Conventional approaches to water quality characterization can provide data on individual chemical components of each water sample. This analyte-by-analyte approach currently serves many useful research and compliance monitoring needs. However these approaches, which require a ...
Teaching Analytical Chemistry to Pharmacy Students: A Combined, Iterative Approach
ERIC Educational Resources Information Center
Masania, Jinit; Grootveld, Martin; Wilson, Philippe B.
2018-01-01
Analytical chemistry has often been a difficult subject to teach in a classroom or lecture-based context. Numerous strategies for overcoming the inherently practical-based difficulties have been suggested, each with differing pedagogical theories. Here, we present a combined approach to tackling the problem of teaching analytical chemistry, with…
NASA Technical Reports Server (NTRS)
Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav
2010-01-01
Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.
Lucklum, Ralf; Zubtsov, Mikhail; Schmidt, Marc-Peter; Mukhin, Nikolay V.; Hirsch, Soeren
2017-01-01
The current work demonstrates a novel surface acoustic wave (SAW) based phononic crystal sensor approach that allows the integration of a velocimetry-based sensor concept into single chip integrated solutions, such as Lab-on-a-Chip devices. The introduced sensor platform merges advantages of ultrasonic velocimetry analytic systems and a microacoustic sensor approach. It is based on the analysis of structural resonances in a periodic composite arrangement of microfluidic channels confined within a liquid analyte. Completed theoretical and experimental investigations show the ability to utilize periodic structure localized modes for the detection of volumetric properties of liquids and prove the efficacy of the proposed sensor concept. PMID:28946609
Oseev, Aleksandr; Lucklum, Ralf; Zubtsov, Mikhail; Schmidt, Marc-Peter; Mukhin, Nikolay V; Hirsch, Soeren
2017-09-23
The current work demonstrates a novel surface acoustic wave (SAW) based phononic crystal sensor approach that allows the integration of a velocimetry-based sensor concept into single chip integrated solutions, such as Lab-on-a-Chip devices. The introduced sensor platform merges advantages of ultrasonic velocimetry analytic systems and a microacoustic sensor approach. It is based on the analysis of structural resonances in a periodic composite arrangement of microfluidic channels confined within a liquid analyte. Completed theoretical and experimental investigations show the ability to utilize periodic structure localized modes for the detection of volumetric properties of liquids and prove the efficacy of the proposed sensor concept.
Fang, Jun; Park, Se-Chul; Schlag, Leslie; Stauden, Thomas; Pezoldt, Jörg; Jacobs, Heiko O
2014-12-03
In the field of sensors that target the detection of airborne analytes, Corona/lens-based-collection provides a new path to achieve a high sensitivity. An active-matrix-based analyte collection approach referred to as "airborne analyte memory chip/recorder" is demonstrated, which takes and stores airborne analytes in a matrix to provide an exposure history for off-site analysis. © 2014 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
ERIC Educational Resources Information Center
Yen, Cheng-Huang; Chen, I-Chuan; Lai, Su-Chun; Chuang, Yea-Ru
2015-01-01
Traces of learning behaviors generally provide insights into learners and the learning processes that they employ. In this article, a learning-analytics-based approach is proposed for managing cognitive load by adjusting the instructional strategies used in online courses. The technology-based learning environment examined in this study involved a…
NASA Astrophysics Data System (ADS)
Toh, Chee-Seng
2007-04-01
A research-focused approach is described for a nonlaboratory-based graduate-level module on analytical chemistry. The approach utilizes commonly practiced activities carried out in active research laboratories, in particular, activities involving logging of ideas and thoughts, journal clubs, proposal writing, classroom participation and discussions, and laboratory tours. This approach was adapted without compromising the course content and results suggest possible adaptation and implementation in other graduate-level courses.
Value of Flexibility - Phase 1
2010-09-25
weaknesses of each approach. During this period, we also explored the development of an analytical framework based on sound mathematical constructs... mathematical constructs. A review of the current state-of-the-art showed that there is little unifying theory or guidance on best approaches to...research activities is in developing a coherent value based definition of flexibility that is based on an analytical framework that is mathematically
NASA Astrophysics Data System (ADS)
Krasichkov, Alexander S.; Grigoriev, Eugene B.; Bogachev, Mikhail I.; Nifontov, Eugene M.
2015-10-01
We suggest an analytical approach to the adaptive thresholding in a shape anomaly detection problem. We find an analytical expression for the distribution of the cosine similarity score between a reference shape and an observational shape hindered by strong measurement noise that depends solely on the noise level and is independent of the particular shape analyzed. The analytical treatment is also confirmed by computer simulations and shows nearly perfect agreement. Using this analytical solution, we suggest an improved shape anomaly detection approach based on adaptive thresholding. We validate the noise robustness of our approach using typical shapes of normal and pathological electrocardiogram cycles hindered by additive white noise. We show explicitly that under high noise levels our approach considerably outperforms the conventional tactic that does not take into account variations in the noise level.
Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania
2015-04-15
In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.
An Analysis of Machine- and Human-Analytics in Classification.
Tam, Gary K L; Kothari, Vivek; Chen, Min
2017-01-01
In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.
Jinghao Li; John F. Hunt; Shaoqin Gong; Zhiyong Cai
2016-01-01
This paper presents a simplified analytical model and balanced design approach for modeling lightweight wood-based structural panels in bending. Because many design parameters are required to input for the model of finite element analysis (FEA) during the preliminary design process and optimization, the equivalent method was developed to analyze the mechanical...
Bridging analytical approaches for low-carbon transitions
NASA Astrophysics Data System (ADS)
Geels, Frank W.; Berkhout, Frans; van Vuuren, Detlef P.
2016-06-01
Low-carbon transitions are long-term multi-faceted processes. Although integrated assessment models have many strengths for analysing such transitions, their mathematical representation requires a simplification of the causes, dynamics and scope of such societal transformations. We suggest that integrated assessment model-based analysis should be complemented with insights from socio-technical transition analysis and practice-based action research. We discuss the underlying assumptions, strengths and weaknesses of these three analytical approaches. We argue that full integration of these approaches is not feasible, because of foundational differences in philosophies of science and ontological assumptions. Instead, we suggest that bridging, based on sequential and interactive articulation of different approaches, may generate a more comprehensive and useful chain of assessments to support policy formation and action. We also show how these approaches address knowledge needs of different policymakers (international, national and local), relate to different dimensions of policy processes and speak to different policy-relevant criteria such as cost-effectiveness, socio-political feasibility, social acceptance and legitimacy, and flexibility. A more differentiated set of analytical approaches thus enables a more differentiated approach to climate policy making.
Finding accurate frontiers: A knowledge-intensive approach to relational learning
NASA Technical Reports Server (NTRS)
Pazzani, Michael; Brunk, Clifford
1994-01-01
An approach to analytic learning is described that searches for accurate entailments of a Horn Clause domain theory. A hill-climbing search, guided by an information based evaluation function, is performed by applying a set of operators that derive frontiers from domain theories. The analytic learning system is one component of a multi-strategy relational learning system. We compare the accuracy of concepts learned with this analytic strategy to concepts learned with an analytic strategy that operationalizes the domain theory.
ERIC Educational Resources Information Center
Toh, Chee-Seng
2007-01-01
A project is described which incorporates nonlaboratory research skills in a graduate level course on analytical chemistry. This project will help students to grasp the basic principles and concepts of modern analytical techniques and also help them develop relevant research skills in analytical chemistry.
NASA Astrophysics Data System (ADS)
Boonprasert, Lapisarin; Tupsai, Jiraporn; Yuenyong, Chokchai
2018-01-01
This study reported Grade 8 students' analytical thinking and attitude toward science in teaching and learning about soil and its' pollution through science technology and society (STS) approach. The participants were 36 Grade 8 students in Naklang, Nongbualumphu, Thailand. The teaching and learning about soil and its' pollution through STS approach had carried out for 6 weeks. The soil and its' pollution unit through STS approach was developed based on framework of Yuenyong (2006) that consisted of five stages including (1) identification of social issues, (2) identification of potential solutions, (3) need for knowledge, (4) decision-making, and (5) socialization stage. Students' analytical thinking and attitude toward science was collected during their learning by participant observation, analytical thinking test, students' tasks, and journal writing. The findings revealed that students could gain their capability of analytical thinking. They could give ideas or behave the characteristics of analytical thinking such as thinking for classifying, compare and contrast, reasoning, interpreting, collecting data and decision making. Students' journal writing reflected that the STS class of soil and its' pollution motivated students. The paper will discuss implications of these for science teaching and learning through STS in Thailand.
Analytical and simulator study of advanced transport
NASA Technical Reports Server (NTRS)
Levison, W. H.; Rickard, W. W.
1982-01-01
An analytic methodology, based on the optimal-control pilot model, was demonstrated for assessing longitidunal-axis handling qualities of transport aircraft in final approach. Calibration of the methodology is largely in terms of closed-loop performance requirements, rather than specific vehicle response characteristics, and is based on a combination of published criteria, pilot preferences, physical limitations, and engineering judgment. Six longitudinal-axis approach configurations were studied covering a range of handling qualities problems, including the presence of flexible aircraft modes. The analytical procedure was used to obtain predictions of Cooper-Harper ratings, a solar quadratic performance index, and rms excursions of important system variables.
MS-based analytical methodologies to characterize genetically modified crops.
García-Cañas, Virginia; Simó, Carolina; León, Carlos; Ibáñez, Elena; Cifuentes, Alejandro
2011-01-01
The development of genetically modified crops has had a great impact on the agriculture and food industries. However, the development of any genetically modified organism (GMO) requires the application of analytical procedures to confirm the equivalence of the GMO compared to its isogenic non-transgenic counterpart. Moreover, the use of GMOs in foods and agriculture faces numerous criticisms from consumers and ecological organizations that have led some countries to regulate their production, growth, and commercialization. These regulations have brought about the need of new and more powerful analytical methods to face the complexity of this topic. In this regard, MS-based technologies are increasingly used for GMOs analysis to provide very useful information on GMO composition (e.g., metabolites, proteins). This review focuses on the MS-based analytical methodologies used to characterize genetically modified crops (also called transgenic crops). First, an overview on genetically modified crops development is provided, together with the main difficulties of their analysis. Next, the different MS-based analytical approaches applied to characterize GM crops are critically discussed, and include "-omics" approaches and target-based approaches. These methodologies allow the study of intended and unintended effects that result from the genetic transformation. This information is considered to be essential to corroborate (or not) the equivalence of the GM crop with its isogenic non-transgenic counterpart. Copyright © 2010 Wiley Periodicals, Inc.
Observability during planetary approach navigation
NASA Technical Reports Server (NTRS)
Bishop, Robert H.; Burkhart, P. Daniel; Thurman, Sam W.
1993-01-01
The objective of the research is to develop an analytic technique to predict the relative navigation capability of different Earth-based radio navigation measurements. In particular, the problem is to determine the relative ability of geocentric range and Doppler measurements to detect the effects of the target planet gravitational attraction on the spacecraft during the planetary approach and near-encounter mission phases. A complete solution to the two-dimensional problem has been developed. Relatively simple analytic formulas are obtained for range and Doppler measurements which describe the observability content of the measurement data along the approach trajectories. An observability measure is defined which is based on the observability matrix for nonlinear systems. The results show good agreement between the analytic observability analysis and the computational batch processing method.
Experimental Validation of the Transverse Shear Behavior of a Nomex Core for Sandwich Panels
NASA Astrophysics Data System (ADS)
Farooqi, M. I.; Nasir, M. A.; Ali, H. M.; Ali, Y.
2017-05-01
This work deals with determination of the transverse shear moduli of a Nomex® honeycomb core of sandwich panels. Their out-of-plane shear characteristics depend on the transverse shear moduli of the honeycomb core. These moduli were determined experimentally, numerically, and analytically. Numerical simulations were performed by using a unit cell model and three analytical approaches. Analytical calculations showed that two of the approaches provided reasonable predictions for the transverse shear modulus as compared with experimental results. However, the approach based upon the classical lamination theory showed large deviations from experimental data. Numerical simulations also showed a trend similar to that resulting from the analytical models.
NASA Astrophysics Data System (ADS)
Tarasenko, Alexander
2018-01-01
Diffusion of particles adsorbed on a homogeneous one-dimensional lattice is investigated using a theoretical approach and MC simulations. The analytical dependencies calculated in the framework of approach are tested using the numerical data. The perfect coincidence of the data obtained by these different methods demonstrates that the correctness of the approach based on the theory of the non-equilibrium statistical operator.
Use of multiple colorimetric indicators for paper-based microfluidic devices.
Dungchai, Wijitar; Chailapakul, Orawon; Henry, Charles S
2010-08-03
We report here the use of multiple indicators for a single analyte for paper-based microfluidic devices (microPAD) in an effort to improve the ability to visually discriminate between analyte concentrations. In existing microPADs, a single dye system is used for the measurement of a single analyte. In our approach, devices are designed to simultaneously quantify analytes using multiple indicators for each analyte improving the accuracy of the assay. The use of multiple indicators for a single analyte allows for different indicator colors to be generated at different analyte concentration ranges as well as increasing the ability to better visually discriminate colors. The principle of our devices is based on the oxidation of indicators by hydrogen peroxide produced by oxidase enzymes specific for each analyte. Each indicator reacts at different peroxide concentrations and therefore analyte concentrations, giving an extended range of operation. To demonstrate the utility of our approach, the mixture of 4-aminoantipyrine and 3,5-dichloro-2-hydroxy-benzenesulfonic acid, o-dianisidine dihydrochloride, potassium iodide, acid black, and acid yellow were chosen as the indicators for simultaneous semi-quantitative measurement of glucose, lactate, and uric acid on a microPAD. Our approach was successfully applied to quantify glucose (0.5-20 mM), lactate (1-25 mM), and uric acid (0.1-7 mM) in clinically relevant ranges. The determination of glucose, lactate, and uric acid in control serum and urine samples was also performed to demonstrate the applicability of this device for biological sample analysis. Finally results for the multi-indicator and single indicator system were compared using untrained readers to demonstrate the improvements in accuracy achieved with the new system. 2010 Elsevier B.V. All rights reserved.
Goal-Oriented Probability Density Function Methods for Uncertainty Quantification
2015-12-11
approximations or data-driven approaches. We investigated the accuracy of analytical tech- niques based Kubo -Van Kampen operator cumulant expansions for...analytical techniques based Kubo -Van Kampen operator cumulant expansions for Langevin equations driven by fractional Brownian motion and other noises
Big data analytics in immunology: a knowledge-based approach.
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.
Using Configural Frequency Analysis as a Person-Centered Analytic Approach with Categorical Data
ERIC Educational Resources Information Center
Stemmler, Mark; Heine, Jörg-Henrik
2017-01-01
Configural frequency analysis and log-linear modeling are presented as person-centered analytic approaches for the analysis of categorical or categorized data in multi-way contingency tables. Person-centered developmental psychology, based on the holistic interactionistic perspective of the Stockholm working group around David Magnusson and Lars…
A Machine-Learning-Driven Sky Model.
Satylmys, Pynar; Bashford-Rogers, Thomas; Chalmers, Alan; Debattista, Kurt
2017-01-01
Sky illumination is responsible for much of the lighting in a virtual environment. A machine-learning-based approach can compactly represent sky illumination from both existing analytic sky models and from captured environment maps. The proposed approach can approximate the captured lighting at a significantly reduced memory cost and enable smooth transitions of sky lighting to be created from a small set of environment maps captured at discrete times of day. The author's results demonstrate accuracy close to the ground truth for both analytical and capture-based methods. The approach has a low runtime overhead, so it can be used as a generic approach for both offline and real-time applications.
Data analytics approach to create waste generation profiles for waste management and collection.
Niska, Harri; Serkkola, Ari
2018-04-30
Extensive monitoring data on waste generation is increasingly collected in order to implement cost-efficient and sustainable waste management operations. In addition, geospatial data from different registries of the society are opening for free usage. Novel data analytics approaches can be built on the top of the data to produce more detailed, and in-time waste generation information for the basis of waste management and collection. In this paper, a data-based approach based on the self-organizing map (SOM) and the k-means algorithm is developed for creating a set of waste generation type profiles. The approach is demonstrated using the extensive container-level waste weighting data collected in the metropolitan area of Helsinki, Finland. The results obtained highlight the potential of advanced data analytic approaches in producing more detailed waste generation information e.g. for the basis of tailored feedback services for waste producers and the planning and optimization of waste collection and recycling. Copyright © 2018 Elsevier Ltd. All rights reserved.
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.
Saha, Arindam; Jana, Nikhil R
2015-01-14
Although microfluidic approach is widely used in various point of care diagnostics, its implementation in surface enhanced Raman spectroscopy (SERS)-based detection is challenging. This is because SERS signal depends on plasmonic nanoparticle aggregation induced generation of stable electromagnetic hot spots and in currently available microfluidic platform this condition is difficult to adapt. Here we show that SERS can be adapted using simple paper based microfluidic system where both the plasmonic nanomaterials and analyte are used in mobile phase. This approach allows analyte induced controlled particle aggregation and electromagnetic hot spot generation inside the microfluidic channel with the resultant SERS signal, which is highly reproducible and sensitive. This approach has been used for reproducible detection of protein in the pico to femtomolar concentration. Presented approach is simple, rapid, and cost-effective, and requires low sample volume. Method can be extended for SERS-based detection of other biomolecules.
Pigache, Francois; Messine, Frédéric; Nogarede, Bertrand
2007-07-01
This paper deals with a deterministic and rational way to design piezoelectric transformers in radial mode. The proposed approach is based on the study of the inverse problem of design and on its reformulation as a mixed constrained global optimization problem. The methodology relies on the association of the analytical models for describing the corresponding optimization problem and on an exact global optimization software, named IBBA and developed by the second author to solve it. Numerical experiments are presented and compared in order to validate the proposed approach.
Using Learning Analytics for Preserving Academic Integrity
ERIC Educational Resources Information Center
Amigud, Alexander; Arnedo-Moreno, Joan; Daradoumis, Thanasis; Guerrero-Roldan, Ana-Elena
2017-01-01
This paper presents the results of integrating learning analytics into the assessment process to enhance academic integrity in the e-learning environment. The goal of this research is to evaluate the computational-based approach to academic integrity. The machine-learning based framework learns students' patterns of language use from data,…
Pavement Performance : Approaches Using Predictive Analytics
DOT National Transportation Integrated Search
2018-03-23
Acceptable pavement condition is paramount to road safety. Using predictive analytics techniques, this project attempted to develop models that provide an assessment of pavement condition based on an array of indictors that include pavement distress,...
Berton, Paula; Lana, Nerina B; Ríos, Juan M; García-Reyes, Juan F; Altamirano, Jorgelina C
2016-01-28
Green chemistry principles for developing methodologies have gained attention in analytical chemistry in recent decades. A growing number of analytical techniques have been proposed for determination of organic persistent pollutants in environmental and biological samples. In this light, the current review aims to present state-of-the-art sample preparation approaches based on green analytical principles proposed for the determination of polybrominated diphenyl ethers (PBDEs) and metabolites (OH-PBDEs and MeO-PBDEs) in environmental and biological samples. Approaches to lower the solvent consumption and accelerate the extraction, such as pressurized liquid extraction, microwave-assisted extraction, and ultrasound-assisted extraction, are discussed in this review. Special attention is paid to miniaturized sample preparation methodologies and strategies proposed to reduce organic solvent consumption. Additionally, extraction techniques based on alternative solvents (surfactants, supercritical fluids, or ionic liquids) are also commented in this work, even though these are scarcely used for determination of PBDEs. In addition to liquid-based extraction techniques, solid-based analytical techniques are also addressed. The development of greener, faster and simpler sample preparation approaches has increased in recent years (2003-2013). Among green extraction techniques, those based on the liquid phase predominate over those based on the solid phase (71% vs. 29%, respectively). For solid samples, solvent assisted extraction techniques are preferred for leaching of PBDEs, and liquid phase microextraction techniques are mostly used for liquid samples. Likewise, green characteristics of the instrumental analysis used after the extraction and clean-up steps are briefly discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
Technology advancement for integrative stem cell analyses.
Jeong, Yoon; Choi, Jonghoon; Lee, Kwan Hyi
2014-12-01
Scientists have endeavored to use stem cells for a variety of applications ranging from basic science research to translational medicine. Population-based characterization of such stem cells, while providing an important foundation to further development, often disregard the heterogeneity inherent among individual constituents within a given population. The population-based analysis and characterization of stem cells and the problems associated with such a blanket approach only underscore the need for the development of new analytical technology. In this article, we review current stem cell analytical technologies, along with the advantages and disadvantages of each, followed by applications of these technologies in the field of stem cells. Furthermore, while recent advances in micro/nano technology have led to a growth in the stem cell analytical field, underlying architectural concepts allow only for a vertical analytical approach, in which different desirable parameters are obtained from multiple individual experiments and there are many technical challenges that limit vertically integrated analytical tools. Therefore, we propose--by introducing a concept of vertical and horizontal approach--that there is the need of adequate methods to the integration of information, such that multiple descriptive parameters from a stem cell can be obtained from a single experiment.
Comparison of three methods for wind turbine capacity factor estimation.
Ditkovich, Y; Kuperman, A
2014-01-01
Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first "quasiexact" approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second "analytic" approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third "approximate" approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation.
Clinical judgement in the era of big data and predictive analytics.
Chin-Yee, Benjamin; Upshur, Ross
2018-06-01
Clinical judgement is a central and longstanding issue in the philosophy of medicine which has generated significant interest over the past few decades. In this article, we explore different approaches to clinical judgement articulated in the literature, focusing in particular on data-driven, mathematical approaches which we contrast with narrative, virtue-based approaches to clinical reasoning. We discuss the tension between these different clinical epistemologies and further explore the implications of big data and machine learning for a philosophy of clinical judgement. We argue for a pluralistic, integrative approach, and demonstrate how narrative, virtue-based clinical reasoning will remain indispensable in an era of big data and predictive analytics. © 2017 John Wiley & Sons, Ltd.
Lores, Marta; Llompart, Maria; Alvarez-Rivera, Gerardo; Guerra, Eugenia; Vila, Marlene; Celeiro, Maria; Lamas, J Pablo; Garcia-Jares, Carmen
2016-04-07
Cosmetic products placed on the market and their ingredients, must be safe under reasonable conditions of use, in accordance to the current legislation. Therefore, regulated and allowed chemical substances must meet the regulatory criteria to be used as ingredients in cosmetics and personal care products, and adequate analytical methodology is needed to evaluate the degree of compliance. This article reviews the most recent methods (2005-2015) used for the extraction and the analytical determination of the ingredients included in the positive lists of the European Regulation of Cosmetic Products (EC 1223/2009): comprising colorants, preservatives and UV filters. It summarizes the analytical properties of the most relevant analytical methods along with the possibilities of fulfilment of the current regulatory issues. The cosmetic legislation is frequently being updated; consequently, the analytical methodology must be constantly revised and improved to meet safety requirements. The article highlights the most important advances in analytical methodology for cosmetics control, both in relation to the sample pretreatment and extraction and the different instrumental approaches developed to solve this challenge. Cosmetics are complex samples, and most of them require a sample pretreatment before analysis. In the last times, the research conducted covering this aspect, tended to the use of green extraction and microextraction techniques. Analytical methods were generally based on liquid chromatography with UV detection, and gas and liquid chromatographic techniques hyphenated with single or tandem mass spectrometry; but some interesting proposals based on electrophoresis have also been reported, together with some electroanalytical approaches. Regarding the number of ingredients considered for analytical control, single analyte methods have been proposed, although the most useful ones in the real life cosmetic analysis are the multianalyte approaches. Copyright © 2016 Elsevier B.V. All rights reserved.
Comparison of NMR simulations of porous media derived from analytical and voxelized representations.
Jin, Guodong; Torres-Verdín, Carlos; Toumelin, Emmanuel
2009-10-01
We develop and compare two formulations of the random-walk method, grain-based and voxel-based, to simulate the nuclear-magnetic-resonance (NMR) response of fluids contained in various models of porous media. The grain-based approach uses a spherical grain pack as input, where the solid surface is analytically defined without an approximation. In the voxel-based approach, the input is a computer-tomography or computer-generated image of reconstructed porous media. Implementation of the two approaches is largely the same, except for the representation of porous media. For comparison, both approaches are applied to various analytical and digitized models of porous media: isolated spherical pore, simple cubic packing of spheres, and random packings of monodisperse and polydisperse spheres. We find that spin magnetization decays much faster in the digitized models than in their analytical counterparts. The difference in decay rate relates to the overestimation of surface area due to the discretization of the sample; it cannot be eliminated even if the voxel size decreases. However, once considering the effect of surface-area increase in the simulation of surface relaxation, good quantitative agreement is found between the two approaches. Different grain or pore shapes entail different rates of increase of surface area, whereupon we emphasize that the value of the "surface-area-corrected" coefficient may not be universal. Using an example of X-ray-CT image of Fontainebleau rock sample, we show that voxel size has a significant effect on the calculated surface area and, therefore, on the numerically simulated magnetization response.
An Analytic Hierarchy Process for School Quality and Inspection: Model Development and Application
ERIC Educational Resources Information Center
Al Qubaisi, Amal; Badri, Masood; Mohaidat, Jihad; Al Dhaheri, Hamad; Yang, Guang; Al Rashedi, Asma; Greer, Kenneth
2016-01-01
Purpose: The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach: The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the…
A Functional Analytic Approach to Group Psychotherapy
ERIC Educational Resources Information Center
Vandenberghe, Luc
2009-01-01
This article provides a particular view on the use of Functional Analytical Psychotherapy (FAP) in a group therapy format. This view is based on the author's experiences as a supervisor of Functional Analytical Psychotherapy Groups, including groups for women with depression and groups for chronic pain patients. The contexts in which this approach…
Alexovič, Michal; Horstkotte, Burkhard; Solich, Petr; Sabo, Ján
2016-02-04
Simplicity, effectiveness, swiftness, and environmental friendliness - these are the typical requirements for the state of the art development of green analytical techniques. Liquid phase microextraction (LPME) stands for a family of elegant sample pretreatment and analyte preconcentration techniques preserving these principles in numerous applications. By using only fractions of solvent and sample compared to classical liquid-liquid extraction, the extraction kinetics, the preconcentration factor, and the cost efficiency can be increased. Moreover, significant improvements can be made by automation, which is still a hot topic in analytical chemistry. This review surveys comprehensively and in two parts the developments of automation of non-dispersive LPME methodologies performed in static and dynamic modes. Their advantages and limitations and the reported analytical performances are discussed and put into perspective with the corresponding manual procedures. The automation strategies, techniques, and their operation advantages as well as their potentials are further described and discussed. In this first part, an introduction to LPME and their static and dynamic operation modes as well as their automation methodologies is given. The LPME techniques are classified according to the different approaches of protection of the extraction solvent using either a tip-like (needle/tube/rod) support (drop-based approaches), a wall support (film-based approaches), or microfluidic devices. In the second part, the LPME techniques based on porous supports for the extraction solvent such as membranes and porous media are overviewed. An outlook on future demands and perspectives in this promising area of analytical chemistry is finally given. Copyright © 2015 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Phatak, A. V.
1980-01-01
A systematic analytical approach to the determination of helicopter IFR precision approach requirements is formulated. The approach is based upon the hypothesis that pilot acceptance level or opinion rating of a given system is inversely related to the degree of pilot involvement in the control task. A nonlinear simulation of the helicopter approach to landing task incorporating appropriate models for UH-1H aircraft, the environmental disturbances and the human pilot was developed as a tool for evaluating the pilot acceptance hypothesis. The simulated pilot model is generic in nature and includes analytical representation of the human information acquisition, processing, and control strategies. Simulation analyses in the flight director mode indicate that the pilot model used is reasonable. Results of the simulation are used to identify candidate pilot workload metrics and to test the well known performance-work-load relationship. A pilot acceptance analytical methodology is formulated as a basis for further investigation, development and validation.
ERIC Educational Resources Information Center
Lotfipour-Saedi, Kazem
2015-01-01
This paper represents some suggestions towards discourse-analytic approaches for ESL/EFL education, with the focus on identifying the textual forms which can contribute to the textual difficulty. Textual difficulty/comprehensibility, rather than being purely text-based or reader-dependent, is certainly a matter of interaction between text and…
ERIC Educational Resources Information Center
Yogev, Sara; Brett, Jeanne
This paper offers a conceptual framework for the intersection of work and family roles based on the constructs of work involvement and family involvement. The theoretical and empirical literature on the intersection of work and family roles is reviewed from two analytical approaches. From the individual level of analysis, the literature reviewed…
NASA Astrophysics Data System (ADS)
Maghsoudi, Mohammad Javad; Mohamed, Z.; Sudin, S.; Buyamin, S.; Jaafar, H. I.; Ahmad, S. M.
2017-08-01
This paper proposes an improved input shaping scheme for an efficient sway control of a nonlinear three dimensional (3D) overhead crane with friction using the particle swarm optimization (PSO) algorithm. Using this approach, a higher payload sway reduction is obtained as the input shaper is designed based on a complete nonlinear model, as compared to the analytical-based input shaping scheme derived using a linear second order model. Zero Vibration (ZV) and Distributed Zero Vibration (DZV) shapers are designed using both analytical and PSO approaches for sway control of rail and trolley movements. To test the effectiveness of the proposed approach, MATLAB simulations and experiments on a laboratory 3D overhead crane are performed under various conditions involving different cable lengths and sway frequencies. Their performances are studied based on a maximum residual of payload sway and Integrated Absolute Error (IAE) values which indicate total payload sway of the crane. With experiments, the superiority of the proposed approach over the analytical-based is shown by 30-50% reductions of the IAE values for rail and trolley movements, for both ZV and DZV shapers. In addition, simulations results show higher sway reductions with the proposed approach. It is revealed that the proposed PSO-based input shaping design provides higher payload sway reductions of a 3D overhead crane with friction as compared to the commonly designed input shapers.
Analytical quality by design: a tool for regulatory flexibility and robust analytics.
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
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
ERIC Educational Resources Information Center
Comaskey, Erin M.; Savage, Robert S.; Abrami, Philip
2009-01-01
This study explores whether two computer-based literacy interventions--a "synthetic phonics" and an "analytic phonics" approach produce qualitatively distinct effects on the early phonological abilities and reading skills of disadvantaged urban Kindergarten (Reception) children. Participants (n=53) were assigned by random allocation to one of the…
Farzanehfar, Vahid; Faizi, Mehrdad; Naderi, Nima; Kobarfard, Farzad
2017-01-01
Dibutyl phthalate (DBP) is a phthalic acid ester and is widely used in polymeric products to make them more flexible. DBP is found in almost every plastic material and is believed to be persistent in the environment. Various analytical methods have been used to measure DBP in different matrices. Considering the ubiquitous nature of DBP, the most important challenge in DBP analyses is the contamination of even analytical grade organic solvents with this compound and lack of availability of a true blank matrix to construct the calibration line. Standard addition method or using artificial matrices reduce the precision and accuracy of the results. In this study a surrogate analyte approach that is based on using deuterium labeled analyte (DBP-d4) to construct the calibration line was applied to determine DBP in hexane samples. PMID:28496469
A consortium-driven framework to guide the implementation of ICH M7 Option 4 control strategies.
Barber, Chris; Antonucci, Vincent; Baumann, Jens-Christoph; Brown, Roland; Covey-Crump, Elizabeth; Elder, David; Elliott, Eric; Fennell, Jared W; Gallou, Fabrice; Ide, Nathan D; Jordine, Guido; Kallemeyn, Jeffrey M; Lauwers, Dirk; Looker, Adam R; Lovelle, Lucie E; McLaughlin, Mark; Molzahn, Robert; Ott, Martin; Schils, Didier; Oestrich, Rolf Schulte; Stevenson, Neil; Talavera, Pere; Teasdale, Andrew; Urquhart, Michael W; Varie, David L; Welch, Dennie
2017-11-01
The ICH M7 Option 4 control of (potentially) mutagenic impurities is based on the use of scientific principles in lieu of routine analytical testing. This approach can reduce the burden of analytical testing without compromising patient safety, provided a scientifically rigorous approach is taken which is backed up by sufficient theoretical and/or analytical data. This paper introduces a consortium-led initiative and offers a proposal on the supporting evidence that could be presented in regulatory submissions. Copyright © 2017 Elsevier Inc. All rights reserved.
Estimation of the limit of detection using information theory measures.
Fonollosa, Jordi; Vergara, Alexander; Huerta, Ramón; Marco, Santiago
2014-01-31
Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise. Copyright © 2013 Elsevier B.V. All rights reserved.
Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua
2018-01-01
Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Developing Students' Ideas about Lens Imaging: Teaching Experiments with an Image-Based Approach
ERIC Educational Resources Information Center
Grusche, Sascha
2017-01-01
Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists' analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students' ideas, teaching experiments are performed and evaluated using…
Cierniak, Robert; Lorent, Anna
2016-09-01
The main aim of this paper is to investigate properties of our originally formulated statistical model-based iterative approach applied to the image reconstruction from projections problem which are related to its conditioning, and, in this manner, to prove a superiority of this approach over ones recently used by other authors. The reconstruction algorithm based on this conception uses a maximum likelihood estimation with an objective adjusted to the probability distribution of measured signals obtained from an X-ray computed tomography system with parallel beam geometry. The analysis and experimental results presented here show that our analytical approach outperforms the referential algebraic methodology which is explored widely in the literature and exploited in various commercial implementations. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lumb, Matthew P.; Naval Research Laboratory, Washington, DC 20375; Steiner, Myles A.
The analytical drift-diffusion formalism is able to accurately simulate a wide range of solar cell architectures and was recently extended to include those with back surface reflectors. However, as solar cells approach the limits of material quality, photon recycling effects become increasingly important in predicting the behavior of these cells. In particular, the minority carrier diffusion length is significantly affected by the photon recycling, with consequences for the solar cell performance. In this paper, we outline an approach to account for photon recycling in the analytical Hovel model and compare analytical model predictions to GaAs-based experimental devices operating close tomore » the fundamental efficiency limit.« less
Analytical approximation and numerical simulations for periodic travelling water waves
NASA Astrophysics Data System (ADS)
Kalimeris, Konstantinos
2017-12-01
We present recent analytical and numerical results for two-dimensional periodic travelling water waves with constant vorticity. The analytical approach is based on novel asymptotic expansions. We obtain numerical results in two different ways: the first is based on the solution of a constrained optimization problem, and the second is realized as a numerical continuation algorithm. Both methods are applied on some examples of non-constant vorticity. This article is part of the theme issue 'Nonlinear water waves'.
DNA strand displacement reaction for programmable release of biomolecules.
Ramezani, Hamid; Jed Harrison, D
2015-05-14
Sample cleanup is a major processing step in many analytical assays. Here, we propose an approach to capture-and-release of analytes based on the DNA strand displacement reaction (SDR) and demonstrate its application to a fluoroimmunoassay on beads for a thyroid cancer biomarker, thyroglobulin. The SDR-based cleanup showed no interference from matrix molecules in serum.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.
In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less
Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.; ...
2017-12-05
In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less
On Establishing Big Data Wave Breakwaters with Analytics (Invited)
NASA Astrophysics Data System (ADS)
Riedel, M.
2013-12-01
The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.
ERIC Educational Resources Information Center
Stickney, Jeff Alan
2009-01-01
Comparing the early, analytic attempt to define "sound" teaching with the current use of criteria-based rating schemes, Jeff Stickney turns to Wittgenstein's holistic, contextualist approach to judging teaching against its complex "background" within our "form of life." To exemplify this approach, Stickney presents cases of classroom practice…
Immunoanalysis Methods for the Detection of Dioxins and Related Chemicals
Tian, Wenjing; Xie, Heidi Qunhui; Fu, Hualing; Pei, Xinhui; Zhao, Bin
2012-01-01
With the development of biotechnology, approaches based on antibodies, such as enzyme-linked immunosorbent assay (ELISA), active aryl hydrocarbon immunoassay (Ah-I) and other multi-analyte immunoassays, have been utilized as alternatives to the conventional techniques based on gas chromatography and mass spectroscopy for the analysis of dioxin and dioxin-like compounds in environmental and biological samples. These screening methods have been verified as rapid, simple and cost-effective. This paper provides an overview on the development and application of antibody-based approaches, such as ELISA, Ah-I, and multi-analyte immunoassays, covering the sample extraction and cleanup, antigen design, antibody preparation and immunoanalysis. However, in order to meet the requirements for on-site fast detection and relative quantification of dioxins in the environment, further optimization is needed to make these immuno-analytical methods more sensitive and easy to use. PMID:23443395
Classical Dynamics of Fullerenes
NASA Astrophysics Data System (ADS)
Sławianowski, Jan J.; Kotowski, Romuald K.
2017-06-01
The classical mechanics of large molecules and fullerenes is studied. The approach is based on the model of collective motion of these objects. The mixed Lagrangian (material) and Eulerian (space) description of motion is used. In particular, the Green and Cauchy deformation tensors are geometrically defined. The important issue is the group-theoretical approach to describing the affine deformations of the body. The Hamiltonian description of motion based on the Poisson brackets methodology is used. The Lagrange and Hamilton approaches allow us to formulate the mechanics in the canonical form. The method of discretization in analytical continuum theory and in classical dynamics of large molecules and fullerenes enable us to formulate their dynamics in terms of the polynomial expansions of configurations. Another approach is based on the theory of analytical functions and on their approximations by finite-order polynomials. We concentrate on the extremely simplified model of affine deformations or on their higher-order polynomial perturbations.
Pan, Yijie; Wang, Yongtian; Liu, Juan; Li, Xin; Jia, Jia
2014-03-01
Previous research [Appl. Opt.52, A290 (2013)] has revealed that Fourier analysis of three-dimensional affine transformation theory can be used to improve the computation speed of the traditional polygon-based method. In this paper, we continue our research and propose an improved full analytical polygon-based method developed upon this theory. Vertex vectors of primitive and arbitrary triangles and the pseudo-inverse matrix were used to obtain an affine transformation matrix representing the spatial relationship between the two triangles. With this relationship and the primitive spectrum, we analytically obtained the spectrum of the arbitrary triangle. This algorithm discards low-level angular dependent computations. In order to add diffusive reflection to each arbitrary surface, we also propose a whole matrix computation approach that takes advantage of the affine transformation matrix and uses matrix multiplication to calculate shifting parameters of similar sub-polygons. The proposed method improves hologram computation speed for the conventional full analytical approach. Optical experimental results are demonstrated which prove that the proposed method can effectively reconstruct three-dimensional scenes.
Multiplexed Paper Analytical Device for Quantification of Metals using Distance-Based Detection
Cate, David M.; Noblitt, Scott D.; Volckens, John; Henry, Charles S.
2015-01-01
Exposure to metal-containing aerosols has been linked with adverse health outcomes for almost every organ in the human body. Commercially available techniques for quantifying particulate metals are time-intensive, laborious, and expensive; often sample analysis exceeds $100. We report a simple technique, based upon a distance-based detection motif, for quantifying metal concentrations of Ni, Cu, and Fe in airborne particulate matter using microfluidic paper-based analytical devices. Paper substrates are used to create sensors that are self-contained, self-timing, and require only a drop of sample for operation. Unlike other colorimetric approaches in paper microfluidics that rely on optical instrumentation for analysis, with distance-based detection, analyte is quantified visually based on the distance of a colorimetric reaction, similar to reading temperature on a thermometer. To demonstrate the effectiveness of this approach, Ni, Cu, and Fe were measured individually in single-channel devices; detection limits as low as 0.1, 0.1, and 0.05 µg were reported for Ni, Cu, and Fe. Multiplexed analysis of all three metals was achieved with detection limits of 1, 5, and 1 µg for Ni, Cu, and Fe. We also extended the dynamic range for multi-analyte detection by printing concentration gradients of colorimetric reagents using an off the shelf inkjet printer. Analyte selectivity was demonstrated for common interferences. To demonstrate utility of the method, Ni, Cu, and Fe were measured from samples of certified welding fume; levels measured with paper sensors matched known values determined gravimetrically. PMID:26009988
Panchal, Mitesh B; Upadhyay, Sanjay H
2014-09-01
In this study, the feasibility of single walled boron nitride nanotube (SWBNNT)-based biosensors has been ensured considering the continuum modelling-based simulation approach, for mass-based detection of various bacterium/viruses. Various types of bacterium or viruses have been taken into consideration at the free-end of the cantilevered configuration of the SWBNNT, as a biosensor. Resonant frequency shift-based analysis has been performed with the adsorption of various bacterium/viruses considered as additional mass to the SWBNNT-based sensor system. The continuum mechanics-based analytical approach, considering effective wall thickness has been considered to validate the finite element method (FEM)-based simulation results, based on continuum volume-based modelling of the SWBNNT. As a systematic analysis approach, the FEM-based simulation results are found in excellent agreement with the analytical results, to analyse the SWBNNTs for their wide range of applications such as nanoresonators, biosensors, gas-sensors, transducers and so on. The obtained results suggest that by using the SWBNNT of smaller size the sensitivity of the sensor system can be enhanced and detection of the bacterium/virus having mass of 4.28 × 10⁻²⁴ kg can be effectively performed.
Ultramicroelectrode Array Based Sensors: A Promising Analytical Tool for Environmental Monitoring
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
DOT National Transportation Integrated Search
1975-05-01
The report describes an analytical approach to estimation of fuel consumption in rail transportation, and provides sample computer calculations suggesting the sensitivity of fuel usage to various parameters. The model used is based upon careful delin...
Earthdata Cloud Analytics Project
NASA Technical Reports Server (NTRS)
Ramachandran, Rahul; Lynnes, Chris
2018-01-01
This presentation describes a nascent project in NASA to develop a framework to support end-user analytics of NASA's Earth science data in the cloud. The chief benefit of migrating EOSDIS (Earth Observation System Data and Information Systems) data to the cloud is to position the data next to enormous computing capacity to allow end users to process data at scale. The Earthdata Cloud Analytics project will user a service-based approach to facilitate the infusion of evolving analytics technology and the integration with non-NASA analytics or other complementary functionality at other agencies and in other nations.
Evolution of accelerometer methods for physical activity research.
Troiano, Richard P; McClain, James J; Brychta, Robert J; Chen, Kong Y
2014-07-01
The technology and application of current accelerometer-based devices in physical activity (PA) research allow the capture and storage or transmission of large volumes of raw acceleration signal data. These rich data not only provide opportunities to improve PA characterisation, but also bring logistical and analytic challenges. We discuss how researchers and developers from multiple disciplines are responding to the analytic challenges and how advances in data storage, transmission and big data computing will minimise logistical challenges. These new approaches also bring the need for several paradigm shifts for PA researchers, including a shift from count-based approaches and regression calibrations for PA energy expenditure (PAEE) estimation to activity characterisation and EE estimation based on features extracted from raw acceleration signals. Furthermore, a collaborative approach towards analytic methods is proposed to facilitate PA research, which requires a shift away from multiple independent calibration studies. Finally, we make the case for a distinction between PA represented by accelerometer-based devices and PA assessed by self-report. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Cáceres, C; Canfarotta, F; Chianella, I; Pereira, E; Moczko, E; Esen, C; Guerreiro, A; Piletska, E; Whitcombe, M J; Piletsky, S A
2016-02-21
The aim of this work is to evaluate whether the size of the analyte used as template for the synthesis of molecularly imprinted polymer nanoparticles (nanoMIPs) can affect their performance in pseudo-enzyme linked immunosorbent assays (pseudo-ELISAs). Successful demonstration of a nanoMIPs-based pseudo-ELISA for vancomycin (1449.3 g mol(-1)) was demonstrated earlier. In the present investigation, the following analytes were selected: horseradish peroxidase (HRP, 44 kDa), cytochrome C (Cyt C, 12 kDa) biotin (244.31 g mol(-1)) and melamine (126.12 g mol(-1)). NanoMIPs with a similar composition for all analytes were synthesised by persulfate-initiated polymerisation in water. In addition, core-shell nanoMIPs coated with polyethylene glycol (PEG) and imprinted for melamine were produced in organics and tested. The polymerisation of the nanoparticles was done using a solid-phase approach with the correspondent template immobilised on glass beads. The performance of the nanoMIPs used as replacement for antibodies in direct pseudo-ELISA (for the enzymes) and competitive pseudo-ELISA for the smaller analytes was investigated. For the competitive mode we rely on competition for the binding to the nanoparticles between free analyte and corresponding analyte-HRP conjugate. The results revealed that the best performances were obtained for nanoMIPs synthesised in aqueous media for the larger analytes. In addition, this approach was successful for biotin but completely failed for the smallest template melamine. This problem was solved using nanoMIP prepared by UV polymerisation in an organic media with a PEG shell. This study demonstrates that the preparation of nanoMIP by solid-phase approach can produce material with high affinity and potential to replace antibodies in ELISA tests for both large and small analytes. This makes this technology versatile and applicable to practically any target analyte and diagnostic field.
