loss due to non-specific binding, especially container surface adsorption, is not uncommon in the quantitative analysis of urine samples. In developing a sensitive LC-MS/MS method for the determination of a drug candidate, BAF312, in human urine, a simple procedure was outlined for identification, confirmation and prevention of analyte non-specific binding to a container surface and to recover the 'non-specific loss' of an analyte, if no transfer has occurred to the original urine samples. Non-specific binding or container surface adsorption can be quickly identified by using freshly spiked urine calibration standards and pre-pooled QC samples during a LC-MS/MS feasibility run. The resulting low recovery of an analyte in urine samples can be prevented through the use of additives, such as the non-ionic surfactant Tween-80, CHAPS and others, to the container prior to urine sample collection. If the urine samples have not been transferred from the bulk container, the 'non-specific binding' of an analyte to the container surface can be reversed by the addition of a specified amount of CHAPS, Tween-80 or bovine serum albumin, followed by appropriate mixing. Among the above agents, Tween-80 is the most cost-effective. beta-cyclodextrin may be suitable in stabilizing the analyte of interest in urine via pre-treating the matrix with the agent. However, post-addition of beta-cyclodextrin to untreated urine samples does not recover the 'lost' analyte due to non-specific binding or container surface adsorption. In the case of BAF312, a dynamic range of 0.0200-20.0 ng/ml in human urine was validated with an overall accuracy and precision for QC sample results ranging from -3.2 to 5.1% (bias) and 3.9 to 10.2% (CV), respectively. Pre- and post-addition of 0.5% (v/v) Tween-80 to the container provided excellent overall analyte recovery and minimal MS signal suppression when a liquid-liquid extraction in combination with an isocratic LC separation was employed. The

Photography by Cameras Integrated in Smartphones as a Tool for Analytical Chemistry Represented by an Butyrylcholinesterase Activity Assay.

PubMed

Pohanka, Miroslav

2015-06-11

Smartphones are popular devices frequently equipped with sensitive sensors and great computational ability. Despite the widespread availability of smartphones, practical uses in analytical chemistry are limited, though some papers have proposed promising applications. In the present paper, a smartphone is used as a tool for the determination of cholinesterasemia i.e., the determination of a biochemical marker butyrylcholinesterase (BChE). The work should demonstrate suitability of a smartphone-integrated camera for analytical purposes. Paper strips soaked with indoxylacetate were used for the determination of BChE activity, while the standard Ellman's assay was used as a reference measurement. In the smartphone-based assay, BChE converted indoxylacetate to indigo blue and coloration was photographed using the phone's integrated camera. A RGB color model was analyzed and color values for the individual color channels were determined. The assay was verified using plasma samples and samples containing pure BChE, and validated using Ellmans's assay. The smartphone assay was proved to be reliable and applicable for routine diagnoses where BChE serves as a marker (liver function tests; some poisonings, etc.). It can be concluded that the assay is expected to be of practical applicability because of the results' relevance.

Quantitation of HBV DNA in human serum using a branched DNA (bDNA) signal amplification assay.

PubMed

Hendricks, D A; Stowe, B J; Hoo, B S; Kolberg, J; Irvine, B D; Neuwald, P D; Urdea, M S; Perrillo, R P

1995-11-01

The aim of this study was to establish the performance characteristics of a nonradioisotopic branched DNA (bDNA) signal amplification assay for quantitation of hepatitis B virus (HBV) DNA in human serum. Quantitation was determined from a standard curve and expressed as HBV DNA equivalents/mL (Eq/mL; 285,000 Eq = 1 pg of double stranded HBV DNA). The bDNA assay exhibited a nearly four log dynamic range of quantitation and an analytical detection limit of approximately 100,000 Eq/mL. To ensure a specificity of 99.7%, the quantitation limit was set at 700,000 Eq/mL. The interassay percent coefficient of variance for quantification values ranged from 10% to 15% when performed by novice users with different sets of reagents. Using the bDNA assay, HBV DNA was detected in 94% to 100% of hepatitis B e antigen-positive specimens and 27% to 31% of hepatitis B e antigen-negative specimens from chronic HBV-infected patients. The bDNA assay may be useful as a prognostic and therapy monitoring tool for the management of HBV-infected patients undergoing antiviral treatment.

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

Analytical aids in land management planning

Treesearch

David R. Betters

1978-01-01

Quantitative techniques may be applied to aid in completing various phases of land management planning. Analytical procedures which have been used include a procedure for public involvement, PUBLIC; a matrix information generator, MAGE5; an allocation procedure, linear programming (LP); and an input-output economic analysis (EA). These techniques have proven useful in...

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...

Managing complex research datasets using electronic tools: a meta-analysis exemplar.

PubMed

Brown, Sharon A; Martin, Ellen E; Garcia, Theresa J; Winter, Mary A; García, Alexandra A; Brown, Adama; Cuevas, Heather E; Sumlin, Lisa L

2013-06-01

Meta-analyses of broad scope and complexity require investigators to organize many study documents and manage communication among several research staff. Commercially available electronic tools, for example, EndNote, Adobe Acrobat Pro, Blackboard, Excel, and IBM SPSS Statistics (SPSS), are useful for organizing and tracking the meta-analytic process as well as enhancing communication among research team members. The purpose of this article is to describe the electronic processes designed, using commercially available software, for an extensive, quantitative model-testing meta-analysis. Specific electronic tools improved the efficiency of (a) locating and screening studies, (b) screening and organizing studies and other project documents, (c) extracting data from primary studies, (d) checking data accuracy and analyses, and (e) communication among team members. The major limitation in designing and implementing a fully electronic system for meta-analysis was the requisite upfront time to decide on which electronic tools to use, determine how these tools would be used, develop clear guidelines for their use, and train members of the research team. The electronic process described here has been useful in streamlining the process of conducting this complex meta-analysis and enhancing communication and sharing documents among research team members.

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...

Quantitative Electron Probe Microanalysis: State of the Art

NASA Technical Reports Server (NTRS)

Carpernter, P. K.

2005-01-01

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete

Capturing student mathematical engagement through differently enacted classroom practices: applying a modification of Watson's analytical tool

NASA Astrophysics Data System (ADS)

Patahuddin, Sitti Maesuri; Puteri, Indira; Lowrie, Tom; Logan, Tracy; Rika, Baiq

2018-04-01

This study examined student mathematical engagement through the intended and enacted lessons taught by two teachers in two different middle schools in Indonesia. The intended lesson was developed using the ELPSA learning design to promote mathematical engagement. Based on the premise that students will react to the mathematical tasks in the forms of words and actions, the analysis focused on identifying the types of mathematical engagement promoted through the intended lesson and performed by students during the lesson. Using modified Watson's analytical tool (2007), students' engagement was captured from what the participants' did or said mathematically. We found that teachers' enacted practices had an influence on student mathematical engagement. The teacher who demonstrated content in explicit ways tended to limit the richness of the engagement; whereas the teacher who presented activities in an open-ended manner fostered engagement.

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

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

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

Quantitative Hydrocarbon Surface Analysis

NASA Technical Reports Server (NTRS)

Douglas, Vonnie M.

2000-01-01

The elimination of ozone depleting substances, such as carbon tetrachloride, has resulted in the use of new analytical techniques for cleanliness verification and contamination sampling. The last remaining application at Rocketdyne which required a replacement technique was the quantitative analysis of hydrocarbons by infrared spectrometry. This application, which previously utilized carbon tetrachloride, was successfully modified using the SOC-400, a compact portable FTIR manufactured by Surface Optics Corporation. This instrument can quantitatively measure and identify hydrocarbons from solvent flush of hardware as well as directly analyze the surface of metallic components without the use of ozone depleting chemicals. Several sampling accessories are utilized to perform analysis for various applications.

Automated Quantitative Rare Earth Elements Mineralogy by Scanning Electron Microscopy

NASA Astrophysics Data System (ADS)

Sindern, Sven; Meyer, F. Michael

2016-09-01

Increasing industrial demand of rare earth elements (REEs) stems from the central role they play for advanced technologies and the accelerating move away from carbon-based fuels. However, REE production is often hampered by the chemical, mineralogical as well as textural complexity of the ores with a need for better understanding of their salient properties. This is not only essential for in-depth genetic interpretations but also for a robust assessment of ore quality and economic viability. The design of energy and cost-efficient processing of REE ores depends heavily on information about REE element deportment that can be made available employing automated quantitative process mineralogy. Quantitative mineralogy assigns numeric values to compositional and textural properties of mineral matter. Scanning electron microscopy (SEM) combined with a suitable software package for acquisition of backscatter electron and X-ray signals, phase assignment and image analysis is one of the most efficient tools for quantitative mineralogy. The four different SEM-based automated quantitative mineralogy systems, i.e. FEI QEMSCAN and MLA, Tescan TIMA and Zeiss Mineralogic Mining, which are commercially available, are briefly characterized. Using examples of quantitative REE mineralogy, this chapter illustrates capabilities and limitations of automated SEM-based systems. Chemical variability of REE minerals and analytical uncertainty can reduce performance of phase assignment. This is shown for the REE phases parisite and synchysite. In another example from a monazite REE deposit, the quantitative mineralogical parameters surface roughness and mineral association derived from image analysis are applied for automated discrimination of apatite formed in a breakdown reaction of monazite and apatite formed by metamorphism prior to monazite breakdown. SEM-based automated mineralogy fulfils all requirements for characterization of complex unconventional REE ores that will become

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…

Measurements of the quantitative lateral analytical resolution at evaporated aluminium and silver layers with the JEOL JXA-8530F FEG-EPMA

NASA Astrophysics Data System (ADS)

Berger, D.; Nissen, J.

2018-01-01

The studies in this paper are part of systematic investigations of the lateral analytical resolution of the field emission electron microprobe JEOL JXA-8530F. Hereby, the quantitative lateral resolution, which is achieved in practise, is in the focus of interest. The approach is to determine the minimum thickness of a metallic layer for which an accurate quantitative element analysis in cross-section is still possible. Previous measurements were accomplished at sputtered gold (Z = 79) layers, where a lateral resolution in the range of 140 to 170 nm was achieved at suitable parameters of the microprobe. To study the Z-dependence of the lateral resolution, now aluminium (Z = 13) resp. silver (Z = 47) layers with different thicknesses were generated by evaporation and prepared in cross-section subsequently by use of a focussed Ga-ion beam (FIB). Each layer was analysed quantitatively with different electron energies. The thinnest layer which can be resolved specifies the best lateral resolution. These measured values were compared on the one hand with Monte Carlo simulations and on the other hand with predictions from formulas from the literature. The measurements fit well to the simulated and calculated values, except the ones at the lowest primary electron energies with an overvoltage below ˜ 2. The reason for this discrepancy is not clear yet and has to be clarified by further investigations. The results apply for any microanalyser - even with energy-dispersive X-ray spectrometry (EDS) detection - if the probe diameters, which might deviate from those of the JEOL JXA-8530F, at suitable analysing parameters are considered.

Development of a comprehensive analytical platform for the detection and quantitation of food fraud using a biomarker approach. The oregano adulteration case study.

PubMed

Wielogorska, Ewa; Chevallier, Olivier; Black, Connor; Galvin-King, Pamela; Delêtre, Marc; Kelleher, Colin T; Haughey, Simon A; Elliott, Christopher T

2018-01-15

Due to increasing number of food fraud incidents, there is an inherent need for the development and implementation of analytical platforms enabling detection and quantitation of adulteration. In this study a set of unique biomarkers of commonly found oregano adulterants became the targets in the development of a LC-MS/MS method which underwent a rigorous in-house validation. The method presented very high selectivity and specificity, excellent linearity (R 2 >0.988) low decision limits and detection capabilities (<2%), acceptable accuracy (intra-assay 92-113%, inter-assay 69-138%) and precision (CV<20%). The method was compared with an established FTIR screening assay and revealed a good correlation of quali- and quantitative results (R 2 >0.81). An assessment of 54 suspected adulterated oregano samples revealed that almost 90% of them contained at least one bulking agent, with a median level of adulteration of 50%. Such innovative methodologies need to be established as routine testing procedures to detect and ultimately deter food fraud. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular Rotors for Universal Quantitation of Nanoscale Hydrophobic Interfaces in Microplate Format.

PubMed

Bisso, Paul W; Tai, Michelle; Katepalli, Hari; Bertrand, Nicolas; Blankschtein, Daniel; Langer, Robert

2018-01-10

Hydrophobic self-assembly pairs diverse chemical precursors and simple formulation processes to access a vast array of functional colloids. Exploration of this design space, however, is stymied by lack of broadly general, high-throughput colloid characterization tools. Here, we show that a narrow structural subset of fluorescent, zwitterionic molecular rotors, dialkylaminostilbazolium sulfonates [DASS] with intermediate-length alkyl tails, fills this major analytical void by quantitatively sensing hydrophobic interfaces in microplate format. DASS dyes supersede existing interfacial probes by avoiding off-target fluorogenic interactions and dye aggregation while preserving hydrophobic partitioning strength. To illustrate the generality of this approach, we demonstrate (i) a microplate-based technique for measuring mass concentration of small (20-200 nm), dilute (submicrogram sensitivity) drug delivery nanoparticles; (ii) elimination of particle size, surfactant chemistry, and throughput constraints on quantifying the complex surfactant/metal oxide adsorption isotherms critical for environmental remediation and enhanced oil recovery; and (iii) more reliable self-assembly onset quantitation for chemically and structurally distinct amphiphiles. These methods could streamline the development of nanotechnologies for a broad range of applications.

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 ANALYTICAL CHEMISTRY OF ...

EPA Pesticide Factsheets

Within the scope of a number of emerging contaminant issues in environmental analysis, one area that has received a great deal of public interest has been the assessment of the role of pharmaceuticals and personal care products (PPCPs) as stressors and agents of change in ecosystems as well as their role in unplanned human exposure. The relationship between personal actions and the occurrence of PPCPs in the environment is clear-cut and comprehensible to the public. In this overview, we attempt to examine the separations aspect of the analytical approach to the vast array of potential analytes among this class of compounds. We also highlight the relationship between these compounds and endocrine disrupting compounds (EDCs) and between PPCPs and EDCs and the more traditional environmental analytes such as the persistent organic pollutants (POPs). Although the spectrum of chemical behavior extends from hydrophobic to hydrophilic, the current focus has shifted to moderately and highly polar analytes. Thus, emphasis on HPLC and LC/MS has grown and MS/MS has become a detection technique of choice with either electrospray ionization or atmospheric pressure chemical ionization. This contrasts markedly with the bench mark approach of capillary GC, GC/MS and electron ionization in traditional environmental analysis. The expansion of the analyte list has fostered new vigor in the development of environmental analytical chemistry, modernized the range of tools appli

Visual Analytics for Law Enforcement: Deploying a Service-Oriented Analytic Framework for Web-based Visualization

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

Dowson, Scott T.; Bruce, Joseph R.; Best, Daniel M.

