Hidden Markov models for evolution and comparative genomics analysis.

PubMed

Bykova, Nadezda A; Favorov, Alexander V; Mironov, Andrey A

2013-01-01

The problem of reconstruction of ancestral states given a phylogeny and data from extant species arises in a wide range of biological studies. The continuous-time Markov model for the discrete states evolution is generally used for the reconstruction of ancestral states. We modify this model to account for a case when the states of the extant species are uncertain. This situation appears, for example, if the states for extant species are predicted by some program and thus are known only with some level of reliability; it is common for bioinformatics field. The main idea is formulation of the problem as a hidden Markov model on a tree (tree HMM, tHMM), where the basic continuous-time Markov model is expanded with the introduction of emission probabilities of observed data (e.g. prediction scores) for each underlying discrete state. Our tHMM decoding algorithm allows us to predict states at the ancestral nodes as well as to refine states at the leaves on the basis of quantitative comparative genomics. The test on the simulated data shows that the tHMM approach applied to the continuous variable reflecting the probabilities of the states (i.e. prediction score) appears to be more accurate then the reconstruction from the discrete states assignment defined by the best score threshold. We provide examples of applying our model to the evolutionary analysis of N-terminal signal peptides and transcription factor binding sites in bacteria. The program is freely available at http://bioinf.fbb.msu.ru/~nadya/tHMM and via web-service at http://bioinf.fbb.msu.ru/treehmmweb.

Systems thinking, the Swiss Cheese Model and accident analysis: a comparative systemic analysis of the Grayrigg train derailment using the ATSB, AcciMap and STAMP models.

PubMed

Underwood, Peter; Waterson, Patrick

2014-07-01

The Swiss Cheese Model (SCM) is the most popular accident causation model and is widely used throughout various industries. A debate exists in the research literature over whether the SCM remains a viable tool for accident analysis. Critics of the model suggest that it provides a sequential, oversimplified view of accidents. Conversely, proponents suggest that it embodies the concepts of systems theory, as per the contemporary systemic analysis techniques. The aim of this paper was to consider whether the SCM can provide a systems thinking approach and remain a viable option for accident analysis. To achieve this, the train derailment at Grayrigg was analysed with an SCM-based model (the ATSB accident investigation model) and two systemic accident analysis methods (AcciMap and STAMP). The analysis outputs and usage of the techniques were compared. The findings of the study showed that each model applied the systems thinking approach. However, the ATSB model and AcciMap graphically presented their findings in a more succinct manner, whereas STAMP more clearly embodied the concepts of systems theory. The study suggests that, whilst the selection of an analysis method is subject to trade-offs that practitioners and researchers must make, the SCM remains a viable model for accident analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparative analysis of Goodwin's business cycle models

NASA Astrophysics Data System (ADS)

Antonova, A. O.; Reznik, S.; Todorov, M. D.

2016-10-01

We compare the behavior of solutions of Goodwin's business cycle equation in the form of neutral delay differential equation with fixed delay (NDDE model) and in the form of the differential equations of 3rd, 4th and 5th orders (ODE model's). Such ODE model's (Taylor series expansion of NDDE in powers of θ) are proposed in N. Dharmaraj and K. Vela Velupillai [6] for investigation of the short periodic sawthooth oscillations in NDDE. We show that the ODE's of 3rd, 4th and 5th order may approximate the asymptotic behavior of only main Goodwin's mode, but not the sawthooth modes. If the order of the Taylor series expansion exceeds 5, then the approximate ODE becomes unstable independently of time lag θ.