Development of computer-based analytical tool for assessing physical protection system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mardhi, Alim, E-mail: alim-m@batan.go.id; Chulalongkorn University, Faculty of Engineering, Nuclear Engineering Department, 254 Phayathai Road, Pathumwan, Bangkok Thailand. 10330; Pengvanich, Phongphaeth, E-mail: ppengvan@gmail.com
Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work,more » we have developed a computer–based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system’s detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.« less
Development of computer-based analytical tool for assessing physical protection system
NASA Astrophysics Data System (ADS)
Mardhi, Alim; Pengvanich, Phongphaeth
2016-01-01
Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work, we have developed a computer-based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system's detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.
An evolution based biosensor receptor DNA sequence generation algorithm.
Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng
2010-01-01
A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.
Thomas, Jason M; Chakraborty, Banani; Sen, Dipankar; Yu, Hua-Zhong
2012-08-22
A general approach is described for the de novo design and construction of aptamer-based electrochemical biosensors, for potentially any analyte of interest (ranging from small ligands to biological macromolecules). As a demonstration of the approach, we report the rapid development of a made-to-order electronic sensor for a newly reported early biomarker for lung cancer (CTAP III/NAP2). The steps include the in vitro selection and characterization of DNA aptamer sequences, design and biochemical testing of wholly DNA sensor constructs, and translation to a functional electrode-bound sensor format. The working principle of this distinct class of electronic biosensors is the enhancement of DNA-mediated charge transport in response to analyte binding. We first verify such analyte-responsive charge transport switching in solution, using biochemical methods; successful sensor variants were then immobilized on gold electrodes. We show that using these sensor-modified electrodes, CTAP III/NAP2 can be detected with both high specificity and sensitivity (K(d) ~1 nM) through a direct electrochemical reading. To investigate the underlying basis of analyte binding-induced conductivity switching, we carried out Förster Resonance Energy Transfer (FRET) experiments. The FRET data establish that analyte binding-induced conductivity switching in these sensors results from very subtle structural/conformational changes, rather than large scale, global folding events. The implications of this finding are discussed with respect to possible charge transport switching mechanisms in electrode-bound sensors. Overall, the approach we describe here represents a unique design principle for aptamer-based electrochemical sensors; its application should enable rapid, on-demand access to a class of portable biosensors that offer robust, inexpensive, and operationally simplified alternatives to conventional antibody-based immunoassays.
NASA Technical Reports Server (NTRS)
Elbanna, Hesham M.; Carlson, Leland A.
1992-01-01
The quasi-analytical approach is applied to the three-dimensional full potential equation to compute wing aerodynamic sensitivity coefficients in the transonic regime. Symbolic manipulation is used to reduce the effort associated with obtaining the sensitivity equations, and the large sensitivity system is solved using 'state of the art' routines. Results are compared to those obtained by the direct finite difference approach and both methods are evaluated to determine their computational accuracy and efficiency. The quasi-analytical approach is shown to be accurate and efficient for large aerodynamic systems.
Modern reaction-based indicator systems†
2010-01-01
Traditional analyte-specific synthetic receptors or sensors have been developed on the basis of supramolecular interactions (e.g., hydrogen bonding, electrostatics, weak coordinative bonds). Unfortunately, this approach is often subject to limitations. As a result, increasing attention within the chemical sensor community is turning to the use of analyte-specific molecular indicators, wherein substrate-triggered reactions are used to signal the presence of a given analyte. This tutorial review highlights recent reaction-based indicator systems that have been used to detect selected anions, cations, reactive oxygen species, and neutral substrates. PMID:19587959
NASA Astrophysics Data System (ADS)
Nicgorski, Dana; Avitabile, Peter
2010-07-01
Frequency-based substructuring is a very popular approach for the generation of system models from component measured data. Analytically the approach has been shown to produce accurate results. However, implementation with actual test data can cause difficulties and cause problems with the system response prediction. In order to produce good results, extreme care is needed in the measurement of the drive point and transfer impedances of the structure as well as observe all the conditions for a linear time invariant system. Several studies have been conducted to show the sensitivity of the technique to small variations that often occur during typical testing of structures. These variations have been observed in actual tested configurations and have been substantiated with analytical models to replicate the problems typically encountered. The use of analytically simulated issues helps to clearly see the effects of typical measurement difficulties often observed in test data. This paper presents some of these common problems observed and provides guidance and recommendations for data to be used for this modeling approach.
Total analysis systems with Thermochromic Etching Discs technology.
Avella-Oliver, Miquel; Morais, Sergi; Carrascosa, Javier; Puchades, Rosa; Maquieira, Ángel
2014-12-16
A new analytical system based on Thermochromic Etching Discs (TED) technology is presented. TED comprises a number of attractive features such as track independency, selective irradiation, a high power laser, and the capability to create useful assay platforms. The analytical versatility of this tool opens up a wide range of possibilities to design new compact disc-based total analysis systems applicable in chemistry and life sciences. In this paper, TED analytical implementation is described and discussed, and their analytical potential is supported by several applications. Microarray immunoassay, immunofiltration assay, solution measurement, and cell culture approaches are herein addressed in order to demonstrate the practical capacity of this system. The analytical usefulness of TED technology is herein demonstrated, describing how to exploit this tool for developing truly integrated analytical systems that provide solutions within the point of care framework.
Hervatis, Vasilis; Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil
2015-10-06
Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators' decision making. A deductive case study approach was applied to develop the conceptual model. The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach.
Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil
2015-01-01
Background Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. Objective The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators’ decision making. Methods A deductive case study approach was applied to develop the conceptual model. Results The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. Conclusions The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach. PMID:27731840
"Dip-and-read" paper-based analytical devices using distance-based detection with color screening.
Yamada, Kentaro; Citterio, Daniel; Henry, Charles S
2018-05-15
An improved paper-based analytical device (PAD) using color screening to enhance device performance is described. Current detection methods for PADs relying on the distance-based signalling motif can be slow due to the assay time being limited by capillary flow rates that wick fluid through the detection zone. For traditional distance-based detection motifs, analysis can take up to 45 min for a channel length of 5 cm. By using a color screening method, quantification with a distance-based PAD can be achieved in minutes through a "dip-and-read" approach. A colorimetric indicator line deposited onto a paper substrate using inkjet-printing undergoes a concentration-dependent colorimetric response for a given analyte. This color intensity-based response has been converted to a distance-based signal by overlaying a color filter with a continuous color intensity gradient matching the color of the developed indicator line. As a proof-of-concept, Ni quantification in welding fume was performed as a model assay. The results of multiple independent user testing gave mean absolute percentage error and average relative standard deviations of 10.5% and 11.2% respectively, which were an improvement over analysis based on simple visual color comparison with a read guide (12.2%, 14.9%). In addition to the analytical performance comparison, an interference study and a shelf life investigation were performed to further demonstrate practical utility. The developed system demonstrates an alternative detection approach for distance-based PADs enabling fast (∼10 min), quantitative, and straightforward assays.
NASA Astrophysics Data System (ADS)
Laminack, William; Gole, James
2015-12-01
A unique MEMS/NEMS approach is presented for the modeling of a detection platform for mixed gas interactions. Mixed gas analytes interact with nanostructured decorating metal oxide island sites supported on a microporous silicon substrate. The Inverse Hard/Soft acid/base (IHSAB) concept is used to assess a diversity of conductometric responses for mixed gas interactions as a function of these nanostructured metal oxides. The analyte conductometric responses are well represented using a combination diffusion/absorption-based model for multi-gas interactions where a newly developed response absorption isotherm, based on the Fermi distribution function is applied. A further coupling of this model with the IHSAB concept describes the considerations in modeling of multi-gas mixed analyte-interface, and analyte-analyte interactions. Taking into account the molecular electronic interaction of both the analytes with each other and an extrinsic semiconductor interface we demonstrate how the presence of one gas can enhance or diminish the reversible interaction of a second gas with the extrinsic semiconductor interface. These concepts demonstrate important considerations in the array-based formats for multi-gas sensing and its applications.
Applying SF-Based Genre Approaches to English Writing Class
ERIC Educational Resources Information Center
Wu, Yan; Dong, Hailin
2009-01-01
By exploring genre approaches in systemic functional linguistics and examining the analytic tools that can be applied to the process of English learning and teaching, this paper seeks to find a way of applying genre approaches to English writing class.
Pang, Susan; Cowen, Simon
2017-12-13
We describe a novel generic method to derive the unknown endogenous concentrations of analyte within complex biological matrices (e.g. serum or plasma) based upon the relationship between the immunoassay signal response of a biological test sample spiked with known analyte concentrations and the log transformed estimated total concentration. If the estimated total analyte concentration is correct, a portion of the sigmoid on a log-log plot is very close to linear, allowing the unknown endogenous concentration to be estimated using a numerical method. This approach obviates conventional relative quantification using an internal standard curve and need for calibrant diluent, and takes into account the individual matrix interference on the immunoassay by spiking the test sample itself. This technique is based on standard additions for chemical analytes. Unknown endogenous analyte concentrations within even 2-fold diluted human plasma may be determined reliably using as few as four reaction wells.
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 documents.
Jáčová, Jaroslava; Gardlo, Alžběta; Friedecký, David; Adam, Tomáš; Dimandja, Jean-Marie D
2017-08-18
Orthogonality is a key parameter that is used to evaluate the separation power of chromatography-based two-dimensional systems. It is necessary to scale the separation data before the assessment of the orthogonality. Current scaling approaches are sample-dependent, and the extent of the retention space that is converted into a normalized retention space is set according to the retention times of the first and last analytes contained in a unique sample to elute. The presence or absence of a highly retained analyte in a sample can thus significantly influence the amount of information (in terms of the total amount of separation space) contained in the normalized retention space considered for the calculation of the orthogonality. We propose a Whole Separation Space Scaling (WOSEL) approach that accounts for the whole separation space delineated by the analytical method, and not the sample. This approach enables an orthogonality-based evaluation of the efficiency of the analytical system that is independent of the sample selected. The WOSEL method was compared to two currently used orthogonality approaches through the evaluation of in silico-generated chromatograms and real separations of human biofluids and petroleum samples. WOSEL exhibits sample-to-sample stability values of 3.8% on real samples, compared to 7.0% and 10.1% for the two other methods, respectively. Using real analyses, we also demonstrate that some previously developed approaches can provide misleading conclusions on the overall orthogonality of a two-dimensional chromatographic system. Copyright © 2017 Elsevier B.V. All rights reserved.
Flexible aircraft dynamic modeling for dynamic analysis and control synthesis
NASA Technical Reports Server (NTRS)
Schmidt, David K.
1989-01-01
The linearization and simplification of a nonlinear, literal model for flexible aircraft is highlighted. Areas of model fidelity that are critical if the model is to be used for control system synthesis are developed and several simplification techniques that can deliver the necessary model fidelity are discussed. These techniques include both numerical and analytical approaches. An analytical approach, based on first-order sensitivity theory is shown to lead not only to excellent numerical results, but also to closed-form analytical expressions for key system dynamic properties such as the pole/zero factors of the vehicle transfer-function matrix. The analytical results are expressed in terms of vehicle mass properties, vibrational characteristics, and rigid-body and aeroelastic stability derivatives, thus leading to the underlying causes for critical dynamic characteristics.
Some Psychometric and Design Implications of Game-Based Learning Analytics
ERIC Educational Resources Information Center
Gibson, David; Clarke-Midura, Jody
2013-01-01
The rise of digital game and simulation-based learning applications has led to new approaches in educational measurement that take account of patterns in time, high resolution paths of action, and clusters of virtual performance artifacts. The new approaches, which depart from traditional statistical analyses, include data mining, machine…
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
Effects of CDA Instruction on EFL Analytical Reading Practices
ERIC Educational Resources Information Center
Hazaea, Abduljalil Nasr; Alzubi, Ali Abbas
2017-01-01
Discourse-based approaches to EFL reading have shifted the students' passive role to become 'text resistant'. This paper examines the extent to which Critical Discourse Analysis (CDA) enhances analytical reading practices in English as a Foreign Language (EFL) reading context among Preparatory Year students at Najran University. The paper…
Promoting Efficacy Research on Functional Analytic Psychotherapy
ERIC Educational Resources Information Center
Maitland, Daniel W. M.; Gaynor, Scott T.
2012-01-01
Functional Analytic Psychotherapy (FAP) is a form of therapy grounded in behavioral principles that utilizes therapist reactions to shape target behavior. Despite a growing literature base, there is a paucity of research to establish the efficacy of FAP. As a general approach to psychotherapy, and how the therapeutic relationship produces change,…
A Visual Analytics Approach for Station-Based Air Quality Data
Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui
2016-01-01
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117
A Visual Analytics Approach for Station-Based Air Quality Data.
Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui
2016-12-24
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.
Technology Advancement for Integrative Stem Cell Analyses
Jeong, Yoon
2014-01-01
Scientists have endeavored to use stem cells for a variety of applications ranging from basic science research to translational medicine. Population-based characterization of such stem cells, while providing an important foundation to further development, often disregard the heterogeneity inherent among individual constituents within a given population. The population-based analysis and characterization of stem cells and the problems associated with such a blanket approach only underscore the need for the development of new analytical technology. In this article, we review current stem cell analytical technologies, along with the advantages and disadvantages of each, followed by applications of these technologies in the field of stem cells. Furthermore, while recent advances in micro/nano technology have led to a growth in the stem cell analytical field, underlying architectural concepts allow only for a vertical analytical approach, in which different desirable parameters are obtained from multiple individual experiments and there are many technical challenges that limit vertically integrated analytical tools. Therefore, we propose—by introducing a concept of vertical and horizontal approach—that there is the need of adequate methods to the integration of information, such that multiple descriptive parameters from a stem cell can be obtained from a single experiment. PMID:24874188
Spiral trajectory design: a flexible numerical algorithm and base analytical equations.
Pipe, James G; Zwart, Nicholas R
2014-01-01
Spiral-based trajectories for magnetic resonance imaging can be advantageous, but are often cumbersome to design or create. This work presents a flexible numerical algorithm for designing trajectories based on explicit definition of radial undersampling, and also gives several analytical expressions for charactering the base (critically sampled) class of these trajectories. Expressions for the gradient waveform, based on slew and amplitude limits, are developed such that a desired pitch in the spiral k-space trajectory is followed. The source code for this algorithm, written in C, is publicly available. Analytical expressions approximating the spiral trajectory (ignoring the radial component) are given to characterize measurement time, gradient heating, maximum gradient amplitude, and off-resonance phase for slew-limited and gradient amplitude-limited cases. Several numerically calculated trajectories are illustrated, and base Archimedean spirals are compared with analytically obtained results. Several different waveforms illustrate that the desired slew and amplitude limits are reached, as are the desired undersampling patterns, using the numerical method. For base Archimedean spirals, the results of the numerical and analytical approaches are in good agreement. A versatile numerical algorithm was developed, and was written in publicly available code. Approximate analytical formulas are given that help characterize spiral trajectories. Copyright © 2013 Wiley Periodicals, Inc.
Proceedings of the Workshop on Change of Representation and Problem Reformulation
NASA Technical Reports Server (NTRS)
Lowry, Michael R.
1992-01-01
The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.
Bioinspired Methodology for Artificial Olfaction
Raman, Baranidharan; Hertz, Joshua L.; Benkstein, Kurt D.; Semancik, Steve
2008-01-01
Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of “electronic noses” typically involves recognition of “pretrained” chemicals, while long-term operation and generalization of training to allow chemical classification of “unknown” analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications. PMID:18855409
Vass, Andrea; Robles-Molina, José; Pérez-Ortega, Patricia; Gilbert-López, Bienvenida; Dernovics, Mihaly; Molina-Díaz, Antonio; García-Reyes, Juan F
2016-07-01
The aim of the study was to evaluate the performance of different chromatographic approaches for the liquid chromatography/mass spectrometry (LC-MS(/MS)) determination of 24 highly polar pesticides. The studied compounds, which are in most cases unsuitable for conventional LC-MS(/MS) multiresidue methods were tested with nine different chromatographic conditions, including two different hydrophilic interaction liquid chromatography (HILIC) columns, two zwitterionic-type mixed-mode columns, three normal-phase columns operated in HILIC-mode (bare silica and two silica-based chemically bonded columns (cyano and amino)), and two standard reversed-phase C18 columns. Different sets of chromatographic parameters in positive (for 17 analytes) and negative ionization modes (for nine analytes) were examined. In order to compare the different approaches, a semi-quantitative classification was proposed, calculated as the percentage of an empirical performance value, which consisted of three main features: (i) capacity factor (k) to characterize analyte separation from the void, (ii) relative response factor, and (iii) peak shape based on analytes' peak width. While no single method was able to provide appropriate detection of all the 24 studied species in a single run, the best suited approach for the compounds ionized in positive mode was based on a UHPLC HILIC column with 1.8 μm particle size, providing appropriate results for 22 out of the 24 species tested. In contrast, the detection of glyphosate and aminomethylphosphonic acid could only be achieved with a zwitterionic-type mixed-mode column, which proved to be suitable only for the pesticides detected in negative ion mode. Finally, the selected approach (UHPLC HILIC) was found to be useful for the determination of multiple pesticides in oranges using HILIC-ESI-MS/MS, with limits of quantitation in the low microgram per kilogram in most cases. Graphical Abstract HILIC improves separation of multiclass polar pesticides.
Lagrangian based methods for coherent structure detection
NASA Astrophysics Data System (ADS)
Allshouse, Michael R.; Peacock, Thomas
2015-09-01
There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.
An NCI-FDA Interagency Oncology Task Force (IOTF) Molecular Diagnostics Workshop was held on October 30, 2008 in Cambridge, MA, to discuss requirements for analytical validation of protein-based multiplex technologies in the context of its intended use. This workshop developed through NCI's Clinical Proteomic Technologies for Cancer initiative and the FDA focused on technology-specific analytical validation processes to be addressed prior to use in clinical settings. In making this workshop unique, a case study approach was used to discuss issues related to
Translucent Radiosity: Efficiently Combining Diffuse Inter-Reflection and Subsurface Scattering.
Sheng, Yu; Shi, Yulong; Wang, Lili; Narasimhan, Srinivasa G
2014-07-01
It is hard to efficiently model the light transport in scenes with translucent objects for interactive applications. The inter-reflection between objects and their environments and the subsurface scattering through the materials intertwine to produce visual effects like color bleeding, light glows, and soft shading. Monte-Carlo based approaches have demonstrated impressive results but are computationally expensive, and faster approaches model either only inter-reflection or only subsurface scattering. In this paper, we present a simple analytic model that combines diffuse inter-reflection and isotropic subsurface scattering. Our approach extends the classical work in radiosity by including a subsurface scattering matrix that operates in conjunction with the traditional form factor matrix. This subsurface scattering matrix can be constructed using analytic, measurement-based or simulation-based models and can capture both homogeneous and heterogeneous translucencies. Using a fast iterative solution to radiosity, we demonstrate scene relighting and dynamically varying object translucencies at near interactive rates.
Cryogenic parallel, single phase flows: an analytical approach
NASA Astrophysics Data System (ADS)
Eichhorn, R.
2017-02-01
Managing the cryogenic flows inside a state-of-the-art accelerator cryomodule has become a demanding endeavour: In order to build highly efficient modules, all heat transfers are usually intercepted at various temperatures. For a multi-cavity module, operated at 1.8 K, this requires intercepts at 4 K and at 80 K at different locations with sometimes strongly varying heat loads which for simplicity reasons are operated in parallel. This contribution will describe an analytical approach, based on optimization theories.
MASS SPECTROMETRY-BASED METABOLOMICS
Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D.
2007-01-01
This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. PMID:16921475
Shiokawa, Yuka; Date, Yasuhiro; Kikuchi, Jun
2018-02-21
Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress in data mining methods for analysis of big data derived from chemical and biological systems. From this perspective, use of a general "linear" multivariate analysis alone limits interpretations due to "non-linear" variations in metabolic data from living organisms. Here we describe a kernel principal component analysis (KPCA)-incorporated analytical approach for extracting useful information from metabolic profiling data. To overcome the limitation of important variable (metabolite) determinations, we incorporated a random forest conditional variable importance measure into our KPCA-based analytical approach to demonstrate the relative importance of metabolites. Using a market basket analysis, hippurate, the most important variable detected in the importance measure, was associated with high levels of some vitamins and minerals present in foods eaten the previous day, suggesting a relationship between increased hippurate and intake of a wide variety of vegetables and fruits. Therefore, the KPCA-incorporated analytical approach described herein enabled us to capture input-output responses, and should be useful not only for metabolic profiling but also for profiling in other areas of biological and environmental systems.
NASA Astrophysics Data System (ADS)
Li, Zhao; Wang, Dazhi; Zheng, Di; Yu, Linxin
2017-10-01
Rotational permanent magnet eddy current couplers are promising devices for torque and speed transmission without any mechanical contact. In this study, flux-concentration disk-type permanent magnet eddy current couplers with double conductor rotor are investigated. Given the drawback of the accurate three-dimensional finite element method, this paper proposes a mixed two-dimensional analytical modeling approach. Based on this approach, the closed-form expressions of magnetic field, eddy current, electromagnetic force and torque for such devices are obtained. Finally, a three-dimensional finite element method is employed to validate the analytical results. Besides, a prototype is manufactured and tested for the torque-speed characteristic.
The Task-Based Approach in Language Teaching
ERIC Educational Resources Information Center
Sánchez, Aquilino
2004-01-01
The Task-Based Approach (TBA) has gained popularity in the field of language teaching since the last decade of the 20th Century and significant scholars have joined the discussion and increased the amount of analytical studies on the issue. Nevertheless experimental research is poor, and the tendency of some of the scholars is nowadays shifting…
A Corpus-Based Approach to Online Materials Development for Writing Research Articles
ERIC Educational Resources Information Center
Chang, Ching-Fen; Kuo, Chih-Hua
2011-01-01
There has been increasing interest in the possible applications of corpora to both linguistic research and pedagogy. This study takes a corpus-based, genre-analytic approach to discipline-specific materials development. Combining corpus analysis with genre analysis makes it possible to develop teaching materials that are not only authentic but…
Political Communication Research and the Uses and Gratifications Model: A Critique.
ERIC Educational Resources Information Center
Swanson, David L.
1979-01-01
Discusses the limited value of research based on the uses and gratifications approach, particularly in the area of political communication. The limitations arise from the approach's commitment to the variable analytic method. (JMF)
Ide, A H; Nogueira, J M F
2018-05-10
The present contribution aims to design new-generation bar adsorptive microextraction (BAμE) devices that promote an innovative and much better user-friendly analytical approach. The novel BAμE devices were lab-made prepared having smaller dimensions by using flexible nylon-based supports (7.5 × 1.0 mm) coated with convenient sorbents (≈ 0.5 mg). This novel advance allows effective microextraction and back-extraction ('only single liquid desorption step') stages as well as interfacing enhancement with the instrumental systems dedicated for routine analysis. To evaluate the achievements of these improvements, four antidepressant agents (bupropion, citalopram, amitriptyline and trazodone) were used as model compounds in aqueous media combined with liquid chromatography (LC) systems. By using an N-vinylpyrrolidone based-polymer phase good selectivity and efficiency were obtained. Assays performed on 25 mL spiked aqueous samples, yielded average recoveries in between 67.8 ± 12.4% (bupropion) and 88.3 ± 12.1% (citalopram), under optimized experimental conditions. The analytical performance also showed convenient precision (RSD < 12%) and detection limits (50 ng L -1 ), as well as linear dynamic ranges (160-2000 ng L -1 ) with suitable determination coefficients (r 2 > 0.9820). The application of the proposed analytical approach on biological fluids showed negligible matrix effects by using the standard addition methodology. From the data obtained, the new-generation BAμE devices presented herein provide an innovative and robust analytical cycle, are simple to prepare, cost-effective, user-friendly and compatible with the current LC autosampler systems. Furthermore, the novel devices were designed to be disposable and used together with negligible amounts of organic solvents (100 μL) during back-extraction, in compliance with the green analytical chemistry principles. In short, the new-generation BAμE devices showed to be an eco-user-friendly approach for trace analysis of priority compounds in biological fluids and a versatile alternative over other well-stablished sorption-based microextraction techniques. Copyright © 2018 Elsevier B.V. All rights reserved.
Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research
ERIC Educational Resources Information Center
He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne
2018-01-01
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Classifying Correlation Matrices into Relatively Homogeneous Subgroups: A Cluster Analytic Approach
ERIC Educational Resources Information Center
Cheung, Mike W.-L.; Chan, Wai
2005-01-01
Researchers are becoming interested in combining meta-analytic techniques and structural equation modeling to test theoretical models from a pool of studies. Most existing procedures are based on the assumption that all correlation matrices are homogeneous. Few studies have addressed what the next step should be when studies being analyzed are…
ERIC Educational Resources Information Center
Gao, Ruomei
2015-01-01
In a typical chemistry instrumentation laboratory, students learn analytical techniques through a well-developed procedure. Such an approach, however, does not engage students in a creative endeavor. To foster the intrinsic motivation of students' desire to learn, improve their confidence in self-directed learning activities and enhance their…
Geometrical enhancement of the electric field: Application of fractional calculus in nanoplasmonics
NASA Astrophysics Data System (ADS)
Baskin, E.; Iomin, A.
2011-12-01
We developed an analytical approach, for a wave propagation in metal-dielectric nanostructures in the quasi-static limit. This consideration establishes a link between fractional geometry of the nanostructure and fractional integro-differentiation. The method is based on fractional calculus and permits to obtain analytical expressions for the electric-field enhancement.
Significance Testing in Confirmatory Factor Analytic Models.
ERIC Educational Resources Information Center
Khattab, Ali-Maher; Hocevar, Dennis
Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…
NASA Astrophysics Data System (ADS)
Haritan, Idan; Moiseyev, Nimrod
2017-07-01
Resonances play a major role in a large variety of fields in physics and chemistry. Accordingly, there is a growing interest in methods designed to calculate them. Recently, Landau et al. proposed a new approach to analytically dilate a single eigenvalue from the stabilization graph into the complex plane. This approach, termed Resonances Via Padé (RVP), utilizes the Padé approximant and is based on a unique analysis of the stabilization graph. Yet, analytic continuation of eigenvalues from the stabilization graph into the complex plane is not a new idea. In 1975, Jordan suggested an analytic continuation method based on the branch point structure of the stabilization graph. The method was later modified by McCurdy and McNutt, and it is still being used today. We refer to this method as the Truncated Characteristic Polynomial (TCP) method. In this manuscript, we perform an in-depth comparison between the RVP and the TCP methods. We demonstrate that while both methods are important and complementary, the advantage of one method over the other is problem-dependent. Illustrative examples are provided in the manuscript.
Maier, Barbara; Vogeser, Michael
2013-04-01
Isotope dilution LC-MS/MS methods used in the clinical laboratory typically involve multi-point external calibration in each analytical series. Our aim was to test the hypothesis that determination of target analyte concentrations directly derived from the relation of the target analyte peak area to the peak area of a corresponding stable isotope labelled internal standard compound [direct isotope dilution analysis (DIDA)] may be not inferior to conventional external calibration with respect to accuracy and reproducibility. Quality control samples and human serum pools were analysed in a comparative validation protocol for cortisol as an exemplary analyte by LC-MS/MS. Accuracy and reproducibility were compared between quantification either involving a six-point external calibration function, or a result calculation merely based on peak area ratios of unlabelled and labelled analyte. Both quantification approaches resulted in similar accuracy and reproducibility. For specified analytes, reliable analyte quantification directly derived from the ratio of peak areas of labelled and unlabelled analyte without the need for a time consuming multi-point calibration series is possible. This DIDA approach is of considerable practical importance for the application of LC-MS/MS in the clinical laboratory where short turnaround times often have high priority.
McMillin, Gwendolyn A; Marin, Stephanie J; Johnson-Davis, Kamisha L; Lawlor, Bryan G; Strathmann, Frederick G
2015-02-01
The major objective of this research was to propose a simplified approach for the evaluation of medication adherence in chronic pain management patients, using liquid chromatography time-of-flight (TOF) mass spectrometry, performed in parallel with select homogeneous enzyme immunoassays (HEIAs). We called it a "hybrid" approach to urine drug testing. The hybrid approach was defined based on anticipated positivity rates, availability of commercial reagents for HEIAs, and assay performance, particularly analytical sensitivity and specificity for drug(s) of interest. Subsequent to implementation of the hybrid approach, time to result was compared with that observed with other urine drug testing approaches. Opioids, benzodiazepines, zolpidem, amphetamine-like stimulants, and methylphenidate metabolite were detected by TOF mass spectrometry to maximize specificity and sensitivity of these 37 drug analytes. Barbiturates, cannabinoid metabolite, carisoprodol, cocaine metabolite, ethyl glucuronide, methadone, phencyclidine, propoxyphene, and tramadol were detected by HEIAs that performed adequately and/or for which positivity rates were very low. Time to result was significantly reduced compared with the traditional approach. The hybrid approach to urine drug testing provides a simplified and analytically specific testing process that minimizes the need for secondary confirmation. Copyright© by the American Society for Clinical Pathology.
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
Yun, Changhong; Dashwood, Wan-Mohaiza; Kwong, Lawrence N; Gao, Song; Yin, Taijun; Ling, Qinglan; Singh, Rashim; Dashwood, Roderick H; Hu, Ming
2018-01-30
An accurate and reliable UPLC-MS/MS method is reported for the quantification of endogenous Prostaglandin E2 (PGE 2 ) in rat colonic mucosa and polyps. This method adopted the "surrogate analyte plus authentic bio-matrix" approach, using two different stable isotopic labeled analogs - PGE 2 -d9 as the surrogate analyte and PGE 2 -d4 as the internal standard. A quantitative standard curve was constructed with the surrogate analyte in colonic mucosa homogenate, and the method was successfully validated with the authentic bio-matrix. Concentrations of endogenous PGE 2 in both normal and inflammatory tissue homogenates were back-calculated based on the regression equation. Because of no endogenous interference on the surrogate analyte determination, the specificity was particularly good. By using authentic bio-matrix for validation, the matrix effect and exaction recovery are identically same for the quantitative standard curve and actual samples - this notably increased the assay accuracy. The method is easy, fast, robust and reliable for colon PGE 2 determination. This "surrogate analyte" approach was applied to measure the Pirc (an Apc-mutant rat kindred that models human FAP) mucosa and polyps PGE 2 , one of the strong biomarkers of colorectal cancer. A similar concept could be applied to endogenous biomarkers in other tissues. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Chiadamrong, N.; Piyathanavong, V.
2017-12-01
Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
Analytical and numerical treatment of drift-tearing modes in plasma slab
NASA Astrophysics Data System (ADS)
Mirnov, V. V.; Hegna, C. C.; Sovinec, C. R.; Howell, E. C.
2016-10-01
Two-fluid corrections to linear tearing modes includes 1) diamagnetic drifts that reduce the growth rate and 2) electron and ion decoupling on short scales that can lead to fast reconnection. We have recently developed an analytical model that includes effects 1) and 2) and important contribution from finite electron parallel thermal conduction. Both the tendencies 1) and 2) are confirmed by an approximate analytic dispersion relation that is derived using a perturbative approach of small ion-sound gyroradius ρs. This approach is only valid at the beginning of the transition from the collisional to semi-collisional regimes. Further analytical and numerical work is performed to cover the full interval of ρs connecting these two limiting cases. Growth rates are computed from analytic theory with a shooting method. They match the resistive MHD regime with the dispersion relations known at asymptotically large ion-sound gyroradius. A comparison between this analytical treatment and linear numerical simulations using the NIMROD code with cold ions and hot electrons in plasma slab is reported. The material is based on work supported by the U.S. DOE and NSF.
ERIC Educational Resources Information Center
Wang, Li
2012-01-01
The aim of this paper is to build a capability-based framework, drawing upon the strengths of other approaches, which is applicable to the complexity of the urban-rural divide in education in China. It starts with a brief introduction to the capability approach. This is followed by a discussion of how the rights-based approach and resource-based…
Collector modulation in high-voltage bipolar transistor in the saturation mode: Analytical approach
NASA Astrophysics Data System (ADS)
Dmitriev, A. P.; Gert, A. V.; Levinshtein, M. E.; Yuferev, V. S.
2018-04-01
A simple analytical model is developed, capable of replacing the numerical solution of a system of nonlinear partial differential equations by solving a simple algebraic equation when analyzing the collector resistance modulation of a bipolar transistor in the saturation mode. In this approach, the leakage of the base current into the emitter and the recombination of non-equilibrium carriers in the base are taken into account. The data obtained are in good agreement with the results of numerical calculations and make it possible to describe both the motion of the front of the minority carriers and the steady state distribution of minority carriers across the collector in the saturation mode.
NASA Astrophysics Data System (ADS)
Milic, Vladimir; Kasac, Josip; Novakovic, Branko
2015-10-01
This paper is concerned with ?-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone-Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for ?-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton's method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system.
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.
Synergistic relationships between Analytical Chemistry and written standards.
Valcárcel, Miguel; Lucena, Rafael
2013-07-25
This paper describes the mutual impact of Analytical Chemistry and several international written standards (norms and guides) related to knowledge management (CEN-CWA 14924:2004), social responsibility (ISO 26000:2010), management of occupational health and safety (OHSAS 18001/2), environmental management (ISO 14001:2004), quality management systems (ISO 9001:2008) and requirements of the competence of testing and calibration laboratories (ISO 17025:2004). The intensity of this impact, based on a two-way influence, is quite different depending on the standard considered. In any case, a new and fruitful approach to Analytical Chemistry based on these relationships can be derived. Copyright © 2013 Elsevier B.V. All rights reserved.
Achieving Cost Reduction Through Data Analytics.
Rocchio, Betty Jo
2016-10-01
The reimbursement structure of the US health care system is shifting from a volume-based system to a value-based system. Adopting a comprehensive data analytics platform has become important to health care facilities, in part to navigate this shift. Hospitals generate plenty of data, but actionable analytics are necessary to help personnel interpret and apply data to improve practice. Perioperative services is an important revenue-generating department for hospitals, and each perioperative service line requires a tailored approach to be successful in managing outcomes and controlling costs. Perioperative leaders need to prepare to use data analytics to reduce variation in supplies, labor, and overhead. Mercy, based in Chesterfield, Missouri, adopted a perioperative dashboard that helped perioperative leaders collaborate with surgeons and perioperative staff members to organize and analyze health care data, which ultimately resulted in significant cost savings. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.
Probabilistic evaluation of on-line checks in fault-tolerant multiprocessor systems
NASA Technical Reports Server (NTRS)
Nair, V. S. S.; Hoskote, Yatin V.; Abraham, Jacob A.
1992-01-01
The analysis of fault-tolerant multiprocessor systems that use concurrent error detection (CED) schemes is much more difficult than the analysis of conventional fault-tolerant architectures. Various analytical techniques have been proposed to evaluate CED schemes deterministically. However, these approaches are based on worst-case assumptions related to the failure of system components. Often, the evaluation results do not reflect the actual fault tolerance capabilities of the system. A probabilistic approach to evaluate the fault detecting and locating capabilities of on-line checks in a system is developed. The various probabilities associated with the checking schemes are identified and used in the framework of the matrix-based model. Based on these probabilistic matrices, estimates for the fault tolerance capabilities of various systems are derived analytically.
Comparison of Three Methods for Wind Turbine Capacity Factor Estimation
Ditkovich, Y.; Kuperman, A.
2014-01-01
Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first “quasiexact” approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second “analytic” approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third “approximate” approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation. PMID:24587755
Analytical and Computational Properties of Distributed Approaches to MDO
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia M.; Lewis, Robert Michael
2000-01-01
Historical evolution of engineering disciplines and the complexity of the MDO problem suggest that disciplinary autonomy is a desirable goal in formulating and solving MDO problems. We examine the notion of disciplinary autonomy and discuss the analytical properties of three approaches to formulating and solving MDO problems that achieve varying degrees of autonomy by distributing the problem along disciplinary lines. Two of the approaches-Optimization by Linear Decomposition and Collaborative Optimization-are based on bi-level optimization and reflect what we call a structural perspective. The third approach, Distributed Analysis Optimization, is a single-level approach that arises from what we call an algorithmic perspective. The main conclusion of the paper is that disciplinary autonomy may come at a price: in the bi-level approaches, the system-level constraints introduced to relax the interdisciplinary coupling and enable disciplinary autonomy can cause analytical and computational difficulties for optimization algorithms. The single-level alternative we discuss affords a more limited degree of autonomy than that of the bi-level approaches, but without the computational difficulties of the bi-level methods. Key Words: Autonomy, bi-level optimization, distributed optimization, multidisciplinary optimization, multilevel optimization, nonlinear programming, problem integration, system synthesis
Multi-country health surveys: are the analyses misleading?
Masood, Mohd; Reidpath, Daniel D
2014-05-01
The aim of this paper was to review the types of approaches currently utilized in the analysis of multi-country survey data, specifically focusing on design and modeling issues with a focus on analyses of significant multi-country surveys published in 2010. A systematic search strategy was used to identify the 10 multi-country surveys and the articles published from them in 2010. The surveys were selected to reflect diverse topics and foci; and provide an insight into analytic approaches across research themes. The search identified 159 articles appropriate for full text review and data extraction. The analyses adopted in the multi-country surveys can be broadly classified as: univariate/bivariate analyses, and multivariate/multivariable analyses. Multivariate/multivariable analyses may be further divided into design- and model-based analyses. Of the 159 articles reviewed, 129 articles used model-based analysis, 30 articles used design-based analyses. Similar patterns could be seen in all the individual surveys. While there is general agreement among survey statisticians that complex surveys are most appropriately analyzed using design-based analyses, most researchers continued to use the more common model-based approaches. Recent developments in design-based multi-level analysis may be one approach to include all the survey design characteristics. This is a relatively new area, however, and there remains statistical, as well as applied analytic research required. An important limitation of this study relates to the selection of the surveys used and the choice of year for the analysis, i.e., year 2010 only. There is, however, no strong reason to believe that analytic strategies have changed radically in the past few years, and 2010 provides a credible snapshot of current practice.
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.
Measurement-based reliability prediction methodology. M.S. Thesis
NASA Technical Reports Server (NTRS)
Linn, Linda Shen
1991-01-01
In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.
Career Decision Statuses among Portuguese Secondary School Students: A Cluster Analytical Approach
ERIC Educational Resources Information Center
Santos, Paulo Jorge; Ferreira, Joaquim Armando
2012-01-01
Career indecision is a complex phenomenon and an increasing number of authors have proposed that undecided individuals do not form a group with homogeneous characteristics. This study examines career decision statuses among a sample of 362 12th-grade Portuguese students. A cluster-analytical procedure, based on a battery of instruments designed to…
Taking the Edusemiotic Turn: A Body~Mind Approach to Education
ERIC Educational Resources Information Center
Semetsky, Inna
2014-01-01
Educational philosophy in English-speaking countries tends to be informed mainly by analytic philosophy common to Western thinking. A welcome alternative is provided by pragmatism in the tradition of Peirce, James and Dewey. Still, the habit of the so-called linguistic turn has a firm grip in terms of analytic philosophy based on the logic of…
A Comprehensive Analytical Solution of the Nonlinear Pendulum
ERIC Educational Resources Information Center
Ochs, Karlheinz
2011-01-01
In this paper, an analytical solution for the differential equation of the simple but nonlinear pendulum is derived. This solution is valid for any time and is not limited to any special initial instance or initial values. Moreover, this solution holds if the pendulum swings over or not. The method of approach is based on Jacobi elliptic functions…
ERIC Educational Resources Information Center
Schaal, David W.
2012-01-01
This article presents an introduction to "The Behavior-Analytic Origins of Constraint-Induced Movement Therapy: An Example of Behavioral Neurorehabilitation," by Edward Taub and his colleagues (Taub, 2012). Based on extensive experimentation with animal models of peripheral nerve injury, Taub and colleagues have created an approach to overcoming…
Integrating DNA strand displacement circuitry to the nonlinear hybridization chain reaction.
Zhang, Zhuo; Fan, Tsz Wing; Hsing, I-Ming
2017-02-23
Programmable and modular attributes of DNA molecules allow one to develop versatile sensing platforms that can be operated isothermally and enzyme-free. In this work, we present an approach to integrate upstream DNA strand displacement circuits that can be turned on by a sequence-specific microRNA analyte with a downstream nonlinear hybridization chain reaction for a cascading hyperbranched nucleic acid assembly. This system provides a two-step amplification strategy for highly sensitive detection of the miRNA analyte, conducive for multiplexed detection. Multiple miRNA analytes were tested with our integrated circuitry using the same downstream signal amplification setting, showing the decoupling of nonlinear self-assembly with the analyte sequence. Compared with the reported methods, our signal amplification approach provides an additional control module for higher-order DNA self-assembly and could be developed into a promising platform for the detection of critical nucleic-acid based biomarkers.
Satellite Orbit Under Influence of a Drag - Analytical Approach
NASA Astrophysics Data System (ADS)
Martinović, M. M.; Šegan, S. D.
2017-12-01
The report studies some changes in orbital elements of the artificial satellites of Earth under influence of atmospheric drag. In order to develop possibilities of applying the results in many future cases, an analytical interpretation of the orbital element perturbations is given via useful, but very long expressions. The development is based on the TD88 air density model, recently upgraded with some additional terms. Some expressions and formulae were developed by the computer algebra system Mathematica and tested in some hypothetical cases. The results have good agreement with iterative (numerical) approach.
Metabolomics of Genetically Modified Crops
Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia
2014-01-01
Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064
Analytical determination of thermal conductivity of W-UO2 and W-UN CERMET nuclear fuels
NASA Astrophysics Data System (ADS)
Webb, Jonathan A.; Charit, Indrajit
2012-08-01
The thermal conductivity of tungsten based CERMET fuels containing UO2 and UN fuel particles are determined as a function of particle geometry, stabilizer fraction and fuel-volume fraction, by using a combination of an analytical approach and experimental data collected from literature. Thermal conductivity is estimated using the Bruggeman-Fricke model. This study demonstrates that thermal conductivities of various CERMET fuels can be analytically predicted to values that are very close to the experimentally determined ones.
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.
Lagrangian based methods for coherent structure detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu; Peacock, Thomas, E-mail: tomp@mit.edu
There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other twomore » approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.« less
Mechanics of additively manufactured porous biomaterials based on the rhombicuboctahedron unit cell.
Hedayati, R; Sadighi, M; Mohammadi-Aghdam, M; Zadpoor, A A
2016-01-01
Thanks to recent developments in additive manufacturing techniques, it is now possible to fabricate porous biomaterials with arbitrarily complex micro-architectures. Micro-architectures of such biomaterials determine their physical and biological properties, meaning that one could potentially improve the performance of such biomaterials through rational design of micro-architecture. The relationship between the micro-architecture of porous biomaterials and their physical and biological properties has therefore received increasing attention recently. In this paper, we studied the mechanical properties of porous biomaterials made from a relatively unexplored unit cell, namely rhombicuboctahedron. We derived analytical relationships that relate the micro-architecture of such porous biomaterials, i.e. the dimensions of the rhombicuboctahedron unit cell, to their elastic modulus, Poisson's ratio, and yield stress. Finite element models were also developed to validate the analytical solutions. Analytical and numerical results were compared with experimental data from one of our recent studies. It was found that analytical solutions and numerical results show a very good agreement particularly for smaller values of apparent density. The elastic moduli predicted by analytical and numerical models were in very good agreement with experimental observations too. While in excellent agreement with each other, analytical and numerical models somewhat over-predicted the yield stress of the porous structures as compared to experimental data. As the ratio of the vertical struts to the inclined struts, α, approaches zero and infinity, the rhombicuboctahedron unit cell respectively approaches the octahedron (or truncated cube) and cube unit cells. For those limits, the analytical solutions presented here were found to approach the analytic solutions obtained for the octahedron, truncated cube, and cube unit cells, meaning that the presented solutions are generalizations of the analytical solutions obtained for several other types of porous biomaterials. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Appel, Marius; Lahn, Florian; Buytaert, Wouter; Pebesma, Edzer
2018-04-01
Earth observation (EO) datasets are commonly provided as collection of scenes, where individual scenes represent a temporal snapshot and cover a particular region on the Earth's surface. Using these data in complex spatiotemporal modeling becomes difficult as soon as data volumes exceed a certain capacity or analyses include many scenes, which may spatially overlap and may have been recorded at different dates. In order to facilitate analytics on large EO datasets, we combine and extend the geospatial data abstraction library (GDAL) and the array-based data management and analytics system SciDB. We present an approach to automatically convert collections of scenes to multidimensional arrays and use SciDB to scale computationally intensive analytics. We evaluate the approach in three study cases on national scale land use change monitoring with Landsat imagery, global empirical orthogonal function analysis of daily precipitation, and combining historical climate model projections with satellite-based observations. Results indicate that the approach can be used to represent various EO datasets and that analyses in SciDB scale well with available computational resources. To simplify analyses of higher-dimensional datasets as from climate model output, however, a generalization of the GDAL data model might be needed. All parts of this work have been implemented as open-source software and we discuss how this may facilitate open and reproducible EO analyses.
Teaching Demography to Undergraduates: A Pedagogical Dilemma.
ERIC Educational Resources Information Center
Abowitz, Deborah A.