2009-04-14

This paper presents key components of the Law Enforcement Information Framework (LEIF) that provides communications, situational awareness, and visual analytics tools in a service-oriented architecture supporting web-based desktop and handheld device users. LEIF simplifies interfaces and visualizations of well-established visual analytical techniques to improve usability. Advanced analytics capability is maintained by enhancing the underlying processing to support the new interface. LEIF development is driven by real-world user feedback gathered through deployments at three operational law enforcement organizations in the US. LEIF incorporates a robust information ingest pipeline supporting a wide variety of information formats. LEIF also insulates interface and analyticalmore » components from information sources making it easier to adapt the framework for many different data repositories.« less

Detection of UV-treatment effects on plankton by rapid analytic tools for ballast water compliance monitoring immediately following treatment

NASA Astrophysics Data System (ADS)

Bradie, Johanna; Gianoli, Claudio; He, Jianjun; Lo Curto, Alberto; Stehouwer, Peter; Veldhuis, Marcel; Welschmeyer, Nick; Younan, Lawrence; Zaake, André; Bailey, Sarah

2018-03-01

Non-indigenous species seriously threaten native biodiversity. To reduce establishments, the International Maritime Organization established the Convention for the Control and Management of Ships' Ballast Water and Sediments which limits organism concentrations at discharge under regulation D-2. Most ships will comply by using on-board treatment systems to disinfect their ballast water. Port state control officers will need simple, rapid methods to detect compliance. Appropriate monitoring methods may be dependent on treatment type, since different treatments will affect organisms by a variety of mechanisms. Many indicative tools have been developed, but must be examined to ensure the measured variable is an appropriate signal for the response of the organisms to the applied treatment. We assessed the abilities of multiple analytic tools to rapidly detect the effects of a ballast water treatment system based on UV disinfection. All devices detected a large decrease in the concentrations of vital organisms ≥ 50 μm and organisms < 10 μm (mean 82.7-99.7% decrease across devices), but results were more variable for the ≥ 10 to < 50 μm size class (mean 9.0-99.9% decrease across devices). Results confirm the necessity to choose tools capable of detecting the damage inflicted on living organisms, as examined herein for UV-C treatment systems.

ANTONIA perfusion and stroke. A software tool for the multi-purpose analysis of MR perfusion-weighted datasets and quantitative ischemic stroke assessment.

PubMed

Forkert, N D; Cheng, B; Kemmling, A; Thomalla, G; Fiehler, J

2014-01-01

The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation. Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses. For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used. Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.

Visualization and Analytics Tools for Infectious Disease Epidemiology: A Systematic Review

PubMed Central

Carroll, Lauren N.; Au, Alan P.; Detwiler, Landon Todd; Fu, Tsung-chieh; Painter, Ian S.; Abernethy, Neil F.

2014-01-01

Background A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) Identify public health user needs and preferences for infectious disease information visualization tools; (2) Identify existing infectious disease information visualization tools and characterize their architecture and features; (3) Identify commonalities among approaches applied to different data types; and (4) Describe tool usability evaluation efforts and barriers to the adoption of such tools. Methods We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. Results A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and

Visualization and analytics tools for infectious disease epidemiology: a systematic review.

PubMed

Carroll, Lauren N; Au, Alan P; Detwiler, Landon Todd; Fu, Tsung-Chieh; Painter, Ian S; Abernethy, Neil F

2014-10-01

A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools. We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool

Hierarchical Analytical Approaches for Unraveling the Composition of Proprietary Mixtures

EPA Pesticide Factsheets

The composition of commercial mixtures including pesticide inert ingredients, aircraft deicers, and aqueous film-forming foam (AFFF) formulations, and by analogy, fracking fluids, are proprietary. Quantitative analytical methodologies can only be developed for mixture components once their identities are known. Because proprietary mixtures may contain volatile and non-volatile components, a hierarchy of analytical methods is often required for the full identification of all proprietary mixture components.

Analyte species and concentration identification using differentially functionalized microcantilever arrays and artificial neural networks

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

Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J

2006-01-01

In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. Anmore » artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.« less

The Role of Cations on the Performance of Lithium Ion Batteries: A Quantitative Analytical Approach.

PubMed

Nowak, Sascha; Winter, Martin

2018-02-20

Lithium ion batteries are nowadays the state-of-the-art power sources for portable electronic devices and the most promising candidate for energy storage in large-size batteries, e.g., pure and hybrid vehicles. However, the degradation of the cell components minimizes both storage and operation lifetime (calendar and cycle life), which is called aging. Due to the numerous different aging effects, in either the single constituents or their interactions with each other, many reports about methodologies and techniques, both electrochemical and analytical, can be found in the literature. However, quantitative data about the degradation effects were seldom stated. One important effect is the cation distribution and migration during operation. Metal dissolution and metal migration of the cathode and the corresponding deposition of these metals on the graphitic anode are known harmful degradation effects, especially for the formed solid electrolyte interphase on the surface of the anode. Depending on the applied cell chemistries and therefore the cathode material, different mechanisms were reported so far. For lithium manganese oxide based cells, the acidification of the electrolyte due to composition of the conduction salt is attributed as the main source of metal migration. Due to subsequent loss of manganese from the cathode, the overall performance of the cell is seriously impaired. Based on the obtained observations, this degradation mechanism was adapted to lithium nickel cobalt manganese based cells as main cause of the capacity fading. However, with the help a developed total X-ray fluorescence method and additional surface and electrolyte investigations, the proposed HF based mechanism was disproven. Instead, the migration was directly associated with material defects or mechanical spalling of the particles. Furthermore, with the obtained quantitative data of the migrated transition metals on the anode and separator, the contribution on the capacity fade was

Towards a green analytical laboratory: microextraction techniques as a useful tool for the monitoring of polluted soils

NASA Astrophysics Data System (ADS)

Lopez-Garcia, Ignacio; Viñas, Pilar; Campillo, Natalia; Hernandez Cordoba, Manuel; Perez Sirvent, Carmen

2016-04-01

Microextraction techniques are a valuable tool at the analytical laboratory since they allow sensitive measurements of pollutants to be carried out by means of easily available instrumentation. There is a large number of such procedures involving miniaturized liquid-liquid or liquid-solid extractions with the common denominator of using very low amounts (only a few microliters) or even none of organic solvents. Since minimal amounts of reagents are involved, and the generation of residues is consequently minimized, the approach falls within the concept of Green Analytical Chemistry. This general methodology is useful both for inorganic and organic pollutants. Thus, low amounts of metallic ions can be measured without the need of using ICP-MS since this instrument can be replaced by a simple AAS spectrometer which is commonly present in any laboratory and involves low acquisition and maintenance costs. When dealing with organic pollutants, the microextracts obtained can be introduced into liquid or gas chromatographs equipped with common detectors and there is no need for the most sophisticated and expensive mass spectrometers. This communication reports an overview of the advantages of such a methodology, and gives examples for the determination of some particular contaminants in soil and water samples The authors are grateful to the Comunidad Autonóma de la Región de Murcia , Spain (Fundación Séneca, 19888/GERM/15) for financial support

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.

New EVSE Analytical Tools/Models: Electric Vehicle Infrastructure Projection Tool (EVI-Pro)

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

Wood, Eric W; Rames, Clement L; Muratori, Matteo

This presentation addresses the fundamental question of how much charging infrastructure is needed in the United States to support PEVs. It complements ongoing EVSE initiatives by providing a comprehensive analysis of national PEV charging infrastructure requirements. The result is a quantitative estimate for a U.S. network of non-residential (public and workplace) EVSE that would be needed to support broader PEV adoption. The analysis provides guidance to public and private stakeholders who are seeking to provide nationwide charging coverage, improve the EVSE business case by maximizing station utilization, and promote effective use of private/public infrastructure investments.

Quantitative Measurement of Local Infrared Absorption and Dielectric Function with Tip-Enhanced Near-Field Microscopy.

PubMed

Govyadinov, Alexander A; Amenabar, Iban; Huth, Florian; Carney, P Scott; Hillenbrand, Rainer

2013-05-02

Scattering-type scanning near-field optical microscopy (s-SNOM) and Fourier transform infrared nanospectroscopy (nano-FTIR) are emerging tools for nanoscale chemical material identification. Here, we push s-SNOM and nano-FTIR one important step further by enabling them to quantitatively measure local dielectric constants and infrared absorption. Our technique is based on an analytical model, which allows for a simple inversion of the near-field scattering problem. It yields the dielectric permittivity and absorption of samples with 2 orders of magnitude improved spatial resolution compared to far-field measurements and is applicable to a large class of samples including polymers and biological matter. We verify the capabilities by determining the local dielectric permittivity of a PMMA film from nano-FTIR measurements, which is in excellent agreement with far-field ellipsometric data. We further obtain local infrared absorption spectra with unprecedented accuracy in peak position and shape, which is the key to quantitative chemometrics on the nanometer scale.

Quantitative dispersion microscopy

PubMed Central

Fu, Dan; Choi, Wonshik; Sung, Yongjin; Yaqoob, Zahid; Dasari, Ramachandra R.; Feld, Michael

2010-01-01

Refractive index dispersion is an intrinsic optical property and a useful source of contrast in biological imaging studies. In this report, we present the first dispersion phase imaging of living eukaryotic cells. We have developed quantitative dispersion microscopy based on the principle of quantitative phase microscopy. The dual-wavelength quantitative phase microscope makes phase measurements at 310 nm and 400 nm wavelengths to quantify dispersion (refractive index increment ratio) of live cells. The measured dispersion of living HeLa cells is found to be around 1.088, which agrees well with that measured directly for protein solutions using total internal reflection. This technique, together with the dry mass and morphology measurements provided by quantitative phase microscopy, could prove to be a useful tool for distinguishing different types of biomaterials and studying spatial inhomogeneities of biological samples. PMID:21113234

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.

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

Heat as a groundwater tracer in shallow and deep heterogeneous media: Analytical solution, spreadsheet tool, and field applications

USGS Publications Warehouse

Kurylyk, Barret L.; Irvine, Dylan J.; Carey, Sean K.; Briggs, Martin A.; Werkema, Dale D.; Bonham, Mariah

2017-01-01

Groundwater flow advects heat, and thus, the deviation of subsurface temperatures from an expected conduction‐dominated regime can be analysed to estimate vertical water fluxes. A number of analytical approaches have been proposed for using heat as a groundwater tracer, and these have typically assumed a homogeneous medium. However, heterogeneous thermal properties are ubiquitous in subsurface environments, both at the scale of geologic strata and at finer scales in streambeds. Herein, we apply the analytical solution of Shan and Bodvarsson (2004), developed for estimating vertical water fluxes in layered systems, in 2 new environments distinct from previous vadose zone applications. The utility of the solution for studying groundwater‐surface water exchange is demonstrated using temperature data collected from an upwelling streambed with sediment layers, and a simple sensitivity analysis using these data indicates the solution is relatively robust. Also, a deeper temperature profile recorded in a borehole in South Australia is analysed to estimate deeper water fluxes. The analytical solution is able to match observed thermal gradients, including the change in slope at sediment interfaces. Results indicate that not accounting for layering can yield errors in the magnitude and even direction of the inferred Darcy fluxes. A simple automated spreadsheet tool (Flux‐LM) is presented to allow users to input temperature and layer data and solve the inverse problem to estimate groundwater flux rates from shallow (e.g., <1 m) or deep (e.g., up to 100 m) profiles. The solution is not transient, and thus, it should be cautiously applied where diel signals propagate or in deeper zones where multi‐decadal surface signals have disturbed subsurface thermal regimes.

Sensors for detecting analytes in fluids

NASA Technical Reports Server (NTRS)

Lewis, Nathan S. (Inventor); Severin, Erik (Inventor)

1998-01-01

Chemical sensors for detecting analytes in fluids comprise first and second conductive elements (e.g., electrical leads) electrically coupled to and separated by a chemically sensitive resistor which provides an electrical path between the conductive elements. The resistor comprises a plurality of alternating nonconductive regions (comprising a nonconductive organic polymer) and conductive regions (comprising a conductive material) transverse to the electrical path. The resistor provides a difference in resistance between the conductive elements when contacted with a fluid comprising a chemical analyte at a first concentration, than when contacted with a fluid comprising the chemical analyte at a second different concentration. Arrays of such sensors are constructed with at least two sensors having different chemically sensitive resistors providing dissimilar such differences in resistance. Variability in chemical sensitivity from sensor to sensor is provided by qualitatively or quantitatively varying the composition of the conductive and/or nonconductive regions. An electronic nose for detecting an analyte in a fluid may be constructed by using such arrays in conjunction with an electrical measuring device electrically connected to the conductive elements of each sensor.

Sensors for detecting analytes in fluids

NASA Technical Reports Server (NTRS)

Severin, Erik (Inventor); Lewis, Nathan S. (Inventor)

2001-01-01

Chemical sensors for detecting analytes in fluids comprise first and second conductive elements (e.g., electrical leads) electrically coupled to and separated by a chemically sensitive resistor which provides an electrical path between the conductive elements. The resistor comprises a plurality of alternating nonconductive regions (comprising a nonconductive organic polymer) and conductive regions (comprising a conductive material) transverse to the electrical path. The resistor provides a difference in resistance between the conductive elements when contacted with a fluid comprising a chemical analyte at a first concentration, than when contacted with a fluid comprising the chemical analyte at a second different concentration. Arrays of such sensors are constructed with at least two sensors having different chemically sensitive resistors providing dissimilar such differences in resistance. Variability in chemical sensitivity from sensor to sensor is provided by qualitatively or quantitatively varying the composition of the conductive and/or nonconductive regions. An electronic nose for detecting an analyte in a fluid may be constructed by using such arrays in conjunction with an electrical measuring device electrically connected to the conductive elements of each sensor.

Sensors for detecting analytes in fluids

NASA Technical Reports Server (NTRS)

Lewis, Nathan S. (Inventor); Severin, Erik (Inventor)

1999-01-01

Chemical sensors for detecting analytes in fluids comprise first and second conductive elements (e.g., electrical leads) electrically coupled to and separated by a chemically sensitive resistor which provides an electrical path between the conductive elements. The resistor comprises a plurality of alternating nonconductive regions (comprising a nonconductive organic polymer) and conductive regions (comprising a conductive material) transverse to the electrical path. The resistor provides a difference in resistance between the conductive elements when contacted with a fluid comprising a chemical analyte at a first concentration, than when contacted with a fluid comprising the chemical analyte at a second different concentration. Arrays of such sensors are constructed with at least two sensors having different chemically sensitive resistors providing dissimilar such differences in resistance. Variability in chemical sensitivity from sensor to sensor is provided by qualitatively or quantitatively varying the composition of the conductive and/or nonconductive regions. An electronic nose for detecting an analyte in a fluid may be constructed by using such arrays in conjunction with an electrical measuring device electrically connected to the conductive elements of each sensor.

Photography by Cameras Integrated in Smartphones as a Tool for Analytical Chemistry Represented by an Butyrylcholinesterase Activity Assay

PubMed Central

Pohanka, Miroslav

2015-01-01

Smartphones are popular devices frequently equipped with sensitive sensors and great computational ability. Despite the widespread availability of smartphones, practical uses in analytical chemistry are limited, though some papers have proposed promising applications. In the present paper, a smartphone is used as a tool for the determination of cholinesterasemia i.e., the determination of a biochemical marker butyrylcholinesterase (BChE). The work should demonstrate suitability of a smartphone-integrated camera for analytical purposes. Paper strips soaked with indoxylacetate were used for the determination of BChE activity, while the standard Ellman’s assay was used as a reference measurement. In the smartphone-based assay, BChE converted indoxylacetate to indigo blue and coloration was photographed using the phone’s integrated camera. A RGB color model was analyzed and color values for the individual color channels were determined. The assay was verified using plasma samples and samples containing pure BChE, and validated using Ellmans’s assay. The smartphone assay was proved to be reliable and applicable for routine diagnoses where BChE serves as a marker (liver function tests; some poisonings, etc.). It can be concluded that the assay is expected to be of practical applicability because of the results’ relevance. PMID:26110404

The FAQUIRE Approach: FAst, QUantitative, hIghly Resolved and sEnsitivity Enhanced 1H, 13C Data.

PubMed

Farjon, Jonathan; Milande, Clément; Martineau, Estelle; Akoka, Serge; Giraudeau, Patrick

2018-02-06

The targeted analysis of metabolites in complex mixtures is a challenging issue. NMR is one of the major tools in this field, but there is a strong need for more sensitive, better-resolved, and faster quantitative methods. In this framework, we introduce the concept of FAst, QUantitative, hIghly Resolved and sEnsitivity enhanced (FAQUIRE) NMR to push forward the limits of metabolite NMR analysis. 2D 1 H, 13 C 2D quantitative maps are promising alternatives for enhancing the spectral resolution but are highly time-consuming because of (i) the intrinsic nature of 2D, (ii) the longer recycling times required for quantitative conditions, and (iii) the higher number of scans needed to reduce the level of detection/quantification to access low concentrated metabolites. To reach this aim, speeding up the recently developed QUantItative Perfected and pUre shifted HSQC (QUIPU HSQC) is an interesting attempt to develop the FAQUIRE concept. Thanks to the combination of spectral aliasing, nonuniform sampling, and variable repetition time, the acquisition time of 2D quantitative maps is reduced by a factor 6 to 9, while conserving a high spectral resolution thanks to a pure shift approach. The analytical potential of the new Quick QUIPU HSQC (Q QUIPU HSQC) is evaluated on a model metabolite sample, and its potential is shown on breast-cell extracts embedding metabolites at millimolar to submillimolar concentrations.

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Yaxiaer, Yalikun; Kobayashi, Hirofumi; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis - an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

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.

Usefulness of the automatic quantitative estimation tool for cerebral blood flow: clinical assessment of the application software tool AQCEL.

PubMed

Momose, Mitsuhiro; Takaki, Akihiro; Matsushita, Tsuyoshi; Yanagisawa, Shin; Yano, Kesato; Miyasaka, Tadashi; Ogura, Yuka; Kadoya, Masumi

2011-01-01

AQCEL enables automatic reconstruction of single-photon emission computed tomogram (SPECT) without image degradation and quantitative analysis of cerebral blood flow (CBF) after the input of simple parameters. We ascertained the usefulness and quality of images obtained by the application software AQCEL in clinical practice. Twelve patients underwent brain perfusion SPECT using technetium-99m ethyl cysteinate dimer at rest and after acetazolamide (ACZ) loading. Images reconstructed using AQCEL were compared with those reconstructed using conventional filtered back projection (FBP) method for qualitative estimation. Two experienced nuclear medicine physicians interpreted the image quality using the following visual scores: 0, same; 1, slightly superior; 2, superior. For quantitative estimation, the mean CBF values of the normal hemisphere of the 12 patients using ACZ calculated by the AQCEL method were compared with those calculated by the conventional method. The CBF values of the 24 regions of the 3-dimensional stereotaxic region of interest template (3DSRT) calculated by the AQCEL method at rest and after ACZ loading were compared to those calculated by the conventional method. No significant qualitative difference was observed between the AQCEL and conventional FBP methods in the rest study. The average score by the AQCEL method was 0.25 ± 0.45 and that by the conventional method was 0.17 ± 0.39 (P = 0.34). There was a significant qualitative difference between the AQCEL and conventional methods in the ACZ loading study. The average score for AQCEL was 0.83 ± 0.58 and that for the conventional method was 0.08 ± 0.29 (P = 0.003). During quantitative estimation using ACZ, the mean CBF values of 12 patients calculated by the AQCEL method were 3-8% higher than those calculated by the conventional method. The square of the correlation coefficient between these methods was 0.995. While comparing the 24 3DSRT regions of 12 patients, the squares of the correlation

Visual analytics in medical education: impacting analytical reasoning and decision making for quality improvement.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2015-01-01

The medical curriculum is the main tool representing the entire undergraduate medical education. Due to its complexity and multilayered structure it is of limited use to teachers in medical education for quality improvement purposes. In this study we evaluated three visualizations of curriculum data from a pilot course, using teachers from an undergraduate medical program and applying visual analytics methods. We found that visual analytics can be used to positively impacting analytical reasoning and decision making in medical education through the realization of variables capable to enhance human perception and cognition on complex curriculum data. The positive results derived from our evaluation of a medical curriculum and in a small scale, signify the need to expand this method to an entire medical curriculum. As our approach sustains low levels of complexity it opens a new promising direction in medical education informatics research.

Post-translational quantitation by SRM/MRM: applications in cardiology.

PubMed

Gianazza, Erica; Banfi, Cristina

2018-06-04

Post-translational modifications (PTMs) have an important role in the regulation of protein function, localization and interaction with other molecules. PTMs apply a dynamic control of proteins both in physiological and pathological conditions. The study of disease-specific PTMs allows identifying potential biomarkers and developing effective drugs. Enrichment techniques combined with high-resolution MS/MS analysis provide attractive results on PTMs characterization. Selected reaction monitoring/multiple reaction monitoring (SRM/MRM) is a powerful targeted assay for the quantitation and validation of PTMs in complex biological samples. Areas covered: The most frequent PTMs are described in terms of biological role and analytical methods commonly used to detect them. The applications of SRM/MRM for the absolute quantitation of PTMs are reported and a specific section is focused on PTMs detection in proteins that are involved in cardiovascular system and heart diseases. Expert commentary: PTMs characterization in relation to disease pathology is still in progress, but targeted proteomics by LC-MS/MS has significantly upgraded the knowledge in the last years. Advances in enrichment strategies and software tools will facilitate the interpretation of high PTMs complexity. Promising studies confirm the great potentiality of SRM/MRM to study PTMs in cardiovascular field and PTMomics could be very useful in a clinical perspective.

Title: Experimental and analytical study of frictional anisotropy of nanotubes

NASA Astrophysics Data System (ADS)

Riedo, Elisa; Gao, Yang; Li, Tai-De; Chiu, Hsiang-Chih; Kim, Suenne; Klinke, Christian; Tosatti, Erio

The frictional properties of Carbon and Boron Nitride nanotubes (NTs) are very important in a variety of applications, including composite materials, carbon fibers, and micro/nano-electromechanical systems. Atomic force microscopy (AFM) is a powerful tool to investigate with nanoscale resolution the frictional properties of individual NTs. Here, we report on an experimental study of the frictional properties of different types of supported nanotubes by AFM. We also propose a quantitative model to describe and then predict the frictional properties of nanotubes sliding on a substrate along (longitudinal friction) or perpendicular (transverse friction) their axis. This model provides a simple but general analytical relationship that well describes the acquired experimental data. As an example of potential applications, this experimental method combined with the proposed model can guide to design better NTs-ceramic composites, or to self-assemble the nanotubes on a surface in a given direction. M. Lucas et al., Nature Materials 8, 876-881 (2009).

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.

Urinary 24-h creatinine excretion in adults and its use as a simple tool for the estimation of daily urinary analyte excretion from analyte/creatinine ratios in populations.

PubMed

Johner, S A; Boeing, H; Thamm, M; Remer, T

2015-12-01

The assessment of urinary excretion of specific nutrients (e.g. iodine, sodium) is frequently used to monitor a population's nutrient status. However, when only spot urines are available, always a risk of hydration-status-dependent dilution effects and related misinterpretations exists. The aim of the present study was to establish mean values of 24-h creatinine excretion widely applicable for an appropriate estimation of 24-h excretion rates of analytes from spot urines in adults. Twenty-four-hour creatinine excretion from the formerly representative cross-sectional German VERA Study (n=1463, 20-79 years old) was analysed. Linear regression analysis was performed to identify the most important influencing factors of creatinine excretion. In a subsample of the German DONALD Study (n=176, 20-29 years old), the applicability of the 24-h creatinine excretion values of VERA for the estimation of 24-h sodium and iodine excretion from urinary concentration measurements was tested. In the VERA Study, mean 24-h creatinine excretion was 15.4 mmol per day in men and 11.1 mmol per day in women, significantly dependent on sex, age, body weight and body mass index. Based on the established 24-h creatinine excretion values, mean 24-h iodine and sodium excretions could be estimated from respective analyte/creatinine concentrations, with average deviations <10% compared with the actual 24-h means. The present mean values of 24-h creatinine excretion are suggested as a useful tool to derive realistic hydration-status-independent average 24-h excretion rates from urinary analyte/creatinine ratios. We propose to apply these creatinine reference means routinely in biomarker-based studies aiming at characterizing the nutrient or metabolite status of adult populations by simply measuring metabolite/creatinine ratios in spot urines.

Simplex and duplex event-specific analytical methods for functional biotech maize.

PubMed

Lee, Seong-Hun; Kim, Su-Jeong; Yi, Bu-Young

2009-08-26

Analytical methods are very important in the control of genetically modified organism (GMO) labeling systems or living modified organism (LMO) management for biotech crops. Event-specific primers and probes were developed for qualitative and quantitative analysis for biotech maize event 3272 and LY 038 on the basis of the 3' flanking regions, respectively. The qualitative primers confirmed the specificity by a single PCR product and sensitivity to 0.05% as a limit of detection (LOD). Simplex and duplex quantitative methods were also developed using TaqMan real-time PCR. One synthetic plasmid was constructed from two taxon-specific DNA sequences of maize and two event-specific 3' flanking DNA sequences of event 3272 and LY 038 as reference molecules. In-house validation of the quantitative methods was performed using six levels of mixing samples, from 0.1 to 10.0%. As a result, the biases from the true value and the relative deviations were all within the range of +/-30%. Limits of quantitation (LOQs) of the quantitative methods were all 0.1% for simplex real-time PCRs of event 3272 and LY 038 and 0.5% for duplex real-time PCR of LY 038. This study reports that event-specific analytical methods were applicable for qualitative and quantitative analysis for biotech maize event 3272 and LY 038.

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…

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.

Reliable LC-MS quantitative glycomics using iGlycoMab stable isotope labeled glycans as internal standards.

PubMed

Zhou, Shiyue; Tello, Nadia; Harvey, Alex; Boyes, Barry; Orlando, Ron; Mechref, Yehia

2016-06-01

Glycans have numerous functions in various biological processes and participate in the progress of diseases. Reliable quantitative glycomic profiling techniques could contribute to the understanding of the biological functions of glycans, and lead to the discovery of potential glycan biomarkers for diseases. Although LC-MS is a powerful analytical tool for quantitative glycomics, the variation of ionization efficiency and MS intensity bias are influencing quantitation reliability. Internal standards can be utilized for glycomic quantitation by MS-based methods to reduce variability. In this study, we used stable isotope labeled IgG2b monoclonal antibody, iGlycoMab, as an internal standard to reduce potential for errors and to reduce variabililty due to sample digestion, derivatization, and fluctuation of nanoESI efficiency in the LC-MS analysis of permethylated N-glycans released from model glycoproteins, human blood serum, and breast cancer cell line. We observed an unanticipated degradation of isotope labeled glycans, tracked a source of such degradation, and optimized a sample preparation protocol to minimize degradation of the internal standard glycans. All results indicated the effectiveness of using iGlycoMab to minimize errors originating from sample handling and instruments. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative analysis of the rubric as an assessment tool: an empirical study of student peer-group rating

NASA Astrophysics Data System (ADS)

Hafner, John C.; Hafner, Patti M.

2003-12-01

Although the rubric has emerged as one of the most popular assessment tools in progressive educational programs, there is an unfortunate dearth of information in the literature quantifying the actual effectiveness of the rubric as an assessment tool in the hands of the students. This study focuses on the validity and reliability of the rubric as an assessment tool for student peer-group evaluation in an effort to further explore the use and effectiveness of the rubric. A total of 1577 peer-group ratings using a rubric for an oral presentation was used in this 3-year study involving 107 college biology students. A quantitative analysis of the rubric used in this study shows that it is used consistently by both students and the instructor across the study years. Moreover, the rubric appears to be 'gender neutral' and the students' academic strength has no significant bearing on the way that they employ the rubric. A significant, one-to-one relationship (slope = 1.0) between the instructor's assessment and the students' rating is seen across all years using the rubric. A generalizability study yields estimates of inter-rater reliability of moderate values across all years and allows for the estimation of variance components. Taken together, these data indicate that the general form and evaluative criteria of the rubric are clear and that the rubric is a useful assessment tool for peer-group (and self-) assessment by students. To our knowledge, these data provide the first statistical documentation of the validity and reliability of the rubric for student peer-group assessment.

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…

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.

Applications of reversible covalent chemistry in analytical sample preparation.

PubMed

Siegel, David

2012-12-07

Reversible covalent chemistry (RCC) adds another dimension to commonly used sample preparation techniques like solid-phase extraction (SPE), solid-phase microextraction (SPME), molecular imprinted polymers (MIPs) or immuno-affinity cleanup (IAC): chemical selectivity. By selecting analytes according to their covalent reactivity, sample complexity can be reduced significantly, resulting in enhanced analytical performance for low-abundance target analytes. This review gives a comprehensive overview of the applications of RCC in analytical sample preparation. The major reactions covered include reversible boronic ester formation, thiol-disulfide exchange and reversible hydrazone formation, targeting analyte groups like diols (sugars, glycoproteins and glycopeptides, catechols), thiols (cysteinyl-proteins and cysteinyl-peptides) and carbonyls (carbonylated proteins, mycotoxins). Their applications range from low abundance proteomics to reversible protein/peptide labelling to antibody chromatography to quantitative and qualitative food analysis. In discussing the potential of RCC, a special focus is on the conditions and restrictions of the utilized reaction chemistry.

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

2015-10-02

As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

Generalized Subset Designs in Analytical Chemistry.

PubMed

Surowiec, Izabella; Vikström, Ludvig; Hector, Gustaf; Johansson, Erik; Vikström, Conny; Trygg, Johan

2017-06-20

Design of experiments (DOE) is an established methodology in research, development, manufacturing, and production for screening, optimization, and robustness testing. Two-level fractional factorial designs remain the preferred approach due to high information content while keeping the number of experiments low. These types of designs, however, have never been extended to a generalized multilevel reduced design type that would be capable to include both qualitative and quantitative factors. In this Article we describe a novel generalized fractional factorial design. In addition, it also provides complementary and balanced subdesigns analogous to a fold-over in two-level reduced factorial designs. We demonstrate how this design type can be applied with good results in three different applications in analytical chemistry including (a) multivariate calibration using microwave resonance spectroscopy for the determination of water in tablets, (b) stability study in drug product development, and (c) representative sample selection in clinical studies. This demonstrates the potential of generalized fractional factorial designs to be applied in many other areas of analytical chemistry where representative, balanced, and complementary subsets are required, especially when a combination of quantitative and qualitative factors at multiple levels exists.

Evaluating variability and uncertainty separately in microbial quantitative risk assessment using two R packages.

PubMed

Pouillot, Régis; Delignette-Muller, Marie Laure

2010-09-01

Quantitative risk assessment has emerged as a valuable tool to enhance the scientific basis of regulatory decisions in the food safety domain. This article introduces the use of two new computing resources (R packages) specifically developed to help risk assessors in their projects. The first package, "fitdistrplus", gathers tools for choosing and fitting a parametric univariate distribution to a given dataset. The data may be continuous or discrete. Continuous data may be right-, left- or interval-censored as is frequently obtained with analytical methods, with the possibility of various censoring thresholds within the dataset. Bootstrap procedures then allow the assessor to evaluate and model the uncertainty around the parameters and to transfer this information into a quantitative risk assessment model. The second package, "mc2d", helps to build and study two dimensional (or second-order) Monte-Carlo simulations in which the estimation of variability and uncertainty in the risk estimates is separated. This package easily allows the transfer of separated variability and uncertainty along a chain of conditional mathematical and probabilistic models. The usefulness of these packages is illustrated through a risk assessment of hemolytic and uremic syndrome in children linked to the presence of Escherichia coli O157:H7 in ground beef. These R packages are freely available at the Comprehensive R Archive Network (cran.r-project.org). Copyright 2010 Elsevier B.V. All rights reserved.

Managing complex research datasets using electronic tools: A meta-analysis exemplar

PubMed Central

Brown, Sharon A.; Martin, Ellen E.; Garcia, Theresa J.; Winter, Mary A.; García, Alexandra A.; Brown, Adama; Cuevas, Heather E.; Sumlin, Lisa L.

2013-01-01

Meta-analyses of broad scope and complexity require investigators to organize many study documents and manage communication among several research staff. Commercially available electronic tools, e.g., EndNote, Adobe Acrobat Pro, Blackboard, Excel, and IBM SPSS Statistics (SPSS), are useful for organizing and tracking the meta-analytic process, as well as enhancing communication among research team members. The purpose of this paper is to describe the electronic processes we designed, using commercially available software, for an extensive quantitative model-testing meta-analysis we are conducting. Specific electronic tools improved the efficiency of (a) locating and screening studies, (b) screening and organizing studies and other project documents, (c) extracting data from primary studies, (d) checking data accuracy and analyses, and (e) communication among team members. The major limitation in designing and implementing a fully electronic system for meta-analysis was the requisite upfront time to: decide on which electronic tools to use, determine how these tools would be employed, develop clear guidelines for their use, and train members of the research team. The electronic process described here has been useful in streamlining the process of conducting this complex meta-analysis and enhancing communication and sharing documents among research team members. PMID:23681256

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

PubMed

Calderón-Celis, Francisco; Encinar, Jorge Ruiz; Sanz-Medel, Alfredo

2017-07-31

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and

Quantitative Analysis of the Educational Infrastructure in Colombia Through the Use of a Georeferencing Software and Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Cala Estupiñan, Jose Luis; María González Bernal, Lina; Ponz Tienda, Jose Luis; Gutierrez Bucheli, Laura Andrea; Alejandro Arboleda, Carlos

2017-10-01

The distribution policies of the national budget have been showing an increasing trend of the investment in education infrastructure. This is the reason that makes it necessary to identify the territories with the greatest number of facilities (such as schools, colleges, universities and libraries) and those lacking this type of infrastructure, in order to know where a possible government intervention is required. This work is not intended to give a judgment on the qualitative state of the national infrastructure. It focuses, in terms of infrastructure, on Colombia’s quantitative status of the educational sector, by identifying the territories with more facilities, such as schools, colleges, universities and public libraries. To do this a quantitative index will be created to identify if the coverage of educational infrastructure at departmental level is enough, by taking into account not only the number of facilities, but also the population and the area of influence each one has. The above study is framed within a project of the University of the Andes called “visible Infrastructure”. The index is obtained through a hierarchical analytical process (AHP) and subsequently a linear equation that reflects the variables investigated. The validation of this index is performed through correlations and regressions of social, economic and cultural indicators determined by official entities. All the information on which the analysis is based is official and public. With the end of the armed conflict, it is necessary to focus the planning of public policies to heal the social gaps that the most vulnerable population needs.

Quantitative Analysis of Nail Polish Remover Using Nuclear Magnetic Resonance Spectroscopy Revisited

ERIC Educational Resources Information Center

Hoffmann, Markus M.; Caccamis, Joshua T.; Heitz, Mark P.; Schlecht, Kenneth D.

2008-01-01

Substantial modifications are presented for a previously described experiment using nuclear magnetic resonance (NMR) spectroscopy to quantitatively determine analytes in commercial nail polish remover. The revised experiment is intended for a second- or third-year laboratory course in analytical chemistry and can be conducted for larger laboratory…

HPLC-ESI-QTOF-MS as a powerful analytical tool for characterising phenolic compounds in olive-leaf extracts.

PubMed

Quirantes-Piné, Rosa; Lozano-Sánchez, Jesús; Herrero, Miguel; Ibáñez, Elena; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto

2013-01-01

Olea europaea L. leaves may be considered a cheap, easily available natural source of phenolic compounds. In a previous study we evaluated the possibility of obtaining bioactive phenolic compounds from olive leaves by pressurised liquid extraction (PLE) for their use as natural anti-oxidants. The alimentary use of these kinds of extract makes comprehensive knowledge of their composition essential. To undertake a comprehensive characterisation of two olive-leaf extracts obtained by PLE using high-performance liquid chromatography coupled to electrospray ionisation and quadrupole time-of-flight mass spectrometry (HPLC-ESI-QTOF-MS). Olive leaves were extracted by PLE using ethanol and water as extraction solvents at 150°C and 200°C respectively. Separation was carried out in a HPLC system equipped with a C₁₈-column working in a gradient elution programme coupled to ESI-QTOF-MS operating in negative ion mode. This analytical platform was able to detect 48 compounds and tentatively identify 31 different phenolic compounds in these extracts, including secoiridoids, simple phenols, flavonoids, cinnamic-acid derivatives and benzoic acids. Lucidumoside C was also identified for the first time in olive leaves. The coupling of HPLC-ESI-QTOF-MS led to the in-depth characterisation of the olive-leaf extracts on the basis of mass accuracy, true isotopic pattern and tandem mass spectrometry (MS/MS) spectra. We may conclude therefore that this analytical tool is very valuable in the study of phenolic compounds in plant matrices. Copyright © 2012 John Wiley & Sons, Ltd.

Modeling with Young Students--Quantitative and Qualitative.

ERIC Educational Resources Information Center

Bliss, Joan; Ogborn, Jon; Boohan, Richard; Brosnan, Tim; Mellar, Harvey; Sakonidis, Babis

1999-01-01

A project created tasks and tools to investigate quality and nature of 11- to 14-year-old pupils' reasoning with quantitative and qualitative computer-based modeling tools. Tasks and tools were used in two innovative modes of learning: expressive, where pupils created their own models, and exploratory, where pupils investigated an expert's model.…

Assessing the impact of natural policy experiments on socioeconomic inequalities in health: how to apply commonly used quantitative analytical methods?

PubMed

Hu, Yannan; van Lenthe, Frank J; Hoffmann, Rasmus; van Hedel, Karen; Mackenbach, Johan P

2017-04-20

The scientific evidence-base for policies to tackle health inequalities is limited. Natural policy experiments (NPE) have drawn increasing attention as a means to evaluating the effects of policies on health. Several analytical methods can be used to evaluate the outcomes of NPEs in terms of average population health, but it is unclear whether they can also be used to assess the outcomes of NPEs in terms of health inequalities. The aim of this study therefore was to assess whether, and to demonstrate how, a number of commonly used analytical methods for the evaluation of NPEs can be applied to quantify the effect of policies on health inequalities. We identified seven quantitative analytical methods for the evaluation of NPEs: regression adjustment, propensity score matching, difference-in-differences analysis, fixed effects analysis, instrumental variable analysis, regression discontinuity and interrupted time-series. We assessed whether these methods can be used to quantify the effect of policies on the magnitude of health inequalities either by conducting a stratified analysis or by including an interaction term, and illustrated both approaches in a fictitious numerical example. All seven methods can be used to quantify the equity impact of policies on absolute and relative inequalities in health by conducting an analysis stratified by socioeconomic position, and all but one (propensity score matching) can be used to quantify equity impacts by inclusion of an interaction term between socioeconomic position and policy exposure. Methods commonly used in economics and econometrics for the evaluation of NPEs can also be applied to assess the equity impact of policies, and our illustrations provide guidance on how to do this appropriately. The low external validity of results from instrumental variable analysis and regression discontinuity makes these methods less desirable for assessing policy effects on population-level health inequalities. Increased use of the

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

Piezoelectric sensors based on molecular imprinted polymers for detection of low molecular mass analytes.

PubMed

Uludağ, Yildiz; Piletsky, Sergey A; Turner, Anthony P F; Cooper, Matthew A

2007-11-01

Biomimetic recognition elements employed for the detection of analytes are commonly based on proteinaceous affibodies, immunoglobulins, single-chain and single-domain antibody fragments or aptamers. The alternative supra-molecular approach using a molecularly imprinted polymer now has proven utility in numerous applications ranging from liquid chromatography to bioassays. Despite inherent advantages compared with biochemical/biological recognition (which include robustness, storage endurance and lower costs) there are few contributions that describe quantitative analytical applications of molecularly imprinted polymers for relevant small molecular mass compounds in real-world samples. There is, however, significant literature describing the use of low-power, portable piezoelectric transducers to detect analytes in environmental monitoring and other application areas. Here we review the combination of molecularly imprinted polymers as recognition elements with piezoelectric biosensors for quantitative detection of small molecules. Analytes are classified by type and sample matrix presentation and various molecularly imprinted polymer synthetic fabrication strategies are also reviewed.

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

Development and Validation of a Multiplexed Protein Quantitation Assay for the Determination of Three Recombinant Proteins in Soybean Tissues by Liquid Chromatography with Tandem Mass Spectrometry.

PubMed

Hill, Ryan C; Oman, Trent J; Shan, Guomin; Schafer, Barry; Eble, Julie; Chen, Cynthia

2015-08-26

Currently, traditional immunochemistry technologies such as enzyme-linked immunosorbent assays (ELISA) are the predominant analytical tool used to measure levels of recombinant proteins expressed in genetically engineered (GE) plants. Recent advances in agricultural biotechnology have created a need to develop methods capable of selectively detecting and quantifying multiple proteins in complex matrices because of increasing numbers of transgenic proteins being coexpressed or "stacked" to achieve tolerance to multiple herbicides or to provide multiple modes of action for insect control. A multiplexing analytical method utilizing liquid chromatography with tandem mass spectrometry (LC-MS/MS) has been developed and validated to quantify three herbicide-tolerant proteins in soybean tissues: aryloxyalkanoate dioxygenase (AAD-12), 5-enol-pyruvylshikimate-3-phosphate synthase (2mEPSPS), and phosphinothricin acetyltransferase (PAT). Results from the validation showed high recovery and precision over multiple analysts and laboratories. Results from this method were comparable to those obtained with ELISA with respect to protein quantitation, and the described method was demonstrated to be suitable for multiplex quantitation of transgenic proteins in GE crops.

An overview on forensic analysis devoted to analytical chemists.

PubMed

Castillo-Peinado, L S; Luque de Castro, M D

2017-05-15

The present article has as main aim to show analytical chemists interested in forensic analysis the world they will face if decision in favor of being a forensic analytical chemist is adopted. With this purpose, the most outstanding aspects of forensic analysis in dealing with sampling (involving both bodily and no bodily samples), sample preparation, and analytical equipment used in detection, identification and quantitation of key sample components are critically discussed. The role of the great omics in forensic analysis, and the growing role of the youngest of the great omics -metabolomics- are also discussed. The foreseeable role of integrative omics is also outlined. Copyright © 2017 Elsevier B.V. All rights reserved.

An overview of quantitative approaches in Gestalt perception.

PubMed

Jäkel, Frank; Singh, Manish; Wichmann, Felix A; Herzog, Michael H

2016-09-01

Gestalt psychology is often criticized as lacking quantitative measurements and precise mathematical models. While this is true of the early Gestalt school, today there are many quantitative approaches in Gestalt perception and the special issue of Vision Research "Quantitative Approaches in Gestalt Perception" showcases the current state-of-the-art. In this article we give an overview of these current approaches. For example, ideal observer models are one of the standard quantitative tools in vision research and there is a clear trend to try and apply this tool to Gestalt perception and thereby integrate Gestalt perception into mainstream vision research. More generally, Bayesian models, long popular in other areas of vision research, are increasingly being employed to model perceptual grouping as well. Thus, although experimental and theoretical approaches to Gestalt perception remain quite diverse, we are hopeful that these quantitative trends will pave the way for a unified theory. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

PubMed

Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

2016-04-07

Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

Teaching quantitative biology: goals, assessments, and resources

PubMed Central

Aikens, Melissa L.; Dolan, Erin L.