Modelling submerged coastal environments: Remote sensing technologies, techniques, and comparative analysis

NASA Astrophysics Data System (ADS)

Dillon, Chris

Built upon remote sensing and GIS littoral zone characterization methodologies of the past decade, a series of loosely coupled models aimed to test, compare and synthesize multi-beam SONAR (MBES), Airborne LiDAR Bathymetry (ALB), and satellite based optical data sets in the Gulf of St. Lawrence, Canada, eco-region. Bathymetry and relative intensity metrics for the MBES and ALB data sets were run through a quantitative and qualitative comparison, which included outputs from the Benthic Terrain Modeller (BTM) tool. Substrate classification based on relative intensities of respective data sets and textural indices generated using grey level co-occurrence matrices (GLCM) were investigated. A spatial modelling framework built in ArcGIS(TM) for the derivation of bathymetric data sets from optical satellite imagery was also tested for proof of concept and validation. Where possible, efficiencies and semi-automation for repeatable testing was achieved using ArcGIS(TM) ModelBuilder. The findings from this study could assist future decision makers in the field of coastal management and hydrographic studies. Keywords: Seafloor terrain characterization, Benthic Terrain Modeller (BTM), Multi-beam SONAR, Airborne LiDAR Bathymetry, Satellite Derived Bathymetry, ArcGISTM ModelBuilder, Textural analysis, Substrate classification.

How to Construct More Accurate Student Models: Comparing and Optimizing Knowledge Tracing and Performance Factor Analysis

ERIC Educational Resources Information Center

Gong, Yue; Beck, Joseph E.; Heffernan, Neil T.

2011-01-01

Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), by evaluating their predictive…

Comparative analysis of bleeding risk by the location and shape of arachnoid cysts: a finite element model analysis.

PubMed

Lee, Chang-Hyun; Han, In Seok; Lee, Ji Yeoun; Phi, Ji Hoon; Kim, Seung-Ki; Kim, Young-Eun; Wang, Kyu-Chang

2017-01-01

Although arachnoid cysts (ACs) are observed in various locations, only sylvian ACs are mainly regarded to be associated with bleeding. The reason for this selective association of sylvian ACs with bleeding is not understood well. This study is to investigate the effect of the location and shape of ACs on the risk of bleeding. A developed finite element model of the head/brain was modified for models of sylvian, suprasellar, and posterior fossa ACs. A spherical AC was placed at each location to compare the effect of AC location. Bowl-shaped and oval-shaped AC models were developed to compare the effect by shape. The shear force on the spot-weld elements (SFSW) was measured between the dura and the outer wall of the ACs or the comparable arachnoid membrane in the normal model. All AC models revealed higher SFSW than comparable normal models. By location, sylvian AC displayed the highest SFSW for frontal and lateral impacts. By shape, small outer wall AC models showed higher SFSW than large wall models in sylvian area and lower SFSW than large ones in posterior fossa. In regression analysis, the presence of AC was the only independent risk of bleeding. The bleeding mechanism of ACs is very complex, and the risk quantification failed to show a significant role of location and shape of ACs. The presence of AC increases shear force on impact condition and may be a risk factor of bleeding, and sylvian location of AC may not have additive risks of AC bleeding.

Computer-aided modelling and analysis of PV systems: a comparative study.

PubMed

Koukouvaos, Charalambos; Kandris, Dionisis; Samarakou, Maria

2014-01-01

Modern scientific advances have enabled remarkable efficacy for photovoltaic systems with regard to the exploitation of solar energy, boosting them into having a rapidly growing position among the systems developed for the production of renewable energy. However, in many cases the design, analysis, and control of photovoltaic systems are tasks which are quite complex and thus difficult to be carried out. In order to cope with this kind of problems, appropriate software tools have been developed either as standalone products or parts of general purpose software platforms used to model and simulate the generation, transmission, and distribution of solar energy. The utilization of this kind of software tools may be extremely helpful to the successful performance evaluation of energy systems with maximum accuracy and minimum cost in time and effort. The work presented in this paper aims on a first level at the performance analysis of various configurations of photovoltaic systems through computer-aided modelling. On a second level, it provides a comparative evaluation of the credibility of two of the most advanced graphical programming environments, namely, Simulink and LabVIEW, with regard to their application in photovoltaic systems.