1990-01-01
Describes a course based on the interdisciplinary approach to demography linked to environmental issues. Analytic and interpretive skills are an integral element in the study of population-related problems. Points out that the interdisciplinary approach maintains demographic literacy while analyzing population problems. (SLM)
On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation.
Yang, Harry; Novick, Steven; Burdick, Richard K
Analytical similarity is the foundation for demonstration of biosimilarity between a proposed product and a reference product. For this assessment, currently the U.S. Food and Drug Administration (FDA) recommends a tiered system in which quality attributes are categorized into three tiers commensurate with their risk and approaches of varying statistical rigor are subsequently used for the three-tier quality attributes. Key to the analyses of Tiers 1 and 2 quality attributes is the establishment of equivalence acceptance criterion and quality range. For particular licensure applications, the FDA has provided advice on statistical methods for demonstration of analytical similarity. For example, for Tier 1 assessment, an equivalence test can be used based on an equivalence margin of 1.5 σ R , where σ R is the reference product variability estimated by the sample standard deviation S R from a sample of reference lots. The quality range for demonstrating Tier 2 analytical similarity is of the form X̄ R ± K × σ R where the constant K is appropriately justified. To demonstrate Tier 2 analytical similarity, a large percentage (e.g., 90%) of test product must fall in the quality range. In this paper, through both theoretical derivations and simulations, we show that when the reference drug product lots are correlated, the sample standard deviation S R underestimates the true reference product variability σ R As a result, substituting S R for σ R in the Tier 1 equivalence acceptance criterion and the Tier 2 quality range inappropriately reduces the statistical power and the ability to declare analytical similarity. Also explored is the impact of correlation among drug product lots on Type I error rate and power. Three methods based on generalized pivotal quantities are introduced, and their performance is compared against a two-one-sided tests (TOST) approach. Finally, strategies to mitigate risk of correlation among the reference products lots are discussed. A biosimilar is a generic version of the original biological drug product. A key component of a biosimilar development is the demonstration of analytical similarity between the biosimilar and the reference product. Such demonstration relies on application of statistical methods to establish a similarity margin and appropriate test for equivalence between the two products. This paper discusses statistical issues with demonstration of analytical similarity and provides alternate approaches to potentially mitigate these problems. © PDA, Inc. 2016.
Safety and Suitability for Service Assessment Testing for Surface and Underwater Launched Munitions
2014-12-05
test efficiency that tend to associate the Analytical S3 Test Approach with large, complex munition systems and the Empirical S3 Test Approach with...the smaller, less complex munition systems . 8.1 ANALYTICAL S3 TEST APPROACH. The Analytical S3 test approach, as shown in Figure 3, evaluates...assets than the Analytical S3 Test approach to establish the safety margin of the system . This approach is generally applicable to small munitions
Standardization approaches in absolute quantitative proteomics with mass spectrometry.
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 elemental) proteomics is provided in this review. © 2017 Wiley Periodicals, Inc.
Napolitano, José G.; Gödecke, Tanja; Lankin, David C.; Jaki, Birgit U.; McAlpine, James B.; Chen, Shao-Nong; Pauli, Guido F.
2013-01-01
The development of analytical methods for parallel characterization of multiple phytoconstituents is essential to advance the quality control of herbal products. While chemical standardization is commonly carried out by targeted analysis using gas or liquid chromatography-based methods, more universal approaches based on quantitative 1H NMR (qHNMR) measurements are being used increasingly in the multi-targeted assessment of these complex mixtures. The present study describes the development of a 1D qHNMR-based method for simultaneous identification and quantification of green tea constituents. This approach utilizes computer-assisted 1H iterative Full Spin Analysis (HiFSA) and enables rapid profiling of seven catechins in commercial green tea extracts. The qHNMR results were cross-validated against quantitative profiles obtained with an orthogonal LC-MS/MS method. The relative strengths and weaknesses of both approaches are discussed, with special emphasis on the role of identical reference standards in qualitative and quantitative analyses. PMID:23870106
Odor Recognition vs. Classification in Artificial Olfaction
NASA Astrophysics Data System (ADS)
Raman, Baranidharan; Hertz, Joshua; Benkstein, Kurt; Semancik, Steve
2011-09-01
Most studies in chemical sensing have focused on the problem of precise identification of chemical species that were exposed during the training phase (the recognition problem). However, generalization of training to predict the chemical composition of untrained gases based on their similarity with analytes in the training set (the classification problem) has received very limited attention. These two analytical tasks pose conflicting constraints on the system. While correct recognition requires detection of molecular features that are unique to an analyte, generalization to untrained chemicals requires detection of features that are common across a desired class of analytes. A simple solution that addresses both issues simultaneously can be obtained from biological olfaction, where the odor class and identity information are decoupled and extracted individually over time. Mimicking this approach, we proposed a hierarchical scheme that allowed initial discrimination between broad chemical classes (e.g. contains oxygen) followed by finer refinements using additional data into sub-classes (e.g. ketones vs. alcohols) and, eventually, specific compositions (e.g. ethanol vs. methanol) [1]. We validated this approach using an array of temperature-controlled chemiresistors. We demonstrated that a small set of training analytes is sufficient to allow generalization to novel chemicals and that the scheme provides robust categorization despite aging. Here, we provide further characterization of this approach.
Capel, P.D.; Larson, S.J.
1995-01-01
Minimizing the loss of target organic chemicals from environmental water samples between the time of sample collection and isolation is important to the integrity of an investigation. During this sample holding time, there is a potential for analyte loss through volatilization from the water to the headspace, sorption to the walls and cap of the sample bottle; and transformation through biotic and/or abiotic reactions. This paper presents a chemodynamic-based, generalized approach to estimate the most probable loss processes for individual target organic chemicals. The basic premise is that the investigator must know which loss process(es) are important for a particular analyte, based on its chemodynamic properties, when choosing the appropriate method(s) to prevent loss.
Proactive Supply Chain Performance Management with Predictive Analytics
Stefanovic, Nenad
2014-01-01
Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605
Proactive supply chain performance management with predictive analytics.
Stefanovic, Nenad
2014-01-01
Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.
NASA Astrophysics Data System (ADS)
Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi
2017-07-01
The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.
Review on microfluidic paper-based analytical devices towards commercialisation.
Akyazi, Tugce; Basabe-Desmonts, Lourdes; Benito-Lopez, Fernando
2018-02-25
Paper-based analytical devices introduce an innovative platform technology for fluid handling and analysis, with wide range of applications, promoting low cost, ease of fabrication/operation and equipment independence. This review gives a general overview on the fabrication techniques reported to date, revealing and discussing their weak points as well as the newest approaches in order to overtake current mass production limitations and therefore commercialisation. Moreover, this review aims especially to highlight novel technologies appearing in literature for the effective handling and controlling of fluids. The lack of flow control is the main problem of paper-based analytical devices, which generates obstacles for marketing and slows down the transition of paper devices from the laboratory into the consumers' hands. Copyright © 2017 Elsevier B.V. All rights reserved.
Some contingencies of spelling
Lee, Vicki L.; Sanderson, Gwenda M.
1987-01-01
This paper presents some speculation about the contingencies that might select standard spellings. The speculation is based on a new development in the teaching of spelling—the process writing approach, which lets standard spellings emerge collateral to a high frequency of reading and writing. The paper discusses this approach, contrasts it with behavior-analytic research on spelling, and suggests some new directions for this latter research based on a behavioral interpretation of the process writing approach to spelling. PMID:22477529
A hybrid approach to near-optimal launch vehicle guidance
NASA Technical Reports Server (NTRS)
Leung, Martin S. K.; Calise, Anthony J.
1992-01-01
This paper evaluates a proposed hybrid analytical/numerical approach to launch-vehicle guidance for ascent to orbit injection. The feedback-guidance approach is based on a piecewise nearly analytic zero-order solution evaluated using a collocation method. The zero-order solution is then improved through a regular perturbation analysis, wherein the neglected dynamics are corrected in the first-order term. For real-time implementation, the guidance approach requires solving a set of small dimension nonlinear algebraic equations and performing quadrature. Assessment of performance and reliability are carried out through closed-loop simulation for a vertically launched 2-stage heavy-lift capacity vehicle to a low earth orbit. The solutions are compared with optimal solutions generated from a multiple shooting code. In the example the guidance approach delivers over 99.9 percent of optimal performance and terminal constraint accuracy.
Analytical Sociology: A Bungean Appreciation
NASA Astrophysics Data System (ADS)
Wan, Poe Yu-ze
2012-10-01
Analytical sociology, an intellectual project that has garnered considerable attention across a variety of disciplines in recent years, aims to explain complex social processes by dissecting them, accentuating their most important constituent parts, and constructing appropriate models to understand the emergence of what is observed. To achieve this goal, analytical sociologists demonstrate an unequivocal focus on the mechanism-based explanation grounded in action theory. In this article I attempt a critical appreciation of analytical sociology from the perspective of Mario Bunge's philosophical system, which I characterize as emergentist systemism. I submit that while the principles of analytical sociology and those of Bunge's approach share a lot in common, the latter brings to the fore the ontological status and explanatory importance of supra-individual actors (as concrete systems endowed with emergent causal powers) and macro-social mechanisms (as processes unfolding in and among social systems), and therefore it does not stipulate that every causal explanation of social facts has to include explicit references to individual-level actors and mechanisms. In this sense, Bunge's approach provides a reasonable middle course between the Scylla of sociological reification and the Charybdis of ontological individualism, and thus serves as an antidote to the untenable "strong program of microfoundations" to which some analytical sociologists are committed.
A General and Flexible Approach to Estimating the Social Relations Model Using Bayesian Methods
ERIC Educational Resources Information Center
Ludtke, Oliver; Robitzsch, Alexander; Kenny, David A.; Trautwein, Ulrich
2013-01-01
The social relations model (SRM) is a conceptual, methodological, and analytical approach that is widely used to examine dyadic behaviors and interpersonal perception within groups. This article introduces a general and flexible approach to estimating the parameters of the SRM that is based on Bayesian methods using Markov chain Monte Carlo…
Least Square Regression Method for Estimating Gas Concentration in an Electronic Nose System
Khalaf, Walaa; Pace, Calogero; Gaudioso, Manlio
2009-01-01
We describe an Electronic Nose (ENose) system which is able to identify the type of analyte and to estimate its concentration. The system consists of seven sensors, five of them being gas sensors (supplied with different heater voltage values), the remainder being a temperature and a humidity sensor, respectively. To identify a new analyte sample and then to estimate its concentration, we use both some machine learning techniques and the least square regression principle. In fact, we apply two different training models; the first one is based on the Support Vector Machine (SVM) approach and is aimed at teaching the system how to discriminate among different gases, while the second one uses the least squares regression approach to predict the concentration of each type of analyte. PMID:22573980
Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.
Rochau, U; Jahn, B; Qerimi, V; Burger, E A; Kurzthaler, C; Kluibenschaedl, M; Willenbacher, E; Gastl, G; Willenbacher, W; Siebert, U
2015-05-01
The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM). We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures. Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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
A Generalized Pivotal Quantity Approach to Analytical Method Validation Based on Total Error.
Yang, Harry; Zhang, Jianchun
2015-01-01
The primary purpose of method validation is to demonstrate that the method is fit for its intended use. Traditionally, an analytical method is deemed valid if its performance characteristics such as accuracy and precision are shown to meet prespecified acceptance criteria. However, these acceptance criteria are not directly related to the method's intended purpose, which is usually a gurantee that a high percentage of the test results of future samples will be close to their true values. Alternate "fit for purpose" acceptance criteria based on the concept of total error have been increasingly used. Such criteria allow for assessing method validity, taking into account the relationship between accuracy and precision. Although several statistical test methods have been proposed in literature to test the "fit for purpose" hypothesis, the majority of the methods are not designed to protect the risk of accepting unsuitable methods, thus having the potential to cause uncontrolled consumer's risk. In this paper, we propose a test method based on generalized pivotal quantity inference. Through simulation studies, the performance of the method is compared to five existing approaches. The results show that both the new method and the method based on β-content tolerance interval with a confidence level of 90%, hereafter referred to as the β-content (0.9) method, control Type I error and thus consumer's risk, while the other existing methods do not. It is further demonstrated that the generalized pivotal quantity method is less conservative than the β-content (0.9) method when the analytical methods are biased, whereas it is more conservative when the analytical methods are unbiased. Therefore, selection of either the generalized pivotal quantity or β-content (0.9) method for an analytical method validation depends on the accuracy of the analytical method. It is also shown that the generalized pivotal quantity method has better asymptotic properties than all of the current methods. Analytical methods are often used to ensure safety, efficacy, and quality of medicinal products. According to government regulations and regulatory guidelines, these methods need to be validated through well-designed studies to minimize the risk of accepting unsuitable methods. This article describes a novel statistical test for analytical method validation, which provides better protection for the risk of accepting unsuitable analytical methods. © PDA, Inc. 2015.
Approaching the Limit in Atomic Spectrochemical Analysis.
ERIC Educational Resources Information Center
Hieftje, Gary M.
1982-01-01
To assess the ability of current analytical methods to approach the single-atom detection level, theoretical and experimentally determined detection levels are presented for several chemical elements. A comparison of these methods shows that the most sensitive atomic spectrochemical technique currently available is based on emission from…
ERIC Educational Resources Information Center
Huijsmans, Roy
2012-01-01
Based on fieldwork material from Lao People's Democratic Republic, this paper introduces an analytical framework that transcends compartmentalized approaches towards migration involving young people. The notions of fluid and institutionalized forms of migration illuminate key differences and commonalities in the relational fabric underpinning…
Hierarchical analytical and simulation modelling of human-machine systems with interference
NASA Astrophysics Data System (ADS)
Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.
2017-01-01
The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.
Ahmad, Rafiq; Tripathy, Nirmalya; Park, Jin-Ho; Hahn, Yoon-Bong
2015-08-04
We report a novel straightforward approach for simultaneous and highly-selective detection of multi-analytes (i.e. glucose, cholesterol and urea) using an integrated field-effect transistor (i-FET) array biosensor without any interference in each sensor response. Compared to analytically-measured data, performance of the ZnO nanorod based i-FET array biosensor is found to be highly reliable for rapid detection of multi-analytes in mice blood, and serum and blood samples of diabetic dogs.
Nanoporous membranes enable concentration and transport in fully wet paper-based assays.
Gong, Max M; Zhang, Pei; MacDonald, Brendan D; Sinton, David
2014-08-19
Low-cost paper-based assays are emerging as the platform for diagnostics worldwide. Paper does not, however, readily enable advanced functionality required for complex diagnostics, such as analyte concentration and controlled analyte transport. That is, after the initial wetting, no further analyte manipulation is possible. Here, we demonstrate active concentration and transport of analytes in fully wet paper-based assays by leveraging nanoporous material (mean pore diameter ≈ 4 nm) and ion concentration polarization. Two classes of devices are developed, an external stamp-like device with the nanoporous material separate from the paper-based assay, and an in-paper device patterned with the nanoporous material. Experimental results demonstrate up to 40-fold concentration of a fluorescent tracer in fully wet paper, and directional transport of the tracer over centimeters with efficiencies up to 96%. In-paper devices are applied to concentrate protein and colored dye, extending their limits of detection from ∼10 to ∼2 pmol/mL and from ∼40 to ∼10 μM, respectively. This approach is demonstrated in nitrocellulose membrane as well as paper, and the added cost of the nanoporous material is very low at ∼0.015 USD per device. The result is a major advance in analyte concentration and manipulation for the growing field of low-cost paper-based assays.
ERIC Educational Resources Information Center
Bierschenk, Bernhard
In this study, the Kantian schema has been applied to natural language expression. The novelty of the approach concerns the way in which the Kantian schema interrelates the analytic with the synthetic mode in the construction of the presented formalism. The main thesis is based on the premise that the synthetic, in contrast to the analytic,…
ERIC Educational Resources Information Center
Monroy, Carlos; Rangel, Virginia Snodgrass; Whitaker, Reid
2014-01-01
In this paper, we discuss a scalable approach for integrating learning analytics into an online K-12 science curriculum. A description of the curriculum and the underlying pedagogical framework is followed by a discussion of the challenges to be tackled as part of this integration. We include examples of data visualization based on teacher usage…
Dual metal gate tunneling field effect transistors based on MOSFETs: A 2-D analytical approach
NASA Astrophysics Data System (ADS)
Ramezani, Zeinab; Orouji, Ali A.
2018-01-01
A novel 2-D analytical drain current model of novel Dual Metal Gate Tunnel Field Effect Transistors Based on MOSFETs (DMG-TFET) is presented in this paper. The proposed Tunneling FET is extracted from a MOSFET structure by employing an additional electrode in the source region with an appropriate work function to induce holes in the N+ source region and hence makes it as a P+ source region. The electric field is derived which is utilized to extract the expression of the drain current by analytically integrating the band to band tunneling generation rate in the tunneling region based on the potential profile by solving the Poisson's equation. Through this model, the effects of the thin film thickness and gate voltage on the potential, the electric field, and the effects of the thin film thickness on the tunneling current can be studied. To validate our present model we use SILVACO ATLAS device simulator and the analytical results have been compared with it and found a good agreement.
Hedayati, R; Sadighi, M; Mohammadi-Aghdam, M; Zadpoor, A A
2016-03-01
Additive manufacturing (AM) has enabled fabrication of open-cell porous biomaterials based on repeating unit cells. The micro-architecture of the porous biomaterials and, thus, their physical properties could then be precisely controlled. Due to their many favorable properties, porous biomaterials manufactured using AM are considered as promising candidates for bone substitution as well as for several other applications in orthopedic surgery. The mechanical properties of such porous structures including static and fatigue properties are shown to be strongly dependent on the type of the repeating unit cell based on which the porous biomaterial is built. In this paper, we study the mechanical properties of porous biomaterials made from a relatively new unit cell, namely truncated cube. We present analytical solutions that relate the dimensions of the repeating unit cell to the elastic modulus, Poisson's ratio, yield stress, and buckling load of those porous structures. We also performed finite element modeling to predict the mechanical properties of the porous structures. The analytical solution and computational results were found to be in agreement with each other. The mechanical properties estimated using both the analytical and computational techniques were somewhat higher than the experimental data reported in one of our recent studies on selective laser melted Ti-6Al-4V porous biomaterials. In addition to porosity, the elastic modulus and Poisson's ratio of the porous structures were found to be strongly dependent on the ratio of the length of the inclined struts to that of the uninclined (i.e. vertical or horizontal) struts, α, in the truncated cube unit cell. The geometry of the truncated cube unit cell approaches the octahedral and cube unit cells when α respectively approaches zero and infinity. Consistent with those geometrical observations, the analytical solutions presented in this study approached those of the octahedral and cube unit cells when α approached respectively 0 and infinity. Copyright © 2015 Elsevier B.V. All rights reserved.
Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.
2013-01-01
While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185
Qualitative research in healthcare: an introduction to grounded theory using thematic analysis.
Chapman, A L; Hadfield, M; Chapman, C J
2015-01-01
In today's NHS, qualitative research is increasingly important as a method of assessing and improving quality of care. Grounded theory has developed as an analytical approach to qualitative data over the last 40 years. It is primarily an inductive process whereby theoretical insights are generated from data, in contrast to deductive research where theoretical hypotheses are tested via data collection. Grounded theory has been one of the main contributors to the acceptance of qualitative methods in a wide range of applied social sciences. The influence of grounded theory as an approach is, in part, based on its provision of an explicit framework for analysis and theory generation. Furthermore the stress upon grounding research in the reality of participants has also given it credence in healthcare research. As with all analytical approaches, grounded theory has drawbacks and limitations. It is important to have an understanding of these in order to assess the applicability of this approach to healthcare research. In this review we outline the principles of grounded theory, and focus on thematic analysis as the analytical approach used most frequently in grounded theory studies, with the aim of providing clinicians with the skills to critically review studies using this methodology.
Agut, C; Caron, A; Giordano, C; Hoffman, D; Ségalini, A
2011-09-10
In 2001, a multidisciplinary team made of analytical scientists and statisticians at Sanofi-aventis has published a methodology which has governed, from that time, the transfers from R&D sites to Manufacturing sites of the release monographs. This article provides an overview of the recent adaptations brought to this original methodology taking advantage of our experience and the new regulatory framework, and, in particular, the risk management perspective introduced by ICH Q9. Although some alternate strategies have been introduced in our practices, the comparative testing one, based equivalence testing as statistical approach, remains the standard for assays lying on very critical quality attributes. This is conducted with the concern to control the most important consumer's risk involved at two levels in analytical decisions in the frame of transfer studies: risk, for the receiving laboratory, to take poor release decisions with the analytical method and risk, for the sending laboratory, to accredit such a receiving laboratory on account of its insufficient performances with the method. Among the enhancements to the comparative studies, the manuscript presents the process settled within our company for a better integration of the transfer study into the method life-cycle, just as proposals of generic acceptance criteria and designs for assay and related substances methods. While maintaining rigor and selectivity of the original approach, these improvements tend towards an increased efficiency in the transfer operations. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Schnase, J. L.; Duffy, D. Q.; McInerney, M. A.; Tamkin, G. S.; Thompson, J. H.; Gill, R.; Grieg, C. M.
2012-12-01
MERRA Analytic Services (MERRA/AS) is a cyberinfrastructure resource for developing and evaluating a new generation of climate data analysis capabilities. MERRA/AS supports OBS4MIP activities by reducing the time spent in the preparation of Modern Era Retrospective-Analysis for Research and Applications (MERRA) data used in data-model intercomparison. It also provides a testbed for experimental development of high-performance analytics. MERRA/AS is a cloud-based service built around the Virtual Climate Data Server (vCDS) technology that is currently used by the NASA Center for Climate Simulation (NCCS) to deliver Intergovernmental Panel on Climate Change (IPCC) data to the Earth System Grid Federation (ESGF). Crucial to its effectiveness, MERRA/AS's servers will use a workflow-generated realizable object capability to perform analyses over the MERRA data using the MapReduce approach to parallel storage-based computation. The results produced by these operations will be stored by the vCDS, which will also be able to host code sets for those who wish to explore the use of MapReduce for more advanced analytics. While the work described here will focus on the MERRA collection, these technologies can be used to publish other reanalysis, observational, and ancillary OBS4MIP data to ESGF and, importantly, offer an architectural approach to climate data services that can be generalized to applications and customers beyond the traditional climate research community. In this presentation, we describe our approach, experiences, lessons learned,and plans for the future.; (A) MERRA/AS software stack. (B) Example MERRA/AS interfaces.
Evaluation of the Current Status of the Combinatorial Approach for the Study of Phase Diagrams
Wong-Ng, W.
2012-01-01
This paper provides an evaluation of the effectiveness of using the high throughput combinatorial approach for preparing phase diagrams of thin film and bulk materials. Our evaluation is based primarily on examples of combinatorial phase diagrams that have been reported in the literature as well as based on our own laboratory experiments. Various factors that affect the construction of these phase diagrams are examined. Instrumentation and analytical approaches needed to improve data acquisition and data analysis are summarized. PMID:26900530
Petersen, Per Hyltoft; Sandberg, Sverre; Fraser, Callum G
2011-04-01
The Stockholm conference held in 1999 on "Strategies to set global analytical quality specifications (AQS) in laboratory medicine" reached a consensus and advocated the ubiquitous application of a hierarchical structure of approaches to setting AQS. This approach has been widely used over the last decade, although several issues remain unanswered. A number of new suggestions have been recently proposed for setting AQS. One of these recommendations is described by Haeckel and Wosniok in this issue of Clinical Chemistry and Laboratory Medicine. Their concept is to estimate the increase in false-positive results using conventional population-based reference intervals, the delta false-positive rate due to analytical imprecision and bias, and relate the results directly to the current analytical quality attained. Thus, the actual estimates in the laboratory for imprecision and bias are compared to the AQS. These values are classified in a ranking system according to the closeness to the AQS, and this combination is the new idea of the proposal. Other new ideas have been proposed recently. We wait, with great interest, as should others, to see if these newer approaches become widely used and worthy of incorporation into the hierarchy.
NASA Astrophysics Data System (ADS)
Kiyono, Ken; Tsujimoto, Yutaka
2016-07-01
We develop a general framework to study the time and frequency domain characteristics of detrending-operation-based scaling analysis methods, such as detrended fluctuation analysis (DFA) and detrending moving average (DMA) analysis. In this framework, using either the time or frequency domain approach, the frequency responses of detrending operations are calculated analytically. Although the frequency domain approach based on conventional linear analysis techniques is only applicable to linear detrending operations, the time domain approach presented here is applicable to both linear and nonlinear detrending operations. Furthermore, using the relationship between the time and frequency domain representations of the frequency responses, the frequency domain characteristics of nonlinear detrending operations can be obtained. Based on the calculated frequency responses, it is possible to establish a direct connection between the root-mean-square deviation of the detrending-operation-based scaling analysis and the power spectrum for linear stochastic processes. Here, by applying our methods to DFA and DMA, including higher-order cases, exact frequency responses are calculated. In addition, we analytically investigate the cutoff frequencies of DFA and DMA detrending operations and show that these frequencies are not optimally adjusted to coincide with the corresponding time scale.
Kiyono, Ken; Tsujimoto, Yutaka
2016-07-01
We develop a general framework to study the time and frequency domain characteristics of detrending-operation-based scaling analysis methods, such as detrended fluctuation analysis (DFA) and detrending moving average (DMA) analysis. In this framework, using either the time or frequency domain approach, the frequency responses of detrending operations are calculated analytically. Although the frequency domain approach based on conventional linear analysis techniques is only applicable to linear detrending operations, the time domain approach presented here is applicable to both linear and nonlinear detrending operations. Furthermore, using the relationship between the time and frequency domain representations of the frequency responses, the frequency domain characteristics of nonlinear detrending operations can be obtained. Based on the calculated frequency responses, it is possible to establish a direct connection between the root-mean-square deviation of the detrending-operation-based scaling analysis and the power spectrum for linear stochastic processes. Here, by applying our methods to DFA and DMA, including higher-order cases, exact frequency responses are calculated. In addition, we analytically investigate the cutoff frequencies of DFA and DMA detrending operations and show that these frequencies are not optimally adjusted to coincide with the corresponding time scale.
NASA Astrophysics Data System (ADS)
Sun, Xiaohang; Lee, Hoon Joo; Michielsen, Stephen; Wilusz, Eugene
2018-05-01
Although profiles of axisymmetric capillary bridges between two cylindrical fibers have been extensively studied, little research has been reported on capillary bridges under external forces such as the gravitational force. This is because external forces add significant complications to the Laplace-Young equation, making it difficult to predict drop profiles based on analytical approaches. In this paper, simulations of capillary bridges between two vertically stacked cylindrical fibers with gravitational effect taken into consideration are studied. The asymmetrical structure of capillary bridges that are hard to predict based on analytical approaches was studied via a numerical approach based on Surface Evolver (SE). The axial and the circumferential spreading of liquids on two identical fibers in the presence of gravitational effects are predicted to determine when the gravitational effects are significant or can be neglected. The effect of liquid volume, equilibrium contact angle, the distance between two fibers and fiber radii. The simulation results were verified by comparing them with experimental measurements. Based on SE simulations, curves representing the spreading of capillary bridges along the two cylindrical fibers were obtained. The gravitational effect was scaled based on the difference of the spreading on upper and lower fibers.
Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms.
Goh, Wilson Wen Bin; Wong, Limsoon
2016-09-02
Despite advances in proteomic technologies, idiosyncratic data issues, for example, incomplete coverage and inconsistency, resulting in large data holes, persist. Moreover, because of naïve reliance on statistical testing and its accompanying p values, differential protein signatures identified from such proteomics data have little diagnostic power. Thus, deploying conventional analytics on proteomics data is insufficient for identifying novel drug targets or precise yet sensitive biomarkers. Complex-based analysis is a new analytical approach that has potential to resolve these issues but requires formalization. We categorize complex-based analysis into five method classes or paradigms and propose an even-handed yet comprehensive evaluation rubric based on both simulated and real data. The first four paradigms are well represented in the literature. The fifth and newest paradigm, the network-paired (NP) paradigm, represented by a method called Extremely Small SubNET (ESSNET), dominates in precision-recall and reproducibility, maintains strong performance in small sample sizes, and sensitively detects low-abundance complexes. In contrast, the commonly used over-representation analysis (ORA) and direct-group (DG) test paradigms maintain good overall precision but have severe reproducibility issues. The other two paradigms considered here are the hit-rate and rank-based network analysis paradigms; both of these have good precision-recall and reproducibility, but they do not consider low-abundance complexes. Therefore, given its strong performance, NP/ESSNET may prove to be a useful approach for improving the analytical resolution of proteomics data. Additionally, given its stability, it may also be a powerful new approach toward functional enrichment tests, much like its ORA and DG counterparts.
Teaching Trends in Virtual Education: An Interpretative Approach
ERIC Educational Resources Information Center
Pando, Victor F.
2018-01-01
Based on the theoretical context of discussions about teaching trends in virtual education, particularly for higher education, this research develops an interpretation of some of these trends, resizing what was registered about it by other authors. To that end, a documentary study with an interpretative-analytical approach was carried out. The…
When ICT Meets Schools: Differentiation, Complexity and Adaptability
ERIC Educational Resources Information Center
Tubin, Dorit
2007-01-01
Purpose: The purpose of this study is to explore the interaction between information communication technology (ICT) and the school's organizational structure, and propose an analytical model based both on Luhmann's system theory and empirical findings. Design/methodology/approach: The approach of building a theory from a case study research along…
A Graphical Approach to Teaching Amplifier Design at the Undergraduate Level
ERIC Educational Resources Information Center
Assaad, R. S.; Silva-Martinez, J.
2009-01-01
Current methods of teaching basic amplifier design at the undergraduate level need further development to match today's technological advances. The general class approach to amplifier design is analytical and heavily based on mathematical manipulations. However, the students mathematical abilities are generally modest, creating a void in which…
NASA Astrophysics Data System (ADS)
Zhong, XiaoXu; Liao, ShiJun
2018-01-01
Analytic approximations of the Von Kármán's plate equations in integral form for a circular plate under external uniform pressure to arbitrary magnitude are successfully obtained by means of the homotopy analysis method (HAM), an analytic approximation technique for highly nonlinear problems. Two HAM-based approaches are proposed for either a given external uniform pressure Q or a given central deflection, respectively. Both of them are valid for uniform pressure to arbitrary magnitude by choosing proper values of the so-called convergence-control parameters c 1 and c 2 in the frame of the HAM. Besides, it is found that the HAM-based iteration approaches generally converge much faster than the interpolation iterative method. Furthermore, we prove that the interpolation iterative method is a special case of the first-order HAM iteration approach for a given external uniform pressure Q when c 1 = - θ and c 2 = -1, where θ denotes the interpolation iterative parameter. Therefore, according to the convergence theorem of Zheng and Zhou about the interpolation iterative method, the HAM-based approaches are valid for uniform pressure to arbitrary magnitude at least in the special case c 1 = - θ and c 2 = -1. In addition, we prove that the HAM approach for the Von Kármán's plate equations in differential form is just a special case of the HAM for the Von Kármán's plate equations in integral form mentioned in this paper. All of these illustrate the validity and great potential of the HAM for highly nonlinear problems, and its superiority over perturbation techniques.
NASA Astrophysics Data System (ADS)
Bescond, Marc; Li, Changsheng; Mera, Hector; Cavassilas, Nicolas; Lannoo, Michel
2013-10-01
We present a one-shot current-conserving approach to model the influence of electron-phonon scattering in nano-transistors using the non-equilibrium Green's function formalism. The approach is based on the lowest order approximation (LOA) to the current and its simplest analytic continuation (LOA+AC). By means of a scaling argument, we show how both LOA and LOA+AC can be easily obtained from the first iteration of the usual self-consistent Born approximation (SCBA) algorithm. Both LOA and LOA+AC are then applied to model n-type silicon nanowire field-effect-transistors and are compared to SCBA current characteristics. In this system, the LOA fails to describe electron-phonon scattering, mainly because of the interactions with acoustic phonons at the band edges. In contrast, the LOA+AC still well approximates the SCBA current characteristics, thus demonstrating the power of analytic continuation techniques. The limits of validity of LOA+AC are also discussed, and more sophisticated and general analytic continuation techniques are suggested for more demanding cases.
Managing knowledge business intelligence: A cognitive analytic approach
NASA Astrophysics Data System (ADS)
Surbakti, Herison; Ta'a, Azman
2017-10-01
The purpose of this paper is to identify and analyze integration of Knowledge Management (KM) and Business Intelligence (BI) in order to achieve competitive edge in context of intellectual capital. Methodology includes review of literatures and analyzes the interviews data from managers in corporate sector and models established by different authors. BI technologies have strong association with process of KM for attaining competitive advantage. KM have strong influence from human and social factors and turn them to the most valuable assets with efficient system run under BI tactics and technologies. However, the term of predictive analytics is based on the field of BI. Extracting tacit knowledge is a big challenge to be used as a new source for BI to use in analyzing. The advanced approach of the analytic methods that address the diversity of data corpus - structured and unstructured - required a cognitive approach to provide estimative results and to yield actionable descriptive, predictive and prescriptive results. This is a big challenge nowadays, and this paper aims to elaborate detail in this initial work.
NASA Astrophysics Data System (ADS)
Krishnan, Karthik; Reddy, Kasireddy V.; Ajani, Bhavya; Yalavarthy, Phaneendra K.
2017-02-01
CT and MR perfusion weighted imaging (PWI) enable quantification of perfusion parameters in stroke studies. These parameters are calculated from the residual impulse response function (IRF) based on a physiological model for tissue perfusion. The standard approach for estimating the IRF is deconvolution using oscillatory-limited singular value decomposition (oSVD) or Frequency Domain Deconvolution (FDD). FDD is widely recognized as the fastest approach currently available for deconvolution of CT Perfusion/MR PWI. In this work, three faster methods are proposed. The first is a direct (model based) crude approximation to the final perfusion quantities (Blood flow, Blood volume, Mean Transit Time and Delay) using the Welch-Satterthwaite approximation for gamma fitted concentration time curves (CTC). The second method is a fast accurate deconvolution method, we call Analytical Fourier Filtering (AFF). The third is another fast accurate deconvolution technique using Showalter's method, we call Analytical Showalter's Spectral Filtering (ASSF). Through systematic evaluation on phantom and clinical data, the proposed methods are shown to be computationally more than twice as fast as FDD. The two deconvolution based methods, AFF and ASSF, are also shown to be quantitatively accurate compared to FDD and oSVD.
Strengthening of reinforced concrete beams with basalt-based FRP sheets: An analytical assessment
NASA Astrophysics Data System (ADS)
Nerilli, Francesca; Vairo, Giuseppe
2016-06-01
In this paper the effectiveness of the flexural strengthening of RC beams through basalt fiber-reinforced sheets is investigated. The non-linear flexural response of RC beams strengthened with FRP composites applied at the traction side is described via an analytical formulation. Validation results and some comparative analyses confirm soundness and consistency of the proposed approach, and highlight the good mechanical performances (in terms of strength and ductility enhancement of the beam) produced by basalt-based reinforcements in comparison with traditional glass or carbon FRPs.
Flight simulator fidelity assessment in a rotorcraft lateral translation maneuver
NASA Technical Reports Server (NTRS)
Hess, R. A.; Malsbury, T.; Atencio, A., Jr.
1992-01-01
A model-based methodology for assessing flight simulator fidelity in closed-loop fashion is exercised in analyzing a rotorcraft low-altitude maneuver for which flight test and simulation results were available. The addition of a handling qualities sensitivity function to a previously developed model-based assessment criteria allows an analytical comparison of both performance and handling qualities between simulation and flight test. Model predictions regarding the existence of simulator fidelity problems are corroborated by experiment. The modeling approach is used to assess analytically the effects of modifying simulator characteristics on simulator fidelity.
Strengthening of reinforced concrete beams with basalt-based FRP sheets: An analytical assessment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nerilli, Francesca; Vairo, Giuseppe
2016-06-08
In this paper the effectiveness of the flexural strengthening of RC beams through basalt fiber-reinforced sheets is investigated. The non-linear flexural response of RC beams strengthened with FRP composites applied at the traction side is described via an analytical formulation. Validation results and some comparative analyses confirm soundness and consistency of the proposed approach, and highlight the good mechanical performances (in terms of strength and ductility enhancement of the beam) produced by basalt-based reinforcements in comparison with traditional glass or carbon FRPs.
Developing students’ ideas about lens imaging: teaching experiments with an image-based approach
NASA Astrophysics Data System (ADS)
Grusche, Sascha
2017-07-01
Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists’ analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students’ ideas, teaching experiments are performed and evaluated using qualitative content analysis. Some of the students’ ideas have not been reported before, namely those related to blurry lens images, and those developed by the proposed teaching approach. To describe learning pathways systematically, a conception-versus-time coordinate system is introduced, specifying how teaching actions help students advance toward a scientific understanding.
Tanaka, Shiro; Matsuyama, Yutaka; Ohashi, Yasuo
2017-08-30
Increasing attention has been focused on the use and validation of surrogate endpoints in cancer clinical trials. Previous literature on validation of surrogate endpoints are classified into four approaches: the proportion explained approach; the indirect effects approach; the meta-analytic approach; and the principal stratification approach. The mainstream in cancer research has seen the application of a meta-analytic approach. However, VanderWeele (2013) showed that all four of these approaches potentially suffer from the surrogate paradox. It was also shown that, if a principal surrogate satisfies additional criteria called one-sided average causal sufficiency, the surrogate cannot exhibit a surrogate paradox. Here, we propose a method for estimating principal effects under a monotonicity assumption. Specifically, we consider cancer clinical trials which compare a binary surrogate endpoint and a time-to-event clinical endpoint under two naturally ordered treatments (e.g. combined therapy vs. monotherapy). Estimation based on a mean score estimating equation will be implemented by the expectation-maximization algorithm. We will also apply the proposed method as well as other surrogacy criteria to evaluate the surrogacy of prostate-specific antigen using data from a phase III advanced prostate cancer trial, clarifying the complementary roles of both the principal stratification and meta-analytic approaches in the evaluation of surrogate endpoints in cancer. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
General Analytical Schemes for the Characterization of Pectin-Based Edible Gelled Systems
Haghighi, Maryam; Rezaei, Karamatollah
2012-01-01
Pectin-based gelled systems have gained increasing attention for the design of newly developed food products. For this reason, the characterization of such formulas is a necessity in order to present scientific data and to introduce an appropriate finished product to the industry. Various analytical techniques are available for the evaluation of the systems formulated on the basis of pectin and the designed gel. In this paper, general analytical approaches for the characterization of pectin-based gelled systems were categorized into several subsections including physicochemical analysis, visual observation, textural/rheological measurement, microstructural image characterization, and psychorheological evaluation. Three-dimensional trials to assess correlations among microstructure, texture, and taste were also discussed. Practical examples of advanced objective techniques including experimental setups for small and large deformation rheological measurements and microstructural image analysis were presented in more details. PMID:22645484
NASA Astrophysics Data System (ADS)
Wright, D. J.; Raad, M.; Hoel, E.; Park, M.; Mollenkopf, A.; Trujillo, R.
2016-12-01
Introduced is a new approach for processing spatiotemporal big data by leveraging distributed analytics and storage. A suite of temporally-aware analysis tools summarizes data nearby or within variable windows, aggregates points (e.g., for various sensor observations or vessel positions), reconstructs time-enabled points into tracks (e.g., for mapping and visualizing storm tracks), joins features (e.g., to find associations between features based on attributes, spatial relationships, temporal relationships or all three simultaneously), calculates point densities, finds hot spots (e.g., in species distributions), and creates space-time slices and cubes (e.g., in microweather applications with temperature, humidity, and pressure, or within human mobility studies). These "feature geo analytics" tools run in both batch and streaming spatial analysis mode as distributed computations across a cluster of servers on typical "big" data sets, where static data exist in traditional geospatial formats (e.g., shapefile) locally on a disk or file share, attached as static spatiotemporal big data stores, or streamed in near-real-time. In other words, the approach registers large datasets or data stores with ArcGIS Server, then distributes analysis across a cluster of machines for parallel processing. Several brief use cases will be highlighted based on a 16-node server cluster at 14 Gb RAM per node, allowing, for example, the buffering of over 8 million points or thousands of polygons in 1 minute. The approach is "hybrid" in that ArcGIS Server integrates open-source big data frameworks such as Apache Hadoop and Apache Spark on the cluster in order to run the analytics. In addition, the user may devise and connect custom open-source interfaces and tools developed in Python or Python Notebooks; the common denominator being the familiar REST API.
NASA Astrophysics Data System (ADS)
Bervillier, C.; Boisseau, B.; Giacomini, H.
2008-02-01
The relation between the Wilson-Polchinski and the Litim optimized ERGEs in the local potential approximation is studied with high accuracy using two different analytical approaches based on a field expansion: a recently proposed genuine analytical approximation scheme to two-point boundary value problems of ordinary differential equations, and a new one based on approximating the solution by generalized hypergeometric functions. A comparison with the numerical results obtained with the shooting method is made. A similar accuracy is reached in each case. Both two methods appear to be more efficient than the usual field expansions frequently used in the current studies of ERGEs (in particular for the Wilson-Polchinski case in the study of which they fail).
Baciocchi, Renato; Berardi, Simona; Verginelli, Iason
2010-09-15
Clean-up of contaminated sites is usually based on a risk-based approach for the definition of the remediation goals, which relies on the well known ASTM-RBCA standard procedure. In this procedure, migration of contaminants is described through simple analytical models and the source contaminants' concentration is supposed to be constant throughout the entire exposure period, i.e. 25-30 years. The latter assumption may often result over-protective of human health, leading to unrealistically low remediation goals. The aim of this work is to propose an alternative model taking in account the source depletion, while keeping the original simplicity and analytical form of the ASTM-RBCA approach. The results obtained by the application of this model are compared with those provided by the traditional ASTM-RBCA approach, by a model based on the source depletion algorithm of the RBCA ToolKit software and by a numerical model, allowing to assess its feasibility for inclusion in risk analysis procedures. The results discussed in this work are limited to on-site exposure to contaminated water by ingestion, but the approach proposed can be extended to other exposure pathways. Copyright 2010 Elsevier B.V. All rights reserved.
Directivity pattern of the sound radiated from axisymmetric stepped plates.
He, Xiping; Yan, Xiuli; Li, Na
2016-08-01
For the purpose of optimal design and efficient utilization of the kind of stepped plate radiator in air, in this contribution, an approach for calculation of the directivity pattern of the sound radiated from a stepped plate in flexural vibration with a free edge is developed based on Kirchhoff-Love hypothesis and Rayleigh integral principle. Experimental tests of directivity pattern for a fabricated flat plate and two fabricated plates with one and two step radiators were carried out. It shows that the configuration of the measured directivity patterns by the proposed analytic approach is similar to those of the calculated approach. Comparison of the agreement between the calculated directivity pattern of a stepped plate and its corresponding theoretical piston show that the former radiator is equivalent to the latter, and the diffraction field generated by the unbaffled upper surface may be small. It also shows that the directivity pattern of a stepped radiator is independent of the metallic material but dependent on the thickness of base plate and resonant frequency. The thicker the thickness of base plate, the more directive the radiation is. The proposed analytic approach in this work may be adopted for any other plates with multi-steps.
Baas, Matthijs; Nijstad, Bernard A; Boot, Nathalie C; De Dreu, Carsten K W
2016-06-01
Although many believe that creativity associates with a vulnerability to psychopathology, research findings are inconsistent. Here we address this possible linkage between risk of psychopathology and creativity in nonclinical samples. We propose that propensity for specific psychopathologies can be linked to basic motivational approach and avoidance systems, and that approach and avoidance motivation differentially influences creativity. Based on this reasoning, we predict that propensity for approach-based psychopathologies (e.g., positive schizotypy and risk of bipolar disorder) associates with increased creativity, whereas propensity for avoidance-based psychopathologies (e.g., anxiety, negative schizotypy, and depressive mood) associates with reduced creativity. Previous meta-analyses resonate with this proposition and showed small positive relations between positive schizotypy and creativity and small negative relations between negative schizotypy and creativity and between anxiety and creativity. To this we add new meta-analytic findings showing that risk of bipolar disorder (e.g., hypomania, mania) positively associates with creativity (k = 28, r = .224), whereas depressive mood negatively associates (albeit weakly) with creativity (k = 39, r = -.064). Our theoretical framework, along with the meta-analytic results, indicates when and why specific psychopathologies, and their inclinations, associate with increased or, instead, reduced creativity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Lee, Gibbeum; Cho, Yeunwoo
2018-01-01
A new semi-analytical approach is presented to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of direct numerical approach to this matrix eigenvalue problem, which may suffer from the computational inaccuracy for big data, a pair of integral and differential equations are considered, which are related to the so-called prolate spheroidal wave functions (PSWF). First, the PSWF is expressed as a summation of a small number of the analytical Legendre functions. After substituting them into the PSWF differential equation, a much smaller size matrix eigenvalue problem is obtained than the direct numerical K-L matrix eigenvalue problem. By solving this with a minimal numerical effort, the PSWF and the associated eigenvalue of the PSWF differential equation are obtained. Then, the eigenvalue of the PSWF integral equation is analytically expressed by the functional values of the PSWF and the eigenvalues obtained in the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data such as ordinary irregular waves. It is found that, with the same accuracy, the required memory size of the present method is smaller than that of the direct numerical K-L representation and the computation time of the present method is shorter than that of the semi-analytical method based on the sinusoidal functions.
Towards an Airframe Noise Prediction Methodology: Survey of Current Approaches
NASA Technical Reports Server (NTRS)
Farassat, Fereidoun; Casper, Jay H.
2006-01-01
In this paper, we present a critical survey of the current airframe noise (AFN) prediction methodologies. Four methodologies are recognized. These are the fully analytic method, CFD combined with the acoustic analogy, the semi-empirical method and fully numerical method. It is argued that for the immediate need of the aircraft industry, the semi-empirical method based on recent high quality acoustic database is the best available method. The method based on CFD and the Ffowcs William- Hawkings (FW-H) equation with penetrable data surface (FW-Hpds ) has advanced considerably and much experience has been gained in its use. However, more research is needed in the near future particularly in the area of turbulence simulation. The fully numerical method will take longer to reach maturity. Based on the current trends, it is predicted that this method will eventually develop into the method of choice. Both the turbulence simulation and propagation methods need to develop more for this method to become useful. Nonetheless, the authors propose that the method based on a combination of numerical and analytical techniques, e.g., CFD combined with FW-H equation, should also be worked on. In this effort, the current symbolic algebra software will allow more analytical approaches to be incorporated into AFN prediction methods.
Distribution of shortest cycle lengths in random networks
NASA Astrophysics Data System (ADS)
Bonneau, Haggai; Hassid, Aviv; Biham, Ofer; Kühn, Reimer; Katzav, Eytan
2017-12-01
We present analytical results for the distribution of shortest cycle lengths (DSCL) in random networks. The approach is based on the relation between the DSCL and the distribution of shortest path lengths (DSPL). We apply this approach to configuration model networks, for which analytical results for the DSPL were obtained before. We first calculate the fraction of nodes in the network which reside on at least one cycle. Conditioning on being on a cycle, we provide the DSCL over ensembles of configuration model networks with degree distributions which follow a Poisson distribution (Erdős-Rényi network), degenerate distribution (random regular graph), and a power-law distribution (scale-free network). The mean and variance of the DSCL are calculated. The analytical results are found to be in very good agreement with the results of computer simulations.
Scott, P J; Rigby, M; Ammenwerth, E; McNair, J Brender; Georgiou, A; Hyppönen, H; de Keizer, N; Magrabi, F; Nykänen, P; Gude, W T; Hackl, W
2017-08-01
Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon "Big Data" and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics. Georg Thieme Verlag KG Stuttgart.
NASA Technical Reports Server (NTRS)
Palazzolo, Alan; Bhattacharya, Avijit; Athavale, Mahesh; Venkataraman, Balaji; Ryan, Steve; Funston, Kerry
1997-01-01
This paper highlights bulk flow and CFD-based models prepared to calculate force and leakage properties for seals and shrouded impeller leakage paths. The bulk flow approach uses a Hir's based friction model and the CFD approach solves the Navier Stoke's (NS) equation with a finite whirl orbit or via analytical perturbation. The results show good agreement in most instances with available benchmarks.
Estimation of the uncertainty of analyte concentration from the measurement uncertainty.
Brown, Simon; Cooke, Delwyn G; Blackwell, Leonard F
2015-09-01
Ligand-binding assays, such as immunoassays, are usually analysed using standard curves based on the four-parameter and five-parameter logistic models. An estimate of the uncertainty of an analyte concentration obtained from such curves is needed for confidence intervals or precision profiles. Using a numerical simulation approach, it is shown that the uncertainty of the analyte concentration estimate becomes significant at the extremes of the concentration range and that this is affected significantly by the steepness of the standard curve. We also provide expressions for the coefficient of variation of the analyte concentration estimate from which confidence intervals and the precision profile can be obtained. Using three examples, we show that the expressions perform well.
NASA Astrophysics Data System (ADS)
Samborski, Sylwester; Valvo, Paolo S.
2018-01-01
The paper deals with the numerical and analytical modelling of the end-loaded split test for multi-directional laminates affected by the typical elastic couplings. Numerical analysis of three-dimensional finite element models was performed with the Abaqus software exploiting the virtual crack closure technique (VCCT). The results show possible asymmetries in the widthwise deflections of the specimen, as well as in the strain energy release rate (SERR) distributions along the delamination front. Analytical modelling based on a beam-theory approach was also conducted in simpler cases, where only bending-extension coupling is present, but no out-of-plane effects. The analytical results matched the numerical ones, thus demonstrating that the analytical models are feasible for test design and experimental data reduction.
Flexible manipulator control experiments and analysis
NASA Technical Reports Server (NTRS)
Yurkovich, S.; Ozguner, U.; Tzes, A.; Kotnik, P. T.
1987-01-01
Modeling and control design for flexible manipulators, both from an experimental and analytical viewpoint, are described. From the application perspective, an ongoing effort within the laboratory environment at the Ohio State University, where experimentation on a single link flexible arm is underway is described. Several unique features of this study are described here. First, the manipulator arm is slewed by a direct drive dc motor and has a rigid counterbalance appendage. Current experimentation is from two viewpoints: (1) rigid body slewing and vibration control via actuation with the hub motor, and (2) vibration suppression through the use of structure-mounted proof-mass actuation at the tip. Such an application to manipulator control is of interest particularly in design of space-based telerobotic control systems, but has received little attention to date. From an analytical viewpoint, parameter estimation techniques within the closed-loop for self-tuning adaptive control approaches are discussed. Also introduced is a control approach based on output feedback and frequency weighting to counteract effects of spillover in reduced-order model design. A model of the flexible manipulator based on experimental measurements is evaluated for such estimation and control approaches.
An Artificial Intelligence System to Predict Quality of Service in Banking Organizations
Popovič, Aleš
2016-01-01
Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge. PMID:27313604
An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.
Castelli, Mauro; Manzoni, Luca; Popovič, Aleš
2016-01-01
Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.
Recent trends in analytical procedures in forensic toxicology.
Van Bocxlaer, Jan F
2005-12-01
Forensic toxicology is a very demanding discipline,heavily dependent on good analytical techniques. That is why new trends appear continuously. In the past years. LC-MS has revolutionized target compound analysis and has become the trend, also in toxicology. In LC-MS screening analysis, things are less straightforward and several approaches exist. One promising approach based on accurate LC-MSTOF mass measurements and elemental formula based library searches is discussed. This way of screening has already proven its applicability but at the same time it became obvious that a single accurate mass measurement lacks some specificity when using large compound libraries. CE too is a reemerging approach. The increasingly polar and ionic molecules encountered make it a worthwhile addition to e.g. LC, as illustrated for the analysis of GHB. A third recent trend is the use of MALDI mass spectrometry for small molecules. It is promising for its ease-of-use and high throughput. Unfortunately, re-ports of disappointment but also accomplishment, e.g. the quantitative analysis of LSD as discussed here, alternate, and it remains to be seen whether MALDI really will establish itself. Indeed, not all new trends will prove themselves but the mere fact that many appear in the world of analytical toxicology nowadays is, in itself, encouraging for the future of (forensic) toxicology.
An experiment-based comparative study of fuzzy logic control
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Chen, Yung-Yaw; Lee, Chuen-Chein; Murugesan, S.; Jang, Jyh-Shing
1989-01-01
An approach is presented to the control of a dynamic physical system through the use of approximate reasoning. The approach has been implemented in a program named POLE, and the authors have successfully built a prototype hardware system to solve the cartpole balancing problem in real-time. The approach provides a complementary alternative to the conventional analytical control methodology and is of substantial use when a precise mathematical model of the process being controlled is not available. A set of criteria for comparing controllers based on approximate reasoning and those based on conventional control schemes is furnished.
xQuake: A Modern Approach to Seismic Network Analytics
NASA Astrophysics Data System (ADS)
Johnson, C. E.; Aikin, K. E.
2017-12-01
While seismic networks have expanded over the past few decades, and social needs for accurate and timely information has increased dramatically, approaches to the operational needs of both global and regional seismic observatories have been slow to adopt new technologies. This presentation presents the xQuake system that provides a fresh approach to seismic network analytics based on complexity theory and an adaptive architecture of streaming connected microservices as diverse data (picks, beams, and other data) flow into a final, curated catalog of events. The foundation for xQuake is the xGraph (executable graph) framework that is essentially a self-organizing graph database. An xGraph instance provides both the analytics as well as the data storage capabilities at the same time. Much of the analytics, such as synthetic annealing in the detection process and an evolutionary programing approach for event evolution, draws from the recent GLASS 3.0 seismic associator developed by and for the USGS National Earthquake Information Center (NEIC). In some respects xQuake is reminiscent of the Earthworm system, in that it comprises processes interacting through store and forward rings; not surprising as the first author was the lead architect of the original Earthworm project when it was known as "Rings and Things". While Earthworm components can easily be integrated into the xGraph processing framework, the architecture and analytics are more current (e.g. using a Kafka Broker for store and forward rings). The xQuake system is being released under an unrestricted open source license to encourage and enable sthe eismic community support in further development of its capabilities.
Boyack, Kevin W.; Newman, David; Duhon, Russell J.; Klavans, Richard; Patek, Michael; Biberstine, Joseph R.; Schijvenaars, Bob; Skupin, André; Ma, Nianli; Börner, Katy
2011-01-01
Background We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis. The few comparisons of clustering results from different similarity approaches have focused on small literature sets and have given conflicting results. Our study was designed to seek a robust answer to the question of which similarity approach would generate the most coherent clusters of a biomedical literature set of over two million documents. Methodology We used a corpus of 2.15 million recent (2004-2008) records from MEDLINE, and generated nine different document-document similarity matrices from information extracted from their bibliographic records, including titles, abstracts and subject headings. The nine approaches were comprised of five different analytical techniques with two data sources. The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models – BM25 and PMRA (PubMed Related Articles). The two data sources were a) MeSH subject headings, and b) words from titles and abstracts. Each similarity matrix was filtered to keep the top-n highest similarities per document and then clustered using a combination of graph layout and average-link clustering. Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE. Conclusions PubMed's own related article approach (PMRA) generated the most coherent and most concentrated cluster solution of the nine text-based similarity approaches tested, followed closely by the BM25 approach using titles and abstracts. Approaches using only MeSH subject headings were not competitive with those based on titles and abstracts. PMID:21437291
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ndong, Mamadou; Lauvergnat, David; Nauts, André
2013-11-28
We present new techniques for an automatic computation of the kinetic energy operator in analytical form. These techniques are based on the use of the polyspherical approach and are extended to take into account Cartesian coordinates as well. An automatic procedure is developed where analytical expressions are obtained by symbolic calculations. This procedure is a full generalization of the one presented in Ndong et al., [J. Chem. Phys. 136, 034107 (2012)]. The correctness of the new implementation is analyzed by comparison with results obtained from the TNUM program. We give several illustrations that could be useful for users of themore » code. In particular, we discuss some cyclic compounds which are important in photochemistry. Among others, we show that choosing a well-adapted parameterization and decomposition into subsystems can allow one to avoid singularities in the kinetic energy operator. We also discuss a relation between polyspherical and Z-matrix coordinates: this comparison could be helpful for building an interface between the new code and a quantum chemistry package.« less
Analysis of THG modes for femtosecond laser pulse
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Sidorov, Pavel S.
2017-05-01
THG is used nowadays in many practical applications such as a substance diagnostics, and biological objects imaging, and etc. With developing of new materials and technology (for example, photonic crystal) an attention to THG process analysis grow. Therefore, THG features understanding are a modern problem. Early we have developed new analytical approach based on using the problem invariant for analytical solution construction of the THG process. It should be stressed that we did not use a basic wave non-depletion approximation. Nevertheless, a long pulse duration approximation and plane wave approximation has applied. The analytical solution demonstrates, in particular, an optical bistability property (and may other regimes of frequency tripling) for the third harmonic generation process. But, obviously, this approach does not reflect an influence of a medium dispersion on the frequency tripling. Therefore, in this paper we analyze THG efficiency of a femtosecond laser pulse taking into account a second order dispersion affect as well as self- and crossmodulation of the interacting waves affect on the frequency conversion process. Analysis is made using a computer simulation on the base of Schrödinger equations describing the process under consideration.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Datta, Dipayan, E-mail: datta.dipayan@gmail.com; Gauss, Jürgen, E-mail: gauss@uni-mainz.de
We report analytical calculations of isotropic hyperfine-coupling constants in radicals using a spin-adapted open-shell coupled-cluster theory, namely, the unitary group based combinatoric open-shell coupled-cluster (COSCC) approach within the singles and doubles approximation. A scheme for the evaluation of the one-particle spin-density matrix required in these calculations is outlined within the spin-free formulation of the COSCC approach. In this scheme, the one-particle spin-density matrix for an open-shell state with spin S and M{sub S} = + S is expressed in terms of the one- and two-particle spin-free (charge) density matrices obtained from the Lagrangian formulation that is used for calculating themore » analytic first derivatives of the energy. Benchmark calculations are presented for NO, NCO, CH{sub 2}CN, and two conjugated π-radicals, viz., allyl and 1-pyrrolyl in order to demonstrate the performance of the proposed scheme.« less
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-01-01
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-02-08
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
NASA Astrophysics Data System (ADS)
Kerst, Stijn; Shyrokau, Barys; Holweg, Edward
2018-05-01
This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.
Smartphone-based quantitative measurements on holographic sensors.
Khalili Moghaddam, Gita; Lowe, Christopher Robin
2017-01-01
The research reported herein integrates a generic holographic sensor platform and a smartphone-based colour quantification algorithm in order to standardise and improve the determination of the concentration of analytes of interest. The utility of this approach has been exemplified by analysing the replay colour of the captured image of a holographic pH sensor in near real-time. Personalised image encryption followed by a wavelet-based image compression method were applied to secure the image transfer across a bandwidth-limited network to the cloud. The decrypted and decompressed image was processed through four principal steps: Recognition of the hologram in the image with a complex background using a template-based approach, conversion of device-dependent RGB values to device-independent CIEXYZ values using a polynomial model of the camera and computation of the CIEL*a*b* values, use of the colour coordinates of the captured image to segment the image, select the appropriate colour descriptors and, ultimately, locate the region of interest (ROI), i.e. the hologram in this case, and finally, application of a machine learning-based algorithm to correlate the colour coordinates of the ROI to the analyte concentration. Integrating holographic sensors and the colour image processing algorithm potentially offers a cost-effective platform for the remote monitoring of analytes in real time in readily accessible body fluids by minimally trained individuals.
Smartphone-based quantitative measurements on holographic sensors
Khalili Moghaddam, Gita
2017-01-01
The research reported herein integrates a generic holographic sensor platform and a smartphone-based colour quantification algorithm in order to standardise and improve the determination of the concentration of analytes of interest. The utility of this approach has been exemplified by analysing the replay colour of the captured image of a holographic pH sensor in near real-time. Personalised image encryption followed by a wavelet-based image compression method were applied to secure the image transfer across a bandwidth-limited network to the cloud. The decrypted and decompressed image was processed through four principal steps: Recognition of the hologram in the image with a complex background using a template-based approach, conversion of device-dependent RGB values to device-independent CIEXYZ values using a polynomial model of the camera and computation of the CIEL*a*b* values, use of the colour coordinates of the captured image to segment the image, select the appropriate colour descriptors and, ultimately, locate the region of interest (ROI), i.e. the hologram in this case, and finally, application of a machine learning-based algorithm to correlate the colour coordinates of the ROI to the analyte concentration. Integrating holographic sensors and the colour image processing algorithm potentially offers a cost-effective platform for the remote monitoring of analytes in real time in readily accessible body fluids by minimally trained individuals. PMID:29141008
ZnO-Based Amperometric Enzyme Biosensors
Zhao, Zhiwei; Lei, Wei; Zhang, Xiaobing; Wang, Baoping; Jiang, Helong
2010-01-01
Nanostructured ZnO with its unique properties could provide a suitable microenvironment for immobilization of enzymes while retaining their biological activity, and thus lead to an expanded use of this nanomaterial for the construction of electrochemical biosensors with enhanced analytical performance. ZnO-based enzyme electrochemical biosensors are summarized in several tables for an easy overview according to the target biosensing analyte (glucose, hydrogen peroxide, phenol and cholesterol), respectively. Moreover, recent developments in enzyme electrochemical biosensors based on ZnO nanomaterials are reviewed with an emphasis on the fabrications and features of ZnO, approaches for biosensor construction (e.g., modified electrodes and enzyme immobilization) and biosensor performances. PMID:22205864
NASA Astrophysics Data System (ADS)
Nakadate, Hiromichi; Sekizuka, Eiichi; Minamitani, Haruyuki
We aimed to study the validity of a new analytical approach that reflected the phase from platelet activation to the formation of small platelet aggregates. We hoped that this new approach would enable us to use the particle-counting method with laser-light scattering to measure platelet aggregation in healthy controls and in diabetic patients without complications. We measured agonist-induced platelet aggregation for 10 min. Agonist was added to the platelet-rich plasma 1 min after measurement started. We compared the total scattered light intensity from small aggregates over a 10-min period (established analytical approach) and that over a 2-min period from 1 to 3 min after measurement started (new analytical approach). Consequently platelet aggregation in diabetics with HbA1c ≥ 6.5% was significantly greater than in healthy controls by both analytical approaches. However, platelet aggregation in diabetics with HbA1c < 6.5%, i.e. patients in the early stages of diabetes, was significantly greater than in healthy controls only by the new analytical approach, not by the established analytical approach. These results suggest that platelet aggregation as detected by the particle-counting method using laser-light scattering could be applied in clinical examinations by our new analytical approach.
Optofluidic platforms based on surface-enhanced Raman scattering.
Lim, Chaesung; Hong, Jongin; Chung, Bong Geun; deMello, Andrew J; Choo, Jaebum
2010-05-01
We report recent progress in the development of surface-enhanced Raman scattering (SERS)-based optofluidic platforms for the fast and sensitive detection of chemical and biological analytes. In the current context, a SERS-based optofluidic platform is defined as an integrated analytical device composed of a microfluidic element and a sensitive Raman spectrometer. Optofluidic devices for SERS detection normally involve nanocolloid-based microfluidic systems or metal nanostructure-embedded microfluidic systems. In the current review, recent advances in both approaches are surveyed and assessed. Additionally, integrated real-time sensing systems that combine portable Raman spectrometers with microfluidic devices are also reviewed. Such real-time sensing systems have significant utility in environmental monitoring, forensic science and homeland defense applications.
ERIC Educational Resources Information Center
Liu, Woon Chia; Wang, Chee Keng John; Kee, Ying Hwa; Koh, Caroline; Lim, Boon San Coral; Chua, Lilian
2014-01-01
The development of effective self-regulated learning strategies is of interest to educationalists. In this paper, we examine inherent individual difference in self-regulated learning based on Motivated Learning for Learning Questionnaire (MLSQ) using the cluster analytic approach and examine cluster difference in terms of self-determination theory…
Fast-slow asymptotic for semi-analytical ignition criteria in FitzHugh-Nagumo system.
Bezekci, B; Biktashev, V N
2017-09-01
We study the problem of initiation of excitation waves in the FitzHugh-Nagumo model. Our approach follows earlier works and is based on the idea of approximating the boundary between basins of attraction of propagating waves and of the resting state as the stable manifold of a critical solution. Here, we obtain analytical expressions for the essential ingredients of the theory by singular perturbation using two small parameters, the separation of time scales of the activator and inhibitor and the threshold in the activator's kinetics. This results in a closed analytical expression for the strength-duration curve.
Van den Bulcke, Marc; Lievens, Antoon; Barbau-Piednoir, Elodie; MbongoloMbella, Guillaume; Roosens, Nancy; Sneyers, Myriam; Casi, Amaya Leunda
2010-03-01
The detection of genetically modified (GM) materials in food and feed products is a complex multi-step analytical process invoking screening, identification, and often quantification of the genetically modified organisms (GMO) present in a sample. "Combinatory qPCR SYBRGreen screening" (CoSYPS) is a matrix-based approach for determining the presence of GM plant materials in products. The CoSYPS decision-support system (DSS) interprets the analytical results of SYBRGREEN qPCR analysis based on four values: the C(t)- and T(m) values and the LOD and LOQ for each method. A theoretical explanation of the different concepts applied in CoSYPS analysis is given (GMO Universe, "Prime number tracing", matrix/combinatory approach) and documented using the RoundUp Ready soy GTS40-3-2 as an example. By applying a limited set of SYBRGREEN qPCR methods and through application of a newly developed "prime number"-based algorithm, the nature of subsets of corresponding GMO in a sample can be determined. Together, these analyses provide guidance for semi-quantitative estimation of GMO presence in a food and feed product.
ERIC Educational Resources Information Center
Maynard, Brandy R.; Wilson, Alyssa N.; Labuzienski, Elizabeth; Whiting, Seth W.
2018-01-01
Background and Aims: To examine the effects of mindfulness-based interventions on gambling behavior and symptoms, urges, and financial outcomes. Method: Systematic review and meta-analytic procedures were employed to search, select, code, and analyze studies conducted between 1980 and 2014, assessing the effects of mindfulness-based interventions…
NASA Astrophysics Data System (ADS)
Omenetto, N.; Smith, B. W.; Winefordner, J. D.
1989-01-01
Several theoretical considerations are given on the potential and practical capabilities of a detector of fluorescence radiation whose operating principle is based on a multi-step excitation-ionization scheme involving the fluorescence photons as the first excitation step. This detection technique, which was first proposed by MATVEEVet al. [ Zh. Anal Khim.34, 846 (1979)], combines two independent atomizers, one analytical cell for the excitation of the sample fluorescence and one cell, filled with pure analyte atomic vapor, acting as the ionization detector. One laser beam excites the analyte fluorescence in the analytical cell and one (or two) laser beams are used to ionize the excited atoms in the detector. Several different causes of signal and noise are evaluated, together with a discussion on possible analytical atom reservoirs (flames, furnaces) and laser sources which could be used with this approach. For properly devised conditions, i.e. optical saturation of the fluorescence and unity ionization efficiency, detection limits well below pg/ml in solution and well below femtograms as absolute amounts in furnaces can be predicted. However, scattering problems, which are absent in a conventional laser-enhanced ionization set-up, may be important in this approach.
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.
A Unifying Review of Bioassay-Guided Fractionation, Effect-Directed Analysis and Related Techniques
Weller, Michael G.
2012-01-01
The success of modern methods in analytical chemistry sometimes obscures the problem that the ever increasing amount of analytical data does not necessarily give more insight of practical relevance. As alternative approaches, toxicity- and bioactivity-based assays can deliver valuable information about biological effects of complex materials in humans, other species or even ecosystems. However, the observed effects often cannot be clearly assigned to specific chemical compounds. In these cases, the establishment of an unambiguous cause-effect relationship is not possible. Effect-directed analysis tries to interconnect instrumental analytical techniques with a biological/biochemical entity, which identifies or isolates substances of biological relevance. Successful application has been demonstrated in many fields, either as proof-of-principle studies or even for complex samples. This review discusses the different approaches, advantages and limitations and finally shows some practical examples. The broad emergence of effect-directed analytical concepts might lead to a true paradigm shift in analytical chemistry, away from ever growing lists of chemical compounds. The connection of biological effects with the identification and quantification of molecular entities leads to relevant answers to many real life questions. PMID:23012539
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
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.
NASA Astrophysics Data System (ADS)
Kiani, M.; Abdolali, A.; Safari, M.
2018-03-01
In this article, an analytical approach is presented for the analysis of electromagnetic (EM) scattering from radially inhomogeneous spherical structures (RISSs) based on the duality principle. According to the spherical symmetry, similar angular dependencies in all the regions are considered using spherical harmonics. To extract the radial dependency, the system of differential equations of wave propagation toward the inhomogeneity direction is equated with the dual planar ones. A general duality between electromagnetic fields and parameters and scattering parameters of the two structures is introduced. The validity of the proposed approach is verified through a comprehensive example. The presented approach substitutes a complicated problem in spherical coordinate to an easy, well posed, and previously solved problem in planar geometry. This approach is valid for all continuously varying inhomogeneity profiles. One of the major advantages of the proposed method is the capability of studying two general and applicable types of RISSs. As an interesting application, a class of lens antenna based on the physical concept of the gradient refractive index material is introduced. The approach is used to analyze the EM scattering from the structure and validate strong performance of the lens.
NASA Astrophysics Data System (ADS)
Jones, Ryan M.; Hynynen, Kullervo
2016-01-01
Computed tomography (CT)-based aberration corrections are employed in transcranial ultrasound both for therapy and imaging. In this study, analytical and numerical approaches for calculating aberration corrections based on CT data were compared, with a particular focus on their application to transcranial passive imaging. Two models were investigated: a three-dimensional full-wave numerical model (Connor and Hynynen 2004 IEEE Trans. Biomed. Eng. 51 1693-706) based on the Westervelt equation, and an analytical method (Clement and Hynynen 2002 Ultrasound Med. Biol. 28 617-24) similar to that currently employed by commercial brain therapy systems. Trans-skull time delay corrections calculated from each model were applied to data acquired by a sparse hemispherical (30 cm diameter) receiver array (128 piezoceramic discs: 2.5 mm diameter, 612 kHz center frequency) passively listening through ex vivo human skullcaps (n = 4) to emissions from a narrow-band, fixed source emitter (1 mm diameter, 516 kHz center frequency). Measurements were taken at various locations within the cranial cavity by moving the source around the field using a three-axis positioning system. Images generated through passive beamforming using CT-based skull corrections were compared with those obtained through an invasive source-based approach, as well as images formed without skull corrections, using the main lobe volume, positional shift, peak sidelobe ratio, and image signal-to-noise ratio as metrics for image quality. For each CT-based model, corrections achieved by allowing for heterogeneous skull acoustical parameters in simulation outperformed the corresponding case where homogeneous parameters were assumed. Of the CT-based methods investigated, the full-wave model provided the best imaging results at the cost of computational complexity. These results highlight the importance of accurately modeling trans-skull propagation when calculating CT-based aberration corrections. Although presented in an imaging context, our results may also be applicable to the problem of transmit focusing through the skull.
NASA Astrophysics Data System (ADS)
Gen, Masao; Kakuta, Hideo; Kamimoto, Yoshihito; Wuled Lenggoro, I.
2011-06-01
A detection method based on the surface-enhanced Raman spectroscopy (SERS)-active substrate derived from aerosol nanoparticles and a colloidal suspension for detecting organic molecules of a model analyte (a pesticide) is proposed. This approach can detect the molecules of the derived from its solution with the concentration levels of ppb. For substrate fabrication, a gas-phase method is used to directly deposit Ag nanoparticles on to a silicon substrate having pyramidal structures. By mixing the target analyte with a suspension of Ag colloids purchased in advance, clotianidin analyte on Ag colloid can exist in junctions of co-aggregated Ag colloids. Using (i) a nanostructured substrate made from aerosol nanoparticles and (ii) colloidal suspension can increase the number of activity spots.
NASA Astrophysics Data System (ADS)
Ovsyannikov, A. D.; Kozynchenko, S. A.; Kozynchenko, V. A.
2017-12-01
When developing a particle accelerator for generating the high-precision beams, the injection system design is of importance, because it largely determines the output characteristics of the beam. At the present paper we consider the injection systems consisting of electrodes with given potentials. The design of such systems requires carrying out simulation of beam dynamics in the electrostatic fields. For external field simulation we use the new approach, proposed by A.D. Ovsyannikov, which is based on analytical approximations, or finite difference method, taking into account the real geometry of the injection system. The software designed for solving the problems of beam dynamics simulation and optimization in the injection system for non-relativistic beams has been developed. Both beam dynamics and electric field simulations in the injection system which use analytical approach and finite difference method have been made and the results presented in this paper.
A Hybrid Coarse-graining Approach for Lipid Bilayers at Large Length and Time Scales
Ayton, Gary S.; Voth, Gregory A.
2009-01-01
A hybrid analytic-systematic (HAS) coarse-grained (CG) lipid model is developed and employed in a large-scale simulation of a liposome. The methodology is termed hybrid analyticsystematic as one component of the interaction between CG sites is variationally determined from the multiscale coarse-graining (MS-CG) methodology, while the remaining component utilizes an analytic potential. The systematic component models the in-plane center of mass interaction of the lipids as determined from an atomistic-level MD simulation of a bilayer. The analytic component is based on the well known Gay-Berne ellipsoid of revolution liquid crystal model, and is designed to model the highly anisotropic interactions at a highly coarse-grained level. The HAS CG approach is the first step in an “aggressive” CG methodology designed to model multi-component biological membranes at very large length and timescales. PMID:19281167
Andrés, Axel; Rosés, Martí; Bosch, Elisabeth
2014-11-28
In previous work, a two-parameter model to predict chromatographic retention of ionizable analytes in gradient mode was proposed. However, the procedure required some previous experimental work to get a suitable description of the pKa change with the mobile phase composition. In the present study this previous experimental work has been simplified. The analyte pKa values have been calculated through equations whose coefficients vary depending on their functional group. Forced by this new approach, other simplifications regarding the retention of the totally neutral and totally ionized species also had to be performed. After the simplifications were applied, new prediction values were obtained and compared with the previously acquired experimental data. The simplified model gave pretty good predictions while saving a significant amount of time and resources. Copyright © 2014 Elsevier B.V. All rights reserved.
Improved Quantification of Free and Ester-Bound Gallic Acid in Foods and Beverages by UHPLC-MS/MS.
Newsome, Andrew G; Li, Yongchao; van Breemen, Richard B
2016-02-17
Hydrolyzable tannins are measured routinely during the characterization of food and beverage samples. Most methods for the determination of hydrolyzable tannins use hydrolysis or methanolysis to convert complex tannins to small molecules (gallic acid, methyl gallate, and ellagic acid) for quantification by HPLC-UV. Often unrecognized, analytical limitations and variability inherent in these approaches for the measurement of hydrolyzable tannins include the variable mass fraction (0-0.90) that is released as analyte, contributions of sources other than tannins to hydrolyzable gallate (can exceed >10 wt %/wt), the measurement of both free and total analyte, and lack of controls to account for degradation. An accurate, specific, sensitive, and higher-throughput approach for the determination of hydrolyzable gallate based on ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) that overcomes these limitations was developed.
Verification of out-of-control situations detected by "average of normal" approach.
Liu, Jiakai; Tan, Chin Hon; Loh, Tze Ping; Badrick, Tony
2016-11-01
"Average of normal" (AoN) or "moving average" is increasingly used as an adjunct quality control tool in laboratory practice. Little guidance exists on how to verify if an out-of-control situation in the AoN chart is due to a shift in analytical performance, or underlying patient characteristics. Through simulation based on clinical data, we examined 1) the location of the last apparently stable period in the AoN control chart after an analytical shift, and 2) an approach to verify if the observed shift is related to an analytical shift by repeat testing of archived patient samples from the stable period for 21 common analytes. The number of blocks of results to look back for the stable period increased with the duration of the analytical shift, and was larger when smaller AoN block sizes were used. To verify an analytical shift, 3 archived samples from the analytically stable period should be retested. In particular, the process is deemed to have shifted if a difference of >2 analytical standard deviations (i.e. 1:2s rejection rule) between the original and retested results are observed in any of the 3 samples produced. The probability of Type-1 error (i.e., false rejection) and power (i.e., detecting true analytical shift) of this rule are <0.1 and >0.9, respectively. The use of appropriately archived patient samples to verify an apparent analytical shift is preferred to quality control materials. Nonetheless, the above findings may also apply to quality control materials, barring matrix effects. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Babaie Mahani, A.; Eaton, D. W.
2013-12-01
Ground Motion Prediction Equations (GMPEs) are widely used in Probabilistic Seismic Hazard Assessment (PSHA) to estimate ground-motion amplitudes at Earth's surface as a function of magnitude and distance. Certain applications, such as hazard assessment for caprock integrity in the case of underground storage of CO2, waste disposal sites, and underground pipelines, require subsurface estimates of ground motion; at present, such estimates depend upon theoretical modeling and simulations. The objective of this study is to derive correction factors for GMPEs to enable estimation of amplitudes in the subsurface. We use a semi-analytic approach along with finite-difference simulations of ground-motion amplitudes for surface and underground motions. Spectral ratios of underground to surface motions are used to calculate the correction factors. Two predictive methods are used. The first is a semi-analytic approach based on a quarter-wavelength method that is widely used for earthquake site-response investigations; the second is a numerical approach based on elastic finite-difference simulations of wave propagation. Both methods are evaluated using recordings of regional earthquakes by broadband seismometers installed at the surface and at depths of 1400 m and 2100 m in the Sudbury Neutrino Observatory, Canada. Overall, both methods provide a reasonable fit to the peaks and troughs observed in the ratios of real data. The finite-difference method, however, has the capability to simulate ground motion ratios more accurately than the semi-analytic approach.
Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science
NASA Astrophysics Data System (ADS)
Riedel, Morris; Ramachandran, Rahul; Baumann, Peter
2014-05-01
The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.
Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science
NASA Technical Reports Server (NTRS)
Riedel, Morris; Ramachandran, Rahul; Baumann, Peter
2014-01-01
The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.
NASA Astrophysics Data System (ADS)
Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha
2016-04-01
This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.
Free and Forced Vibrations of Thick-Walled Anisotropic Cylindrical Shells
NASA Astrophysics Data System (ADS)
Marchuk, A. V.; Gnedash, S. V.; Levkovskii, S. A.
2017-03-01
Two approaches to studying the free and forced axisymmetric vibrations of cylindrical shell are proposed. They are based on the three-dimensional theory of elasticity and division of the original cylindrical shell with concentric cross-sectional circles into several coaxial cylindrical shells. One approach uses linear polynomials to approximate functions defined in plan and across the thickness. The other approach also uses linear polynomials to approximate functions defined in plan, but their variation with thickness is described by the analytical solution of a system of differential equations. Both approaches have approximation and arithmetic errors. When determining the natural frequencies by the semi-analytical finite-element method in combination with the divide and conqure method, it is convenient to find the initial frequencies by the finite-element method. The behavior of the shell during free and forced vibrations is analyzed in the case where the loading area is half the shell thickness
Luo, Yuan; Szolovits, Peter; Dighe, Anand S; Baron, Jason M
2018-06-01
A key challenge in clinical data mining is that most clinical datasets contain missing data. Since many commonly used machine learning algorithms require complete datasets (no missing data), clinical analytic approaches often entail an imputation procedure to "fill in" missing data. However, although most clinical datasets contain a temporal component, most commonly used imputation methods do not adequately accommodate longitudinal time-based data. We sought to develop a new imputation algorithm, 3-dimensional multiple imputation with chained equations (3D-MICE), that can perform accurate imputation of missing clinical time series data. We extracted clinical laboratory test results for 13 commonly measured analytes (clinical laboratory tests). We imputed missing test results for the 13 analytes using 3 imputation methods: multiple imputation with chained equations (MICE), Gaussian process (GP), and 3D-MICE. 3D-MICE utilizes both MICE and GP imputation to integrate cross-sectional and longitudinal information. To evaluate imputation method performance, we randomly masked selected test results and imputed these masked results alongside results missing from our original data. We compared predicted results to measured results for masked data points. 3D-MICE performed significantly better than MICE and GP-based imputation in a composite of all 13 analytes, predicting missing results with a normalized root-mean-square error of 0.342, compared to 0.373 for MICE alone and 0.358 for GP alone. 3D-MICE offers a novel and practical approach to imputing clinical laboratory time series data. 3D-MICE may provide an additional tool for use as a foundation in clinical predictive analytics and intelligent clinical decision support.
Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik; ...
2017-10-06
A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik
A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less
Feasibility of Self-Reflection as a Tool to Balance Clinical Reasoning Strategies
ERIC Educational Resources Information Center
Sibbald, Matthew; de Bruin, Anique B. H.
2012-01-01
Clinicians are believed to use two predominant reasoning strategies: system 1 based pattern recognition, and system 2 based analytical reasoning. Balancing these cognitive reasoning strategies is widely believed to reduce diagnostic error. However, clinicians approach different problems with different reasoning strategies. This study explores…
Ungerer, Jacobus P J; Pretorius, Carel J
2014-04-01
Highly-sensitive cardiac troponin (cTn) assays are being introduced into the market. In this study we argue that the classification of cTn assays into sensitive and highly-sensitive is flawed and recommend a more appropriate way to characterize analytical sensitivity of cTn assays. The raw data of 2252 cardiac troponin I (cTnI) tests done in duplicate with a 'sensitive' assay was extracted and used to calculate the cTnI levels in all, including those below the 'limit of detection' (LoD) that were censored. Duplicate results were used to determine analytical imprecision. We show that cTnI can be quantified in all samples including those with levels below the LoD and that the actual margins of error decrease as concentrations approach zero. The dichotomous classification of cTn assays into sensitive and highly-sensitive is theoretically flawed and characterizing analytical sensitivity as a continuous variable based on imprecision at 0 and the 99th percentile cut-off would be more appropriate.
NASA Astrophysics Data System (ADS)
Danaeifar, Mohammad; Granpayeh, Nosrat
2018-03-01
An analytical method is presented to analyze and synthesize bianisotropic metasurfaces. The equivalent parameters of metasurfaces in terms of meta-atom properties and other specifications of metasurfaces are derived. These parameters are related to electric, magnetic, and electromagnetic/magnetoelectric dipole moments of the bianisotropic media, and they can simplify the analysis of complicated and multilayer structures. A metasurface of split ring resonators is studied as an example demonstrating the proposed method. The optical properties of the meta-atom are explored, and the calculated polarizabilities are applied to find the reflection coefficient and the equivalent parameters of the metasurface. Finally, a structure consisting of two metasurfaces of the split ring resonators is provided, and the proposed analytical method is applied to derive the reflection coefficient. The validity of this analytical approach is verified by full-wave simulations which demonstrate good accuracy of the equivalent parameter method. This method can be used in the analysis and synthesis of bianisotropic metasurfaces with different materials and in different frequency ranges by considering electric, magnetic, and electromagnetic/magnetoelectric dipole moments.
NASA Technical Reports Server (NTRS)
Karandikar, Harsh M.
1997-01-01
An approach for objective and quantitative technical and cost risk analysis during product development, which is applicable from the earliest stages, is discussed. The approach is supported by a software tool called the Analytical System for Uncertainty and Risk Estimation (ASURE). Details of ASURE, the underlying concepts and its application history, are provided.
An Investigation of Visual, Aural, Motion and Control Movement Cues.
ERIC Educational Resources Information Center
Matheny, W. G.; And Others
A study was conducted to determine the ways in which multi-sensory cues can be simulated and effectively used in the training of pilots. Two analytical bases, one called the stimulus environment approach and the other an information array approach, are developed along with a cue taxonomy. Cues are postulated on the basis of information gained from…
NASA Astrophysics Data System (ADS)
Aghakhani, Amirreza; Basdogan, Ipek; Erturk, Alper
2016-04-01
Plate-like components are widely used in numerous automotive, marine, and aerospace applications where they can be employed as host structures for vibration based energy harvesting. Piezoelectric patch harvesters can be easily attached to these structures to convert the vibrational energy to the electrical energy. Power output investigations of these harvesters require accurate models for energy harvesting performance evaluation and optimization. Equivalent circuit modeling of the cantilever-based vibration energy harvesters for estimation of electrical response has been proposed in recent years. However, equivalent circuit formulation and analytical modeling of multiple piezo-patch energy harvesters integrated to thin plates including nonlinear circuits has not been studied. In this study, equivalent circuit model of multiple parallel piezoelectric patch harvesters together with a resistive load is built in electronic circuit simulation software SPICE and voltage frequency response functions (FRFs) are validated using the analytical distributedparameter model. Analytical formulation of the piezoelectric patches in parallel configuration for the DC voltage output is derived while the patches are connected to a standard AC-DC circuit. The analytic model is based on the equivalent load impedance approach for piezoelectric capacitance and AC-DC circuit elements. The analytic results are validated numerically via SPICE simulations. Finally, DC power outputs of the harvesters are computed and compared with the peak power amplitudes in the AC output case.
Distributed adaptive diagnosis of sensor faults using structural response data
NASA Astrophysics Data System (ADS)
Dragos, Kosmas; Smarsly, Kay
2016-10-01
The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.
NASA Astrophysics Data System (ADS)
Mananga, Eugene Stephane; Charpentier, Thibault
2015-04-01
In this paper we present a theoretical perturbative approach for describing the NMR spectrum of strongly dipolar-coupled spin systems under fast magic-angle spinning. Our treatment is based on two approaches: the Floquet approach and the Floquet-Magnus expansion. The Floquet approach is well known in the NMR community as a perturbative approach to get analytical approximations. Numerical procedures are based on step-by-step numerical integration of the corresponding differential equations. The Floquet-Magnus expansion is a perturbative approach of the Floquet theory. Furthermore, we address the " γ -encoding" effect using the Floquet-Magnus expansion approach. We show that the average over " γ " angle can be performed for any Hamiltonian with γ symmetry.
The Water-Energy-Food Nexus: A systematic review of methods for nexus assessment
NASA Astrophysics Data System (ADS)
Albrecht, Tamee R.; Crootof, Arica; Scott, Christopher A.
2018-04-01
The water-energy-food (WEF) nexus is rapidly expanding in scholarly literature and policy settings as a novel way to address complex resource and development challenges. The nexus approach aims to identify tradeoffs and synergies of water, energy, and food systems, internalize social and environmental impacts, and guide development of cross-sectoral policies. However, while the WEF nexus offers a promising conceptual approach, the use of WEF nexus methods to systematically evaluate water, energy, and food interlinkages or support development of socially and politically-relevant resource policies has been limited. This paper reviews WEF nexus methods to provide a knowledge base of existing approaches and promote further development of analytical methods that align with nexus thinking. The systematic review of 245 journal articles and book chapters reveals that (a) use of specific and reproducible methods for nexus assessment is uncommon (less than one-third); (b) nexus methods frequently fall short of capturing interactions among water, energy, and food—the very linkages they conceptually purport to address; (c) assessments strongly favor quantitative approaches (nearly three-quarters); (d) use of social science methods is limited (approximately one-quarter); and (e) many nexus methods are confined to disciplinary silos—only about one-quarter combine methods from diverse disciplines and less than one-fifth utilize both quantitative and qualitative approaches. To help overcome these limitations, we derive four key features of nexus analytical tools and methods—innovation, context, collaboration, and implementation—from the literature that reflect WEF nexus thinking. By evaluating existing nexus analytical approaches based on these features, we highlight 18 studies that demonstrate promising advances to guide future research. This paper finds that to address complex resource and development challenges, mixed-methods and transdisciplinary approaches are needed that incorporate social and political dimensions of water, energy, and food; utilize multiple and interdisciplinary approaches; and engage stakeholders and decision-makers.
Bias Assessment of General Chemistry Analytes using Commutable Samples.
Koerbin, Gus; Tate, Jillian R; Ryan, Julie; Jones, Graham Rd; Sikaris, Ken A; Kanowski, David; Reed, Maxine; Gill, Janice; Koumantakis, George; Yen, Tina; St John, Andrew; Hickman, Peter E; Simpson, Aaron; Graham, Peter
2014-11-01
Harmonisation of reference intervals for routine general chemistry analytes has been a goal for many years. Analytical bias may prevent this harmonisation. To determine if analytical bias is present when comparing methods, the use of commutable samples, or samples that have the same properties as the clinical samples routinely analysed, should be used as reference samples to eliminate the possibility of matrix effect. The use of commutable samples has improved the identification of unacceptable analytical performance in the Netherlands and Spain. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has undertaken a pilot study using commutable samples in an attempt to determine not only country specific reference intervals but to make them comparable between countries. Australia and New Zealand, through the Australasian Association of Clinical Biochemists (AACB), have also undertaken an assessment of analytical bias using commutable samples and determined that of the 27 general chemistry analytes studied, 19 showed sufficiently small between method biases as to not prevent harmonisation of reference intervals. Application of evidence based approaches including the determination of analytical bias using commutable material is necessary when seeking to harmonise reference intervals.
A new method for constructing analytic elements for groundwater flow.
NASA Astrophysics Data System (ADS)
Strack, O. D.
2007-12-01
The analytic element method is based upon the superposition of analytic functions that are defined throughout the infinite domain, and can be used to meet a variety of boundary conditions. Analytic elements have been use successfully for a number of problems, mainly dealing with the Poisson equation (see, e.g., Theory and Applications of the Analytic Element Method, Reviews of Geophysics, 41,2/1005 2003 by O.D.L. Strack). The majority of these analytic elements consists of functions that exhibit jumps along lines or curves. Such linear analytic elements have been developed also for other partial differential equations, e.g., the modified Helmholz equation and the heat equation, and were constructed by integrating elementary solutions, the point sink and the point doublet, along a line. This approach is limiting for two reasons. First, the existence is required of the elementary solutions, and, second, the integration tends to limit the range of solutions that can be obtained. We present a procedure for generating analytic elements that requires merely the existence of a harmonic function with the desired properties; such functions exist in abundance. The procedure to be presented is used to generalize this harmonic function in such a way that the resulting expression satisfies the applicable differential equation. The approach will be applied, along with numerical examples, for the modified Helmholz equation and for the heat equation, while it is noted that the method is in no way restricted to these equations. The procedure is carried out entirely in terms of complex variables, using Wirtinger calculus.