2014-01-01

More than a decade has passed since the publication of BIO2010, calling for an increased emphasis on quantitative skills in the undergraduate biology curriculum. In that time, relatively few papers have been published that describe educational innovations in quantitative biology or provide evidence of their effects on students. Using a “backward design” framework, we lay out quantitative skill and attitude goals, assessment strategies, and teaching resources to help biologists teach more quantitatively. Collaborations between quantitative biologists and education researchers are necessary to develop a broader and more appropriate suite of assessment tools, and to provide much-needed evidence on how particular teaching strategies affect biology students' quantitative skill development and attitudes toward quantitative work. PMID:25368425

SERS-based application in food analytics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cialla-May, Dana; Radu, Andreea; Jahn, Martin; Weber, Karina; Popp, Jürgen

2017-02-01

To establish detection schemes in life science applications, specific and sensitive methods allowing for fast detection times are required. Due to the interaction of molecules with strong electromagnetic fields excited at metallic nanostructures, the molecular fingerprint specific Raman spectrum is increased by several orders of magnitude. This effect is described as surface-enhanced Raman spectroscopy (SERS) and became a very powerful analytical tool in many fields of application. Within this presentation, we will introduce innovative bottom-up strategies to prepare SERS-active nanostructures coated with a lipophilic sensor layer. To do so, the food colorant Sudan III, an indirect carcinogen substance found in chili powder, palm oil or spice mixtures, is detected quantitatively in the background of the competitor riboflavin as well as paprika powder extracts. The SERS-based detection of azorubine (E122) in commercial available beverages with different complexity (e.g. sugar content, alcohol concentration) illustrates the strong potential of SERS as a qualitative as well as semiquantitative prescan method in food analytics. Here, a good agreement between the estimated concentration employing SERS as well as the gold standard technique HPLC, a highly laborious method, is found. Finally, SERS is applied to detect vitamin B2 and B12 in cereals as well as the estimate the ratio of lycopene and β-carotene in tomatoes. Acknowledgement: Funding the projects "QuantiSERS" and "Jenaer Biochip Initiative 2.0" within the framework "InnoProfile Transfer - Unternehmen Region" the Federal Ministry of Education and Research, Germany (BMBF) is gratefully acknowledged.

Comparison of selected analytical techniques for protein sizing, quantitation and molecular weight determination.

PubMed

Goetz, H; Kuschel, M; Wulff, T; Sauber, C; Miller, C; Fisher, S; Woodward, C

2004-09-30

Protein analysis techniques are developing fast due to the growing number of proteins obtained by recombinant DNA techniques. In the present paper we compare selected techniques, which are used for protein sizing, quantitation and molecular weight determination: sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE), lab-on-a-chip or microfluidics technology (LoaC), size exclusion chromatography (SEC) and mass spectrometry (MS). We compare advantages and limitations of each technique in respect to different application areas, analysis time, protein sizing and quantitation performance.

On-line near infrared spectroscopy as a Process Analytical Technology (PAT) tool to control an industrial seeded API crystallization.

PubMed

Schaefer, C; Lecomte, C; Clicq, D; Merschaert, A; Norrant, E; Fotiadu, F

2013-09-01

The final step of an active pharmaceutical ingredient (API) manufacturing synthesis process consists of a crystallization during which the API and residual solvent contents have to be quantified precisely in order to reach a predefined seeding point. A feasibility study was conducted to demonstrate the suitability of on-line NIR spectroscopy to control this step in line with new version of the European Medicines Agency (EMA) guideline [1]. A quantitative method was developed at laboratory scale using statistical design of experiments (DOE) and multivariate data analysis such as principal component analysis (PCA) and partial least squares (PLS) regression. NIR models were built to quantify the API in the range of 9-12% (w/w) and to quantify the residual methanol in the range of 0-3% (w/w). To improve the predictive ability of the models, the development procedure encompassed: outliers elimination, optimum model rank definition, spectral range and spectral pre-treatment selection. Conventional criteria such as, number of PLS factors, R(2), root mean square errors of calibration, cross-validation and prediction (RMSEC, RMSECV, RMSEP) enabled the selection of three model candidates. These models were tested in the industrial pilot plant during three technical campaigns. Results of the most suitable models were evaluated against to the chromatographic reference methods. Maximum relative bias of 2.88% was obtained about API target content. Absolute bias of 0.01 and 0.02% (w/w) respectively were achieved at methanol content levels of 0.10 and 0.13% (w/w). The repeatability was assessed as sufficient for the on-line monitoring of the 2 analytes. The present feasibility study confirmed the possibility to use on-line NIR spectroscopy as a PAT tool to monitor in real-time both the API and the residual methanol contents, in order to control the seeding of an API crystallization at industrial scale. Furthermore, the successful scale-up of the method proved its capability to be

Tools for Genetic Studies in Experimental Populations of Polyploids.

PubMed

Bourke, Peter M; Voorrips, Roeland E; Visser, Richard G F; Maliepaard, Chris

2018-01-01

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies

Tools for Genetic Studies in Experimental Populations of Polyploids

PubMed Central

Bourke, Peter M.; Voorrips, Roeland E.; Visser, Richard G. F.; Maliepaard, Chris

2018-01-01

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies

Sensor arrays for detecting analytes in fluids

NASA Technical Reports Server (NTRS)

Lewis, Nathan S. (Inventor); Freund, Michael S. (Inventor)

1996-01-01

Chemical sensors for detecting analytes in fluids comprise first and second conductive elements (e.g. electrical leads) electrically coupled to and separated by a chemically sensitive resistor which provides an electrical path between the conductive elements. The resistor comprises a plurality of alternating nonconductive regions (comprising a nonconductive organic polymer) and conductive regions (comprising a conductive material) transverse to the electrical path. The resistor provides a difference in resistance between the conductive elements when contacted with a fluid comprising a chemical analyte at a first concentration, than when contacted with a fluid comprising the chemical analyte at a second different concentration. Arrays of such sensors are constructed with at least two sensors having different chemically sensitive resistors providing dissimilar such differences in resistance. Variability in chemical sensitivity from sensor to sensor is provided by qualitatively or quantitatively varying the composition of the conductive and/or nonconductive regions. An electronic nose for detecting an analyte in a fluid may be constructed by using such arrays in conjunction with an electrical measuring device electrically connected to the conductive elements of each sensor.

High Performance Liquid Chromatography of Vitamin A: A Quantitative Determination.

ERIC Educational Resources Information Center

Bohman, Ove; And Others

1982-01-01

Experimental procedures are provided for the quantitative determination of Vitamin A (retinol) in food products by analytical liquid chromatography. Standard addition and calibration curve extraction methods are outlined. (SK)

Analytical Validation of Quantitative Real-Time PCR Methods for Quantification of Trypanosoma cruzi DNA in Blood Samples from Chagas Disease Patients

PubMed Central

Ramírez, Juan Carlos; Cura, Carolina Inés; Moreira, Otacilio da Cruz; Lages-Silva, Eliane; Juiz, Natalia; Velázquez, Elsa; Ramírez, Juan David; Alberti, Anahí; Pavia, Paula; Flores-Chávez, María Delmans; Muñoz-Calderón, Arturo; Pérez-Morales, Deyanira; Santalla, José; Guedes, Paulo Marcos da Matta; Peneau, Julie; Marcet, Paula; Padilla, Carlos; Cruz-Robles, David; Valencia, Edward; Crisante, Gladys Elena; Greif, Gonzalo; Zulantay, Inés; Costales, Jaime Alfredo; Alvarez-Martínez, Miriam; Martínez, Norma Edith; Villarroel, Rodrigo; Villarroel, Sandro; Sánchez, Zunilda; Bisio, Margarita; Parrado, Rudy; Galvão, Lúcia Maria da Cunha; da Câmara, Antonia Cláudia Jácome; Espinoza, Bertha; de Noya, Belkisyole Alarcón; Puerta, Concepción; Riarte, Adelina; Diosque, Patricio; Sosa-Estani, Sergio; Guhl, Felipe; Ribeiro, Isabela; Aznar, Christine; Britto, Constança; Yadón, Zaida Estela; Schijman, Alejandro G.

2015-01-01

An international study was performed by 26 experienced PCR laboratories from 14 countries to assess the performance of duplex quantitative real-time PCR (qPCR) strategies on the basis of TaqMan probes for detection and quantification of parasitic loads in peripheral blood samples from Chagas disease patients. Two methods were studied: Satellite DNA (SatDNA) qPCR and kinetoplastid DNA (kDNA) qPCR. Both methods included an internal amplification control. Reportable range, analytical sensitivity, limits of detection and quantification, and precision were estimated according to international guidelines. In addition, inclusivity and exclusivity were estimated with DNA from stocks representing the different Trypanosoma cruzi discrete typing units and Trypanosoma rangeli and Leishmania spp. Both methods were challenged against 156 blood samples provided by the participant laboratories, including samples from acute and chronic patients with varied clinical findings, infected by oral route or vectorial transmission. kDNA qPCR showed better analytical sensitivity than SatDNA qPCR with limits of detection of 0.23 and 0.70 parasite equivalents/mL, respectively. Analyses of clinical samples revealed a high concordance in terms of sensitivity and parasitic loads determined by both SatDNA and kDNA qPCRs. This effort is a major step toward international validation of qPCR methods for the quantification of T. cruzi DNA in human blood samples, aiming to provide an accurate surrogate biomarker for diagnosis and treatment monitoring for patients with Chagas disease. PMID:26320872

A novel approach for quantitation of nonderivatized sialic acid in protein therapeutics using hydrophilic interaction chromatographic separation and nano quantity analyte detection.

PubMed

Chemmalil, Letha; Suravajjala, Sreekanth; See, Kate; Jordan, Eric; Furtado, Marsha; Sun, Chong; Hosselet, Stephen

2015-01-01

This paper describes a novel approach for the quantitation of nonderivatized sialic acid in glycoproteins, separated by hydrophilic interaction chromatography, and detection by Nano Quantity Analyte Detector (NQAD). The detection technique of NQAD is based on measuring change in the size of dry aerosol and converting the particle count rate into chromatographic output signal. NQAD detector is suitable for the detection of sialic acid, which lacks sufficiently active chromophore or fluorophore. The water condensation particle counting technology allows the analyte to be enlarged using water vapor to provide highest sensitivity. Derivatization-free analysis of glycoproteins using HPLC/NQAD method with PolyGLYCOPLEX™ amide column is well correlated with HPLC method with precolumn derivatization using 1, 2-diamino-4, 5-methylenedioxybenzene (DMB) as well as the Dionex-based high-pH anion-exchange chromatography (or ion chromatography) with pulsed amperometric detection (HPAEC-PAD). With the elimination of derivatization step, HPLC/NQAD method is more efficient than HPLC/DMB method. HPLC/NQAD method is more reproducible than HPAEC-PAD method as HPAEC-PAD method suffers high variability because of electrode fouling during analysis. Overall, HPLC/NQAD method offers broad linear dynamic range as well as excellent precision, accuracy, repeatability, reliability, and ease of use, with acceptable comparability to the commonly used HPAEC-PAD and HPLC/DMB methods. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Engaging Business Students in Quantitative Skills Development

ERIC Educational Resources Information Center

Cronin, Anthony; Carroll, Paula

2015-01-01

In this paper the complex problems of developing quantitative and analytical skills in undergraduate first year, first semester business students are addressed. An action research project, detailing how first year business students perceive the relevance of data analysis and inferential statistics in light of the economic downturn and the…

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

Analytical Microscopy and Imaging Science | Materials Science | NREL

Science.gov Websites

Microanalysis (EPMA) for quantitative compositional analysis. It relies on wavelength-dispersive spectroscopy to Science group in NREL's Materials Science Center. Mowafak Al-Jassim Group Manager Dr. Al-Jassim manages the Analytical Microscopy and Imaging Science group with the Materials Science Center. Email | 303-384

Quantitative evaluation of the matrix effect in bioanalytical methods based on LC-MS: A comparison of two approaches.

PubMed

Rudzki, Piotr J; Gniazdowska, Elżbieta; Buś-Kwaśnik, Katarzyna

2018-06-05

Liquid chromatography coupled to mass spectrometry (LC-MS) is a powerful tool for studying pharmacokinetics and toxicokinetics. Reliable bioanalysis requires the characterization of the matrix effect, i.e. influence of the endogenous or exogenous compounds on the analyte signal intensity. We have compared two methods for the quantitation of matrix effect. The CVs(%) of internal standard normalized matrix factors recommended by the European Medicines Agency were evaluated against internal standard normalized relative matrix effects derived from Matuszewski et al. (2003). Both methods use post-extraction spiked samples, but matrix factors require also neat solutions. We have tested both approaches using analytes of diverse chemical structures. The study did not reveal relevant differences in the results obtained with both calculation methods. After normalization with the internal standard, the CV(%) of the matrix factor was on average 0.5% higher than the corresponding relative matrix effect. The method adopted by the European Medicines Agency seems to be slightly more conservative in the analyzed datasets. Nine analytes of different structures enabled a general overview of the problem, still, further studies are encouraged to confirm our observations. Copyright © 2018 Elsevier B.V. All rights reserved.

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

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.

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...

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.

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

Health impact assessment – A survey on quantifying tools

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

Fehr, Rainer, E-mail: rainer.fehr@uni-bielefeld.de; Mekel, Odile C.L., E-mail: odile.mekel@lzg.nrw.de; Fintan Hurley, J., E-mail: fintan.hurley@iom-world.org

Integrating human health into prospective impact assessments is known to be challenging. This is true for both approaches: dedicated health impact assessments (HIA) as well as inclusion of health into more general impact assessments. Acknowledging the full range of participatory, qualitative, and quantitative approaches, this study focuses on the latter, especially on computational tools for quantitative health modelling. We conducted a survey among tool developers concerning the status quo of development and availability of such tools; experiences made with model usage in real-life situations; and priorities for further development. Responding toolmaker groups described 17 such tools, most of them beingmore » maintained and reported as ready for use and covering a wide range of topics, including risk & protective factors, exposures, policies, and health outcomes. In recent years, existing models have been improved and were applied in new ways, and completely new models emerged. There was high agreement among respondents on the need to further develop methods for assessment of inequalities and uncertainty. The contribution of quantitative modeling to health foresight would benefit from building joint strategies of further tool development, improving the visibility of quantitative tools and methods, and engaging continuously with actual and potential users. - Highlights: • A survey investigated computational tools for health impact quantification. • Formal evaluation of such tools has been rare. • Handling inequalities and uncertainties are priority areas for further development. • Health foresight would benefit from tool developers and users forming a community. • Joint development strategies across computational tools are needed.« less

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

Big Data Analytics in Healthcare

PubMed Central

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S. M. Reza; Beard, Daniel A.

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined. PMID:26229957

Big Data Analytics in Healthcare.

PubMed

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

Quantitative analyses of bifunctional molecules.

PubMed

Braun, Patrick D; Wandless, Thomas J

2004-05-11

Small molecules can be discovered or engineered to bind tightly to biologically relevant proteins, and these molecules have proven to be powerful tools for both basic research and therapeutic applications. In many cases, detailed biophysical analyses of the intermolecular binding events are essential for improving the activity of the small molecules. These interactions can often be characterized as straightforward bimolecular binding events, and a variety of experimental and analytical techniques have been developed and refined to facilitate these analyses. Several investigators have recently synthesized heterodimeric molecules that are designed to bind simultaneously with two different proteins to form ternary complexes. These heterodimeric molecules often display compelling biological activity; however, they are difficult to characterize. The bimolecular interaction between one protein and the heterodimeric ligand (primary dissociation constant) can be determined by a number of methods. However, the interaction between that protein-ligand complex and the second protein (secondary dissociation constant) is more difficult to measure due to the noncovalent nature of the original protein-ligand complex. Consequently, these heterodimeric compounds are often characterized in terms of their activity, which is an experimentally dependent metric. We have developed a general quantitative mathematical model that can be used to measure both the primary (protein + ligand) and secondary (protein-ligand + protein) dissociation constants for heterodimeric small molecules. These values are largely independent of the experimental technique used and furthermore provide a direct measure of the thermodynamic stability of the ternary complexes that are formed. Fluorescence polarization and this model were used to characterize the heterodimeric molecule, SLFpYEEI, which binds to both FKBP12 and the Fyn SH2 domain, demonstrating that the model is useful for both predictive as well as ex

A general analytical platform and strategy in search for illegal drugs.

PubMed

Johansson, Monika; Fransson, Dick; Rundlöf, Torgny; Huynh, Ngoc-Hang; Arvidsson, Torbjörn

2014-11-01

An effective screening procedure to identify and quantify active pharmaceutical substances in suspected illegal medicinal products is described. The analytical platform, consisting of accurate mass determination with liquid chromatography time-of-flight mass spectrometry (LC-QTOF-MS) in combination with nuclear magnetic resonance (NMR) spectroscopy provides an excellent analytical tool to screen for unknowns in medicinal products, food supplements and herbal formulations. This analytical approach has been successfully applied to analyze thousands of samples. The general screening method usually starts with a methanol extraction of tablets/capsules followed by liquid chromatographic separation on a Halo Phenyl-Hexyl column (2.7μm; 100mm×2.1mm) using an acetonitrile/0.1% formic acid gradient as eluent. The accurate mass of peaks of interest was recorded and a search made against an in-house database containing approximately 4200 substances, mostly pharmaceutical compounds. The search could be general or tailored against different classes of compounds. Hits were confirmed by analyzing a reference substance and/or by NMR. Quantification was normally performed with quantitative NMR (qNMR) spectroscopy. Applications for weight-loss substances like sibutramine and orlistat, sexual potency enhancement (PDE-5 inhibitors), and analgesic drugs are presented in this study. We have also identified prostaglandin analogues in eyelash growth serum, exemplified by isopropyl cloprostenate and bimatoprost. For creams and ointments, matrix solid-phase dispersion (MSPD) was found to give a clean extracts with high recovery prior to LC-MS analyses. The structural elucidation of cetilistat, a new weight-loss substance recently found in illegal medicines purchased over the Internet, is also presented. Copyright © 2014 Elsevier B.V. All rights reserved.

Analytical Eco-Scale for Assessing the Greenness of a Developed RP-HPLC Method Used for Simultaneous Analysis of Combined Antihypertensive Medications.

PubMed

Mohamed, Heba M; Lamie, Nesrine T

2016-09-01

In the past few decades the analytical community has been focused on eliminating or reducing the usage of hazardous chemicals and solvents, in different analytical methodologies, that have been ascertained to be extremely dangerous to human health and environment. In this context, environmentally friendly, green, or clean practices have been implemented in different research areas. This study presents a greener alternative of conventional RP-HPLC methods for the simultaneous determination and quantitative analysis of a pharmaceutical ternary mixture composed of telmisartan, hydrochlorothiazide, and amlodipine besylate, using an ecofriendly mobile phase and short run time with the least amount of waste production. This solvent-replacement approach was feasible without compromising method performance criteria, such as separation efficiency, peak symmetry, and chromatographic retention. The greenness profile of the proposed method was assessed and compared with reported conventional methods using the analytical Eco-Scale as an assessment tool. The proposed method was found to be greener in terms of usage of hazardous chemicals and solvents, energy consumption, and production of waste. The proposed method can be safely used for the routine analysis of the studied pharmaceutical ternary mixture with a minimal detrimental impact on human health and the environment.

hydropower biological evaluation tools

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

This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways

Quantitative PCR for Genetic Markers of Human Fecal Pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantificationapproach. We report the development of quantitative PCR assays for quantification of two recently described human-...

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.

Clinical Utility of Quantitative Imaging

PubMed Central

Rosenkrantz, Andrew B; Mendiratta-Lala, Mishal; Bartholmai, Brian J.; Ganeshan, Dhakshinamoorthy; Abramson, Richard G.; Burton, Kirsteen R.; Yu, John-Paul J.; Scalzetti, Ernest M.; Yankeelov, Thomas E.; Subramaniam, Rathan M.; Lenchik, Leon

2014-01-01

Quantitative imaging (QI) is increasingly applied in modern radiology practice, assisting in the clinical assessment of many patients and providing a source of biomarkers for a spectrum of diseases. QI is commonly used to inform patient diagnosis or prognosis, determine the choice of therapy, or monitor therapy response. Because most radiologists will likely implement some QI tools to meet the patient care needs of their referring clinicians, it is important for all radiologists to become familiar with the strengths and limitations of QI. The Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force has explored the clinical application of QI and summarizes its work in this review. We provide an overview of the clinical use of QI by discussing QI tools that are currently employed in clinical practice, clinical applications of these tools, approaches to reporting of QI, and challenges to implementing QI. It is hoped that these insights will help radiologists recognize the tangible benefits of QI to their patients, their referring clinicians, and their own radiology practice. PMID:25442800

A gold nanoparticle-based semi-quantitative and quantitative ultrasensitive paper sensor for the detection of twenty mycotoxins

NASA Astrophysics Data System (ADS)

Kong, Dezhao; Liu, Liqiang; Song, Shanshan; Suryoprabowo, Steven; Li, Aike; Kuang, Hua; Wang, Libing; Xu, Chuanlai

2016-02-01

A semi-quantitative and quantitative multi-immunochromatographic (ICA) strip detection assay was developed for the simultaneous detection of twenty types of mycotoxins from five classes, including zearalenones (ZEAs), deoxynivalenols (DONs), T-2 toxins (T-2s), aflatoxins (AFs), and fumonisins (FBs), in cereal food samples. Sensitive and specific monoclonal antibodies were selected for this assay. The semi-quantitative results were obtained within 20 min by the naked eye, with visual limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.1-0.5, 2.5-250, 0.5-1, 0.25-1 and 2.5-10 μg kg-1, and cut-off values of 0.25-1, 5-500, 1-10, 0.5-2.5 and 5-25 μg kg-1, respectively. The quantitative results were obtained using a hand-held strip scan reader, with the calculated limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.04-0.17, 0.06-49, 0.15-0.22, 0.056-0.49 and 0.53-1.05 μg kg-1, respectively. The analytical results of spiked samples were in accordance with the accurate content in the simultaneous detection analysis. This newly developed ICA strip assay is suitable for the on-site detection and rapid initial screening of mycotoxins in cereal samples, facilitating both semi-quantitative and quantitative determination.A semi-quantitative and quantitative multi-immunochromatographic (ICA) strip detection assay was developed for the simultaneous detection of twenty types of mycotoxins from five classes, including zearalenones (ZEAs), deoxynivalenols (DONs), T-2 toxins (T-2s), aflatoxins (AFs), and fumonisins (FBs), in cereal food samples. Sensitive and specific monoclonal antibodies were selected for this assay. The semi-quantitative results were obtained within 20 min by the naked eye, with visual limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.1-0.5, 2.5-250, 0.5-1, 0.25-1 and 2.5-10 μg kg-1, and cut-off values of 0.25-1, 5-500, 1-10, 0.5-2.5 and 5-25 μg kg-1, respectively. The quantitative results were obtained using a hand-held strip scan

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.

Improving the usefulness of a tool for appraising the quality of qualitative, quantitative and mixed methods studies, the Mixed Methods Appraisal Tool (MMAT).

PubMed

Hong, Quan Nha; Gonzalez-Reyes, Araceli; Pluye, Pierre

2018-06-01

Systematic reviews combining qualitative, quantitative, and/or mixed methods studies are increasingly popular because of their potential for addressing complex interventions and phenomena, specifically for assessing and improving clinical practice. A major challenge encountered with this type of review is the appraisal of the quality of individual studies given the heterogeneity of the study designs. The Mixed Methods Appraisal Tool (MMAT) was developed to help overcome this challenge. The aim of this study was to explore the usefulness of the MMAT by seeking the views and experiences of researchers who have used it. We conducted a qualitative descriptive study using semistructured interviews with MMAT users. A purposeful sample was drawn from the researchers who had previously contacted the developer of the MMAT, and those who have published a systematic review for which they had used the MMAT. All interviews were transcribed verbatim and analyzed by 2 coders using thematic analysis. Twenty participants from 8 countries were interviewed. Thirteen themes were identified and grouped into the 2 dimensions of usefulness, ie, utility and usability. The themes related to utility concerned the coverage, completeness, flexibility, and other utilities of the tool. Those regarding usability were related to the learnability, efficiency, satisfaction, and errors that could be made due to difficulties understanding or selecting the items to appraise. On the basis of the results of this study, we make several recommendations for improving the MMAT. This will contribute to greater usefulness of the MMAT. © 2018 John Wiley & Sons, Ltd.

Real-time imaging as an emerging process analytical technology tool for monitoring of fluid bed coating process.

PubMed

Naidu, Venkata Ramana; Deshpande, Rucha S; Syed, Moinuddin R; Wakte, Pravin S

2018-07-01

A direct imaging system (Eyecon TM ) was used as a Process Analytical Technology (PAT) tool to monitor fluid bed coating process. Eyecon TM generated real-time onscreen images, particle size and shape information of two identically manufactured laboratory-scale batches. Eyecon TM has accuracy of measuring the particle size increase of ±1 μm on particles in the size range of 50-3000 μm. Eyecon TM captured data every 2 s during the entire process. The moving average of D90 particle size values recorded by Eyecon TM were calculated for every 30 min to calculate the radial coating thickness of coated particles. After the completion of coating process, the radial coating thickness was found to be 11.3 and 9.11 μm, with a standard deviation of ±0.68 and 1.8 μm for Batch 1 and Batch 2, respectively. The coating thickness was also correlated with percent weight build-up by gel permeation chromatography (GPC) and dissolution. GPC indicated weight build-up of 10.6% and 9.27% for Batch 1 and Batch 2, respectively. In conclusion, weight build-up of 10% can also be correlated with 10 ± 2 μm increase in the coating thickness of pellets, indicating the potential applicability of real-time imaging as an endpoint determination tool for fluid bed coating process.

Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies.

PubMed

Percy, Andrew J; Yang, Juncong; Hardie, Darryl B; Chambers, Andrew G; Tamura-Wells, Jessica; Borchers, Christoph H

2015-06-15

Spurred on by the growing demand for panels of validated disease biomarkers, increasing efforts have focused on advancing qualitative and quantitative tools for more highly multiplexed and sensitive analyses of a multitude of analytes in various human biofluids. In quantitative proteomics, evolving strategies involve the use of the targeted multiple reaction monitoring (MRM) mode of mass spectrometry (MS) with stable isotope-labeled standards (SIS) used for internal normalization. Using that preferred approach with non-invasive urine samples, we have systematically advanced and rigorously assessed the methodology toward the precise quantitation of the largest, multiplexed panel of candidate protein biomarkers in human urine to date. The concentrations of the 136 proteins span >5 orders of magnitude (from 8.6 μg/mL to 25 pg/mL), with average CVs of 8.6% over process triplicate. Detailed here is our quantitative method, the analysis strategy, a feasibility application to prostate cancer samples, and a discussion of the utility of this method in translational studies. Copyright © 2015 Elsevier Inc. All rights reserved.

The use of selective adsorbents in capillary electrophoresis-mass spectrometry for analyte preconcentration and microreactions: a powerful three-dimensional tool for multiple chemical and biological applications.

PubMed

Guzman, N A; Stubbs, R J

2001-10-01

Much attention has recently been directed to the development and application of online sample preconcentration and microreactions in capillary electrophoresis using selective adsorbents based on chemical or biological specificity. The basic principle involves two interacting chemical or biological systems with high selectivity and affinity for each other. These molecular interactions in nature usually involve noncovalent and reversible chemical processes. Properly bound to a solid support, an "affinity ligand" can selectively adsorb a "target analyte" found in a simple or complex mixture at a wide range of concentrations. As a result, the isolated analyte is enriched and highly purified. When this affinity technique, allowing noncovalent chemical interactions and biochemical reactions to occur, is coupled on-line to high-resolution capillary electrophoresis and mass spectrometry, a powerful tool of chemical and biological information is created. This paper describes the concept of biological recognition and affinity interaction on-line with high-resolution separation, the fabrication of an "analyte concentrator-microreactor", optimization conditions of adsorption and desorption, the coupling to mass spectrometry, and various applications of clinical and pharmaceutical interest.

Experimental validation of the AVIVET trap, a tool to quantitatively monitor the dynamics of Dermanyssus gallinae populations in laying hens.

PubMed

Lammers, G A; Bronneberg, R G G; Vernooij, J C M; Stegeman, J A

2017-06-01

Dermanyssus gallinae (D.gallinae) infestation causes economic losses due to impaired health and production of hens and costs of parasite control across the world. Moreover, infestations are associated with reduced welfare of hens and may cause itching in humans. To effectively implement control methods it is crucially important to have high quality information about the D.gallinae populations in poultry houses in space and time. At present no validated tool is available to quantitatively monitor the dynamics of all four stages of D.gallinae (i.e., eggs, larvae, nymphs, and adults) in poultry houses.This article describes the experimental validation of the AVIVET trap, a device to quantitatively monitor dynamics of D.gallinae infestations. We used the device to study D.gallinae in fully equipped cages with two white specific pathogen free Leghorn laying hens experimentally exposed to three different infestation levels of D.gallinae (low to high).The AVIVET trap was successfully able to detect D.gallinae at high (5,000 D.gallinae), medium (2,500 D.gallinae), and low (50 D.gallinae) level of D.gallinae infestation. The linear equation Y = 10∧10∧(0.47 + 1.21X) with Y = log10 (Total number of D.gallinae nymphs and adults) in the cage and X = log10 (Total number of D.gallinae nymphs and adults) in the AVIVET trap explained 93.8% of the variation.The weight of D.gallinae in the AVIVET trap also appears to be a reliable parameter for quantifying D.gallinae infestation in a poultry house. The weight of D.gallinae in the AVIVET trap correlates 99.6% (P < 0.000) to the counted number of all stages of D.gallinae in the trap (i.e., eggs, larvae, nymphs, and adults) indicating that the trap is highly specific.From this experiment it can be concluded that the AVIVET trap is promising as quantitative tool for monitoring D.gallinae dynamics in a poultry house. © 2016 Poultry Science Association Inc.

Big Data Geo-Analytical Tool Development for Spatial Analysis Uncertainty Visualization and Quantification Needs

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J. R.; Baker, D. V.

2015-12-01

As big data computing capabilities are increasingly paired with spatial analytical tools and approaches, there is a need to ensure uncertainty associated with the datasets used in these analyses is adequately incorporated and portrayed in results. Often the products of spatial analyses, big data and otherwise, are developed using discontinuous, sparse, and often point-driven data to represent continuous phenomena. Results from these analyses are generally presented without clear explanations of the uncertainty associated with the interpolated values. The Variable Grid Method (VGM) offers users with a flexible approach designed for application to a variety of analyses where users there is a need to study, evaluate, and analyze spatial trends and patterns while maintaining connection to and communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analysis through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom 'Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation

Comparative study between univariate spectrophotometry and multivariate calibration as analytical tools for quantitation of Benazepril alone and in combination with Amlodipine.

PubMed

Farouk, M; Elaziz, Omar Abd; Tawakkol, Shereen M; Hemdan, A; Shehata, Mostafa A

2014-04-05

Four simple, accurate, reproducible, and selective methods have been developed and subsequently validated for the determination of Benazepril (BENZ) alone and in combination with Amlodipine (AML) in pharmaceutical dosage form. The first method is pH induced difference spectrophotometry, where BENZ can be measured in presence of AML as it showed maximum absorption at 237nm and 241nm in 0.1N HCl and 0.1N NaOH, respectively, while AML has no wavelength shift in both solvents. The second method is the new Extended Ratio Subtraction Method (EXRSM) coupled to Ratio Subtraction Method (RSM) for determination of both drugs in commercial dosage form. The third and fourth methods are multivariate calibration which include Principal Component Regression (PCR) and Partial Least Squares (PLSs). A detailed validation of the methods was performed following the ICH guidelines and the standard curves were found to be linear in the range of 2-30μg/mL for BENZ in difference and extended ratio subtraction spectrophotometric method, and 5-30 for AML in EXRSM method, with well accepted mean correlation coefficient for each analyte. The intra-day and inter-day precision and accuracy results were well within the acceptable limits. Copyright © 2013 Elsevier B.V. All rights reserved.

Absolute activity quantitation from projections using an analytical approach: comparison with iterative methods in Tc-99m and I-123 brain SPECT

NASA Astrophysics Data System (ADS)

Fakhri, G. El; Kijewski, M. F.; Moore, S. C.

2001-06-01

Estimates of SPECT activity within certain deep brain structures could be useful for clinical tasks such as early prediction of Alzheimer's disease with Tc-99m or Parkinson's disease with I-123; however, such estimates are biased by poor spatial resolution and inaccurate scatter and attenuation corrections. We compared an analytical approach (AA) of more accurate quantitation to a slower iterative approach (IA). Monte Carlo simulated projections of 12 normal and 12 pathologic Tc-99m perfusion studies, as well as 12, normal and 12 pathologic I-123 neurotransmission studies, were generated using a digital brain phantom and corrected for scatter by a multispectral fitting procedure. The AA included attenuation correction by a modified Metz-Fan algorithm and activity estimation by a technique that incorporated Metz filtering to compensate for variable collimator response (VCR), IA-modeled attenuation, and VCR in the projector/backprojector of an ordered subsets-expectation maximization (OSEM) algorithm. Bias and standard deviation over the 12 normal and 12 pathologic patients were calculated with respect to the reference values in the corpus callosum, caudate nucleus, and putamen. The IA and AA yielded similar quantitation results in both Tc-99m and I-123 studies in all brain structures considered in both normal and pathologic patients. The bias with respect to the reference activity distributions was less than 7% for Tc-99m studies, but greater than 30% for I-123 studies, due to partial volume effect in the striata. Our results were validated using I-123 physical acquisitions of an anthropomorphic brain phantom. The IA yielded quantitation accuracy comparable to that obtained with IA, while requiring much less processing time. However, in most conditions, IA yielded lower noise for the same bias than did AA.

Quantitative PCR for genetic markers of human fecal pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantification approach. We report the development of quantitative PCR assays for enumeration of two recently described hum...

Quantitative Clinical Diagnostic Analysis of Acetone in Human Blood by HPLC: A Metabolomic Search for Acetone as Indicator

PubMed Central

Akgul Kalkan, Esin; Sahiner, Mehtap; Ulker Cakir, Dilek; Alpaslan, Duygu; Yilmaz, Selehattin

2016-01-01

Using high-performance liquid chromatography (HPLC) and 2,4-dinitrophenylhydrazine (2,4-DNPH) as a derivatizing reagent, an analytical method was developed for the quantitative determination of acetone in human blood. The determination was carried out at 365 nm using an ultraviolet-visible (UV-Vis) diode array detector (DAD). For acetone as its 2,4-dinitrophenylhydrazone derivative, a good separation was achieved with a ThermoAcclaim C18 column (15 cm × 4.6 mm × 3 μm) at retention time (t R) 12.10 min and flowrate of 1 mL min−1 using a (methanol/acetonitrile) water elution gradient. The methodology is simple, rapid, sensitive, and of low cost, exhibits good reproducibility, and allows the analysis of acetone in biological fluids. A calibration curve was obtained for acetone using its standard solutions in acetonitrile. Quantitative analysis of acetone in human blood was successfully carried out using this calibration graph. The applied method was validated in parameters of linearity, limit of detection and quantification, accuracy, and precision. We also present acetone as a useful tool for the HPLC-based metabolomic investigation of endogenous metabolism and quantitative clinical diagnostic analysis. PMID:27298750

Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline

PubMed Central

Schilling, Birgit; Rardin, Matthew J.; MacLean, Brendan X.; Zawadzka, Anna M.; Frewen, Barbara E.; Cusack, Michael P.; Sorensen, Dylan J.; Bereman, Michael S.; Jing, Enxuan; Wu, Christine C.; Verdin, Eric; Kahn, C. Ronald; MacCoss, Michael J.; Gibson, Bradford W.

2012-01-01

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models. PMID:22454539

Measurement of very low amounts of arsenic in soils and waters: is ICP-MS the indispensable analytical tool?

NASA Astrophysics Data System (ADS)

López-García, Ignacio; Marín-Hernández, Juan Jose; Perez-Sirvent, Carmen; Hernandez-Cordoba, Manuel

2017-04-01

The toxicity of arsenic and its wide distribution in the nature needs nowadays not to be emphasized, and the convenience of reliable analytical tools for arsenic determination at very low levels is clear. Leaving aside atomic fluorescence spectrometers specifically designed for this purpose, the task is currently carried out by using inductively coupled plasma mass spectrometry (ICP-MS), a powerful but expensive technique that is not available in all laboratories. However, as the recent literature clearly shows, a similar or even better analytical performance for the determination of several elements can be achieved by replacing the ICP-MS instrument by an AAS spectrometer (which is commonly present in any laboratory and involves low acquisition and maintenance costs) provided that a simple microextraction step is used to preconcentrate the sample. This communication reports the optimization and results obtained with a new analytical procedure based on this idea and focused to the determination of very low concentrations of arsenic in waters and extracts from soils and sediments. The procedure is based on a micro-solid phase extraction process for the separation and preconcentration of arsenic that uses magnetic particles covered with silver nanoparticles functionalized with the sodium salt of 2-mercaptoethane-sulphonate (MESNa). This composite is obtained in an easy way in the laboratory. After the sample is treated with a low amount (only a few milligrams) of the magnetic material, the solid phase is separated by means of a magnetic field, and then introduced into an electrothermal atomizer (ETAAS) for arsenic determination. The preconcentration factor is close to 200 with a detection limit below 0.1 µg L-1 arsenic. Speciation of As(III) and As(V) can be achieved by means of two extractions carried out at different acidity. The results for total arsenic are verified using certified reference materials. The authors are grateful to the Comunidad Autonóma de la

Quantitative evaluation of intensive remedial action using long-term monitoring and tracer data at a DNAPL contaminated site, Wonju, Korea

NASA Astrophysics Data System (ADS)

Lee, S. S.; Kim, H. J.; Kim, M. O.; Lee, K.; Lee, K. K.

2016-12-01

A study finding evidence of remediation represented on monitoring data before and after in site intensive remedial action was performed with various quantitative evaluation methods such as mass discharge analysis, tracer data, statistical trend analysis, and analytical solutions at DNAPL contaminated site, Wonju, Korea. Remediation technologies such as soil vapor extraction, soil flushing, biostimulation, and pump-and-treat have been applied to eliminate the contaminant sources of trichloroethylene (TCE) and to prevent the migration of TCE plume from remediation target zones. Prior to the remediation action, the concentration and mass discharges of TCE at all transects were affected by seasonal recharge variation and residual DNAPLs sources. After the remediation, the effect of remediation took place clearly at the main source zone and industrial complex. By tracing a time-series of plume evolution, a greater variation in the TCE concentrations was detected at the plumes near the source zones compared to the relatively stable plumes in the downstream. The removal amount of the residual source mass during the intensive remedial action was estimated to evaluate the efficiency of the intensive remedial action using analytical solution. From results of quantitative evaluation using analytical solution, it is assessed that the intensive remedial action had effectively performed with removal efficiency of 70% for the residual source mass during the remediation period. Analytical solution which can consider and quantify the impacts of partial mass reduction have been proven to be useful tools for quantifying unknown contaminant source mass and verifying dissolved concentration at the DNAPL contaminated site and evaluating the efficiency of remediation using long-term monitoring data. Acknowledgement : This subject was supported by the Korea Ministry of Environment under "GAIA project (173-092-009) and (201400540010)", R&D Project on Enviornmental Management of Geologic CO

Assessment of catchments' flooding potential: a physically-based analytical tool

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Schirmer, M.

2016-12-01

The assessment of the flooding potential of river catchments is critical in many research and applied fields, ranging from river science and geomorphology to urban planning and the insurance industry. Predicting magnitude and frequency of floods is key to prevent and mitigate the negative effects of high flows, and has therefore long been the focus of hydrologic research. Here, the recurrence intervals of seasonal flow maxima are estimated through a novel physically-based analytic approach, which links the extremal distribution of streamflows to the stochastic dynamics of daily discharge. An analytical expression of the seasonal flood-frequency curve is provided, whose parameters embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which expresses catchment saturation prior to rainfall events, needs to be calibrated on the observed maxima. The method has been tested in a set of catchments featuring heterogeneous daily flow regimes. The model is able to reproduce characteristic shapes of flood-frequency curves emerging in erratic and persistent flow regimes and provides good estimates of seasonal flow maxima in different climatic regions. Performances are steady when the magnitude of events with return times longer than the available sample size is estimated. This makes the approach especially valuable for regions affected by data scarcity.

Directivity analysis of meander-line-coil EMATs with a wholly analytical method.

PubMed

Xie, Yuedong; Liu, Zenghua; Yin, Liyuan; Wu, Jiande; Deng, Peng; Yin, Wuliang

2017-01-01

This paper presents the simulation and experimental study of the radiation pattern of a meander-line-coil EMAT. A wholly analytical method, which involves the coupling of two models: an analytical EM model and an analytical UT model, has been developed to build EMAT models and analyse the Rayleigh waves' beam directivity. For a specific sensor configuration, Lorentz forces are calculated using the EM analytical method, which is adapted from the classic Deeds and Dodd solution. The calculated Lorentz force density are imported to an analytical ultrasonic model as driven point sources, which produce the Rayleigh waves within a layered medium. The effect of the length of the meander-line-coil on the Rayleigh waves' beam directivity is analysed quantitatively and verified experimentally. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Quantitative prediction of solute strengthening in aluminium alloys.

PubMed

Leyson, Gerard Paul M; Curtin, William A; Hector, Louis G; Woodward, Christopher F

2010-09-01

Despite significant advances in computational materials science, a quantitative, parameter-free prediction of the mechanical properties of alloys has been difficult to achieve from first principles. Here, we present a new analytic theory that, with input from first-principles calculations, is able to predict the strengthening of aluminium by substitutional solute atoms. Solute-dislocation interaction energies in and around the dislocation core are first calculated using density functional theory and a flexible-boundary-condition method. An analytic model for the strength, or stress to move a dislocation, owing to the random field of solutes, is then presented. The theory, which has no adjustable parameters and is extendable to other metallic alloys, predicts both the energy barriers to dislocation motion and the zero-temperature flow stress, allowing for predictions of finite-temperature flow stresses. Quantitative comparisons with experimental flow stresses at temperature T=78 K are made for Al-X alloys (X=Mg, Si, Cu, Cr) and good agreement is obtained.

Big Data Analytics in Chemical Engineering.

PubMed

Chiang, Leo; Lu, Bo; Castillo, Ivan

2017-06-07

Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.

The challenge of big data in public health: an opportunity for visual analytics.

PubMed

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data's volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

The Challenge of Big Data in Public Health: An Opportunity for Visual Analytics

PubMed Central

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data’s volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research. PMID:24678376

Raman-in-SEM, a multimodal and multiscale analytical tool: performance for materials and expertise.

PubMed

Wille, Guillaume; Bourrat, Xavier; Maubec, Nicolas; Lahfid, Abdeltif

2014-12-01

The availability of Raman spectroscopy in a powerful analytical scanning electron microscope (SEM) allows morphological, elemental, chemical, physical and electronic analysis without moving the sample between instruments. This paper documents the metrological performance of the SEMSCA commercial Raman interface operated in a low vacuum SEM. It provides multiscale and multimodal analyses as Raman/EDS, Raman/cathodoluminescence or Raman/STEM (STEM: scanning transmission electron microscopy) as well as Raman spectroscopy on nanomaterials. Since Raman spectroscopy in a SEM can be influenced by several SEM-related phenomena, this paper firstly presents a comparison of this new tool with a conventional micro-Raman spectrometer. Then, some possible artefacts are documented, which are due to the impact of electron beam-induced contamination or cathodoluminescence contribution to the Raman spectra, especially with geological samples. These effects are easily overcome by changing or adapting the Raman spectrometer and the SEM settings and methodology. The deletion of the adverse effect of cathodoluminescence is solved by using a SEM beam shutter during Raman acquisition. In contrast, this interface provides the ability to record the cathodoluminescence (CL) spectrum of a phase. In a second part, this study highlights the interest and efficiency of the coupling in characterizing micrometric phases at the same point. This multimodal approach is illustrated with various issues encountered in geosciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Quantitative Phase Determination by Using a Michelson Interferometer

ERIC Educational Resources Information Center

Pomarico, Juan A.; Molina, Pablo F.; D'Angelo, Cristian

2007-01-01

The Michelson interferometer is one of the best established tools for quantitative interferometric measurements. It has been, and is still successfully used, not only for scientific purposes, but it is also introduced in undergraduate courses for qualitative demonstrations as well as for quantitative determination of several properties such as…

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

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

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…

Targeted methods for quantitative analysis of protein glycosylation

PubMed Central

Goldman, Radoslav; Sanda, Miloslav

2018-01-01

Quantification of proteins by LC-MS/MS-MRM has become a standard method with broad projected clinical applicability. MRM quantification of protein modifications is, however, far less utilized, especially in the case of glycoproteins. This review summarizes current methods for quantitative analysis of protein glycosylation with a focus on MRM methods. We describe advantages of this quantitative approach, analytical parameters that need to be optimized to achieve reliable measurements, and point out the limitations. Differences between major classes of N- and O-glycopeptides are described and class-specific glycopeptide assays are demonstrated. PMID:25522218

Correlated Raman micro-spectroscopy and scanning electron microscopy analyses of flame retardants in environmental samples: a micro-analytical tool for probing chemical composition, origin and spatial distribution.

PubMed

Ghosal, Sutapa; Wagner, Jeff

2013-07-07

We present correlated application of two micro-analytical techniques: scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) and Raman micro-spectroscopy (RMS) for the non-invasive characterization and molecular identification of flame retardants (FRs) in environmental dusts and consumer products. The SEM/EDS-RMS technique offers correlated, morphological, molecular, spatial distribution and semi-quantitative elemental concentration information at the individual particle level with micrometer spatial resolution and minimal sample preparation. The presented methodology uses SEM/EDS analyses for rapid detection of particles containing FR specific elements as potential indicators of FR presence in a sample followed by correlated RMS analyses of the same particles for characterization of the FR sub-regions and surrounding matrices. The spatially resolved characterization enabled by this approach provides insights into the distributional heterogeneity as well as potential transfer and exposure mechanisms for FRs in the environment that is typically not available through traditional FR analysis. We have used this methodology to reveal a heterogeneous distribution of highly concentrated deca-BDE particles in environmental dust, sometimes in association with identifiable consumer materials. The observed coexistence of deca-BDE with consumer material in dust is strongly indicative of its release into the environment via weathering/abrasion of consumer products. Ingestion of such enriched FR particles in dust represents a potential for instantaneous exposure to high FR concentrations. Therefore, correlated SEM/RMS analysis offers a novel investigative tool for addressing an area of important environmental concern.

Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages.

PubMed

Zhu, R; Zacharias, L; Wooding, K M; Peng, W; Mechref, Y

2017-01-01

Protein glycosylation is one of the most important posttranslational modifications. Numerous biological functions are related to protein glycosylation. However, analytical challenges remain in the glycoprotein analysis. To overcome the challenges associated with glycoprotein analysis, many analytical techniques were developed in recent years. Enrichment methods were used to improve the sensitivity of detection, while HPLC and mass spectrometry methods were developed to facilitate the separation of glycopeptides/proteins and enhance detection, respectively. Fragmentation techniques applied in modern mass spectrometers allow the structural interpretation of glycopeptides/proteins, while automated software tools started replacing manual processing to improve the reliability and throughput of the analysis. In this chapter, the current methodologies of glycoprotein analysis were discussed. Multiple analytical techniques are compared, and advantages and disadvantages of each technique are highlighted. © 2017 Elsevier Inc. All rights reserved.

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

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Temperature-controlled micro-TLC: a versatile green chemistry and fast analytical tool for separation and preliminary screening of steroids fraction from biological and environmental samples.

PubMed

Zarzycki, Paweł K; Slączka, Magdalena M; Zarzycka, Magdalena B; Bartoszuk, Małgorzata A; Włodarczyk, Elżbieta; Baran, Michał J

2011-11-01

This paper is a continuation of our previous research focusing on development of micro-TLC methodology under temperature-controlled conditions. The main goal of present paper is to demonstrate separation and detection capability of micro-TLC technique involving simple analytical protocols without multi-steps sample pre-purification. One of the advantages of planar chromatography over its column counterpart is that each TLC run can be performed using non-previously used stationary phase. Therefore, it is possible to fractionate or separate complex samples characterized by heavy biological matrix loading. In present studies components of interest, mainly steroids, were isolated from biological samples like fish bile using single pre-treatment steps involving direct organic liquid extraction and/or deproteinization by freeze-drying method. Low-molecular mass compounds with polarity ranging from estetrol to progesterone derived from the environmental samples (lake water, untreated and treated sewage waters) were concentrated using optimized solid-phase extraction (SPE). Specific bands patterns for samples derived from surface water of the Middle Pomerania in northern part of Poland can be easily observed on obtained micro-TLC chromatograms. This approach can be useful as simple and non-expensive complementary method for fast control and screening of treated sewage water discharged by the municipal wastewater treatment plants. Moreover, our experimental results show the potential of micro-TLC as an efficient tool for retention measurements of a wide range of steroids under reversed-phase (RP) chromatographic conditions. These data can be used for further optimalization of SPE or HPLC systems working under RP conditions. Furthermore, we also demonstrated that micro-TLC based analytical approach can be applied as an effective method for the internal standard (IS) substance search. Generally, described methodology can be applied for fast fractionation or screening of the

Quantitative Ultrasound-Assisted Extraction for Trace-Metal Determination: An Experiment for Analytical Chemistry

ERIC Educational Resources Information Center

Lavilla, Isela; Costas, Marta; Pena-Pereira, Francisco; Gil, Sandra; Bendicho, Carlos

2011-01-01

Ultrasound-assisted extraction (UAE) is introduced to upper-level analytical chemistry students as a simple strategy focused on sample preparation for trace-metal determination in biological tissues. Nickel extraction in seafood samples and quantification by electrothermal atomic absorption spectrometry (ETAAS) are carried out by a team of four…

Simultaneous quantitative analysis of main components in linderae reflexae radix with one single marker.

PubMed

Wang, Li-Li; Zhang, Yun-Bin; Sun, Xiao-Ya; Chen, Sui-Qing

2016-05-08

Establish a quantitative analysis of multi-components by the single marker (QAMS) method for quality evaluation and validate its feasibilities by the simultaneous quantitative assay of four main components in Linderae Reflexae Radix. Four main components of pinostrobin, pinosylvin, pinocembrin, and 3,5-dihydroxy-2-(1- p -mentheneyl)- trans -stilbene were selected as analytes to evaluate the quality by RP-HPLC coupled with a UV-detector. The method was evaluated by a comparison of the quantitative results between the external standard method and QAMS with a different HPLC system. The results showed that no significant differences were found in the quantitative results of the four contents of Linderae Reflexae Radix determined by the external standard method and QAMS (RSD <3%). The contents of four analytes (pinosylvin, pinocembrin, pinostrobin, and Reflexanbene I) in Linderae Reflexae Radix were determined by the single marker of pinosylvin. This fingerprint was the spectra determined by Shimadzu LC-20AT and Waters e2695 HPLC that were equipped with three different columns.

Comparing listeriosis risks in at-risk populations using a user-friendly quantitative microbial risk assessment tool and epidemiological data.

PubMed

Falk, L E; Fader, K A; Cui, D S; Totton, S C; Fazil, A M; Lammerding, A M; Smith, B A

2016-10-01

Although infection by the pathogenic bacterium Listeria monocytogenes is relatively rare, consequences can be severe, with a high case-fatality rate in vulnerable populations. A quantitative, probabilistic risk assessment tool was developed to compare estimates of the number of invasive listeriosis cases in vulnerable Canadian subpopulations given consumption of contaminated ready-to-eat delicatessen meats and hot dogs, under various user-defined scenarios. The model incorporates variability and uncertainty through Monte Carlo simulation. Processes considered within the model include cross-contamination, growth, risk factor prevalence, subpopulation susceptibilities, and thermal inactivation. Hypothetical contamination events were simulated. Results demonstrated varying risk depending on the consumer risk factors and implicated product (turkey delicatessen meat without growth inhibitors ranked highest for this scenario). The majority (80%) of listeriosis cases were predicted in at-risk subpopulations comprising only 20% of the total Canadian population, with the greatest number of predicted cases in the subpopulation with dialysis and/or liver disease. This tool can be used to simulate conditions and outcomes under different scenarios, such as a contamination event and/or outbreak, to inform public health interventions.

Ultrafast Screening and Quantitation of Pesticides in Food and Environmental Matrices by Solid-Phase Microextraction-Transmission Mode (SPME-TM) and Direct Analysis in Real Time (DART).

PubMed

Gómez-Ríos, Germán Augusto; Gionfriddo, Emanuela; Poole, Justen; Pawliszyn, Janusz

2017-07-05

The direct interface of microextraction technologies to mass spectrometry (MS) has unquestionably revolutionized the speed and efficacy at which complex matrices are analyzed. Solid Phase Micro Extraction-Transmission Mode (SPME-TM) is a technology conceived as an effective synergy between sample preparation and ambient ionization. Succinctly, the device consists of a mesh coated with polymeric particles that extracts analytes of interest present in a given sample matrix. This coated mesh acts as a transmission-mode substrate for Direct Analysis in Real Time (DART), allowing for rapid and efficient thermal desorption/ionization of analytes previously concentrated on the coating, and dramatically lowering the limits of detection attained by sole DART analysis. In this study, we present SPME-TM as a novel tool for the ultrafast enrichment of pesticides present in food and environmental matrices and their quantitative determination by MS via DART ionization. Limits of quantitation in the subnanogram per milliliter range can be attained, while total analysis time does not exceed 2 min per sample. In addition to target information obtained via tandem MS, retrospective studies of the same sample via high-resolution mass spectrometry (HRMS) were accomplished by thermally desorbing a different segment of the microextraction device.

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

Nuclear medicine and quantitative imaging research (instrumentation and quantitative methods of evaluation)

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

Beck, R.N.; Cooper, M.D.

1990-09-01

This report summarizes goals and accomplishments of the research program supported under DOE Grant No. FG02-86ER60418 entitled Instrumentation and Quantitative Methods of Evaluation, with R. Beck, P. I. and M. Cooper, Co-P.I. during the period January 15, 1990 through September 1, 1990. This program addresses the problems involving the basic science and technology underlying the physical and conceptual tools of radioactive tracer methodology as they relate to the measurement of structural and functional parameters of physiologic importance in health and disease. The principal tool is quantitative radionuclide imaging. The overall objective of this program is to further the development andmore » transfer of radiotracer methodology from basic theory to routine clinical practice in order that individual patients and society as a whole will receive the maximum net benefit from the new knowledge gained. The focus of the research is on the development of new instruments and radiopharmaceuticals, and the evaluation of these through the phase of clinical feasibility. 7 figs.« less

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

Fast analytical scatter estimation using graphics processing units.

PubMed

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

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.

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

PubMed Central

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-01-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of TOF scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (Direct Image Reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias vs. variance performance to iterative TOF reconstruction with a matched resolution model. PMID:27032968

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

NASA Astrophysics Data System (ADS)

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-05-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of time-of-flight (TOF) scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (DIRECT: direct image reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias versus variance performance to iterative TOF reconstruction with a matched resolution model.

Analytical capabilities and services of Lawrence Livermore Laboratory's General Chemistry Division. [Methods available at Lawrence Livermore

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

Gutmacher, R.; Crawford, R.

This comprehensive guide to the analytical capabilities of Lawrence Livermore Laboratory's General Chemistry Division describes each analytical method in terms of its principle, field of application, and qualitative and quantitative uses. Also described are the state and quantity of sample required for analysis, processing time, available instrumentation, and responsible personnel.

Analytical Chemical Sensing in the Submillimeter/terahertz Spectral Range

NASA Astrophysics Data System (ADS)

Moran, Benjamin L.; Fosnight, Alyssa M.; Medvedev, Ivan R.; Neese, Christopher F.

2012-06-01

Highly sensitive and selective Terahertz sensor utilized to quantitatively analyze a complex mixture of Volatile Organic Compounds is reported. To best demonstrate analytical capabilities of THz chemical sensors we chose to perform analytical quantitative analysis of a certified gas mixture using a novel prototype chemical sensor that couples a commercial preconcentration system (Entech 7100A) to a high resolution THz spectrometer. We selected Method TO-14A certified mixture of 39 volatile organic compounds (VOCs) diluted to 1 part per million (ppm) in nitrogen. 26 of the 39 chemicals were identified by us as suitable for THz spectroscopic detection. Entech 7100A system is designed and marketed as an inlet system for Gas Chromatography-Mass Spectrometry (GC-MS) instruments with a specific focus on TO-14 and TO-15 EPA sampling methods. Its preconcentration efficiency is high for the 39 chemicals in the mixture used for this study and our preliminary results confirm this. Here we present the results of this study which serves as basis for our ongoing research in environmental sensing and analysis of exhaled human breath.

Learning Analytics as Assemblage: Criticality and Contingency in Online Education

ERIC Educational Resources Information Center

Scott, John; Nichols, T. Philip

2017-01-01

Recently, the possibilities for leveraging "big data" in research and pedagogy have given rise to the growing field of "learning analytics" in online education. While much of this work has focused on quantitative metrics, some have called for critical perspectives that interrogate such data as an interplay between technical…

How Dispositional Learning Analytics Helps Understanding the Worked-Example Principle

ERIC Educational Resources Information Center

Tempelaar, Dirk

2017-01-01

This empirical study aims to demonstrate how Dispositional Learning Analytics can contribute in the investigation of the effectiveness of didactical scenarios in authentic settings, where previous research has mostly been laboratory based. Using a showcase based on learning processes of 1080 students in a blended introductory quantitative course,…

Tool for Ranking Research Options

NASA Technical Reports Server (NTRS)

Ortiz, James N.; Scott, Kelly; Smith, Harold

2005-01-01

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

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.

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.

Ratio of sequential chromatograms for quantitative analysis and peak deconvolution: Application to standard addition method and process monitoring

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

Synovec, R.E.; Johnson, E.L.; Bahowick, T.J.

1990-08-01

This paper describes a new technique for data analysis in chromatography, based on taking the point-by-point ratio of sequential chromatograms that have been base line corrected. This ratio chromatogram provides a robust means for the identification and the quantitation of analytes. In addition, the appearance of an interferent is made highly visible, even when it coelutes with desired analytes. For quantitative analysis, the region of the ratio chromatogram corresponding to the pure elution of an analyte is identified and is used to calculate a ratio value equal to the ratio of concentrations of the analyte in sequential injections. For themore » ratio value calculation, a variance-weighted average is used, which compensates for the varying signal-to-noise ratio. This ratio value, or equivalently the percent change in concentration, is the basis of a chromatographic standard addition method and an algorithm to monitor analyte concentration in a process stream. In the case of overlapped peaks, a spiking procedure is used to calculate both the original concentration of an analyte and its signal contribution to the original chromatogram. Thus, quantitation and curve resolution may be performed simultaneously, without peak modeling or curve fitting. These concepts are demonstrated by using data from ion chromatography, but the technique should be applicable to all chromatographic techniques.« less

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.

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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.

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.

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.

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-05-01

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO 2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Practical applications of surface analytic tools in tribology