Computer-Aided Modelling and Analysis of PV Systems: A Comparative Study

PubMed Central

Koukouvaos, Charalambos

2014-01-01

Modern scientific advances have enabled remarkable efficacy for photovoltaic systems with regard to the exploitation of solar energy, boosting them into having a rapidly growing position among the systems developed for the production of renewable energy. However, in many cases the design, analysis, and control of photovoltaic systems are tasks which are quite complex and thus difficult to be carried out. In order to cope with this kind of problems, appropriate software tools have been developed either as standalone products or parts of general purpose software platforms used to model and simulate the generation, transmission, and distribution of solar energy. The utilization of this kind of software tools may be extremely helpful to the successful performance evaluation of energy systems with maximum accuracy and minimum cost in time and effort. The work presented in this paper aims on a first level at the performance analysis of various configurations of photovoltaic systems through computer-aided modelling. On a second level, it provides a comparative evaluation of the credibility of two of the most advanced graphical programming environments, namely, Simulink and LabVIEW, with regard to their application in photovoltaic systems. PMID:24772007

Comparative Analysis of InSAR Digital Surface Models for Test Area Bucharest

NASA Astrophysics Data System (ADS)

Dana, Iulia; Poncos, Valentin; Teleaga, Delia

2010-03-01

This paper presents the results of the interferometric processing of ERS Tandem, ENVISAT and TerraSAR- X for digital surface model (DSM) generation. The selected test site is Bucharest (Romania), a built-up area characterized by the usual urban complex pattern: mixture of buildings with different height levels, paved roads, vegetation, and water bodies. First, the DSMs were generated following the standard interferometric processing chain. Then, the accuracy of the DSMs was analyzed against the SPOT HRS model (30 m resolution at the equator). A DSM derived by optical stereoscopic processing of SPOT 5 HRG data and also the SRTM (3 arc seconds resolution at the equator) DSM have been included in the comparative analysis.

Comparative analysis of numerical models of pipe handling equipment used in offshore drilling applications

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

Pawlus, Witold, E-mail: witold.p.pawlus@ieee.org; Ebbesen, Morten K.; Hansen, Michael R.

Design of offshore drilling equipment is a task that involves not only analysis of strict machine specifications and safety requirements but also consideration of changeable weather conditions and harsh environment. These challenges call for a multidisciplinary approach and make the design process complex. Various modeling software products are currently available to aid design engineers in their effort to test and redesign equipment before it is manufactured. However, given the number of available modeling tools and methods, the choice of the proper modeling methodology becomes not obvious and – in some cases – troublesome. Therefore, we present a comparative analysis ofmore » two popular approaches used in modeling and simulation of mechanical systems: multibody and analytical modeling. A gripper arm of the offshore vertical pipe handling machine is selected as a case study for which both models are created. In contrast to some other works, the current paper shows verification of both systems by benchmarking their simulation results against each other. Such criteria as modeling effort and results accuracy are evaluated to assess which modeling strategy is the most suitable given its eventual application.« less

Measurement error in time-series analysis: a simulation study comparing modelled and monitored data.

PubMed

Butland, Barbara K; Armstrong, Ben; Atkinson, Richard W; Wilkinson, Paul; Heal, Mathew R; Doherty, Ruth M; Vieno, Massimo

2013-11-13

Assessing health effects from background exposure to air pollution is often hampered by the sparseness of pollution monitoring networks. However, regional atmospheric chemistry-transport models (CTMs) can provide pollution data with national coverage at fine geographical and temporal resolution. We used statistical simulation to compare the impact on epidemiological time-series analysis of additive measurement error in sparse monitor data as opposed to geographically and temporally complete model data. Statistical simulations were based on a theoretical area of 4 regions each consisting of twenty-five 5 km × 5 km grid-squares. In the context of a 3-year Poisson regression time-series analysis of the association between mortality and a single pollutant, we compared the error impact of using daily grid-specific model data as opposed to daily regional average monitor data. We investigated how this comparison was affected if we changed the number of grids per region containing a monitor. To inform simulations, estimates (e.g. of pollutant means) were obtained from observed monitor data for 2003-2006 for national network sites across the UK and corresponding model data that were generated by the EMEP-WRF CTM. Average within-site correlations between observed monitor and model data were 0.73 and 0.76 for rural and urban daily maximum 8-hour ozone respectively, and 0.67 and 0.61 for rural and urban loge(daily 1-hour maximum NO2). When regional averages were based on 5 or 10 monitors per region, health effect estimates exhibited little bias. However, with only 1 monitor per region, the regression coefficient in our time-series analysis was attenuated by an estimated 6% for urban background ozone, 13% for rural ozone, 29% for urban background loge(NO2) and 38% for rural loge(NO2). For grid-specific model data the corresponding figures were 19%, 22%, 54% and 44% respectively, i.e. similar for rural loge(NO2) but more marked for urban loge(NO2). Even if correlations between

Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique

NASA Astrophysics Data System (ADS)

Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida

2018-04-01

The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.

Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

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

Zheng, Nina; Zhou, Nan; Fridley, David

The past decade has seen the development of various scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions, with each new approach adding insights to our understanding of the changing dynamics of energy consumption and aggregate future energy trends. With the recent growing focus on China's energy use and emission mitigation potential, a range of Chinese outlook models have been developed across different institutions including in China's Energy Research Institute's 2050 China Energy and CO2 Emissions Report, McKinsey & Co's China's Green Revolution report, the UK Sussex Energy Group and Tyndall Centre's China's Energy Transition report, and the China-specificmore » section of the IEA World Energy Outlook 2009. At the same time, the China Energy Group at Lawrence Berkeley National Laboratory (LBNL) has developed a bottom-up, end-use energy model for China with scenario analysis of energy and emission pathways out to 2050. A robust and credible energy and emission model will play a key role in informing policymakers by assessing efficiency policy impacts and understanding the dynamics of future energy consumption and energy saving and emission reduction potential. This is especially true for developing countries such as China, where uncertainties are greater while the economy continues to undergo rapid growth and industrialization. A slightly different assumption or storyline could result in significant discrepancies among different model results. Therefore, it is necessary to understand the key models in terms of their scope, methodologies, key driver assumptions and the associated findings. A comparative analysis of LBNL's energy end-use model scenarios with the five above studies was thus conducted to examine similarities and divergences in methodologies, scenario storylines, macroeconomic drivers and assumptions as well as aggregate energy and emission scenario results. Besides directly tracing different energy and CO{sub 2} savings

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for

Model Ambiguities in Configurational Comparative Research

ERIC Educational Resources Information Center

Baumgartner, Michael; Thiem, Alrik

2017-01-01

For many years, sociologists, political scientists, and management scholars have readily relied on Qualitative Comparative Analysis (QCA) for the purpose of configurational causal modeling. However, this article reveals that a severe problem in the application of QCA has gone unnoticed so far: model ambiguities. These arise when multiple causal…

Comparative mRNA analysis of behavioral and genetic mouse models of aggression.

PubMed

Malki, Karim; Tosto, Maria G; Pain, Oliver; Sluyter, Frans; Mineur, Yann S; Crusio, Wim E; de Boer, Sietse; Sandnabba, Kenneth N; Kesserwani, Jad; Robinson, Edward; Schalkwyk, Leonard C; Asherson, Philip

2016-04-01

Mouse models of aggression have traditionally compared strains, most notably BALB/cJ and C57BL/6. However, these strains were not designed to study aggression despite differences in aggression-related traits and distinct reactivity to stress. This study evaluated expression of genes differentially regulated in a stress (behavioral) mouse model of aggression with those from a recent genetic mouse model aggression. The study used a discovery-replication design using two independent mRNA studies from mouse brain tissue. The discovery study identified strain (BALB/cJ and C57BL/6J) × stress (chronic mild stress or control) interactions. Probe sets differentially regulated in the discovery set were intersected with those uncovered in the replication study, which evaluated differences between high and low aggressive animals from three strains specifically bred to study aggression. Network analysis was conducted on overlapping genes uncovered across both studies. A significant overlap was found with the genetic mouse study sharing 1,916 probe sets with the stress model. Fifty-one probe sets were found to be strongly dysregulated across both studies mapping to 50 known genes. Network analysis revealed two plausible pathways including one centered on the UBC gene hub which encodes ubiquitin, a protein well-known for protein degradation, and another on P38 MAPK. Findings from this study support the stress model of aggression, which showed remarkable molecular overlap with a genetic model. The study uncovered a set of candidate genes including the Erg2 gene, which has previously been implicated in different psychopathologies. The gene networks uncovered points at a Redox pathway as potentially being implicated in aggressive related behaviors. © 2016 Wiley Periodicals, Inc.

Comparative Analysis of VaR Estimation of Double Long-Memory GARCH Models: Empirical Analysis of China's Stock Market

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Guo, Jianping; Xu, Lin

GARCH models are widely used to model the volatility of financial assets and measure VaR. Based on the characteristics of long-memory and lepkurtosis and fat tail of stock market return series, we compared the ability of double long-memory GARCH models with skewed student-t-distribution to compute VaR, through the empirical analysis of Shanghai Composite Index (SHCI) and Shenzhen Component Index (SZCI). The results show that the ARFIMA-HYGARCH model performance better than others, and at less than or equal to 2.5 percent of the level of VaR, double long-memory GARCH models have stronger ability to evaluate in-sample VaRs in long position than in short position while there is a diametrically opposite conclusion for ability of out-of-sample VaR forecast.

Conceptual model of iCAL4LA: Proposing the components using comparative analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Zulaiha; Mutalib, Ariffin Abdul

2016-08-01

This paper discusses an on-going study that initiates an initial process in determining the common components for a conceptual model of interactive computer-assisted learning that is specifically designed for low achieving children. This group of children needs a specific learning support that can be used as an alternative learning material in their learning environment. In order to develop the conceptual model, this study extracts the common components from 15 strongly justified computer assisted learning studies. A comparative analysis has been conducted to determine the most appropriate components by using a set of specific indication classification to prioritize the applicability. The results of the extraction process reveal 17 common components for consideration. Later, based on scientific justifications, 16 of them were selected as the proposed components for the model.

A Comparative of business process modelling techniques

NASA Astrophysics Data System (ADS)

Tangkawarow, I. R. H. T.; Waworuntu, J.

2016-04-01

In this era, there is a lot of business process modeling techniques. This article is the research about differences of business process modeling techniques. For each technique will explain about the definition and the structure. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on 2 criteria: notation and how it works when implemented in Somerleyton Animal Park. Each technique will end with the advantages and disadvantages. The final conclusion will give recommend of business process modeling techniques that easy to use and serve the basis for evaluating further modelling techniques.

Accuracy of Bolton analysis measured in laser scanned digital models compared with plaster models (gold standard) and cone-beam computer tomography images.

PubMed

Kim, Jooseong; Lagravére, Manuel O

2016-01-01

The aim of this study was to compare the accuracy of Bolton analysis obtained from digital models scanned with the Ortho Insight three-dimensional (3D) laser scanner system to those obtained from cone-beam computed tomography (CBCT) images and traditional plaster models. CBCT scans and plaster models were obtained from 50 patients. Plaster models were scanned using the Ortho Insight 3D laser scanner; Bolton ratios were calculated with its software. CBCT scans were imported and analyzed using AVIZO software. Plaster models were measured with a digital caliper. Data were analyzed with descriptive statistics and the intraclass correlation coefficient (ICC). