LDEF data: Comparisons with existing models

Science.gov (United States)

Coombs, Cassandra R.; Watts, Alan J.; Wagner, John D.; Atkinson, Dale R.

1993-04-01

The relationship between the observed cratering impact damage on the Long Duration Exposure Facility (LDEF) versus the existing models for both the natural environment of micrometeoroids and the man-made debris was investigated. Experimental data was provided by several LDEF Principal Investigators, Meteoroid and Debris Special Investigation Group (M&D SIG) members, and by the Kennedy Space Center Analysis Team (KSC A-Team) members. These data were collected from various aluminum materials around the LDEF satellite. A PC (personal computer) computer program, SPENV, was written which incorporates the existing models of the Low Earth Orbit (LEO) environment. This program calculates the expected number of impacts per unit area as functions of altitude, orbital inclination, time in orbit, and direction of the spacecraft surface relative to the velocity vector, for both micrometeoroids and man-made debris. Since both particle models are couched in terms of impact fluxes versus impactor particle size, and much of the LDEF data is in the form of crater production rates, scaling laws have been used to relate the two. Also many hydrodynamic impact computer simulations were conducted, using CTH, of various impact events, that identified certain modes of response, including simple metallic target cratering, perforations and delamination effects of coatings.

Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization

Directory of Open Access Journals (Sweden)

Xuefeng Yan

2013-01-01

Full Text Available The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation.

Modeling with Young Students--Quantitative and Qualitative.

Science.gov (United States)

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

1999-01-01

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

A website evaluation model by integration of previous evaluation models using a quantitative approach

Directory of Open Access Journals (Sweden)

Ali Moeini

2015-01-01

Full Text Available Regarding the ecommerce growth, websites play an essential role in business success. Therefore, many authors have offered website evaluation models since 1995. Although, the multiplicity and diversity of evaluation models make it difficult to integrate them into a single comprehensive model. In this paper a quantitative method has been used to integrate previous models into a comprehensive model that is compatible with them. In this approach the researcher judgment has no role in integration of models and the new model takes its validity from 93 previous models and systematic quantitative approach.

A quantitative speciation model for the adsorption of organic pollutants on activated carbon.

Science.gov (United States)

Grivé, M; García, D; Domènech, C; Richard, L; Rojo, I; Martínez, X; Rovira, M

2013-01-01

Granular activated carbon (GAC) is commonly used as adsorbent in water treatment plants given its high capacity for retaining organic pollutants in aqueous phase. The current knowledge on GAC behaviour is essentially empirical, and no quantitative description of the chemical relationships between GAC surface groups and pollutants has been proposed. In this paper, we describe a quantitative model for the adsorption of atrazine onto GAC surface. The model is based on results of potentiometric titrations and three types of adsorption experiments which have been carried out in order to determine the nature and distribution of the functional groups on the GAC surface, and evaluate the adsorption characteristics of GAC towards atrazine. Potentiometric titrations have indicated the existence of at least two different families of chemical groups on the GAC surface, including phenolic- and benzoic-type surface groups. Adsorption experiments with atrazine have been satisfactorily modelled with the geochemical code PhreeqC, assuming that atrazine is sorbed onto the GAC surface in equilibrium (log Ks = 5.1 ± 0.5). Independent thermodynamic calculations suggest a possible adsorption of atrazine on a benzoic derivative. The present work opens a new approach for improving the adsorption capabilities of GAC towards organic pollutants by modifying its chemical properties.

Modelling and Quantitative Analysis of LTRACK–A Novel Mobility Management Algorithm

Directory of Open Access Journals (Sweden)

Benedek Kovács

2006-01-01

Full Text Available This paper discusses the improvements and parameter optimization issues of LTRACK, a recently proposed mobility management algorithm. Mathematical modelling of the algorithm and the behavior of the Mobile Node (MN are used to optimize the parameters of LTRACK. A numerical method is given to determine the optimal values of the parameters. Markov chains are used to model both the base algorithm and the so-called loop removal effect. An extended qualitative and quantitative analysis is carried out to compare LTRACK to existing handover mechanisms such as MIP, Hierarchical Mobile IP (HMIP, Dynamic Hierarchical Mobility Management Strategy (DHMIP, Telecommunication Enhanced Mobile IP (TeleMIP, Cellular IP (CIP and HAWAII. LTRACK is sensitive to network topology and MN behavior so MN movement modelling is also introduced and discussed with different topologies. The techniques presented here can not only be used to model the LTRACK algorithm, but other algorithms too. There are many discussions and calculations to support our mathematical model to prove that it is adequate in many cases. The model is valid on various network levels, scalable vertically in the ISO-OSI layers and also scales well with the number of network elements.

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

Science.gov (United States)

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

The landscape of existing models for high-throughput exposure assessment

DEFF Research Database (Denmark)

Jolliet, O.; Fantke, Peter; Huang, L.

2017-01-01

and ability to easily handle large datasets. For building materials a series of diffusion-based models have been developed to predict the chemicals emissions from building materials to indoor air, but existing models require complex analytical or numerical solutions, which are not suitable for LCA or HTS...... applications. Thus, existing model solutions needed to be simplified for application in LCA and HTS, and a parsimonious model has been developed by Huang et al. (2017) to address this need. For SVOCs, simplified solutions do exist, assuming constant SVOC concentrations in building materials and steadystate...... for skin permeation and volatilization as competing processes and that requires a limited number of readily available physiochemical properties would be suitable for LCA and HTS purposes. Thus, the multi-pathway exposure model for chemicals in cosmetics developed by Ernstoff et al.constitutes a suitable...

Parts of the Whole: Strategies for the Spread of Quantitative Literacy: What Models Can Tell Us

Directory of Open Access Journals (Sweden)

Dorothy Wallace

2014-07-01

Full Text Available Two conceptual frameworks, one from graph theory and one from dynamical systems, have been offered as explanations for complex phenomena in biology and also as possible models for the spread of ideas. The two models are based on different assumptions and thus predict quite different outcomes for the fate of either biological species or ideas. We argue that, depending on the culture in which they exist, one can identify which model is more likely to reflect the survival of two competing ideas. Based on this argument we suggest how two strategies for embedding and normalizing quantitative literacy in a given institution are likely to succeed or fail.

Quantitative risk assessment system (QRAS)

Science.gov (United States)

Weinstock, Robert M (Inventor); Smidts, Carol S (Inventor); Mosleh, Ali (Inventor); Chang, Yung-Hsien (Inventor); Swaminathan, Sankaran (Inventor); Groen, Francisco J (Inventor); Tan, Zhibin (Inventor)

2001-01-01

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

Testing process predictions of models of risky choice: a quantitative model comparison approach

Science.gov (United States)

Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

2013-01-01

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

Testing Process Predictions of Models of Risky Choice: A Quantitative Model Comparison Approach

Directory of Open Access Journals (Sweden)

Thorsten ePachur

2013-09-01

Full Text Available This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or nonlinear functions thereof and the separate evaluation of risky options (expectation models. Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models. We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter, Gigerenzer, & Hertwig, 2006, and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up and direction of search (i.e., gamble-wise vs. reason-wise. In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly; acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988 called similarity. In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies.

Quantitative sociodynamics stochastic methods and models of social interaction processes

CERN Document Server

Helbing, Dirk

1995-01-01

Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the log...

Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes

CERN Document Server

Helbing, Dirk

2010-01-01

This new edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens new perspectives in the social sciences. It includes many established models a...

A Review of Quantitative Situation Assessment Models for Nuclear Power Plant Operators

International Nuclear Information System (INIS)

Lee, Hyun Chul; Seong, Poong Hyun

2009-01-01

Situation assessment is the process of developing situation awareness and situation awareness is defined as 'the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future.' Situation awareness is an important element influencing human actions because human decision making is based on the result of situation assessment or situation awareness. There are many models for situation awareness and those models can be categorized into qualitative or quantitative. As the effects of some input factors on situation awareness can be investigated through the quantitative models, the quantitative models are more useful for the design of operator interfaces, automation strategies, training program, and so on, than the qualitative models. This study presents the review of two quantitative models of situation assessment (SA) for nuclear power plant operators

Quantitative system validation in model driven design

DEFF Research Database (Denmark)

Hermanns, Hilger; Larsen, Kim Guldstrand; Raskin, Jean-Francois

2010-01-01

The European STREP project Quasimodo1 develops theory, techniques and tool components for handling quantitative constraints in model-driven development of real-time embedded systems, covering in particular real-time, hybrid and stochastic aspects. This tutorial highlights the advances made, focus...

Quantitative interface models for simulating microstructure evolution

International Nuclear Information System (INIS)

Zhu, J.Z.; Wang, T.; Zhou, S.H.; Liu, Z.K.; Chen, L.Q.

2004-01-01

To quantitatively simulate microstructural evolution in real systems, we investigated three different interface models: a sharp-interface model implemented by the software DICTRA and two diffuse-interface models which use either physical order parameters or artificial order parameters. A particular example is considered, the diffusion-controlled growth of a γ ' precipitate in a supersaturated γ matrix in Ni-Al binary alloys. All three models use the thermodynamic and kinetic parameters from the same databases. The temporal evolution profiles of composition from different models are shown to agree with each other. The focus is on examining the advantages and disadvantages of each model as applied to microstructure evolution in alloys

Hidden Markov Model for quantitative prediction of snowfall

Indian Academy of Sciences (India)

A Hidden Markov Model (HMM) has been developed for prediction of quantitative snowfall in Pir-Panjal and Great Himalayan mountain ranges of Indian Himalaya. The model predicts snowfall for two days in advance using daily recorded nine meteorological variables of past 20 winters from 1992–2012. There are six ...

Modeling conflict : research methods, quantitative modeling, and lessons learned.

Energy Technology Data Exchange (ETDEWEB)

Rexroth, Paul E.; Malczynski, Leonard A.; Hendrickson, Gerald A.; Kobos, Peter Holmes; McNamara, Laura A.

2004-09-01

This study investigates the factors that lead countries into conflict. Specifically, political, social and economic factors may offer insight as to how prone a country (or set of countries) may be for inter-country or intra-country conflict. Largely methodological in scope, this study examines the literature for quantitative models that address or attempt to model conflict both in the past, and for future insight. The analysis concentrates specifically on the system dynamics paradigm, not the political science mainstream approaches of econometrics and game theory. The application of this paradigm builds upon the most sophisticated attempt at modeling conflict as a result of system level interactions. This study presents the modeling efforts built on limited data and working literature paradigms, and recommendations for future attempts at modeling conflict.

Quantitative Models and Analysis for Reactive Systems

DEFF Research Database (Denmark)

Thrane, Claus

phones and websites. Acknowledging that now more than ever, systems come in contact with the physical world, we need to revise the way we construct models and verification algorithms, to take into account the behavior of systems in the presence of approximate, or quantitative information, provided...

Quantitative model analysis with diverse biological data: applications in developmental pattern formation.

Science.gov (United States)

Pargett, Michael; Umulis, David M

2013-07-15

Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works, and to infer regulatory interactions that produce a model consistent with the observed data. Both of these approaches to modeling are informed by experimental data, however, much of the data available or even acquirable are not quantitative. Data that is not strictly quantitative cannot be used by classical, quantitative, model-based analyses that measure a difference between the measured observation and the model prediction for that observation. To bridge the model-to-data gap, a variety of techniques have been developed to measure model "fitness" and provide numerical values that can subsequently be used in model optimization or model inference studies. Here, we discuss a selection of traditional and novel techniques to transform data of varied quality and enable quantitative comparison with mathematical models. This review is intended to both inform the use of these model analysis methods, focused on parameter estimation, and to help guide the choice of method to use for a given study based on the type of data available. Applying techniques such as normalization or optimal scaling may significantly improve the utility of current biological data in model-based study and allow greater integration between disparate types of data. Copyright © 2013 Elsevier Inc. All rights reserved.

Interpretation of protein quantitation using the Bradford assay: comparison with two calculation models.

Science.gov (United States)

Ku, Hyung-Keun; Lim, Hyuk-Min; Oh, Kyong-Hwa; Yang, Hyo-Jin; Jeong, Ji-Seon; Kim, Sook-Kyung

2013-03-01

The Bradford assay is a simple method for protein quantitation, but variation in the results between proteins is a matter of concern. In this study, we compared and normalized quantitative values from two models for protein quantitation, where the residues in the protein that bind to anionic Coomassie Brilliant Blue G-250 comprise either Arg and Lys (Method 1, M1) or Arg, Lys, and His (Method 2, M2). Use of the M2 model yielded much more consistent quantitation values compared with use of the M1 model, which exhibited marked overestimations against protein standards. Copyright © 2012 Elsevier Inc. All rights reserved.

Modelling the feasibility of retrofitting hydropower to existing South ...

African Journals Online (AJOL)

An investigation was carried out with the primary objective of ascertaining whether it is possible to develop a model for determining the feasibility of retrofitting hydropower to existing dams in South Africa. The need for such a model is primarily due to the growing importance of small-scale hydropower projects resulting from ...

Evaluation of recent quantitative magnetospheric magnetic field models

International Nuclear Information System (INIS)

Walker, R.J.

1976-01-01

Recent quantitative magnetospheric field models contain many features not found in earlier models. Magnetopause models which include the effects of the dipole tilt were presented. More realistic models of the tail field include tail currents which close on the magnetopause, cross-tail currents of finite thickness, and cross-tail current models which model the position of the neutral sheet as a function of tilt. Finally, models have attempted to calculate the field of currents distributed in the inner magnetosphere. As the purpose of a magnetospheric model is to provide a mathematical description of the field that reasonably reproduces the observed magnetospheric field, several recent models were compared with the observed ΔB(B/sub observed/--B/sub main field/) contours. Models containing only contributions from magnetopause and tail current systems are able to reproduce the observed quiet time field only in an extremely qualitative way. The best quantitative agreement between models and observations occurs when currents distributed in the inner magnetosphere are added to the magnetopause and tail current systems. However, the distributed current models are valid only for zero tilt. Even the models which reproduce the average observed field reasonably well may not give physically reasonable field gradients. Three of the models evaluated contain regions in the near tail in which the field gradient reverses direction. One region in which all the models fall short is that around the polar cusp, though most can be used to calculate the position of the last closed field line reasonably well

Quantitative Analysis of Probabilistic Models of Software Product Lines with Statistical Model Checking

DEFF Research Database (Denmark)

ter Beek, Maurice H.; Legay, Axel; Lluch Lafuente, Alberto

2015-01-01

We investigate the suitability of statistical model checking techniques for analysing quantitative properties of software product line models with probabilistic aspects. For this purpose, we enrich the feature-oriented language FLAN with action rates, which specify the likelihood of exhibiting pa...

Correlations of 3T DCE-MRI Quantitative Parameters with Microvessel Density in a Human-Colorectal-Cancer Xenograft Mouse Model

International Nuclear Information System (INIS)

Ahn, Sung Jun; An, Chan Sik; Koom, Woong Sub; Song, Ho Taek; Suh, Jin Suck

2011-01-01

To investigate the correlation between quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) parameters and microvascular density (MVD) in a human-colon-cancer xenograft mouse model using 3 Tesla MRI. A human-colon-cancer xenograft model was produced by subcutaneously inoculating 1 X 106 DLD-1 human-colon-cancer cells into the right hind limbs of 10 mice. The tumors were allowed to grow for two weeks and then assessed using MRI. DCE-MRI was performed by tail vein injection of 0.3 mmol/kg of gadolinium. A region of interest (ROI) was drawn at the midpoints along the z-axes of the tumors, and a Tofts model analysis was performed. The quantitative parameters (Ktrans, Kep and Ve) from the whole transverse ROI and the hotspot ROI of the tumor were calculated. Immunohistochemical microvessel staining was performed and analyzed according to Weidner's criteria at the corresponding MRI sections. Additional Hematoxylin and Eosin staining was performed to evaluate tumor necrosis. The Mann-Whitney test and Spearman's rho correlation analysis were performed to prove the existence of a correlation between the quantitative parameters, necrosis, and MVD. Whole transverse ROI of the tumor showed no significant relationship between the MVD values and quantitative DCE-MRI parameters. In the hotspot ROI, there was a difference in MVD between low and high group of Ktrans and Kep that had marginally statistical significance (ps = 0.06 and 0.07, respectively). Also, Ktrans and Kep were found to have an inverse relationship with MVD (r -0.61, p = 0.06 in Ktrans; r = -0.60, p = 0.07 in Kep). Quantitative analysis of T1-weighted DCE-MRI using hotspot ROI may provide a better histologic match than whole transverse section ROI. Within the hotspots, Ktrans and Kep tend to have a reverse correlation with MVD in this colon cancer mouse model.

Correlations of 3T DCE-MRI Quantitative Parameters with Microvessel Density in a Human-Colorectal-Cancer Xenograft Mouse Model

Energy Technology Data Exchange (ETDEWEB)

Ahn, Sung Jun; An, Chan Sik; Koom, Woong Sub; Song, Ho Taek; Suh, Jin Suck [Yonsei University College of Medicine, Seoul (Korea, Republic of)

2011-11-15

To investigate the correlation between quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) parameters and microvascular density (MVD) in a human-colon-cancer xenograft mouse model using 3 Tesla MRI. A human-colon-cancer xenograft model was produced by subcutaneously inoculating 1 X 106 DLD-1 human-colon-cancer cells into the right hind limbs of 10 mice. The tumors were allowed to grow for two weeks and then assessed using MRI. DCE-MRI was performed by tail vein injection of 0.3 mmol/kg of gadolinium. A region of interest (ROI) was drawn at the midpoints along the z-axes of the tumors, and a Tofts model analysis was performed. The quantitative parameters (Ktrans, Kep and Ve) from the whole transverse ROI and the hotspot ROI of the tumor were calculated. Immunohistochemical microvessel staining was performed and analyzed according to Weidner's criteria at the corresponding MRI sections. Additional Hematoxylin and Eosin staining was performed to evaluate tumor necrosis. The Mann-Whitney test and Spearman's rho correlation analysis were performed to prove the existence of a correlation between the quantitative parameters, necrosis, and MVD. Whole transverse ROI of the tumor showed no significant relationship between the MVD values and quantitative DCE-MRI parameters. In the hotspot ROI, there was a difference in MVD between low and high group of Ktrans and Kep that had marginally statistical significance (ps = 0.06 and 0.07, respectively). Also, Ktrans and Kep were found to have an inverse relationship with MVD (r -0.61, p = 0.06 in Ktrans; r = -0.60, p = 0.07 in Kep). Quantitative analysis of T1-weighted DCE-MRI using hotspot ROI may provide a better histologic match than whole transverse section ROI. Within the hotspots, Ktrans and Kep tend to have a reverse correlation with MVD in this colon cancer mouse model.

Model for Quantitative Evaluation of Enzyme Replacement Treatment

Directory of Open Access Journals (Sweden)

Radeva B.

2009-12-01

Full Text Available Gaucher disease is the most frequent lysosomal disorder. Its enzyme replacement treatment was the new progress of modern biotechnology, successfully used in the last years. The evaluation of optimal dose of each patient is important due to health and economical reasons. The enzyme replacement is the most expensive treatment. It must be held continuously and without interruption. Since 2001, the enzyme replacement therapy with Cerezyme*Genzyme was formally introduced in Bulgaria, but after some time it was interrupted for 1-2 months. The dose of the patients was not optimal. The aim of our work is to find a mathematical model for quantitative evaluation of ERT of Gaucher disease. The model applies a kind of software called "Statistika 6" via the input of the individual data of 5-year-old children having the Gaucher disease treated with Cerezyme. The output results of the model gave possibilities for quantitative evaluation of the individual trends in the development of the disease of each child and its correlation. On the basis of this results, we might recommend suitable changes in ERT.

A Review on Quantitative Models for Sustainable Food Logistics Management

Directory of Open Access Journals (Sweden)

M. Soysal

2012-12-01

Full Text Available The last two decades food logistics systems have seen the transition from a focus on traditional supply chain management to food supply chain management, and successively, to sustainable food supply chain management. The main aim of this study is to identify key logistical aims in these three phases and analyse currently available quantitative models to point out modelling challenges in sustainable food logistics management (SFLM. A literature review on quantitative studies is conducted and also qualitative studies are consulted to understand the key logistical aims more clearly and to identify relevant system scope issues. Results show that research on SFLM has been progressively developing according to the needs of the food industry. However, the intrinsic characteristics of food products and processes have not yet been handled properly in the identified studies. The majority of the works reviewed have not contemplated on sustainability problems, apart from a few recent studies. Therefore, the study concludes that new and advanced quantitative models are needed that take specific SFLM requirements from practice into consideration to support business decisions and capture food supply chain dynamics.

Modeling and validation of existing VAV system components

Energy Technology Data Exchange (ETDEWEB)

Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal, PQ (Canada)

2004-07-01

The optimization of supervisory control strategies and local-loop controllers can improve the performance of HVAC (heating, ventilating, air-conditioning) systems. In this study, the component model of the fan, the damper and the cooling coil were developed and validated against monitored data of an existing variable air volume (VAV) system installed at Montreal's Ecole de Technologie Superieure. The measured variables that influence energy use in individual HVAC models included: (1) outdoor and return air temperature and relative humidity, (2) supply air and water temperatures, (3) zone airflow rates, (4) supply duct, outlet fan, mixing plenum static pressures, (5) fan speed, and (6) minimum and principal damper and cooling and heating coil valve positions. The additional variables that were considered, but not measured were: (1) fan and outdoor airflow rate, (2) inlet and outlet cooling coil relative humidity, and (3) liquid flow rate through the heating or cooling coils. The paper demonstrates the challenges of the validation process when monitored data of existing VAV systems are used. 7 refs., 11 figs.

A quantitative phase field model for hydride precipitation in zirconium alloys: Part I. Development of quantitative free energy functional

International Nuclear Information System (INIS)

Shi, San-Qiang; Xiao, Zhihua

2015-01-01

A temperature dependent, quantitative free energy functional was developed for the modeling of hydride precipitation in zirconium alloys within a phase field scheme. The model takes into account crystallographic variants of hydrides, interfacial energy between hydride and matrix, interfacial energy between hydrides, elastoplastic hydride precipitation and interaction with externally applied stress. The model is fully quantitative in real time and real length scale, and simulation results were compared with limited experimental data available in the literature with a reasonable agreement. The work calls for experimental and/or theoretical investigations of some of the key material properties that are not yet available in the literature

How Can Blockchain Technology Disrupt the Existing Business Models?

OpenAIRE

Witold Nowiński; Miklós Kozma

2017-01-01

Objective: The main purpose of the paper is to show that blockchain technology may disrupt the existing business models and to explore how this may occur. Research Design & Methods: This is a theory development paper which relies on a literature review and desk re-search. The discussion of the reviewed sources leads to the formulation of three re-search propositions. Findings: The paper provides a short overview of key literature on business models and business model innovation, indic...

Modeling Logistic Performance in Quantitative Microbial Risk Assessment

NARCIS (Netherlands)

Rijgersberg, H.; Tromp, S.O.; Jacxsens, L.; Uyttendaele, M.

2010-01-01

In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

Science.gov (United States)

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Quantitative models for sustainable supply chain management

DEFF Research Database (Denmark)

Brandenburg, M.; Govindan, Kannan; Sarkis, J.

2014-01-01

and directions of this research area, this paper provides a content analysis of 134 carefully identified papers on quantitative, formal models that address sustainability aspects in the forward SC. It was found that a preponderance of the publications and models appeared in a limited set of six journals......Sustainability, the consideration of environmental factors and social aspects, in supply chain management (SCM) has become a highly relevant topic for researchers and practitioners. The application of operations research methods and related models, i.e. formal modeling, for closed-loop SCM...... and reverse logistics has been effectively reviewed in previously published research. This situation is in contrast to the understanding and review of mathematical models that focus on environmental or social factors in forward supply chains (SC), which has seen less investigation. To evaluate developments...

Performance Theories for Sentence Coding: Some Quantitative Models

Science.gov (United States)

Aaronson, Doris; And Others

1977-01-01

This study deals with the patterns of word-by-word reading times over a sentence when the subject must code the linguistic information sufficiently for immediate verbatim recall. A class of quantitative models is considered that would account for reading times at phrase breaks. (Author/RM)

Methodologies for quantitative systems pharmacology (QSP) models : Design and Estimation

NARCIS (Netherlands)

Ribba, B.; Grimm, Hp; Agoram, B.; Davies, M.R.; Gadkar, K.; Niederer, S.; van Riel, N.; Timmis, J.; van der Graaf, Ph.

2017-01-01

With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early

Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation

NARCIS (Netherlands)

Ribba, B.; Grimm, H. P.; Agoram, B.; Davies, M. R.; Gadkar, K.; Niederer, S.; van Riel, N.; Timmis, J.; van der Graaf, P. H.

2017-01-01

With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early

On the existence of optimal contract mechanisms for incomplete information principal-agent models

NARCIS (Netherlands)

Balder, E.J.

1997-01-01

Two abstract results are given for the existence of optimal contract selection mechanisms in principal-agent models; by a suitable reformulation of the (almost) incentive compatibility constraint, they deal with both single- and multi-agent models. In particular, it is shown that the existence

Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose

DEFF Research Database (Denmark)

Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K.

2017-01-01

physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study......The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10− 5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different...... attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio...

Quantitative metal magnetic memory reliability modeling for welded joints

Science.gov (United States)

Xing, Haiyan; Dang, Yongbin; Wang, Ben; Leng, Jiancheng

2016-03-01

Metal magnetic memory(MMM) testing has been widely used to detect welded joints. However, load levels, environmental magnetic field, and measurement noises make the MMM data dispersive and bring difficulty to quantitative evaluation. In order to promote the development of quantitative MMM reliability assessment, a new MMM model is presented for welded joints. Steel Q235 welded specimens are tested along the longitudinal and horizontal lines by TSC-2M-8 instrument in the tensile fatigue experiments. The X-ray testing is carried out synchronously to verify the MMM results. It is found that MMM testing can detect the hidden crack earlier than X-ray testing. Moreover, the MMM gradient vector sum K vs is sensitive to the damage degree, especially at early and hidden damage stages. Considering the dispersion of MMM data, the K vs statistical law is investigated, which shows that K vs obeys Gaussian distribution. So K vs is the suitable MMM parameter to establish reliability model of welded joints. At last, the original quantitative MMM reliability model is first presented based on the improved stress strength interference theory. It is shown that the reliability degree R gradually decreases with the decreasing of the residual life ratio T, and the maximal error between prediction reliability degree R 1 and verification reliability degree R 2 is 9.15%. This presented method provides a novel tool of reliability testing and evaluating in practical engineering for welded joints.

Quantitative chemogenomics: machine-learning models of protein-ligand interaction.

Science.gov (United States)

Andersson, Claes R; Gustafsson, Mats G; Strömbergsson, Helena

2011-01-01

Chemogenomics is an emerging interdisciplinary field that lies in the interface of biology, chemistry, and informatics. Most of the currently used drugs are small molecules that interact with proteins. Understanding protein-ligand interaction is therefore central to drug discovery and design. In the subfield of chemogenomics known as proteochemometrics, protein-ligand-interaction models are induced from data matrices that consist of both protein and ligand information along with some experimentally measured variable. The two general aims of this quantitative multi-structure-property-relationship modeling (QMSPR) approach are to exploit sparse/incomplete information sources and to obtain more general models covering larger parts of the protein-ligand space, than traditional approaches that focuses mainly on specific targets or ligands. The data matrices, usually obtained from multiple sparse/incomplete sources, typically contain series of proteins and ligands together with quantitative information about their interactions. A useful model should ideally be easy to interpret and generalize well to new unseen protein-ligand combinations. Resolving this requires sophisticated machine-learning methods for model induction, combined with adequate validation. This review is intended to provide a guide to methods and data sources suitable for this kind of protein-ligand-interaction modeling. An overview of the modeling process is presented including data collection, protein and ligand descriptor computation, data preprocessing, machine-learning-model induction and validation. Concerns and issues specific for each step in this kind of data-driven modeling will be discussed. © 2011 Bentham Science Publishers

On the usability of quantitative modelling in operations strategy decission making

NARCIS (Netherlands)

Akkermans, H.A.; Bertrand, J.W.M.

1997-01-01

Quantitative modelling seems admirably suited to help managers in their strategic decision making on operations management issues, but in practice models are rarely used for this purpose. Investigates the reasons why, based on a detailed cross-case analysis of six cases of modelling-supported

Impact of implementation choices on quantitative predictions of cell-based computational models

Science.gov (United States)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

Coalescence model of two collinear cracks existing in steam generator tubes

International Nuclear Information System (INIS)

Moon, S.-I.; Chang, Y.-S.; Kim, Y.-J.; Park, Y.-W.; Song, M.-H.; Choi, Y.-H.; Lee, J.-H.

2005-01-01

The 40% of wall thickness criterion has been used as a plugging rule of steam generator tubes but it can be applicable just to a single-cracked tubes. In the previous studies preformed by the authors, a total of 10 local failure prediction models were introduced to estimate the coalescence load of two adjacent collinear through-wall cracks existing in thin plates, and the reaction force model and plastic zone contact model were selected as optimum models among them. The objective of this study is to verify the applicability of the proposed optimum local failure prediction models to the tubes with two collinear through-wall cracks. For this, a series of plastic collapse tests and finite element analyses were carried out using the tubes containing two collinear through-wall cracks. It has been shown that the proposed optimum failure models can predict the local failure behavior of two collinear through-wall cracks existing in tubes well. And a coalescence evaluation diagram was developed which can be used to determine whether the adjacent cracks detected by NED coalsece or not. (authors)

Quantitative analysis of a wind energy conversion model

International Nuclear Information System (INIS)

Zucker, Florian; Gräbner, Anna; Strunz, Andreas; Meyn, Jan-Peter

2015-01-01

A rotor of 12 cm diameter is attached to a precision electric motor, used as a generator, to make a model wind turbine. Output power of the generator is measured in a wind tunnel with up to 15 m s −1 air velocity. The maximum power is 3.4 W, the power conversion factor from kinetic to electric energy is c p = 0.15. The v 3 power law is confirmed. The model illustrates several technically important features of industrial wind turbines quantitatively. (paper)

Quantitative Systems Pharmacology: A Case for Disease Models.

Science.gov (United States)

Musante, C J; Ramanujan, S; Schmidt, B J; Ghobrial, O G; Lu, J; Heatherington, A C

2017-01-01

Quantitative systems pharmacology (QSP) has emerged as an innovative approach in model-informed drug discovery and development, supporting program decisions from exploratory research through late-stage clinical trials. In this commentary, we discuss the unique value of disease-scale "platform" QSP models that are amenable to reuse and repurposing to support diverse clinical decisions in ways distinct from other pharmacometrics strategies. © 2016 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of The American Society for Clinical Pharmacology and Therapeutics.

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

Science.gov (United States)

Anderson, Ryan; Clegg, Samuel M.; Frydenvang, Jens; Wiens, Roger C.; McLennan, Scott M.; Morris, Richard V.; Ehlmann, Bethany L.; Dyar, M. Darby

2017-01-01

Accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response of an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “sub-model” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. The sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

Science.gov (United States)

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Improving the monitoring of quantitative conditions of peacetime fuel stocks at pumping stations

Directory of Open Access Journals (Sweden)

Slaviša M. Ilić

2011-04-01

Full Text Available The paper has solved the problem of optimizing the existing inefficient and irrational system of the quantitative monitoring of the situation in peacetime fuel supplies at the pumping stations in the Army of Serbia. A study of existing organizational forms, military pumping stations as well as civilian ones, was carried out. Based on the completion of the survey by competent persons in the military, the methods of expert evaluation and the obtained quantitative indicator of the tested models, a multicriteria optimization was performed in order to select the optimal model. The optimization of the existing models, in terms of efficiency and economy, would be the rationalization and modernization - automation of military capacity and greater reliance on automated civilian pumping stations. Introduction Within the framework of the undergoing reform of the Serbian Army and in order to reduce the total costs, it is necessary to optimize the existing supply system that is technologically outdated, inefficient and uneconomic. The problem of research in this paper is reduced to the selection of an optimal model of the quantitative monitoring of the state of peacetime stocks of fuel at the pumping stations in the Serbian Army, in order to ensure economical operation and efficient monitoring of available and issued quantities, aiming at better decision making and management in the supply system as well as at achieving faster system response, with greater reliance on government logistics. Organization of work and monitoring the fuel quantitative status at pumping stations The existing system of monitoring the quantitative state of fuel pumping stations in the Army of Serbia has the following disadvantages: getting unreliable data, due to outdated equipment for fuel handling and measuring equipment, and manual collection of data; creation of unauthorized shortages (due to subjective human error or deception; inadequate engagement of respective material and

Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

International Nuclear Information System (INIS)

Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

2006-01-01

Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

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

Science.gov (United States)

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

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

A Quantitative Human Spacecraft Design Evaluation Model for Assessing Crew Accommodation and Utilization

Science.gov (United States)

Fanchiang, Christine

Crew performance, including both accommodation and utilization factors, is an integral part of every human spaceflight mission from commercial space tourism, to the demanding journey to Mars and beyond. Spacecraft were historically built by engineers and technologists trying to adapt the vehicle into cutting edge rocketry with the assumption that the astronauts could be trained and will adapt to the design. By and large, that is still the current state of the art. It is recognized, however, that poor human-machine design integration can lead to catastrophic and deadly mishaps. The premise of this work relies on the idea that if an accurate predictive model exists to forecast crew performance issues as a result of spacecraft design and operations, it can help designers and managers make better decisions throughout the design process, and ensure that the crewmembers are well-integrated with the system from the very start. The result should be a high-quality, user-friendly spacecraft that optimizes the utilization of the crew while keeping them alive, healthy, and happy during the course of the mission. Therefore, the goal of this work was to develop an integrative framework to quantitatively evaluate a spacecraft design from the crew performance perspective. The approach presented here is done at a very fundamental level starting with identifying and defining basic terminology, and then builds up important axioms of human spaceflight that lay the foundation for how such a framework can be developed. With the framework established, a methodology for characterizing the outcome using a mathematical model was developed by pulling from existing metrics and data collected on human performance in space. Representative test scenarios were run to show what information could be garnered and how it could be applied as a useful, understandable metric for future spacecraft design. While the model is the primary tangible product from this research, the more interesting outcome of

Rupture of the atherosclerotic plaque: does a good animal model exist?

NARCIS (Netherlands)

Cullen, Paul; Baetta, Roberta; Bellosta, Stefano; Bernini, Franco; Chinetti, Giulia; Cignarella, Andrea; von Eckardstein, Arnold; Exley, Andrew; Goddard, Martin; Hofker, Marten; Hurt-Camejo, Eva; Kanters, Edwin; Kovanen, Petri; Lorkowski, Stefan; McPheat, William; Pentikäinen, Markku; Rauterberg, Jürgen; Ritchie, Andrew; Staels, Bart; Weitkamp, Benedikt; de Winther, Menno

2003-01-01

By its very nature, rupture of the atherosclerotic plaque is difficult to study directly in humans. A good animal model would help us not only to understand how rupture occurs but also to design and test treatments to prevent it from happening. However, several difficulties surround existing models

Teaching Note--"By Any Means Necessary!" Infusing Socioeconomic Justice Content into Quantitative Research Course Work

Science.gov (United States)

Slayter, Elspeth M.

2017-01-01

Existing research suggests a majority of faculty include social justice content in research courses but not through the use of existing quantitative data for in-class activities that foster mastery of data analysis and interpretation and curiosity about social justice-related topics. By modeling data-driven dialogue and the deconstruction of…

77 FR 41985 - Use of Influenza Disease Models To Quantitatively Evaluate the Benefits and Risks of Vaccines: A...

Science.gov (United States)

2012-07-17

... models to generate quantitative estimates of the benefits and risks of influenza vaccination. The public...] Use of Influenza Disease Models To Quantitatively Evaluate the Benefits and Risks of Vaccines: A... Influenza Disease Models to Quantitatively Evaluate the Benefits and Risks of Vaccines: A Technical Workshop...

Expert judgement models in quantitative risk assessment

Energy Technology Data Exchange (ETDEWEB)

Rosqvist, T. [VTT Automation, Helsinki (Finland); Tuominen, R. [VTT Automation, Tampere (Finland)

1999-12-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed.

Expert judgement models in quantitative risk assessment

International Nuclear Information System (INIS)

Rosqvist, T.; Tuominen, R.

1999-01-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed

Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models

Science.gov (United States)

van der Wijk, Lars; Proost, Johannes H.; Sinha, Bhanu; Touw, Daan J.

2017-01-01

Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid

Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models.

Directory of Open Access Journals (Sweden)

Anna Gomes

Full Text Available Gentamicin shows large variations in half-life and volume of distribution (Vd within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1 creating an optimal model for endocarditis patients; and 2 assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE and Median Absolute Prediction Error (MDAPE were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358 renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076 L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68% as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37% and standard (MDPE -0.90%, MDAPE 4.82% models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to

Quantitative model of New Zealand's energy supply industry

Energy Technology Data Exchange (ETDEWEB)

Smith, B. R. [Victoria Univ., Wellington, (New Zealand); Lucas, P. D. [Ministry of Energy Resources (New Zealand)

1977-10-15

A mathematical model is presented to assist in an analysis of energy policy options available. The model is based on an engineering orientated description of New Zealand's energy supply and distribution system. The system is cast as a linear program, in which energy demand is satisfied at least cost. The capacities and operating modes of process plant (such as power stations, oil refinery units, and LP-gas extraction plants) are determined by the model, as well as the optimal mix of fuels supplied to the final consumers. Policy analysis with the model enables a wide ranging assessment of the alternatives and uncertainties within a consistent quantitative framework. It is intended that the model be used as a tool to investigate the relative effects of various policy options, rather than to present a definitive plan for satisfying the nation's energy requirements.

A general mixture model for mapping quantitative trait loci by using molecular markers

NARCIS (Netherlands)

Jansen, R.C.

1992-01-01

In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers.

Comparison of conventional, model-based quantitative planar, and quantitative SPECT image processing methods for organ activity estimation using In-111 agents

International Nuclear Information System (INIS)

He, Bin; Frey, Eric C

2006-01-01

Accurate quantification of organ radionuclide uptake is important for patient-specific dosimetry. The quantitative accuracy from conventional conjugate view methods is limited by overlap of projections from different organs and background activity, and attenuation and scatter. In this work, we propose and validate a quantitative planar (QPlanar) processing method based on maximum likelihood (ML) estimation of organ activities using 3D organ VOIs and a projector that models the image degrading effects. Both a physical phantom experiment and Monte Carlo simulation (MCS) studies were used to evaluate the new method. In these studies, the accuracies and precisions of organ activity estimates for the QPlanar method were compared with those from conventional planar (CPlanar) processing methods with various corrections for scatter, attenuation and organ overlap, and a quantitative SPECT (QSPECT) processing method. Experimental planar and SPECT projections and registered CT data from an RSD Torso phantom were obtained using a GE Millenium VH/Hawkeye system. The MCS data were obtained from the 3D NCAT phantom with organ activity distributions that modelled the uptake of 111 In ibritumomab tiuxetan. The simulations were performed using parameters appropriate for the same system used in the RSD torso phantom experiment. The organ activity estimates obtained from the CPlanar, QPlanar and QSPECT methods from both experiments were compared. From the results of the MCS experiment, even with ideal organ overlap correction and background subtraction, CPlanar methods provided limited quantitative accuracy. The QPlanar method with accurate modelling of the physical factors increased the quantitative accuracy at the cost of requiring estimates of the organ VOIs in 3D. The accuracy of QPlanar approached that of QSPECT, but required much less acquisition and computation time. Similar results were obtained from the physical phantom experiment. We conclude that the QPlanar method, based

Real Patient and its Virtual Twin: Application of Quantitative Systems Toxicology Modelling in the Cardiac Safety Assessment of Citalopram.

Science.gov (United States)

Patel, Nikunjkumar; Wiśniowska, Barbara; Jamei, Masoud; Polak, Sebastian

2017-11-27

A quantitative systems toxicology (QST) model for citalopram was established to simulate, in silico, a 'virtual twin' of a real patient to predict the occurrence of cardiotoxic events previously reported in patients under various clinical conditions. The QST model considers the effects of citalopram and its most notable electrophysiologically active primary (desmethylcitalopram) and secondary (didesmethylcitalopram) metabolites, on cardiac electrophysiology. The in vitro cardiac ion channel current inhibition data was coupled with the biophysically detailed model of human cardiac electrophysiology to investigate the impact of (i) the inhibition of multiple ion currents (I Kr , I Ks , I CaL ); (ii) the inclusion of metabolites in the QST model; and (iii) unbound or total plasma as the operating drug concentration, in predicting clinically observed QT prolongation. The inclusion of multiple ion channel current inhibition and metabolites in the simulation with unbound plasma citalopram concentration provided the lowest prediction error. The predictive performance of the model was verified with three additional therapeutic and supra-therapeutic drug exposure clinical cases. The results indicate that considering only the hERG ion channel inhibition of only the parent drug is potentially misleading, and the inclusion of active metabolite data and the influence of other ion channel currents should be considered to improve the prediction of potential cardiac toxicity. Mechanistic modelling can help bridge the gaps existing in the quantitative translation from preclinical cardiac safety assessment to clinical toxicology. Moreover, this study shows that the QST models, in combination with appropriate drug and systems parameters, can pave the way towards personalised safety assessment.

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

International Nuclear Information System (INIS)

Bindschadler, Michael; Alessio, Adam M; Modgil, Dimple; La Riviere, Patrick J; Branch, Kelley R

2014-01-01

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g) −1 , cardiac output = 3, 5, 8 L min −1 ). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This

Recent trends in social systems quantitative theories and quantitative models

CERN Document Server

Hošková-Mayerová, Šárka; Soitu, Daniela-Tatiana; Kacprzyk, Janusz

2017-01-01

The papers collected in this volume focus on new perspectives on individuals, society, and science, specifically in the field of socio-economic systems. The book is the result of a scientific collaboration among experts from “Alexandru Ioan Cuza” University of Iaşi (Romania), “G. d’Annunzio” University of Chieti-Pescara (Italy), "University of Defence" of Brno (Czech Republic), and "Pablo de Olavide" University of Sevilla (Spain). The heterogeneity of the contributions presented in this volume reflects the variety and complexity of social phenomena. The book is divided in four Sections as follows. The first Section deals with recent trends in social decisions. Specifically, it aims to understand which are the driving forces of social decisions. The second Section focuses on the social and public sphere. Indeed, it is oriented on recent developments in social systems and control. Trends in quantitative theories and models are described in Section 3, where many new formal, mathematical-statistical to...

Identifying best existing practice for characterization modeling in life cycle impact assessment

DEFF Research Database (Denmark)

Hauschild, Michael Zwicky; Goedkoop, Mark; Guinée, Jeroen

2013-01-01

Purpose: Life cycle impact assessment (LCIA) is a field of active development. The last decade has seen prolific publication of new impact assessment methods covering many different impact categories and providing characterization factors that often deviate from each other for the same substance...... and impact. The LCA standard ISO 14044 is rather general and unspecific in its requirements and offers little help to the LCA practitioner who needs to make a choice. With the aim to identify the best among existing characterization models and provide recommendations to the LCA practitioner, a study...... was performed for the Joint Research Centre of the European Commission (JRC). Methods Existing LCIA methods were collected and their individual characterization models identified at both midpoint and endpoint levels and supplemented with other environmental models of potential use for LCIA. No new developments...

Existence and uniqueness of solution for a model problem of transonic flow

International Nuclear Information System (INIS)

Tangmanee, S.

1985-11-01

A model problem of transonic flow ''the Tricomi equation'' bounded by the rectangular-curve boundary is studied. We transform the model problem into a symmetric positive system and an admissible boundary condition is posed. We show that with some conditions the existence and uniqueness of the solution are guaranteed. (author)

A quantitative risk-based model for reasoning over critical system properties

Science.gov (United States)

Feather, M. S.

2002-01-01

This position paper suggests the use of a quantitative risk-based model to help support reeasoning and decision making that spans many of the critical properties such as security, safety, survivability, fault tolerance, and real-time.

Tip-Enhanced Raman Voltammetry: Coverage Dependence and Quantitative Modeling.

Science.gov (United States)

Mattei, Michael; Kang, Gyeongwon; Goubert, Guillaume; Chulhai, Dhabih V; Schatz, George C; Jensen, Lasse; Van Duyne, Richard P

2017-01-11

Electrochemical atomic force microscopy tip-enhanced Raman spectroscopy (EC-AFM-TERS) was employed for the first time to observe nanoscale spatial variations in the formal potential, E 0' , of a surface-bound redox couple. TERS cyclic voltammograms (TERS CVs) of single Nile Blue (NB) molecules were acquired at different locations spaced 5-10 nm apart on an indium tin oxide (ITO) electrode. Analysis of TERS CVs at different coverages was used to verify the observation of single-molecule electrochemistry. The resulting TERS CVs were fit to the Laviron model for surface-bound electroactive species to quantitatively extract the formal potential E 0' at each spatial location. Histograms of single-molecule E 0' at each coverage indicate that the electrochemical behavior of the cationic oxidized species is less sensitive to local environment than the neutral reduced species. This information is not accessible using purely electrochemical methods or ensemble spectroelectrochemical measurements. We anticipate that quantitative modeling and measurement of site-specific electrochemistry with EC-AFM-TERS will have a profound impact on our understanding of the role of nanoscale electrode heterogeneity in applications such as electrocatalysis, biological electron transfer, and energy production and storage.

Genomic value prediction for quantitative traits under the epistatic model

Directory of Open Access Journals (Sweden)

Xu Shizhong

2011-01-01

Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

[A quantitative risk assessment model of salmonella on carcass in poultry slaughterhouse].

Science.gov (United States)

Zhang, Yu; Chen, Yuzhen; Hu, Chunguang; Zhang, Huaning; Bi, Zhenwang; Bi, Zhenqiang

2015-05-01

To construct a quantitative risk assessment model of salmonella on carcass in poultry slaughterhouse and to find out effective interventions to reduce salmonella contamination. We constructed a modular process risk model (MPRM) from evisceration to chilling in Excel Sheet using the data of the process parameters in poultry and the Salmomella concentration surveillance of Jinan in 2012. The MPRM was simulated by @ risk software. The concentration of salmonella on carcass after chilling was 1.96MPN/g which was calculated by model. The sensitive analysis indicated that the correlation coefficient of the concentration of salmonella after defeathering and in chilling pool were 0.84 and 0.34,which were the primary factors to the concentration of salmonella on carcass after chilling. The study provided a quantitative assessment model structure for salmonella on carcass in poultry slaughterhouse. The risk manager could control the contamination of salmonella on carcass after chilling by reducing the concentration of salmonella after defeathering and in chilling pool.

Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions

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Frédéric Barraquand

2014-03-01

Full Text Available Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was “too low” in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice.

A Propagative Model of Simultaneous Impact: Existence, Uniqueness, and Design Consequences

OpenAIRE

Seghete, Vlad; Murphey, Todd

2017-01-01

This paper presents existence and uniqueness results for a propagative model of simultaneous impacts that is guaranteed to conserve energy and momentum in the case of elastic impacts with extensions to perfectly plastic and inelastic impacts. A corresponding time-stepping algorithm that guarantees conservation of continuous energy and discrete momentum is developed, also with extensions to plastic and inelastic impacts. The model is illustrated in simulation using billiard balls and a two-dim...

Existence of global attractor for the Trojan Y Chromosome model

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Xiaopeng Zhao

2012-04-01

Full Text Available This paper is concerned with the long time behavior of solution for the equation derived by the Trojan Y Chromosome (TYC model with spatial spread. Based on the regularity estimates for the semigroups and the classical existence theorem of global attractors, we prove that this equations possesses a global attractor in $H^k(\\Omega^4$ $(k\\geq 0$ space.

A semi-quantitative model for risk appreciation and risk weighing

DEFF Research Database (Denmark)

Bos, Peter M.J.; Boon, Polly E.; van der Voet, Hilko

2009-01-01

Risk managers need detailed information on (1) the type of effect, (2) the size (severity) of the expected effect(s) and (3) the fraction of the population at risk to decide on well-balanced risk reduction measures. A previously developed integrated probabilistic risk assessment (IPRA) model...... provides quantitative information on these three parameters. A semi-quantitative tool is presented that combines information on these parameters into easy-readable charts that will facilitate risk evaluations of exposure situations and decisions on risk reduction measures. This tool is based on a concept...... detailed information on the estimated health impact in a given exposure situation. These graphs will facilitate the discussions on appropriate risk reduction measures to be taken....

Existence of Torsional Solitons in a Beam Model of Suspension Bridge

Science.gov (United States)

Benci, Vieri; Fortunato, Donato; Gazzola, Filippo

2017-11-01

This paper studies the existence of solitons, namely stable solitary waves, in an idealized suspension bridge. The bridge is modeled as an unbounded degenerate plate, that is, a central beam with cross sections, and displays two degrees of freedom: the vertical displacement of the beam and the torsional angles of the cross sections. Under fairly general assumptions, we prove the existence of solitons. Under the additional assumption of large tension in the sustaining cables, we prove that these solitons have a nontrivial torsional component. This appears relevant for security since several suspension bridges collapsed due to torsional oscillations.

A quantitative model to assess Social Responsibility in Environmental Science and Technology.

Science.gov (United States)

Valcárcel, M; Lucena, R

2014-01-01

The awareness of the impact of human activities in society and environment is known as "Social Responsibility" (SR). It has been a topic of growing interest in many enterprises since the fifties of the past Century, and its implementation/assessment is nowadays supported by international standards. There is a tendency to amplify its scope of application to other areas of the human activities, such as Research, Development and Innovation (R + D + I). In this paper, a model of quantitative assessment of Social Responsibility in Environmental Science and Technology (SR EST) is described in detail. This model is based on well established written standards as the EFQM Excellence model and the ISO 26000:2010 Guidance on SR. The definition of five hierarchies of indicators, the transformation of qualitative information into quantitative data and the dual procedure of self-evaluation and external evaluation are the milestones of the proposed model, which can be applied to Environmental Research Centres and institutions. In addition, a simplified model that facilitates its implementation is presented in the article. © 2013 Elsevier B.V. All rights reserved.

Quantitative graph theory mathematical foundations and applications

CERN Document Server

Dehmer, Matthias

2014-01-01

The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, this book covers a wide range of quantitative-graph theoretical concepts and methods, including those pertaining to real and random graphs such as:Comparative approaches (graph similarity or distance)Graph measures to characterize graphs quantitat

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Quantitative prediction of drug side effects based on drug-related features.

Science.gov (United States)

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

Quantitative aspects and dynamic modelling of glucosinolate metabolism

DEFF Research Database (Denmark)

Vik, Daniel

. This enables comparison of transcript and protein levels across mutants and upon induction. I find that unchallenged plants show good correspondence between protein and transcript, but that treatment with methyljasmonate results in significant differences (chapter 1). Functional genomics are used to study......). The construction a dynamic quantitative model of GLS hydrolysis is described. Simulations reveal potential effects on auxin signalling that could reflect defensive strategies (chapter 4). The results presented grant insights into, not only the dynamics of GLS biosynthesis and hydrolysis, but also the relationship...

Modeling the Static Force of a Festo Pneumatic Muscle Actuator: A New Approach and a Comparison to Existing Models

Directory of Open Access Journals (Sweden)

Mirco Martens

2017-11-01

Full Text Available In this paper, a new approach for modeling the static force characteristic of Festo pneumatic muscle actuators (PMAs will be presented. The model is physically motivated and therefore gives a deeper understanding of the Festo PMA. After introducing the new model, it will be validated through a comparison to a measured force map of a Festo DMSP-10-250 and a DMSP-20-300, respectively. It will be shown that the error between the new model and the measured data is below 4.4% for the DMSP-10-250 and below 2.35% for the DMSP-20-300. In addition, the quality of the presented model will be compared to the quality of existing models by comparing the maximum error. It can be seen that the newly introduced model is closer to the measured force characteristic of a Festo PMA than any existing model.

Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation.

Science.gov (United States)

Ribba, B; Grimm, H P; Agoram, B; Davies, M R; Gadkar, K; Niederer, S; van Riel, N; Timmis, J; van der Graaf, P H

2017-08-01

With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early Development to focus discussions on two critical methodological aspects of QSP model development: optimal structural granularity and parameter estimation. We here report in a perspective article a summary of presentations and discussions. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Comparison of semi-quantitative and quantitative dynamic contrast-enhanced MRI evaluations of vertebral marrow perfusion in a rat osteoporosis model.

Science.gov (United States)

Zhu, Jingqi; Xiong, Zuogang; Zhang, Jiulong; Qiu, Yuyou; Hua, Ting; Tang, Guangyu

2017-11-14

This study aims to investigate the technical feasibility of semi-quantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the assessment of longitudinal changes of marrow perfusion in a rat osteoporosis model, using bone mineral density (BMD) measured by micro-computed tomography (micro-CT) and histopathology as the gold standards. Fifty rats were randomly assigned to the control group (n=25) and ovariectomy (OVX) group whose bilateral ovaries were excised (n=25). Semi-quantitative and quantitative DCE-MRI, micro-CT, and histopathological examinations were performed on lumbar vertebrae at baseline and 3, 6, 9, and 12 weeks after operation. The differences between the two groups in terms of semi-quantitative DCE-MRI parameter (maximum enhancement, E max ), quantitative DCE-MRI parameters (volume transfer constant, K trans ; interstitial volume, V e ; and efflux rate constant, K ep ), micro-CT parameter (BMD), and histopathological parameter (microvessel density, MVD) were compared at each of the time points using an independent-sample t test. The differences in these parameters between baseline and other time points in each group were assessed via Bonferroni's multiple comparison test. A Pearson correlation analysis was applied to assess the relationships between DCE-MRI, micro-CT, and histopathological parameters. In the OVX group, the E max values decreased significantly compared with those of the control group at weeks 6 and 9 (p=0.003 and 0.004, respectively). The K trans values decreased significantly compared with those of the control group from week 3 (pquantitative DCE-MRI, the quantitative DCE-MRI parameter K trans is a more sensitive and accurate index for detecting early reduced perfusion in osteoporotic bone.

Current Challenges in the First Principle Quantitative Modelling of the Lower Hybrid Current Drive in Tokamaks

Science.gov (United States)

Peysson, Y.; Bonoli, P. T.; Chen, J.; Garofalo, A.; Hillairet, J.; Li, M.; Qian, J.; Shiraiwa, S.; Decker, J.; Ding, B. J.; Ekedahl, A.; Goniche, M.; Zhai, X.

2017-10-01

The Lower Hybrid (LH) wave is widely used in existing tokamaks for tailoring current density profile or extending pulse duration to steady-state regimes. Its high efficiency makes it particularly attractive for a fusion reactor, leading to consider it for this purpose in ITER tokamak. Nevertheless, if basics of the LH wave in tokamak plasma are well known, quantitative modeling of experimental observations based on first principles remains a highly challenging exercise, despite considerable numerical efforts achieved so far. In this context, a rigorous methodology must be carried out in the simulations to identify the minimum number of physical mechanisms that must be considered to reproduce experimental shot to shot observations and also scalings (density, power spectrum). Based on recent simulations carried out for EAST, Alcator C-Mod and Tore Supra tokamaks, the state of the art in LH modeling is reviewed. The capability of fast electron bremsstrahlung, internal inductance li and LH driven current at zero loop voltage to constrain all together LH simulations is discussed, as well as the needs of further improvements (diagnostics, codes, LH model), for robust interpretative and predictive simulations.

Quantitative modelling of HDPE spurt experiments using wall slip and generalised Newtonian flow

NARCIS (Netherlands)

Doelder, den C.F.J.; Koopmans, R.J.; Molenaar, J.

1998-01-01

A quantitative model to describe capillary rheometer experiments is presented. The model can generate ‘two-branched' discontinuous flow curves and the associated pressure oscillations. Polymer compressibility in the barrel, incompressible axisymmetric generalised Newtonian flow in the die, and a

A quantitative and dynamic model of the Arabidopsis flowering time gene regulatory network.

Directory of Open Access Journals (Sweden)

Felipe Leal Valentim

Full Text Available Various environmental signals integrate into a network of floral regulatory genes leading to the final decision on when to flower. Although a wealth of qualitative knowledge is available on how flowering time genes regulate each other, only a few studies incorporated this knowledge into predictive models. Such models are invaluable as they enable to investigate how various types of inputs are combined to give a quantitative readout. To investigate the effect of gene expression disturbances on flowering time, we developed a dynamic model for the regulation of flowering time in Arabidopsis thaliana. Model parameters were estimated based on expression time-courses for relevant genes, and a consistent set of flowering times for plants of various genetic backgrounds. Validation was performed by predicting changes in expression level in mutant backgrounds and comparing these predictions with independent expression data, and by comparison of predicted and experimental flowering times for several double mutants. Remarkably, the model predicts that a disturbance in a particular gene has not necessarily the largest impact on directly connected genes. For example, the model predicts that SUPPRESSOR OF OVEREXPRESSION OF CONSTANS (SOC1 mutation has a larger impact on APETALA1 (AP1, which is not directly regulated by SOC1, compared to its effect on LEAFY (LFY which is under direct control of SOC1. This was confirmed by expression data. Another model prediction involves the importance of cooperativity in the regulation of APETALA1 (AP1 by LFY, a prediction supported by experimental evidence. Concluding, our model for flowering time gene regulation enables to address how different quantitative inputs are combined into one quantitative output, flowering time.

Existence theory for a Poisson-Nernst-Planck model of electrophoresis

OpenAIRE

Bedin, Luciano; Thompson, Mark

2011-01-01

A system modeling the electrophoretic motion of a charged rigid macromolecule immersed in a incompressible ionized fluid is considered. The ionic concentration is governing by the Nernst-Planck equation coupled with the Poisson equation for the electrostatic potential, Navier-Stokes and Newtonian equations for the fluid and the macromolecule dynamics, respectively. A local in time existence result for suitable weak solutions is established, following the approach of Desjardins and Esteban [Co...

Wires in the soup: quantitative models of cell signaling

Science.gov (United States)

Cheong, Raymond; Levchenko, Andre

2014-01-01

Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks enabling this can be quite complex, necessitating for their unraveling by sophisticated computational modeling coupled with precise experimentation. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. This review highlights the case of the NF-κB pathway in order to illustrate how a quantitative model of a signaling pathway can be gradually constructed through continuous experimental validation, and what lessons one might learn from such exercises. PMID:18291655

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

Science.gov (United States)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization

A quantitative analysis of instabilities in the linear chiral sigma model

International Nuclear Information System (INIS)

Nemes, M.C.; Nielsen, M.; Oliveira, M.M. de; Providencia, J. da

1990-08-01

We present a method to construct a complete set of stationary states corresponding to small amplitude motion which naturally includes the continuum solution. The energy wheighted sum rule (EWSR) is shown to provide for a quantitative criterium on the importance of instabilities which is known to occur in nonasymptotically free theories. Out results for the linear σ model showed be valid for a large class of models. A unified description of baryon and meson properties in terms of the linear σ model is also given. (author)

Evaluating quantitative and qualitative models: An application for nationwide water erosion assessment in Ethiopia

NARCIS (Netherlands)

Sonneveld, B.G.J.S.; Keyzer, M.A.; Stroosnijder, L

2011-01-01

This paper tests the candidacy of one qualitative response model and two quantitative models for a nationwide water erosion hazard assessment in Ethiopia. After a descriptive comparison of model characteristics the study conducts a statistical comparison to evaluate the explanatory power of the

Evaluating quantitative and qualitative models: an application for nationwide water erosion assessment in Ethiopia

NARCIS (Netherlands)

Sonneveld, B.G.J.S.; Keyzer, M.A.; Stroosnijder, L.

2011-01-01

This paper tests the candidacy of one qualitative response model and two quantitative models for a nationwide water erosion hazard assessment in Ethiopia. After a descriptive comparison of model characteristics the study conducts a statistical comparison to evaluate the explanatory power of the

Canards Existence in FitzHugh-Nagumo and Hodgkin-Huxley Neuronal Models

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Jean-Marc Ginoux

2015-01-01

Full Text Available In a previous paper we have proposed a new method for proving the existence of “canard solutions” for three- and four-dimensional singularly perturbed systems with only one fast variable which improves the methods used until now. The aim of this work is to extend this method to the case of four-dimensional singularly perturbed systems with two slow and two fast variables. This method enables stating a unique generic condition for the existence of “canard solutions” for such four-dimensional singularly perturbed systems which is based on the stability of folded singularities (pseudo singular points in this case of the normalized slow dynamics deduced from a well-known property of linear algebra. This unique generic condition is identical to that provided in previous works. Application of this method to the famous coupled FitzHugh-Nagumo equations and to the Hodgkin-Huxley model enables showing the existence of “canard solutions” in such systems.

The quantitative modelling of human spatial habitability

Science.gov (United States)

Wise, J. A.

1985-01-01

A model for the quantitative assessment of human spatial habitability is presented in the space station context. The visual aspect assesses how interior spaces appear to the inhabitants. This aspect concerns criteria such as sensed spaciousness and the affective (emotional) connotations of settings' appearances. The kinesthetic aspect evaluates the available space in terms of its suitability to accommodate human movement patterns, as well as the postural and anthrometric changes due to microgravity. Finally, social logic concerns how the volume and geometry of available space either affirms or contravenes established social and organizational expectations for spatial arrangements. Here, the criteria include privacy, status, social power, and proxemics (the uses of space as a medium of social communication).

PERCEPTION AND BEHAVIOR ANALYSIS OF COMMUNITY TO THE EXISTENCE OF POIGAR PFMU MODEL

Directory of Open Access Journals (Sweden)

Arif Irawan

2017-04-01

Full Text Available Implementation of community empowerment scheme in the Poigar Production Forest Management Unit (PFMU Model area needs to take into account on community perception and behavior. This study aimed to determine the level of perception and behavior of the community towards the existence Poigar PFMU Model and to recommend the appropriate community empowerment scheme. To find out the perceptios and behavior of the Lolan Village community towards Poigar PFMU Model was by using Likert Scale. Furthermore, to determine the factors that influence people's behavior, then Spearman rank (Rs correlation test was used. The results showed that the level of perception of Lolan village communities to the existence of the Poigar PFMU Model was in good category, while the society behavior was in the less category. A good public perception of the Poigar PFMU Model area, did not have significant influence on its behavior. Community social characteristics that correlate with the behavior of the community were among others: education, level of income sourced from outside the area and level of interaction with the forest. Based on this, community empowerment strategy that is most likely to do in Poigar PFMU Model is through the Forestry Partnership Scheme.

Global existence and uniqueness result for the diffusive Peterlin viscoelastic model

Czech Academy of Sciences Publication Activity Database

Medviďová-Lukáčová, M.; Mizerová, H.; Nečasová, Šárka

2015-01-01

Roč. 120, June (2015), s. 154-170 ISSN 0362-546X R&D Projects: GA ČR GA13-00522S Institutional support: RVO:67985840 Keywords : Peterlin viscoelastic model * existence * uniqueness Subject RIV: BA - General Mathematics Impact factor: 1.125, year: 2015 http://www.sciencedirect.com/science/article/pii/S0362546X1500070X

Quantitative EPR A Practitioners Guide

CERN Document Server

Eaton, Gareth R; Barr, David P; Weber, Ralph T

2010-01-01

This is the first comprehensive yet practical guide for people who perform quantitative EPR measurements. No existing book provides this level of practical guidance to ensure the successful use of EPR. There is a growing need in both industrial and academic research to provide meaningful and accurate quantitative EPR results. This text discusses the various sample, instrument and software related aspects required for EPR quantitation. Specific topics include: choosing a reference standard, resonator considerations (Q, B1, Bm), power saturation characteristics, sample positioning, and finally, putting all the factors together to obtain an accurate spin concentration of a sample.

Modeling logistic performance in quantitative microbial risk assessment.

Science.gov (United States)

Rijgersberg, Hajo; Tromp, Seth; Jacxsens, Liesbeth; Uyttendaele, Mieke

2010-01-01

In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.

Quantitative and Functional Requirements for Bioluminescent Cancer Models.

Science.gov (United States)

Feys, Lynn; Descamps, Benedicte; Vanhove, Christian; Vermeulen, Stefan; Vandesompele, J O; Vanderheyden, Katrien; Messens, Kathy; Bracke, Marc; De Wever, Olivier

2016-01-01

Bioluminescent cancer models are widely used but detailed quantification of the luciferase signal and functional comparison with a non-transfected control cell line are generally lacking. In the present study, we provide quantitative and functional tests for luciferase-transfected cells. We quantified the luciferase expression in BLM and HCT8/E11 transfected cancer cells, and examined the effect of long-term luciferin exposure. The present study also investigated functional differences between parental and transfected cancer cells. Our results showed that quantification of different single-cell-derived populations are superior with droplet digital polymerase chain reaction. Quantification of luciferase protein level and luciferase bioluminescent activity is only useful when there is a significant difference in copy number. Continuous exposure of cell cultures to luciferin leads to inhibitory effects on mitochondrial activity, cell growth and bioluminescence. These inhibitory effects correlate with luciferase copy number. Cell culture and mouse xenograft assays showed no significant functional differences between luciferase-transfected and parental cells. Luciferase-transfected cells should be validated by quantitative and functional assays before starting large-scale experiments. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Integration of CFD codes and advanced combustion models for quantitative burnout determination

Energy Technology Data Exchange (ETDEWEB)

Javier Pallares; Inmaculada Arauzo; Alan Williams [University of Zaragoza, Zaragoza (Spain). Centre of Research for Energy Resources and Consumption (CIRCE)

2007-10-15

CFD codes and advanced kinetics combustion models are extensively used to predict coal burnout in large utility boilers. Modelling approaches based on CFD codes can accurately solve the fluid dynamics equations involved in the problem but this is usually achieved by including simple combustion models. On the other hand, advanced kinetics combustion models can give a detailed description of the coal combustion behaviour by using a simplified description of the flow field, this usually being obtained from a zone-method approach. Both approximations describe correctly general trends on coal burnout, but fail to predict quantitative values. In this paper a new methodology which takes advantage of both approximations is described. In the first instance CFD solutions were obtained of the combustion conditions in the furnace in the Lamarmora power plant (ASM Brescia, Italy) for a number of different conditions and for three coals. Then, these furnace conditions were used as inputs for a more detailed chemical combustion model to predict coal burnout. In this, devolatilization was modelled using a commercial macromolecular network pyrolysis model (FG-DVC). For char oxidation an intrinsic reactivity approach including thermal annealing, ash inhibition and maceral effects, was used. Results from the simulations were compared against plant experimental values, showing a reasonable agreement in trends and quantitative values. 28 refs., 4 figs., 4 tabs.

Stepwise kinetic equilibrium models of quantitative polymerase chain reaction

Directory of Open Access Journals (Sweden)

Cobbs Gary

2012-08-01

Full Text Available Abstract Background Numerous models for use in interpreting quantitative PCR (qPCR data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Results Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the

Stepwise kinetic equilibrium models of quantitative polymerase chain reaction.

Science.gov (United States)

Cobbs, Gary

2012-08-16

Numerous models for use in interpreting quantitative PCR (qPCR) data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the literature. They also give better estimates of

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

Science.gov (United States)

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (pEEG patterns such as generalized periodic discharges (pEEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative modeling of the ionospheric response to geomagnetic activity

Directory of Open Access Journals (Sweden)

T. J. Fuller-Rowell

Full Text Available A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard

Quantitative modeling of the ionospheric response to geomagnetic activity

Directory of Open Access Journals (Sweden)

T. J. Fuller-Rowell

2000-07-01

Full Text Available A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard

Quantitative Methods in Supply Chain Management Models and Algorithms

CERN Document Server

Christou, Ioannis T

2012-01-01

Quantitative Methods in Supply Chain Management presents some of the most important methods and tools available for modeling and solving problems arising in the context of supply chain management. In the context of this book, “solving problems” usually means designing efficient algorithms for obtaining high-quality solutions. The first chapter is an extensive optimization review covering continuous unconstrained and constrained linear and nonlinear optimization algorithms, as well as dynamic programming and discrete optimization exact methods and heuristics. The second chapter presents time-series forecasting methods together with prediction market techniques for demand forecasting of new products and services. The third chapter details models and algorithms for planning and scheduling with an emphasis on production planning and personnel scheduling. The fourth chapter presents deterministic and stochastic models for inventory control with a detailed analysis on periodic review systems and algorithmic dev...

Measuring and Managing Value Co-Creation Process: Overview of Existing Theoretical Models

Directory of Open Access Journals (Sweden)

Monika Skaržauskaitė

2013-08-01

Full Text Available Purpose — the article is to provide a holistic view on concept of value co-creation and existing models for measuring and managing it by conducting theoretical analysis of scientific literature sources targeting the integration of various approaches. Most important and relevant results of the literature study are presented with a focus on changed roles of organizations and consumers. This article aims at contributing theoretically to the research stream of measuring co-creation of value in order to gain knowledge for improvement of organizational performance and enabling new and innovative means of value creation. Design/methodology/approach. The nature of this research is exploratory – theoretical analysis and synthesis of scientific literature sources targeting the integration of various approaches was performed. This approach was chosen due to the absence of established theory on models of co-creation, possible uses in organizations and systematic overview of tools measuring/suggesting how to measure co-creation. Findings. While the principles of managing and measuring co-creation in regards of consumer motivation and involvement are widely researched, little attempt has been made to identify critical factors and create models dealing with organizational capabilities and managerial implications of value co-creation. Systematic analysis of literature revealed a gap not only in empirical research concerning organization’s role in co-creation process, but in theoretical and conceptual levels, too. Research limitations/implications. The limitations of this work as a literature review lies in its nature – the complete reliance on previously published research papers and the availability of these studies. For a deeper understanding of co-creation management and for developing models that can be used in real-life organizations, a broader theoretical, as well as empirical, research is necessary. Practical implications. Analysis of the

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Statistical analysis of probabilistic models of software product lines with quantitative constraints

DEFF Research Database (Denmark)

Beek, M.H. ter; Legay, A.; Lluch Lafuente, Alberto

2015-01-01

We investigate the suitability of statistical model checking for the analysis of probabilistic models of software product lines with complex quantitative constraints and advanced feature installation options. Such models are specified in the feature-oriented language QFLan, a rich process algebra...... of certain behaviour to the expected average cost of products. This is supported by a Maude implementation of QFLan, integrated with the SMT solver Z3 and the distributed statistical model checker MultiVeStA. Our approach is illustrated with a bikes product line case study....

Human eyeball model reconstruction and quantitative analysis.

Science.gov (United States)

Xing, Qi; Wei, Qi

2014-01-01

Determining shape of the eyeball is important to diagnose eyeball disease like myopia. In this paper, we present an automatic approach to precisely reconstruct three dimensional geometric shape of eyeball from MR Images. The model development pipeline involved image segmentation, registration, B-Spline surface fitting and subdivision surface fitting, neither of which required manual interaction. From the high resolution resultant models, geometric characteristics of the eyeball can be accurately quantified and analyzed. In addition to the eight metrics commonly used by existing studies, we proposed two novel metrics, Gaussian Curvature Analysis and Sphere Distance Deviation, to quantify the cornea shape and the whole eyeball surface respectively. The experiment results showed that the reconstructed eyeball models accurately represent the complex morphology of the eye. The ten metrics parameterize the eyeball among different subjects, which can potentially be used for eye disease diagnosis.

The Quantitative Preparation of Future Geoscience Graduate Students

Science.gov (United States)

Manduca, C. A.; Hancock, G. S.

2006-12-01

Modern geoscience is a highly quantitative science. In February, a small group of faculty and graduate students from across the country met to discuss the quantitative preparation of geoscience majors for graduate school. The group included ten faculty supervising graduate students in quantitative areas spanning the earth, atmosphere, and ocean sciences; five current graduate students in these areas; and five faculty teaching undergraduate students in the spectrum of institutions preparing students for graduate work. Discussion focused in four key ares: Are incoming graduate students adequately prepared for the quantitative aspects of graduate geoscience programs? What are the essential quantitative skills are that are required for success in graduate school? What are perceived as the important courses to prepare students for the quantitative aspects of graduate school? What programs/resources would be valuable in helping faculty/departments improve the quantitative preparation of students? The participants concluded that strengthening the quantitative preparation of undergraduate geoscience majors would increase their opportunities in graduate school. While specifics differed amongst disciplines, a special importance was placed on developing the ability to use quantitative skills to solve geoscience problems. This requires the ability to pose problems so they can be addressed quantitatively, understand the relationship between quantitative concepts and physical representations, visualize mathematics, test the reasonableness of quantitative results, creatively move forward from existing models/techniques/approaches, and move between quantitative and verbal descriptions. A list of important quantitative competencies desirable in incoming graduate students includes mechanical skills in basic mathematics, functions, multi-variate analysis, statistics and calculus, as well as skills in logical analysis and the ability to learn independently in quantitative ways

Quantitative modelling and analysis of a Chinese smart grid: a stochastic model checking case study

DEFF Research Database (Denmark)

Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming

2014-01-01

Cyber-physical systems integrate information and communication technology with the physical elements of a system, mainly for monitoring and controlling purposes. The conversion of traditional power grid into a smart grid, a fundamental example of a cyber-physical system, raises a number of issues...... that require novel methods and applications. One of the important issues in this context is the verification of certain quantitative properties of the system. In this paper, we consider a specific Chinese smart grid implementation as a case study and address the verification problem for performance and energy...... consumption.We employ stochastic model checking approach and present our modelling and analysis study using PRISM model checker....

Bibliography - Existing Guidance for External Hazard Modelling

International Nuclear Information System (INIS)

Decker, Kurt

2015-01-01

The bibliography of deliverable D21.1 includes existing international and national guidance documents and standards on external hazard assessment together with a selection of recent scientific papers, which are regarded to provide useful information on the state of the art of external event modelling. The literature database is subdivided into International Standards, National Standards, and Science Papers. The deliverable is treated as a 'living document' which is regularly updated as necessary during the lifetime of ASAMPSA-E. The current content of the database is about 140 papers. Most of the articles are available as full-text versions in PDF format. The deliverable is available as an EndNote X4 database and as text files. The database includes the following information: Reference, Key words, Abstract (if available), PDF file of the original paper (if available), Notes (comments by the ASAMPSA-E consortium if available) The database is stored at the ASAMPSA-E FTP server hosted by IRSN. PDF files of original papers are accessible through the EndNote software

A Result on the Existence and Uniqueness of Stationary Solutions for a Bioconvective Flow Model

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Aníbal Coronel

2018-01-01

Full Text Available In this note, we prove the existence and uniqueness of weak solutions for the boundary value problem modelling the stationary case of the bioconvective flow problem. The bioconvective model is a boundary value problem for a system of four equations: the nonlinear Stokes equation, the incompressibility equation, and two transport equations. The unknowns of the model are the velocity of the fluid, the pressure of the fluid, the local concentration of microorganisms, and the oxygen concentration. We derive some appropriate a priori estimates for the weak solution, which implies the existence, by application of Gossez theorem, and the uniqueness by standard methodology of comparison of two arbitrary solutions.

Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

Science.gov (United States)

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, an...

Conversion of IVA Human Computer Model to EVA Use and Evaluation and Comparison of the Result to Existing EVA Models

Science.gov (United States)

Hamilton, George S.; Williams, Jermaine C.

1998-01-01

This paper describes the methods, rationale, and comparative results of the conversion of an intravehicular (IVA) 3D human computer model (HCM) to extravehicular (EVA) use and compares the converted model to an existing model on another computer platform. The task of accurately modeling a spacesuited human figure in software is daunting: the suit restricts the human's joint range of motion (ROM) and does not have joints collocated with human joints. The modeling of the variety of materials needed to construct a space suit (e. g. metal bearings, rigid fiberglass torso, flexible cloth limbs and rubber coated gloves) attached to a human figure is currently out of reach of desktop computer hardware and software. Therefore a simplified approach was taken. The HCM's body parts were enlarged and the joint ROM was restricted to match the existing spacesuit model. This basic approach could be used to model other restrictive environments in industry such as chemical or fire protective clothing. In summary, the approach provides a moderate fidelity, usable tool which will run on current notebook computers.

Clinical prediction in defined populations: a simulation study investigating when and how to aggregate existing models

Directory of Open Access Journals (Sweden)

Glen P. Martin

2017-01-01

Full Text Available Abstract Background Clinical prediction models (CPMs are increasingly deployed to support healthcare decisions but they are derived inconsistently, in part due to limited data. An emerging alternative is to aggregate existing CPMs developed for similar settings and outcomes. This simulation study aimed to investigate the impact of between-population-heterogeneity and sample size on aggregating existing CPMs in a defined population, compared with developing a model de novo. Methods Simulations were designed to mimic a scenario in which multiple CPMs for a binary outcome had been derived in distinct, heterogeneous populations, with potentially different predictors available in each. We then generated a new ‘local’ population and compared the performance of CPMs developed for this population by aggregation, using stacked regression, principal component analysis or partial least squares, with redevelopment from scratch using backwards selection and penalised regression. Results While redevelopment approaches resulted in models that were miscalibrated for local datasets of less than 500 observations, model aggregation methods were well calibrated across all simulation scenarios. When the size of local data was less than 1000 observations and between-population-heterogeneity was small, aggregating existing CPMs gave better discrimination and had the lowest mean square error in the predicted risks compared with deriving a new model. Conversely, given greater than 1000 observations and significant between-population-heterogeneity, then redevelopment outperformed the aggregation approaches. In all other scenarios, both aggregation and de novo derivation resulted in similar predictive performance. Conclusion This study demonstrates a pragmatic approach to contextualising CPMs to defined populations. When aiming to develop models in defined populations, modellers should consider existing CPMs, with aggregation approaches being a suitable modelling

Existence, uniqueness, monotonicity and asymptotic behaviour of travelling waves for epidemic models

International Nuclear Information System (INIS)

Hsu, Cheng-Hsiung; Yang, Tzi-Sheng

2013-01-01

The purpose of this work is to investigate the existence, uniqueness, monotonicity and asymptotic behaviour of travelling wave solutions for a general epidemic model arising from the spread of an epidemic by oral–faecal transmission. First, we apply Schauder's fixed point theorem combining with a supersolution and subsolution pair to derive the existence of positive monotone monostable travelling wave solutions. Then, applying the Ikehara's theorem, we determine the exponential rates of travelling wave solutions which converge to two different equilibria as the moving coordinate tends to positive infinity and negative infinity, respectively. Finally, using the sliding method, we prove the uniqueness result provided the travelling wave solutions satisfy some boundedness conditions. (paper)

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

Science.gov (United States)

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

A suite of models to support the quantitative assessment of spread in pest risk analysis

NARCIS (Netherlands)

Robinet, C.; Kehlenbeck, H.; Werf, van der W.

2012-01-01

In the frame of the EU project PRATIQUE (KBBE-2007-212459 Enhancements of pest risk analysis techniques) a suite of models was developed to support the quantitative assessment of spread in pest risk analysis. This dataset contains the model codes (R language) for the four models in the suite. Three

Quantitative stress measurement of elastic deformation using mechanoluminescent sensor: An intensity ratio model

Science.gov (United States)

Cai, Tao; Guo, Songtao; Li, Yongzeng; Peng, Di; Zhao, Xiaofeng; Liu, Yingzheng

2018-04-01

The mechanoluminescent (ML) sensor is a newly developed non-invasive technique for stress/strain measurement. However, its application has been mostly restricted to qualitative measurement due to the lack of a well-defined relationship between ML intensity and stress. To achieve accurate stress measurement, an intensity ratio model was proposed in this study to establish a quantitative relationship between the stress condition and its ML intensity in elastic deformation. To verify the proposed model, experiments were carried out on a ML measurement system using resin samples mixed with the sensor material SrAl2O4:Eu2+, Dy3+. The ML intensity ratio was found to be dependent on the applied stress and strain rate, and the relationship acquired from the experimental results agreed well with the proposed model. The current study provided a physical explanation for the relationship between ML intensity and its stress condition. The proposed model was applicable in various SrAl2O4:Eu2+, Dy3+-based ML measurement in elastic deformation, and could provide a useful reference for quantitative stress measurement using the ML sensor in general.

Quantitative Modeling of Acid Wormholing in Carbonates- What Are the Gaps to Bridge

KAUST Repository

Qiu, Xiangdong; Zhao, Weishu; Chang, Frank; Dyer, Steve

2013-01-01

Conventional wormhole propagation models largely ignore the impact of reaction products. When implemented in a job design, the significant errors can result in treatment fluid schedule, rate, and volume. A more accurate method to simulate carbonate matrix acid treatments would accomodate the effect of reaction products on reaction kinetics. It is the purpose of this work to properly account for these effects. This is an important step in achieving quantitative predictability of wormhole penetration during an acidzing treatment. This paper describes the laboratory procedures taken to obtain the reaction-product impacted kinetics at downhole conditions using a rotating disk apparatus, and how this new set of kinetics data was implemented in a 3D wormholing model to predict wormhole morphology and penetration velocity. The model explains some of the differences in wormhole morphology observed in limestone core flow experiments where injection pressure impacts the mass transfer of hydrogen ions to the rock surface. The model uses a CT scan rendered porosity field to capture the finer details of the rock fabric and then simulates the fluid flow through the rock coupled with reactions. Such a validated model can serve as a base to scale up to near wellbore reservoir and 3D radial flow geometry allowing a more quantitative acid treatment design.

Resources on Quantitative/Statistical Research for Applied Linguists

Science.gov (United States)

Brown, James Dean

2004-01-01

The purpose of this review article is to survey and evaluate existing books on quantitative/statistical research in applied linguistics. The article begins by explaining the types of texts that will not be reviewed, then it briefly describes nine books that address how to do quantitative/statistical applied linguistics research. The review then…

Common data model for natural language processing based on two existing standard information models: CDA+GrAF.

Science.gov (United States)

Meystre, Stéphane M; Lee, Sanghoon; Jung, Chai Young; Chevrier, Raphaël D

2012-08-01

An increasing need for collaboration and resources sharing in the Natural Language Processing (NLP) research and development community motivates efforts to create and share a common data model and a common terminology for all information annotated and extracted from clinical text. We have combined two existing standards: the HL7 Clinical Document Architecture (CDA), and the ISO Graph Annotation Format (GrAF; in development), to develop such a data model entitled "CDA+GrAF". We experimented with several methods to combine these existing standards, and eventually selected a method wrapping separate CDA and GrAF parts in a common standoff annotation (i.e., separate from the annotated text) XML document. Two use cases, clinical document sections, and the 2010 i2b2/VA NLP Challenge (i.e., problems, tests, and treatments, with their assertions and relations), were used to create examples of such standoff annotation documents, and were successfully validated with the XML schemata provided with both standards. We developed a tool to automatically translate annotation documents from the 2010 i2b2/VA NLP Challenge format to GrAF, and automatically generated 50 annotation documents using this tool, all successfully validated. Finally, we adapted the XSL stylesheet provided with HL7 CDA to allow viewing annotation XML documents in a web browser, and plan to adapt existing tools for translating annotation documents between CDA+GrAF and the UIMA and GATE frameworks. This common data model may ease directly comparing NLP tools and applications, combining their output, transforming and "translating" annotations between different NLP applications, and eventually "plug-and-play" of different modules in NLP applications. Copyright © 2011 Elsevier Inc. All rights reserved.

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

Science.gov (United States)

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

Science.gov (United States)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Mapping quantitative trait loci in a selectively genotyped outbred population using a mixture model approach

NARCIS (Netherlands)

Johnson, David L.; Jansen, Ritsert C.; Arendonk, Johan A.M. van

1999-01-01

A mixture model approach is employed for the mapping of quantitative trait loci (QTL) for the situation where individuals, in an outbred population, are selectively genotyped. Maximum likelihood estimation of model parameters is obtained from an Expectation-Maximization (EM) algorithm facilitated by

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

Science.gov (United States)

Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

Experiment selection for the discrimination of semi-quantitative models of dynamical systems

NARCIS (Netherlands)

Vatcheva, [No Value; de Jong, H; Bernard, O; Mars, NJI

Modeling an experimental system often results in a number of alternative models that are all justified by the available experimental data. To discriminate among these models, additional experiments are needed. Existing methods for the selection of discriminatory experiments in statistics and in

Variable selection in near infrared spectroscopy for quantitative models of homologous analogs of cephalosporins

Directory of Open Access Journals (Sweden)

Yan-Chun Feng

2014-07-01

Full Text Available Two universal spectral ranges (4550–4100 cm-1 and 6190–5510 cm-1 for construction of quantitative models of homologous analogs of cephalosporins were proposed by evaluating the performance of five spectral ranges and their combinations, using three data sets of cephalosporins for injection, i.e., cefuroxime sodium, ceftriaxone sodium and cefoperazone sodium. Subsequently, the proposed ranges were validated by using eight calibration sets of other homologous analogs of cephalosporins for injection, namely cefmenoxime hydrochloride, ceftezole sodium, cefmetazole, cefoxitin sodium, cefotaxime sodium, cefradine, cephazolin sodium and ceftizoxime sodium. All the constructed quantitative models for the eight kinds of cephalosporins using these universal ranges could fulfill the requirements for quick quantification. After that, competitive adaptive reweighted sampling (CARS algorithm and infrared (IR–near infrared (NIR two-dimensional (2D correlation spectral analysis were used to determine the scientific basis of these two spectral ranges as the universal regions for the construction of quantitative models of cephalosporins. The CARS algorithm demonstrated that the ranges of 4550–4100 cm-1 and 6190–5510 cm-1 included some key wavenumbers which could be attributed to content changes of cephalosporins. The IR–NIR 2D spectral analysis showed that certain wavenumbers in these two regions have strong correlations to the structures of those cephalosporins that were easy to degrade.

Refining the statistical model for quantitative immunostaining of surface-functionalized nanoparticles by AFM.

Science.gov (United States)

MacCuspie, Robert I; Gorka, Danielle E

2013-10-01

Recently, an atomic force microscopy (AFM)-based approach for quantifying the number of biological molecules conjugated to a nanoparticle surface at low number densities was reported. The number of target molecules conjugated to the analyte nanoparticle can be determined with single nanoparticle fidelity using antibody-mediated self-assembly to decorate the analyte nanoparticles with probe nanoparticles (i.e., quantitative immunostaining). This work refines the statistical models used to quantitatively interpret the observations when AFM is used to image the resulting structures. The refinements add terms to the previous statistical models to account for the physical sizes of the analyte nanoparticles, conjugated molecules, antibodies, and probe nanoparticles. Thus, a more physically realistic statistical computation can be implemented for a given sample of known qualitative composition, using the software scripts provided. Example AFM data sets, using horseradish peroxidase conjugated to gold nanoparticles, are presented to illustrate how to implement this method successfully.

Quantitative determination of Auramine O by terahertz spectroscopy with 2DCOS-PLSR model

Science.gov (United States)

Zhang, Huo; Li, Zhi; Chen, Tao; Qin, Binyi

2017-09-01

Residues of harmful dyes such as Auramine O (AO) in herb and food products threaten the health of people. So, fast and sensitive detection techniques of the residues are needed. As a powerful tool for substance detection, terahertz (THz) spectroscopy was used for the quantitative determination of AO by combining with an improved partial least-squares regression (PLSR) model in this paper. Absorbance of herbal samples with different concentrations was obtained by THz-TDS in the band between 0.2THz and 1.6THz. We applied two-dimensional correlation spectroscopy (2DCOS) to improve the PLSR model. This method highlighted the spectral differences of different concentrations, provided a clear criterion of the input interval selection, and improved the accuracy of detection result. The experimental result indicated that the combination of the THz spectroscopy and 2DCOS-PLSR is an excellent quantitative analysis method.

Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization

Directory of Open Access Journals (Sweden)

Qian Wang

2016-01-01

Full Text Available Spectroscopy is an efficient and widely used quantitative analysis method. In this paper, a spectral quantitative analysis model with combining wavelength selection and topology structure optimization is proposed. For the proposed method, backpropagation neural network is adopted for building the component prediction model, and the simultaneousness optimization of the wavelength selection and the topology structure of neural network is realized by nonlinear adaptive evolutionary programming (NAEP. The hybrid chromosome in binary scheme of NAEP has three parts. The first part represents the topology structure of neural network, the second part represents the selection of wavelengths in the spectral data, and the third part represents the parameters of mutation of NAEP. Two real flue gas datasets are used in the experiments. In order to present the effectiveness of the methods, the partial least squares with full spectrum, the partial least squares combined with genetic algorithm, the uninformative variable elimination method, the backpropagation neural network with full spectrum, the backpropagation neural network combined with genetic algorithm, and the proposed method are performed for building the component prediction model. Experimental results verify that the proposed method has the ability to predict more accurately and robustly as a practical spectral analysis tool.

Quantitative Finance

Science.gov (United States)

James, Jessica

2017-01-01

Quantitative finance is a field that has risen to prominence over the last few decades. It encompasses the complex models and calculations that value financial contracts, particularly those which reference events in the future, and apply probabilities to these events. While adding greatly to the flexibility of the market available to corporations and investors, it has also been blamed for worsening the impact of financial crises. But what exactly does quantitative finance encompass, and where did these ideas and models originate? We show that the mathematics behind finance and behind games of chance have tracked each other closely over the centuries and that many well-known physicists and mathematicians have contributed to the field.

Qualitative and quantitative guidelines for the comparison of environmental model predictions

International Nuclear Information System (INIS)

Scott, M.

1995-03-01

The question of how to assess or compare predictions from a number of models is one of concern in the validation of models, in understanding the effects of different models and model parameterizations on model output, and ultimately in assessing model reliability. Comparison of model predictions with observed data is the basic tool of model validation while comparison of predictions amongst different models provides one measure of model credibility. The guidance provided here is intended to provide qualitative and quantitative approaches (including graphical and statistical techniques) to such comparisons for use within the BIOMOVS II project. It is hoped that others may find it useful. It contains little technical information on the actual methods but several references are provided for the interested reader. The guidelines are illustrated on data from the VAMP CB scenario. Unfortunately, these data do not permit all of the possible approaches to be demonstrated since predicted uncertainties were not provided. The questions considered are concerned with a) intercomparison of model predictions and b) comparison of model predictions with the observed data. A series of examples illustrating some of the different types of data structure and some possible analyses have been constructed. A bibliography of references on model validation is provided. It is important to note that the results of the various techniques discussed here, whether qualitative or quantitative, should not be considered in isolation. Overall model performance must also include an evaluation of model structure and formulation, i.e. conceptual model uncertainties, and results for performance measures must be interpreted in this context. Consider a number of models which are used to provide predictions of a number of quantities at a number of time points. In the case of the VAMP CB scenario, the results include predictions of total deposition of Cs-137 and time dependent concentrations in various

Thermodynamic Modeling of a Solid Oxide Fuel Cell to Couple with an Existing Gas Turbine Engine Model

Science.gov (United States)

Brinson, Thomas E.; Kopasakis, George

2004-01-01

The Controls and Dynamics Technology Branch at NASA Glenn Research Center are interested in combining a solid oxide fuel cell (SOFC) to operate in conjunction with a gas turbine engine. A detailed engine model currently exists in the Matlab/Simulink environment. The idea is to incorporate a SOFC model within the turbine engine simulation and observe the hybrid system's performance. The fuel cell will be heated to its appropriate operating condition by the engine s combustor. Once the fuel cell is operating at its steady-state temperature, the gas burner will back down slowly until the engine is fully operating on the hot gases exhausted from the SOFC. The SOFC code is based on a steady-state model developed by The U.S. Department of Energy (DOE). In its current form, the DOE SOFC model exists in Microsoft Excel and uses Visual Basics to create an I-V (current-voltage) profile. For the project's application, the main issue with this model is that the gas path flow and fuel flow temperatures are used as input parameters instead of outputs. The objective is to create a SOFC model based on the DOE model that inputs the fuel cells flow rates and outputs temperature of the flow streams; therefore, creating a temperature profile as a function of fuel flow rate. This will be done by applying the First Law of Thermodynamics for a flow system to the fuel cell. Validation of this model will be done in two procedures. First, for a given flow rate the exit stream temperature will be calculated and compared to DOE SOFC temperature as a point comparison. Next, an I-V curve and temperature curve will be generated where the I-V curve will be compared with the DOE SOFC I-V curve. Matching I-V curves will suggest validation of the temperature curve because voltage is a function of temperature. Once the temperature profile is created and validated, the model will then be placed into the turbine engine simulation for system analysis.

Establishing the existence of a distance-based upper bound for a fuzzy DEA model using duality

International Nuclear Information System (INIS)

Soleimani-damaneh, M.

2009-01-01

In a recent paper [Soleimani-damaneh M. Fuzzy upper bounds and their applications. Chaos, Solitons and Fractals 2008;36:217-25.], I established the existence of a distance-based fuzzy upper bound for the objective function of a fuzzy DEA model, using the properties of a discussed signed distance, and provided an effective approach to solve that model. In this paper a new dual-based proof for the existence of the above-mentioned upper bound is provided which gives a useful insight into the theory of fuzzy DEA.

Using Integrated Environmental Modeling to Automate a Process-Based Quantitative Microbial Risk Assessment (presentation)

Science.gov (United States)

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and...

A new quantitative model of ecological compensation based on ecosystem capital in Zhejiang Province, China*

Science.gov (United States)

Jin, Yan; Huang, Jing-feng; Peng, Dai-liang

2009-01-01

Ecological compensation is becoming one of key and multidiscipline issues in the field of resources and environmental management. Considering the change relation between gross domestic product (GDP) and ecological capital (EC) based on remote sensing estimation, we construct a new quantitative estimate model for ecological compensation, using county as study unit, and determine standard value so as to evaluate ecological compensation from 2001 to 2004 in Zhejiang Province, China. Spatial differences of the ecological compensation were significant among all the counties or districts. This model fills up the gap in the field of quantitative evaluation of regional ecological compensation and provides a feasible way to reconcile the conflicts among benefits in the economic, social, and ecological sectors. PMID:19353749

Fixing the cracks in the crystal ball: A maturity model for quantitative risk assessment

International Nuclear Information System (INIS)

Rae, Andrew; Alexander, Rob; McDermid, John

2014-01-01

Quantitative risk assessment (QRA) is widely practiced in system safety, but there is insufficient evidence that QRA in general is fit for purpose. Defenders of QRA draw a distinction between poor or misused QRA and correct, appropriately used QRA, but this distinction is only useful if we have robust ways to identify the flaws in an individual QRA. In this paper we present a comprehensive maturity model for QRA which covers all the potential flaws discussed in the risk assessment literature and in a collection of risk assessment peer reviews. We provide initial validation of the completeness and realism of the model. Our risk assessment maturity model provides a way to prioritise both process development within an organisation and empirical research within the QRA community. - Highlights: • Quantitative risk assessment (QRA) is widely practiced, but there is insufficient evidence that it is fit for purpose. • A given QRA may be good, or it may not – we need systematic ways to distinguish this. • We have created a maturity model for QRA which covers all the potential flaws discussed in the risk assessment literature. • We have provided initial validation of the completeness and realism of the model. • The maturity model can also be used to prioritise QRA research discipline-wide

Discussions on the non-equilibrium effects in the quantitative phase field model of binary alloys

International Nuclear Information System (INIS)

Zhi-Jun, Wang; Jin-Cheng, Wang; Gen-Cang, Yang

2010-01-01

All the quantitative phase field models try to get rid of the artificial factors of solutal drag, interface diffusion and interface stretch in the diffuse interface. These artificial non-equilibrium effects due to the introducing of diffuse interface are analysed based on the thermodynamic status across the diffuse interface in the quantitative phase field model of binary alloys. Results indicate that the non-equilibrium effects are related to the negative driving force in the local region of solid side across the diffuse interface. The negative driving force results from the fact that the phase field model is derived from equilibrium condition but used to simulate the non-equilibrium solidification process. The interface thickness dependence of the non-equilibrium effects and its restriction on the large scale simulation are also discussed. (cross-disciplinary physics and related areas of science and technology)

Mentoring for junior medical faculty: Existing models and suggestions for low-resource settings.

Science.gov (United States)

Menon, Vikas; Muraleedharan, Aparna; Bhat, Ballambhattu Vishnu

2016-02-01

Globally, there is increasing recognition about the positive benefits and impact of mentoring on faculty retention rates, career satisfaction and scholarly output. However, emphasis on research and practice of mentoring is comparatively meagre in low and middle income countries. In this commentary, we critically examine two existing models of mentorship for medical faculty and offer few suggestions for an integrated hybrid model that can be adapted for use in low resource settings. Copyright © 2016 Elsevier B.V. All rights reserved.

Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

Science.gov (United States)

Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven

2006-01-01

A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

Quantitative model for the blood pressure‐lowering interaction of valsartan and amlodipine

Science.gov (United States)

Heo, Young‐A; Holford, Nick; Kim, Yukyung; Son, Mijeong

2016-01-01

Aims The objective of this study was to develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model to quantitatively describe the antihypertensive effect of combined therapy with amlodipine and valsartan. Methods PK modelling was used with data collected from 48 healthy volunteers receiving a single dose of combined formulation of 10 mg amlodipine and 160 mg valsartan. Systolic (SBP) and diastolic blood pressure (DBP) were recorded during combined administration. SBP and DBP data for each drug alone were gathered from the literature. PKPD models of each drug and for combined administration were built with NONMEM 7.3. Results A two‐compartment model with zero order absorption best described the PK data of both drugs. Amlodipine and valsartan monotherapy effects on SBP and DBP were best described by an I max model with an effect compartment delay. Combined therapy was described using a proportional interaction term as follows: (D1 + D2) +ALPHA×(D1 × D2). D1 and D2 are the predicted drug effects of amlodipine and valsartan monotherapy respectively. ALPHA is the interaction term for combined therapy. Quantitative estimates of ALPHA were −0.171 (95% CI: −0.218, −0.143) for SBP and −0.0312 (95% CI: −0.07739, −0.00283) for DBP. These infra‐additive interaction terms for both SBP and DBP were consistent with literature results for combined administration of drugs in these classes. Conclusion PKPD models for SBP and DBP successfully described the time course of the antihypertensive effects of amlodipine and valsartan. An infra‐additive interaction between amlodipine and valsartan when used in combined administration was confirmed and quantified. PMID:27504853

Using Mathematical Modeling and Set-Based Design Principles to Recommend an Existing CVL Design

Science.gov (United States)

2017-09-01

MATHEMATICAL MODELING AND SET-BASED DESIGN PRINCIPLES TO RECOMMEND AN EXISTING CVL DESIGN by William H. Ehlies September 2017 Thesis Advisor...Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE...September 2017 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE USING MATHEMATICAL MODELING AND SET-BASED DESIGN PRINCIPLES

Tannin structural elucidation and quantitative ³¹P NMR analysis. 1. Model compounds.

Science.gov (United States)

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

2013-10-02

Tannins and flavonoids are secondary metabolites of plants that display a wide array of biological activities. This peculiarity is related to the inhibition of extracellular enzymes that occurs through the complexation of peptides by tannins. Not only the nature of these interactions, but more fundamentally also the structure of these heterogeneous polyphenolic molecules are not completely clear. This first paper describes the development of a new analytical method for the structural characterization of tannins on the basis of tannin model compounds employing an in situ labeling of all labile H groups (aliphatic OH, phenolic OH, and carboxylic acids) with a phosphorus reagent. The ³¹P NMR analysis of ³¹P-labeled samples allowed the unprecedented quantitative and qualitative structural characterization of hydrolyzable tannins, proanthocyanidins, and catechin tannin model compounds, forming the foundations for the quantitative structural elucidation of a variety of actual tannin samples described in part 2 of this series.

Resources on quantitative/statistical research for applied linguists

OpenAIRE

Brown , James Dean

2004-01-01

Abstract The purpose of this review article is to survey and evaluate existing books on quantitative/statistical research in applied linguistics. The article begins by explaining the types of texts that will not be reviewed, then it briefly describes nine books that address how to do quantitative/statistical applied linguistics research. The review then compares (in prose and tables) the general characteris...

Towards Quantitative Spatial Models of Seabed Sediment Composition.

Directory of Open Access Journals (Sweden)

David Stephens

Full Text Available There is a need for fit-for-purpose maps for accurately depicting the types of seabed substrate and habitat and the properties of the seabed for the benefits of research, resource management, conservation and spatial planning. The aim of this study is to determine whether it is possible to predict substrate composition across a large area of seabed using legacy grain-size data and environmental predictors. The study area includes the North Sea up to approximately 58.44°N and the United Kingdom's parts of the English Channel and the Celtic Seas. The analysis combines outputs from hydrodynamic models as well as optical remote sensing data from satellite platforms and bathymetric variables, which are mainly derived from acoustic remote sensing. We build a statistical regression model to make quantitative predictions of sediment composition (fractions of mud, sand and gravel using the random forest algorithm. The compositional data is analysed on the additive log-ratio scale. An independent test set indicates that approximately 66% and 71% of the variability of the two log-ratio variables are explained by the predictive models. A EUNIS substrate model, derived from the predicted sediment composition, achieved an overall accuracy of 83% and a kappa coefficient of 0.60. We demonstrate that it is feasible to spatially predict the seabed sediment composition across a large area of continental shelf in a repeatable and validated way. We also highlight the potential for further improvements to the method.

BEopt-CA (Ex): A Tool for Optimal Integration of EE, DR and PV in Existing California Homes

Energy Technology Data Exchange (ETDEWEB)

Christensen, C.; Horowitz, S.; Maguire, J.; Tabares-Velasco, P.; Springer, D.; Coates, P.; Bell, C.; Price, S.; Sreedharan, P.; Pickrell, K.

2014-04-01

Opportunities for combining energy efficiency, demand response, and energy storage with PV are often missed, because the required knowledge and expertise for these different technologies exist in separate organizations or individuals. Furthermore, there is a lack of quantitative tools to optimize energy efficiency, demand response and energy storage with PV, especially for existing buildings. As technology costs evolve (e.g., the ongoing reduction in the cost of PV), design strategies need to be adjusted accordingly based on quantitative analysis.

Quantitative Analysis of the Security of Software-Defined Network Controller Using Threat/Effort Model

Directory of Open Access Journals (Sweden)

Zehui Wu

2017-01-01

Full Text Available SDN-based controller, which is responsible for the configuration and management of the network, is the core of Software-Defined Networks. Current methods, which focus on the secure mechanism, use qualitative analysis to estimate the security of controllers, leading to inaccurate results frequently. In this paper, we employ a quantitative approach to overcome the above shortage. Under the analysis of the controller threat model we give the formal model results of the APIs, the protocol interfaces, and the data items of controller and further provide our Threat/Effort quantitative calculation model. With the help of Threat/Effort model, we are able to compare not only the security of different versions of the same kind controller but also different kinds of controllers and provide a basis for controller selection and secure development. We evaluated our approach in four widely used SDN-based controllers which are POX, OpenDaylight, Floodlight, and Ryu. The test, which shows the similarity outcomes with the traditional qualitative analysis, demonstrates that with our approach we are able to get the specific security values of different controllers and presents more accurate results.

A practical model for pressure probe system response estimation (with review of existing models)

Science.gov (United States)

Hall, B. F.; Povey, T.

2018-04-01

The accurate estimation of the unsteady response (bandwidth) of pneumatic pressure probe systems (probe, line and transducer volume) is a common practical problem encountered in the design of aerodynamic experiments. Understanding the bandwidth of the probe system is necessary to capture unsteady flow features accurately. Where traversing probes are used, the desired traverse speed and spatial gradients in the flow dictate the minimum probe system bandwidth required to resolve the flow. Existing approaches for bandwidth estimation are either complex or inaccurate in implementation, so probes are often designed based on experience. Where probe system bandwidth is characterized, it is often done experimentally, requiring careful experimental set-up and analysis. There is a need for a relatively simple but accurate model for estimation of probe system bandwidth. A new model is presented for the accurate estimation of pressure probe bandwidth for simple probes commonly used in wind tunnel environments; experimental validation is provided. An additional, simple graphical method for air is included for convenience.

Quantitative Hydraulic Models Of Early Land Plants Provide Insight Into Middle Paleozoic Terrestrial Paleoenvironmental Conditions

Science.gov (United States)

Wilson, J. P.; Fischer, W. W.

2010-12-01

Fossil plants provide useful proxies of Earth’s climate because plants are closely connected, through physiology and morphology, to the environments in which they lived. Recent advances in quantitative hydraulic models of plant water transport provide new insight into the history of climate by allowing fossils to speak directly to environmental conditions based on preserved internal anatomy. We report results of a quantitative hydraulic model applied to one of the earliest terrestrial plants preserved in three dimensions, the ~396 million-year-old vascular plant Asteroxylon mackei. This model combines equations describing the rate of fluid flow through plant tissues with detailed observations of plant anatomy; this allows quantitative estimates of two critical aspects of plant function. First and foremost, results from these models quantify the supply of water to evaporative surfaces; second, results describe the ability of plant vascular systems to resist tensile damage from extreme environmental events, such as drought or frost. This approach permits quantitative comparisons of functional aspects of Asteroxylon with other extinct and extant plants, informs the quality of plant-based environmental proxies, and provides concrete data that can be input into climate models. Results indicate that despite their small size, water transport cells in Asteroxylon could supply a large volume of water to the plant's leaves--even greater than cells from some later-evolved seed plants. The smallest Asteroxylon tracheids have conductivities exceeding 0.015 m^2 / MPa * s, whereas Paleozoic conifer tracheids do not reach this threshold until they are three times wider. However, this increase in conductivity came at the cost of little to no adaptations for transport safety, placing the plant’s vegetative organs in jeopardy during drought events. Analysis of the thickness-to-span ratio of Asteroxylon’s tracheids suggests that environmental conditions of reduced relative

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

Science.gov (United States)

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

Model development for quantitative evaluation of proliferation resistance of nuclear fuel cycles

Energy Technology Data Exchange (ETDEWEB)

Ko, Won Il; Kim, Ho Dong; Yang, Myung Seung

2000-07-01

This study addresses the quantitative evaluation of the proliferation resistance which is important factor of the alternative nuclear fuel cycle system. In this study, model was developed to quantitatively evaluate the proliferation resistance of the nuclear fuel cycles. The proposed models were then applied to Korean environment as a sample study to provide better references for the determination of future nuclear fuel cycle system in Korea. In order to quantify the proliferation resistance of the nuclear fuel cycle, the proliferation resistance index was defined in imitation of an electrical circuit with an electromotive force and various electrical resistance components. The analysis on the proliferation resistance of nuclear fuel cycles has shown that the resistance index as defined herein can be used as an international measure of the relative risk of the nuclear proliferation if the motivation index is appropriately defined. It has also shown that the proposed model can include political issues as well as technical ones relevant to the proliferation resistance, and consider all facilities and activities in a specific nuclear fuel cycle (from mining to disposal). In addition, sensitivity analyses on the sample study indicate that the direct disposal option in a country with high nuclear propensity may give rise to a high risk of the nuclear proliferation than the reprocessing option in a country with low nuclear propensity.

Model development for quantitative evaluation of proliferation resistance of nuclear fuel cycles

International Nuclear Information System (INIS)

Ko, Won Il; Kim, Ho Dong; Yang, Myung Seung

2000-07-01

This study addresses the quantitative evaluation of the proliferation resistance which is important factor of the alternative nuclear fuel cycle system. In this study, model was developed to quantitatively evaluate the proliferation resistance of the nuclear fuel cycles. The proposed models were then applied to Korean environment as a sample study to provide better references for the determination of future nuclear fuel cycle system in Korea. In order to quantify the proliferation resistance of the nuclear fuel cycle, the proliferation resistance index was defined in imitation of an electrical circuit with an electromotive force and various electrical resistance components. The analysis on the proliferation resistance of nuclear fuel cycles has shown that the resistance index as defined herein can be used as an international measure of the relative risk of the nuclear proliferation if the motivation index is appropriately defined. It has also shown that the proposed model can include political issues as well as technical ones relevant to the proliferation resistance, and consider all facilities and activities in a specific nuclear fuel cycle (from mining to disposal). In addition, sensitivity analyses on the sample study indicate that the direct disposal option in a country with high nuclear propensity may give rise to a high risk of the nuclear proliferation than the reprocessing option in a country with low nuclear propensity

Quantitative risk stratification in Markov chains with limiting conditional distributions.

Science.gov (United States)

Chan, David C; Pollett, Philip K; Weinstein, Milton C

2009-01-01

Many clinical decisions require patient risk stratification. The authors introduce the concept of limiting conditional distributions, which describe the equilibrium proportion of surviving patients occupying each disease state in a Markov chain with death. Such distributions can quantitatively describe risk stratification. The authors first establish conditions for the existence of a positive limiting conditional distribution in a general Markov chain and describe a framework for risk stratification using the limiting conditional distribution. They then apply their framework to a clinical example of a treatment indicated for high-risk patients, first to infer the risk of patients selected for treatment in clinical trials and then to predict the outcomes of expanding treatment to other populations of risk. For the general chain, a positive limiting conditional distribution exists only if patients in the earliest state have the lowest combined risk of progression or death. The authors show that in their general framework, outcomes and population risk are interchangeable. For the clinical example, they estimate that previous clinical trials have selected the upper quintile of patient risk for this treatment, but they also show that expanded treatment would weakly dominate this degree of targeted treatment, and universal treatment may be cost-effective. Limiting conditional distributions exist in most Markov models of progressive diseases and are well suited to represent risk stratification quantitatively. This framework can characterize patient risk in clinical trials and predict outcomes for other populations of risk.

Quantifying Zika: Advancing the Epidemiology of Zika With Quantitative Models.

Science.gov (United States)

Keegan, Lindsay T; Lessler, Justin; Johansson, Michael A

2017-12-16

When Zika virus (ZIKV) emerged in the Americas, little was known about its biology, pathogenesis, and transmission potential, and the scope of the epidemic was largely hidden, owing to generally mild infections and no established surveillance systems. Surges in congenital defects and Guillain-Barré syndrome alerted the world to the danger of ZIKV. In the context of limited data, quantitative models were critical in reducing uncertainties and guiding the global ZIKV response. Here, we review some of the models used to assess the risk of ZIKV-associated severe outcomes, the potential speed and size of ZIKV epidemics, and the geographic distribution of ZIKV risk. These models provide important insights and highlight significant unresolved questions related to ZIKV and other emerging pathogens. Published by Oxford University Press for the Infectious Diseases Society of America 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Theory and Practice in Quantitative Genetics

DEFF Research Database (Denmark)

Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

2003-01-01

With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

On the Existence and Uniqueness of JML Estimates for the Partial Credit Model

Science.gov (United States)

Bertoli-Barsotti, Lucio

2005-01-01

A necessary and sufficient condition is given in this paper for the existence and uniqueness of the maximum likelihood (the so-called joint maximum likelihood) estimate of the parameters of the Partial Credit Model. This condition is stated in terms of a structural property of the pattern of the data matrix that can be easily verified on the basis…

Appreciating the difference between design-based and model-based sampling strategies in quantitative morphology of the nervous system.

Science.gov (United States)

Geuna, S

2000-11-20

Quantitative morphology of the nervous system has undergone great developments over recent years, and several new technical procedures have been devised and applied successfully to neuromorphological research. However, a lively debate has arisen on some issues, and a great deal of confusion appears to exist that is definitely responsible for the slow spread of the new techniques among scientists. One such element of confusion is related to uncertainty about the meaning, implications, and advantages of the design-based sampling strategy that characterize the new techniques. In this article, to help remove this uncertainty, morphoquantitative methods are described and contrasted on the basis of the inferential paradigm of the sampling strategy: design-based vs model-based. Moreover, some recommendations are made to help scientists judge the appropriateness of a method used for a given study in relation to its specific goals. Finally, the use of the term stereology to label, more or less expressly, only some methods is critically discussed. Copyright 2000 Wiley-Liss, Inc.

Existence and characterization of optimal control in mathematics model of diabetics population

Science.gov (United States)

Permatasari, A. H.; Tjahjana, R. H.; Udjiani, T.

2018-03-01

Diabetes is a chronic disease with a huge burden affecting individuals and the whole society. In this paper, we constructed the optimal control mathematical model by applying a strategy to control the development of diabetic population. The constructed mathematical model considers the dynamics of disabled people due to diabetes. Moreover, an optimal control approach is proposed in order to reduce the burden of pre-diabetes. Implementation of control is done by preventing the pre-diabetes develop into diabetics with and without complications. The existence of optimal control and characterization of optimal control is discussed in this paper. Optimal control is characterized by applying the Pontryagin minimum principle. The results indicate that there is an optimal control in optimization problem in mathematics model of diabetic population. The effect of the optimal control variable (prevention) is strongly affected by the number of healthy people.

Quantitative Modelling of Trace Elements in Hard Coal.

Science.gov (United States)

Smoliński, Adam; Howaniec, Natalia

2016-01-01

The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross-validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment.

A study on the quantitative model of human response time using the amount and the similarity of information

International Nuclear Information System (INIS)

Lee, Sung Jin

2006-02-01

The mental capacity to retain or recall information, or memory is related to human performance during processing of information. Although a large number of studies have been carried out on human performance, little is known about the similarity effect. The purpose of this study was to propose and validate a quantitative and predictive model on human response time in the user interface with the basic concepts of information amount, similarity and degree of practice. It was difficult to explain human performance by only similarity or information amount. There were two difficulties: constructing a quantitative model on human response time and validating the proposed model by experimental work. A quantitative model based on the Hick's law, the law of practice and similarity theory was developed. The model was validated under various experimental conditions by measuring the participants' response time in the environment of a computer-based display. Human performance was improved by degree of similarity and practice in the user interface. Also we found the age-related human performance which was degraded as he or she was more elder. The proposed model may be useful for training operators who will handle some interfaces and predicting human performance by changing system design

A Cytomorphic Chip for Quantitative Modeling of Fundamental Bio-Molecular Circuits.

Science.gov (United States)

2015-08-01

We describe a 0.35 μm BiCMOS silicon chip that quantitatively models fundamental molecular circuits via efficient log-domain cytomorphic transistor equivalents. These circuits include those for biochemical binding with automatic representation of non-modular and loading behavior, e.g., in cascade and fan-out topologies; for representing variable Hill-coefficient operation and cooperative binding; for representing inducer, transcription-factor, and DNA binding; for probabilistic gene transcription with analogic representations of log-linear and saturating operation; for gain, degradation, and dynamics of mRNA and protein variables in transcription and translation; and, for faithfully representing biological noise via tunable stochastic transistor circuits. The use of on-chip DACs and ADCs enables multiple chips to interact via incoming and outgoing molecular digital data packets and thus create scalable biochemical reaction networks. The use of off-chip digital processors and on-chip digital memory enables programmable connectivity and parameter storage. We show that published static and dynamic MATLAB models of synthetic biological circuits including repressilators, feed-forward loops, and feedback oscillators are in excellent quantitative agreement with those from transistor circuits on the chip. Computationally intensive stochastic Gillespie simulations of molecular production are also rapidly reproduced by the chip and can be reliably tuned over the range of signal-to-noise ratios observed in biological cells.

Nonparametric functional mapping of quantitative trait loci.

Science.gov (United States)

Yang, Jie; Wu, Rongling; Casella, George

2009-03-01

Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

Science.gov (United States)

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Quantitative structure activity relationship model for predicting the depletion percentage of skin allergic chemical substances of glutathione

International Nuclear Information System (INIS)

Si Hongzong; Wang Tao; Zhang Kejun; Duan Yunbo; Yuan Shuping; Fu Aiping; Hu Zhide

2007-01-01

A quantitative model was developed to predict the depletion percentage of glutathione (DPG) compounds by gene expression programming (GEP). Each kind of compound was represented by several calculated structural descriptors involving constitutional, topological, geometrical, electrostatic and quantum-chemical features of compounds. The GEP method produced a nonlinear and five-descriptor quantitative model with a mean error and a correlation coefficient of 10.52 and 0.94 for the training set, 22.80 and 0.85 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones, better than those of the heuristic method

Quantitative model for the generic 3D shape of ICMEs at 1 AU

Science.gov (United States)

Démoulin, P.; Janvier, M.; Masías-Meza, J. J.; Dasso, S.

2016-10-01

Context. Interplanetary imagers provide 2D projected views of the densest plasma parts of interplanetary coronal mass ejections (ICMEs), while in situ measurements provide magnetic field and plasma parameter measurements along the spacecraft trajectory, that is, along a 1D cut. The data therefore only give a partial view of the 3D structures of ICMEs. Aims: By studying a large number of ICMEs, crossed at different distances from their apex, we develop statistical methods to obtain a quantitative generic 3D shape of ICMEs. Methods: In a first approach we theoretically obtained the expected statistical distribution of the shock-normal orientation from assuming simple models of 3D shock shapes, including distorted profiles, and compared their compatibility with observed distributions. In a second approach we used the shock normal and the flux rope axis orientations together with the impact parameter to provide statistical information across the spacecraft trajectory. Results: The study of different 3D shock models shows that the observations are compatible with a shock that is symmetric around the Sun-apex line as well as with an asymmetry up to an aspect ratio of around 3. Moreover, flat or dipped shock surfaces near their apex can only be rare cases. Next, the sheath thickness and the ICME velocity have no global trend along the ICME front. Finally, regrouping all these new results and those of our previous articles, we provide a quantitative ICME generic 3D shape, including the global shape of the shock, the sheath, and the flux rope. Conclusions: The obtained quantitative generic ICME shape will have implications for several aims. For example, it constrains the output of typical ICME numerical simulations. It is also a base for studying the transport of high-energy solar and cosmic particles during an ICME propagation as well as for modeling and forecasting space weather conditions near Earth.

Efficient Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models.

Science.gov (United States)

Allen, R J; Rieger, T R; Musante, C J

2016-03-01

Quantitative systems pharmacology models mechanistically describe a biological system and the effect of drug treatment on system behavior. Because these models rarely are identifiable from the available data, the uncertainty in physiological parameters may be sampled to create alternative parameterizations of the model, sometimes termed "virtual patients." In order to reproduce the statistics of a clinical population, virtual patients are often weighted to form a virtual population that reflects the baseline characteristics of the clinical cohort. Here we introduce a novel technique to efficiently generate virtual patients and, from this ensemble, demonstrate how to select a virtual population that matches the observed data without the need for weighting. This approach improves confidence in model predictions by mitigating the risk that spurious virtual patients become overrepresented in virtual populations.

Multi-factor models and signal processing techniques application to quantitative finance

CERN Document Server

Darolles, Serges; Jay, Emmanuelle

2013-01-01

With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages "embedded" quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented "risk assessment-based" practices.This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an intere

The existence of a stable noncollinear phase in a Heisenberg model with complex structure

Energy Technology Data Exchange (ETDEWEB)

Shopova, Diana V.; Boyadjiev, Todor L

2003-05-19

We have analyzed the properties of a noncollinear magnetic phase obtained in the mean-field analysis of the model of two coupled Heisenberg subsystems. The domain of its existence and stability is narrow and depends on the ratio between the averaged over nearest neighbours microscopic exchange parameters.

Development of quantitative atomic modeling for tungsten transport study Using LHD plasma with tungsten pellet injection

International Nuclear Information System (INIS)

Murakami, I.; Sakaue, H.A.; Suzuki, C.; Kato, D.; Goto, M.; Tamura, N.; Sudo, S.; Morita, S.

2014-10-01

Quantitative tungsten study with reliable atomic modeling is important for successful achievement of ITER and fusion reactors. We have developed tungsten atomic modeling for understanding the tungsten behavior in fusion plasmas. The modeling is applied to the analysis of tungsten spectra observed from currentless plasmas of the Large Helical Device (LHD) with tungsten pellet injection. We found that extreme ultraviolet (EUV) lines of W 24+ to W 33+ ions are very sensitive to electron temperature (Te) and useful to examine the tungsten behavior in edge plasmas. Based on the first quantitative analysis of measured spatial profile of W 44+ ion, the tungsten concentration is determined to be n(W 44+ )/n e = 1.4x10 -4 and the total radiation loss is estimated as ∼4 MW, of which the value is roughly half the total NBI power. (author)

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

Directory of Open Access Journals (Sweden)

Mondry Adrian

2004-08-01

Full Text Available Abstract Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods

Optofluidic time-stretch quantitative phase microscopy.

Science.gov (United States)

Guo, Baoshan; Lei, Cheng; Wu, Yi; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Lee, Sangwook; Isozaki, Akihiro; Li, Ming; Jiang, Yiyue; Yasumoto, Atsushi; Di Carlo, Dino; Tanaka, Yo; Yatomi, Yutaka; Ozeki, Yasuyuki; Goda, Keisuke

2018-03-01

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective. Copyright © 2017 Elsevier Inc. All rights reserved.

Downscaling SSPs in Bangladesh - Integrating Science, Modelling and Stakeholders Through Qualitative and Quantitative Scenarios

Science.gov (United States)

Allan, A.; Barbour, E.; Salehin, M.; Hutton, C.; Lázár, A. N.; Nicholls, R. J.; Rahman, M. M.

2015-12-01

A downscaled scenario development process was adopted in the context of a project seeking to understand relationships between ecosystem services and human well-being in the Ganges-Brahmaputra delta. The aim was to link the concerns and priorities of relevant stakeholders with the integrated biophysical and poverty models used in the project. A 2-stage process was used to facilitate the connection between stakeholders concerns and available modelling capacity: the first to qualitatively describe what the future might look like in 2050; the second to translate these qualitative descriptions into the quantitative form required by the numerical models. An extended, modified SSP approach was adopted, with stakeholders downscaling issues identified through interviews as being priorities for the southwest of Bangladesh. Detailed qualitative futures were produced, before modellable elements were quantified in conjunction with an expert stakeholder cadre. Stakeholder input, using the methods adopted here, allows the top-down focus of the RCPs to be aligned with the bottom-up approach needed to make the SSPs appropriate at the more local scale, and also facilitates the translation of qualitative narrative scenarios into a quantitative form that lends itself to incorporation of biophysical and socio-economic indicators. The presentation will describe the downscaling process in detail, and conclude with findings regarding the importance of stakeholder involvement (and logistical considerations), balancing model capacity with expectations and recommendations on SSP refinement at local levels.

COMPARATIVE ANALYSIS OF SOME EXISTING KINETIC MODELS ...

African Journals Online (AJOL)

The biosorption of three heavy metal ions namely; Zn2+, Cu2+ and Mn2+ using five microorganisms namely; Bacillus circulans, Pseudomonas aeruginosa, Staphylococcus xylosus, Streptomyces rimosus and Yeast (Saccharomyces sp.) were studied. In this paper, the effectiveness of six existing and two proposed kinetic ...

A quantitative dynamic systems model of health-related quality of life among older adults

Science.gov (United States)

Roppolo, Mattia; Kunnen, E Saskia; van Geert, Paul L; Mulasso, Anna; Rabaglietti, Emanuela

2015-01-01

Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population. PMID:26604722

Global existence of solutions to a tear film model with locally elevated evaporation rates

Science.gov (United States)

Gao, Yuan; Ji, Hangjie; Liu, Jian-Guo; Witelski, Thomas P.

2017-07-01

Motivated by a model proposed by Peng et al. (2014) for break-up of tear films on human eyes, we study the dynamics of a generalized thin film model. The governing equations form a fourth-order coupled system of nonlinear parabolic PDEs for the film thickness and salt concentration subject to non-conservative effects representing evaporation. We analytically prove the global existence of solutions to this model with mobility exponents in several different ranges and present numerical simulations that are in agreement with the analytic results. We also numerically capture other interesting dynamics of the model, including finite-time rupture-shock phenomenon due to the instabilities caused by locally elevated evaporation rates, convergence to equilibrium and infinite-time thinning.

Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework

Directory of Open Access Journals (Sweden)

Robert L. Mayes

2013-01-01

Full Text Available Quantitative reasoning is a complex concept with many definitions and a diverse account in the literature. The purpose of this article is to establish a working definition of quantitative reasoning within the context of science, construct a quantitative reasoning framework, and summarize research on key components in that framework. Context underlies all quantitative reasoning; for this review, environmental science serves as the context.In the framework, we identify four components of quantitative reasoning: the quantification act, quantitative literacy, quantitative interpretation of a model, and quantitative modeling. Within each of these components, the framework provides elements that comprise the four components. The quantification act includes the elements of variable identification, communication, context, and variation. Quantitative literacy includes the elements of numeracy, measurement, proportional reasoning, and basic probability/statistics. Quantitative interpretation includes the elements of representations, science diagrams, statistics and probability, and logarithmic scales. Quantitative modeling includes the elements of logic, problem solving, modeling, and inference. A brief comparison of the quantitative reasoning framework with the AAC&U Quantitative Literacy VALUE rubric is presented, demonstrating a mapping of the components and illustrating differences in structure. The framework serves as a precursor for a quantitative reasoning learning progression which is currently under development.

Modeling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets

International Nuclear Information System (INIS)

Cerezo Davila, Carlos; Reinhart, Christoph F.; Bemis, Jamie L.

2016-01-01

City governments and energy utilities are increasingly focusing on the development of energy efficiency strategies for buildings as a key component in emission reduction plans and energy supply strategies. To support these diverse needs, a new generation of Urban Building Energy Models (UBEM) is currently being developed and validated to estimate citywide hourly energy demands at the building level. However, in order for cities to rely on UBEMs, effective model generation and maintenance workflows are needed based on existing urban data structures. Within this context, the authors collaborated with the Boston Redevelopment Authority to develop a citywide UBEM based on official GIS datasets and a custom building archetype library. Energy models for 83,541 buildings were generated and assigned one of 52 use/age archetypes, within the CAD modelling environment Rhinoceros3D. The buildings were then simulated using the US DOE EnergyPlus simulation program, and results for buildings of the same archetype were crosschecked against data from the US national energy consumption surveys. A district-level intervention combining photovoltaics with demand side management is presented to demonstrate the ability of UBEM to provide actionable information. Lack of widely available archetype templates and metered energy data, were identified as key barriers within existing workflows that may impede cities from effectively applying UBEM to guide energy policy. - Highlights: • Data requirements for Urban Building Energy Models are reviewed. • A workflow for UBEM generation from available GIS datasets is developed. • A citywide demand simulation model for Boston is generated and tested. • Limitations for UBEM in current urban data systems are identified and discussed. • Model application for energy management policy is shown in an urban PV scenario.

Novel mathematic models for quantitative transitivity of quality-markers in extraction process of the Buyanghuanwu decoction.

Science.gov (United States)

Zhang, Yu-Tian; Xiao, Mei-Feng; Deng, Kai-Wen; Yang, Yan-Tao; Zhou, Yi-Qun; Zhou, Jin; He, Fu-Yuan; Liu, Wen-Long

2018-06-01

Nowadays, to research and formulate an efficiency extraction system for Chinese herbal medicine, scientists have always been facing a great challenge for quality management, so that the transitivity of Q-markers in quantitative analysis of TCM was proposed by Prof. Liu recently. In order to improve the quality of extraction from raw medicinal materials for clinical preparations, a series of integrated mathematic models for transitivity of Q-markers in quantitative analysis of TCM were established. Buyanghuanwu decoction (BYHWD) was a commonly TCMs prescription, which was used to prevent and treat the ischemic heart and brain diseases. In this paper, we selected BYHWD as an extraction experimental subject to study the quantitative transitivity of TCM. Based on theory of Fick's Rule and Noyes-Whitney equation, novel kinetic models were established for extraction of active components. Meanwhile, fitting out kinetic equations of extracted models and then calculating the inherent parameters in material piece and Q-marker quantitative transfer coefficients, which were considered as indexes to evaluate transitivity of Q-markers in quantitative analysis of the extraction process of BYHWD. HPLC was applied to screen and analyze the potential Q-markers in the extraction process. Fick's Rule and Noyes-Whitney equation were adopted for mathematically modeling extraction process. Kinetic parameters were fitted and calculated by the Statistical Program for Social Sciences 20.0 software. The transferable efficiency was described and evaluated by potential Q-markers transfer trajectory via transitivity availability AUC, extraction ratio P, and decomposition ratio D respectively. The Q-marker was identified with AUC, P, D. Astragaloside IV, laetrile, paeoniflorin, and ferulic acid were studied as potential Q-markers from BYHWD. The relative technologic parameters were presented by mathematic models, which could adequately illustrate the inherent properties of raw materials

PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool

KAUST Repository

AlTurki, Musab

2011-01-01

Statistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability of statistical model checking, and making such scalability of analysis available to tools like Maude, where probabilistic systems can be specified at a high level as probabilistic rewrite theories. It presents PVeStA, an extension and parallelization of the VeStA statistical model checking tool [10]. PVeStA supports statistical model checking of probabilistic real-time systems specified as either: (i) discrete or continuous Markov Chains; or (ii) probabilistic rewrite theories in Maude. Furthermore, the properties that it can model check can be expressed in either: (i) PCTL/CSL, or (ii) the QuaTEx quantitative temporal logic. As our experiments show, the performance gains obtained from parallelization can be very high. © 2011 Springer-Verlag.

Quantitative Decision Support Requires Quantitative User Guidance

Science.gov (United States)

Smith, L. A.

2009-12-01

Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output

Quantitative model of super-Arrhenian behavior in glass forming materials

Science.gov (United States)

Caruthers, J. M.; Medvedev, G. A.

2018-05-01

The key feature of glass forming liquids is the super-Arrhenian temperature dependence of the mobility, where the mobility can increase by ten orders of magnitude or more as the temperature is decreased if crystallization does not intervene. A fundamental description of the super-Arrhenian behavior has been developed; specifically, the logarithm of the relaxation time is a linear function of 1 /U¯x , where U¯x is the independently determined excess molar internal energy and B is a material constant. This one-parameter mobility model quantitatively describes data for 21 glass forming materials, which are all the materials where there are sufficient experimental data for analysis. The effect of pressure on the loga mobility is also described using the same U¯x(T ,p ) function determined from the difference between the liquid and crystalline internal energies. It is also shown that B is well correlated with the heat of fusion. The prediction of the B /U¯x model is compared to the Adam and Gibbs 1 /T S¯x model, where the B /U¯x model is significantly better in unifying the full complement of mobility data. The implications of the B /U¯x model for the development of a fundamental description of glass are discussed.

Spatiotemporal microbiota dynamics from quantitative in vitro and in silico models of the gut

Science.gov (United States)

Hwa, Terence

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth behaviors, which ultimately dictate the gut microbiota composition. Combining measurements of bacterial growth physiology with analysis of published data on human physiology into a quantitative modeling framework, we show how hydrodynamic forces in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla in the gut. Our model quantitatively explains the observed variation of microbiota composition among healthy adults, and predicts colonic water absorption (manifested as stool consistency) and nutrient intake to be two key factors determining this composition. The model further reveals that both factors, which have been identified in recent correlative studies, exert their effects through the same mechanism: changes in colonic pH that differentially affect the growth of different bacteria. Our findings show that a predictive and mechanistic understanding of microbial ecology in the human gut is possible, and offer the hope for the rational design of intervention strategies to actively control the microbiota. This work is supported by the Bill and Melinda Gates Foundation.

A quantitative model of the cardiac ventricular cell incorporating the transverse-axial tubular system

Czech Academy of Sciences Publication Activity Database

Pásek, Michal; Christé, G.; Šimurda, J.

2003-01-01

Roč. 22, č. 3 (2003), s. 355-368 ISSN 0231-5882 R&D Projects: GA ČR GP204/02/D129 Institutional research plan: CEZ:AV0Z2076919 Keywords : cardiac cell * tubular system * quantitative modelling Subject RIV: BO - Biophysics Impact factor: 0.794, year: 2003

Optimizing Existing Multistory Building Designs towards Net-Zero Energy

Directory of Open Access Journals (Sweden)

Mohammad Y. AbuGrain

2017-03-01

Full Text Available Recent global developments in awareness and concerns about environmental problems have led to reconsidering built environment approaches and construction techniques. One of the alternatives is the principle of low/zero-energy buildings. This study investigates the potentials of energy savings in an existing multi-story building in the Mediterranean region in order to achieve net-zero energy as a solution to increasing fossil fuel prices. The Colored building at the Faculty of Architecture, Eastern Mediterranean University, Cyprus was chosen as a target of this study to be investigated and analyzed in order to know how energy efficiency strategies could be applied to the building to reduce annual energy consumption. Since this research objective is to develop a strategy to achieve net-zero energy in existing buildings, case study and problem solving methodologies were applied in this research in order to evaluate the building design in a qualitative manner through observations, in addition to a quantitative method through an energy modeling simulation to achieve desirable results which address the problems. After optimizing the building energy performance, an alternative energy simulation was made of the building in order to make an energy comparison analysis, which leads to reliable conclusions. These methodologies and the strategies used in this research can be applied to similar buildings in order to achieve net-zero energy goals.

Modelling the existing Irish energy-system to identify future energy costs and the maximum wind penetration feasible

International Nuclear Information System (INIS)

Connolly, D.; Leahy, M.; Lund, H.; Mathiesen, B.V.

2010-01-01

In this study a model of the Irish energy-system was developed using EnergyPLAN based on the year 2007, which was then used for three investigations. The first compares the model results with actual values from 2007 to validate its accuracy. The second illustrates the exposure of the existing Irish energy-system to future energy costs by considering future fuel prices, CO 2 prices, and different interest rates. The final investigation identifies the maximum wind penetration feasible on the 2007 Irish energy-system from a technical and economic perspective, as wind is the most promising fluctuating renewable resource available in Ireland. It is concluded that the reference model simulates the Irish energy-system accurately, the annual fuel costs for Ireland's energy could increase by approximately 58% from 2007 to 2020 if a business-as-usual scenario is followed, and the optimum wind penetration for the existing Irish energy-system is approximately 30% from both a technical and economic perspective based on 2020 energy prices. Future studies will use the model developed in this study to show that higher wind penetrations can be achieved if the existing energy-system is modified correctly. Finally, these results are not only applicable to Ireland, but also represent the issues facing many other countries. (author)

Quantitative penetration testing with item response theory

NARCIS (Netherlands)

Pieters, W.; Arnold, F.; Stoelinga, M.I.A.

2013-01-01

Existing penetration testing approaches assess the vulnerability of a system by determining whether certain attack paths are possible in practice. Therefore, penetration testing has thus far been used as a qualitative research method. To enable quantitative approaches to security risk management,

Quantitative Modeling of Membrane Transport and Anisogamy by Small Groups Within a Large-Enrollment Organismal Biology Course

Directory of Open Access Journals (Sweden)

Eric S. Haag

2016-12-01

Full Text Available Quantitative modeling is not a standard part of undergraduate biology education, yet is routine in the physical sciences. Because of the obvious biophysical aspects, classes in anatomy and physiology offer an opportunity to introduce modeling approaches to the introductory curriculum. Here, we describe two in-class exercises for small groups working within a large-enrollment introductory course in organismal biology. Both build and derive biological insights from quantitative models, implemented using spreadsheets. One exercise models the evolution of anisogamy (i.e., small sperm and large eggs from an initial state of isogamy. Groups of four students work on Excel spreadsheets (from one to four laptops per group. The other exercise uses an online simulator to generate data related to membrane transport of a solute, and a cloud-based spreadsheet to analyze them. We provide tips for implementing these exercises gleaned from two years of experience.

Quantitative Risk reduction estimation Tool For Control Systems, Suggested Approach and Research Needs

Energy Technology Data Exchange (ETDEWEB)

Miles McQueen; Wayne Boyer; Mark Flynn; Sam Alessi

2006-03-01

For the past year we have applied a variety of risk assessment technologies to evaluate the risk to critical infrastructure from cyber attacks on control systems. More recently, we identified the need for a stand alone control system risk reduction estimation tool to provide owners and operators of control systems with a more useable, reliable, and credible method for managing the risks from cyber attack. Risk is defined as the probability of a successful attack times the value of the resulting loss, typically measured in lives and dollars. Qualitative and ad hoc techniques for measuring risk do not provide sufficient support for cost benefit analyses associated with cyber security mitigation actions. To address the need for better quantitative risk reduction models we surveyed previous quantitative risk assessment research; evaluated currently available tools; developed new quantitative techniques [17] [18]; implemented a prototype analysis tool to demonstrate how such a tool might be used; used the prototype to test a variety of underlying risk calculational engines (e.g. attack tree, attack graph); and identified technical and research needs. We concluded that significant gaps still exist and difficult research problems remain for quantitatively assessing the risk to control system components and networks, but that a useable quantitative risk reduction estimation tool is not beyond reach.

Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

DEFF Research Database (Denmark)

Wang, Lei

Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method...... to quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...... the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially improves...

Quantitative structure-activity relationship modeling of the toxicity of organothiophosphate pesticides to Daphnia magna and Cyprinus carpio

NARCIS (Netherlands)

Zvinavashe, E.; Du, T.; Griff, T.; Berg, van den J.H.J.; Soffers, A.E.M.F.; Vervoort, J.J.M.; Murk, A.J.; Rietjens, I.

2009-01-01

Within the REACH regulatory framework in the EU, quantitative structure-activity relationships (QSAR) models are expected to help reduce the number of animals used for experimental testing. The objective of this study was to develop QSAR models to describe the acute toxicity of organothiophosphate

Physiological role of Kv1.3 channel in T lymphocyte cell investigated quantitatively by kinetic modeling.

Directory of Open Access Journals (Sweden)

Panpan Hou

Full Text Available Kv1.3 channel is a delayed rectifier channel abundant in human T lymphocytes. Chronic inflammatory and autoimmune disorders lead to the over-expression of Kv1.3 in T cells. To quantitatively study the regulatory mechanism and physiological function of Kv1.3 in T cells, it is necessary to have a precise kinetic model of Kv1.3. In this study, we firstly established a kinetic model capable to precisely replicate all the kinetic features for Kv1.3 channels, and then constructed a T-cell model composed of ion channels including Ca2+-release activated calcium (CRAC channel, intermediate K+ (IK channel, TASK channel and Kv1.3 channel for quantitatively simulating the changes in membrane potentials and local Ca2+ signaling messengers during activation of T cells. Based on the experimental data from current-clamp recordings, we successfully demonstrated that Kv1.3 dominated the membrane potential of T cells to manipulate the Ca2+ influx via CRAC channel. Our results revealed that the deficient expression of Kv1.3 channel would cause the less Ca2+ signal, leading to the less efficiency in secretion. This was the first successful attempt to simulate membrane potential in non-excitable cells, which laid a solid basis for quantitatively studying the regulatory mechanism and physiological role of channels in non-excitable cells.

Geomorphology: now a more quantitative science

International Nuclear Information System (INIS)

Lal, D.

1995-01-01

Geomorphology, one of the oldest branches of planetary science, is now growing into a quantitative field with the development of a nuclear method capable of providing numeric time controls on a great variety of superficial processes. The method complement the conventional dating methods, e.g. 40 K/ 40 Ar, 87 Rb/ 87 Sr, by providing information on geomorphic processes., e.g. the dwell times of rocks on the earth's surface with strict geometrical constraints; e.g., rates of physical and chemical weathering in the past, chronology of events associated with glaciation, etc. This article attempts to discuss the new possibilities that now exist for studying a wide range of geomorphic processes, with examples of some specific isotopic changes that allow one to model glacial chronology, and evolutionary histories of alluvial fans and sand dunes. (author). 9 refs., 3 figs., 4 tabs

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

Science.gov (United States)

Feenstra, Bjarke; Skovgaard, Ib M

2004-06-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

Quantitative Penetration Testing with Item Response Theory

NARCIS (Netherlands)

Arnold, Florian; Pieters, Wolter; Stoelinga, Mariëlle Ida Antoinette

2014-01-01

Existing penetration testing approaches assess the vulnerability of a system by determining whether certain attack paths are possible in practice. Thus, penetration testing has so far been used as a qualitative research method. To enable quantitative approaches to security risk management, including

Quantitative penetration testing with item response theory

NARCIS (Netherlands)

Arnold, Florian; Pieters, Wolter; Stoelinga, Mariëlle

2013-01-01

Existing penetration testing approaches assess the vulnerability of a system by determining whether certain attack paths are possible in practice. Thus, penetration testing has so far been used as a qualitative research method. To enable quantitative approaches to security risk management, including

Properties predictive modeling through the concept of a hybrid interphase existing between phases in contact

Science.gov (United States)

Portan, D. V.; Papanicolaou, G. C.

2018-02-01

From practical point of view, predictive modeling based on the physics of composite material behavior is wealth generating; by guiding material system selection and process choices, by cutting down on experimentation and associated costs; and by speeding up the time frame from the research stage to the market place. The presence of areas with different properties and the existence of an interphase between them have a pronounced influence on the behavior of a composite system. The Viscoelastic Hybrid Interphase Model (VHIM), considers the existence of a non-homogeneous viscoelastic and anisotropic interphase having properties depended on the degree of adhesion between the two phases in contact. The model applies for any physical/mechanical property (e.g. mechanical, thermal, electrical and/or biomechanical). Knowing the interphasial variation of a specific property one can predict the corresponding macroscopic behavior of the composite. Moreover, the model acts as an algorithm and a two-way approach can be used: (i) phases in contact may be chosen to get the desired properties of the final composite system or (ii) the initial phases in contact determine the final behavior of the composite system, that can be approximately predicted. The VHIM has been proven, amongst others, to be extremely useful in biomaterial designing for improved contact with human tissues.

Melanoma screening: Informing public health policy with quantitative modelling.

Directory of Open Access Journals (Sweden)

Stephen Gilmore

Full Text Available Australia and New Zealand share the highest incidence rates of melanoma worldwide. Despite the substantial increase in public and physician awareness of melanoma in Australia over the last 30 years-as a result of the introduction of publicly funded mass media campaigns that began in the early 1980s -mortality has steadily increased during this period. This increased mortality has led investigators to question the relative merits of primary versus secondary prevention; that is, sensible sun exposure practices versus early detection. Increased melanoma vigilance on the part of the public and among physicians has resulted in large increases in public health expenditure, primarily from screening costs and increased rates of office surgery. Has this attempt at secondary prevention been effective? Unfortunately epidemiologic studies addressing the causal relationship between the level of secondary prevention and mortality are prohibitively difficult to implement-it is currently unknown whether increased melanoma surveillance reduces mortality, and if so, whether such an approach is cost-effective. Here I address the issue of secondary prevention of melanoma with respect to incidence and mortality (and cost per life saved by developing a Markov model of melanoma epidemiology based on Australian incidence and mortality data. The advantages of developing a methodology that can determine constraint-based surveillance outcomes are twofold: first, it can address the issue of effectiveness; and second, it can quantify the trade-off between cost and utilisation of medical resources on one hand, and reduced morbidity and lives saved on the other. With respect to melanoma, implementing the model facilitates the quantitative determination of the relative effectiveness and trade-offs associated with different levels of secondary and tertiary prevention, both retrospectively and prospectively. For example, I show that the surveillance enhancement that began in

An overview of quantitative approaches in Gestalt perception.

Science.gov (United States)

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

2016-09-01

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

Quantitative Decision Making Model for Carbon Reduction in Road Construction Projects Using Green Technologies

Directory of Open Access Journals (Sweden)

Woosik Jang

2015-08-01

Full Text Available Numerous countries have established policies for reducing greenhouse gas emissions and have suggested goals pertaining to these reductions. To reach the target reduction amounts, studies on the reduction of carbon emissions have been conducted with regard to all stages and processes in construction projects. According to a study on carbon emissions, the carbon emissions generated during the construction stage of road projects account for approximately 76 to 86% of the total carbon emissions, far exceeding the other stages, such as maintenance or demolition. Therefore, this study aims to develop a quantitative decision making model that supports the application of green technologies (GTs to reduce carbon emissions during the construction stage of road construction projects. First, the authors selected environmental soundness, economic feasibility and constructability as the key assessment indices for evaluating 20 GTs. Second, a fuzzy set/qualitative comparative analysis (FS/QCA was used to establish an objective decision-making model for the assessment of both the quantitative and qualitative characteristics of the key indices. To support the developed model, an expert survey was performed to assess the applicability of each GT from a practical perspective, which was verified with a case study using two additional GTs. The proposed model is expected to support practitioners in the application of suitable GTs to road projects and reduce carbon emissions, resulting in better decision making during road construction projects.

Quantitative coating thickness determination using a coefficient-independent hyperspectral scattering model

NARCIS (Netherlands)

Dingemans, LM; Papadakis, V.; Liu, P.; Adam, A.J.L.; Groves, R.M.

2017-01-01

Background
Hyperspectral imaging is a technique that enables the mapping of spectral signatures across a surface. It is most commonly used for surface chemical mapping in fields as diverse as satellite remote sensing, biomedical imaging and heritage science. Existing models, such as the

Improved modelling of thermal energy savings potential in the existing residential stock using a newly available data source

International Nuclear Information System (INIS)

Dineen, D.; Rogan, F.; Ó Gallachóir, B.P.

2015-01-01

This paper presents a novel bottom up approach to modelling the energy savings potential of energy efficiency improvement measures to be applied through retrofit of the existing dwelling stock. It takes advantage of a newly available, rich dataset on the construction characteristics of the 2011 housing stock in Ireland. The methodological innovation centres on the use of wall construction type in the modelling and analysis. While Ireland is the focus, this approach is applicable to any EU member state for which data on dwelling characteristics exists from surveys carried as part of Energy Performance Certificate calculations. The model is calibrated to the national energy balance for 2011 by varying the internal temperature assumptions. Sensitivity analysis is performed on the effects of internal temperature and rebound. The paper also highlights some limitations posed by data availability on the accuracy and sophistication of models that can currently be developed, specifically in the Irish case. - Highlights: • Archetype model of energy savings potential from retrofit of existing dwelling stock. • Takes advantage of rich dataset on the construction characteristics of the Irish housing stock. • Innovative use of wall construction types in archetype definition possible due to improved data. • Results calibrated to top down estimate of heating demand by adjusting internal temperature. • Highlights limitations on the accuracy and sophistication of models posed by data availability.

Quantitative genetic models of sexual selection by male choice.

Science.gov (United States)

Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

Quantitative Determination of Organic Semiconductor Microstructure from the Molecular to Device Scale

KAUST Repository

Rivnay, Jonathan

2012-10-10

A study was conducted to demonstrate quantitative determination of organic semiconductor microstructure from the molecular to device scale. The quantitative determination of organic semiconductor microstructure from the molecular to device scale was key to obtaining precise description of the molecular structure and microstructure of the materials of interest. This information combined with electrical characterization and modeling allowed for the establishment of general design rules to guide future rational design of materials and devices. Investigations revealed that a number and variety of defects were the largest contributors to the existence of disorder within a lattice, as organic semiconductor crystals were dominated by weak van der Waals bonding. Crystallite size, texture, and variations in structure due to spatial confinement and interfaces were also found to be relevant for transport of free charge carriers and bound excitonic species over distances that were important for device operation.

Web Applications Vulnerability Management using a Quantitative Stochastic Risk Modeling Method

Directory of Open Access Journals (Sweden)

Sergiu SECHEL

2017-01-01

Full Text Available The aim of this research is to propose a quantitative risk modeling method that reduces the guess work and uncertainty from the vulnerability and risk assessment activities of web based applications while providing users the flexibility to assess risk according to their risk appetite and tolerance with a high degree of assurance. The research method is based on the research done by the OWASP Foundation on this subject but their risk rating methodology needed de-bugging and updates in different in key areas that are presented in this paper. The modified risk modeling method uses Monte Carlo simulations to model risk characteristics that can’t be determined without guess work and it was tested in vulnerability assessment activities on real production systems and in theory by assigning discrete uniform assumptions to all risk charac-teristics (risk attributes and evaluate the results after 1.5 million rounds of Monte Carlo simu-lations.

Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose.

Science.gov (United States)

Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K; Abaidoo, Robert C; Dalsgaard, Anders; Hald, Tine

2017-12-01

The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10 -5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10 -4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10 -6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose. Copyright © 2017 Elsevier B.V. All rights reserved.

A quantitative model for estimating mean annual soil loss in cultivated land using 137Cs measurements

International Nuclear Information System (INIS)

Yang Hao; Zhao Qiguo; Du Mingyuan; Minami, Katsuyuki; Hatta, Tamao

2000-01-01

The radioisotope 137 Cs has been widely used to determine rates of cultivated soil loss, Many calibration relationships (including both empirical relationships and theoretical models) have been employed to estimate erosion rates from the amount of 137 Cs lost from the cultivated soil profile. However, there are important limitations which restrict the reliability of these models, which consider only the uniform distribution of 137 Cs in the plough layer and the depth. As a result, erosion rates they may be overestimated or underestimated. This article presents a quantitative model for the relation the amount of 137 Cs lost from the cultivate soil profile and the rate of soil erosion. According to a mass balance model, during the construction of this model we considered the following parameters: the remaining fraction of the surface enrichment layer (F R ), the thickness of the surface enrichment layer (H s ), the depth of the plough layer (H p ), input fraction of the total 137 Cs fallout deposition during a given year t (F t ), radioactive decay of 137 Cs (k), and sampling year (t). The simulation results showed that the amounts of erosion rates estimated using this model were very sensitive to changes in the values of the parameters F R , H s , and H p . We also observed that the relationship between the rate of soil loss and 137 Cs depletion is neither linear nor logarithmic, and is very complex. Although the model is an improvement over existing approaches to derive calibration relationships for cultivated soil, it requires empirical information on local soil properties and the behavior of 137 Cs in the soil profile. There is clearly still a need for more precise information on the latter aspect and, in particular, on the retention of 137 Cs fallout in the top few millimeters of the soil profile and on the enrichment and depletion effects associated with soil redistribution (i.e. for determining accurate values of F R and H s ). (author)

Polymorphic ethyl alcohol as a model system for the quantitative study of glassy behaviour

Energy Technology Data Exchange (ETDEWEB)

Fischer, H E; Schober, H; Gonzalez, M A [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France); Bermejo, F J; Fayos, R; Dawidowski, J [Consejo Superior de Investigaciones Cientificas, Madrid (Spain); Ramos, M A; Vieira, S [Universidad Autonoma de Madrid (Spain)

1997-04-01

The nearly universal transport and dynamical properties of amorphous materials or glasses are investigated. Reasonably successful phenomenological models have been developed to account for these properties as well as the behaviour near the glass-transition, but quantitative microscopic models have had limited success. One hindrance to these investigations has been the lack of a material which exhibits glass-like properties in more than one phase at a given temperature. This report presents results of neutron-scattering experiments for one such material ordinary ethyl alcohol, which promises to be a model system for future investigations of glassy behaviour. (author). 8 refs.

Using the ACT-R architecture to specify 39 quantitative process models of decision making

Directory of Open Access Journals (Sweden)

Julian N. Marewski

2011-08-01

Full Text Available Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.

Use of a plant level logic model for quantitative assessment of systems interactions

International Nuclear Information System (INIS)

Chu, B.B.; Rees, D.C.; Kripps, L.P.; Hunt, R.N.; Bradley, M.

1985-01-01

The Electric Power Research Institute (EPRI) has sponsored a research program to investigate methods for identifying systems interactions (SIs) and for the evaluation of their importance. Phase 1 of the EPRI research project focused on the evaluation of methods for identification of SIs. Major results of the Phase 1 activities are the documentation of four different methodologies for identification of potential SIs and development of guidelines for performing an effective plant walkdown in support of an SI analysis. Phase II of the project, currently being performed, is utilizing a plant level logic model of a pressurized water reactor (PWR) to determine the quantitative importance of identified SIs. In Phase II, previously reported events involving interactions between systems were screened and selected on the basis of their relevance to the Baltimore Gas and Electric (BGandE) Calvert Cliffs Nuclear Power Plant design and perceived potential safety significance. Selected events were then incorporated into the BGandE plant level GO logic model. The model is being exercised to calculate the relative importance of these events. Five previously identified event scenarios, extracted from licensee event reports (LERs) are being evaluated during the course of the study. A key feature of the approach being used in Phase II is the use of a logic model in a manner to effectively evaluate the impact of events on the system level and the plant level for the mitigation of transients. Preliminary study results indicate that the developed methodology can be a viable and effective means for determining the quantitative significance of SIs

A quantitative quasispecies theory-based model of virus escape mutation under immune selection.

Science.gov (United States)

Woo, Hyung-June; Reifman, Jaques

2012-08-07

Viral infections involve a complex interplay of the immune response and escape mutation of the virus quasispecies inside a single host. Although fundamental aspects of such a balance of mutation and selection pressure have been established by the quasispecies theory decades ago, its implications have largely remained qualitative. Here, we present a quantitative approach to model the virus evolution under cytotoxic T-lymphocyte immune response. The virus quasispecies dynamics are explicitly represented by mutations in the combined sequence space of a set of epitopes within the viral genome. We stochastically simulated the growth of a viral population originating from a single wild-type founder virus and its recognition and clearance by the immune response, as well as the expansion of its genetic diversity. Applied to the immune escape of a simian immunodeficiency virus epitope, model predictions were quantitatively comparable to the experimental data. Within the model parameter space, we found two qualitatively different regimes of infectious disease pathogenesis, each representing alternative fates of the immune response: It can clear the infection in finite time or eventually be overwhelmed by viral growth and escape mutation. The latter regime exhibits the characteristic disease progression pattern of human immunodeficiency virus, while the former is bounded by maximum mutation rates that can be suppressed by the immune response. Our results demonstrate that, by explicitly representing epitope mutations and thus providing a genotype-phenotype map, the quasispecies theory can form the basis of a detailed sequence-specific model of real-world viral pathogens evolving under immune selection.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

Science.gov (United States)

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-07

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data

Science.gov (United States)

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-01

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Quantitative Reasoning in Environmental Science: A Learning Progression

Science.gov (United States)

Mayes, Robert Lee; Forrester, Jennifer Harris; Christus, Jennifer Schuttlefield; Peterson, Franziska Isabel; Bonilla, Rachel; Yestness, Nissa

2014-01-01

The ability of middle and high school students to reason quantitatively within the context of environmental science was investigated. A quantitative reasoning (QR) learning progression was created with three progress variables: quantification act, quantitative interpretation, and quantitative modeling. An iterative research design was used as it…

Quantitative modeling of the reaction/diffusion kinetics of two-chemistry photopolymers

Science.gov (United States)

Kowalski, Benjamin Andrew

Optically driven diffusion in photopolymers is an appealing material platform for a broad range of applications, in which the recorded refractive index patterns serve either as images (e.g. data storage, display holography) or as optical elements (e.g. custom GRIN components, integrated optical devices). A quantitative understanding of the reaction/diffusion kinetics is difficult to obtain directly, but is nevertheless necessary in order to fully exploit the wide array of design freedoms in these materials. A general strategy for characterizing these kinetics is proposed, in which key processes are decoupled and independently measured. This strategy enables prediction of a material's potential refractive index change, solely on the basis of its chemical components. The degree to which a material does not reach this potential reveals the fraction of monomer that has participated in unwanted reactions, reducing spatial resolution and dynamic range. This approach is demonstrated for a model material similar to commercial media, achieving quantitative predictions of index response over three orders of exposure dose (~1 to ~103 mJ cm-2) and three orders of feature size (0.35 to 500 microns). The resulting insights enable guided, rational design of new material formulations with demonstrated performance improvement.

The Comparison of Distributed P2P Trust Models Based on Quantitative Parameters in the File Downloading Scenarios

Directory of Open Access Journals (Sweden)

Jingpei Wang

2016-01-01

Full Text Available Varied P2P trust models have been proposed recently; it is necessary to develop an effective method to evaluate these trust models to resolve the commonalities (guiding the newly generated trust models in theory and individuality (assisting a decision maker in choosing an optimal trust model to implement in specific context issues. A new method for analyzing and comparing P2P trust models based on hierarchical parameters quantization in the file downloading scenarios is proposed in this paper. Several parameters are extracted from the functional attributes and quality feature of trust relationship, as well as requirements from the specific network context and the evaluators. Several distributed P2P trust models are analyzed quantitatively with extracted parameters modeled into a hierarchical model. The fuzzy inferring method is applied to the hierarchical modeling of parameters to fuse the evaluated values of the candidate trust models, and then the relative optimal one is selected based on the sorted overall quantitative values. Finally, analyses and simulation are performed. The results show that the proposed method is reasonable and effective compared with the previous algorithms.

Frequency domain modeling and dynamic characteristics evaluation of existing wind turbine systems

Science.gov (United States)

Chiang, Chih-Hung; Yu, Chih-Peng

2016-04-01

It is quite well accepted that frequency domain procedures are suitable for the design and dynamic analysis of wind turbine structures, especially for floating offshore wind turbines, since random wind loads and wave induced motions are most likely simulated in the frequency domain. This paper presents specific applications of an effective frequency domain scheme to the linear analysis of wind turbine structures in which a 1-D spectral element was developed based on the axially-loaded member. The solution schemes are summarized for the spectral analyses of the tower, the blades, and the combined system with selected frequency-dependent coupling effect from foundation-structure interactions. Numerical examples demonstrate that the modal frequencies obtained using spectral-element models are in good agreement with those found in the literature. A 5-element mono-pile model results in less than 0.3% deviation from an existing 160-element model. It is preliminarily concluded that the proposed scheme is relatively efficient in performing quick verification for test data obtained from the on-site vibration measurement using the microwave interferometer.

A quantitative microbial risk assessment model for Listeria monocytogenes in RTE sandwiches

DEFF Research Database (Denmark)

Tirloni, E.; Stella, S.; de Knegt, Leonardo

2018-01-01

within each serving. Then, two dose-response models were alternatively applied: the first used a fixed r value for each of the three population groups, while the second considered a variable r value (lognormal distribution), taking into account the variability in strain virulence and different host...... subpopulations susceptibility. The stochastic model predicted zero cases for total population for both the substrates by using the fixed r approach, while 3 cases were expected when a higher variability (in virulence and susceptibility) was considered in the model; the number of cases increased to 45......A Quantitative Microbial Risk Assessment (QMRA) was performed to estimate the expected number of listeriosis cases due to the consumption, on the last day of shelf life, of 20 000 servings of multi-ingredient sandwiches produced by a medium scale food producer in Italy, by different population...

Initial Description of a Quantitative, Cross-Species (Chimpanzee-Human) Social Responsiveness Measure

Science.gov (United States)

Marrus, Natasha; Faughn, Carley; Shuman, Jeremy; Petersen, Steve E.; Constantino, John N.; Povinelli, Daniel J.; Pruett, John R., Jr.

2011-01-01

Objective: Comparative studies of social responsiveness, an ability that is impaired in autism spectrum disorders, can inform our understanding of both autism and the cognitive architecture of social behavior. Because there is no existing quantitative measure of social responsiveness in chimpanzees, we generated a quantitative, cross-species…

Thai student existing understanding about the solar system model and the motion of the stars

Science.gov (United States)

Anantasook, Sakanan; Yuenyong, Chokchai

2018-01-01

The paper examined Thai student existing understanding about the solar system model and the motion of the stars. The participants included 141 Grade 9 students in four different schools of the Surin province, Thailand. Methodology regarded interpretive paradigm. The tool of interpretation included the Student Celestial Motion Conception Questionnaire (SCMCQ) and informal interview. Given understandings in the SCMCQ were read through and categorized according to students' understandings. Then, students were further probed as informal interview. Students' understandings in each category were counted and percentages computed. Finally, students' understandings across four different schools were compared and contrasted using the percentage of student responses in each category. The findings revealed that most students understand about Sun-Moon-Earth (SME) system and solar system model as well, they can use scientific explanations to explain the celestial objects in solar system and how they orbiting. Unfortunately, most of students (more than 70%) never know about the Polaris, the North Star, and 90.1% of them never know about the ecliptic, and probably also the 12 zodiac constellations. These existing understanding suggested some ideas of teaching and learning about solar system model and the motion of the stars. The paper, then, discussed some learning activities to enhance students to further construct meaning about solar system model and the motion of the stars.

Quantitative Modeling of Acid Wormholing in Carbonates- What Are the Gaps to Bridge

KAUST Repository

Qiu, Xiangdong

2013-01-01

Carbonate matrix acidization extends a well\\'s effective drainage radius by dissolving rock and forming conductive channels (wormholes) from the wellbore. Wormholing is a dynamic process that involves balance between the acid injection rate and reaction rate. Generally, injection rate is well defined where injection profiles can be controlled, whereas the reaction rate can be difficult to obtain due to its complex dependency on interstitial velocity, fluid composition, rock surface properties etc. Conventional wormhole propagation models largely ignore the impact of reaction products. When implemented in a job design, the significant errors can result in treatment fluid schedule, rate, and volume. A more accurate method to simulate carbonate matrix acid treatments would accomodate the effect of reaction products on reaction kinetics. It is the purpose of this work to properly account for these effects. This is an important step in achieving quantitative predictability of wormhole penetration during an acidzing treatment. This paper describes the laboratory procedures taken to obtain the reaction-product impacted kinetics at downhole conditions using a rotating disk apparatus, and how this new set of kinetics data was implemented in a 3D wormholing model to predict wormhole morphology and penetration velocity. The model explains some of the differences in wormhole morphology observed in limestone core flow experiments where injection pressure impacts the mass transfer of hydrogen ions to the rock surface. The model uses a CT scan rendered porosity field to capture the finer details of the rock fabric and then simulates the fluid flow through the rock coupled with reactions. Such a validated model can serve as a base to scale up to near wellbore reservoir and 3D radial flow geometry allowing a more quantitative acid treatment design.

Designing a Qualitative Data Collection Strategy (QDCS) for Africa - Phase 1: A Gap Analysis of Existing Models, Simulations, and Tools Relating to Africa

Science.gov (United States)

2012-06-01

QDCS) for Africa – Phase I: A Gap Analysis of Existing Models, Simulations, and Tools Relating to Africa Ashley N. Bybee , Project Leader Dominick E...Strategy (QDCS) for Africa – Phase I: A Gap Analysis of Existing Models, Simulations, and Tools Relating to Africa Ashley N. Bybee , Project Leader...Africa Phase I: A Gap Analysis of Existing Models, Simulations, and Tools Relating to Africa June 2012 Authors: Dr. Ashley Bybee , Project Lead Dr

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

Science.gov (United States)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

A quantitative approach to modeling the information processing of NPP operators under input information overload

International Nuclear Information System (INIS)

Kim, Jong Hyun; Seong, Poong Hyun

2002-01-01

This paper proposes a quantitative approach to modeling the information processing of NPP operators. The aim of this work is to derive the amount of the information processed during a certain control task under input information overload. We primarily develop the information processing model having multiple stages, which contains information flow. Then the uncertainty of the information is quantified using the Conant's model, a kind of information theory. We also investigate the applicability of this approach to quantifying the information reduction of operators under the input information overload

A toy model to investigate the existence of excitons in the ground state of strongly-correlated semiconductor

Science.gov (United States)

Karima, H. R.; Majidi, M. A.

2018-04-01

Excitons, quasiparticles associated with bound states between an electron and a hole and are typically created when photons with a suitable energy are absorbed in a solid-state material. We propose to study a possible emergence of excitons, created not by photon absorption but the effect of strong electronic correlations. This study is motivated by a recent experimental study of a substrate material SrTiO3 (STO) that reveals strong exitonic signals in its optical conductivity. Here we conjecture that some excitons may already exist in the ground state as a result of the electronic correlations before the additional excitons being created later by photon absorption. To investigate the existence of excitons in the ground state, we propose to study a simple 4-energy-level model that mimics a situation in strongly-correlated semiconductors. The four levels are divided into two groups, lower and upper groups separated by an energy gap, Eg , mimicking the valence and the conduction bands, respectively. Further, we incorporate repulsive Coulomb interactions between the electrons. The model is then solved by exact diagonalization method. Our result shows that the toy model can demonstrate band gap widening or narrowing and the existence of exciton in the ground state depending on interaction parameter values.

Does a General Temperature-Dependent Q10 Model of Soil Respiration Exist at Biome and Global Scale?

Institute of Scientific and Technical Information of China (English)

Hua CHEN; Han-Qin TIAN

2005-01-01

Soil respiration (SR) is commonly modeled by a Q10 (an indicator of temperature sensitivity)function in ecosystem models. Q10is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperaturedependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Subtropical biome on four continents.Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values (Q10 decay rate constants) were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the "global" single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally.The existence of the general temperature-dependent Q10 models of SR in the Boreal and

Quantitative interpretation of great lakes remote sensing data

International Nuclear Information System (INIS)

Shook, D.F.; Salzman, J.; Svehla, R.A.; Gedney, R.T.

1980-01-01

Remote sensing has been applied in the past to the surveillance of Great Lakes water quality, but it has been only partially successful because of the completely empirical approach taken in relating the multispectral scanning data at visible and near-infrared wavelengths to water parameters. Any remote sensing approach using water color information must take into account (1) the existence of many different organic and inorganic species throughtout the Greak Lakes, (2) the occurrence of a mixture of species in most locations, and (3) spatial (inter- and interlake as well as vertical) variations in types and concentrations of species. The radiative transfer model provides a potential method for an orderly analysis of remote sensing data and a physical basis for developing quantitative algorithms. Predictions and field measurements of volume reflectances are presented which clearly show the advantage of using a radiative transfer model. Spectral absorptance and backscattering coefficients for two inorganic sediments are reported

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

Science.gov (United States)

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

A Quantitative bgl Operon Model for E. coli Requires BglF Conformational Change for Sugar Transport

Science.gov (United States)

Chopra, Paras; Bender, Andreas

The bgl operon is responsible for the metabolism of β-glucoside sugars such as salicin or arbutin in E. coli. Its regulatory system involves both positive and negative feedback mechanisms and it can be assumed to be more complex than that of the more closely studied lac and trp operons. We have developed a quantitative model for the regulation of the bgl operon which is subject to in silico experiments investigating its behavior under different hypothetical conditions. Upon administration of 5mM salicin as an inducer our model shows 80-fold induction, which compares well with the 60-fold induction measured experimentally. Under practical conditions 5-10mM inducer are employed, which is in line with the minimum inducer concentration of 1mM required by our model. The necessity of BglF conformational change for sugar transport has been hypothesized previously, and in line with those hypotheses our model shows only minor induction if conformational change is not allowed. Overall, this first quantitative model for the bgl operon gives reasonable predictions that are close to experimental results (where measured). It will be further refined as values of the parameters are determined experimentally. The model was developed in Systems Biology Markup Language (SBML) and it is available from the authors and from the Biomodels repository [www.ebi.ac.uk/biomodels].

Quantitative analysis of CT brain images: a statistical model incorporating partial volume and beam hardening effects

International Nuclear Information System (INIS)

McLoughlin, R.F.; Ryan, M.V.; Heuston, P.M.; McCoy, C.T.; Masterson, J.B.

1992-01-01

The purpose of this study was to construct and evaluate a statistical model for the quantitative analysis of computed tomographic brain images. Data were derived from standard sections in 34 normal studies. A model representing the intercranial pure tissue and partial volume areas, with allowance for beam hardening, was developed. The average percentage error in estimation of areas, derived from phantom tests using the model, was 28.47%. We conclude that our model is not sufficiently accurate to be of clinical use, even though allowance was made for partial volume and beam hardening effects. (author)

Development of an Experimental Model of Diabetes Co-Existing with Metabolic Syndrome in Rats.

Science.gov (United States)

Suman, Rajesh Kumar; Ray Mohanty, Ipseeta; Borde, Manjusha K; Maheshwari, Ujwala; Deshmukh, Y A

2016-01-01

Background. The incidence of metabolic syndrome co-existing with diabetes mellitus is on the rise globally. Objective. The present study was designed to develop a unique animal model that will mimic the pathological features seen in individuals with diabetes and metabolic syndrome, suitable for pharmacological screening of drugs. Materials and Methods. A combination of High-Fat Diet (HFD) and low dose of streptozotocin (STZ) at 30, 35, and 40 mg/kg was used to induce metabolic syndrome in the setting of diabetes mellitus in Wistar rats. Results. The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for the study to induce diabetes mellitus. Various components of metabolic syndrome such as dyslipidemia {(increased triglyceride, total cholesterol, LDL cholesterol, and decreased HDL cholesterol)}, diabetes mellitus (blood glucose, HbA1c, serum insulin, and C-peptide), and hypertension {systolic blood pressure} were mimicked in the developed model of metabolic syndrome co-existing with diabetes mellitus. In addition to significant cardiac injury, atherogenic index, inflammation (hs-CRP), decline in hepatic and renal function were observed in the HF-DC group when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis, and inflammation in heart, pancreas, liver, and kidney of HF-DC group as compared to NC. Conclusion. The present study has developed a unique rodent model of metabolic syndrome, with diabetes as an essential component.

Development of an Experimental Model of Diabetes Co-Existing with Metabolic Syndrome in Rats

Directory of Open Access Journals (Sweden)

Rajesh Kumar Suman

2016-01-01

Full Text Available Background. The incidence of metabolic syndrome co-existing with diabetes mellitus is on the rise globally. Objective. The present study was designed to develop a unique animal model that will mimic the pathological features seen in individuals with diabetes and metabolic syndrome, suitable for pharmacological screening of drugs. Materials and Methods. A combination of High-Fat Diet (HFD and low dose of streptozotocin (STZ at 30, 35, and 40 mg/kg was used to induce metabolic syndrome in the setting of diabetes mellitus in Wistar rats. Results. The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for the study to induce diabetes mellitus. Various components of metabolic syndrome such as dyslipidemia (increased triglyceride, total cholesterol, LDL cholesterol, and decreased HDL cholesterol, diabetes mellitus (blood glucose, HbA1c, serum insulin, and C-peptide, and hypertension {systolic blood pressure} were mimicked in the developed model of metabolic syndrome co-existing with diabetes mellitus. In addition to significant cardiac injury, atherogenic index, inflammation (hs-CRP, decline in hepatic and renal function were observed in the HF-DC group when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis, and inflammation in heart, pancreas, liver, and kidney of HF-DC group as compared to NC. Conclusion. The present study has developed a unique rodent model of metabolic syndrome, with diabetes as an essential component.

Existence of Periodic Solutions and Stability of Zero Solution of a Mathematical Model of Schistosomiasis

Directory of Open Access Journals (Sweden)

Lin Li

2014-01-01

Full Text Available A mathematical model on schistosomiasis governed by periodic differential equations with a time delay was studied. By discussing boundedness of the solutions of this model and construction of a monotonic sequence, the existence of positive periodic solution was shown. The conditions under which the model admits a periodic solution and the conditions under which the zero solution is globally stable are given, respectively. Some numerical analyses show the conditional coexistence of locally stable zero solution and periodic solutions and that it is an effective treatment by simply reducing the population of snails and enlarging the death ratio of snails for the control of schistosomiasis.

Post-hoc pattern-oriented testing and tuning of an existing large model: lessons from the field vole.

Directory of Open Access Journals (Sweden)

Christopher J Topping

Full Text Available Pattern-oriented modeling (POM is a general strategy for modeling complex systems. In POM, multiple patterns observed at different scales and hierarchical levels are used to optimize model structure, to test and select sub-models of key processes, and for calibration. So far, POM has been used for developing new models and for models of low to moderate complexity. It remains unclear, though, whether the basic idea of POM to utilize multiple patterns, could also be used to test and possibly develop existing and established models of high complexity. Here, we use POM to test, calibrate, and further develop an existing agent-based model of the field vole (Microtus agrestis, which was developed and tested within the ALMaSS framework. This framework is complex because it includes a high-resolution representation of the landscape and its dynamics, of the individual's behavior, and of the interaction between landscape and individual behavior. Results of fitting to the range of patterns chosen were generally very good, but the procedure required to achieve this was long and complicated. To obtain good correspondence between model and the real world it was often necessary to model the real world environment closely. We therefore conclude that post-hoc POM is a useful and viable way to test a highly complex simulation model, but also warn against the dangers of over-fitting to real world patterns that lack details in their explanatory driving factors. To overcome some of these obstacles we suggest the adoption of open-science and open-source approaches to ecological simulation modeling.

A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait.

Science.gov (United States)

Geroldinger, Ludwig; Bürger, Reinhard

2014-06-01

The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Greening Existing Buildings in Contemporary Iraqi Urban Reality/ Virtual Model

Directory of Open Access Journals (Sweden)

Saba Jabar Neama Al-Khafaji

2015-11-01

Full Text Available The approach of greening existing buildings, is an urgent necessity, because the greening operation provides the speed and optimal efficiency in the environmental performance, as well as keeping up with the global green architecture revolution. Therefore, greening existing buildings in Iraq is important for trends towards renewable energies, because of what the country went through economic conditions and crises and wars which kept the country away from what took place globally in this issue. The research problem is: insufficient knowledge about the importance and the mechanism of the greening of existing buildings, including its environmental and economic dimensions, by rationalization of energy consumption and preserving the environment. The research objective is: clarifying the importance of greening existing buildings environmentally and economically, providing a virtual experience for greening the presidency building of Baghdad University, through advanced computer program. The main conclusions is: there is difference representing by reducing the disbursed thermal loads amount for cooling in summer and heating in winter through the use of computerized program (DesignBuilder and that after the implementation of greening operations on the building envelope, which confirms its effectiveness in raising the energy performance efficiency inside the building. Hence, the importance of the application of greening existing buildings approach in Iraq, to bring back Iraqi architecture to environmental and local track proper.

Study on quantitative risk assessment model of the third party damage for natural gas pipelines based on fuzzy comprehensive assessment

International Nuclear Information System (INIS)

Qiu, Zeyang; Liang, Wei; Lin, Yang; Zhang, Meng; Wang, Xue

2017-01-01

As an important part of national energy supply system, transmission pipelines for natural gas are possible to cause serious environmental pollution, life and property loss in case of accident. The third party damage is one of the most significant causes for natural gas pipeline system accidents, and it is very important to establish an effective quantitative risk assessment model of the third party damage for reducing the number of gas pipelines operation accidents. Against the third party damage accident has the characteristics such as diversity, complexity and uncertainty, this paper establishes a quantitative risk assessment model of the third party damage based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE). Firstly, risk sources of third party damage should be identified exactly, and the weight of factors could be determined via improved AHP, finally the importance of each factor is calculated by fuzzy comprehensive evaluation model. The results show that the quantitative risk assessment model is suitable for the third party damage of natural gas pipelines and improvement measures could be put forward to avoid accidents based on the importance of each factor. (paper)

Quantitative Measurement of Eyestrain on 3D Stereoscopic Display Considering the Eye Foveation Model and Edge Information

Directory of Open Access Journals (Sweden)

Hwan Heo

2014-05-01

Full Text Available We propose a new method for measuring the degree of eyestrain on 3D stereoscopic displays using a glasses-type of eye tracking device. Our study is novel in the following four ways: first, the circular area where a user’s gaze position exists is defined based on the calculated gaze position and gaze estimation error. Within this circular area, the position where edge strength is maximized can be detected, and we determine this position as the gaze position that has a higher probability of being the correct one. Based on this gaze point, the eye foveation model is defined. Second, we quantitatively evaluate the correlation between the degree of eyestrain and the causal factors of visual fatigue, such as the degree of change of stereoscopic disparity (CSD, stereoscopic disparity (SD, frame cancellation effect (FCE, and edge component (EC of the 3D stereoscopic display using the eye foveation model. Third, by comparing the eyestrain in conventional 3D video and experimental 3D sample video, we analyze the characteristics of eyestrain according to various factors and types of 3D video. Fourth, by comparing the eyestrain with or without the compensation of eye saccades movement in 3D video, we analyze the characteristics of eyestrain according to the types of eye movements in 3D video. Experimental results show that the degree of CSD causes more eyestrain than other factors.

Mastering R for quantitative finance

CERN Document Server

Berlinger, Edina; Badics, Milán; Banai, Ádám; Daróczi, Gergely; Dömötör, Barbara; Gabler, Gergely; Havran, Dániel; Juhász, Péter; Margitai, István; Márkus, Balázs; Medvegyev, Péter; Molnár, Julia; Szucs, Balázs Árpád; Tuza, Ágnes; Vadász, Tamás; Váradi, Kata; Vidovics-Dancs, Ágnes

2015-01-01

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

Quantitative analysis of receptor imaging

International Nuclear Information System (INIS)

Fu Zhanli; Wang Rongfu

2004-01-01

Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

Marketing communications: Qualitative and quantitative paradigm

Directory of Open Access Journals (Sweden)

Uzelac Nikola

2005-01-01

Full Text Available This paper focuses on key issues in relation to the choice of basic language of communication of marketing as a practical and academic field. Principally, marketing managers prefer descriptive way of expression, but they should use the advantages of language of numbers much more. By doing so, they will advance decision-making process - and the communication with finance and top management. In this regard, models offered by academic community could be helpful. This especially pertains to those positive or normative verbal approaches and models in which mathematics and statistical solutions have been embedded, as well as to those which emphasize financial criteria in decision-making. Concerning the process of creation and verification of scientific knowledge, the choice between languages of words and numbers is the part of much wider dimension, because it is inseparable from the decision on basic research orientation. Quantitative paradigm is more appropriate for hypotheses testing, while qualitative paradigm gives greater contribution in their generation. Competition factor could become the key driver of changes by which existing "parallel worlds" of main paradigms would be integrating, for the sake of disciplinary knowledge advancement.

Personnel shift assignment: Existence conditions and network models

NARCIS (Netherlands)

van den Berg, Jeroen P.; van den Berg, J.P.; Panton, David M.

1994-01-01

The personnel scheduling problem is known to be a five-stage process in which the final stage involves the assignment of shifts to the days worked in the schedule. This paper discusses the existence conditions for both continuous and forward rotating shift assignments and heuristic network

In-vivo quantitative measurement

International Nuclear Information System (INIS)

Ito, Takashi

1992-01-01

So far by positron CT, the quantitative analyses of oxygen consumption rate, blood flow distribution, glucose metabolic rate and so on have been carried out. The largest merit of using the positron CT is the observation and verification of mankind have become easy. Recently, accompanying the rapid development of the mapping tracers for central nervous receptors, the observation of many central nervous receptors by the positron CT has become feasible, and must expectation has been placed on the elucidation of brain functions. The conditions required for in vitro processes cannot be realized in strict sense in vivo. The quantitative measurement of in vivo tracer method is carried out by measuring the accumulation and movement of a tracer after its administration. The movement model of the mapping tracer for central nervous receptors is discussed. The quantitative analysis using a steady movement model, the measurement of dopamine receptors by reference method, the measurement of D 2 receptors using 11C-Racloprode by direct method, and the possibility of measuring dynamics bio-reaction are reported. (K.I.)

Systematic Analysis of Quantitative Logic Model Ensembles Predicts Drug Combination Effects on Cell Signaling Networks

Science.gov (United States)

2016-08-27

bovine serum albumin (BSA) diluted to the amount corresponding to that in the media of the stimulated cells. Phospho-JNK comprises two isoforms whose...information accompanies this paper on the CPT: Pharmacometrics & Systems Pharmacology website (http://www.wileyonlinelibrary.com/psp4) Systematic Analysis of Quantitative Logic Model Morris et al. 553 www.wileyonlinelibrary/psp4

A methodology for the extraction of quantitative information from electron microscopy images at the atomic level

International Nuclear Information System (INIS)

Galindo, P L; Pizarro, J; Guerrero, E; Guerrero-Lebrero, M P; Scavello, G; Yáñez, A; Sales, D L; Herrera, M; Molina, S I; Núñez-Moraleda, B M; Maestre, J M

2014-01-01

In this paper we describe a methodology developed at the University of Cadiz (Spain) in the past few years for the extraction of quantitative information from electron microscopy images at the atomic level. This work is based on a coordinated and synergic activity of several research groups that have been working together over the last decade in two different and complementary fields: Materials Science and Computer Science. The aim of our joint research has been to develop innovative high-performance computing techniques and simulation methods in order to address computationally challenging problems in the analysis, modelling and simulation of materials at the atomic scale, providing significant advances with respect to existing techniques. The methodology involves several fundamental areas of research including the analysis of high resolution electron microscopy images, materials modelling, image simulation and 3D reconstruction using quantitative information from experimental images. These techniques for the analysis, modelling and simulation allow optimizing the control and functionality of devices developed using materials under study, and have been tested using data obtained from experimental samples

Quantitative Analysis of Microbes in Water Tank of G.A. Siwabessy Reactor

International Nuclear Information System (INIS)

Itjeu Karliana; Diah Dwiana Lestiani

2003-01-01

The quality of water in reactor system has an important role because it could effect the function as a coolant and the operation of reactor indirectly. The study of microbe analyzes has been carried out to detect the existence of microbes in water tank and quantitative analyzes of microbes also has been applied as a continuation of the previous study. The samples is taken out from the end side of reactor GA Siwabessy's tank, inoculated in TSA (Tripcase Soy Agar) medium, put in incubator at 30 - 35 o C for 4 days. The results of experiment show the reconfirmation for the existence of bacteria and the un-existence of yield. The quantitative analysis with TPC method show the growth rate of bacteria is twice in 24 hours. (author)

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

Science.gov (United States)

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Quantitative histological models suggest endothermy in plesiosaurs

Directory of Open Access Journals (Sweden)

Corinna V. Fleischle

2018-06-01

Full Text Available Background Plesiosaurs are marine reptiles that arose in the Late Triassic and survived to the Late Cretaceous. They have a unique and uniform bauplan and are known for their very long neck and hydrofoil-like flippers. Plesiosaurs are among the most successful vertebrate clades in Earth’s history. Based on bone mass decrease and cosmopolitan distribution, both of which affect lifestyle, indications of parental care, and oxygen isotope analyses, evidence for endothermy in plesiosaurs has accumulated. Recent bone histological investigations also provide evidence of fast growth and elevated metabolic rates. However, quantitative estimations of metabolic rates and bone growth rates in plesiosaurs have not been attempted before. Methods Phylogenetic eigenvector maps is a method for estimating trait values from a predictor variable while taking into account phylogenetic relationships. As predictor variable, this study employs vascular density, measured in bone histological sections of fossil eosauropterygians and extant comparative taxa. We quantified vascular density as primary osteon density, thus, the proportion of vascular area (including lamellar infillings of primary osteons to total bone area. Our response variables are bone growth rate (expressed as local bone apposition rate and resting metabolic rate (RMR. Results Our models reveal bone growth rates and RMRs for plesiosaurs that are in the range of birds, suggesting that plesiosaurs were endotherm. Even for basal eosauropterygians we estimate values in the range of mammals or higher. Discussion Our models are influenced by the availability of comparative data, which are lacking for large marine amniotes, potentially skewing our results. However, our statistically robust inference of fast growth and fast metabolism is in accordance with other evidence for plesiosaurian endothermy. Endothermy may explain the success of plesiosaurs consisting in their survival of the end-Triassic extinction

Quantitative Microbial Risk Assessment Tutorial Installation of Software for Watershed Modeling in Support of QMRA - Updated 2017

Science.gov (United States)

This tutorial provides instructions for accessing, retrieving, and downloading the following software to install on a host computer in support of Quantitative Microbial Risk Assessment (QMRA) modeling: • QMRA Installation • SDMProjectBuilder (which includes the Microbial ...

Downscaling SSPs in the GBM Delta - Integrating Science, Modelling and Stakeholders Through Qualitative and Quantitative Scenarios

Science.gov (United States)

Allan, Andrew; Barbour, Emily; Salehin, Mashfiqus; Munsur Rahman, Md.; Hutton, Craig; Lazar, Attila

2016-04-01

A downscaled scenario development process was adopted in the context of a project seeking to understand relationships between ecosystem services and human well-being in the Ganges-Brahmaputra delta. The aim was to link the concerns and priorities of relevant stakeholders with the integrated biophysical and poverty models used in the project. A 2-stage process was used to facilitate the connection between stakeholders concerns and available modelling capacity: the first to qualitatively describe what the future might look like in 2050; the second to translate these qualitative descriptions into the quantitative form required by the numerical models. An extended, modified SSP approach was adopted, with stakeholders downscaling issues identified through interviews as being priorities for the southwest of Bangladesh. Detailed qualitative futures were produced, before modellable elements were quantified in conjunction with an expert stakeholder cadre. Stakeholder input, using the methods adopted here, allows the top-down focus of the RCPs to be aligned with the bottom-up approach needed to make the SSPs appropriate at the more local scale, and also facilitates the translation of qualitative narrative scenarios into a quantitative form that lends itself to incorporation of biophysical and socio-economic indicators. The presentation will describe the downscaling process in detail, and conclude with findings regarding the importance of stakeholder involvement (and logistical considerations), balancing model capacity with expectations and recommendations on SSP refinement at local levels.

The existence and persistence of household financial hardship

OpenAIRE

Brown, S.; Ghosh, P.; Taylor, K.

2012-01-01

We investigate the existence and persistence of financial hardship at the household level using data from the British Household Panel Survey. Our modelling strategy makes three important contributions to the existing literature on household finances. Firstly, we model nine different types of household financial problems within a joint framework, allowing for correlation in the random effects across the nine equations. Secondly, we develop a dynamic framework in order to model the persistence ...

Existence and non-existence for the full thermomechanical Souza–Auricchio model of shape memory wires

Czech Academy of Sciences Publication Activity Database

Krejčí, Pavel; Stefanelli, U.

2011-01-01

Roč. 16, č. 4 (2011), s. 349-365 ISSN 1081-2865 R&D Projects: GA ČR GAP201/10/2315 Institutional research plan: CEZ:AV0Z10190503 Keywords : shape memory alloys * thermomechanics * existence result * blowup in finite time Subject RIV: BA - General Mathematics Impact factor: 1.012, year: 2011 http://mms.sagepub.com/content/early/2011/03/11/1081286510386935.abstract

Existence and non-existence for the full thermomechanical Souza–Auricchio model of shape memory wires

Czech Academy of Sciences Publication Activity Database

Krejčí, Pavel; Stefanelli, U.

2011-01-01

Roč. 16, č. 4 (2011), s. 349-365 ISSN 1081-2865 R&D Projects: GA ČR GAP201/10/2315 Institutional research plan: CEZ:AV0Z10190503 Keywords : shape memory alloys * thermomechanics * existence result * blowup in finite time Subject RIV: BA - General Mathematics Impact factor: 1.012, year: 2011 http:// mms .sagepub.com/content/early/2011/03/11/1081286510386935.abstract

A Review of the Appropriateness of Existing Micro- and Meso-level Models of Athlete Development within Equestrian Sport

NARCIS (Netherlands)

de Haan, D.M.

2017-01-01

The aim of this paper was to use a case study approach to review the appropriateness of existing micro- and meso-level models of athlete development within the sport specific context of equestrianism. At a micro-level the Long Term Athlete Development (LTAD) model was chosen. At a meso-level, the

Quality control in quantitative computed tomography

International Nuclear Information System (INIS)

Jessen, K.A.; Joergensen, J.

1989-01-01

Computed tomography (CT) has for several years been an indispensable tool in diagnostic radiology, but it is only recently that extraction of quantitative information from CT images has been of practical clinical value. Only careful control of the scan parameters, and especially the scan geometry, allows useful information to be obtained; and it can be demonstrated by simple phantom measurements how sensitive a CT system can be to variations in size, shape and position of the phantom in the gantry aperture. Significant differences exist between systems that are not manifested in normal control of image quality and general performance tests. Therefore an actual system has to be analysed for its suitability for quantitative use of the images before critical clinical applications are justified. (author)

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

Science.gov (United States)

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

Quantitative laser diagnostic and modeling study of C2 and CH chemistry in combustion.

Science.gov (United States)

Köhler, Markus; Brockhinke, Andreas; Braun-Unkhoff, Marina; Kohse-Höinghaus, Katharina

2010-04-15

Quantitative concentration measurements of CH and C(2) have been performed in laminar, premixed, flat flames of propene and cyclopentene with varying stoichiometry. A combination of cavity ring-down (CRD) spectroscopy and laser-induced fluorescence (LIF) was used to enable sensitive detection of these species with high spatial resolution. Previously, CH and C(2) chemistry had been studied, predominantly in methane flames, to understand potential correlations of their formation and consumption. For flames of larger hydrocarbon fuels, however, quantitative information on these small intermediates is scarce, especially under fuel-rich conditions. Also, the combustion chemistry of C(2) in particular has not been studied in detail, and although it has often been observed, its role in potential build-up reactions of higher hydrocarbon species is not well understood. The quantitative measurements performed here are the first to detect both species with good spatial resolution and high sensitivity in the same experiment in flames of C(3) and C(5) fuels. The experimental profiles were compared with results of combustion modeling to reveal details of the formation and consumption of these important combustion molecules, and the investigation was devoted to assist the further understanding of the role of C(2) and of its potential chemical interdependences with CH and other small radicals.

Fast and simple model for atmospheric radiative transfer

NARCIS (Netherlands)

Seidel, F.C.; Kokhanovsky, A.A.; Schaepman, M.E.

2010-01-01

Radiative transfer models (RTMs) are of utmost importance for quantitative remote sensing, especially for compensating atmospheric perturbation. A persistent trade-off exists between approaches that prefer accuracy at the cost of computational complexity, versus those favouring simplicity at the

Quantitative penetration testing with item response theory (extended version)

NARCIS (Netherlands)

Arnold, Florian; Pieters, Wolter; Stoelinga, Mariëlle Ida Antoinette

2013-01-01

Existing penetration testing approaches assess the vulnerability of a system by determining whether certain attack paths are possible in practice. Therefore, penetration testing has thus far been used as a qualitative research method. To enable quantitative approaches to security risk management,

Strategies for MCMC computation in quantitative genetics

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Ibanez, Noelia; Sorensen, Daniel

2006-01-01

Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional but with a sp......Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional...

Laser-induced Breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

International Nuclear Information System (INIS)

Yang, Jianhong; Yi, Cancan; Xu, Jinwu; Ma, Xianghong

2015-01-01

A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine. - Highlights: • Both training and testing samples are considered for analytical lines selection. • The analytical lines are auto-selected based on the built-in characteristics of spectral lines. • The new method can achieve better prediction accuracy and modeling robustness. • Model predictions are given with confidence interval of probabilistic distribution

The relevance of existing health communication models in the email age: An

Science.gov (United States)

Fage-Butler, Antoinette Mary; Jensen, Matilde Nisbeth

2015-01-01

Email communication is being integrated relatively slowly into doctor–patient communication. Patients have expressed enthusiasm for the medium, while doctors are generally more reluctant. As existing health communication models have characteristically assumed the co-presence of doctor and patient and primarily reflect medical practitioners’ perspectives, their suitability in relation to email communication and patients’ perspectives warrants further investigation. Following a two-step process and using the methodology of the integrative literature review, 29 articles from 2004–2014 are analysed with the aim of investigating the advantages and disadvantages of the medium of email from the patient’s perspective. The findings are compared to the health communication models of biomedicine, patient-centeredness, patient education and patient empowerment to investigate these models’ relevance for doctor–patient email communication. Results show that patients identify numerous advantages with email communication, including improved convenience and access, more detailed informational exchanges, greater reflection opportunities, freedom from the medical gaze and the potential to level out power imbalances, as well as a number of primarily medium-related disadvantages. The findings indicate that email can counteract some of the communicative problems associated with biomedicine and suggest the ongoing relevance of aspects of the models of patient empowerment, patient-centeredness and patient education for email communication.

Reproducibility of quantitative planar thallium-201 scintigraphy: quantitative criteria for reversibility of myocardial perfusion defects

International Nuclear Information System (INIS)

Sigal, S.L.; Soufer, R.; Fetterman, R.C.; Mattera, J.A.; Wackers, F.J.

1991-01-01

Fifty-two paired stress/delayed planar 201 TI studies (27 exercise studies, 25 dipyridamole studies) were processed twice by seven technologists to assess inter- and intraobserver variability. The reproducibility was inversely related to the size of 201 Tl perfusion abnormalities. Intraobserver variability was not different between exercise and dipyridamole studies for lesions of similar size. Based upon intraobserver variability, objective quantitative criteria for reversibility of perfusion abnormalities were defined. These objective criteria were tested prospectively in a separate group of 35 201 Tl studies and compared with the subjective interpretation of quantitative circumferential profiles. Overall, exact agreement existed in 78% of images (kappa statistic k = 0.66). We conclude that quantification of planar 201 Tl scans is highly reproducible, with acceptable inter- and intraobserver variability. Objective criteria for lesion reversibility correlated well with analysis by experienced observers

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

Science.gov (United States)

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

2018-01-01

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

Modelling the existing Irish energy-system to identify future energy costs and the maximum wind penetration feasible

DEFF Research Database (Denmark)

Connolly, D.; Lund, Henrik; Mathiesen, Brian Vad

2010-01-01

energy- system to future energy costs by considering future fuel prices, CO2 prices, and different interest rates. The final investigation identifies the maximum wind penetration feasible on the 2007 Irish energy- system from a technical and economic perspective, as wind is the most promising fluctuating...... for the existing Irish energy-system is approximately 30% from both a technical and economic perspective based on 2020 energy prices. Future studies will use the model developed in this study to show that higher wind penetrations can be achieved if the existing energy-system is modified correctly. Finally...... renewable resource available in Ireland. It is concluded that the reference model simulates the Irish energy-system accurately, the annual fuel costs for Ireland’s energy could increase by approximately 58% from 2007 to 2020 if a business-as-usual scenario is followed, and the optimum wind penetration...

A global central banker competency model

Directory of Open Access Journals (Sweden)

David W. Brits

2014-07-01

Full Text Available Orientation: No comprehensive, integrated competency model exists for central bankers. Due to the importance of central banks in the context of the ongoing global financial crisis, it was deemed necessary to design and validate such a model. Research purpose: To craft and validate a comprehensive, integrated global central banker competency model (GCBCM and to assess whether central banks using the GCBCM for training have a higher global influence. Motivation for the study: Limited consensus exists globally about what constitutes a ‘competent’ central banker. A quantitatively validated GCBCM would make a significant contribution to enhancing central banker effectiveness, and also provide a solid foundation for effective people management. Research approach, design and method: A blended quantitative and qualitative research approach was taken. Two sets of hypotheses were tested regarding the relationships between the GCBCM and the training offered, using the model on the one hand, and a central bank’s global influence on the other. Main findings: The GCBCM was generally accepted across all participating central banks globally, although some differences were found between central banks with higher and lower global influence. The actual training offered by central banks in terms of the model, however, is generally limited to technical-functional skills. The GCBCM is therefore at present predominantly aspirational. Significant differences were found regarding the training offered. Practical/managerial implications: By adopting the GCBCM, central banks would be able to develop organisation-specific competency models in order to enhance their organisational capabilities and play their increasingly important global role more effectively. Contribution: A generic conceptual framework for the crafting of a competency model with evaluation criteria was developed. A GCBCM was quantitatively validated.

Need for collection of quantitative distribution data for dosimetry and metabolic modeling

International Nuclear Information System (INIS)

Lathrop, K.A.

1976-01-01

Problems in radiation dose distribution studies in humans are discussed. Data show the effective half-times for 7 Be and 75 Se in the mouse, rat, monkey, dog, and human show no correlation with weight, body surface, or other readily apparent factor that could be used to equate nonhuman and human data. Another problem sometimes encountered in attempting to extrapolate animal data to humans involves equivalent doses of the radiopharmaceutical. A usual human dose for a radiopharmaceutical is 1 ml or 0.017 mg/kg. The same solution injected into a mouse in a convenient volume of 0.1 ml results in a dose of 4 ml/kg or 240 times that received by the human. The effect on whole body retention produced by a dose difference of similar magnitude for selenium in the rat shows the retention is at least twice as great with the smaller amount. With the development of methods for the collection of data throughout the body representing the fractional distribution of radioactivity versus time, not only can more realistic dose estimates be made, but also the tools will be provided for the study of physiological and biochemical interrelationships in the intact subject from which compartmental models may be made which have diagnostic significance. The unique requirement for quantitative biologic data needed for calculation of radiation absorbed doses is the same as the unique scientific contribution that nuclear medicine can make, which is the quantitative in vivo study of physiologic and biochemical processes. The technique involved is not the same as quantitation of a radionuclide image, but is a step beyond

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

Science.gov (United States)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

Deterministic quantitative risk assessment development

Energy Technology Data Exchange (ETDEWEB)

Dawson, Jane; Colquhoun, Iain [PII Pipeline Solutions Business of GE Oil and Gas, Cramlington Northumberland (United Kingdom)

2009-07-01

Current risk assessment practice in pipeline integrity management is to use a semi-quantitative index-based or model based methodology. This approach has been found to be very flexible and provide useful results for identifying high risk areas and for prioritizing physical integrity assessments. However, as pipeline operators progressively adopt an operating strategy of continual risk reduction with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels is becoming evident. Whereas reliability based quantitative risk assessments can be and are routinely carried out on a site-specific basis, they require significant amounts of quantitative data for the results to be meaningful. This need for detailed and reliable data tends to make these methods unwieldy for system-wide risk k assessment applications. This paper describes methods for estimating risk quantitatively through the calibration of semi-quantitative estimates to failure rates for peer pipeline systems. The methods involve the analysis of the failure rate distribution, and techniques for mapping the rate to the distribution of likelihoods available from currently available semi-quantitative programs. By applying point value probabilities to the failure rates, deterministic quantitative risk assessment (QRA) provides greater rigor and objectivity than can usually be achieved through the implementation of semi-quantitative risk assessment results. The method permits a fully quantitative approach or a mixture of QRA and semi-QRA to suit the operator's data availability and quality, and analysis needs. For example, consequence analysis can be quantitative or can address qualitative ranges for consequence categories. Likewise, failure likelihoods can be output as classical probabilities or as expected failure frequencies as required. (author)

Qualitative and quantitative examination of the performance of regional air quality models representing different modeling approaches

International Nuclear Information System (INIS)

Bhumralkar, C.M.; Ludwig, F.L.; Shannon, J.D.; McNaughton, D.

1985-04-01

The calculations of three different air quality models were compared with the best available observations. The comparisons were made without calibrating the models to improve agreement with the observations. Model performance was poor for short averaging times (less than 24 hours). Some of the poor performance can be traced to errors in the input meteorological fields, but error exist on all levels. It should be noted that these models were not originally designed for treating short-term episodes. For short-term episodes, much of the variance in the data can arise from small spatial scale features that tend to be averaged out over longer periods. These small spatial scale features cannot be resolved with the coarse grids that are used for the meteorological and emissions inputs. Thus, it is not surprising that the models performed for the longer averaging times. The models compared were RTM-II, ENAMAP-2 and ACID. (17 refs., 5 figs., 4 tabs

Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

DEFF Research Database (Denmark)

Schoof, Erwin; Erler, Janine

understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

An Evaluation Model of Quantitative and Qualitative Fuzzy Multi-Criteria Decision-Making Approach for Location Selection of Transshipment Ports

Directory of Open Access Journals (Sweden)

Ji-Feng Ding

2013-01-01

Full Text Available The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study.

Application of the thermal efficiency analysis software 'EgWin' at existing power plants

International Nuclear Information System (INIS)

Koda, E.; Takahashi, T.; Nakao, Y.

2008-01-01

'EgWin' is the general purpose software to analyze a thermal efficiency of power system developed in CRIEPI. This software has been used to analyze the existing power generation unit of 30 or more, and the effectiveness has been confirmed. In thermal power plants, it was used for the clarification of the thermal efficiency decrease factor and the quantitative estimation of the influence that each factor gave to the thermal efficiency of the plant. Also it was used for the quantitative estimation of the effect by the operating condition change and the facility remodeling in thermal power, atomic energy, and geothermal power plants. (author)

Modelling a New Product Model on the Basis of an Existing STEP Application Protocol

Directory of Open Access Journals (Sweden)

B.-R. Hoehn

2005-01-01

Full Text Available During the last years a great range of computer aided tools has been generated to support the development process of various products. The goal of a continuous data flow, needed for high efficiency, requires powerful standards for the data exchange. At the FZG (Gear Research Centre of the Technical University of Munich there was a need for a common gear data format for data exchange between gear calculation programs. The STEP standard ISO 10303 was developed for this type of purpose, but a suitable definition of gear data was still missing, even in the Application Protocol AP 214, developed for the design process in the automotive industry. The creation of a new STEP Application Protocol or the extension of existing protocol would be a very time consumpting normative process. So a new method was introduced by FZG. Some very general definitions of an Application Protocol (here AP 214 were used to determine rules for an exact specification of the required kind of data. In this case a product model for gear units was defined based on elements of the AP 214. Therefore no change of the Application Protocol is necessary. Meanwhile the product model for gear units has been published as a VDMA paper and successfully introduced for data exchange within the German gear industry associated with FVA (German Research Organisation for Gears and Transmissions. This method can also be adopted for other applications not yet sufficiently defined by STEP. 

Load-Flow in Multiphase Distribution Networks: Existence, Uniqueness, Non-Singularity, and Linear Models

Energy Technology Data Exchange (ETDEWEB)

Bernstein, Andrey [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wang, Cong [Ecole Polytechnique Federale de Lausanne (EPFL); Le Boudec, Jean-Yves [Ecole Polytechnique Federale de Lausanne (EPFL)

2018-04-06

This paper considers unbalanced multiphase distribution systems with generic topology and different load models, and extends the Z-bus iterative load-flow algorithm based on a fixed-point interpretation of the AC load-flow equations. Explicit conditions for existence and uniqueness of load-flow solutions are presented. These conditions also guarantee convergence of the load-flow algorithm to the unique solution. The proposed methodology is applicable to generic systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. Further, a sufficient condition for the non-singularity of the load-flow Jacobian is proposed. Finally, linear load-flow models are derived, and their approximation accuracy is analyzed. Theoretical results are corroborated through experiments on IEEE test feeders.

Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model.

Science.gov (United States)

Manabe, Sho; Morimoto, Chie; Hamano, Yuya; Fujimoto, Shuntaro; Tamaki, Keiji

2017-01-01

In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software "Kongoh" for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1-4 persons' contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI's contribution in true contributors and non-contributors by using 2-4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI's contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model.

Directory of Open Access Journals (Sweden)

Sho Manabe

Full Text Available In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI from these samples are challenging. In this study, we developed a new open-source software "Kongoh" for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1-4 persons' contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR of a POI's contribution in true contributors and non-contributors by using 2-4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI's contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

Quantitative assessment of changes in landslide risk using a regional scale run-out model

Science.gov (United States)

Hussin, Haydar; Chen, Lixia; Ciurean, Roxana; van Westen, Cees; Reichenbach, Paola; Sterlacchini, Simone

2015-04-01

The risk of landslide hazard continuously changes in time and space and is rarely a static or constant phenomena in an affected area. However one of the main challenges of quantitatively assessing changes in landslide risk is the availability of multi-temporal data for the different components of risk. Furthermore, a truly "quantitative" landslide risk analysis requires the modeling of the landslide intensity (e.g. flow depth, velocities or impact pressures) affecting the elements at risk. Such a quantitative approach is often lacking in medium to regional scale studies in the scientific literature or is left out altogether. In this research we modelled the temporal and spatial changes of debris flow risk in a narrow alpine valley in the North Eastern Italian Alps. The debris flow inventory from 1996 to 2011 and multi-temporal digital elevation models (DEMs) were used to assess the susceptibility of debris flow triggering areas and to simulate debris flow run-out using the Flow-R regional scale model. In order to determine debris flow intensities, we used a linear relationship that was found between back calibrated physically based Flo-2D simulations (local scale models of five debris flows from 2003) and the probability values of the Flow-R software. This gave us the possibility to assign flow depth to a total of 10 separate classes on a regional scale. Debris flow vulnerability curves from the literature and one curve specifically for our case study area were used to determine the damage for different material and building types associated with the elements at risk. The building values were obtained from the Italian Revenue Agency (Agenzia delle Entrate) and were classified per cadastral zone according to the Real Estate Observatory data (Osservatorio del Mercato Immobiliare, Agenzia Entrate - OMI). The minimum and maximum market value for each building was obtained by multiplying the corresponding land-use value (€/msq) with building area and number of floors

Quantitative structure–activity relationship model for amino acids as corrosion inhibitors based on the support vector machine and molecular design

International Nuclear Information System (INIS)

Zhao, Hongxia; Zhang, Xiuhui; Ji, Lin; Hu, Haixiang; Li, Qianshu

2014-01-01

Highlights: • Nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. • Descriptors for QSAR model were selected by principal component analysis. • Binding energy was taken as one of the descriptors for QSAR model. • Acidic solution and protonation of the inhibitor were considered. - Abstract: The inhibition performance of nineteen amino acids was studied by theoretical methods. The affection of acidic solution and protonation of inhibitor were considered in molecular dynamics simulation and the results indicated that the protonated amino-group was not adsorbed on Fe (1 1 0) surface. Additionally, a nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. The correlation coefficient was 0.97 and the root mean square error, the differences between predicted and experimental inhibition efficiencies (%), was 1.48. Furthermore, five new amino acids were theoretically designed and their inhibition efficiencies were predicted by the built QSAR model

Dynamic inundation mapping of Hurricane Harvey flooding in the Houston metro area using hyper-resolution modeling and quantitative image reanalysis

Science.gov (United States)

Noh, S. J.; Lee, J. H.; Lee, S.; Zhang, Y.; Seo, D. J.

2017-12-01

Hurricane Harvey was one of the most extreme weather events in Texas history and left significant damages in the Houston and adjoining coastal areas. To understand better the relative impact to urban flooding of extreme amount and spatial extent of rainfall, unique geography, land use and storm surge, high-resolution water modeling is necessary such that natural and man-made components are fully resolved. In this presentation, we reconstruct spatiotemporal evolution of inundation during Hurricane Harvey using hyper-resolution modeling and quantitative image reanalysis. The two-dimensional urban flood model used is based on dynamic wave approximation and 10 m-resolution terrain data, and is forced by the radar-based multisensor quantitative precipitation estimates. The model domain includes Buffalo, Brays, Greens and White Oak Bayous in Houston. The model is simulated using hybrid parallel computing. To evaluate dynamic inundation mapping, we combine various qualitative crowdsourced images and video footages with LiDAR-based terrain data.

Defect evolution in cosmology and condensed matter quantitative analysis with the velocity-dependent one-scale model

CERN Document Server

Martins, C J A P

2016-01-01

This book sheds new light on topological defects in widely differing systems, using the Velocity-Dependent One-Scale Model to better understand their evolution. Topological defects – cosmic strings, monopoles, domain walls or others - necessarily form at cosmological (and condensed matter) phase transitions. If they are stable and long-lived they will be fossil relics of higher-energy physics. Understanding their behaviour and consequences is a key part of any serious attempt to understand the universe, and this requires modelling their evolution. The velocity-dependent one-scale model is the only fully quantitative model of defect network evolution, and the canonical model in the field. This book provides a review of the model, explaining its physical content and describing its broad range of applicability.

Multivariate characterisation and quantitative structure-property relationship modelling of nitroaromatic compounds

Energy Technology Data Exchange (ETDEWEB)

Joensson, S. [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)], E-mail: sofie.jonsson@nat.oru.se; Eriksson, L.A. [Department of Natural Sciences and Orebro Life Science Center, Orebro University, 701 82 Orebro (Sweden); Bavel, B. van [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)

2008-07-28

A multivariate model to characterise nitroaromatics and related compounds based on molecular descriptors was calculated. Descriptors were collected from literature and through empirical, semi-empirical and density functional theory-based calculations. Principal components were used to describe the distribution of the compounds in a multidimensional space. Four components described 76% of the variation in the dataset. PC1 separated the compounds due to molecular weight, PC2 separated the different isomers, PC3 arranged the compounds according to different functional groups such as nitrobenzoic acids, nitrobenzenes, nitrotoluenes and nitroesters and PC4 differentiated the compounds containing chlorine from other compounds. Quantitative structure-property relationship models were calculated using partial least squares (PLS) projection to latent structures to predict gas chromatographic (GC) retention times and the distribution between the water phase and air using solid-phase microextraction (SPME). GC retention time was found to be dependent on the presence of polar amine groups, electronic descriptors including highest occupied molecular orbital, dipole moments and the melting point. The model of GC retention time was good, but the precision was not precise enough for practical use. An important environmental parameter was measured using SPME, the distribution between headspace (air) and the water phase. This parameter was mainly dependent on Henry's law constant, vapour pressure, log P, content of hydroxyl groups and atmospheric OH rate constant. The predictive capacity of the model substantially improved when recalculating a model using these five descriptors only.

Quantitative Circulatory Physiology: an integrative mathematical model of human physiology for medical education.

Science.gov (United States)

Abram, Sean R; Hodnett, Benjamin L; Summers, Richard L; Coleman, Thomas G; Hester, Robert L

2007-06-01

We have developed Quantitative Circulatory Physiology (QCP), a mathematical model of integrative human physiology containing over 4,000 variables of biological interactions. This model provides a teaching environment that mimics clinical problems encountered in the practice of medicine. The model structure is based on documented physiological responses within peer-reviewed literature and serves as a dynamic compendium of physiological knowledge. The model is solved using a desktop, Windows-based program, allowing students to calculate time-dependent solutions and interactively alter over 750 parameters that modify physiological function. The model can be used to understand proposed mechanisms of physiological function and the interactions among physiological variables that may not be otherwise intuitively evident. In addition to open-ended or unstructured simulations, we have developed 30 physiological simulations, including heart failure, anemia, diabetes, and hemorrhage. Additional stimulations include 29 patients in which students are challenged to diagnose the pathophysiology based on their understanding of integrative physiology. In summary, QCP allows students to examine, integrate, and understand a host of physiological factors without causing harm to patients. This model is available as a free download for Windows computers at http://physiology.umc.edu/themodelingworkshop.

Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

Directory of Open Access Journals (Sweden)

Lorenza A D'Alessandro

2015-04-01

Full Text Available Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF stimulated phosphoinositide-3-kinase (PI3K and mitogen activated protein kinase (MAPK signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

Science.gov (United States)

Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

2015-01-01

A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

Directory of Open Access Journals (Sweden)

Annie eLumen

2015-05-01

Full Text Available A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local

Impact Assessment of Abiotic Resources in LCA: Quantitative Comparison of Selected Characterization Models

DEFF Research Database (Denmark)

Rørbech, Jakob Thaysen; Vadenbo, Carl; Hellweg, Stefanie

2014-01-01

Resources have received significant attention in recent years resulting in development of a wide range of resource depletion indicators within life cycle assessment (LCA). Understanding the differences in assessment principles used to derive these indicators and the effects on the impact assessment...... results is critical for indicator selection and interpretation of the results. Eleven resource depletion methods were evaluated quantitatively with respect to resource coverage, characterization factors (CF), impact contributions from individual resources, and total impact scores. We included 2247...... groups, according to method focus and modeling approach, to aid method selection within LCA....

Combination and Integration of Qualitative and Quantitative Analysis

Directory of Open Access Journals (Sweden)

Philipp Mayring

2001-02-01

Full Text Available In this paper, I am going to outline ways of combining qualitative and quantitative steps of analysis on five levels. On the technical level, programs for the computer-aided analysis of qualitative data offer various combinations. Where the data are concerned, the employment of categories (for instance by using qualitative content analysis allows for combining qualitative and quantitative forms of data analysis. On the individual level, the creation of types and the inductive generalisation of cases allow for proceeding from individual case material to quantitative generalisations. As for research design, different models can be distinguished (preliminary study, generalisation, elaboration, triangulation which combine qualitative and quantitative steps of analysis. Where the logic of research is concerned, it can be shown that an extended process model which combined qualitative and quantitative research can be appropriate and thus lead to an integration of the two approaches. URN: urn:nbn:de:0114-fqs010162

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

Science.gov (United States)

Hahn, Cassidy M.; Iwanowicz, Luke R.; Cornman, Robert S.; Mazik, Patricia M.; Blazer, Vicki S.

2016-01-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

Rapid energy modeling for existing buildings: Testing the business and environmental potential through an experiment at Autodesk

Energy Technology Data Exchange (ETDEWEB)

Deodhar, Aniruddha; Stewart, Emma; Young, Rahul; Khan, Haider

2010-09-15

Retrofits of existing buildings represent a huge, growing market and an opportunity to achieve some of the most sizable and cost-effective carbon reductions in any sector of the economy. More 'zero energy' and 'carbon neutral' buildings are being conceived daily by combining energy efficiency measures with renewable energy technologies. However, for all the progress, the building industry faces technical and cost challenges in identifying the highest potential retrofit candidates. This presentation investigates one potential solution, a technology driven workflow called rapid energy modeling, to accelerate and scale the process of analyzing performance for existing buildings in prioritizing improvements.

Quantitative assessment of manual and robotic microcannulation for eye surgery using new eye model.

Science.gov (United States)

Tanaka, Shinichi; Harada, Kanako; Ida, Yoshiki; Tomita, Kyohei; Kato, Ippei; Arai, Fumihito; Ueta, Takashi; Noda, Yasuo; Sugita, Naohiko; Mitsuishi, Mamoru

2015-06-01

Microcannulation, a surgical procedure for the eye that requires drug injection into a 60-90 µm retinal vein, is difficult to perform manually. Robotic assistance has been proposed; however, its effectiveness in comparison to manual operation has not been quantified. An eye model has been developed to quantify the performance of manual and robotic microcannulation. The eye model, which is implemented with a force sensor and microchannels, also simulates the mechanical constraints of the instrument's movement. Ten subjects performed microcannulation using the model, with and without robotic assistance. The results showed that the robotic assistance was useful for motion stability when the drug was injected, whereas its positioning accuracy offered no advantage. An eye model was used to quantitatively assess the robotic microcannulation performance in comparison to manual operation. This approach could be valid for a better evaluation of surgical robotic assistance. Copyright © 2014 John Wiley & Sons, Ltd.

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

Science.gov (United States)

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advanced quantitative measurement methodology in physics education research

Science.gov (United States)

Wang, Jing

parts. The first part involves the comparison between item response theory (IRT) and classical test theory (CTT). The two theories both provide test item statistics for educational inferences and decisions. The two theories are both applied to Force Concept Inventory data obtained from students enrolled in The Ohio State University. Effort was made to examine the similarity and difference between the two theories, and the possible explanation to the difference. The study suggests that item response theory is more sensitive to the context and conceptual features of the test items than classical test theory. The IRT parameters provide a better measure than CTT parameters for the educational audience to investigate item features. The second part of the dissertation is on the measure of association for binary data. In quantitative assessment, binary data is often encountered because of its simplicity. The current popular measures of association fail under some extremely unbalanced conditions. However, the occurrence of these conditions is not rare in educational data. Two popular association measures, the Pearson's correlation and the tetrachoric correlation are examined. A new method, model based association is introduced, and an educational testing constraint is discussed. The existing popular methods are compared with the model based association measure with and without the constraint. Connections between the value of association and the context and conceptual features of questions are discussed in detail. Results show that all the methods have their advantages and disadvantages. Special attention to the test and data conditions is necessary. The last part of the dissertation is focused on exploratory factor analysis (EFA). The theoretical advantages of EFA are discussed. Typical misunderstanding and misusage of EFA are explored. The EFA is performed on Lawson's Classroom Test of Scientific Reasoning (LCTSR), a widely used assessment on scientific reasoning skills. The

A cascading failure model for analyzing railway accident causation

Science.gov (United States)

Liu, Jin-Tao; Li, Ke-Ping

2018-01-01

In this paper, a new cascading failure model is proposed for quantitatively analyzing the railway accident causation. In the model, the loads of nodes are redistributed according to the strength of the causal relationships between the nodes. By analyzing the actual situation of the existing prevention measures, a critical threshold of the load parameter in the model is obtained. To verify the effectiveness of the proposed cascading model, simulation experiments of a train collision accident are performed. The results show that the cascading failure model can describe the cascading process of the railway accident more accurately than the previous models, and can quantitatively analyze the sensitivities and the influence of the causes. In conclusion, this model can assist us to reveal the latent rules of accident causation to reduce the occurrence of railway accidents.

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

International Nuclear Information System (INIS)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir; He Yan; Xu Jianming

2010-01-01

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

Energy Technology Data Exchange (ETDEWEB)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); He Yan, E-mail: yhe2006@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); Xu Jianming, E-mail: jmxu@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China)

2010-08-15

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

EXISTENCE THEOREM FOR THE PRICES FIXED POINT PROBLEM OF THE OVERLAPPING GENERATIONS MODEL, VIA METRIC SPACES ENDOWED WITH A GRAPH

Directory of Open Access Journals (Sweden)

Magnolia Tilca

2014-10-01

Full Text Available The aim of this paper is to study the existence of the solution for the overlapping generations model, using fixed point theorems in metric spaces endowed with a graph. The overlapping generations model has been introduced and developed by Maurice Allais (1947, Paul Samuelson (1958, Peter Diamond (1965 and so on. The present paper treats the case presented by Edmond (2008 in (Edmond, 2008 for a continuous time. The theorem of existence of the solution for the prices fixed point problem derived from the overlapping generations model gives an approximation of the solution via the graph theory. The tools employed in this study are based on applications of the Jachymski fixed point theorem on metric spaces endowed with a graph (Jachymski, 2008

Report on Integration of Existing Grid Models for N-R HES Interaction Focused on Balancing Authorities for Sub-hour Penalties and Opportunities

International Nuclear Information System (INIS)

McJunkin, Timothy; Epiney, Aaron; Rabiti, Cristian

2017-01-01

This report provides a summary of the effort in the Nuclear-Renewable Hybrid Energy System (N-R HES) project on the level 4 milestone to consider integration of existing grid models into the factors for optimization on shorter time intervals than the existing electric grid models with the Risk Analysis Virtual Environment (RAVEN) and Modelica [1] optimizations and economic analysis that are the focus of the project to date.

Report on Integration of Existing Grid Models for N-R HES Interaction Focused on Balancing Authorities for Sub-hour Penalties and Opportunities

Energy Technology Data Exchange (ETDEWEB)

McJunkin, Timothy [Idaho National Lab. (INL), Idaho Falls, ID (United States); Epiney, Aaron [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-06-01

This report provides a summary of the effort in the Nuclear-Renewable Hybrid Energy System (N-R HES) project on the level 4 milestone to consider integration of existing grid models into the factors for optimization on shorter time intervals than the existing electric grid models with the Risk Analysis Virtual Environment (RAVEN) and Modelica [1] optimizations and economic analysis that are the focus of the project to date.

Development of performance assessment methodology for establishment of quantitative acceptance criteria of near-surface radioactive waste disposal

Energy Technology Data Exchange (ETDEWEB)

Kim, C. R.; Lee, E. Y.; Park, J. W.; Chang, G. M.; Park, H. Y.; Yeom, Y. S. [Korea Hydro and Nuclear Power Co., Ltd., Seoul (Korea, Republic of)

2002-03-15

The contents and the scope of this study are as follows : review of state-of-the-art on the establishment of waste acceptance criteria in foreign near-surface radioactive waste disposal facilities, investigation of radiological assessment methodologies and scenarios, investigation of existing models and computer codes used in performance/safety assessment, development of a performance assessment methodology(draft) to derive quantitatively radionuclide acceptance criteria of domestic near-surface disposal facility, preliminary performance/safety assessment in accordance with the developed methodology.

How to simulate pedestrian behaviors in seismic evacuation for vulnerability reduction of existing buildings

Science.gov (United States)

Quagliarini, Enrico; Bernardini, Gabriele; D'Orazio, Marco

2017-07-01

Understanding and representing how individuals behave in earthquake emergencies would be essentially to assess the impact of vulnerability reduction strategies on existing buildings in seismic areas. In fact, interactions between individuals and the scenario (modified by the earthquake occurrence) are really important in order to understand the possible additional risks for people, especially during the evacuation phase. The current approach is based on "qualitative" aspects, in order to define best practice guidelines for Civil Protection and populations. On the contrary, a "quantitative" description of human response and evacuation motion in similar conditions is urgently needed. Hence, this work defines the rules for pedestrians' earthquake evacuation in urban scenarios, by taking advantages of previous results of real-world evacuation analyses. In particular, motion laws for pedestrians is defined by modifying the Social Force model equation. The proposed model could be used for evaluating individuals' evacuation process and so for defining operative strategies for interferences reduction in critical urban fabric parts (e.g.: interventions on particular buildings, evacuation strategies definition, city parts projects).

Endoscopic skull base training using 3D printed models with pre-existing pathology.

Science.gov (United States)

Narayanan, Vairavan; Narayanan, Prepageran; Rajagopalan, Raman; Karuppiah, Ravindran; Rahman, Zainal Ariff Abdul; Wormald, Peter-John; Van Hasselt, Charles Andrew; Waran, Vicknes

2015-03-01

Endoscopic base of skull surgery has been growing in acceptance in the recent past due to improvements in visualisation and micro instrumentation as well as the surgical maturing of early endoscopic skull base practitioners. Unfortunately, these demanding procedures have a steep learning curve. A physical simulation that is able to reproduce the complex anatomy of the anterior skull base provides very useful means of learning the necessary skills in a safe and effective environment. This paper aims to assess the ease of learning endoscopic skull base exposure and drilling techniques using an anatomically accurate physical model with a pre-existing pathology (i.e., basilar invagination) created from actual patient data. Five models of a patient with platy-basia and basilar invagination were created from the original MRI and CT imaging data of a patient. The models were used as part of a training workshop for ENT surgeons with varying degrees of experience in endoscopic base of skull surgery, from trainees to experienced consultants. The surgeons were given a list of key steps to achieve in exposing and drilling the skull base using the simulation model. They were then asked to list the level of difficulty of learning these steps using the model. The participants found the models suitable for learning registration, navigation and skull base drilling techniques. All participants also found the deep structures to be accurately represented spatially as confirmed by the navigation system. These models allow structured simulation to be conducted in a workshop environment where surgeons and trainees can practice to perform complex procedures in a controlled fashion under the supervision of experts.

Using ISOS consensus test protocols for development of quantitative life test models in ageing of organic solar cells

DEFF Research Database (Denmark)

Kettle, J.; Stoichkov, V.; Kumar, D.

2017-01-01

As Organic Photovoltaic (OPV) development matures, the demand grows for rapid characterisation of degradation and application of Quantitative Accelerated Life Tests (QALT) models to predict and improve reliability. To date, most accelerated testing on OPVs has been conducted using ISOS consensus...

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

Science.gov (United States)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

Science.gov (United States)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Nonstandard Work Schedules and Partnership Quality : Quantitative and Qualitative Findings

NARCIS (Netherlands)

Mills, Melinda; Täht, K

This article questions existing findings and provides new evidence about the consequences of nonstandard work schedules on partnership quality. Using quantitative couple data from The Netherlands Kinship Panel Study (NKPS) (N = 3,016) and semistructured qualitative interviews (N = 34), we found

Prognostic Value of Quantitative Stress Perfusion Cardiac Magnetic Resonance.

Science.gov (United States)

Sammut, Eva C; Villa, Adriana D M; Di Giovine, Gabriella; Dancy, Luke; Bosio, Filippo; Gibbs, Thomas; Jeyabraba, Swarna; Schwenke, Susanne; Williams, Steven E; Marber, Michael; Alfakih, Khaled; Ismail, Tevfik F; Razavi, Reza; Chiribiri, Amedeo

2018-05-01

This study sought to evaluate the prognostic usefulness of visual and quantitative perfusion cardiac magnetic resonance (CMR) ischemic burden in an unselected group of patients and to assess the validity of consensus-based ischemic burden thresholds extrapolated from nuclear studies. There are limited data on the prognostic value of assessing myocardial ischemic burden by CMR, and there are none using quantitative perfusion analysis. Patients with suspected coronary artery disease referred for adenosine-stress perfusion CMR were included (n = 395; 70% male; age 58 ± 13 years). The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction, aborted sudden death, and revascularization after 90 days. Perfusion scans were assessed visually and with quantitative analysis. Cross-validated Cox regression analysis and net reclassification improvement were used to assess the incremental prognostic value of visual or quantitative perfusion analysis over a baseline clinical model, initially as continuous covariates, then using accepted thresholds of ≥2 segments or ≥10% myocardium. After a median 460 days (interquartile range: 190 to 869 days) follow-up, 52 patients reached the primary endpoint. At 2 years, the addition of ischemic burden was found to increase prognostic value over a baseline model of age, sex, and late gadolinium enhancement (baseline model area under the curve [AUC]: 0.75; visual AUC: 0.84; quantitative AUC: 0.85). Dichotomized quantitative ischemic burden performed better than visual assessment (net reclassification improvement 0.043 vs. 0.003 against baseline model). This study was the first to address the prognostic benefit of quantitative analysis of perfusion CMR and to support the use of consensus-based ischemic burden thresholds by perfusion CMR for prognostic evaluation of patients with suspected coronary artery disease. Quantitative analysis provided incremental prognostic value to visual assessment and

Review of existing landfill leachate production models

International Nuclear Information System (INIS)

Khan, T.A.

2000-01-01

The protection of water resources is a fundamental consideration in managing landfill operations. Landfill sites should be designed and operated so as to control leachate production and hence minimize the risk of surface and ground water pollution. A further important development is the use of computer models to estimate the production of leachate from landfill sites. It is revealed from the literature that a number of landfill leachate management model lave been development in recent years. These models allow different engineering schemes to be evaluated and are essential tools for design and operation managements of modern landfills. This paper describes a review of such models mainly focused on their theory, practicability, data requirements, suitability to real situation and usefulness. An evaluation of these models identifies. (author)

Quantitative multimodality imaging in cancer research and therapy.

Science.gov (United States)

Yankeelov, Thomas E; Abramson, Richard G; Quarles, C Chad

2014-11-01

Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.

Quantitative traits and diversification.

Science.gov (United States)

FitzJohn, Richard G

2010-12-01

Quantitative traits have long been hypothesized to affect speciation and extinction rates. For example, smaller body size or increased specialization may be associated with increased rates of diversification. Here, I present a phylogenetic likelihood-based method (quantitative state speciation and extinction [QuaSSE]) that can be used to test such hypotheses using extant character distributions. This approach assumes that diversification follows a birth-death process where speciation and extinction rates may vary with one or more traits that evolve under a diffusion model. Speciation and extinction rates may be arbitrary functions of the character state, allowing much flexibility in testing models of trait-dependent diversification. I test the approach using simulated phylogenies and show that a known relationship between speciation and a quantitative character could be recovered in up to 80% of the cases on large trees (500 species). Consistent with other approaches, detecting shifts in diversification due to differences in extinction rates was harder than when due to differences in speciation rates. Finally, I demonstrate the application of QuaSSE to investigate the correlation between body size and diversification in primates, concluding that clade-specific differences in diversification may be more important than size-dependent diversification in shaping the patterns of diversity within this group.

Quantitative self-assembly prediction yields targeted nanomedicines

Science.gov (United States)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

National electricity planning in settings with low pre-existing grid coverage: Development of a spatial model and case study of Kenya

International Nuclear Information System (INIS)

Parshall, Lily; Pillai, Dana; Mohan, Shashank; Sanoh, Aly; Modi, Vijay

2009-01-01

We develop a spatial electricity planning model to guide grid expansion in countries with low pre-existing electricity coverage. The model can be used to rapidly estimate connection costs and compare different regions and communities. Inputs that are modeled include electricity demand, costs, and geographic characteristics. The spatial nature of the model permits accurate representation of the existing electricity network and population distribution, which form the basis for future expansion decisions. The methodology and model assumptions are illustrated using country-specific data from Kenya. Results show that under most geographic conditions, extension of the national grid is less costly than off-grid options. Based on realistic penetration rates for Kenya, we estimate an average connection cost of $1900 per household, with lower-cost connection opportunities around major cities and in denser rural regions. In areas with an adequate pre-existing medium-voltage backbone, we estimate that over 30% of households could be connected for less than $1000 per connection through infilling. The penetration rate, an exogenous factor chosen by electricity planners, is found to have a large effect on household connection costs, often outweighing socio-economic and spatial factors such as inter-household distance, per-household demand, and proximity to the national grid.

A Quantitative Study of Faculty Perceptions and Attitudes on Asynchronous Virtual Teamwork Using the Technology Acceptance Model

Science.gov (United States)

Wolusky, G. Anthony

2016-01-01

This quantitative study used a web-based questionnaire to assess the attitudes and perceptions of online and hybrid faculty towards student-centered asynchronous virtual teamwork (AVT) using the technology acceptance model (TAM) of Davis (1989). AVT is online student participation in a team approach to problem-solving culminating in a written…

Plutonium chemistry: a synthesis of experimental data and a quantitative model for plutonium oxide solubility

International Nuclear Information System (INIS)

Haschke, J.M.; Oversby, V.M.

2002-01-01

The chemistry of plutonium is important for assessing potential behavior of radioactive waste under conditions of geologic disposal. This paper reviews experimental data on dissolution of plutonium oxide solids, describes a hybrid kinetic-equilibrium model for predicting steady-state Pu concentrations, and compares laboratory results with predicted Pu concentrations and oxidation-state distributions. The model is based on oxidation of PuO 2 by water to produce PuO 2+x , an oxide that can release Pu(V) to solution. Kinetic relationships between formation of PuO 2+x , dissolution of Pu(V), disproportionation of Pu(V) to Pu(IV) and Pu(VI), and reduction of Pu(VI) are given and used in model calculations. Data from tests of pyrochemical salt wastes in brines are discussed and interpreted using the conceptual model. Essential data for quantitative modeling at conditions relevant to nuclear waste repositories are identified and laboratory experiments to determine rate constants for use in the model are discussed

Model developments for quantitative estimates of the benefits of the signals on nuclear power plant availability and economics

International Nuclear Information System (INIS)

Seong, Poong Hyun

1993-01-01

A novel framework for quantitative estimates of the benefits of signals on nuclear power plant availability and economics has been developed in this work. The models developed in this work quantify how the perfect signals affect the human operator's success in restoring the power plant to the desired state when it enters undesirable transients. Also, the models quantify the economic benefits of these perfect signals. The models have been applied to the condensate feedwater system of the nuclear power plant for demonstration. (Author)

Quantitative assessment of biological impact using transcriptomic data and mechanistic network models

International Nuclear Information System (INIS)

Thomson, Ty M.; Sewer, Alain; Martin, Florian; Belcastro, Vincenzo; Frushour, Brian P.; Gebel, Stephan; Park, Jennifer; Schlage, Walter K.; Talikka, Marja; Vasilyev, Dmitry M.; Westra, Jurjen W.; Hoeng, Julia; Peitsch, Manuel C.

2013-01-01

Exposure to biologically active substances such as therapeutic drugs or environmental toxicants can impact biological systems at various levels, affecting individual molecules, signaling pathways, and overall cellular processes. The ability to derive mechanistic insights from the resulting system responses requires the integration of experimental measures with a priori knowledge about the system and the interacting molecules therein. We developed a novel systems biology-based methodology that leverages mechanistic network models and transcriptomic data to quantitatively assess the biological impact of exposures to active substances. Hierarchically organized network models were first constructed to provide a coherent framework for investigating the impact of exposures at the molecular, pathway and process levels. We then validated our methodology using novel and previously published experiments. For both in vitro systems with simple exposure and in vivo systems with complex exposures, our methodology was able to recapitulate known biological responses matching expected or measured phenotypes. In addition, the quantitative results were in agreement with experimental endpoint data for many of the mechanistic effects that were assessed, providing further objective confirmation of the approach. We conclude that our methodology evaluates the biological impact of exposures in an objective, systematic, and quantifiable manner, enabling the computation of a systems-wide and pan-mechanistic biological impact measure for a given active substance or mixture. Our results suggest that various fields of human disease research, from drug development to consumer product testing and environmental impact analysis, could benefit from using this methodology. - Highlights: • The impact of biologically active substances is quantified at multiple levels. • The systems-level impact integrates the perturbations of individual networks. • The networks capture the relationships between

Twelve recommendations for integrating existing systematic reviews into new reviews: EPC guidance.

Science.gov (United States)

Robinson, Karen A; Chou, Roger; Berkman, Nancy D; Newberry, Sydne J; Fu, Rongwei; Hartling, Lisa; Dryden, Donna; Butler, Mary; Foisy, Michelle; Anderson, Johanna; Motu'apuaka, Makalapua; Relevo, Rose; Guise, Jeanne-Marie; Chang, Stephanie

2016-02-01

As time and cost constraints in the conduct of systematic reviews increase, the need to consider the use of existing systematic reviews also increases. We developed guidance on the integration of systematic reviews into new reviews. A workgroup of methodologists from Evidence-based Practice Centers developed consensus-based recommendations. Discussions were informed by a literature scan and by interviews with organizations that conduct systematic reviews. Twelve recommendations were developed addressing selecting reviews, assessing risk of bias, qualitative and quantitative synthesis, and summarizing and assessing body of evidence. We provide preliminary guidance for an efficient and unbiased approach to integrating existing systematic reviews with primary studies in a new review. Copyright © 2016 Elsevier Inc. All rights reserved.

Cracking anxiety in the mouse : a quantitative (epi)genetic approach

NARCIS (Netherlands)

Labots, M.

2017-01-01

The aim of this thesis was to improve existing methodologies and apply genetic strategies in order to identify (main-effect, epistatic, multiple and pleiotropic) quantitative trait loci and to decipher functional candidate genes for anxiety-related behavior and baseline blood plasma total

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Energy Technology Data Exchange (ETDEWEB)

Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

2012-05-15

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

International Nuclear Information System (INIS)

Ghasemi, Jahan B.; Zolfonoun, Ehsan

2012-01-01

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

OpenAIRE

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-01-01

Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

Quantitative acid-base physiology using the Stewart model. Does it improve our understanding of what is really wrong?

NARCIS (Netherlands)

Derksen, R.; Scheffer, G.J.; Hoeven, J.G. van der

2006-01-01

Traditional theories of acid-base balance are based on the Henderson-Hasselbalch equation to calculate proton concentration. The recent revival of quantitative acid-base physiology using the Stewart model has increased our understanding of complicated acid-base disorders, but has also led to several

Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships (MCBIOS)

Science.gov (United States)

Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships Jie Liu1,2, Richard Judson1, Matthew T. Martin1, Huixiao Hong3, Imran Shah1 1National Center for Computational Toxicology (NCCT), US EPA, RTP, NC...

Ontological Proofs of Existence and Non-Existence

Czech Academy of Sciences Publication Activity Database

Hájek, Petr

2008-01-01

Roč. 90, č. 2 (2008), s. 257-262 ISSN 0039-3215 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : ontological proofs * existence * non-existence * Gödel * Caramuel Subject RIV: BA - General Mathematics

Initiation of microporosity from pre-existing bubbles: a computational study

International Nuclear Information System (INIS)

Sasikumar, Roschen; Savithri, S; Walker, Michael J; Sundarraj, Suresh

2008-01-01

Representation of the pore nucleation phenomenon has been a weak link in models of microporosity formation in castings. Porosity models in the literature use different criteria for the stage at which a pore first appears. Pre-existence of microbubbles in the melt has been proposed by many as the reason for non-classical nucleation of pores at low supersaturations. However, nucleation of pores from pre-existing bubbles has not been explicitly modeled or included in models of microporosity. In this paper we present a model for initiation of hydrogen porosity by diffusion of hydrogen into pre-existing bubbles containing insoluble gas. We find that small pre-existing microbubbles have a quiescent stage of very slow growth until a critical supersaturation is built up, followed by a stage of rapid growth that exhausts most of the built-up supersaturation. After that the growth takes place at a small supersaturation until the end of solidification. The phenomenon is analogous to the undercooling and recalescence that occurs during nucleation and growth of solid grains

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays.

Science.gov (United States)

Hahn, Cassidy M; Iwanowicz, Luke R; Cornman, Robert S; Mazik, Patricia M; Blazer, Vicki S

2016-12-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest. Published by Elsevier Inc.

Supporting the Constructive Use of Existing Hydrological Models in Participatory Settings: a Set of "Rules of the Game"

Directory of Open Access Journals (Sweden)

Pieter W. G. Bots

2011-06-01

Full Text Available When hydrological models are used in support of water management decisions, stakeholders often contest these models because they perceive certain aspects to be inadequately addressed. A strongly contested model may be abandoned completely, even when stakeholders could potentially agree on the validity of part of the information it can produce. The development of a new model is costly, and the results may be contested again. We consider how existing hydrological models can be used in a policy process so as to benefit from both hydrological knowledge and the perspectives and local knowledge of stakeholders. We define a code of conduct as a set of "rules of the game" that we base on a case study of developing a water management plan for a Natura 2000 site in the Netherlands. We propose general rules for agenda management and information sharing, and more specific rules for model use and option development. These rules structure the interactions among actors, help them to explicitly acknowledge uncertainties, and prevent expertise from being neglected or overlooked. We designed the rules to favor openness, protection of core stakeholder values, the use of relevant substantive knowledge, and the momentum of the process. We expect that these rules, although developed on the basis of a water-management issue, can also be applied to support the use of existing computer models in other policy domains. As rules will shape actions only when they are constantly affirmed by actors, we expect that the rules will become less useful in an "unruly" social environment where stakeholders constantly challenge the proceedings.

Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images.

Science.gov (United States)

Echegaray, Sebastian; Bakr, Shaimaa; Rubin, Daniel L; Napel, Sandy

2017-10-06

The aim of this study was to develop an open-source, modular, locally run or server-based system for 3D radiomics feature computation that can be used on any computer system and included in existing workflows for understanding associations and building predictive models between image features and clinical data, such as survival. The QIFE exploits various levels of parallelization for use on multiprocessor systems. It consists of a managing framework and four stages: input, pre-processing, feature computation, and output. Each stage contains one or more swappable components, allowing run-time customization. We benchmarked the engine using various levels of parallelization on a cohort of CT scans presenting 108 lung tumors. Two versions of the QIFE have been released: (1) the open-source MATLAB code posted to Github, (2) a compiled version loaded in a Docker container, posted to DockerHub, which can be easily deployed on any computer. The QIFE processed 108 objects (tumors) in 2:12 (h/mm) using 1 core, and 1:04 (h/mm) hours using four cores with object-level parallelization. We developed the Quantitative Image Feature Engine (QIFE), an open-source feature-extraction framework that focuses on modularity, standards, parallelism, provenance, and integration. Researchers can easily integrate it with their existing segmentation and imaging workflows by creating input and output components that implement their existing interfaces. Computational efficiency can be improved by parallelizing execution at the cost of memory usage. Different parallelization levels provide different trade-offs, and the optimal setting will depend on the size and composition of the dataset to be processed.

Global existence of periodic solutions on a simplified BAM neural network model with delays

International Nuclear Information System (INIS)

Zheng Baodong; Zhang Yazhuo; Zhang Chunrui

2008-01-01

A simplified n-dimensional BAM neural network model with delays is considered. Some results of Hopf bifurcations occurring at the zero equilibrium as the delay increases are exhibited. Global existence of periodic solutions are established using a global Hopf bifurcation result of Wu [Wu J. Symmetric functional-differential equations and neural networks with memory. Trans Am Math Soc 1998;350:4799-838], and a Bendixson criterion for higher dimensional ordinary differential equations due to Li and Muldowney [Li MY, Muldowney J. On Bendixson's criterion. J Differ Equations 1994;106:27-39]. Finally, computer simulations are performed to illustrate the analytical results found

Quantitative evaluation and modeling of two-dimensional neovascular network complexity: the surface fractal dimension

International Nuclear Information System (INIS)

Grizzi, Fabio; Russo, Carlo; Colombo, Piergiuseppe; Franceschini, Barbara; Frezza, Eldo E; Cobos, Everardo; Chiriva-Internati, Maurizio

2005-01-01

Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects. This paper introduces the surface fractal dimension (D s ) as a numerical index of the two-dimensional (2-D) geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution. We show that D s significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth. Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth

Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

Science.gov (United States)

Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

2017-10-01

The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

Science.gov (United States)

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Non Linear Programming (NLP formulation for quantitative modeling of protein signal transduction pathways.

Directory of Open Access Journals (Sweden)

Alexander Mitsos

Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Absolute quantitation of myocardial blood flow with {sup 201}Tl and dynamic SPECT in canine: optimisation and validation of kinetic modelling

Energy Technology Data Exchange (ETDEWEB)

Iida, Hidehiro; Kim, Kyeong-Min; Nakazawa, Mayumi; Sohlberg, Antti; Zeniya, Tsutomu; Hayashi, Takuya; Watabe, Hiroshi [National Cardiovascular Center Research Institute, Department of Investigative Radiology, Suita City, Osaka (Japan); Eberl, Stefan [National Cardiovascular Center Research Institute, Department of Investigative Radiology, Suita City, Osaka (Japan); Royal Prince Alfred Hospital, PET and Nuclear Medicine Department, Camperdown, NSW (Australia); Tamura, Yoshikazu [Akita Kumiai General Hospital, Department of Cardiology, Akita City (Japan); Ono, Yukihiko [Akita Research Institute of Brain, Akita City (Japan)

2008-05-15

{sup 201}Tl has been extensively used for myocardial perfusion and viability assessment. Unlike {sup 99m}Tc-labelled agents, such as {sup 99m}Tc-sestamibi and {sup 99m}Tc-tetrofosmine, the regional concentration of {sup 201}Tl varies with time. This study is intended to validate a kinetic modelling approach for in vivo quantitative estimation of regional myocardial blood flow (MBF) and volume of distribution of {sup 201}Tl using dynamic SPECT. Dynamic SPECT was carried out on 20 normal canines after the intravenous administration of {sup 201}Tl using a commercial SPECT system. Seven animals were studied at rest, nine during adenosine infusion, and four after beta-blocker administration. Quantitative images were reconstructed with a previously validated technique, employing OS-EM with attenuation-correction, and transmission-dependent convolution subtraction scatter correction. Measured regional time-activity curves in myocardial segments were fitted to two- and three-compartment models. Regional MBF was defined as the influx rate constant (K{sub 1}) with corrections for the partial volume effect, haematocrit and limited first-pass extraction fraction, and was compared with that determined from radio-labelled microspheres experiments. Regional time-activity curves responded well to pharmacological stress. Quantitative MBF values were higher with adenosine and decreased after beta-blocker compared to a resting condition. MBFs obtained with SPECT (MBF{sub SPECT}) correlated well with the MBF values obtained by the radio-labelled microspheres (MBF{sub MS}) (MBF{sub SPECT} = -0.067 + 1.042 x MBF{sub MS}, p < 0.001). The three-compartment model provided better fit than the two-compartment model, but the difference in MBF values between the two methods was small and could be accounted for with a simple linear regression. Absolute quantitation of regional MBF, for a wide physiological flow range, appears to be feasible using {sup 201}Tl and dynamic SPECT. (orig.)

Credit Institutions Management Evaluation using Quantitative Methods

Directory of Open Access Journals (Sweden)

Nicolae Dardac

2006-02-01

Full Text Available Credit institutions supervising mission by state authorities is mostly assimilated with systemic risk prevention. In present, the mission is orientated on analyzing the risk profile of the credit institutions, the mechanism and existing systems as management tools providing to bank rules the proper instruments to avoid and control specific bank risks. Rating systems are sophisticated measurement instruments which are capable to assure the above objectives, such as success in banking risk management. The management quality is one of the most important elements from the set of variables used in the quoting process in credit operations. Evaluation of this quality is – generally speaking – fundamented on quantitative appreciations which can induce subjectivism and heterogeneity in quotation. The problem can be solved by using, complementary, quantitative technics such us DEA (Data Envelopment Analysis.

Quantitative Model for Supply Chain Visibility: Process Capability Perspective

Directory of Open Access Journals (Sweden)

Youngsu Lee

2016-01-01

Full Text Available Currently, the intensity of enterprise competition has increased as a result of a greater diversity of customer needs as well as the persistence of a long-term recession. The results of competition are becoming severe enough to determine the survival of company. To survive global competition, each firm must focus on achieving innovation excellence and operational excellence as core competency for sustainable competitive advantage. Supply chain management is now regarded as one of the most effective innovation initiatives to achieve operational excellence, and its importance has become ever more apparent. However, few companies effectively manage their supply chains, and the greatest difficulty is in achieving supply chain visibility. Many companies still suffer from a lack of visibility, and in spite of extensive research and the availability of modern technologies, the concepts and quantification methods to increase supply chain visibility are still ambiguous. Based on the extant researches in supply chain visibility, this study proposes an extended visibility concept focusing on a process capability perspective and suggests a more quantitative model using Z score in Six Sigma methodology to evaluate and improve the level of supply chain visibility.

Static Universe model existing due to the matter-dark energy coupling

International Nuclear Information System (INIS)

Cabo Bizet, A.; Cabo Montes de Oca, A.

2007-08-01

The work investigates a static, isotropic and almost homogeneous Universe containing a real scalar field modeling the Dark-Energy (quintaessence) interacting with pressureless matter. It is argued that the interaction between matter and the Dark Energy, is essential for the very existence of the considered solution. Assuming the possibility that Dark-Energy can be furnished by the Dilaton (a scalar field reflecting the condensation of string states with zero angular momentum) we fix the value of scalar field at the origin to the Planck scale. It became possible to fix the ratio of the amount of Dark Energy to matter energy, in the currently estimated value (0.7)/0.3 and also the observed magnitude of the Hubble constant. The small value of the mass for the scalar field chosen for fixing the above ratio and Hubble effect strength, results to be of the order of 10 -29 cm -1 , a small value which seems to be compatible with the zero mass of the Dilaton in the lowest approximations. (author)

Assessment of managed aquifer recharge potential using ensembles of local models.

Science.gov (United States)

Smith, Anthony J; Pollock, Daniel W

2012-01-01

A simple quantitative approach for assessing the artificial recharge potential of large regions using spatial ensembles of local models is proposed. The method extends existing qualitative approaches and enables rapid assessments within a programmable environment. Spatial discretization of a water resource region into continuous local domains allows simple local models to be applied independently in each domain using lumped parameters. The ensemble results can be analyzed directly or combined with other quantitative and thematic information and visualized as regional suitability maps. A case study considers the hydraulic potential for surface infiltration across a large water resource region using a published analytic model for basin recharge. The model solution was implemented within a geographic information system and evaluated independently in >21,000 local domains using lumped parameters derived from existing regional datasets. Computer execution times to run the whole ensemble and process the results were in the order of a few minutes. Relevant aspects of the case study results and general conclusions concerning the utility and limitations of the method are discussed. © 2011, CSIRO. Ground Water © 2011, National Ground Water Association.

Quantitative predictions from competition theory with incomplete information on model parameters tested against experiments across diverse taxa

OpenAIRE

Fort, Hugo

2017-01-01

We derive an analytical approximation for making quantitative predictions for ecological communities as a function of the mean intensity of the inter-specific competition and the species richness. This method, with only a fraction of the model parameters (carrying capacities and competition coefficients), is able to predict accurately empirical measurements covering a wide variety of taxa (algae, plants, protozoa).

Catching the Right Wave: Evaluating Wave Energy Resources and Potential Compatibility with Existing Marine and Coastal Uses

Science.gov (United States)

Kim, Choong-Ki; Toft, Jodie E.; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D.; Ruckelshaus, Marry H.; Arkema, Katie K.; Guannel, Gregory; Wood, Spencer A.; Bernhardt, Joanna R.; Tallis, Heather; Plummer, Mark L.; Halpern, Benjamin S.; Pinsky, Malin L.; Beck, Michael W.; Chan, Francis; Chan, Kai M. A.; Levin, Phil S.; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses. PMID:23144824

Catching the right wave: evaluating wave energy resources and potential compatibility with existing marine and coastal uses.

Science.gov (United States)

Kim, Choong-Ki; Toft, Jodie E; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D; Ruckelshaus, Marry H; Arkema, Katie K; Guannel, Gregory; Wood, Spencer A; Bernhardt, Joanna R; Tallis, Heather; Plummer, Mark L; Halpern, Benjamin S; Pinsky, Malin L; Beck, Michael W; Chan, Francis; Chan, Kai M A; Levin, Phil S; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses.

[Quantitative models between canopy hyperspectrum and its component features at apple tree prosperous fruit stage].

Science.gov (United States)

Wang, Ling; Zhao, Geng-xing; Zhu, Xi-cun; Lei, Tong; Dong, Fang

2010-10-01

Hyperspectral technique has become the basis of quantitative remote sensing. Hyperspectrum of apple tree canopy at prosperous fruit stage consists of the complex information of fruits, leaves, stocks, soil and reflecting films, which was mostly affected by component features of canopy at this stage. First, the hyperspectrum of 18 sample apple trees with reflecting films was compared with that of 44 trees without reflecting films. It could be seen that the impact of reflecting films on reflectance was obvious, so the sample trees with ground reflecting films should be separated to analyze from those without ground films. Secondly, nine indexes of canopy components were built based on classified digital photos of 44 apple trees without ground films. Thirdly, the correlation between the nine indexes and canopy reflectance including some kinds of conversion data was analyzed. The results showed that the correlation between reflectance and the ratio of fruit to leaf was the best, among which the max coefficient reached 0.815, and the correlation between reflectance and the ratio of leaf was a little better than that between reflectance and the density of fruit. Then models of correlation analysis, linear regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the hyperspectral reflectance and the ratio of fruit to leaf with the softwares of DPS and LIBSVM. It was feasible that all of the four models in 611-680 nm characteristic band are feasible to be used to predict, while the model accuracy of BP neural network and support vector regression was better than one-variable linear regression and multi-variable regression, and the accuracy of support vector regression model was the best. This study will be served as a reliable theoretical reference for the yield estimation of apples based on remote sensing data.

Exploring alternative models for sex-linked quantitative trait loci in outbred populations: application to an iberian x landrace pig intercross.

OpenAIRE

Pérez-Enciso, Miguel; Clop, Alex; Folch, Josep M; Sánchez, Armand; Oliver, Maria A; Ovilo, Cristina; Barragán, C; Varona, Luis; Noguera, José L

2002-01-01

We present a very flexible method that allows us to analyze X-linked quantitative trait loci (QTL) in crosses between outbred lines. The dosage compensation phenomenon is modeled explicitly in an identity-by-descent approach. A variety of models can be fitted, ranging from considering alternative fixed alleles within the founder breeds to a model where the only genetic variation is within breeds, as well as mixed models. Different genetic variances within each founder breed can be estimated. ...

The quantitative imaging network: the role of quantitative imaging in radiation therapy

International Nuclear Information System (INIS)

Tandon, Pushpa; Nordstrom, Robert J.; Clark, Laurence

2014-01-01

The potential value of modern medical imaging methods has created a need for mechanisms to develop, translate and disseminate emerging imaging technologies and, ideally, to quantitatively correlate those with other related laboratory methods, such as the genomics and proteomics analyses required to support clinical decisions. One strategy to meet these needs efficiently and cost effectively is to develop an international network to share and reach consensus on best practices, imaging protocols, common databases, and open science strategies, and to collaboratively seek opportunities to leverage resources wherever possible. One such network is the Quantitative Imaging Network (QIN) started by the National Cancer Institute, USA. The mission of the QIN is to improve the role of quantitative imaging for clinical decision making in oncology by the development and validation of data acquisition, analysis methods, and other quantitative imaging tools to predict or monitor the response to drug or radiation therapy. The network currently has 24 teams (two from Canada and 22 from the USA) and several associate members, including one from Tata Memorial Centre, Mumbai, India. Each QIN team collects data from ongoing clinical trials and develops software tools for quantitation and validation to create standards for imaging research, and for use in developing models for therapy response prediction and measurement and tools for clinical decision making. The members of QIN are addressing a wide variety of cancer problems (Head and Neck cancer, Prostrate, Breast, Brain, Lung, Liver, Colon) using multiple imaging modalities (PET, CT, MRI, FMISO PET, DW-MRI, PET-CT). (author)

Thermodynamic modelling of shape memory behaviour: some examples

International Nuclear Information System (INIS)

Stalmans, R.; Humbeeck, J. van; Delaey, L.

1995-01-01

This paper gives a general view of a recently developed thermodynamic model of the thermoelastic martensitic transformation. Unlike existing empirical, mathematical or thermodynamic models, this generalised thermodynamic model can be used to understand and describe quantitatively the overall thermomechanical behaviour of polycrystalline shape memory alloys. Important points of difference between this and previous thermodynamic models are that the contributions of the stored elastic energy and of the crystal defects are also included. In addition, the mathematical approach and the assumptions in this model are selected in such a way that the calculations yield close approximations of the real behaviour and that the final mathematical equations are relatively simple. Several illustrations indicate that this model, in contrast to other models, can be used to understand the shape memory behaviour of complex cases. As an example of quantitative calculations, it is shown that this modelling can be an effective tool in the ''design'' of multifunctional materials consisting of shape memory elements embedded in matrix materials. (orig.)

40 CFR Table 4 to Subpart Bbbb of... - Model Rule-Class II Emission Limits for Existing Small Municipal Waste Combustion Unit a

Science.gov (United States)

2010-07-01

... Existing Small Municipal Waste Combustion Unit a 4 Table 4 to Subpart BBBB of Part 60 Protection of... NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste Combustion... Part 60—Model Rule—Class II Emission Limits for Existing Small Municipal Waste Combustion Unit a For...

Interdiffusion of the aluminum magnesium system. Quantitative analysis and numerical model; Interdiffusion des Aluminium-Magnesium-Systems. Quantitative Analyse und numerische Modellierung

Energy Technology Data Exchange (ETDEWEB)

Seperant, Florian

2012-03-21

Aluminum coatings are a promising approach to protect magnesium alloys against corrosion and thereby making them accessible to a variety of technical applications. Thermal treatment enhances the adhesion of the aluminium coating on magnesium by interdiffusion. For a deeper understanding of the diffusion process at the interface, a quantitative description of the Al-Mg system is necessary. On the basis of diffusion experiments with infinite reservoirs of aluminum and magnesium, the interdiffusion coefficients of the intermetallic phases of the Al-Mg-system are calculated with the Sauer-Freise method for the first time. To solve contradictions in the literature concerning the intrinsic diffusion coefficients, the possibility of a bifurcation of the Kirkendall plane is considered. Furthermore, a physico-chemical description of interdiffusion is provided to interpret the observed phase transitions. The developed numerical model is based on a temporally varied discretization of the space coordinate. It exhibits excellent quantitative agreement with the experimentally measured concentration profile. This confirms the validity of the obtained diffusion coefficients. Moreover, the Kirkendall shift in the Al-Mg system is simulated for the first time. Systems with thin aluminum coatings on magnesium also exhibit a good correlation between simulated and experimental concentration profiles. Thus, the diffusion coefficients are also valid for Al-coated systems. Hence, it is possible to derive parameters for a thermal treatment by simulation, resulting in an optimized modification of the magnesium surface for technical applications.

Improving Perovskite Solar Cells: Insights From a Validated Device Model

NARCIS (Netherlands)

Sherkar, Tejas S.; Momblona, Cristina; Gil-Escrig, Lidon; Bolink, Henk J.; Koster, L. Jan Anton

2017-01-01

To improve the efficiency of existing perovskite solar cells (PSCs), a detailed understanding of the underlying device physics during their operation is essential. Here, a device model has been developed and validated that describes the operation of PSCs and quantitatively explains the role of

How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis.

Science.gov (United States)

Drasdo, Dirk; Hoehme, Stefan; Hengstler, Jan G

2014-10-01

From the more than 100 liver diseases described, many of those with high incidence rates manifest themselves by histopathological changes, such as hepatitis, alcoholic liver disease, fatty liver disease, fibrosis, and, in its later stages, cirrhosis, hepatocellular carcinoma, primary biliary cirrhosis and other disorders. Studies of disease pathogeneses are largely based on integrating -omics data pooled from cells at different locations with spatial information from stained liver structures in animal models. Even though this has led to significant insights, the complexity of interactions as well as the involvement of processes at many different time and length scales constrains the possibility to condense disease processes in illustrations, schemes and tables. The combination of modern imaging modalities with image processing and analysis, and mathematical models opens up a promising new approach towards a quantitative understanding of pathologies and of disease processes. This strategy is discussed for two examples, ammonia metabolism after drug-induced acute liver damage, and the recovery of liver mass as well as architecture during the subsequent regeneration process. This interdisciplinary approach permits integration of biological mechanisms and models of processes contributing to disease progression at various scales into mathematical models. These can be used to perform in silico simulations to promote unravelling the relation between architecture and function as below illustrated for liver regeneration, and bridging from the in vitro situation and animal models to humans. In the near future novel mechanisms will usually not be directly elucidated by modelling. However, models will falsify hypotheses and guide towards the most informative experimental design. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Using the ACT-R architecture to specify 39 quantitative process models of decision making

NARCIS (Netherlands)

Marewski, Julian N.; Mehlhorn, Katja

Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a

Preclinical Magnetic Resonance Fingerprinting (MRF) at 7 T: Effective Quantitative Imaging for Rodent Disease Models

Science.gov (United States)

Gao, Ying; Chen, Yong; Ma, Dan; Jiang, Yun; Herrmann, Kelsey A.; Vincent, Jason A.; Dell, Katherine M.; Drumm, Mitchell L.; Brady-Kalnay, Susann M.; Griswold, Mark A.; Flask, Chris A.; Lu, Lan

2015-01-01

High field, preclinical magnetic resonance imaging (MRI) scanners are now commonly used to quantitatively assess disease status and efficacy of novel therapies in a wide variety of rodent models. Unfortunately, conventional MRI methods are highly susceptible to respiratory and cardiac motion artifacts resulting in potentially inaccurate and misleading data. We have developed an initial preclinical, 7.0 T MRI implementation of the highly novel Magnetic Resonance Fingerprinting (MRF) methodology that has been previously described for clinical imaging applications. The MRF technology combines a priori variation in the MRI acquisition parameters with dictionary-based matching of acquired signal evolution profiles to simultaneously generate quantitative maps of T1 and T2 relaxation times and proton density. This preclinical MRF acquisition was constructed from a Fast Imaging with Steady-state Free Precession (FISP) MRI pulse sequence to acquire 600 MRF images with both evolving T1 and T2 weighting in approximately 30 minutes. This initial high field preclinical MRF investigation demonstrated reproducible and differentiated estimates of in vitro phantoms with different relaxation times. In vivo preclinical MRF results in mouse kidneys and brain tumor models demonstrated an inherent resistance to respiratory motion artifacts as well as sensitivity to known pathology. These results suggest that MRF methodology may offer the opportunity for quantification of numerous MRI parameters for a wide variety of preclinical imaging applications. PMID:25639694

Implementation of partnership management model of SMK (Vocational High School) with existing industries in mechanical engineering expertise in Central Java

Science.gov (United States)

Sumbodo, Wirawan; Pardjono, Samsudi, Rahadjo, Winarno Dwi

2018-03-01

This study aims to determine the existing conditions of implementation of partnership management model of SMK with the industry on the mechanical engineering expertise in Central Java. The method used is descriptive analysis. The research result shows that the implementation of partnership management model of SMK based on new existing industry produces ready graduates of 62.5% which belongs to low category, although the partnership program of SMK with the industry is done well with the average score of 3.17. As many as 37.5% of SMK graduates of Mechanical Engineering Expertise Program choose to continue their studies or to be an entrepreneur. It is expected that the partnership model of SMK with the industry can be developed into a reference for government policy in developing SMK that is able to produce graduates who are ready to work according to the needs of partner industry.

[A new method of processing quantitative PCR data].

Science.gov (United States)

Ke, Bing-Shen; Li, Guang-Yun; Chen, Shi-Min; Huang, Xiang-Yan; Chen, Ying-Jian; Xu, Jun

2003-05-01

Today standard PCR can't satisfy the need of biotechnique development and clinical research any more. After numerous dynamic research, PE company found there is a linear relation between initial template number and cycling time when the accumulating fluorescent product is detectable.Therefore,they developed a quantitative PCR technique to be used in PE7700 and PE5700. But the error of this technique is too great to satisfy the need of biotechnique development and clinical research. A better quantitative PCR technique is needed. The mathematical model submitted here is combined with the achievement of relative science,and based on the PCR principle and careful analysis of molecular relationship of main members in PCR reaction system. This model describes the function relation between product quantity or fluorescence intensity and initial template number and other reaction conditions, and can reflect the accumulating rule of PCR product molecule accurately. Accurate quantitative PCR analysis can be made use this function relation. Accumulated PCR product quantity can be obtained from initial template number. Using this model to do quantitative PCR analysis,result error is only related to the accuracy of fluorescence intensity or the instrument used. For an example, when the fluorescence intensity is accurate to 6 digits and the template size is between 100 to 1,000,000, the quantitative result accuracy will be more than 99%. The difference of result error is distinct using same condition,same instrument but different analysis method. Moreover,if the PCR quantitative analysis system is used to process data, it will get result 80 times of accuracy than using CT method.

Nonstandard Work Schedules and Partnership Quality: Quantitative and Qualitative Findings

Science.gov (United States)

Mills, Melinda; Taht, Kadri

2010-01-01

This article questions existing findings and provides new evidence about the consequences of nonstandard work schedules on partnership quality. Using quantitative couple data from The Netherlands Kinship Panel Study (NKPS) (N = 3,016) and semistructured qualitative interviews (N = 34), we found that, for women, schedules with varying hours…

Adaptive Finite Element-Discrete Element Analysis for Microseismic Modelling of Hydraulic Fracture Propagation of Perforation in Horizontal Well considering Pre-Existing Fractures

Directory of Open Access Journals (Sweden)

Yongliang Wang

2018-01-01

Full Text Available Hydrofracturing technology of perforated horizontal well has been widely used to stimulate the tight hydrocarbon reservoirs for gas production. To predict the hydraulic fracture propagation, the microseismicity can be used to infer hydraulic fractures state; by the effective numerical methods, microseismic events can be addressed from changes of the computed stresses. In numerical models, due to the challenges in accurately representing the complex structure of naturally fractured reservoir, the interaction between hydraulic and pre-existing fractures has not yet been considered and handled satisfactorily. To overcome these challenges, the adaptive finite element-discrete element method is used to refine mesh, effectively identify the fractures propagation, and investigate microseismic modelling. Numerical models are composed of hydraulic fractures, pre-existing fractures, and microscale pores, and the seepage analysis based on the Darcy’s law is used to determine fluid flow; then moment tensors in microseismicity are computed based on the computed stresses. Unfractured and naturally fractured models are compared to assess the influences of pre-existing fractures on hydrofracturing. The damaged and contact slip events were detected by the magnitudes, B-values, Hudson source type plots, and focal spheres.

Physically based dynamic run-out modelling for quantitative debris flow risk assessment: a case study in Tresenda, northern Italy

Czech Academy of Sciences Publication Activity Database

Quan Luna, B.; Blahůt, Jan; Camera, C.; Van Westen, C.; Apuani, T.; Jetten, V.; Sterlacchini, S.

2014-01-01

Roč. 72, č. 3 (2014), s. 645-661 ISSN 1866-6280 Institutional support: RVO:67985891 Keywords : debris flow * FLO-2D * run-out * quantitative hazard and risk assessment * vulnerability * numerical modelling Subject RIV: DB - Geology ; Mineralogy Impact factor: 1.765, year: 2014

Socioeconomic influences on biodiversity, ecosystem services and human well-being: a quantitative application of the DPSIR model in Jiangsu, China.

Science.gov (United States)

Hou, Ying; Zhou, Shudong; Burkhard, Benjamin; Müller, Felix

2014-08-15

One focus of ecosystem service research is the connection between biodiversity, ecosystem services and human well-being as well as the socioeconomic influences on them. Despite existing investigations, exact impacts from the human system on the dynamics of biodiversity, ecosystem services and human well-being are still uncertain because of the insufficiency of the respective quantitative analyses. Our research aims are discerning the socioeconomic influences on biodiversity, ecosystem services and human well-being and demonstrating mutual impacts between these items. We propose a DPSIR framework coupling ecological integrity, ecosystem services as well as human well-being and suggest DPSIR indicators for the case study area Jiangsu, China. Based on available statistical and surveying data, we revealed the factors significantly impacting biodiversity, ecosystem services and human well-being in the research area through factor analysis and correlation analysis, using the 13 prefecture-level cities of Jiangsu as samples. The results show that urbanization and industrialization in the urban areas have predominant positive influences on regional biodiversity, agricultural productivity and tourism services as well as rural residents' living standards. Additionally, the knowledge, technology and finance inputs for agriculture also have generally positive impacts on these system components. Concerning regional carbon storage, non-cropland vegetation cover obviously plays a significant positive role. Contrarily, the expansion of farming land and the increase of total food production are two important negative influential factors of biodiversity, ecosystem's food provisioning service capacity, regional tourism income and the well-being of the rural population. Our study provides a promising approach based on the DPSIR model to quantitatively capture the socioeconomic influential factors of biodiversity, ecosystem services and human well-being for human-environmental systems

Aspects of quantitative secondary ion mass spectrometry

International Nuclear Information System (INIS)

Grauer, R.

1982-05-01

Parameters which have an influence on the formation of secondary ions by ion bombardment of a solid matrix are discussed. Quantitative SIMS-analysis with the help of calibration standards necessitates a stringent control of these parameters. This is particularly valid for the oxygen partial pressure which for metal analysis has to be maintained constant also under ultra high vacuum. The performance of the theoretical LTE-model (Local Thermal Equilibrium) using internal standards will be compared with the analysis with the help of external standards. The LTE-model does not satisfy the requirements for quantitative analysis. (Auth.)

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

Science.gov (United States)

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Quantitative aspects of the cytochemical demonstration of glucose-6-phosphate dehydrogenase with tetranitro BT studied in a model system of polyacrylamide films

NARCIS (Netherlands)

van Noorden, C. J.; Tas, J.

1980-01-01

The cytochemical determination of the activity of glucose-6-phosphate dehydrogenase (G6PDH) with tetranitro blue tetrazolium (TNBT) was studied with model films of polyacrylamide gel incorporating purified enzyme. This model system enabled a quantitative study to be made of different parameters

TU-G-303-00: Radiomics: Advances in the Use of Quantitative Imaging Used for Predictive Modeling

International Nuclear Information System (INIS)

2015-01-01

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

TU-G-303-00: Radiomics: Advances in the Use of Quantitative Imaging Used for Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-06-15

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

Kinetic Dissection of the Pre-existing Conformational Equilibrium in the Trypsin Fold*

Science.gov (United States)

Vogt, Austin D.; Chakraborty, Pradipta; Di Cera, Enrico

2015-01-01

Structural biology has recently documented the conformational plasticity of the trypsin fold for both the protease and zymogen in terms of a pre-existing equilibrium between closed (E*) and open (E) forms of the active site region. How such plasticity is manifested in solution and affects ligand recognition by the protease and zymogen is poorly understood in quantitative terms. Here we dissect the E*-E equilibrium with stopped-flow kinetics in the presence of excess ligand or macromolecule. Using the clotting protease thrombin and its zymogen precursor prethrombin-2 as relevant models we resolve the relative distribution of the E* and E forms and the underlying kinetic rates for their interconversion. In the case of thrombin, the E* and E forms are distributed in a 1:4 ratio and interconvert on a time scale of 45 ms. In the case of prethrombin-2, the equilibrium is shifted strongly (10:1 ratio) in favor of the closed E* form and unfolds over a faster time scale of 4.5 ms. The distribution of E* and E forms observed for thrombin and prethrombin-2 indicates that zymogen activation is linked to a significant shift in the pre-existing equilibrium between closed and open conformations that facilitates ligand binding to the active site. These findings broaden our mechanistic understanding of how conformational transitions control ligand recognition by thrombin and its zymogen precursor prethrombin-2 and have direct relevance to other members of the trypsin fold. PMID:26216877

Synthesis of quantitative and qualitative research: an example using Critical Interpretive Synthesis.

Science.gov (United States)

Flemming, Kate

2010-01-01

This paper is a report of a Critical Interpretive Synthesis to synthesize quantitative research, in the form of an effectiveness review and a guideline, with qualitative research to examine the use of morphine to treat cancer-related pain. Critical Interpretive Synthesis is a new method of reviewing, developed from meta-ethnography, which integrates systematic review methodology with a qualitative tradition of enquiry. It has not previously been used specifically to synthesize effectiveness and qualitative literature. Data sources. An existing systematic review of quantitative research and a guideline examining the effectiveness of oral morphine to treat cancer pain were identified. Electronic searches of Medline, CINAHL, Embase, PsychINFO, Health Management Information Consortium database and the Social Science Citation Index to identify qualitative research were carried out in May 2008. Qualitative research papers reporting on the use of morphine to treat cancer pain were identified. The findings of the effectiveness research were used as a framework to guide the translation of findings from qualitative research using an integrative grid. A secondary translation of findings from the qualitative research, not specifically mapped to the effectiveness literature, was guided by the framework. Nineteen qualitative papers were synthesized with the quantitative effectiveness literature, producing 14 synthetic constructs. These were developed into four synthesizing arguments which drew on patients', carers' and healthcare professionals' interpretations of the meaning and context of the use of morphine to treat cancer pain. Critical Interpretive Synthesis can be adapted to synthesize reviews of quantitative research into effectiveness with qualitative research and fits into an existing typology of approaches to synthesizing qualitative and quantitative research.

Global existence result for the generalized Peterlin viscoelastic model

Czech Academy of Sciences Publication Activity Database

Lukáčová-Medviďová, M.; Mizerová, H.; Nečasová, Šárka; Renardy, M.

2017-01-01

Roč. 49, č. 4 (2017), s. 2950-2964 ISSN 0036-1410 R&D Projects: GA ČR GA13-00522S Institutional support: RVO:67985840 Keywords : Peterlin viscoelastic equations * global existence * weak solutions Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 1.648, year: 2016 http://epubs.siam.org/doi/abs/10.1137/16M1068505

On the Dichotomy of Qualitative and Quantitative Researches in Contemporary Scientific Methodology

Directory of Open Access Journals (Sweden)

U V Suvakovic

2011-12-01

Full Text Available Argumentation in favor of overcoming the long-ago-established dichotomy of qualitative and quantitative scientific research is presented in the article. Proceeding from the view of materialistic dialecticians that every scientific research must deal with a subject, the author assumes that it is impossible to conduct a quantitative research without first establishing the quality to be studied. This also concerns measuring, which is referred only to quantitative procedures in literature. By way of illustration, the author designs two instruments for measuring the successfulness of political parties - the scale and the quotient of party successfulness. On the other hand, even the qualitative analysis usually involves certain quantifications. The author concludes that to achieve methodological correctness the existing dichotomy of qualitative and quantitative research should be considered as overcome and a typology of scientific research including predominantly qualitative and predominantly quantitative studies, depending on the methodological components prevailing in them, should be used.

Quantitative analysis of prediction models for hot cracking in ...

Indian Academy of Sciences (India)

A RodrМguez-Prieto

2017-11-16

Nov 16, 2017 ... enhancing safety margins and adding greater precision to quantitative accident prediction [45]. One deterministic methodology is the stringency level (SL) approach, which is recognized as a valuable decision tool in the selection of standardized materials specifications to prevent potential failures [3].

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

Energy Technology Data Exchange (ETDEWEB)

Yang, Chin-Rang [National Inst. of Health (NIH), Bethesda, MD (United States). National Heart, Lung and Blood Inst.

2013-12-11

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

Science.gov (United States)

T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

Experimental data available for radiation damage modelling in reactor materials

International Nuclear Information System (INIS)

Wollenberger, H.

Radiation damage modelling requires rate constants for production, annihilation and trapping of defects. The literature is reviewed with respect to experimental determination of such constants. Useful quantitative information exists only for Cu and Al. Special emphasis is given to the temperature dependence of the rate constants

A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

International Nuclear Information System (INIS)

Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

2014-01-01

A quantitative local computed tomography combined with data-constrained modelling has been developed. The method could improve distinctly the spatial resolution and the composition resolution in a sample larger than the field of view, for quantitative characterization of three-dimensional distributions of material compositions and void. Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials

BBN based Quantitative Assessment of Software Design Specification

International Nuclear Information System (INIS)

Eom, Heung-Seop; Park, Gee-Yong; Kang, Hyun-Gook; Kwon, Kee-Choon; Chang, Seung-Cheol

2007-01-01

Probabilistic Safety Assessment (PSA), which is one of the important methods in assessing the overall safety of a nuclear power plant (NPP), requires quantitative reliability information of safety-critical software, but the conventional reliability assessment methods can not provide enough information for PSA of a NPP. Therefore current PSA which includes safety-critical software does not usually consider the reliability of the software or uses arbitrary values for it. In order to solve this situation this paper proposes a method that can produce quantitative reliability information of safety-critical software for PSA by making use of Bayesian Belief Networks (BBN). BBN has generally been used to model an uncertain system in many research fields including the safety assessment of software. The proposed method was constructed by utilizing BBN which can combine the qualitative and the quantitative evidence relevant to the reliability of safety critical software. The constructed BBN model can infer a conclusion in a formal and a quantitative way. A case study was carried out with the proposed method to assess the quality of software design specification (SDS) of safety-critical software that will be embedded in a reactor protection system. The intermediate V and V results of the software design specification were used as inputs to the BBN model

40 CFR Table 5 to Subpart Bbbb of... - Model Rule-Carbon Monoxide Emission Limits for Existing Small Municipal Waste Combustion Units

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Model Rule-Carbon Monoxide Emission... BBBB of Part 60—Model Rule—Carbon Monoxide Emission Limits for Existing Small Municipal Waste... PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Small Municipal Waste...

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

Directory of Open Access Journals (Sweden)

Jessica L Fitterer

Full Text Available Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78 though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media, increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point. Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast modelling over small areas (e.g., blocks.

A Quantitative, Time-Dependent Model of Oxygen Isotopes in the Solar Nebula: Step one

Science.gov (United States)

Nuth, J. A.; Paquette, J. A.; Farquhar, A.; Johnson, N. M.

2011-01-01

The remarkable discovery that oxygen isotopes in primitive meteorites were fractionated along a line of slope I rather than along the typical slope 0,52 terrestrial fractionation line occurred almost 40 years ago, However, a satisfactory, quantitative explanation for this observation has yet to be found, though many different explanations have been proposed, The first of these explanations proposed that the observed line represented the final product produced by mixing molecular cloud dust with a nucleosynthetic component, rich in O-16, possibly resulting from a nearby supernova explosion, Donald Clayton suggested that Galactic Chemical Evolution would gradually change the oxygen isotopic composition of the interstellar grain population by steadily producing O-16 in supernovae, then producing the heavier isotopes as secondary products in lower mass stars, Thiemens and collaborators proposed a chemical mechanism that relied on the availability of additional active rotational and vibrational states in otherwise-symmetric molecules, such as CO2, O3 or SiO2, containing two different oxygen isotopes and a second, photochemical process that suggested that differential photochemical dissociation processes could fractionate oxygen , This second line of research has been pursued by several groups, though none of the current models is quantitative,

The Y4-RNA fragment, a potential diagnostic marker, exists in saliva

Directory of Open Access Journals (Sweden)

Tatsuya Ishikawa

2017-06-01

Full Text Available The 94-nt full-length Y4-RNA is thought to have roles in the initiation of DNA replication and RNA quality control. Although its 31/32-nt fragment also exists abundantly in plasma, little is known about its physiological role. Since the 31/32-nt Y4-RNA fragment in sera is reported to be more abundant in patients with coronary artery disease than healthy persons, the fragment may have a potential for a diagnostic and/or prognostic biomarker for some diseases regardless of its functionality. As a step toward further investigation of its potential utility, we examined if the 31/32-nt Y4-RNA fragment also exists in saliva that can be obtained noninvasively, and showed that, in addition to the 31/32-nt fragment, 14- and 11-nt Y4-RNA fragments are present in all saliva RNA samples from four healthy persons. We established a PCR method to accurately quantitate the amount of the 31/32-nt Y4-RNA fragment, and estimated its amount in saliva of healthy persons to be 0.06 ± 0.04 fmol per nanogram of saliva RNA. We also tried to develop an easier quantitation method using a DNA molecular beacon. Keywords: Y4-RNA fragment, Saliva RNA, Diagnostic/prognostic marker, Next-generation sequencing, RT-PCR, Molecular beacon

Psychological Contract Development: An Integration of Existing Knowledge to Form a Temporal Model

Directory of Open Access Journals (Sweden)

Kelly Windle

2014-07-01

Full Text Available The psychological contract has received substantial theoretical attention over the past two decades as a popular framework within which to examine contemporary employment relationships. Previous research mostly examines breach and violation of the psychological contract and its impact on employee organization outcomes. Few studies have employed longitudinal, prospective research designs to investigate the psychological contract and as a result, psychological contract content and formation are incompletely understood. It is argued that employment relationships may be better proactively managed with greater understanding of formation and changes in the psychological contract. We examine existing psychological contract literature to identify five key factors proposed to contribute to the formation of psychological contracts. We extend the current research by integrating these factors for the first time into a temporal model of psychological contract development.

A quantitative experiment on the fountain effect in superfluid helium

Science.gov (United States)

Amigó, M. L.; Herrera, T.; Neñer, L.; Peralta Gavensky, L.; Turco, F.; Luzuriaga, J.

2017-09-01

Superfluid helium, a state of matter existing at low temperatures, shows many remarkable properties. One example is the so called fountain effect, where a heater can produce a jet of helium. This converts heat into mechanical motion; a machine with no moving parts, but working only below 2 K. Allen and Jones first demonstrated the effect in 1938, but their work was basically qualitative. We now present data of a quantitative version of the experiment. We have measured the heat supplied, the temperature and the height of the jet produced. We also develop equations, based on the two-fluid model of superfluid helium, that give a satisfactory fit to the data. The experiment has been performed by advanced undergraduate students in our home institution, and illustrates in a vivid way some of the striking properties of the superfluid state.

Global existence and asymptotic behavior of a model for biological control of invasive species via supermale introduction

KAUST Repository

Parshad, Rana

2013-01-01

The purpose of this manuscript is to propose a model for the biological control of invasive species, via introduction of phenotypically modified organisms into a target population. We are inspired by the earlier Trojan Y Chromosome model [J.B. Gutierrez, J.L. Teem, J. Theo. Bio., 241(22), 333-341, 2006]. However, in the current work, we remove the assumption of logisticgrowth rate, and do not consider the addition of sex-reversed supermales. Also the constant birth and death coefficients, considered earlier, are replaced by functionally dependent ones. In this case the nonlinearities present serious difficulties since they change sign, and the components of the solution are not a priori bounded, in some Lp-space for p large, to permit theapplication of the well known regularizing effect principle. Thus functional methods to deducethe global existence in time, for the system in question, are not applicable. Our techniques are based on the Lyapunov functional method. We prove global existence of solutions, as well asexistence of a finite dimensional global attractor, that supports states of extinction. Our analytical finding are in accordance with numerical simulations, which we also present. © 2013 International Press.

Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

Directory of Open Access Journals (Sweden)

Sharifuddin M. Zain

2011-11-01

Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

Toward best practices in data processing and analysis for intact biotherapeutics by MS in quantitative bioanalysis.

Science.gov (United States)

Kellie, John F; Kehler, Jonathan R; Karlinsey, Molly Z; Summerfield, Scott G

2017-12-01

Typically, quantitation of biotherapeutics from biological matrices by LC-MS is based on a surrogate peptide approach to determine molecule concentration. Recent efforts have focused on quantitation of the intact protein molecules or larger mass subunits of monoclonal antibodies. To date, there has been limited guidance for large or intact protein mass quantitation for quantitative bioanalysis. Intact- and subunit-level analyses of biotherapeutics from biological matrices are performed at 12-25 kDa mass range with quantitation data presented. Linearity, bias and other metrics are presented along with recommendations made on the viability of existing quantitation approaches. This communication is intended to start a discussion around intact protein data analysis and processing, recognizing that other published contributions will be required.

Quantitative Comparison of Tolerance-Based Feature Transforms

OpenAIRE

Reniers, Dennie; Telea, Alexandru

2006-01-01

Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary images. Of these, two are novel methods and two extend existing distance transform algorithms. We quantitatively and qualitatively compare all algorithms on speed and accuracy of both distance and...

First experiences with model based iterative reconstructions influence on quantitative plaque volume and intensity measurements in coronary computed tomography angiography

DEFF Research Database (Denmark)

Precht, Helle; Kitslaar, Pieter H.; Broersen, Alexander

2017-01-01

Purpose: Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model- based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) im- ages on quantitative measurements in coronary arteries for plaque volumes and intensities. Methods...

Improvement of the ID model for quantitative network data

DEFF Research Database (Denmark)

Sørensen, Peter Borgen; Damgaard, Christian Frølund; Dupont, Yoko Luise

2015-01-01

Many interactions are often poorly registered or even unobserved in empirical quantitative networks. Hence, the output of the statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. Such artefa......Many interactions are often poorly registered or even unobserved in empirical quantitative networks. Hence, the output of the statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks......)1. This presentation will illustrate the application of the ID method based on a data set which consists of counts of visits by 152 pollinator species to 16 plant species. The method is based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi...... reproduce the high number of zero valued cells in the data set and mimic the sampling distribution. 1 Sørensen et al, Journal of Pollination Ecology, 6(18), 2011, pp129-139...

Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study.

Science.gov (United States)

Paquette, Philippe; El Khamlichi, Youssef; Lamontagne, Martin; Higgins, Johanne; Gagnon, Dany H

2017-08-01

Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. Both measurement techniques yielded excellent association ( r  = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.

Testing the efficacy of existing force-endurance models to account for the prevalence of obesity in the workforce.

Science.gov (United States)

Pajoutan, Mojdeh; Cavuoto, Lora A; Mehta, Ranjana K

2017-10-01

This study evaluates whether the existing force-endurance relationship models are predictive of endurance time for overweight and obese individuals, and if not, provide revised models that can be applied for ergonomics practice. Data was collected from 141 participants (49 normal weight, 50 overweight, 42 obese) who each performed isometric endurance tasks of hand grip, shoulder flexion, and trunk extension at four levels of relative workload. Subject-specific fatigue rates and a general model of the force-endurance relationship were determined and compared to two fatigue models from the literature. There was a lack of fit between previous models and the current data for the grip (ICC = 0.8), with a shift toward lower endurance times for the new data. Application of the revised models can facilitate improved workplace design and job evaluation to accommodate the capacities of the current workforce.

Comparison of evolutionary algorithms in gene regulatory network model inference.

LENUS (Irish Health Repository)

2010-01-01

ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

Correlation between the model accuracy and model-based SOC estimation

International Nuclear Information System (INIS)

Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

2017-01-01

State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

Science.gov (United States)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

Hanford Site background: Evaluation of existing soil radionuclide data

International Nuclear Information System (INIS)

1995-07-01

This report is an evaluation of the existing data on radiological background for soils in the vicinity of the Hanford Site. The primary purpose of this report is to assess the adequacy of the existing data to serve as a radiological background baseline for use in environmental restoration and remediation activities at the Hanford Site. The soil background data compiled and evaluated in this report were collected by the Pacific Northwest Laboratory (PNL) and Washington State Department of Health (DOH) radiation surveillance programs in southeastern Washington. These two programs provide the largest well-documented, quantitative data sets available to evaluate background conditions at the Hanford Site. The data quality objectives (DQOs) considered in this evaluation include the amount of data, number of sampling localities, spatial coverage, number and types of radionuclides reported, frequency of reporting, documentation and traceability of sampling and laboratory methods used, and comparability between sets of data. Although other data on soil radionuclide abundances around the Hanford Site exist, they are generally limited in scope and lack the DQOs necessary for consideration with the PNL and DOH data sets. Collectively, these two sources provide data on the activities of 25 radionuclides and four other parameters (gross alpha, gross beta, total uranium, and total thorium). These measurements were made on samples from the upper 2.5 cm of soil at over 70 localities within the region

Energy Dispersive Spectrometry and Quantitative Analysis Short Course. Introduction to X-ray Energy Dispersive Spectrometry and Quantitative Analysis

Science.gov (United States)

Carpenter, Paul; Curreri, Peter A. (Technical Monitor)

2002-01-01

This course will cover practical applications of the energy-dispersive spectrometer (EDS) to x-ray microanalysis. Topics covered will include detector technology, advances in pulse processing, resolution and performance monitoring, detector modeling, peak deconvolution and fitting, qualitative and quantitative analysis, compositional mapping, and standards. An emphasis will be placed on use of the EDS for quantitative analysis, with discussion of typical problems encountered in the analysis of a wide range of materials and sample geometries.

A Predictive Model for Yeast Cell Polarization in Pheromone Gradients.

Science.gov (United States)

Muller, Nicolas; Piel, Matthieu; Calvez, Vincent; Voituriez, Raphaël; Gonçalves-Sá, Joana; Guo, Chin-Lin; Jiang, Xingyu; Murray, Andrew; Meunier, Nicolas

2016-04-01

Budding yeast cells exist in two mating types, a and α, which use peptide pheromones to communicate with each other during mating. Mating depends on the ability of cells to polarize up pheromone gradients, but cells also respond to spatially uniform fields of pheromone by polarizing along a single axis. We used quantitative measurements of the response of a cells to α-factor to produce a predictive model of yeast polarization towards a pheromone gradient. We found that cells make a sharp transition between budding cycles and mating induced polarization and that they detect pheromone gradients accurately only over a narrow range of pheromone concentrations corresponding to this transition. We fit all the parameters of the mathematical model by using quantitative data on spontaneous polarization in uniform pheromone concentration. Once these parameters have been computed, and without any further fit, our model quantitatively predicts the yeast cell response to pheromone gradient providing an important step toward understanding how cells communicate with each other.

The Lexicographic Treatment of Quantitative Pronouns in Zulu

Directory of Open Access Journals (Sweden)

Gilles-Maurice de Schryver

2011-10-01

Full Text Available

Abstract: In Zulu, there are three kinds of quantitatives: inclusive, exclusive and numeral. For the lemmatization of these, even existing traditional dictionaries felt the need to move away from a pure 'stem' approach towards a 'word' approach. In a new Zulu–English dictionary project, this is not only confirmed, but is taken one step further with particular attention to the microstructure.

Keywords: LEXICOGRAPHY, DICTIONARY, BILINGUAL, CORPUS, LEMMATIZATION,FREQUENCY, ZULU (ISIZULU, ENGLISH, QUANTITATIVE PRONOUN, INCLUSIVE QUANTITATIVEPRONOUN, EXCLUSIVE QUANTITATIVE PRONOUN, (INCLUSIVE NUMERALQUANTITATIVE PRONOUN, USER-FRIENDLY

Samenvatting: De lexicografische behandeling van kwantitatieve pronominain Zoeloe. In Zoeloe zijn er drie soorten kwantitatieven: inclusieve, exclusieve en numerieke.Voor de lemmatisatie daarvan voelden zelfs bestaande traditionele woordenboeken de noodom stam-lemmatisatie te verlaten voor woord-lemmatisatie. In een nieuw Zoeloe–Engels woordenboekprojectwordt dit niet alleen bevestigd, doch wordt ook een stap verder gegaan, met bijzondereaandacht voor de microstructuur.

Sleutelwoorden: LEXICOGRAFIE, WOORDENBOEK, TWEETALIG, CORPUS, LEMMATISATIE,FREQUENTIE, ZOELOE, ENGELS, KWANTITATIEF PRONOMEN, INCLUSIEFKWANTITATIEF PRONOMEN, EXCLUSIEF KWANTITATIEF PRONOMEN, (INCLUSIEFNUMERIEK KWANTITATIEF PRONOMEN, GEBRUIKSVRIENDELIJK

Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

International Nuclear Information System (INIS)

Shin, Seung Ki; Seong, Poong Hyun

2008-01-01

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

A novel baseline correction method using convex optimization framework in laser-induced breakdown spectroscopy quantitative analysis

Science.gov (United States)

Yi, Cancan; Lv, Yong; Xiao, Han; Ke, Ke; Yu, Xun

2017-12-01

For laser-induced breakdown spectroscopy (LIBS) quantitative analysis technique, baseline correction is an essential part for the LIBS data preprocessing. As the widely existing cases, the phenomenon of baseline drift is generated by the fluctuation of laser energy, inhomogeneity of sample surfaces and the background noise, which has aroused the interest of many researchers. Most of the prevalent algorithms usually need to preset some key parameters, such as the suitable spline function and the fitting order, thus do not have adaptability. Based on the characteristics of LIBS, such as the sparsity of spectral peaks and the low-pass filtered feature of baseline, a novel baseline correction and spectral data denoising method is studied in this paper. The improved technology utilizes convex optimization scheme to form a non-parametric baseline correction model. Meanwhile, asymmetric punish function is conducted to enhance signal-noise ratio (SNR) of the LIBS signal and improve reconstruction precision. Furthermore, an efficient iterative algorithm is applied to the optimization process, so as to ensure the convergence of this algorithm. To validate the proposed method, the concentration analysis of Chromium (Cr),Manganese (Mn) and Nickel (Ni) contained in 23 certified high alloy steel samples is assessed by using quantitative models with Partial Least Squares (PLS) and Support Vector Machine (SVM). Because there is no prior knowledge of sample composition and mathematical hypothesis, compared with other methods, the method proposed in this paper has better accuracy in quantitative analysis, and fully reflects its adaptive ability.

Classification-based quantitative analysis of stable isotope labeling by amino acids in cell culture (SILAC) data.

Science.gov (United States)

Kim, Seongho; Carruthers, Nicholas; Lee, Joohyoung; Chinni, Sreenivasa; Stemmer, Paul

2016-12-01

Stable isotope labeling by amino acids in cell culture (SILAC) is a practical and powerful approach for quantitative proteomic analysis. A key advantage of SILAC is the ability to simultaneously detect the isotopically labeled peptides in a single instrument run and so guarantee relative quantitation for a large number of peptides without introducing any variation caused by separate experiment. However, there are a few approaches available to assessing protein ratios and none of the existing algorithms pays considerable attention to the proteins having only one peptide hit. We introduce new quantitative approaches to dealing with SILAC protein-level summary using classification-based methodologies, such as Gaussian mixture models with EM algorithms and its Bayesian approach as well as K-means clustering. In addition, a new approach is developed using Gaussian mixture model and a stochastic, metaheuristic global optimization algorithm, particle swarm optimization (PSO), to avoid either a premature convergence or being stuck in a local optimum. Our simulation studies show that the newly developed PSO-based method performs the best among others in terms of F1 score and the proposed methods further demonstrate the ability of detecting potential markers through real SILAC experimental data. No matter how many peptide hits the protein has, the developed approach can be applicable, rescuing many proteins doomed to removal. Furthermore, no additional correction for multiple comparisons is necessary for the developed methods, enabling direct interpretation of the analysis outcomes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative Verification and Synthesis of Attack-Defence Scenarios

DEFF Research Database (Denmark)

Aslanyan, Zaruhi; Nielson, Flemming; Parker, David

2016-01-01

analysis of quantitative properties of complex attack-defence scenarios, using an extension of attack-defence trees which models temporal ordering of actions and allows explicit dependencies in the strategies adopted by attackers and defenders. We adopt a game-theoretic approach, translating attack...... which guarantee or optimise some quantitative property, such as the probability of a successful attack, the expected cost incurred, or some multi-objective trade-off between the two. We implement our approach, building upon the PRISM-games model checker, and apply it to a case study of an RFID goods...

Schumpeterian economic dynamics as a quantifiable model of evolution

Science.gov (United States)

Thurner, Stefan; Klimek, Peter; Hanel, Rudolf

2010-07-01

We propose a simple quantitative model of Schumpeterian economic dynamics. New goods and services are endogenously produced through combinations of existing goods. As soon as new goods enter the market, they may compete against already existing goods. In other words, new products can have destructive effects on existing goods. As a result of this competition mechanism, existing goods may be driven out from the market—often causing cascades of secondary defects (Schumpeterian gales of destruction). The model leads to generic dynamics characterized by phases of relative economic stability followed by phases of massive restructuring of markets—which could be interpreted as Schumpeterian business 'cycles'. Model time series of product diversity and productivity reproduce several stylized facts of economics time series on long timescales, such as GDP or business failures, including non-Gaussian fat tailed distributions and volatility clustering. The model is phrased in an open, non-equilibrium setup which can be understood as a self-organized critical system. Its diversity dynamics can be understood by the time-varying topology of the active production networks.

Technical manual for basic version of the Markov chain nest productivity model (MCnest)

Science.gov (United States)

The Markov Chain Nest Productivity Model (or MCnest) integrates existing toxicity information from three standardized avian toxicity tests with information on species life history and the timing of pesticide applications relative to the timing of avian breeding seasons to quantit...

User’s manual for basic version of MCnest Markov chain nest productivity model

Science.gov (United States)

The Markov Chain Nest Productivity Model (or MCnest) integrates existing toxicity information from three standardized avian toxicity tests with information on species life history and the timing of pesticide applications relative to the timing of avian breeding seasons to quantit...

The role of pre-existing disturbances in the effect of marine reserves on coastal ecosystems: a modelling approach.

Directory of Open Access Journals (Sweden)

Marie Savina

Full Text Available We have used an end-to-end ecosystem model to explore responses over 30 years to coastal no-take reserves covering up to 6% of the fifty thousand square kilometres of continental shelf and slope off the coast of New South Wales (Australia. The model is based on the Atlantis framework, which includes a deterministic, spatially resolved three-dimensional biophysical model that tracks nutrient flows through key biological groups, as well as extraction by a range of fisheries. The model results support previous empirical studies in finding clear benefits of reserves to top predators such as sharks and rays throughout the region, while also showing how many of their major prey groups (including commercial species experienced significant declines. It was found that the net impact of marine reserves was dependent on the pre-existing levels of disturbance (i.e. fishing pressure, and to a lesser extent on the size of the marine reserves. The high fishing scenario resulted in a strongly perturbed system, where the introduction of marine reserves had clear and mostly direct effects on biomass and functional biodiversity. However, under the lower fishing pressure scenario, the introduction of marine reserves caused both direct positive effects, mainly on shark groups, and indirect negative effects through trophic cascades. Our study illustrates the need to carefully align the design and implementation of marine reserves with policy and management objectives. Trade-offs may exist not only between fisheries and conservation objectives, but also among conservation objectives.

A quantitative modeling of the contributions of localized surface plasmon resonance and interband transitions to absorbance of gold nanoparticles