2017-01-01
Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described. PMID:28542338
Young, Brian; King, Jonathan L; Budowle, Bruce; Armogida, Luigi
2017-01-01
Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described.
Meisser Redeuil, Karine; Longet, Karin; Bénet, Sylvie; Munari, Caroline; Campos-Giménez, Esther
2015-11-27
This manuscript reports a validated analytical approach for the quantification of 21 water soluble vitamins and their main circulating forms in human plasma. Isotope dilution-based sample preparation consisted of protein precipitation using acidic methanol enriched with stable isotope labelled internal standards. Separation was achieved by reversed-phase liquid chromatography and detection performed by tandem mass spectrometry in positive electrospray ionization mode. Instrumental lower limits of detection and quantification reached <0.1-10nM and 0.2-25nM, respectively. Commercially available pooled human plasma was used to build matrix-matched calibration curves ranging 2-500, 5-1250, 20-5000 or 150-37500nM depending on the analyte. The overall performance of the method was considered adequate, with 2.8-20.9% and 5.2-20.0% intra and inter-day precision, respectively and averaged accuracy reaching 91-108%. Recovery experiments were also performed and reached in average 82%. This analytical approach was then applied for the quantification of circulating water soluble vitamins in human plasma single donor samples. The present report provides a sensitive and reliable approach for the quantification of water soluble vitamins and main circulating forms in human plasma. In the future, the application of this analytical approach will give more confidence to provide a comprehensive assessment of water soluble vitamins nutritional status and bioavailability studies in humans. Copyright © 2015 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whipple, C
Several alternative approaches to address the question {open_quotes}How safe is safe enough?{close_quotes} are reviewed and an attempt is made to apply the reasoning behind these approaches to the issue of acceptability of radiation exposures received in space. The approaches to the issue of the acceptability of technological risk described here are primarily analytical, and are drawn from examples in the management of environmental health risks. These include risk-based approaches, in which specific quantitative risk targets determine the acceptability of an activity, and cost-benefit and decision analysis, which generally focus on the estimation and evaluation of risks, benefits and costs, inmore » a framework that balances these factors against each other. These analytical methods tend by their quantitative nature to emphasize the magnitude of risks, costs and alternatives, and to downplay other factors, especially those that are not easily expressed in quantitative terms, that affect acceptance or rejection of risk. Such other factors include the issues of risk perceptions and how and by whom risk decisions are made.« less
Approach of Decision Making Based on the Analytic Hierarchy Process for Urban Landscape Management
NASA Astrophysics Data System (ADS)
Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan
2013-03-01
This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.
Approach of decision making based on the analytic hierarchy process for urban landscape management.
Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan
2013-03-01
This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.
NASA Astrophysics Data System (ADS)
Capitaine, N.; Folgueira, M.
2012-12-01
In a previous paper (Capitaine et al. 2006), referred here as Paper I, we demonstrated the possibility of integrating the Earth's rotational motion in terms of the coordinates (X, Y ) of the celestial intermediate pole (CIP) unit vector in the Geocentric celestial reference system (GCRS). Here, we report on the approach that has been followed for solving the equations in the case of an axially symmetric rigid Earth and the semi-analytical (X, Y ) solution obtained from the expression of the external torque acting on the Earth derived from the most complete semi-analytical solutions for the Earth, Moon and planets.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cong, Yongzheng; Rausch, Sarah J.; Geng, Tao
2014-10-27
Here we show that a closed pneumatic microvalve on a PDMS chip can serve as a semipermeable membrane under an applied potential, enabling current to pass through while blocking the passage of charged analytes. Enrichment of both anionic and cationic species has been demonstrated, and concentration factors of ~70 have been achieved in just 8 s. Once analytes are concentrated, the valve is briefly opened and the sample is hydrodynamically injected onto an integrated microchip or capillary electrophoresis (CE) column. In contrast to existing preconcentration approaches, the membrane-based method described here enables both rapid analyte concentration as well as highmore » resolution separations.« less
Argumentation in Science Education: A Model-based Framework
NASA Astrophysics Data System (ADS)
Böttcher, Florian; Meisert, Anke
2011-02-01
The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.
Yuan, Mingquan; Alocilja, Evangelyn C; Chakrabartty, Shantanu
2016-08-01
This paper presents a wireless, self-powered, affinity-based biosensor based on the integration of paper-based microfluidics with our previously reported method for self-assembling radio-frequency (RF) antennas. At the core of the proposed approach is a silver-enhancement technique that grows portions of a RF antenna in regions where target antigens hybridize with target specific affinity probes. The hybridization regions are defined by a network of nitrocellulose based microfluidic channels which implement a self-powered approach to sample the reagent and control its flow and mixing. The integration substrate for the biosensor has been constructed using polyethylene and the patterning of the antenna on the substrate has been achieved using a low-cost ink-jet printing technique. The substrate has been integrated with passive radio-frequency identification (RFID) tags to demonstrate that the resulting sensor-tag can be used for continuous monitoring in a food supply-chain where direct measurement of analytes is typically considered to be impractical. We validate the proof-of-concept operation of the proposed sensor-tag using IgG as a model analyte and using a 915 MHz Ultra-high-frequency (UHF) RFID tagging technology.
Modelling vortex-induced fluid-structure interaction.
Benaroya, Haym; Gabbai, Rene D
2008-04-13
The principal goal of this research is developing physics-based, reduced-order, analytical models of nonlinear fluid-structure interactions associated with offshore structures. Our primary focus is to generalize the Hamilton's variational framework so that systems of flow-oscillator equations can be derived from first principles. This is an extension of earlier work that led to a single energy equation describing the fluid-structure interaction. It is demonstrated here that flow-oscillator models are a subclass of the general, physical-based framework. A flow-oscillator model is a reduced-order mechanical model, generally comprising two mechanical oscillators, one modelling the structural oscillation and the other a nonlinear oscillator representing the fluid behaviour coupled to the structural motion.Reduced-order analytical model development continues to be carried out using a Hamilton's principle-based variational approach. This provides flexibility in the long run for generalizing the modelling paradigm to complex, three-dimensional problems with multiple degrees of freedom, although such extension is very difficult. As both experimental and analytical capabilities advance, the critical research path to developing and implementing fluid-structure interaction models entails-formulating generalized equations of motion, as a superset of the flow-oscillator models; and-developing experimentally derived, semi-analytical functions to describe key terms in the governing equations of motion. The developed variational approach yields a system of governing equations. This will allow modelling of multiple d.f. systems. The extensions derived generalize the Hamilton's variational formulation for such problems. The Navier-Stokes equations are derived and coupled to the structural oscillator. This general model has been shown to be a superset of the flow-oscillator model. Based on different assumptions, one can derive a variety of flow-oscillator models.
Capillary waveguide optrodes: an approach to optical sensing in medical diagnostics
NASA Astrophysics Data System (ADS)
Lippitsch, Max E.; Draxler, Sonja; Kieslinger, Dietmar; Lehmann, Hartmut; Weigl, Bernhard H.
1996-07-01
Glass capillaries with a chemically sensitive coating on the inner surface are used as optical sensors for medical diagnostics. A capillary simultaneously serves as a sample compartment, a sensor element, and an inhomogeneous optical waveguide. Various detection schemes based on absorption, fluorescence intensity, or fluorescence lifetime are described. In absorption-based capillary waveguide optrodes the absorption in the sensor layer is analyte dependent; hence light transmission along the inhomogeneous waveguiding structure formed by the capillary wall and the sensing layer is a function of the analyte concentration. Similarly, in fluorescence-based capillary optrodes the fluorescence intensity or the fluorescence lifetime of an indicator dye fixed in the sensing layer is analyte dependent; thus the specific property of fluorescent light excited in the sensing layer and thereafter guided along the inhomogeneous waveguiding structure is a function of the analyte concentration. Both schemes are experimentally demonstrated, one with carbon dioxide as the analyte and the other one with oxygen. The device combines optical sensors with the standard glass capillaries usually applied to gather blood drops from fingertips, to yield a versatile diagnostic instrument, integrating the sample compartment, the optical sensor, and the light-collecting optics into a single piece. This ensures enhanced sensor performance as well as improved handling compared with other sensors. waveguide, blood gases, medical diagnostics.
Optimal guidance law development for an advanced launch system
NASA Technical Reports Server (NTRS)
Calise, Anthony J.; Leung, Martin S. K.
1995-01-01
The objective of this research effort was to develop a real-time guidance approach for launch vehicles ascent to orbit injection. Various analytical approaches combined with a variety of model order and model complexity reduction have been investigated. Singular perturbation methods were first attempted and found to be unsatisfactory. The second approach based on regular perturbation analysis was subsequently investigated. It also fails because the aerodynamic effects (ignored in the zero order solution) are too large to be treated as perturbations. Therefore, the study demonstrates that perturbation methods alone (both regular and singular perturbations) are inadequate for use in developing a guidance algorithm for the atmospheric flight phase of a launch vehicle. During a second phase of the research effort, a hybrid analytic/numerical approach was developed and evaluated. The approach combines the numerical methods of collocation and the analytical method of regular perturbations. The concept of choosing intelligent interpolating functions is also introduced. Regular perturbation analysis allows the use of a crude representation for the collocation solution, and intelligent interpolating functions further reduce the number of elements without sacrificing the approximation accuracy. As a result, the combined method forms a powerful tool for solving real-time optimal control problems. Details of the approach are illustrated in a fourth order nonlinear example. The hybrid approach is then applied to the launch vehicle problem. The collocation solution is derived from a bilinear tangent steering law, and results in a guidance solution for the entire flight regime that includes both atmospheric and exoatmospheric flight phases.
Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill
2012-01-01
In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226
Tschandl, P; Kittler, H; Schmid, K; Zalaudek, I; Argenziano, G
2015-06-01
There are two strategies to approach the dermatoscopic diagnosis of pigmented skin tumours, namely the verbal-based analytic and the more visual-global heuristic method. It is not known if one or the other is more efficient in teaching dermatoscopy. To compare two teaching methods in short-term training of dermatoscopy to medical students. Fifty-seven medical students in the last year of the curriculum were given a 1-h lecture of either the heuristic- or the analytic-based teaching of dermatoscopy. Before and after this session, they were shown the same 50 lesions and asked to diagnose them and rate for chance of malignancy. Test lesions consisted of melanomas, basal cell carcinomas, nevi, seborrhoeic keratoses, benign vascular tumours and dermatofibromas. Performance measures were diagnostic accuracy regarding malignancy as measured by the area under the curves of receiver operating curves (range: 0-1), as well as per cent correct diagnoses (range: 0-100%). Diagnostic accuracy as well as per cent correct diagnoses increased by +0.21 and +32.9% (heuristic teaching) and +0.19 and +35.7% (analytic teaching) respectively (P for all <0.001). Neither for diagnostic accuracy (P = 0.585), nor for per cent correct diagnoses (P = 0.298) was a difference between the two groups. Short-term training of dermatoscopy to medical students allows significant improvement in diagnostic abilities. Choosing a heuristic or analytic method does not have an influence on this effect in short training using common pigmented skin lesions. © 2014 European Academy of Dermatology and Venereology.
Quantifying Seepage Flux using Sediment Temperatures
This report provides a demonstration of different modeling approaches that use sediment temperatures to estimate the magnitude and direction of water flux across the groundwater-surface water transition zone. Analytical models based on steady-state or transient temperature solut...
Performance characterization of material identification systems
NASA Astrophysics Data System (ADS)
Brown, Christopher D.; Green, Robert L.
2006-10-01
In recent years a number of analytical devices have been proposed and marketed specifically to enable field-based material identification. Technologies reliant on mass, near- and mid-infrared, and Raman spectroscopies are available today, and other platforms are imminent. These systems tend to perform material recognition based on an on-board library of material signatures. While figures of merit for traditional quantitative analytical sensors are broadly established (e.g., SNR, selectivity, sensitivity, limit of detection/decision), measures of performance for material identification systems have not been systematically discussed. In this paper we present an approach to performance characterization similar in spirit to ROC curves, but including elements of precision-recall curves and specialized for the intended-use of material identification systems. Important experimental considerations are discussed, including study design, sources of bias, uncertainty estimation, and cross-validation and the approach as a whole is illustrated using a commercially available handheld Raman material identification system.
Tate, Jillian R; Sikaris, Ken A; Jones, Graham RD; Yen, Tina; Koerbin, Gus; Ryan, Julie; Reed, Maxine; Gill, Janice; Koumantakis, George; Hickman, Peter; Graham, Peter
2014-01-01
Scientific evidence supports the use of common reference intervals (RIs) for many general chemistry analytes, in particular those with sound calibration and traceability in place. Already the Nordic countries and United Kingdom have largely achieved harmonised RIs. Following a series of workshops organised by the Australasian Association of Clinical Biochemists (AACB) between 2012 and 2014 at which an evidence-based approach for determination of common intervals was developed, pathology organisations in Australia and New Zealand have reached a scientific consensus on what adult and paediatric intervals we should use across Australasia. The aim of this report is to describe the processes that the AACB and the Royal College of Pathologists of Australasia have taken towards recommending the implementation of a first panel of common RIs for use in Australasia. PMID:25678727
Nekhay, Olexandr; Arriaza, Manuel; Boerboom, Luc
2009-07-01
The study presents an approach that combined objective information such as sampling or experimental data with subjective information such as expert opinions. This combined approach was based on the Analytic Network Process method. It was applied to evaluate soil erosion risk and overcomes one of the drawbacks of USLE/RUSLE soil erosion models, namely that they do not consider interactions among soil erosion factors. Another advantage of this method is that it can be used if there are insufficient experimental data. The lack of experimental data can be compensated for through the use of expert evaluations. As an example of the proposed approach, the risk of soil erosion was evaluated in olive groves in Southern Spain, showing the potential of the ANP method for modelling a complex physical process like soil erosion.
NASA Astrophysics Data System (ADS)
S, Chidambara Raja; P, Karthikeyan; Kumaraswamidhas, L. A.; M, Ramu
2018-05-01
Most of the thermal design systems involve two phase materials and analysis of such systems requires detailed understanding of the thermal characteristics of the two phase material. This article aimed to develop geometry dependent unit cell approach model by considering the effects of all primary parameters (conductivity ratio and concentration) and secondary parameters (geometry, contact resistance, natural convection, Knudsen and radiation) for the estimation of effective thermal conductivity of two-phase materials. The analytical equations have been formulated based on isotherm approach for 2-D and 3-D spatially periodic medium. The developed models are validated with standard models and suited for all kind of operating conditions. The results have shown substantial improvement compared to the existing models and are in good agreement with the experimental data.
NASA Technical Reports Server (NTRS)
Idris, Husni; Vivona, Robert; Garcia-Chico, Jose L.
2008-01-01
This document describes preliminary research on a distributed, trajectory-oriented approach for traffic complexity management. The approach is to manage traffic complexity in a distributed control environment, based on preserving trajectory flexibility and minimizing constraints. In particular, the document presents an analytical framework to study trajectory flexibility and the impact of trajectory constraints on it. The document proposes preliminary flexibility metrics that can be interpreted and measured within the framework.
Gika, Helen G; Theodoridis, Georgios A; Earll, Mark; Wilson, Ian D
2012-09-01
An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.
Metabolomics and Diabetes: Analytical and Computational Approaches
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
Rodushkin, I; Bergman, T; Douglas, G; Engström, E; Sörlin, D; Baxter, D C
2007-02-05
Different analytical approaches for origin differentiation between vendace and whitefish caviars from brackish- and freshwaters were tested using inductively coupled plasma double focusing sector field mass spectrometry (ICP-SFMS) and multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). These approaches involve identifying differences in elemental concentrations or sample-specific isotopic composition (Sr and Os) variations. Concentrations of 72 elements were determined by ICP-SFMS following microwave-assisted digestion in vendace and whitefish caviar samples from Sweden (from both brackish and freshwater), Finland and USA, as well as in unprocessed vendace roe and salt used in caviar production. This data set allows identification of elements whose contents in caviar can be affected by salt addition as well as by contamination during production and packaging. Long-term method reproducibility was assessed for all analytes based on replicate caviar preparations/analyses and variations in element concentrations in caviar from different harvests were evaluated. The greatest utility for differentiation was demonstrated for elements with varying concentrations between brackish and freshwaters (e.g. As, Br, Sr). Elemental ratios, specifically Sr/Ca, Sr/Mg and Sr/Ba, are especially useful for authentication of vendace caviar processed from brackish water roe, due to the significant differences between caviar from different sources, limited between-harvest variations and relatively high concentrations in samples, allowing precise determination by modern analytical instrumentation. Variations in the 87Sr/86Sr ratio for vendace caviar from different harvests (on the order of 0.05-0.1%) is at least 10-fold less than differences between caviar processed from brackish and freshwater roe. Hence, Sr isotope ratio measurements (either by ICP-SFMS or by MC-ICP-MS) have great potential for origin differentiation. On the contrary, it was impossible to differentiate between Swedish caviar processed from brackish water roe and Finnish freshwater caviar based solely on 187Os/188Os ratios.
Rebecca McLain; Melissa R. Poe; Kelly Biedenweg; Lee K. Cerveny; Diane Besser; Dale J. Blahna
2013-01-01
Ecosystem-based planning and management have stimulated the need to gather sociocultural values and human uses of land in formats accessible to diverse planners and researchers. Human Ecology Mapping (HEM) approaches offer promising spatial data gathering and analytical tools, while also addressing important questions about human-landscape connections. This article...
ERIC Educational Resources Information Center
Luan, Jing; Zhao, Chun-Mei; Hayek, John C.
2009-01-01
Data mining provides both systematic and systemic ways to detect patterns of student engagement among students at hundreds of institutions. Using traditional statistical techniques alone, the task would be significantly difficult--if not impossible--considering the size and complexity in both data and analytical approaches necessary for this…
ERIC Educational Resources Information Center
Schaber, Peter M.; Hobika, Geoffrey
2018-01-01
The case study approach provides students with a better appreciation of how scientists solve problems and conduct themselves in the "real world". When applied to the undergraduate chemistry laboratory, this approach also challenges critical thinking skills and creativity in ways "cook book" experiments very often do not. This…
ERIC Educational Resources Information Center
Janson, Harald; Mathiesen, Kristin S.
2008-01-01
The authors applied I-States as Objects Analysis (ISOA), a recently proposed person-oriented analytic approach, to the study of temperament development in 921 Norwegian children from a population-based sample. A 5-profile classification based on cluster analysis of standardized mother reports of activity, sociability, emotionality, and shyness at…
Improving Workplace-Based Assessment and Feedback by an E-Portfolio Enhanced with Learning Analytics
ERIC Educational Resources Information Center
van der Schaaf, Marieke; Donkers, Jeroen; Slof, Bert; Moonen-van Loon, Joyce; van Tartwijk, Jan; Driessen, Eric; Badii, Atta; Serban, Ovidiu; Ten Cate, Olle
2017-01-01
Electronic portfolios (E-portfolios) are crucial means for workplace-based assessment and feedback. Although E-portfolios provide a useful approach to view each learner's progress, so far options for personalized feedback and potential data about a learner's performances at the workplace often remain unexploited. This paper advocates that…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sprenger, Lisa, E-mail: Lisa.Sprenger@tu-dresden.de; Lange, Adrian; Odenbach, Stefan
2013-12-15
Ferrofluids are colloidal suspensions consisting of magnetic nanoparticles dispersed in a carrier liquid. Their thermodiffusive behaviour is rather strong compared to molecular binary mixtures, leading to a Soret coefficient (S{sub T}) of 0.16 K{sup −1}. Former experiments with dilute magnetic fluids have been done with thermogravitational columns or horizontal thermodiffusion cells by different research groups. Considering the horizontal thermodiffusion cell, a former analytical approach has been used to solve the phenomenological diffusion equation in one dimension assuming a constant concentration gradient over the cell's height. The current experimental work is based on the horizontal separation cell and emphasises the comparison ofmore » the concentration development in different concentrated magnetic fluids and at different temperature gradients. The ferrofluid investigated is the kerosene-based EMG905 (Ferrotec) to be compared with the APG513A (Ferrotec), both containing magnetite nanoparticles. The experiments prove that the separation process linearly depends on the temperature gradient and that a constant concentration gradient develops in the setup due to the separation. Analytical one dimensional and numerical three dimensional approaches to solve the diffusion equation are derived to be compared with the solution used so far for dilute fluids to see if formerly made assumptions also hold for higher concentrated fluids. Both, the analytical and numerical solutions, either in a phenomenological or a thermodynamic description, are able to reproduce the separation signal gained from the experiments. The Soret coefficient can then be determined to 0.184 K{sup −1} in the analytical case and 0.29 K{sup −1} in the numerical case. Former theoretical approaches for dilute magnetic fluids underestimate the strength of the separation in the case of a concentrated ferrofluid.« less
Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady
2017-09-01
Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.
The evolution of analytical chemistry methods in foodomics.
Gallo, Monica; Ferranti, Pasquale
2016-01-08
The methodologies of food analysis have greatly evolved over the past 100 years, from basic assays based on solution chemistry to those relying on the modern instrumental platforms. Today, the development and optimization of integrated analytical approaches based on different techniques to study at molecular level the chemical composition of a food may allow to define a 'food fingerprint', valuable to assess nutritional value, safety and quality, authenticity and security of foods. This comprehensive strategy, defined foodomics, includes emerging work areas such as food chemistry, phytochemistry, advanced analytical techniques, biosensors and bioinformatics. Integrated approaches can help to elucidate some critical issues in food analysis, but also to face the new challenges of a globalized world: security, sustainability and food productions in response to environmental world-wide changes. They include the development of powerful analytical methods to ensure the origin and quality of food, as well as the discovery of biomarkers to identify potential food safety problems. In the area of nutrition, the future challenge is to identify, through specific biomarkers, individual peculiarities that allow early diagnosis and then a personalized prognosis and diet for patients with food-related disorders. Far from the aim of an exhaustive review of the abundant literature dedicated to the applications of omic sciences in food analysis, we will explore how classical approaches, such as those used in chemistry and biochemistry, have evolved to intersect with the new omics technologies to produce a progress in our understanding of the complexity of foods. Perhaps most importantly, a key objective of the review will be to explore the development of simple and robust methods for a fully applied use of omics data in food science. Copyright © 2015 Elsevier B.V. All rights reserved.
Purely numerical approach for analyzing flow to a well intercepting a vertical fracture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Narasimhan, T.N.; Palen, W.A.
1979-03-01
A numerical method, based on an Integral Finite Difference approach, is presented to investigate wells intercepting fractures in general and vertical fractures in particular. Such features as finite conductivity, wellbore storage, damage, and fracture deformability and its influence as permeability are easily handled. The advantage of the numerical approach is that it is based on fewer assumptions than analytic solutions and hence has greater generality. Illustrative examples are given to validate the method against known solutions. New results are presenteed to demonstrate the applicability of the method to problems not apparently considered in the literature so far.
Tensor scale: An analytic approach with efficient computation and applications☆
Xu, Ziyue; Saha, Punam K.; Dasgupta, Soura
2015-01-01
Scale is a widely used notion in computer vision and image understanding that evolved in the form of scale-space theory where the key idea is to represent and analyze an image at various resolutions. Recently, we introduced a notion of local morphometric scale referred to as “tensor scale” using an ellipsoidal model that yields a unified representation of structure size, orientation and anisotropy. In the previous work, tensor scale was described using a 2-D algorithmic approach and a precise analytic definition was missing. Also, the application of tensor scale in 3-D using the previous framework is not practical due to high computational complexity. In this paper, an analytic definition of tensor scale is formulated for n-dimensional (n-D) images that captures local structure size, orientation and anisotropy. Also, an efficient computational solution in 2- and 3-D using several novel differential geometric approaches is presented and the accuracy of results is experimentally examined. Also, a matrix representation of tensor scale is derived facilitating several operations including tensor field smoothing to capture larger contextual knowledge. Finally, the applications of tensor scale in image filtering and n-linear interpolation are presented and the performance of their results is examined in comparison with respective state-of-art methods. Specifically, the performance of tensor scale based image filtering is compared with gradient and Weickert’s structure tensor based diffusive filtering algorithms. Also, the performance of tensor scale based n-linear interpolation is evaluated in comparison with standard n-linear and windowed-sinc interpolation methods. PMID:26236148
SensePath: Understanding the Sensemaking Process Through Analytic Provenance.
Nguyen, Phong H; Xu, Kai; Wheat, Ashley; Wong, B L William; Attfield, Simon; Fields, Bob
2016-01-01
Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process.
NASA Technical Reports Server (NTRS)
Dubinskiy, Mark A.; Kamal, Mohammed M.; Misra, Prabhaker
1995-01-01
The availability of manned laboratory facilities in space offers wonderful opportunities and challenges in microgravity combustion science and technology. In turn, the fundamentals of microgravity combustion science can be studied via spectroscopic characterization of free radicals generated in flames. The laser-induced fluorescence (LIF) technique is a noninvasive method of considerable utility in combustion physics and chemistry suitable for monitoring not only specific species and their kinetics, but it is also important for imaging of flames. This makes LIF one of the most important tools for microgravity combustion science. Flame characterization under microgravity conditions using LIF is expected to be more informative than other methods aimed at searching for effects like pumping phenomenon that can be modeled via ground level experiments. A primary goal of our work consisted in working out an innovative approach to devising an LIF-based analytical unit suitable for in-space flame characterization. It was decided to follow two approaches in tandem: (1) use the existing laboratory (non-portable) equipment and determine the optimal set of parameters for flames that can be used as analytical criteria for flame characterization under microgravity conditions; and (2) use state-of-the-art developments in laser technology and concentrate some effort in devising a layout for the portable analytical equipment. This paper presents an up-to-date summary of the results of our experiments aimed at the creation of the portable device for combustion studies in a microgravity environment, which is based on a portable UV tunable solid-state laser for excitation of free radicals normally present in flames in detectable amounts. A systematic approach has allowed us to make a convenient choice of species under investigation, as well as the proper tunable laser system, and also enabled us to carry out LIF experiments on free radicals using a solid-state laser tunable in the UV.
ERIC Educational Resources Information Center
Chen, Jinshi
2017-01-01
Legal case brief writing is pedagogically important yet insufficiently discussed for Chinese EFL learners majoring in law. Based on process genre approach and discourse information theory (DIT), the present study designs a corpus-based analytical model for Chinese EFL learners' autonomy in legal case brief writing and explores the process of case…
DOE Office of Scientific and Technical Information (OSTI.GOV)
P Yu
Unlike traditional 'wet' analytical methods which during processing for analysis often result in destruction or alteration of the intrinsic protein structures, advanced synchrotron radiation-based Fourier transform infrared microspectroscopy has been developed as a rapid and nondestructive and bioanalytical technique. This cutting-edge synchrotron-based bioanalytical technology, taking advantages of synchrotron light brightness (million times brighter than sun), is capable of exploring the molecular chemistry or structure of a biological tissue without destruction inherent structures at ultra-spatial resolutions. In this article, a novel approach is introduced to show the potential of the advanced synchrotron-based analytical technology, which can be used to study plant-basedmore » food or feed protein molecular structure in relation to nutrient utilization and availability. Recent progress was reported on using synchrotron-based bioanalytical technique synchrotron radiation-based Fourier transform infrared microspectroscopy and diffused reflectance infrared Fourier transform spectroscopy to detect the effects of gene-transformation (Application 1), autoclaving (Application 2), and bio-ethanol processing (Application 3) on plant-based food and feed protein structure changes on a molecular basis. The synchrotron-based technology provides a new approach for plant-based protein structure research at ultra-spatial resolutions at cellular and molecular levels.« less
Guise, Jeanne-Marie; Chang, Christine; Viswanathan, Meera; Glick, Susan; Treadwell, Jonathan; Umscheid, Craig A; Whitlock, Evelyn; Fu, Rongwei; Berliner, Elise; Paynter, Robin; Anderson, Johanna; Motu'apuaka, Pua; Trikalinos, Tom
2014-11-01
The purpose of this Agency for Healthcare Research and Quality Evidence-based Practice Center methods white paper was to outline approaches to conducting systematic reviews of complex multicomponent health care interventions. We performed a literature scan and conducted semistructured interviews with international experts who conduct research or systematic reviews of complex multicomponent interventions (CMCIs) or organizational leaders who implement CMCIs in health care. Challenges identified include lack of consistent terminology for such interventions (eg, complex, multicomponent, multidimensional, multifactorial); a wide range of approaches used to frame the review, from grouping interventions by common features to using more theoretical approaches; decisions regarding whether and how to quantitatively analyze the interventions, from holistic to individual component analytic approaches; and incomplete and inconsistent reporting of elements critical to understanding the success and impact of multicomponent interventions, such as methods used for implementation the context in which interventions are implemented. We provide a framework for the spectrum of conceptual and analytic approaches to synthesizing studies of multicomponent interventions and an initial list of critical reporting elements for such studies. This information is intended to help systematic reviewers understand the options and tradeoffs available for such reviews. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Huang, Ching-Sheng; Yeh, Hund-Der
2016-11-01
This study introduces an analytical approach to estimate drawdown induced by well extraction in a heterogeneous confined aquifer with an irregular outer boundary. The aquifer domain is divided into a number of zones according to the zonation method for representing the spatial distribution of a hydraulic parameter field. The lateral boundary of the aquifer can be considered under the Dirichlet, Neumann or Robin condition at different parts of the boundary. Flow across the interface between two zones satisfies the continuities of drawdown and flux. Source points, each of which has an unknown volumetric rate representing the boundary effect on the drawdown, are allocated around the boundary of each zone. The solution of drawdown in each zone is expressed as a series in terms of the Theis equation with unknown volumetric rates from the source points. The rates are then determined based on the aquifer boundary conditions and the continuity requirements. The estimated aquifer drawdown by the present approach agrees well with a finite element solution developed based on the Mathematica function NDSolve. As compared with the existing numerical approaches, the present approach has a merit of directly computing the drawdown at any given location and time and therefore takes much less computing time to obtain the required results in engineering applications.
Kyriakou, Adamos; Neufeld, Esra; Werner, Beat; Székely, Gábor; Kuster, Niels
2015-01-01
Transcranial focused ultrasound (tcFUS) is an attractive noninvasive modality for neurosurgical interventions. The presence of the skull, however, compromises the efficiency of tcFUS therapy, as its heterogeneous nature and acoustic characteristics induce significant distortion of the acoustic energy deposition, focal shifts, and thermal gain decrease. Phased-array transducers allow for partial compensation of skull-induced aberrations by application of precalculated phase and amplitude corrections. An integrated numerical framework allowing for 3D full-wave, nonlinear acoustic and thermal simulations has been developed and applied to tcFUS. Simulations were performed to investigate the impact of skull aberrations, the possibility of extending the treatment envelope, and adverse secondary effects. The simulated setup comprised an idealized model of the ExAblate Neuro and a detailed MR-based anatomical head model. Four different approaches were employed to calculate aberration corrections (analytical calculation of the aberration corrections disregarding tissue heterogeneities; a semi-analytical ray-tracing approach compensating for the presence of the skull; two simulation-based time-reversal approaches with and without pressure amplitude corrections which account for the entire anatomy). These impact of these approaches on the pressure and temperature distributions were evaluated for 22 brain-targets. While (semi-)analytical approaches failed to induced high pressure or ablative temperatures in any but the targets in the close vicinity of the geometric focus, simulation-based approaches indicate the possibility of considerably extending the treatment envelope (including targets below the transducer level and locations several centimeters off the geometric focus), generation of sharper foci, and increased targeting accuracy. While the prediction of achievable aberration correction appears to be unaffected by the detailed bone-structure, proper consideration of inhomogeneity is required to predict the pressure distribution for given steering parameters. Simulation-based approaches to calculate aberration corrections may aid in the extension of the tcFUS treatment envelope as well as predict and avoid secondary effects (standing waves, skull heating). Due to their superior performance, simulationbased techniques may prove invaluable in the amelioration of skull-induced aberration effects in tcFUS therapy. The next steps are to investigate shear-wave-induced effects in order to reliably exclude secondary hot-spots, and to develop comprehensive uncertainty assessment and validation procedures.
ANALYTiC: An Active Learning System for Trajectory Classification.
Soares Junior, Amilcar; Renso, Chiara; Matwin, Stan
2017-01-01
The increasing availability and use of positioning devices has resulted in large volumes of trajectory data. However, semantic annotations for such data are typically added by domain experts, which is a time-consuming task. Machine-learning algorithms can help infer semantic annotations from trajectory data by learning from sets of labeled data. Specifically, active learning approaches can minimize the set of trajectories to be annotated while preserving good performance measures. The ANALYTiC web-based interactive tool visually guides users through this annotation process.
Liu, Min; Zhang, Chunsun; Liu, Feifei
2015-09-03
In this work, we first introduce the fabrication of microfluidic cloth-based analytical devices (μCADs) using a wax screen-printing approach that is suitable for simple, inexpensive, rapid, low-energy-consumption and high-throughput preparation of cloth-based analytical devices. We have carried out a detailed study on the wax screen-printing of μCADs and have obtained some interesting results. Firstly, an analytical model is established for the spreading of molten wax in cloth. Secondly, a new wax screen-printing process has been proposed for fabricating μCADs, where the melting of wax into the cloth is much faster (∼5 s) and the heating temperature is much lower (75 °C). Thirdly, the experimental results show that the patterning effects of the proposed wax screen-printing method depend to a certain extent on types of screens, wax melting temperatures and melting time. Under optimized conditions, the minimum printing width of hydrophobic wax barrier and hydrophilic channel is 100 μm and 1.9 mm, respectively. Importantly, the developed analytical model is also well validated by these experiments. Fourthly, the μCADs fabricated by the presented wax screen-printing method are used to perform a proof-of-concept assay of glucose or protein in artificial urine with rapid high-throughput detection taking place on a 48-chamber cloth-based device and being performed by a visual readout. Overall, the developed cloth-based wax screen-printing and arrayed μCADs should provide a new research direction in the development of advanced sensor arrays for detection of a series of analytes relevant to many diverse applications. Copyright © 2015 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Logan, J. R.; Pulvermacher, M. K.
1991-01-01
Range Scheduling Aid (RSA) is presented in the form of the viewgraphs. The following subject areas are covered: satellite control network; current and new approaches to range scheduling; MITRE tasking; RSA features; RSA display; constraint based analytic capability; RSA architecture; and RSA benefits.
Adverse outcome pathway networks II: Network analytics
The US EPA is developing more cost effective and efficient ways to evaluate chemical safety using high throughput and computationally based testing strategies. An important component of this approach is the ability to translate chemical effects on fundamental biological processes...
Semi-analytical approach to estimate railroad tank car shell puncture
DOT National Transportation Integrated Search
2011-03-16
This paper describes the development of engineering-based equations to estimate the puncture resistance of railroad tank cars under a generalized shell or side impact scenario. Resistance to puncture is considered in terms of puncture velocity, which...
1992-12-01
from several intellectual subfields, various re- searchers have produced lists of intersegment relations - from philosophers (e.g., [ Toulmin 5k]) to...Approach Integrating Case-Based and Analytical Methods. Ph.D. dissertation, Georgia Institute of Technology. [ Toulmin 58] Toulmin , S. 1958. The Uses of
New vistas in refractive laser beam shaping with an analytic design approach
NASA Astrophysics Data System (ADS)
Duerr, Fabian; Thienpont, Hugo
2014-05-01
Many commercial, medical and scientific applications of the laser have been developed since its invention. Some of these applications require a specific beam irradiance distribution to ensure optimal performance. Often, it is possible to apply geometrical methods to design laser beam shapers. This common design approach is based on the ray mapping between the input plane and the output beam. Geometric ray mapping designs with two plano-aspheric lenses have been thoroughly studied in the past. Even though analytic expressions for various ray mapping functions do exist, the surface profiles of the lenses are still calculated numerically. In this work, we present an alternative novel design approach that allows direct calculation of the rotational symmetric lens profiles described by analytic functions. Starting from the example of a basic beam expander, a set of functional differential equations is derived from Fermat's principle. This formalism allows calculating the exact lens profiles described by Taylor series coefficients up to very high orders. To demonstrate the versatility of this new approach, two further cases are solved: a Gaussian to at-top irradiance beam shaping system, and a beam shaping system that generates a more complex dark-hollow Gaussian (donut-like) irradiance profile with zero intensity in the on-axis region. The presented ray tracing results confirm the high accuracy of all calculated solutions and indicate the potential of this design approach for refractive beam shaping applications.
Cassidy, Liam; Prasse, Daniela; Linke, Dennis; Schmitz, Ruth A; Tholey, Andreas
2016-10-07
The recent discovery of an increasing number of small open reading frames (sORF) creates the need for suitable analytical technologies for the comprehensive identification of the corresponding gene products. For biological and functional studies the knowledge of the entire set of proteins and sORF gene products is essential. Consequently in the present study we evaluated analytical approaches that will allow for simultaneous analysis of widest parts of the proteome together with the predicted sORF. We performed a full proteome analysis of the methane producing archaeon Methanosarcina mazei strain Gö1 cytosolic proteome using a high/low pH reversed phase LC-MS bottom-up approach. The second analytical approach was based on semi-top-down strategy, encompassing a separation at intact protein level using a GelFree system, followed by digestion and LC-MS analysis. A high overlap in identified proteins was found for both approaches yielding the most comprehensive coverage of the cytosolic proteome of this organism achieved so far. The application of the second approach in combination with an adjustment of the search criteria for database searches further led to a significant increase of sORF peptide identifications, finally allowing to detect and identify 28 sORF gene products.
Shao, Jingyuan; Cao, Wen; Qu, Haibin; Pan, Jianyang; Gong, Xingchu
2018-01-01
The aim of this study was to present a novel analytical quality by design (AQbD) approach for developing an HPLC method to analyze herbal extracts. In this approach, critical method attributes (CMAs) and critical method parameters (CMPs) of the analytical method were determined using the same data collected from screening experiments. The HPLC-ELSD method for separation and quantification of sugars in Codonopsis Radix extract (CRE) samples and Astragali Radix extract (ARE) samples was developed as an example method with a novel AQbD approach. Potential CMAs and potential CMPs were found with Analytical Target Profile. After the screening experiments, the retention time of the D-glucose peak of CRE samples, the signal-to-noise ratio of the D-glucose peak of CRE samples, and retention time of the sucrose peak in ARE samples were considered CMAs. The initial and final composition of the mobile phase, flow rate, and column temperature were found to be CMPs using a standard partial regression coefficient method. The probability-based design space was calculated using a Monte-Carlo simulation method and verified by experiments. The optimized method was validated to be accurate and precise, and then it was applied in the analysis of CRE and ARE samples. The present AQbD approach is efficient and suitable for analysis objects with complex compositions.
Delgado, Alejandra; Posada-Ureta, Oscar; Olivares, Maitane; Vallejo, Asier; Etxebarria, Nestor
2013-12-15
In this study a priority organic pollutants usually found in environmental water samples were considered to accomplish two extraction and analysis approaches. Among those compounds organochlorine compounds, pesticides, phthalates, phenols and residues of pharmaceutical and personal care products were included. The extraction and analysis steps were based on silicone rod extraction (SR) followed by liquid desorption in combination with large volume injection-programmable temperature vaporiser (LVI-PTV) and gas chromatography-mass spectrometry (GC-MS). Variables affecting the analytical response as a function of the programmable temperature vaporiser (PTV) parameters were firstly optimised following an experimental design approach. The SR extraction and desorption conditions were assessed afterwards, including matrix modification, time extraction, and stripping solvent composition. Subsequently, the possibility of performing membrane enclosed sorptive coating extraction (MESCO) as a modified extraction approach was also evaluated. The optimised method showed low method detection limits (3-35 ng L(-1)), acceptable accuracy (78-114%) and precision values (<13%) for most of the studied analytes regardless of the aqueous matrix. Finally, the developed approach was successfully applied to the determination of target analytes in aqueous environmental matrices including estuarine and wastewater samples. © 2013 Elsevier B.V. All rights reserved.
Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya
2018-05-01
Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.
Screening new psychoactive substances in urban wastewater using high resolution mass spectrometry.
González-Mariño, Iria; Gracia-Lor, Emma; Bagnati, Renzo; Martins, Claudia P B; Zuccato, Ettore; Castiglioni, Sara
2016-06-01
Analysis of drug residues in urban wastewater could complement epidemiological studies in detecting the use of new psychoactive substances (NPS), a continuously changing group of drugs hard to monitor by classical methods. We initially selected 52 NPS potentially used in Italy based on seizure data and consumption alerts provided by the Antidrug Police Department and the National Early Warning System. Using a linear ion trap-Orbitrap high resolution mass spectrometer, we designed a suspect screening and a target method approach and compared them for the analysis of 24 h wastewater samples collected at the treatment plant influents of four Italian cities. This highlighted the main limitations of these two approaches, so we could propose requirements for future research. A library of MS/MS spectra of 16 synthetic cathinones and 19 synthetic cannabinoids, for which analytical standards were acquired, was built at different collision energies and is available on request. The stability of synthetic cannabinoids was studied in analytical standards and wastewater, identifying the best analytical conditions for future studies. To the best of our knowledge, these are the first stability data on NPS. Few suspects were identified in Italian wastewater samples, in accordance with recent epidemiological data reporting a very low prevalence of use of NPS in Italy. This study outlines an analytical approach for NPS identification and measurement in urban wastewater and for estimating their use in the population.
Peraman, R.; Bhadraya, K.; Reddy, Y. Padmanabha; Reddy, C. Surayaprakash; Lokesh, T.
2015-01-01
By considering the current regulatory requirement for an analytical method development, a reversed phase high performance liquid chromatographic method for routine analysis of etofenamate in dosage form has been optimized using analytical quality by design approach. Unlike routine approach, the present study was initiated with understanding of quality target product profile, analytical target profile and risk assessment for method variables that affect the method response. A liquid chromatography system equipped with a C18 column (250×4.6 mm, 5 μ), a binary pump and photodiode array detector were used in this work. The experiments were conducted based on plan by central composite design, which could save time, reagents and other resources. Sigma Tech software was used to plan and analyses the experimental observations and obtain quadratic process model. The process model was used for predictive solution for retention time. The predicted data from contour diagram for retention time were verified actually and it satisfied with actual experimental data. The optimized method was achieved at 1.2 ml/min flow rate of using mobile phase composition of methanol and 0.2% triethylamine in water at 85:15, % v/v, pH adjusted to 6.5. The method was validated and verified for targeted method performances, robustness and system suitability during method transfer. PMID:26997704
Analytical optical scattering in clouds
NASA Technical Reports Server (NTRS)
Phanord, Dieudonne D.
1989-01-01
An analytical optical model for scattering of light due to lightning by clouds of different geometry is being developed. The self-consistent approach and the equivalent medium concept of Twersky was used to treat the case corresponding to outside illumination. Thus, the resulting multiple scattering problem is transformed with the knowledge of the bulk parameters, into scattering by a single obstacle in isolation. Based on the size parameter of a typical water droplet as compared to the incident wave length, the problem for the single scatterer equivalent to the distribution of cloud particles can be solved either by Mie or Rayleigh scattering theory. The super computing code of Wiscombe can be used immediately to produce results that can be compared to the Monte Carlo computer simulation for outside incidence. A fairly reasonable inverse approach using the solution of the outside illumination case was proposed to model analytically the situation for point sources located inside the thick optical cloud. Its mathematical details are still being investigated. When finished, it will provide scientists an enhanced capability to study more realistic clouds. For testing purposes, the direct approach to the inside illumination of clouds by lightning is under consideration. Presently, an analytical solution for the cubic cloud will soon be obtained. For cylindrical or spherical clouds, preliminary results are needed for scattering by bounded obstacles above or below a penetrable surface interface.
The intrinsic fluorescence of FAD and its application in analytical chemistry: a review
NASA Astrophysics Data System (ADS)
Galbán, Javier; Sanz-Vicente, Isabel; Navarro, Jesús; de Marcos, Susana
2016-12-01
This review (with 106 references) mainly deals with the analytical applications of flavin-adenine dinucleotide (FAD) fluorescence. In the first section, the spectroscopic properties of this compound are reviewed at the light of his different acid-base, oxidation and structural forms; the chemical and spectroscopic properties of flavin mononucleotide (FMN) and other flavins will be also briefly discussed. The second section discusses how the properties of FAD fluorescence changes in flavoenzymes (FvEs), again considering the different chemical and structural forms; the glucose oxidase (GOx) and the choline oxidase (ChOx) cases will be commented. Since almost certainly the most reported analytical application of FAD fluorescence is as an auto-indicator in enzymatic methods catalysed by FvE oxidoreductases, it is important to know how the concentrations of the different forms of FAD changes along the reaction and, consequently, the fluorescence and the analytical signals. An approach to do this will be presented in section 3. The fourth part of the paper compiles the analytical applications which have been reported until now based in these fluorescence properties. Finally, some suggestions about tentative future research are also given.
The intrinsic fluorescence of FAD and its application in analytical chemistry: a review.
Galbán, Javier; Sanz-Vicente, Isabel; Navarro, Jesús; de Marcos, Susana
2016-12-19
This review (with 106 references) mainly deals with the analytical applications of flavin-adenine dinucleotide (FAD) fluorescence. In the first section, the spectroscopic properties of this compound are reviewed at the light of his different acid-base, oxidation and structural forms; the chemical and spectroscopic properties of flavin mononucleotide (FMN) and other flavins will be also briefly discussed. The second section discusses how the properties of FAD fluorescence changes in flavoenzymes (FvEs), again considering the different chemical and structural forms; the glucose oxidase (GOx) and the choline oxidase (ChOx) cases will be commented. Since almost certainly the most reported analytical application of FAD fluorescence is as an auto-indicator in enzymatic methods catalysed by FvE oxidoreductases, it is important to know how the concentrations of the different forms of FAD changes along the reaction and, consequently, the fluorescence and the analytical signals. An approach to do this will be presented in section 3. The fourth part of the paper compiles the analytical applications which have been reported until now based in these fluorescence properties. Finally, some suggestions about tentative future research are also given.
Analytical derivation: An epistemic game for solving mathematically based physics problems
NASA Astrophysics Data System (ADS)
Bajracharya, Rabindra R.; Thompson, John R.
2016-06-01
Problem solving, which often involves multiple steps, is an integral part of physics learning and teaching. Using the perspective of the epistemic game, we documented a specific game that is commonly pursued by students while solving mathematically based physics problems: the analytical derivation game. This game involves deriving an equation through symbolic manipulations and routine mathematical operations, usually without any physical interpretation of the processes. This game often creates cognitive obstacles in students, preventing them from using alternative resources or better approaches during problem solving. We conducted hour-long, semi-structured, individual interviews with fourteen introductory physics students. Students were asked to solve four "pseudophysics" problems containing algebraic and graphical representations. The problems required the application of the fundamental theorem of calculus (FTC), which is one of the most frequently used mathematical concepts in physics problem solving. We show that the analytical derivation game is necessary, but not sufficient, to solve mathematically based physics problems, specifically those involving graphical representations.
Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop.
Legg, Philip A; Chung, David H S; Parry, Matthew L; Bown, Rhodri; Jones, Mark W; Griffiths, Iwan W; Chen, Min
2013-12-01
Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently change for different tasks. In this work, we develop a visual analytics systems that overcomes the shortcomings of the traditional approach. We make use of a sketch-based interface to enable users to specify search requirement in a flexible manner without depending on semantic annotation. We employ active machine learning to train different analytical models for different types of search requirements. We use visualization to facilitate knowledge discovery at the different stages of visual analytics. This includes visualizing the parameter space of the trained model, visualizing the search space to support interactive browsing, visualizing candidature search results to support rapid interaction for active learning while minimizing watching videos, and visualizing aggregated information of the search results. We demonstrate the system for searching spatiotemporal attributes from sports video to identify key instances of the team and player performance.
An, Jiwoo; Rahn, Kira L; Anderson, Jared L
2017-05-15
A headspace single drop microextraction (HS-SDME) method and a dispersive liquid-liquid microextraction (DLLME) method were developed using two tetrachloromanganate ([MnCl 4 2- ])-based magnetic ionic liquids (MIL) as extraction solvents for the determination of twelve aromatic compounds, including four polyaromatic hydrocarbons, by reversed phase high-performance liquid chromatography (HPLC). The analytical performance of the developed HS-SDME method was compared to the DLLME approach employing the same MILs. In the HS-SDME approach, the magnetic field generated by the magnet was exploited to suspend the MIL solvent from the tip of a rod magnet. The utilization of MILs in HS-SDME resulted in a highly stable microdroplet under elevated temperatures and long extraction times, overcoming a common challenge encountered in traditional SDME approaches of droplet instability. The low UV absorbance of the [MnCl 4 2- ]-based MILs permitted direct analysis of the analyte enriched extraction solvent by HPLC. In HS-SDME, the effects of ionic strength of the sample solution, temperature of the extraction system, extraction time, stir rate, and headspace volume on extraction efficiencies were examined. Coefficients of determination (R 2 ) ranged from 0.994 to 0.999 and limits of detection (LODs) varied from 0.04 to 1.0μgL -1 with relative recoveries from lake water ranging from 70.2% to 109.6%. For the DLLME method, parameters including disperser solvent type and volume, ionic strength of the sample solution, mass of extraction solvent, and extraction time were studied and optimized. Coefficients of determination for the DLLME method varied from 0.997 to 0.999 with LODs ranging from 0.05 to 1.0μgL -1 . Relative recoveries from lake water samples ranged from 68.7% to 104.5%. Overall, the DLLME approach permitted faster extraction times and higher enrichment factors for analytes with low vapor pressure whereas the HS-SDME approach exhibited better extraction efficiencies for analytes with relatively higher vapor pressure. Copyright © 2017 Elsevier B.V. All rights reserved.
An analytic approach to cyber adversarial dynamics
NASA Astrophysics Data System (ADS)
Sweeney, Patrick; Cybenko, George
2012-06-01
To date, cyber security investment by both the government and commercial sectors has been largely driven by the myopic best response of players to the actions of their adversaries and their perception of the adversarial environment. However, current work in applying traditional game theory to cyber operations typically assumes that games exist with prescribed moves, strategies, and payos. This paper presents an analytic approach to characterizing the more realistic cyber adversarial metagame that we believe is being played. Examples show that understanding the dynamic metagame provides opportunities to exploit an adversary's anticipated attack strategy. A dynamic version of a graph-based attack-defend game is introduced, and a simulation shows how an optimal strategy can be selected for success in the dynamic environment.
Approximate analytical solutions in the analysis of thin elastic plates
NASA Astrophysics Data System (ADS)
Goloskokov, Dmitriy P.; Matrosov, Alexander V.
2018-05-01
Two approaches to the construction of approximate analytical solutions for bending of a rectangular thin plate are presented: the superposition method based on the method of initial functions (MIF) and the one built using the Green's function in the form of orthogonal series. Comparison of two approaches is carried out by analyzing a square plate clamped along its contour. Behavior of the moment and the shear force in the neighborhood of the corner points is discussed. It is shown that both solutions give identical results at all points of the plate except for the neighborhoods of the corner points. There are differences in the values of bending moments and generalized shearing forces in the neighborhoods of the corner points.
Minarik, Marek; Franc, Martin; Minarik, Milan
2018-06-15
A new instrumental approach to recycling HPLC is described. The concept is based on fast reintroduction of incremental peak sections back onto the separation column. The re-circulation is performed within a closed loop containing only the column and two synchronized switching valves. By having HPLC pump out of the cycle, the method minimizes peak broadening due to dead volume. As a result the efficiency is dramatically increased allowing for the most demanding analytical applications. In addition, a parking loop is employed for temporary storage of analytes from the middle section of the separated mixture prior to their recycling. Copyright © 2018 Elsevier B.V. All rights reserved.
Analytical surveillance of emerging drugs of abuse and drug formulations
Thomas, Brian F.; Pollard, Gerald T.; Grabenauer, Megan
2012-01-01
Uncontrolled recreational drugs are proliferating in number and variety. Effects of long-term use are unknown, and regulation is problematic, as efforts to control one chemical often lead to several other structural analogs. Advanced analytical instrumentation and methods are continuing to be developed to identify drugs, chemical constituents of products, and drug substances and metabolites in biological fluids. Several mass spectrometry based approaches appear promising, particularly those that involve high resolution chromatographic and mass spectrometric methods that allow unbiased data acquisition and sophisticated data interrogation. Several of these techniques are shown to facilitate both targeted and broad spectrum analysis, which is often of particular benefit when dealing with misleadingly labeled products or assessing a biological matrix for illicit drugs and metabolites. The development and application of novel analytical approaches such as these will help to assess the nature and degree of exposure and risk and, where necessary, inform forensics and facilitate implementation of specific regulation and control measures. PMID:23154240
Analytic study of orbiter landing profiles
NASA Technical Reports Server (NTRS)
Walker, H. J.
1981-01-01
A broad survey of possible orbiter landing configurations was made with specific goals of defining boundaries for the landing task. The results suggest that the center of the corridors between marginal and routine represents a more or less optimal preflare condition for regular operations. Various constraints used to define the boundaries are based largely on qualitative judgements from earlier flight experience with the X-15 and lifting body research aircraft. The results should serve as useful background for expanding and validating landing simulation programs. The analytic approach offers a particular advantage in identifying trends due to the systematic variation of factors such as vehicle weight, load factor, approach speed, and aim point. Limitations such as a constant load factor during the flare and using a fixed gear deployment time interval, can be removed by increasing the flexibility of the computer program. This analytic definition of landing profiles of the orbiter may suggest additional studies, includin more configurations or more comparisons of landing profiles within and beyond the corridor boundaries.
Annual banned-substance review: analytical approaches in human sports drug testing.
Thevis, Mario; Kuuranne, Tiia; Geyer, Hans; Schänzer, Wilhelm
2015-01-01
Within the mosaic display of international anti-doping efforts, analytical strategies based on up-to-date instrumentation as well as most recent information about physiology, pharmacology, metabolism, etc., of prohibited substances and methods of doping are indispensable. The continuous emergence of new chemical entities and the identification of arguably beneficial effects of established or even obsolete drugs on endurance, strength, and regeneration, necessitate frequent and adequate adaptations of sports drug testing procedures. These largely rely on exploiting new technologies, extending the substance coverage of existing test protocols, and generating new insights into metabolism, distribution, and elimination of compounds prohibited by the World Anti-Doping Agency (WADA). In reference of the content of the 2014 Prohibited List, literature concerning human sports drug testing that was published between October 2013 and September 2014 is summarized and reviewed in this annual banned-substance review, with particular emphasis on analytical approaches and their contribution to enhanced doping controls. Copyright © 2014 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.
2017-10-01
In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.
Multimodal system planning technique : an analytical approach to peak period operation
DOT National Transportation Integrated Search
1995-11-01
The multimodal system planning technique described in this report is an improvement of the methodology used in the Dallas System Planning Study. The technique includes a spreadsheet-based process to identify the costs of congestion, construction, and...
Hsiao-Hsuan Wang; William Grant; Todd Swannack; Jianbang Gan; William Rogers; Tomasz Koralewski; James Miller; John W. Taylor Jr.
2011-01-01
We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework.
Adverse outcome pathway networks: Development, analytics and applications
The US EPA is developing more cost effective and efficient ways to evaluate chemical safety using high throughput and computationally based testing strategies. An important component of this approach is the ability to translate chemical effects on fundamental biological processes...
FastChem: An ultra-fast equilibrium chemistry
NASA Astrophysics Data System (ADS)
Kitzmann, Daniel; Stock, Joachim
2018-04-01
FastChem is an equilibrium chemistry code that calculates the chemical composition of the gas phase for given temperatures and pressures. Written in C++, it is based on a semi-analytic approach, and is optimized for extremely fast and accurate calculations.
Manuscript 116 Mechanisms: DNA Reactive Aagents
ABSTRACT The U.S. Environmental Protection Agency’s Guidelines for Carcinogen Risk Assessment (2005) uses an analytical framework for conducting a quantitative cancer risk assessment that is based on mode of action/key events and human relevance. The approach stresses the enh...
Adverse outcome pathway networks: Development, analytics, and applications
Product Description:The US EPA is developing more cost effective and efficient ways to evaluate chemical safety using high throughput and computationally based testing strategies. An important component of this approach is the ability to translate chemical effects on fundamental ...
Achieving optimal SERS through enhanced experimental design
Fisk, Heidi; Westley, Chloe; Turner, Nicholas J.
2016-01-01
One of the current limitations surrounding surface‐enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal‐based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd. PMID:27587905
Achieving optimal SERS through enhanced experimental design.
Fisk, Heidi; Westley, Chloe; Turner, Nicholas J; Goodacre, Royston
2016-01-01
One of the current limitations surrounding surface-enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal-based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.
Whittlesea, B W; Price, J R
2001-03-01
In studies of the mere exposure effect, rapid presentation of items can increase liking without accurate recognition. The effect on liking has been explained as a misattribution of fluency caused by prior presentation. However, fluency is also a source of feelings of familiarity. It is, therefore, surprising that prior experience can enhance liking without also causing familiarity-based recognition. We suggest that when study opportunities are minimal and test items are perceptually similar, people adopt an analytic approach, attempting to recognize distinctive features. That strategy fails because rapid presentation prevents effective encoding of such features; it also prevents people from experiencing fluency and a consequent feeling of familiarity. We suggest that the liking-without-recognition effect results from using an effective (nonanalytic) strategy in judging pleasantness, but an ineffective (analytic) strategy in recognition. Explanations of the mere exposure effect based on a distinction between implicit and explicit memory are unnecessary.
Two-condition within-participant statistical mediation analysis: A path-analytic framework.
Montoya, Amanda K; Hayes, Andrew F
2017-03-01
Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of 2 different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this article we recast Judd et al.'s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path-analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al.'s method requires, because it relies only on an inference about the product of paths-the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path-analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Gómez-Caravaca, Ana M; Maggio, Rubén M; Cerretani, Lorenzo
2016-03-24
Today virgin and extra-virgin olive oil (VOO and EVOO) are food with a large number of analytical tests planned to ensure its quality and genuineness. Almost all official methods demand high use of reagents and manpower. Because of that, analytical development in this area is continuously evolving. Therefore, this review focuses on analytical methods for EVOO/VOO which use fast and smart approaches based on chemometric techniques in order to reduce time of analysis, reagent consumption, high cost equipment and manpower. Experimental approaches of chemometrics coupled with fast analytical techniques such as UV-Vis spectroscopy, fluorescence, vibrational spectroscopies (NIR, MIR and Raman fluorescence), NMR spectroscopy, and other more complex techniques like chromatography, calorimetry and electrochemical techniques applied to EVOO/VOO production and analysis have been discussed throughout this work. The advantages and drawbacks of this association have also been highlighted. Chemometrics has been evidenced as a powerful tool for the oil industry. In fact, it has been shown how chemometrics can be implemented all along the different steps of EVOO/VOO production: raw material input control, monitoring during process and quality control of final product. Copyright © 2016 Elsevier B.V. All rights reserved.
Empirical and semi-analytical models for predicting peak outflows caused by embankment dam failures
NASA Astrophysics Data System (ADS)
Wang, Bo; Chen, Yunliang; Wu, Chao; Peng, Yong; Song, Jiajun; Liu, Wenjun; Liu, Xin
2018-07-01
Prediction of peak discharge of floods has attracted great attention for researchers and engineers. In present study, nine typical nonlinear mathematical models are established based on database of 40 historical dam failures. The first eight models that were developed with a series of regression analyses are purely empirical, while the last one is a semi-analytical approach that was derived from an analytical solution of dam-break floods in a trapezoidal channel. Water depth above breach invert (Hw), volume of water stored above breach invert (Vw), embankment length (El), and average embankment width (Ew) are used as independent variables to develop empirical formulas of estimating the peak outflow from breached embankment dams. It is indicated from the multiple regression analysis that a function using the former two variables (i.e., Hw and Vw) produce considerably more accurate results than that using latter two variables (i.e., El and Ew). It is shown that the semi-analytical approach works best in terms of both prediction accuracy and uncertainty, and the established empirical models produce considerably reasonable results except the model only using El. Moreover, present models have been compared with other models available in literature for estimating peak discharge.
A Decision Analytic Approach to Exposure-Based Chemical Prioritization
Mitchell, Jade; Pabon, Nicolas; Collier, Zachary A.; Egeghy, Peter P.; Cohen-Hubal, Elaine; Linkov, Igor; Vallero, Daniel A.
2013-01-01
The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. PMID:23940664
Bayesian estimation of the discrete coefficient of determination.
Chen, Ting; Braga-Neto, Ulisses M
2016-12-01
The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.
NASA Technical Reports Server (NTRS)
Ustinov, Eugene A.
2006-01-01
In a recent publication (Ustinov, 2002), we proposed an analytic approach to evaluation of radiative and geophysical weighting functions for remote sensing of a blackbody planetary atmosphere, based on general linearization approach applied to the case of nadir viewing geometry. In this presentation, the general linearization approach is applied to the limb viewing geometry. The expressions, similar to those obtained in (Ustinov, 2002), are obtained for weighting functions with respect to the distance along the line of sight. Further on, these expressions are converted to the expressions for weighting functions with respect to the vertical coordinate in the atmosphere. Finally, the numerical representation of weighting functions in the form of matrices of partial derivatives of grid limb radiances with respect to the grid values of atmospheric parameters is used for a convolution with the finite field of view of the instrument.
Consistent approach to describing aircraft HIRF protection
NASA Technical Reports Server (NTRS)
Rimbey, P. R.; Walen, D. B.
1995-01-01
The high intensity radiated fields (HIRF) certification process as currently implemented is comprised of an inconsistent combination of factors that tend to emphasize worst case scenarios in assessing commercial airplane certification requirements. By examining these factors which include the process definition, the external HIRF environment, the aircraft coupling and corresponding internal fields, and methods of measuring equipment susceptibilities, activities leading to an approach to appraising airplane vulnerability to HIRF are proposed. This approach utilizes technically based criteria to evaluate the nature of the threat, including the probability of encountering the external HIRF environment. No single test or analytic method comprehensively addresses the full HIRF threat frequency spectrum. Additional tools such as statistical methods must be adopted to arrive at more realistic requirements to reflect commercial aircraft vulnerability to the HIRF threat. Test and analytic data are provided to support the conclusions of this report. This work was performed under NASA contract NAS1-19360, Task 52.
May, Stephen A
2013-01-01
Confusion about the nature of human reasoning and its appropriate application to patients has hampered veterinary students' development of these skills. Expertise is associated with greater ability to deploy pattern recognition (type 1 reasoning), which is aided by progressive development of data-driven, forward reasoning (in contrast to scientific, backward reasoning), analytical approaches that lead to schema acquisition. The associative nature of type 1 reasoning makes it prone to bias, particularly in the face of "cognitive miserliness," when clues that indicate the need for triangulation with an analytical approach are ignored. However, combined reasoning approaches, from the earliest stages, are more successful than one approach alone, so it is important that those involved in curricular design and delivery promote student understanding of reasoning generally, and the situations in which reasoning goes awry, and develop students' ability to reason safely and accurately whether presented with a familiar case or with a case that they have never seen before.
Optimal synchronization of Kuramoto oscillators: A dimensional reduction approach
NASA Astrophysics Data System (ADS)
Pinto, Rafael S.; Saa, Alberto
2015-12-01
A recently proposed dimensional reduction approach for studying synchronization in the Kuramoto model is employed to build optimal network topologies to favor or to suppress synchronization. The approach is based in the introduction of a collective coordinate for the time evolution of the phase locked oscillators, in the spirit of the Ott-Antonsen ansatz. We show that the optimal synchronization of a Kuramoto network demands the maximization of the quadratic function ωTL ω , where ω stands for the vector of the natural frequencies of the oscillators and L for the network Laplacian matrix. Many recently obtained numerical results can be reobtained analytically and in a simpler way from our maximization condition. A computationally efficient hill climb rewiring algorithm is proposed to generate networks with optimal synchronization properties. Our approach can be easily adapted to the case of the Kuramoto models with both attractive and repulsive interactions, and again many recent numerical results can be rederived in a simpler and clearer analytical manner.
Cuddy, Michael F; Poda, Aimee R; Moser, Robert D; Weiss, Charles A; Cairns, Carolyn; Steevens, Jeffery A
2016-01-01
Nanoscale ingredients in commercial products represent a point of emerging environmental concern due to recent findings that correlate toxicity with small particle size. A weight-of-evidence (WOE) approach based upon multiple lines of evidence (LOE) is developed here to assess nanomaterials as they exist in consumer product formulations, providing a qualitative assessment regarding the presence of nanomaterials, along with a baseline estimate of nanoparticle concentration if nanomaterials do exist. Electron microscopy, analytical separations, and X-ray detection methods were used to identify and characterize nanomaterials in sunscreen formulations. The WOE/LOE approach as applied to four commercial sunscreen products indicated that all four contained at least 10% dispersed primary particles having at least one dimension <100 nm in size. Analytical analyses confirmed that these constituents were comprised of zinc oxide (ZnO) or titanium dioxide (TiO2). The screening approaches developed herein offer a streamlined, facile means to identify potentially hazardous nanomaterial constituents with minimal abrasive processing of the raw material.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Isaacs, Sivan, E-mail: sivan.isaacs@gmail.com; Abdulhalim, Ibrahim; NEW CREATE Programme, School of Materials Science and Engineering, 1 CREATE Way, Research Wing, #02-06/08, Singapore 138602
2015-05-11
Using an insulator-metal-insulator structure with dielectric having refractive index (RI) larger than the analyte, long range surface plasmon (SP) resonance exhibiting ultra-high penetration depth is demonstrated for sensing applications of large bioentities at wavelengths in the visible range. Based on the diverging beam approach in Kretschmann-Raether configuration, one of the SP resonances is shown to shift in response to changes in the analyte RI while the other is fixed; thus, it can be used as a built in reference. The combination of the high sensitivity, high penetration depth and self-reference using the diverging beam approach in which a dark linemore » is detected of the high sensitivity, high penetration depth, self-reference, and the diverging beam approach in which a dark line is detected using large number of camera pixels with a smart algorithm for sub-pixel resolution, a sensor with ultra-low detection limit is demonstrated suitable for large bioentities.« less
Effects of joints in truss structures
NASA Technical Reports Server (NTRS)
Ikegami, R.
1988-01-01
The response of truss-type structures for future space applications, such as Large Deployable Reflector (LDR), will be directly affected by joint performance. Some of the objectives of research at BAC were to characterize structural joints, establish analytical approaches that incorporate joint characteristics, and experimentally establish the validity of the analytical approaches. The test approach to characterize joints for both erectable and deployable-type structures was based upon a Force State Mapping Technique. The approach pictorially shows how the nonlinear joint results can be used for equivalent linear analysis. Testing of the Space Station joints developed at LaRC (a hinged joint at 2 Hz and a clevis joint at 2 Hz) successfully revealed the nonlinear characteristics of the joints. The Space Station joints were effectively linear when loaded to plus or minus 500 pounds with a corresponding displacement of about plus or minus 0.0015 inch. It was indicated that good linear joints exist which are compatible with errected structures, but that difficulty may be encountered if nonlinear-type joints are incorporated in the structure.
Suba, Dávid; Urbányi, Zoltán; Salgó, András
2016-10-01
Capillary electrophoresis techniques are widely used in the analytical biotechnology. Different electrophoretic techniques are very adequate tools to monitor size-and charge heterogenities of protein drugs. Method descriptions and development studies of capillary zone electrophoresis (CZE) have been described in literature. Most of them are performed based on the classical one-factor-at-time (OFAT) approach. In this study a very simple method development approach is described for capillary zone electrophoresis: a "two-phase-four-step" approach is introduced which allows a rapid, iterative method development process and can be a good platform for CZE method. In every step the current analytical target profile and an appropriate control strategy were established to monitor the current stage of development. A very good platform was established to investigate intact and digested protein samples. Commercially available monoclonal antibody was chosen as model protein for the method development study. The CZE method was qualificated after the development process and the results were presented. The analytical system stability was represented by the calculated RSD% value of area percentage and migration time of the selected peaks (<0.8% and <5%) during the intermediate precision investigation. Copyright © 2016 Elsevier B.V. All rights reserved.
Analytical method of waste allocation in waste management systems: Concept, method and case study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bergeron, Francis C., E-mail: francis.b.c@videotron.ca
Waste is not a rejected item to dispose anymore but increasingly a secondary resource to exploit, influencing waste allocation among treatment operations in a waste management (WM) system. The aim of this methodological paper is to present a new method for the assessment of the WM system, the “analytical method of the waste allocation process” (AMWAP), based on the concept of the “waste allocation process” defined as the aggregation of all processes of apportioning waste among alternative waste treatment operations inside or outside the spatial borders of a WM system. AMWAP contains a conceptual framework and an analytical approach. Themore » conceptual framework includes, firstly, a descriptive model that focuses on the description and classification of the WM system. It includes, secondly, an explanatory model that serves to explain and to predict the operation of the WM system. The analytical approach consists of a step-by-step analysis for the empirical implementation of the conceptual framework. With its multiple purposes, AMWAP provides an innovative and objective modular method to analyse a WM system which may be integrated in the framework of impact assessment methods and environmental systems analysis tools. Its originality comes from the interdisciplinary analysis of the WAP and to develop the conceptual framework. AMWAP is applied in the framework of an illustrative case study on the household WM system of Geneva (Switzerland). It demonstrates that this method provides an in-depth and contextual knowledge of WM. - Highlights: • The study presents a new analytical method based on the waste allocation process. • The method provides an in-depth and contextual knowledge of the waste management system. • The paper provides a reproducible procedure for professionals, experts and academics. • It may be integrated into impact assessment or environmental system analysis tools. • An illustrative case study is provided based on household waste management in Geneva.« less
NASA Astrophysics Data System (ADS)
Nguyen, Duc Anh; Cat Vu, Minh; Willems, Patrick; Monbaliu, Jaak
2017-04-01
Salt intrusion is the most acute problem for irrigation water quality in coastal regions during dry seasons. The use of numerical hydrodynamic models is widespread and has become the prevailing approach to simulate the salinity distribution in an estuary. Despite its power to estimate both spatial and temporal salinity variations along the estuary, this approach also has its drawbacks. The high computational cost and the need for detailed hydrological, bathymetric and tidal datasets, put some limits on the usability in particular case studies. In poor data environments, analytical salt intrusion models are more widely used as they require less data and have a further reduction of the computational effort. There are few studies however where a more comprehensive comparison is made between the performance of a numerical hydrodynamic and an analytical model. In this research the multi-channel Ma Estuary in Vietnam is considered as a case study. Both the analytical and the hydrodynamic simulation approaches have been applied and were found capable to mimic the longitudinal salt distribution along the estuary. The data to construct the MIKE11 model include observations provided by a network of fixed hydrological stations and the cross-section measurements along the estuary. The analytic model is developed in parallel but based on information obtained from the hydrological network only (typical for poor data environment). Note that the two convergence length parameters of this simplified model are usually extracted from topography data including cross-sectional area and width along the estuary. Furthermore, freshwater discharge data are needed but these are gauged further upstream outside of the tidal region and unable to reflect the individual flows entering the multi-channel estuary. In order to tackle the poor data environment limitations, a new approach was needed to calibrate the two estuary geometry parameters of the parsimonious salt intrusion model. Compared to the values based on a field survey for the estuary, the calibrated cross-sectional convergence length values are in very high agreement. By assuming a linear relation between inverses of the individual flows entering the estuary and inverses of the sum of flows gauged further upstream, the individual flows can be assessed. Evaluation on the modeling approaches at high water slack shows that the two modeling approaches have similar results. They explain salinity distribution along the Ma Estuary reasonably well with Nash-Sutcliffe efficiency values at gauging stations along the estuary of 0.50 or higher. These performances demonstrate the predictive power of the simplified salt intrusion model and of the proposed parameter/input estimation approach, even with the poorer data.
Using Analytics to Transform a Problem-Based Case Library: An Educational Design Research Approach
ERIC Educational Resources Information Center
Schmidt, Matthew; Tawfik, Andrew A.
2018-01-01
This article describes the iterative design, development, and evaluation of a case-based learning environment focusing on an ill-structured sales management problem. We discuss our processes and situate them within the broader framework of educational design research. The learning environment evolved over the course of three design phases. A…
ERIC Educational Resources Information Center
Ma, Ning; Xin, Shuang; Du, Jia-Yuan
2018-01-01
Personalized learning based on learning analytics has become increasingly important for teachers' development via providing adaptive contents and strategies for teachers by identifying their questions and needs. Currently, most studies on teachers' professional development focus on pre-service teachers, and studies on teachers' personalized…
Quantitative photoacoustic imaging in the acoustic regime using SPIM
NASA Astrophysics Data System (ADS)
Beigl, Alexander; Elbau, Peter; Sadiq, Kamran; Scherzer, Otmar
2018-05-01
While in standard photoacoustic imaging the propagation of sound waves is modeled by the standard wave equation, our approach is based on a generalized wave equation with variable sound speed and material density, respectively. In this paper we present an approach for photoacoustic imaging, which in addition to the recovery of the absorption density parameter, the imaging parameter of standard photoacoustics, also allows us to reconstruct the spatially varying sound speed and density, respectively, of the medium. We provide analytical reconstruction formulas for all three parameters based in a linearized model based on single plane illumination microscopy (SPIM) techniques.
McDermott, Imelda; Checkland, Kath; Harrison, Stephen; Snow, Stephanie; Coleman, Anna
2013-01-01
The language used by National Health Service (NHS) "commissioning" managers when discussing their roles and responsibilities can be seen as a manifestation of "identity work", defined as a process of identifying. This paper aims to offer a novel approach to analysing "identity work" by triangulation of multiple analytical methods, combining analysis of the content of text with analysis of its form. Fairclough's discourse analytic methodology is used as a framework. Following Fairclough, the authors use analytical methods associated with Halliday's systemic functional linguistics. While analysis of the content of interviews provides some information about NHS Commissioners' perceptions of their roles and responsibilities, analysis of the form of discourse that they use provides a more detailed and nuanced view. Overall, the authors found that commissioning managers have a higher level of certainty about what commissioning is not rather than what commissioning is; GP managers have a high level of certainty of their identity as a GP rather than as a manager; and both GP managers and non-GP managers oscillate between multiple identities depending on the different situations they are in. This paper offers a novel approach to triangulation, based not on the usual comparison of multiple data sources, but rather based on the application of multiple analytical methods to a single source of data. This paper also shows the latent uncertainty about the nature of commissioning enterprise in the English NHS.
Efficient Band-to-Trap Tunneling Model Including Heterojunction Band Offset
Gao, Xujiao; Huang, Andy; Kerr, Bert
2017-10-25
In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carriermore » recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.« less
Efficient Band-to-Trap Tunneling Model Including Heterojunction Band Offset
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, Xujiao; Huang, Andy; Kerr, Bert
In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carriermore » recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.« less
Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)
NASA Astrophysics Data System (ADS)
Bishop, M. P.; Houser, C.; Lemmons, K.
2015-12-01
Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.
Magnetic solid-phase extraction using carbon nanotubes as sorbents: a review.
Herrero-Latorre, C; Barciela-García, J; García-Martín, S; Peña-Crecente, R M; Otárola-Jiménez, J
2015-09-10
Magnetic solid-phase extraction (M-SPE) is a procedure based on the use of magnetic sorbents for the separation and preconcentration of different organic and inorganic analytes from large sample volumes. The magnetic sorbent is added to the sample solution and the target analyte is adsorbed onto the surface of the magnetic sorbent particles (M-SPs). Analyte-M-SPs are separated from the sample solution by applying an external magnetic field and, after elution with the appropriate solvent, the recovered analyte is analyzed. This approach has several advantages over traditional solid phase extraction as it avoids time-consuming and tedious on-column SPE procedures and it provides a rapid and simple analyte separation that avoids the need for centrifugation or filtration steps. As a consequence, in the past few years a great deal of research has been focused on M-SPE, including the development of new sorbents and novel automation strategies. In recent years, the use of magnetic carbon nanotubes (M-CNTs) as a sorption substrate in M-SPE has become an active area of research. These materials have exceptional mechanical, electrical, optical and magnetic properties and they also have an extremely large surface area and varied possibilities for functionalization. This review covers the synthesis of M-CNTs and the different approaches for the use of these compounds in M-SPE. The performance, general characteristics and applications of M-SPE based on magnetic carbon nanotubes for organic and inorganic analysis have been evaluated on the basis of more than 110 references. Finally, some important challenges with respect the use of magnetic carbon nanotubes in M-SPE are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
Source-term development for a contaminant plume for use by multimedia risk assessment models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whelan, Gene; McDonald, John P.; Taira, Randal Y.
1999-12-01
Multimedia modelers from the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE) are collaborating to conduct a comprehensive and quantitative benchmarking analysis of four intermedia models: DOE's Multimedia Environmental Pollutant Assessment System (MEPAS), EPA's MMSOILS, EPA's PRESTO, and DOE's RESidual RADioactivity (RESRAD). These models represent typical analytically, semi-analytically, and empirically based tools that are utilized in human risk and endangerment assessments for use at installations containing radioactive and/or hazardous contaminants. Although the benchmarking exercise traditionally emphasizes the application and comparison of these models, the establishment of a Conceptual Site Model (CSM) should be viewed with equalmore » importance. This paper reviews an approach for developing a CSM of an existing, real-world, Sr-90 plume at DOE's Hanford installation in Richland, Washington, for use in a multimedia-based benchmarking exercise bet ween MEPAS, MMSOILS, PRESTO, and RESRAD. In an unconventional move for analytically based modeling, the benchmarking exercise will begin with the plume as the source of contamination. The source and release mechanism are developed and described within the context of performing a preliminary risk assessment utilizing these analytical models. By beginning with the plume as the source term, this paper reviews a typical process and procedure an analyst would follow in developing a CSM for use in a preliminary assessment using this class of analytical tool.« less
A self-consistent first-principle based approach to model carrier mobility in organic materials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meded, Velimir; Friederich, Pascal; Symalla, Franz
2015-12-31
Transport through thin organic amorphous films, utilized in OLEDs and OPVs, has been a challenge to model by using ab-initio methods. Charge carrier mobility depends strongly on the disorder strength and reorganization energy, both of which are significantly affected by the details in environment of each molecule. Here we present a multi-scale approach to describe carrier mobility in which the materials morphology is generated using DEPOSIT, a Monte Carlo based atomistic simulation approach, or, alternatively by molecular dynamics calculations performed with GROMACS. From this morphology we extract the material specific hopping rates, as well as the on-site energies using amore » fully self-consistent embedding approach to compute the electronic structure parameters, which are then used in an analytic expression for the carrier mobility. We apply this strategy to compute the carrier mobility for a set of widely studied molecules and obtain good agreement between experiment and theory varying over several orders of magnitude in the mobility without any freely adjustable parameters. The work focuses on the quantum mechanical step of the multi-scale workflow, explains the concept along with the recently published workflow optimization, which combines density functional with semi-empirical tight binding approaches. This is followed by discussion on the analytic formula and its agreement with established percolation fits as well as kinetic Monte Carlo numerical approaches. Finally, we skatch an unified multi-disciplinary approach that integrates materials science simulation and high performance computing, developed within EU project MMM@HPC.« less
Della Pelle, Flavio; Compagnone, Dario
2018-02-04
Polyphenolic compounds (PCs) have received exceptional attention at the end of the past millennium and as much at the beginning of the new one. Undoubtedly, these compounds in foodstuffs provide added value for their well-known health benefits, for their technological role and also marketing. Many efforts have been made to provide simple, effective and user friendly analytical methods for the determination and antioxidant capacity (AOC) evaluation of food polyphenols. In a parallel track, over the last twenty years, nanomaterials (NMs) have made their entry in the analytical chemistry domain; NMs have, in fact, opened new paths for the development of analytical methods with the common aim to improve analytical performance and sustainability, becoming new tools in quality assurance of food and beverages. The aim of this review is to provide information on the most recent developments of new NMs-based tools and strategies for total polyphenols (TP) determination and AOC evaluation in food. In this review optical, electrochemical and bioelectrochemical approaches have been reviewed. The use of nanoparticles, quantum dots, carbon nanomaterials and hybrid materials for the detection of polyphenols is the main subject of the works reported. However, particular attention has been paid to the success of the application in real samples, in addition to the NMs. In particular, the discussion has been focused on methods/devices presenting, in the opinion of the authors, clear advancement in the fields, in terms of simplicity, rapidity and usability. This review aims to demonstrate how the NM-based approaches represent valid alternatives to classical methods for polyphenols analysis, and are mature to be integrated for the rapid quality assessment of food quality in lab or directly in the field.
2018-01-01
Polyphenolic compounds (PCs) have received exceptional attention at the end of the past millennium and as much at the beginning of the new one. Undoubtedly, these compounds in foodstuffs provide added value for their well-known health benefits, for their technological role and also marketing. Many efforts have been made to provide simple, effective and user friendly analytical methods for the determination and antioxidant capacity (AOC) evaluation of food polyphenols. In a parallel track, over the last twenty years, nanomaterials (NMs) have made their entry in the analytical chemistry domain; NMs have, in fact, opened new paths for the development of analytical methods with the common aim to improve analytical performance and sustainability, becoming new tools in quality assurance of food and beverages. The aim of this review is to provide information on the most recent developments of new NMs-based tools and strategies for total polyphenols (TP) determination and AOC evaluation in food. In this review optical, electrochemical and bioelectrochemical approaches have been reviewed. The use of nanoparticles, quantum dots, carbon nanomaterials and hybrid materials for the detection of polyphenols is the main subject of the works reported. However, particular attention has been paid to the success of the application in real samples, in addition to the NMs. In particular, the discussion has been focused on methods/devices presenting, in the opinion of the authors, clear advancement in the fields, in terms of simplicity, rapidity and usability. This review aims to demonstrate how the NM-based approaches represent valid alternatives to classical methods for polyphenols analysis, and are mature to be integrated for the rapid quality assessment of food quality in lab or directly in the field. PMID:29401719
Woolfenden, Elizabeth
2010-04-16
Sorbent tubes/traps are widely used in combination with gas chromatographic (GC) analytical methods to monitor the vapour-phase fraction of organic compounds in air. Target compounds range in volatility from acetylene and freons to phthalates and PCBs and include apolar, polar and reactive species. Airborne vapour concentrations will vary depending on the nature of the location, nearby pollution sources, weather conditions, etc. Levels can range from low percent concentrations in stack and vent emissions to low part per trillion (ppt) levels in ultra-clean outdoor locations. Hundreds, even thousands of different compounds may be present in any given atmosphere. GC is commonly used in combination with mass spectrometry (MS) detection especially for environmental monitoring or for screening uncharacterised workplace atmospheres. Given the complexity and variability of organic vapours in air, no one sampling approach suits every monitoring scenario. A variety of different sampling strategies and sorbent media have been developed to address specific applications. Key sorbent-based examples include: active (pumped) sampling onto tubes packed with one or more sorbents held at ambient temperature; diffusive (passive) sampling onto sorbent tubes/cartridges; on-line sampling of air/gas streams into cooled sorbent traps; and transfer of air samples from containers (canisters, Tedlar) bags, etc.) into cooled sorbent focusing traps. Whichever sampling approach is selected, subsequent analysis almost always involves either solvent extraction or thermal desorption (TD) prior to GC(/MS) analysis. The overall performance of the air monitoring method will depend heavily on appropriate selection of key sampling and analytical parameters. This comprehensive review of air monitoring using sorbent tubes/traps is divided into 2 parts. (1) Sorbent-based air sampling option. (2) Sorbent selection and other aspects of optimizing sorbent-based air monitoring methods. The paper presents current state-of-the-art and recent developments in relevant areas such as sorbent research, sampler design, enhanced approaches to analytical quality assurance and on-tube derivatisation. Copyright 2009 Elsevier B.V. All rights reserved.
Mowlavi, Ali Asghar; Fornasier, Maria Rossa; Mirzaei, Mohammd; Bregant, Paola; de Denaro, Mario
2014-10-01
The beta and gamma absorbed fractions in organs and tissues are the important key factors of radionuclide internal dosimetry based on Medical Internal Radiation Dose (MIRD) approach. The aim of this study is to find suitable analytical functions for beta and gamma absorbed fractions in spherical and ellipsoidal volumes with a uniform distribution of iodine-131 radionuclide. MCNPX code has been used to calculate the energy absorption from beta and gamma rays of iodine-131 uniformly distributed inside different ellipsoids and spheres, and then the absorbed fractions have been evaluated. We have found the fit parameters of a suitable analytical function for the beta absorbed fraction, depending on a generalized radius for ellipsoid based on the radius of sphere, and a linear fit function for the gamma absorbed fraction. The analytical functions that we obtained from fitting process in Monte Carlo data can be used for obtaining the absorbed fractions of iodine-131 beta and gamma rays for any volume of the thyroid lobe. Moreover, our results for the spheres are in good agreement with the results of MIRD and other scientific literatures.
Learning Analytics Considered Harmful
ERIC Educational Resources Information Center
Dringus, Laurie P.
2012-01-01
This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through…
Den Hartog, Emiel A; Havenith, George
2010-01-01
For wearers of protective clothing in radiation environments there are no quantitative guidelines available for the effect of a radiative heat load on heat exchange. Under the European Union funded project ThermProtect an analytical effort was defined to address the issue of radiative heat load while wearing protective clothing. As within the ThermProtect project much information has become available from thermal manikin experiments in thermal radiation environments, these sets of experimental data are used to verify the analytical approach. The analytical approach provided a good prediction of the heat loss in the manikin experiments, 95% of the variance was explained by the model. The model has not yet been validated at high radiative heat loads and neglects some physical properties of the radiation emissivity. Still, the analytical approach provides a pragmatic approach and may be useful for practical implementation in protective clothing standards for moderate thermal radiation environments.
Diagnosing Prion Diseases: Mass Spectrometry-Based Approaches
USDA-ARS?s Scientific Manuscript database
Mass spectrometry is an established means of quantitating the prions present in infected hamsters. Calibration curves relating the area ratios of the selected analyte peptides and their oxidized analogs to stable isotope labeled internal standards were prepared. The limit of detection (LOD) and limi...
AN APPROACH TO METHODS DEVELOPMENT FOR HUMAN EXPOSURE ASSESSMENT STUDIES
Human exposure assessment studies require methods that are rapid, cost-effective and have a high sample through-put. The development of analytical methods for exposure studies should be based on specific information for individual studies. Human exposure studies suggest that di...
Orcutt, Karen M; Jones, W Scott; McDonald, Andrea; Schrock, David; Wallace, Karl J
2010-01-01
The measurement of trace analytes in aqueous systems has become increasingly important for understanding ocean primary productivity. In oceanography, iron (Fe) is a key element in regulating ocean productivity, microplankton assemblages and has been identified as a causative element in the development of some harmful algal blooms. The chemosenor developed in this study is based on an indicator displacement approach that utilizes time-resolved fluorescence and fluorescence resonance energy transfer as the sensing mechanism to achieve detection of Fe3+ ions as low as 5 nM. This novel approach holds promise for the development of photoactive chemosensors for ocean deployment.
Hess, Cornelius; Sydow, Konrad; Kueting, Theresa; Kraemer, Michael; Maas, Alexandra
2018-02-01
The requirement for correct evaluation of forensic toxicological results in daily routine work and scientific studies is reliable analytical data based on validated methods. Validation of a method gives the analyst tools to estimate the efficacy and reliability of the analytical method. Without validation, data might be contested in court and lead to unjustified legal consequences for a defendant. Therefore, new analytical methods to be used in forensic toxicology require careful method development and validation of the final method. Until now, there are no publications on the validation of chromatographic mass spectrometric methods for the detection of endogenous substances although endogenous analytes can be important in Forensic Toxicology (alcohol consumption marker, congener alcohols, gamma hydroxy butyric acid, human insulin and C-peptide, creatinine, postmortal clinical parameters). For these analytes, conventional validation instructions cannot be followed completely. In this paper, important practical considerations in analytical method validation for endogenous substances will be discussed which may be used as guidance for scientists wishing to develop and validate analytical methods for analytes produced naturally in the human body. Especially the validation parameters calibration model, analytical limits, accuracy (bias and precision) and matrix effects and recovery have to be approached differently. Highest attention should be paid to selectivity experiments. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Brandstetter, Gerd; Govindjee, Sanjay
2012-03-01
Existing analytical and numerical methodologies are discussed and then extended in order to calculate critical contamination-particle sizes, which will result in deleterious effects during EUVL E-chucking in the face of an error budget on the image-placement-error (IPE). The enhanced analytical models include a gap dependant clamping pressure formulation, the consideration of a general material law for realistic particle crushing and the influence of frictional contact. We present a discussion of the defects of the classical de-coupled modeling approach where particle crushing and mask/chuck indentation are separated from the global computation of mask bending. To repair this defect we present a new analytic approach based on an exact Hankel transform method which allows a fully coupled solution. This will capture the contribution of the mask indentation to the image-placement-error (estimated IPE increase of 20%). A fully coupled finite element model is used to validate the analytical models and to further investigate the impact of a mask back-side CrN-layer. The models are applied to existing experimental data with good agreement. For a standard material combination, a given IPE tolerance of 1 nm and a 15 kPa closing pressure, we derive bounds for single particles of cylindrical shape (radius × height < 44 μm) and spherical shape (diameter < 12 μm).
NASA Astrophysics Data System (ADS)
Hreniuc, V.; Hreniuc, A.; Pescaru, A.
2017-08-01
Solving a general strength problem of a ship hull may be done using analytical approaches which are useful to deduce the buoyancy forces distribution, the weighting forces distribution along the hull and the geometrical characteristics of the sections. These data are used to draw the free body diagrams and to compute the stresses. The general strength problems require a large amount of calculi, therefore it is interesting how a computer may be used to solve such problems. Using computer programming an engineer may conceive software instruments based on analytical approaches. However, before developing the computer code the research topic must be thoroughly analysed, in this way being reached a meta-level of understanding of the problem. The following stage is to conceive an appropriate development strategy of the original software instruments useful for the rapid development of computer aided analytical models. The geometrical characteristics of the sections may be computed using a bool algebra that operates with ‘simple’ geometrical shapes. By ‘simple’ we mean that for the according shapes we have direct calculus relations. In the set of ‘simple’ shapes we also have geometrical entities bounded by curves approximated as spline functions or as polygons. To conclude, computer programming offers the necessary support to solve general strength ship hull problems using analytical methods.
Equivalent-circuit models for electret-based vibration energy harvesters
NASA Astrophysics Data System (ADS)
Phu Le, Cuong; Halvorsen, Einar
2017-08-01
This paper presents a complete analysis to build a tool for modelling electret-based vibration energy harvesters. The calculational approach includes all possible effects of fringing fields that may have significant impact on output power. The transducer configuration consists of two sets of metal strip electrodes on a top substrate that faces electret strips deposited on a bottom movable substrate functioning as a proof mass. Charge distribution on each metal strip is expressed by series expansion using Chebyshev polynomials multiplied by a reciprocal square-root form. The Galerkin method is then applied to extract all charge induction coefficients. The approach is validated by finite element calculations. From the analytic tool, a variety of connection schemes for power extraction in slot-effect and cross-wafer configurations can be lumped to a standard equivalent circuit with inclusion of parasitic capacitance. Fast calculation of the coefficients is also obtained by a proposed closed-form solution based on leading terms of the series expansions. The achieved analytical result is an important step for further optimisation of the transducer geometry and maximising harvester performance.
A splay tree-based approach for efficient resource location in P2P networks.
Zhou, Wei; Tan, Zilong; Yao, Shaowen; Wang, Shipu
2014-01-01
Resource location in structured P2P system has a critical influence on the system performance. Existing analytical studies of Chord protocol have shown some potential improvements in performance. In this paper a splay tree-based new Chord structure called SChord is proposed to improve the efficiency of locating resources. We consider a novel implementation of the Chord finger table (routing table) based on the splay tree. This approach extends the Chord finger table with additional routing entries. Adaptive routing algorithm is proposed for implementation, and it can be shown that hop count is significantly minimized without introducing any other protocol overheads. We analyze the hop count of the adaptive routing algorithm, as compared to Chord variants, and demonstrate sharp upper and lower bounds for both worst-case and average case settings. In addition, we theoretically analyze the hop reducing in SChord and derive the fact that SChord can significantly reduce the routing hops as compared to Chord. Several simulations are presented to evaluate the performance of the algorithm and support our analytical findings. The simulation results show the efficiency of SChord.
An Analytic Equation Partitioning Climate Variation and Human Impacts on River Sediment Load
NASA Astrophysics Data System (ADS)
Zhang, J.; Gao, G.; Fu, B.
2017-12-01
Spatial or temporal patterns and process-based equations could co-exist in hydrologic model. Yet, existing approaches quantifying the impacts of those variables on river sediment load (RSL) changes are found to be severely limited, and new ways to evaluate the contribution of these variables are thus needed. Actually, the Newtonian modeling is hardly achievable for this process due to the limitation of both observations and knowledge of mechanisms, whereas laws based on the Darwinian approach could provide one component of a developed hydrologic model. Since that streamflow is the carrier of suspended sediment, sediment load changes are documented in changes of streamflow and suspended sediment concentration (SSC) - water discharge relationships. Consequently, an analytic equation for river sediment load changes are proposed to explicitly quantify the relative contributions of climate variation and direct human impacts on river sediment load changes. Initially, the sediment rating curve, which is of great significance in RSL changes analysis, was decomposed as probability distribution of streamflow and the corresponding SSC - water discharge relationships at equally spaced discharge classes. Furthermore, a proposed segmentation algorithm based on the fractal theory was used to decompose RSL changes attributed to these two portions. Additionally, the water balance framework was utilized and the corresponding elastic parameters were calculated. Finally, changes in climate variables (i.e. precipitation and potential evapotranspiration) and direct human impacts on river sediment load could be figured out. By data simulation, the efficiency of the segmentation algorithm was verified. The analytic equation provides a superior Darwinian approach partitioning climate and human impacts on RSL changes, as only data series of precipitation, potential evapotranspiration and SSC - water discharge are demanded.
Good quantification practices of flavours and fragrances by mass spectrometry.
Begnaud, Frédéric; Chaintreau, Alain
2016-10-28
Over the past 15 years, chromatographic techniques with mass spectrometric detection have been increasingly used to monitor the rapidly expanded list of regulated flavour and fragrance ingredients. This trend entails a need for good quantification practices suitable for complex media, especially for multi-analytes. In this article, we present experimental precautions needed to perform the analyses and ways to process the data according to the most recent approaches. This notably includes the identification of analytes during their quantification and method validation, when applied to real matrices, based on accuracy profiles. A brief survey of application studies based on such practices is given.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Authors.
On the Use of Accelerated Test Methods for Characterization of Advanced Composite Materials
NASA Technical Reports Server (NTRS)
Gates, Thomas S.
2003-01-01
A rational approach to the problem of accelerated testing for material characterization of advanced polymer matrix composites is discussed. The experimental and analytical methods provided should be viewed as a set of tools useful in the screening of material systems for long-term engineering properties in aerospace applications. Consideration is given to long-term exposure in extreme environments that include elevated temperature, reduced temperature, moisture, oxygen, and mechanical load. Analytical formulations useful for predictive models that are based on the principles of time-based superposition are presented. The need for reproducible mechanisms, indicator properties, and real-time data are outlined as well as the methodologies for determining specific aging mechanisms.
Silva, Thalita G; de Araujo, William R; Muñoz, Rodrigo A A; Richter, Eduardo M; Santana, Mário H P; Coltro, Wendell K T; Paixão, Thiago R L C
2016-05-17
We report the development of a simple, portable, low-cost, high-throughput visual colorimetric paper-based analytical device for the detection of procaine in seized cocaine samples. The interference of most common cutting agents found in cocaine samples was verified, and a novel electrochemical approach was used for sample pretreatment in order to increase the selectivity. Under the optimized experimental conditions, a linear analytical curve was obtained for procaine concentrations ranging from 5 to 60 μmol L(-1), with a detection limit of 0.9 μmol L(-1). The accuracy of the proposed method was evaluated using seized cocaine samples and an addition and recovery protocol.
Current Trends in Nanomaterial-Based Amperometric Biosensors
Hayat, Akhtar; Catanante, Gaëlle; Marty, Jean Louis
2014-01-01
The last decade has witnessed an intensive research effort in the field of electrochemical sensors, with a particular focus on the design of amperometric biosensors for diverse analytical applications. In this context, nanomaterial integration in the construction of amperometric biosensors may constitute one of the most exciting approaches. The attractive properties of nanomaterials have paved the way for the design of a wide variety of biosensors based on various electrochemical detection methods to enhance the analytical characteristics. However, most of these nanostructured materials are not explored in the design of amperometric biosensors. This review aims to provide insight into the diverse properties of nanomaterials that can be possibly explored in the construction of amperometric biosensors. PMID:25494347
Vaxenburg, Roman; Wyche, Isis; Svoboda, Karel; Efros, Alexander L.
2018-01-01
Vibrations are important cues for tactile perception across species. Whisker-based sensation in mice is a powerful model system for investigating mechanisms of tactile perception. However, the role vibration plays in whisker-based sensation remains unsettled, in part due to difficulties in modeling the vibration of whiskers. Here, we develop an analytical approach to calculate the vibrations of whiskers striking objects. We use this approach to quantify vibration forces during active whisker touch at a range of locations along the whisker. The frequency and amplitude of vibrations evoked by contact are strongly dependent on the position of contact along the whisker. The magnitude of vibrational shear force and bending moment is comparable to quasi-static forces. The fundamental vibration frequencies are in a detectable range for mechanoreceptor properties and below the maximum spike rates of primary sensory afferents. These results suggest two dynamic cues exist that rodents can use for object localization: vibration frequency and comparison of vibrational to quasi-static force magnitude. These complement the use of quasi-static force angle as a distance cue, particularly for touches close to the follicle, where whiskers are stiff and force angles hardly change during touch. Our approach also provides a general solution to calculation of whisker vibrations in other sensing tasks. PMID:29584719
Watts, R R; Langone, J J; Knight, G J; Lewtas, J
1990-01-01
A two-day technical workshop was convened November 10-11, 1986, to discuss analytical approaches for determining trace amounts of cotinine in human body fluids resulting from passive exposure to environmental tobacco smoke (ETS). The workshop, jointly sponsored by the U.S. Environmental Protection Agency and Centers for Disease Control, was attended by scientists with expertise in cotinine analytical methodology and/or conduct of human monitoring studies related to ETS. The workshop format included technical presentations, separate panel discussions on chromatography and immunoassay analytical approaches, and group discussions related to the quality assurance/quality control aspects of future monitoring programs. This report presents a consensus of opinion on general issues before the workshop panel participants and also a detailed comparison of several analytical approaches being used by the various represented laboratories. The salient features of the chromatography and immunoassay analytical methods are discussed separately. PMID:2190812
Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason
2016-01-01
With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs. PMID:27983713
Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason
2016-12-15
With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM³ ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.
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.
Soft Argon-Propane Dielectric Barrier Discharge Ionization.
Schütz, Alexander; Lara-Ortega, Felipe J; Klute, Felix David; Brandt, Sebastian; Schilling, Michael; Michels, Antje; Veza, Damir; Horvatic, Vlasta; García-Reyes, Juan F; Franzke, Joachim
2018-03-06
Dielectric barrier discharges (DBDs) have been used as soft ionization sources (DBDI) for organic mass spectrometry (DBDI-MS) for approximately ten years. Helium-based DBDI is often used because of its good ionization efficiency, low ignition voltage, and homogeneous plasma conditions. Argon needs much higher ignition voltages than helium when the same discharge geometry is used. A filamentary plasma, which is not suitable for soft ionization, may be produced instead of a homogeneous plasma. This difference results in N 2 , present in helium and argon as an impurity, being Penning-ionized by helium but not by metastable argon atoms. In this study, a mixture of argon and propane (C 3 H 8 ) was used as an ignition aid to decrease the ignition and working voltages, because propane can be Penning-ionized by argon metastables. This approach leads to homogeneous argon-based DBDI. Furthermore, operating DBDI in an open environment assumes that many uncharged analyte molecules do not interact with the reactant ions. To overcome this disadvantage, we present a novel approach, where the analyte is introduced in an enclosed system through the discharge capillary itself. This nonambient DBDI-MS arrangement is presented and characterized and could advance the novel connection of DBDI with analytical separation techniques such as gas chromatography (GC) and high-pressure liquid chromatography (HPLC) in the near future.
Kouri, T T; Gant, V A; Fogazzi, G B; Hofmann, W; Hallander, H O; Guder, W G
2000-07-01
Improved standardized performance is needed because urinalysis continues to be one of the most frequently requested laboratory tests. Since 1997, the European Confederation of Laboratory Medicine (ECLM) has been supporting an interdisciplinary project aiming to produce European urinalysis guidelines. More than seventy clinical chemists, microbiologists and ward-based clinicians, as well as representatives of manufacturers are taking part. These guidelines aim to improve the quality and consistency of chemical urinalysis, particle counting and bacterial culture by suggesting optimal investigative processes that could be applied in Europe. The approach is based on medical needs for urinalysis. The importance of the pre-analytical stage for total quality is stressed by detailed illustrative advice for specimen collection. Attention is also given to emerging automated technology. For cost containment reasons, both optimum (ideal) procedures and minimum analytical approaches are suggested. Since urinalysis mostly lacks genuine reference methods (primary reference measurement procedures; Level 4), a novel classification of the methods is proposed: comparison measurement procedures (Level 3), quantitative routine procedures (Level 2), and ordinal scale examinations (Level 1). Stepwise strategies are suggested to save costs, applying different rules for general and specific patient populations. New analytical quality specifications have been created. After a consultation period, the final written text will be published in full as a separate document.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coletti, Chiara, E-mail: chiara.coletti@studenti.u
During the firing of bricks, mineralogical and textural transformations produce an artificial aggregate characterised by significant porosity. Particularly as regards pore-size distribution and the interconnection model, porosity is an important parameter to evaluate and predict the durability of bricks. The pore system is in fact the main element, which correlates building materials and their environment (especially in cases of aggressive weathering, e.g., salt crystallisation and freeze-thaw cycles) and determines their durability. Four industrial bricks with differing compositions and firing temperatures were analysed with “direct” and “indirect” techniques, traditional methods (mercury intrusion porosimetry, hydric tests, nitrogen adsorption) and new analytical approachesmore » based on digital image reconstruction of 2D and 3D models (back-scattered electrons and computerised X-ray micro-Tomography, respectively). The comparison of results from different analytical methods in the “overlapping ranges” of porosity and the careful reconstruction of a cumulative curve, allowed overcoming their specific limitations and achieving better knowledge on the pore system of bricks. - Highlights: •Pore-size distribution and structure of the pore system in four commercial bricks •A multi-analytical approach combining “direct” and “indirect” techniques •Traditional methods vs. new approaches based on 2D/3D digital image reconstruction •The use of “overlapping ranges” to overcome the limitations of various techniques.« less
Buvé, Carolien; Van Bedts, Tine; Haenen, Annelien; Kebede, Biniam; Braekers, Roel; Hendrickx, Marc; Van Loey, Ann; Grauwet, Tara
2018-07-01
Accurate shelf-life dating of food products is crucial for consumers and industries. Therefore, in this study we applied a science-based approach for shelf-life assessment, including accelerated shelf-life testing (ASLT), acceptability testing and the screening of analytical attributes for fast shelf-life predictions. Shelf-stable strawberry juice was selected as a case study. Ambient storage (20 °C) had no effect on the aroma-based acceptance of strawberry juice. The colour-based acceptability decreased during storage under ambient and accelerated (28-42 °C) conditions. The application of survival analysis showed that the colour-based shelf-life was reached in the early stages of storage (≤11 weeks) and that the shelf-life was shortened at higher temperatures. None of the selected attributes (a * and ΔE * value, anthocyanin and ascorbic acid content) is an ideal analytical marker for shelf-life predictions in the investigated temperature range (20-42 °C). Nevertheless, an overall analytical cut-off value over the whole temperature range can be selected. Colour changes of strawberry juice during storage are shelf-life limiting. Combining ASLT with acceptability testing allowed to gain faster insight into the change in colour-based acceptability and to perform shelf-life predictions relying on scientific data. An analytical marker is a convenient tool for shelf-life predictions in the context of ASLT. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
Validation of Analytical Damping Ratio by Fatigue Stress Limit
NASA Astrophysics Data System (ADS)
Foong, Faruq Muhammad; Chung Ket, Thein; Beng Lee, Ooi; Aziz, Abdul Rashid Abdul
2018-03-01
The optimisation process of a vibration energy harvester is usually restricted to experimental approaches due to the lack of an analytical equation to describe the damping of a system. This study derives an analytical equation, which describes the first mode damping ratio of a clamp-free cantilever beam under harmonic base excitation by combining the transverse equation of motion of the beam with the damping-stress equation. This equation, as opposed to other common damping determination methods, is independent of experimental inputs or finite element simulations and can be solved using a simple iterative convergence method. The derived equation was determined to be correct for cases when the maximum bending stress in the beam is below the fatigue limit stress of the beam. However, an increasing trend in the error between the experiment and the analytical results were observed at high stress levels. Hence, the fatigue limit stress was used as a parameter to define the validity of the analytical equation.
Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.
Endert, A; Fiaux, P; North, C
2012-12-01
Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaurov, Alexander A., E-mail: kaurov@uchicago.edu
The methods for studying the epoch of cosmic reionization vary from full radiative transfer simulations to purely analytical models. While numerical approaches are computationally expensive and are not suitable for generating many mock catalogs, analytical methods are based on assumptions and approximations. We explore the interconnection between both methods. First, we ask how the analytical framework of excursion set formalism can be used for statistical analysis of numerical simulations and visual representation of the morphology of ionization fronts. Second, we explore the methods of training the analytical model on a given numerical simulation. We present a new code which emergedmore » from this study. Its main application is to match the analytical model with a numerical simulation. Then, it allows one to generate mock reionization catalogs with volumes exceeding the original simulation quickly and computationally inexpensively, meanwhile reproducing large-scale statistical properties. These mock catalogs are particularly useful for cosmic microwave background polarization and 21 cm experiments, where large volumes are required to simulate the observed signal.« less
NASA Technical Reports Server (NTRS)
Hong, D. C.; Langer, J. S.
1986-01-01
An analytic approach to the problem of predicting the widths of fingers in a Hele-Shaw cell is presented. The analysis is based on the WKB technique developed recently for dealing with the effects of surface tension in the problem of dendritic solidification. It is found that the relation between the dimensionless width lambda and the dimensionless group of parameters containing the surface tension, nu, has the form lambda - 1/2 = nu exp 2/3 in the limit of small nu.
Scribed transparency microplates mounted on a modified standard microplate.
Cheong, Brandon Huey-Ping; Chua, Wei Seong; Liew, Oi Wah; Ng, Tuck Wah
2014-08-01
The immense cost effectiveness of using transparencies as analyte handling implements in microplate instrumentation offers the possibility of application even in resource-limited laboratories. In this work, a standard microplate was adapted to serve as the permanent base for disposable scribed transparencies. The approach is shown to ameliorate evaporation, which can affect assay accuracy when analytes need to be incubated for some time. It also offers assurance against fluorescence measurement errors due to the cross-talk of samples from adjacent wells. Copyright © 2014 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
St. John, C.M.
1977-04-01
An underground repository containing heat generating, High Level Waste or Spent Unreprocessed Fuel may be approximated as a finite number of heat sources distributed across the plane of the repository. The resulting temperature, displacement and stress changes may be calculated using analytical solutions, providing linear thermoelasticity is assumed. This report documents a computer program based on this approach and gives results that form the basis for a comparison between the effects of disposing of High Level Waste and Spent Unreprocessed Fuel.
Big data analytics as a service infrastructure: challenges, desired properties and solutions
NASA Astrophysics Data System (ADS)
Martín-Márquez, Manuel
2015-12-01
CERN's accelerator complex generates a very large amount of data. A large volumen of heterogeneous data is constantly generated from control equipment and monitoring agents. These data must be stored and analysed. Over the decades, CERN's researching and engineering teams have applied different approaches, techniques and technologies for this purpose. This situation has minimised the necessary collaboration and, more relevantly, the cross data analytics over different domains. These two factors are essential to unlock hidden insights and correlations between the underlying processes, which enable better and more efficient daily-based accelerator operations and more informed decisions. The proposed Big Data Analytics as a Service Infrastructure aims to: (1) integrate the existing developments; (2) centralise and standardise the complex data analytics needs for CERN's research and engineering community; (3) deliver real-time, batch data analytics and information discovery capabilities; and (4) provide transparent access and Extract, Transform and Load (ETL), mechanisms to the various and mission-critical existing data repositories. This paper presents the desired objectives and properties resulting from the analysis of CERN's data analytics requirements; the main challenges: technological, collaborative and educational and; potential solutions.
Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses.
Griffith, Daniel A; Peres-Neto, Pedro R
2006-10-01
Recently, analytical approaches based on the eigenfunctions of spatial configuration matrices have been proposed in order to consider explicitly spatial predictors. The present study demonstrates the usefulness of eigenfunctions in spatial modeling applied to ecological problems and shows equivalencies of and differences between the two current implementations of this methodology. The two approaches in this category are the distance-based (DB) eigenvector maps proposed by P. Legendre and his colleagues, and spatial filtering based upon geographic connectivity matrices (i.e., topology-based; CB) developed by D. A. Griffith and his colleagues. In both cases, the goal is to create spatial predictors that can be easily incorporated into conventional regression models. One important advantage of these two approaches over any other spatial approach is that they provide a flexible tool that allows the full range of general and generalized linear modeling theory to be applied to ecological and geographical problems in the presence of nonzero spatial autocorrelation.
An initial investigation into methods of computing transonic aerodynamic sensitivity coefficients
NASA Technical Reports Server (NTRS)
Carlson, Leland A.
1992-01-01
Research conducted during the period from July 1991 through December 1992 is covered. A method based upon the quasi-analytical approach was developed for computing the aerodynamic sensitivity coefficients of three dimensional wings in transonic and subsonic flow. In addition, the method computes for comparison purposes the aerodynamic sensitivity coefficients using the finite difference approach. The accuracy and validity of the methods are currently under investigation.
NASA Astrophysics Data System (ADS)
Fischer, Ulrich; Celia, Michael A.
1999-04-01
Functional relationships for unsaturated flow in soils, including those between capillary pressure, saturation, and relative permeabilities, are often described using analytical models based on the bundle-of-tubes concept. These models are often limited by, for example, inherent difficulties in prediction of absolute permeabilities, and in incorporation of a discontinuous nonwetting phase. To overcome these difficulties, an alternative approach may be formulated using pore-scale network models. In this approach, the pore space of the network model is adjusted to match retention data, and absolute and relative permeabilities are then calculated. A new approach that allows more general assignments of pore sizes within the network model provides for greater flexibility to match measured data. This additional flexibility is especially important for simultaneous modeling of main imbibition and drainage branches. Through comparisons between the network model results, analytical model results, and measured data for a variety of both undisturbed and repacked soils, the network model is seen to match capillary pressure-saturation data nearly as well as the analytical model, to predict water phase relative permeabilities equally well, and to predict gas phase relative permeabilities significantly better than the analytical model. The network model also provides very good estimates for intrinsic permeability and thus for absolute permeabilities. Both the network model and the analytical model lost accuracy in predicting relative water permeabilities for soils characterized by a van Genuchten exponent n≲3. Overall, the computational results indicate that reliable predictions of both relative and absolute permeabilities are obtained with the network model when the model matches the capillary pressure-saturation data well. The results also indicate that measured imbibition data are crucial to good predictions of the complete hysteresis loop.
13C-based metabolic flux analysis: fundamentals and practice.
Yang, Tae Hoon
2013-01-01
Isotope-based metabolic flux analysis is one of the emerging technologies applied to system level metabolic phenotype characterization in metabolic engineering. Among the developed approaches, (13)C-based metabolic flux analysis has been established as a standard tool and has been widely applied to quantitative pathway characterization of diverse biological systems. To implement (13)C-based metabolic flux analysis in practice, comprehending the underlying mathematical and computational modeling fundamentals is of importance along with carefully conducted experiments and analytical measurements. Such knowledge is also crucial when designing (13)C-labeling experiments and properly acquiring key data sets essential for in vivo flux analysis implementation. In this regard, the modeling fundamentals of (13)C-labeling systems and analytical data processing are the main topics we will deal with in this chapter. Along with this, the relevant numerical optimization techniques are addressed to help implementation of the entire computational procedures aiming at (13)C-based metabolic flux analysis in vivo.
NASA Astrophysics Data System (ADS)
Shahrajabian, Maryam; Hormozi-Nezhad, M. Reza
2016-08-01
Array-based sensor is an interesting approach that suggests an alternative to expensive analytical methods. In this work, we introduce a novel, simple, and sensitive nanoparticle-based chemiluminescence (CL) sensor array for discrimination of biothiols (e.g., cysteine, glutathione and glutathione disulfide). The proposed CL sensor array is based on the CL efficiencies of four types of enhanced nanoparticle-based CL systems. The intensity of CL was altered to varying degrees upon interaction with biothiols, producing unique CL response patterns. These distinct CL response patterns were collected as “fingerprints” and were then identified through chemometric methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA). The developed array was able to successfully differentiate between cysteine, glutathione and glutathione disulfide in a wide concentration range. Moreover, it was applied to distinguish among the above analytes in human plasma.
Array-based sensing using nanoparticles: an alternative approach for cancer diagnostics.
Le, Ngoc D B; Yazdani, Mahdieh; Rotello, Vincent M
2014-07-01
Array-based sensing using nanoparticles (NPs) provides an attractive alternative to specific biomarker-focused strategies for cancer diagnosis. The physical and chemical properties of NPs provide both the recognition and transduction capabilities required for biosensing. Array-based sensors utilize a combined response from the interactions between sensors and analytes to generate a distinct pattern (fingerprint) for each analyte. These interactions can be the result of either the combination of multiple specific biomarker recognition (specific binding) or multiple selective binding responses, known as chemical nose sensing. The versatility of the latter array-based sensing using NPs can facilitate the development of new personalized diagnostic methodologies in cancer diagnostics, a necessary evolution in the current healthcare system to better provide personalized treatments. This review will describe the basic principle of array-based sensors, along with providing examples of both invasive and noninvasive samples used in cancer diagnosis.
Fulford, K. W. M
2011-01-01
In the current climate of dramatic advances in the neurosciences, it has been widely assumed that the diagnosis of mental disorder is a matter exclusively for value-free science. Starting from a detailed case history, this paper describes how, to the contrary, values come into the diagnosis of mental disorders, directly through the criteria at the heart of psychiatry’s most scientifically grounded classification, the American Psychiatric Association’s DSM (Diagnostic and Statistical Manual). Various possible interpretations of the prominence of values in psychiatric diagnosis are outlined. Drawing on work in the Oxford analytic tradition of philosophy, it is shown that, properly understood, the prominence of psychiatric diagnostic values reflects the necessary engagement of psychiatry with the diversity of individual human values. This interpretation opens up psychiatric diagnostic assessment to the resources of a new skills-based approach to working with complex and conflicting values (also derived from analytic philosophy) called ‘values-based practice.’ Developments in values-based practice in training, policy and research in mental health are briefly outlined. The paper concludes with an indication of how the integration of values-based with evidence-based approaches provides the basis for psychiatric practice in the twenty-first century that is both science-based and person-centred. PMID:21694963
A Decision Analytic Approach to Exposure-Based Chemical Prioritization
The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient d...
40 CFR 80.47 - Performance-based Analytical Test Method Approach.
Code of Federal Regulations, 2014 CFR
2014-07-01
... chemistry and statistics, or at least a bachelor's degree in chemical engineering, from an accredited... be compensated for any known chemical interferences using good laboratory practices. (3) The test... section, individual test results shall be compensated for any known chemical interferences using good...
Commercial Demand Module - NEMS Documentation
2017-01-01
Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.
Replica and extreme-value analysis of the Jarzynski free-energy estimator
NASA Astrophysics Data System (ADS)
Palassini, Matteo; Ritort, Felix
2008-03-01
We analyze the Jarzynski estimator of free-energy differences from nonequilibrium work measurements. By a simple mapping onto Derrida's Random Energy Model, we obtain a scaling limit for the expectation of the bias of the estimator. We then derive analytical approximations in three different regimes of the scaling parameter x = log(N)/W, where N is the number of measurements and W the mean dissipated work. Our approach is valid for a generic distribution of the dissipated work, and is based on a replica symmetry breaking scheme for x >> 1, the asymptotic theory of extreme value statistics for x << 1, and a direct approach for x near one. The combination of the three analytic approximations describes well Monte Carlo data for the expectation value of the estimator, for a wide range of values of N, from N=1 to large N, and for different work distributions. Based on these results, we introduce improved free-energy estimators and discuss the application to the analysis of experimental data.
Probabilistic dual heuristic programming-based adaptive critic
NASA Astrophysics Data System (ADS)
Herzallah, Randa
2010-02-01
Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.
Frost, Megan C; Meyerhoff, Mark E
2015-01-01
We review approaches and challenges in developing chemical sensor-based methods to accurately and continuously monitor levels of key analytes in blood related directly to the status of critically ill hospitalized patients. Electrochemical and optical sensor-based technologies have been pursued to measure important critical care species in blood [i.e., oxygen, carbon dioxide, pH, electrolytes (K(+), Na(+), Cl(-), etc.), glucose, and lactate] in real-time or near real-time. The two main configurations examined to date for achieving this goal have been intravascular catheter sensors and patient attached ex vivo sensors with intermittent blood sampling via an attached indwelling catheter. We discuss the status of these configurations and the main issues affecting the accuracy of the measurements, including cell adhesion and thrombus formation on the surface of the sensors, sensor drift, sensor selectivity, etc. Recent approaches to mitigate these nagging performance issues that have prevented these technologies from clinical use are also discussed.
Zhang, He; Hu, Xinjiang; Fu, Xin
2014-07-15
This study reports the development of an aptamer-mediated microfluidic beads-based sensor for multiple analytes detection and quantification using multienzyme-linked nanoparticle amplification and quantum dots labels. Adenosine and cocaine were selected as the model analytes to validate the assay design based on strand displacement induced by target-aptamer complex. Microbeads functionalized with the aptamers and modified electron rich proteins were arrayed within a microfluidic channel and were connected with the horseradish peroxidases (HRP) and capture DNA probe derivative gold nanoparticles (AuNPs) via hybridization. The conformational transition of aptamer induced by target-aptamer complex contributes to the displacement of functionalized AuNPs and decreases the fluorescence signal of microbeads. In this approach, increased binding events of HRP on each nanosphere and enhanced mass transport capability inherent from microfluidics are integrated for enhancing the detection sensitivity of analytes. Based on the dual signal amplification strategy, the developed aptamer-based microfluidic bead array sensor could discriminate as low as 0.1 pM of adenosine and 0.5 pM cocaine, and showed a 500-fold increase in detection limit of adenosine compared to the off-chip test. The results proved the microfluidic-based method was a rapid and efficient system for aptamer-based targets assays (adenosine (0.1 pM) and cocaine (0.5 pM)), requiring only minimal (microliter) reagent use. This work demonstrated the successful application of aptamer-based microfluidic beads array sensor for detection of important molecules in biomedical fields. Copyright © 2014 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Davies, Alison; Ramsay, Jill; Lindfield, Helen; Couperthwaite, John
2005-01-01
This paper examines BSc Physiotherapy students' experiences of developing their neurological observational and analytical skills using a blend of traditional classroom activities and computer-based materials at the University of Birmingham. New teaching and learning resources were developed and supported in the School of Health Sciences using Web…
ERIC Educational Resources Information Center
McGill, D. A.; van der Vleuten, C. P. M.; Clarke, M. J.
2011-01-01
Even though rater-based judgements of clinical competence are widely used, they are context sensitive and vary between individuals and institutions. To deal adequately with rater-judgement unreliability, evaluating the reliability of workplace rater-based assessments in the local context is essential. Using such an approach, the primary intention…
ERIC Educational Resources Information Center
Iniguez, J.; Raposo, V.
2009-01-01
In this paper we analyse the behaviour of a small-scale model of a magnetic levitation system based on the Inductrack concept. Drag and lift forces acting on our prototype, moving above a continuous copper track, are studied analytically following a simple low-speed approach. The experimental results are in good agreement with the theoretical…
A Cluster-Analytical Approach towards Physical Activity and Eating Habits among 10-Year-Old Children
ERIC Educational Resources Information Center
Sabbe, Dieter; De Bourdeaudhuij, I.; Legiest, E.; Maes, L.
2008-01-01
The purpose was to investigate whether clusters--based on physical activity (PA) and eating habits--can be found among children, and to explore subgroups' characteristics. A total of 1725 10-year olds completed a self-administered questionnaire. K-means cluster analysis was based on the weekly quantity of vigorous and moderate PA, the excess index…
ERIC Educational Resources Information Center
Utami, Sri; Nursalam; Hargono, Rachmat; Susilaningrum, Rekawati
2016-01-01
The purpose of this study was to analyze the performance of midwives based on the task commitment. This was an observational analytic with cross sectional approach. Multistage random sampling was used to determine the public health center, proportional random sampling to selected participants. The samples were 222 midwives in the public health…
MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control
NASA Astrophysics Data System (ADS)
Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming
2017-09-01
Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.
Riccati parameterized self-similar waves in two-dimensional graded-index waveguide
NASA Astrophysics Data System (ADS)
Kumar De, Kanchan; Goyal, Amit; Raju, Thokala Soloman; Kumar, C. N.; Panigrahi, Prasanta K.
2015-04-01
An analytical method based on gauge-similarity transformation technique has been employed for mapping a (2+1)- dimensional variable coefficient coupled nonlinear Schrödinger equations (vc-CNLSE) with dispersion, nonlinearity and gain to standard NLSE. Under certain functional relations we construct a large family of self-similar waves in the form of bright similaritons, Akhmediev breathers and rogue waves. We report the effect of dispersion on the intensity of the solitary waves. Further, we illustrate the procedure to amplify the intensity of self-similar waves using isospectral Hamiltonian approach. This approach provides an efficient mechanism to generate analytically a wide class of tapering profiles and widths by exploiting the Riccati parameter. Equivalently, it enables one to control efficiently the self-similar wave structures and hence their evolution.
Label-free probing of genes by time-domain terahertz sensing.
Haring Bolivar, P; Brucherseifer, M; Nagel, M; Kurz, H; Bosserhoff, A; Büttner, R
2002-11-07
A label-free sensing approach for the label-free characterization of genetic material with terahertz (THz) electromagnetic waves is presented. Time-resolved THz analysis of polynucleotides demonstrates a strong dependence of the complex refractive index of DNA molecules in the THz frequency range on their hybridization state. By monitoring THz signals one can thus infer the binding state (hybridized or denatured) of oligo- and polynucleotides, enabling the label-free determination the genetic composition of unknown DNA sequences. A broadband experimental proof-of-principle in a freespace analytic configuration, as well as a higher-sensitivity approach using integrated THz sensors reaching femtomol detection levels and demonstrating the capability to detect single-base mutations, are presented. The potential application for next generation high-throughput label-free genetic analytic systems is discussed.
NASA Technical Reports Server (NTRS)
Glenn, G. M.
1977-01-01
A preflight analysis of the ALT separation reference trajectories for the tailcone on, forward, and aft cg orbiter configurations is documented. The ALT separation reference trajectories encompass the time from physical separation of the orbiter from the carrier to orbiter attainment of the maximum ALT interface airspeed. The trajectories include post separation roll maneuvers by both vehicles and are generated using the final preflight data base. The trajectories so generated satisfy all known separation design criteria and violate no known constraints. The requirement for this analysis is given along with the specifications, assumptions, and analytical approach used to generate the separation trajectories. The results of the analytical approach are evaluated, and conclusions and recommendations are summarized.
Similarity solution of the Boussinesq equation
NASA Astrophysics Data System (ADS)
Lockington, D. A.; Parlange, J.-Y.; Parlange, M. B.; Selker, J.
Similarity transforms of the Boussinesq equation in a semi-infinite medium are available when the boundary conditions are a power of time. The Boussinesq equation is reduced from a partial differential equation to a boundary-value problem. Chen et al. [Trans Porous Media 1995;18:15-36] use a hodograph method to derive an integral equation formulation of the new differential equation which they solve by numerical iteration. In the present paper, the convergence of their scheme is improved such that numerical iteration can be avoided for all practical purposes. However, a simpler analytical approach is also presented which is based on Shampine's transformation of the boundary value problem to an initial value problem. This analytical approximation is remarkably simple and yet more accurate than the analytical hodograph approximations.
2017-06-16
Acoustic Impacts on Marine Mammals and Sea Turtles: Methods and Analytical Approach for Phase III Training and Testing Sarah A. Blackstock Joseph O...December 2017 4. TITLE AND SUBTITLE Quantifying Acoustic Impacts on Marine Mammals and Sea Turtles: Methods and Analytical Approach for Phase III...Navy’s Phase III Study Areas as described in each Environmental Impact Statement/ Overseas Environmental Impact Statement and describes the methods
Gamage, K A A; Joyce, M J
2011-10-01
A novel analytical approach is described that accounts for self-shielding of γ radiation in decommissioning scenarios. The approach is developed with plutonium-239, cobalt-60 and caesium-137 as examples; stainless steel and concrete have been chosen as the media for cobalt-60 and caesium-137, respectively. The analytical methods have been compared MCNPX 2.6.0 simulations. A simple, linear correction factor relates the analytical results and the simulated estimates. This has the potential to greatly simplify the estimation of self-shielding effects in decommissioning activities. Copyright © 2011 Elsevier Ltd. All rights reserved.
Systematic Review of Model-Based Economic Evaluations of Treatments for Alzheimer's Disease.
Hernandez, Luis; Ozen, Asli; DosSantos, Rodrigo; Getsios, Denis
2016-07-01
Numerous economic evaluations using decision-analytic models have assessed the cost effectiveness of treatments for Alzheimer's disease (AD) in the last two decades. It is important to understand the methods used in the existing models of AD and how they could impact results, as they could inform new model-based economic evaluations of treatments for AD. The aim of this systematic review was to provide a detailed description on the relevant aspects and components of existing decision-analytic models of AD, identifying areas for improvement and future development, and to conduct a quality assessment of the included studies. We performed a systematic and comprehensive review of cost-effectiveness studies of pharmacological treatments for AD published in the last decade (January 2005 to February 2015) that used decision-analytic models, also including studies considering patients with mild cognitive impairment (MCI). The background information of the included studies and specific information on the decision-analytic models, including their approach and components, assumptions, data sources, analyses, and results, were obtained from each study. A description of how the modeling approaches and assumptions differ across studies, identifying areas for improvement and future development, is provided. At the end, we present our own view of the potential future directions of decision-analytic models of AD and the challenges they might face. The included studies present a variety of different approaches, assumptions, and scope of decision-analytic models used in the economic evaluation of pharmacological treatments of AD. The major areas for improvement in future models of AD are to include domains of cognition, function, and behavior, rather than cognition alone; include a detailed description of how data used to model the natural course of disease progression were derived; state and justify the economic model selected and structural assumptions and limitations; provide a detailed (rather than high-level) description of the cost components included in the model; and report on the face-, internal-, and cross-validity of the model to strengthen the credibility and confidence in model results. The quality scores of most studies were rated as fair to good (average 87.5, range 69.5-100, in a scale of 0-100). Despite the advancements in decision-analytic models of AD, there remain several areas of improvement that are necessary to more appropriately and realistically capture the broad nature of AD and the potential benefits of treatments in future models of AD.
NASA Astrophysics Data System (ADS)
Touil, B.; Bendib, A.; Bendib-Kalache, K.
2017-02-01
The longitudinal dielectric function is derived analytically from the relativistic Vlasov equation for arbitrary values of the relevant parameters z = m c 2 / T , where m is the rest electron mass, c is the speed of light, and T is the electron temperature in energy units. A new analytical approach based on the Legendre polynomial expansion and continued fractions was used. Analytical expression of the electron distribution function was derived. The real part of the dispersion relation and the damping rate of electron plasma waves are calculated both analytically and numerically in the whole range of the parameter z . The results obtained improve significantly the previous results reported in the literature. For practical purposes, explicit expressions of the real part of the dispersion relation and the damping rate in the range z > 30 and strongly relativistic regime are also proposed.
An Optoelectronic Nose for Detection of Toxic Gases
Lim, Sung H.; Feng, Liang; Kemling, Jonathan W.; Musto, Christopher J.; Suslick, Kenneth S.
2009-01-01
We have developed a simple colorimetric sensor array (CSA) for the detection of a wide range of volatile analytes and applied it to the detection of toxic gases. The sensor consists of a disposable array of cross-responsive nanoporous pigments whose colors are changed by diverse chemical interactions with analytes. Although no single chemically responsive pigment is specific for any one analyte, the pattern of color change for the array is a unique molecular fingerprint. Clear differentiation among 19 different toxic industrial chemicals (TICs) within two minutes of exposure at IDLH (immediately dangerous to life or health) concentration has been demonstrated. Quantification of each analyte is easily accomplished based on the color change of the array, and excellent detection limits have been demonstrated, generally below the PELs (permissible exposure limits). Identification of the TICs was readily achieved using a standard chemometric approach, i.e., hierarchical clustering analysis (HCA), with no misclassifications over 140 trials. PMID:20160982
An optoelectronic nose for the detection of toxic gases.
Lim, Sung H; Feng, Liang; Kemling, Jonathan W; Musto, Christopher J; Suslick, Kenneth S
2009-10-01
We have developed a simple colorimetric sensor array that detects a wide range of volatile analytes and then applied it to the detection of toxic gases. The sensor consists of a disposable array of cross-responsive nanoporous pigments with colours that are changed by diverse chemical interactions with analytes. Although no single chemically responsive pigment is specific for any one analyte, the pattern of colour change for the array is a unique molecular fingerprint. Clear differentiation among 19 different toxic industrial chemicals (TICs) within two minutes of exposure at concentrations immediately dangerous to life or health were demonstrated. Based on the colour change of the array, quantification of each analyte was accomplished easily, and excellent detection limits were achieved, generally below the permissible exposure limits. Different TICs were identified readily using a standard chemometric approach (hierarchical clustering analysis), with no misclassifications over 140 trials.
Coates, James; Jeyaseelan, Asha K; Ybarra, Norma; David, Marc; Faria, Sergio; Souhami, Luis; Cury, Fabio; Duclos, Marie; El Naqa, Issam
2015-04-01
We explore analytical and data-driven approaches to investigate the integration of genetic variations (single nucleotide polymorphisms [SNPs] and copy number variations [CNVs]) with dosimetric and clinical variables in modeling radiation-induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients. Sixty-two patients who underwent curative hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 and 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Fifty-four patients had full dosimetric profiles. Two parallel modeling approaches were compared to assess the risk of severe RB (Grade⩾3) and ED (Grade⩾1); Maximum likelihood estimated generalized Lyman-Kutcher-Burman (LKB) and logistic regression. Statistical resampling based on cross-validation was used to evaluate model predictive power and generalizability to unseen data. Integration of biological variables xrcc1 CNV and SNP improved the fit of the RB and ED analytical and data-driven models. Cross-validation of the generalized LKB models yielded increases in classification performance of 27.4% for RB and 14.6% for ED when xrcc1 CNV and SNP were included, respectively. Biological variables added to logistic regression modeling improved classification performance over standard dosimetric models by 33.5% for RB and 21.2% for ED models. As a proof-of-concept, we demonstrated that the combination of genetic and dosimetric variables can provide significant improvement in NTCP prediction using analytical and data-driven approaches. The improvement in prediction performance was more pronounced in the data driven approaches. Moreover, we have shown that CNVs, in addition to SNPs, may be useful structural genetic variants in predicting radiation toxicities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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.
Duester, Lars; Fabricius, Anne-Lena; Jakobtorweihen, Sven; Philippe, Allan; Weigl, Florian; Wimmer, Andreas; Schuster, Michael; Nazar, Muhammad Faizan
2016-11-01
Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.
Gangadharan, R; Prasanna, G; Bhat, M R; Murthy, C R L; Gopalakrishnan, S
2009-11-01
Conventional analytical/numerical methods employing triangulation technique are suitable for locating acoustic emission (AE) source in a planar structure without structural discontinuities. But these methods cannot be extended to structures with complicated geometry, and, also, the problem gets compounded if the material of the structure is anisotropic warranting complex analytical velocity models. A geodesic approach using Voronoi construction is proposed in this work to locate the AE source in a composite structure. The approach is based on the fact that the wave takes minimum energy path to travel from the source to any other point in the connected domain. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. In this work, the geodesic approach is shown more suitable for a practicable source location solution in a composite structure with arbitrary surface containing finite discontinuities. Experiments have been conducted on composite plate specimens of simple and complex geometry to validate this method.
Rosi, Francesca; Legan, Lea; Miliani, Costanza; Ropret, Polonca
2017-05-01
A new analytical approach, based on micro-transflection measurements from a diamond-coated metal sampling stick, is presented for the analysis of painting varnishes. Minimally invasive sampling is performed from the varnished surface using the stick, which is directly used as a transflection substrate for micro Fourier transform infrared (FTIR) measurements. With use of a series of varnished model paints, the micro-transflection method has been proved to be a valuable tool for the identification of surface components thanks to the selectivity of the sampling, the enhancement of the absorbance signal, and the easier spectral interpretation because the profiles are similar to transmission mode ones. Driven by these positive outcomes, the method was then tested as tool supporting noninvasive reflection FTIR spectroscopy during the assessment of varnish removal by solvent cleaning on paint models. Finally, the integrated analytical approach based on the two reflection methods was successfully applied for the monitoring of the cleaning of the sixteenth century painting Presentation in the Temple by Vittore Carpaccio. Graphical Abstract Micro-transflection FTIR on a metallic stick for the identification of varnishes during painting cleanings.
Aguirre-Urreta, Miguel I; Ellis, Michael E; Sun, Wenying
2012-03-01
This research investigates the performance of a proportion-based approach to meta-analytic moderator estimation through a series of Monte Carlo simulations. This approach is most useful when the moderating potential of a categorical variable has not been recognized in primary research and thus heterogeneous groups have been pooled together as a single sample. Alternative scenarios representing different distributions of group proportions are examined along with varying numbers of studies, subjects per study, and correlation combinations. Our results suggest that the approach is largely unbiased in its estimation of the magnitude of between-group differences and performs well with regard to statistical power and type I error. In particular, the average percentage bias of the estimated correlation for the reference group is positive and largely negligible, in the 0.5-1.8% range; the average percentage bias of the difference between correlations is also minimal, in the -0.1-1.2% range. Further analysis also suggests both biases decrease as the magnitude of the underlying difference increases, as the number of subjects in each simulated primary study increases, and as the number of simulated studies in each meta-analysis increases. The bias was most evident when the number of subjects and the number of studies were the smallest (80 and 36, respectively). A sensitivity analysis that examines its performance in scenarios down to 12 studies and 40 primary subjects is also included. This research is the first that thoroughly examines the adequacy of the proportion-based approach. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.
Netchacovitch, L; Thiry, J; De Bleye, C; Dumont, E; Cailletaud, J; Sacré, P-Y; Evrard, B; Hubert, Ph; Ziemons, E
2017-08-15
Since the Food and Drug Administration (FDA) published a guidance based on the Process Analytical Technology (PAT) approach, real-time analyses during manufacturing processes are in real expansion. In this study, in-line Raman spectroscopic analyses were performed during a Hot-Melt Extrusion (HME) process to determine the Active Pharmaceutical Ingredient (API) content in real-time. The method was validated based on a univariate and a multivariate approach and the analytical performances of the obtained models were compared. Moreover, on one hand, in-line data were correlated with the real API concentration present in the sample quantified by a previously validated off-line confocal Raman microspectroscopic method. On the other hand, in-line data were also treated in function of the concentration based on the weighing of the components in the prepared mixture. The importance of developing quantitative methods based on the use of a reference method was thus highlighted. The method was validated according to the total error approach fixing the acceptance limits at ±15% and the α risk at ±5%. This method reaches the requirements of the European Pharmacopeia norms for the uniformity of content of single-dose preparations. The validation proves that future results will be in the acceptance limits with a previously defined probability. Finally, the in-line validated method was compared with the off-line one to demonstrate its ability to be used in routine analyses. Copyright © 2017 Elsevier B.V. All rights reserved.
The generation of criteria for selecting analytical tools for landscape management
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,...
Electronic properties of a molecular system with Platinum
NASA Astrophysics Data System (ADS)
Ojeda, J. H.; Medina, F. G.; Becerra-Alonso, David
2017-10-01
The electronic properties are studied using a finite homogeneous molecule called Trans-platinum-linked oligo(tetraethenylethenes). This system is composed of individual molecules such as benzene rings, platinum, Phosphore and Sulfur. The mechanism for the study of the electron transport through this system is based on placing the molecule between metal contacts to control the current through the molecular system. We study this molecule based on the tight-binding approach for the calculation of the transport properties using the Landauer-Büttiker formalism and the Fischer-Lee relationship, based on a semi-analytic Green's function method within a real-space renormalization approach. Our results show a significant agreement with experimental measurements.
Analytical procedure validation and the quality by design paradigm.
Rozet, Eric; Lebrun, Pierre; Michiels, Jean-François; Sondag, Perceval; Scherder, Tara; Boulanger, Bruno
2015-01-01
Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a quality by design (QbD) approach, there have been many discussions on the opportunity for analytical procedure developments to follow a similar approach. While development and optimization of analytical procedure following QbD principles have been largely discussed and described, the place of analytical procedure validation in this framework has not been clarified. This article aims at showing that analytical procedure validation is fully integrated into the QbD paradigm and is an essential step in developing analytical procedures that are effectively fit for purpose. Adequate statistical methodologies have also their role to play: such as design of experiments, statistical modeling, and probabilistic statements. The outcome of analytical procedure validation is also an analytical procedure design space, and from it, control strategy can be set.
Diffusion of Super-Gaussian Profiles
ERIC Educational Resources Information Center
Rosenberg, C.-J.; Anderson, D.; Desaix, M.; Johannisson, P.; Lisak, M.
2007-01-01
The present analysis describes an analytically simple and systematic approximation procedure for modelling the free diffusive spreading of initially super-Gaussian profiles. The approach is based on a self-similar ansatz for the evolution of the diffusion profile, and the parameter functions involved in the modelling are determined by suitable…
Analytical solution of the nonlinear diffusion equation
NASA Astrophysics Data System (ADS)
Shanker Dubey, Ravi; Goswami, Pranay
2018-05-01
In the present paper, we derive the solution of the nonlinear fractional partial differential equations using an efficient approach based on the q -homotopy analysis transform method ( q -HATM). The fractional diffusion equations derivatives are considered in Caputo sense. The derived results are graphically demonstrated as well.
Differentiation from First Principles Using Spreadsheets
ERIC Educational Resources Information Center
Lim, Kieran F.
2008-01-01
In the teaching of calculus, the algebraic derivation of the derivative (gradient function) enables the student to obtain an analytic "global" gradient function. However, to the best of this author's knowledge, all current technology-based approaches require the student to obtain the derivative (gradient) at a single point by…
DOT National Transportation Integrated Search
2011-06-14
This paper presents a novel analytical approach to and techniques for translating characteristics of uncertainty in predicting sector entry times and times in sector for individual flights into characteristics of uncertainty in predicting one-minute ...
Development of a robust space power system decision model
NASA Astrophysics Data System (ADS)
Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert
2001-02-01
NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .
Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R
2018-04-25
Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.
NASA Technical Reports Server (NTRS)
Mengshoel, Ole J.; Roth, Dan; Wilkins, David C.
2001-01-01
Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.
NASA Astrophysics Data System (ADS)
Mashayekhi, Mohammad Jalali; Behdinan, Kamran
2017-10-01
The increasing demand to minimize undesired vibration and noise levels in several high-tech industries has generated a renewed interest in vibration transfer path analysis. Analyzing vibration transfer paths within a system is of crucial importance in designing an effective vibration isolation strategy. Most of the existing vibration transfer path analysis techniques are empirical which are suitable for diagnosis and troubleshooting purpose. The lack of an analytical transfer path analysis to be used in the design stage is the main motivation behind this research. In this paper an analytical transfer path analysis based on the four-pole theory is proposed for multi-energy-domain systems. Bond graph modeling technique which is an effective approach to model multi-energy-domain systems is used to develop the system model. In this paper an electro-mechanical system is used as a benchmark example to elucidate the effectiveness of the proposed technique. An algorithm to obtain the equivalent four-pole representation of a dynamical systems based on the corresponding bond graph model is also presented in this paper.
Rehman, Abdul; Hamilton, Andrew; Chung, Alfred; Baker, Gary A; Wang, Zhe; Zeng, Xiangqun
2011-10-15
An eight-sensor array coupling a chemoselective room-temperature ionic liquid (RTIL) with quartz crystal microbalance (QCM) transduction is presented in this work in order to demonstrate the power of this approach in differentiating closely related analytes in sensory devices. The underlying mechanism behind the specific sensory response was explored by (i) studying mass loading and viscoelasticity effects of the sensing layers, predominantly through variation in damping impedance, the combination of which determines the sensitivity; (ii) creation of a solvation model based on Abraham's solvation descriptors which reveals the fact that polarizability and lipophilicity are the main factors influencing the dissolution of gas analytes into the RTILs; and (iii) determination of enthalpy and entropy values for the studied interactions and comparison via a simulation model, which is also effective for pattern discrimination, in order to establish a foundation for the analytical scientist as well as inspiration for synthetic pathways and innovative research into next-generation sensory approaches. The reported sensors displayed an excellent sensitivity with detection limit of <0.2%, fast response and recovery, and a workable temperature range of 27-55 °C and even higher. Linear discriminant analysis (LDA) showed a discrimination accuracy of 86-92% for nitromethane and 1-ethyl-2-nitrobenzene, 71% for different mixtures of nitromethane, and 100% for these analytes when thermodynamic parameters were used as input data. We envisage applications to detecting other nitroaromatics and security-related gas targets, and high-temperature or real-time situations where manual access is restricted, opening up new horizons in chemical sensing. © 2011 American Chemical Society
NASA Astrophysics Data System (ADS)
Sajnóg, Adam; Hanć, Anetta; Makuch, Krzysztof; Koczorowski, Ryszard; Barałkiewicz, Danuta
2016-11-01
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used for in-situ quantitative analysis of oral mucosa of patients before and after implantation with titanium implants and a closing screw based on Ti6Al4V alloy. Two calibration strategies were applied, both were based on matrix matched solid standards with analytes addition. A novel approach was the application of powdered egg white proteins as a matrix material which have a similar composition to the examined tissue. In the another approach, certified reference material Bovine Muscle ERM-BB184 was used. The isotope 34S was found to be the most appropriate as an internal standard since it is homogenously distributed in the examined tissues and resulted in lower relative standard deviation values of signal of analytes of interest. Other isotopes (13C, 26Mg, 43Ca) were also evaluated as potential internal standards. The analytical performance parameters and microwave digestion of solid standards followed by solution nebulization ICP-MS analysis proved that both calibration methods are fit for their intended purpose. The LA-ICP-MS analysis on the surface of tissues after the implantation process revealed an elevated content of elements in comparison to the control group. Analytes are distributed inhomogeneously and display local maximal content of Ti up to ca. 900 μg g- 1, Al up to ca. 760 μg g- 1 and for V up to 160 μg g- 1.
Gao, Le; Li, Jian; Wu, Yandan; Yu, Miaohao; Chen, Tian; Shi, Zhixiong; Zhou, Xianqing; Sun, Zhiwei
2016-11-01
Two simple and efficient pretreatment procedures have been developed for the simultaneous extraction and cleanup of six novel brominated flame retardants (NBFRs) and eight common polybrominated diphenyl ethers (PBDEs) in human serum. The first sample pretreatment procedure was a quick, easy, cheap, effective, rugged, and safe (QuEChERS)-based approach. An acetone/hexane mixture was employed to isolate the lipid and analytes from the serum with a combination of MgSO 4 and NaCl, followed by a dispersive solid-phase extraction (d-SPE) step using C18 particles as a sorbent. The second sample pretreatment procedure was based on solid-phase extraction. The sample extraction and cleanup were conducted directly on an Oasis HLB SPE column using 5 % aqueous isopropanol, concentrated sulfuric acid, and 10 % aqueous methanol, followed by elution with dichloromethane. The NBFRs and PBDEs were then detected using gas chromatography-negative chemical ionization mass spectrometry (GC-NCI MS). The methods were assessed for repeatability, accuracy, selectivity, limits of detection (LODs), and linearity. The results of spike recovery experiments in fetal bovine serum showed that average recoveries ranged from 77.9 % to 128.8 % with relative standard deviations (RSDs) from 0.73 % to 12.37 % for most of the analytes. The LODs for the analytes in fetal bovine serum ranged from 0.3 to 50.8 pg/mL except for decabromodiphenyl ethane. The proposed method was successfully applied to the determination of the 14 brominated flame retardants in human serum. The two pretreatment procedures described here are simple, accurate, and precise, and are suitable for the routine analysis of human serum. Graphical Abstract Workflow of a QuEChERS-based approach (top) and an SPE-based approach (bottom) for the detection of PBDEs and NBFRs in serum.
Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.
Komenda, Martin; Víta, Martin; Vaitsis, Christos; Schwarz, Daniel; Pokorná, Andrea; Zary, Nabil; Dušek, Ladislav
2015-01-01
No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.
Curriculum Mapping with Academic Analytics in Medical and Healthcare Education
Komenda, Martin; Víta, Martin; Vaitsis, Christos; Schwarz, Daniel; Pokorná, Andrea; Zary, Nabil; Dušek, Ladislav
2015-01-01
Background No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution’s curriculum, including tools for unveiling relationships inside curricular datasets. Objective We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. Methods We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom’s taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. Results We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. Conclusions We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining. PMID:26624281
NASA Technical Reports Server (NTRS)
Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.
1992-01-01
An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.
NASA Technical Reports Server (NTRS)
Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.
1992-01-01
An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Datta, Dipayan, E-mail: datta@uni-mainz.de; Gauss, Jürgen, E-mail: gauss@uni-mainz.de
2014-09-14
An analytic scheme is presented for the evaluation of first derivatives of the energy for a unitary group based spin-adapted coupled cluster (CC) theory, namely, the combinatoric open-shell CC (COSCC) approach within the singles and doubles approximation. The widely used Lagrange multiplier approach is employed for the derivation of an analytical expression for the first derivative of the energy, which in combination with the well-established density-matrix formulation, is used for the computation of first-order electrical properties. Derivations of the spin-adapted lambda equations for determining the Lagrange multipliers and the expressions for the spin-free effective density matrices for the COSCC approachmore » are presented. Orbital-relaxation effects due to the electric-field perturbation are treated via the Z-vector technique. We present calculations of the dipole moments for a number of doublet radicals in their ground states using restricted open-shell Hartree-Fock (ROHF) and quasi-restricted HF (QRHF) orbitals in order to demonstrate the applicability of our analytic scheme for computing energy derivatives. We also report calculations of the chlorine electric-field gradients and nuclear quadrupole-coupling constants for the CCl, CH{sub 2}Cl, ClO{sub 2}, and SiCl radicals.« less
Are waves of relational assumptions eroding traditional analysis?
Meredith-Owen, William
2013-11-01
The author designates as 'traditional' those elements of psychoanalytic presumption and practice that have, in the wake of Fordham's legacy, helped to inform analytical psychology and expand our capacity to integrate the shadow. It is argued that this element of the broad spectrum of Jungian practice is in danger of erosion by the underlying assumptions of the relational approach, which is fast becoming the new establishment. If the maps of the traditional landscape of symbolic reference (primal scene, Oedipus et al.) are disregarded, analysts are left with only their own self-appointed authority with which to orientate themselves. This self-centric epistemological basis of the relationalists leads to a revision of 'analytic attitude' that may be therapeutic but is not essentially analytic. This theme is linked to the perennial challenge of balancing differentiation and merger and traced back, through Chasseguet-Smirgel, to its roots in Genesis. An endeavour is made to illustrate this within the Journal convention of clinically based discussion through a commentary on Colman's (2013) avowedly relational treatment of the case material presented in his recent Journal paper 'Reflections on knowledge and experience' and through an assessment of Jessica Benjamin's (2004) relational critique of Ron Britton's (1989) transference embodied approach. © 2013, The Society of Analytical Psychology.
Alexovič, Michal; Horstkotte, Burkhard; Solich, Petr; Sabo, Ján
2016-02-11
A critical overview on automation of modern liquid phase microextraction (LPME) approaches based on the liquid impregnation of porous sorbents and membranes is presented. It is the continuation of part 1, in which non-dispersive LPME techniques based on the use of the extraction phase (EP) in the form of drop, plug, film, or microflow have been surveyed. Compared to the approaches described in part 1, porous materials provide an improved support for the EP. Simultaneously they allow to enlarge its contact surface and to reduce the risk of loss by incident flow or by components of surrounding matrix. Solvent-impregnated membranes or hollow fibres are further ideally suited for analyte extraction with simultaneous or subsequent back-extraction. Their use can therefore improve the procedure robustness and reproducibility as well as it "opens the door" to the new operation modes and fields of application. However, additional work and time are required for membrane replacement and renewed impregnation. Automation of porous support-based and membrane-based approaches plays an important role in the achievement of better reliability, rapidness, and reproducibility compared to manual assays. Automated renewal of the extraction solvent and coupling of sample pretreatment with the detection instrumentation can be named as examples. The different LPME methodologies using impregnated membranes and porous supports for the extraction phase and the different strategies of their automation, and their analytical applications are comprehensively described and discussed in this part. Finally, an outlook on future demands and perspectives of LPME techniques from both parts as a promising area in the field of sample pretreatment is given. Copyright © 2015 Elsevier B.V. All rights reserved.
Structural analysis and design of multivariable control systems: An algebraic approach
NASA Technical Reports Server (NTRS)
Tsay, Yih Tsong; Shieh, Leang-San; Barnett, Stephen
1988-01-01
The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.
Mahieu, Nathaniel G; Patti, Gary J
2017-10-03
When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.
NASA Astrophysics Data System (ADS)
Chen, H.
2018-06-01
This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/ β interface, and the Al concentration at γ/ γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.
NASA Astrophysics Data System (ADS)
Chen, H.
2018-03-01
This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/β interface, and the Al concentration at γ/γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.
Forecasting hotspots using predictive visual analytics approach
Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David
2014-12-30
A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.
A New Analytic Framework for Moderation Analysis --- Moving Beyond Analytic Interactions
Tang, Wan; Yu, Qin; Crits-Christoph, Paul; Tu, Xin M.
2009-01-01
Conceptually, a moderator is a variable that modifies the effect of a predictor on a response. Analytically, a common approach as used in most moderation analyses is to add analytic interactions involving the predictor and moderator in the form of cross-variable products and test the significance of such terms. The narrow scope of such a procedure is inconsistent with the broader conceptual definition of moderation, leading to confusion in interpretation of study findings. In this paper, we develop a new approach to the analytic procedure that is consistent with the concept of moderation. The proposed framework defines moderation as a process that modifies an existing relationship between the predictor and the outcome, rather than simply a test of a predictor by moderator interaction. The approach is illustrated with data from a real study. PMID:20161453
A new frequency approach for light flicker evaluation in electric power systems
NASA Astrophysics Data System (ADS)
Feola, Luigi; Langella, Roberto; Testa, Alfredo
2015-12-01
In this paper, a new analytical estimator for light flicker in frequency domain, which is able to take into account also the frequency components neglected by the classical methods proposed in literature, is proposed. The analytical solutions proposed apply for any generic stationary signal affected by interharmonic distortion. The light flicker analytical estimator proposed is applied to numerous numerical case studies with the goal of showing i) the correctness and the improvements of the analytical approach proposed with respect to the other methods proposed in literature and ii) the accuracy of the results compared to those obtained by means of the classical International Electrotechnical Commission (IEC) flickermeter. The usefulness of the proposed analytical approach is that it can be included in signal processing tools for interharmonic penetration studies for the integration of renewable energy sources in future smart grids.
TCSPC based approaches for multiparameter detection in living cells
NASA Astrophysics Data System (ADS)
Jahn, Karolina; Buschmann, Volker; Koberling, Felix; Hille, Carsten
2014-03-01
In living cells a manifold of processes take place simultaneously. This implies a precise regulation of intracellular ion homeostasis. In order to understand their spatio-temporal pattern comprehensively, the development of multiplexing concepts is essential. Due to the multidimensional characteristics of fluorescence dyes (absorption and emission spectra, decay time, anisotropy), the highly sensitive and non-invasive fluorescence microscopy is a versatile tool for realising multiplexing concepts. A prerequisite are analyte-specific fluorescence dyes with low cross-sensitivity to other dyes and analytes, respectively. Here, two approaches for multiparameter detection in living cells are presented. Insect salivary glands are well characterised secretory active tissues which were used as model systems to evaluate multiplexing concepts. Salivary glands secrete a KCl-rich or NaCl-rich fluid upon stimulation which is mainly regulated by intracellular Ca2+ as second messenger. Thus, pairwise detection of intracellular Na+, Cl- and Ca2+ with the fluorescent dyes ANG2, MQAE and ACR were tested. Therefore, the dyes were excited simultaneously (2-photon excitation) and their corresponding fluorescence decay times were recorded within two spectral ranges using time-correlated singlephoton counting (TCSPC). A second approach presented here is based on a new TCSPC-platform covering decay time detection from picoseconds to milliseconds. Thereby, nanosecond decaying cellular fluorescence and microsecond decaying phosphorescence of Ruthenium-complexes, which is quenched by oxygen, were recorded simultaneously. In both cases changes in luminescence decay times can be linked to changes in analyte concentrations. In consequence of simultaneous excitation as well as detection, it is possible to get a deeper insight into spatio-temporal pattern in living tissues.
Dai, James Y.; Hughes, James P.
2012-01-01
The meta-analytic approach to evaluating surrogate end points assesses the predictiveness of treatment effect on the surrogate toward treatment effect on the clinical end point based on multiple clinical trials. Definition and estimation of the correlation of treatment effects were developed in linear mixed models and later extended to binary or failure time outcomes on a case-by-case basis. In a general regression setting that covers nonnormal outcomes, we discuss in this paper several metrics that are useful in the meta-analytic evaluation of surrogacy. We propose a unified 3-step procedure to assess these metrics in settings with binary end points, time-to-event outcomes, or repeated measures. First, the joint distribution of estimated treatment effects is ascertained by an estimating equation approach; second, the restricted maximum likelihood method is used to estimate the means and the variance components of the random treatment effects; finally, confidence intervals are constructed by a parametric bootstrap procedure. The proposed method is evaluated by simulations and applications to 2 clinical trials. PMID:22394448
Modern Adaptive Analytics Approach to Lowering Seismic Network Detection Thresholds
NASA Astrophysics Data System (ADS)
Johnson, C. E.
2017-12-01
Modern seismic networks present a number of challenges, but perhaps most notably are those related to 1) extreme variation in station density, 2) temporal variation in station availability, and 3) the need to achieve detectability for much smaller events of strategic importance. The first of these has been reasonably addressed in the development of modern seismic associators, such as GLASS 3.0 by the USGS/NEIC, though some work still remains to be done in this area. However, the latter two challenges demand special attention. Station availability is impacted by weather, equipment failure or the adding or removing of stations, and while thresholds have been pushed to increasingly smaller magnitudes, new algorithms are needed to achieve even lower thresholds. Station availability can be addressed by a modern, adaptive architecture that maintains specified performance envelopes using adaptive analytics coupled with complexity theory. Finally, detection thresholds can be lowered using a novel approach that tightly couples waveform analytics with the event detection and association processes based on a principled repicking algorithm that uses particle realignment for enhanced phase discrimination.
Asadollahi, Aziz; Khazanovich, Lev
2018-04-11
The emergence of ultrasonic dry point contact (DPC) transducers that emit horizontal shear waves has enabled efficient collection of high-quality data in the context of a nondestructive evaluation of concrete structures. This offers an opportunity to improve the quality of evaluation by adapting advanced imaging techniques. Reverse time migration (RTM) is a simulation-based reconstruction technique that offers advantages over conventional methods, such as the synthetic aperture focusing technique. RTM is capable of imaging boundaries and interfaces with steep slopes and the bottom boundaries of inclusions and defects. However, this imaging technique requires a massive amount of memory and its computation cost is high. In this study, both bottlenecks of the RTM are resolved when shear transducers are used for data acquisition. An analytical approach was developed to obtain the source and receiver wavefields needed for imaging using reverse time migration. It is shown that the proposed analytical approach not only eliminates the high memory demand, but also drastically reduces the computation time from days to minutes. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Chen, G.; Chacón, L.
2013-08-01
We propose a 1D analytical particle mover for the recent charge- and energy-conserving electrostatic particle-in-cell (PIC) algorithm in Ref. [G. Chen, L. Chacón, D.C. Barnes, An energy- and charge-conserving, implicit, electrostatic particle-in-cell algorithm, Journal of Computational Physics 230 (2011) 7018-7036]. The approach computes particle orbits exactly for a given piece-wise linear electric field. The resulting PIC algorithm maintains the exact charge and energy conservation properties of the original algorithm, but with improved performance (both in efficiency and robustness against the number of particles and timestep). We demonstrate the advantageous properties of the scheme with a challenging multiscale numerical test case, the ion acoustic wave. Using the analytical mover as a reference, we demonstrate that the choice of error estimator in the Crank-Nicolson mover has significant impact on the overall performance of the implicit PIC algorithm. The generalization of the approach to the multi-dimensional case is outlined, based on a novel and simple charge conserving interpolation scheme.
Hierarchical Matching and Regression with Application to Photometric Redshift Estimation
NASA Astrophysics Data System (ADS)
Murtagh, Fionn
2017-06-01
This work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is motivated by the variety of cosmological objects such as elliptical, spiral, active, and merging galaxies at a wide range of redshifts. Our aim is matching and similarity-based analytics that takes account of discrete relationships in the data. The information structure of the data is represented by a hierarchy or tree where the branch structure, rather than just the proximity, is important. The representation is related to p-adic number theory. The clustering or binning of the data values, related to the precision of the measurements, has a central role in this methodology. If used for regression, our approach is a method of cluster-wise regression, generalizing nearest neighbour regression. Both to exemplify this analytics approach, and to demonstrate computational benefits, we address the well-known photometric redshift or `photo-z' problem, seeking to match Sloan Digital Sky Survey (SDSS) spectroscopic and photometric redshifts.
Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics
Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert
2014-01-01
The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes two domains (patients and drugs) and encodes three relationships (patient similarity, drug similarity, and patient-drug prior associations). We describe a novel approach for performing a label propagation procedure to spread the label information representing the effectiveness of different drugs for different patients over this heterogeneous graph. The proposed method has been applied on a real-world EHR dataset to help identify personalized treatments for hypercholesterolemia. The experimental results demonstrate the effectiveness of the approach and suggest that the combination of appropriate patient similarity and drug similarity analytics could lead to actionable insights for personalized medicine. Particularly, by leveraging drug similarity in combination with patient similarity, our method could perform well even on new or rarely used drugs for which there are few records of known past performance. PMID:25717413
Phosphorescent nanosensors for in vivo tracking of histamine levels.
Cash, Kevin J; Clark, Heather A
2013-07-02
Continuously tracking bioanalytes in vivo will enable clinicians and researchers to profile normal physiology and monitor diseased states. Current in vivo monitoring system designs are limited by invasive implantation procedures and biofouling, limiting the utility of these tools for obtaining physiologic data. In this work, we demonstrate the first success in optically tracking histamine levels in vivo using a modular, injectable sensing platform based on diamine oxidase and a phosphorescent oxygen nanosensor. Our new approach increases the range of measurable analytes by combining an enzymatic recognition element with a reversible nanosensor capable of measuring the effects of enzymatic activity. We use these enzyme nanosensors (EnzNS) to monitor the in vivo histamine dynamics as the concentration rapidly increases and decreases due to administration and clearance. The EnzNS system measured kinetics that match those reported from ex vivo measurements. This work establishes a modular approach to in vivo nanosensor design for measuring a broad range of potential target analytes. Simply replacing the recognition enzyme, or both the enzyme and nanosensor, can produce a new sensor system capable of measuring a wide range of specific analytical targets in vivo.
Narrating practice: reflective accounts and the textual construction of reality.
Taylor, Carolyn
2003-05-01
Two approaches dominate current thinking in health and welfare: evidence-based practice and reflective practice. Whilst there is debate about the merits of evidence-based practice, reflective practice is generally accepted with critical debate as an important educational tool. Where critique does exist it tends to adopt a Foucauldian approach, focusing on the surveillance and self-regulatory aspects of reflective practice. This article acknowledges the critical purchase on the concept of reflective practice offered by Foucauldian approaches but argues that microsociological and discourse analytic approaches can further illuminate the subject and thus serve as a complement to them. The claims of proponents of reflective practice are explored, in opposition to the technical-rational approach of evidence-based practice. Reflective practice tends to adopt a naive or romantic realist position and fails to acknowledge the ways in which reflective accounts construct the world of practice. Microsociological approaches can help us to understand reflective accounts as examples of case-talk, constructed in a narrative form in the same way as case records and presentations.
Riemann-Hilbert technique scattering analysis of metamaterial-based asymmetric 2D open resonators
NASA Astrophysics Data System (ADS)
Kamiński, Piotr M.; Ziolkowski, Richard W.; Arslanagić, Samel
2017-12-01
The scattering properties of metamaterial-based asymmetric two-dimensional open resonators excited by an electric line source are investigated analytically. The resonators are, in general, composed of two infinite and concentric cylindrical layers covered with an infinitely thin, perfect conducting shell that has an infinite axial aperture. The line source is oriented parallel to the cylinder axis. An exact analytical solution of this problem is derived. It is based on the dual-series approach and its transformation to the equivalent Riemann-Hilbert problem. Asymmetric metamaterial-based configurations are found to lead simultaneously to large enhancements of the radiated power and to highly steerable Huygens-like directivity patterns; properties not attainable with the corresponding structurally symmetric resonators. The presented open resonator designs are thus interesting candidates for many scientific and engineering applications where enhanced directional near- and far-field responses, tailored with beam shaping and steering capabilities, are highly desired.
Using Neural Networks for Sensor Validation
NASA Technical Reports Server (NTRS)
Mattern, Duane L.; Jaw, Link C.; Guo, Ten-Huei; Graham, Ronald; McCoy, William
1998-01-01
This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.
Progress in chemical luminescence-based biosensors: A critical review.
Roda, Aldo; Mirasoli, Mara; Michelini, Elisa; Di Fusco, Massimo; Zangheri, Martina; Cevenini, Luca; Roda, Barbara; Simoni, Patrizia
2016-02-15
Biosensors are a very active research field. They have the potential to lead to low-cost, rapid, sensitive, reproducible, and miniaturized bioanalytical devices, which exploit the high binding avidity and selectivity of biospecific binding molecules together with highly sensitive detection principles. Of the optical biosensors, those based on chemical luminescence detection (including chemiluminescence, bioluminescence, electrogenerated chemiluminescence, and thermochemiluminescence) are particularly attractive, due to their high-to-signal ratio and the simplicity of the required measurement equipment. Several biosensors based on chemical luminescence have been described for quantitative, and in some cases multiplex, analysis of organic molecules (such as hormones, drugs, pollutants), proteins, and nucleic acids. These exploit a variety of miniaturized analytical formats, such as microfluidics, microarrays, paper-based analytical devices, and whole-cell biosensors. Nevertheless, despite the high analytical performances described in the literature, the field of chemical luminescence biosensors has yet to demonstrate commercial success. This review presents the main recent advances in the field and discusses the approaches, challenges, and open issues, with the aim of stimulating a broader interest in developing chemical luminescence biosensors and improving their commercial exploitation. Copyright © 2015 Elsevier B.V. All rights reserved.
OLED-based biosensing platform with ZnO nanoparticles for enzyme immobilization
NASA Astrophysics Data System (ADS)
Cai, Yuankun; Shinar, Ruth; Shinar, Joseph
2009-08-01
Organic light-emitting diode (OLED)-based sensing platforms are attractive for photoluminescence (PL)-based monitoring of a variety of analytes. Among the promising OLED attributes for sensing applications is the thin and flexible size and design of the OLED pixel array that is used for PL excitation. To generate a compact, fielddeployable sensor, other major sensor components, such as the sensing probe and the photodetector, in addition to the thin excitation source, should be compact. To this end, the OLED-based sensing platform was tested with composite thin biosensing films, where oxidase enzymes were immobilized on ZnO nanoparticles, rather than dissolved in solution, to generate a more compact device. The analytes tested, glucose, cholesterol, and lactate, were monitored by following their oxidation reactions in the presence of oxygen and their respective oxidase enzymes. During such reactions, oxygen is consumed and its residual concentration, which is determined by the initial concentration of the above-mentioned analytes, is monitored. The sensors utilized the oxygen-sensitive dye Pt octaethylporphyrin, embedded in polystyrene. The enzymes were sandwiched between two thin ZnO layers, an approach that was found to improve the stability of the sensing probes.
ERIC Educational Resources Information Center
Gade, Shubhada; Chari, Suresh
2013-01-01
The Medical Council of India, in the recent "Vision 2015" document, recommended curricular reforms for undergraduates. Case-based learning (CBL) is one method where students are motivated toward self-directed learning and to develop analytic and problem-solving skills. An overview of thyroid physiology was given in a didactic lecture. A…
Antibodies and antibody-derived analytical biosensors
Sharma, Shikha; Byrne, Hannah
2016-01-01
The rapid diagnosis of many diseases and timely initiation of appropriate treatment are critical determinants that promote optimal clinical outcomes and general public health. Biosensors are now being applied for rapid diagnostics due to their capacity for point-of-care use with minimum need for operator input. Antibody-based biosensors or immunosensors have revolutionized diagnostics for the detection of a plethora of analytes such as disease markers, food and environmental contaminants, biological warfare agents and illicit drugs. Antibodies are ideal biorecognition elements that provide sensors with high specificity and sensitivity. This review describes monoclonal and recombinant antibodies and different immobilization approaches crucial for antibody utilization in biosensors. Examples of applications of a variety of antibody-based sensor formats are also described. PMID:27365031
Affinity-based biosensors as promising tools for gene doping detection.
Minunni, Maria; Scarano, Simona; Mascini, Marco
2008-05-01
Innovative bioanalytical approaches can be foreseen as interesting means for solving relevant emerging problems in anti-doping control. Sport authorities fear that the newer form of doping, so-called gene doping, based on a misuse of gene therapy, will be undetectable and thus much less preventable. The World Anti-Doping Agency has already asked scientists to assist in finding ways to prevent and detect this newest kind of doping. In this Opinion article we discuss the main aspects of gene doping, from the putative target analytes to suitable sampling strategies. Moreover, we discuss the potential application of affinity sensing in this field, which so far has been successfully applied to a variety of analytical problems, from clinical diagnostics to food and environmental analysis.
Biosensors for the determination of environmental inhibitors of enzymes
NASA Astrophysics Data System (ADS)
Evtugyn, Gennadii A.; Budnikov, Herman C.; Nikolskaya, Elena B.
1999-12-01
Characteristic features of functioning and practical application of enzyme-based biosensors for the determination of environmental pollutants as enzyme inhibitors are considered with special emphasis on the influence of the methods used for the measurement of the rates of enzymic reactions, of enzyme immobilisation procedure and of the composition of the reaction medium on the analytical characteristics of inhibitor assays. The published data on the development of biosensors for detecting pesticides and heavy metals are surveyed. Special attention is given to the use of cholinesterase-based biosensors in environmental and analytical monitoring. The approaches to the estimation of kinetic parameters of inhibition are reviewed and the factors determining the selectivity and sensitivity of inhibitor assays in environmental objects are analysed. The bibliography includes 195 references.
ERIC Educational Resources Information Center
Thorsland, Martin N.; Novak, Joseph D.
1974-01-01
Described is an approach to assessment of intuitive and analytic modes of thinking in physics. These modes of thinking are associated with Ausubel's theory of learning. High ability in either intuitive or analytic thinking was associated with success in college physics, with high learning efficiency following a pattern expected on the basis of…
DNA barcode-based delineation of putative species: efficient start for taxonomic workflows
Kekkonen, Mari; Hebert, Paul D N
2014-01-01
The analysis of DNA barcode sequences with varying techniques for cluster recognition provides an efficient approach for recognizing putative species (operational taxonomic units, OTUs). This approach accelerates and improves taxonomic workflows by exposing cryptic species and decreasing the risk of synonymy. This study tested the congruence of OTUs resulting from the application of three analytical methods (ABGD, BIN, GMYC) to sequence data for Australian hypertrophine moths. OTUs supported by all three approaches were viewed as robust, but 20% of the OTUs were only recognized by one or two of the methods. These OTUs were examined for three criteria to clarify their status. Monophyly and diagnostic nucleotides were both uninformative, but information on ranges was useful as sympatric sister OTUs were viewed as distinct, while allopatric OTUs were merged. This approach revealed 124 OTUs of Hypertrophinae, a more than twofold increase from the currently recognized 51 species. Because this analytical protocol is both fast and repeatable, it provides a valuable tool for establishing a basic understanding of species boundaries that can be validated with subsequent studies. PMID:24479435
New approaches in GMO detection.
Querci, Maddalena; Van den Bulcke, Marc; Zel, Jana; Van den Eede, Guy; Broll, Hermann
2010-03-01
The steady rate of development and diffusion of genetically modified plants and their increasing diversification of characteristics, genes and genetic control elements poses a challenge in analysis of genetically modified organisms (GMOs). It is expected that in the near future the picture will be even more complex. Traditional approaches, mostly based on the sequential detection of one target at a time, or on a limited multiplexing, allowing only a few targets to be analysed at once, no longer meet the testing requirements. Along with new analytical technologies, new approaches for the detection of GMOs authorized for commercial purposes in various countries have been developed that rely on (1) a smart and accurate strategy for target selection, (2) the use of high-throughput systems or platforms for the detection of multiple targets and (3) algorithms that allow the conversion of analytical results into an indication of the presence of individual GMOs potentially present in an unknown sample. This paper reviews the latest progress made in GMO analysis, taking examples from the most recently developed strategies and tools, and addresses some of the critical aspects related to these approaches.
NASA Astrophysics Data System (ADS)
Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.
2018-06-01
The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.
Data Literacy: Real-World Learning through Problem-Solving with Data Sets
ERIC Educational Resources Information Center
Erwin, Robin W., Jr.
2015-01-01
The achievement of deep learning by secondary students requires teaching approaches that draw students into task commitment, integrated curricula, and analytical thinking. By using real-world data sets in project based instructional units, teachers can guide students in analyzing, interpreting, and reporting quantitative data. Working with…
ADHD and Reading Disabilities: A Cluster Analytic Approach for Distinguishing Subgroups.
ERIC Educational Resources Information Center
Bonafina, Marcela A.; Newcorn, Jeffrey H.; McKay, Kathleen E.; Koda, Vivian H.; Halperin, Jeffrey M.
2000-01-01
Using cluster analysis, a study empirically divided 54 children with attention-deficit/hyperactivity disorder (ADHD) based on their Full Scale IQ and reading ability. Clusters had different patterns of cognitive, behavioral, and neurochemical functions, as determined by discrepancies in Verbal-Performance IQ, academic achievement, parent…
Decision making in prioritization of required operational capabilities
NASA Astrophysics Data System (ADS)
Andreeva, P.; Karev, M.; Kovacheva, Ts.
2015-10-01
The paper describes an expert heuristic approach to prioritization of required operational capabilities in the field of defense. Based on expert assessment and by application of the method of Analytical Hierarchical Process, a methodology for their prioritization has been developed. It has been applied to practical simulation decision making games.
Selecting Evaluation Comparison Groups: A Cluster Analytic Approach.
ERIC Educational Resources Information Center
Davis, Todd Mclin; McLean, James E.
A persistent problem in the evaluation of field-based projects is the lack of no-treatment comparison groups. Frequently, potential comparison groups are confounded by socioeconomic, racial, or other factors. Among the possible methods for dealing with this problem are various matching procedures, but they are cumbersome to use with multiple…
Teaching Advanced Vehicle Dynamics Using a Project Based Learning (PBL) Approach
ERIC Educational Resources Information Center
Redkar, Sangram
2012-01-01
This paper presents an interesting teaching experiment carried out at XXX University. The author offered a new course in computational/analytical vehicle dynamics to senior undergraduate students, graduate students and practicing engineers. The objective of the course was to present vehicle dynamics theory with practical applications using…
Newton Algorithms for Analytic Rotation: An Implicit Function Approach
ERIC Educational Resources Information Center
Boik, Robert J.
2008-01-01
In this paper implicit function-based parameterizations for orthogonal and oblique rotation matrices are proposed. The parameterizations are used to construct Newton algorithms for minimizing differentiable rotation criteria applied to "m" factors and "p" variables. The speed of the new algorithms is compared to that of existing algorithms and to…
Particle Acceleration and Radiative Losses at Relativistic Shocks
NASA Astrophysics Data System (ADS)
Dempsey, P.; Duffy, P.
A semi-analytic approach to the relativistic transport equation with isotropic diffusion and consistent radiative losses is presented. It is based on the eigenvalue method first introduced in Kirk & Schneider [5]and Heavens & Drury [3]. We demonstrate the pitch-angle dependence of the cut-off in relativistic shocks.
Multilayered Word Structure Model for Assessing Spelling of Finnish Children in Shallow Orthography
ERIC Educational Resources Information Center
Kulju, Pirjo; Mäkinen, Marita
2017-01-01
This study explores Finnish children's word-level spelling by applying a linguistically based multilayered word structure model for assessing spelling performance. The model contributes to the analytical qualitative assessment approach in order to identify children's spelling performance for enhancing writing skills. The children (N = 105)…
NASA Astrophysics Data System (ADS)
Setiawan, R.
2018-05-01
In this paper, Economic Order Quantity (EOQ) of the vendor-buyer supply-chain model under a probabilistic condition with imperfect quality items has been analysed. The analysis is delivered using two concepts in game theory approach, which is Stackelberg equilibrium and Pareto Optimal, under non-cooperative and cooperative games, respectively. Another result is getting acomparison of theoptimal result between integrated scheme and game theory approach based on analytical and numerical result using appropriate simulation data.
Pumping tests in nonuniform aquifers - The radially symmetric case
Butler, J.J.
1988-01-01
Traditionally, pumping-test-analysis methodology has been limited to applications involving aquifers whose properties are assumed uniform in space. This work attempts to assess the applicability of analytical methodology to a broader class of units with spatially varying properties. An examination of flow behavior in a simple configuration consisting of pumping from the center of a circular disk embedded in a matrix of differing properties is the basis for this investigation. A solution describing flow in this configuration is obtained through Laplace-transform techniques using analytical and numerical inversion schemes. Approaches for the calculation of flow properties in conditions that can be roughly represented by this simple configuration are proposed. Possible applications include a wide variety of geologic structures, as well as the case of a well skin resulting from drilling or development. Of more importance than the specifics of these techniques for analysis of water-level responses is the insight into flow behavior during a pumping test that is provided by the large-time form of the derived solution. The solution reveals that drawdown during a pumping test can be considered to consist of two components that are dependent and independent of near-well properties, respectively. Such an interpretation of pumping-test drawdown allows some general conclusions to be drawn concerning the relationship between parameters calculated using analytical approaches based on curve-matching and those calculated using approaches based on the slope of a semilog straight line plot. The infinite-series truncation that underlies the semilog analytical approaches is shown to remove further contributions of near-well material to total drawdown. In addition, the semilog distance-drawdown approach is shown to yield an expression that is equivalent to the Thiem equation. These results allow some general recommendations to be made concerning observation-well placement for pumping tests in nonuniform aquifers. The relative diffusivity of material on either side of a discontinuity is shown to be the major factor in controlling flow behavior during the period in which the front of the cone of depression is moving across the discontinuity. Though resulting from an analysis of flow in an idealized configuration, the insights of this work into flow behavior during a pumping test are applicable to a wide class of nonuniform units. ?? 1988.
Analytical approaches to determination of total choline in foods and dietary supplements.
Phillips, Melissa M
2012-06-01
Choline is a quaternary amine that is synthesized in the body or consumed through the diet. Choline is critical for cell membrane structure and function and in synthesis of the neurotransmitter acetylcholine. Although the human body produces this micronutrient, dietary supplementation of choline is necessary for good health. The major challenge in the analysis of choline in foods and dietary supplements is in the extraction and/or hydrolysis approach. In many products, choline is present as choline esters, which can be quantitated individually or treated with acid, base, or enzymes in order to release choline ions for analysis. A critical review of approaches based on extraction and quantitation of each choline ester as well as hydrolysis-based methods for determination of total choline in foods and dietary supplements is presented.
Analytics that Inform the University: Using Data You Already Have
ERIC Educational Resources Information Center
Dziuban, Charles; Moskal, Patsy; Cavanagh, Thomas; Watts, Andre
2012-01-01
The authors describe the University of Central Florida's top-down/bottom-up action analytics approach to using data to inform decision-making at the University of Central Florida. The top-down approach utilizes information about programs, modalities, and college implementation of Web initiatives. The bottom-up approach continuously monitors…
Recent Advances in Analytical Pyrolysis to Investigate Organic Materials in Heritage Science.
Degano, Ilaria; Modugno, Francesca; Bonaduce, Ilaria; Ribechini, Erika; Colombini, Maria Perla
2018-06-18
The molecular characterization of organic materials in samples from artworks and historical objects traditionally entailed qualitative and quantitative analyses by HPLC and GC. Today innovative approaches based on analytical pyrolysis enable samples to be analysed without any chemical pre-treatment. Pyrolysis, which is often considered as a screening technique, shows previously unexplored potential thanks to recent instrumental developments. Organic materials that are macromolecular in nature, or undergo polymerization upon curing and ageing can now be better investigated. Most constituents of paint layers and archaeological organic substances contain major insoluble and chemically non-hydrolysable fractions that are inaccessible to GC or HPLC. To date, molecular scientific investigations of the organic constituents of artworks and historical objects have mostly focused on the minor constituents of the sample. This review presents recent advances in the qualitative and semi-quantitative analyses of organic materials in heritage objects based on analytical pyrolysis coupled with mass spectrometry. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Silina, Yuliya E; Volmer, Dietrich A
2013-12-07
Analytical applications often require rapid measurement of compounds from complex sample mixtures. High-speed mass spectrometry approaches frequently utilize techniques based on direct ionization of the sample by laser irradiation, mostly by means of matrix-assisted laser desorption/ionization (MALDI). Compounds of low molecular weight are difficult to analyze by MALDI, however, because of severe interferences in the low m/z range from the organic matrix used for desorption/ionization. In recent years, surface-assisted laser desorption/ionization (SALDI) techniques have shown promise for small molecule analysis, due to the unique properties of nanostructured surfaces, in particular, the lack of a chemical background in the low m/z range and enhanced production of analyte ions by SALDI. This short review article presents a summary of the most promising recent developments in SALDI materials for MS analysis of low molecular weight analytes, with emphasis on nanostructured materials based on metals and semiconductors.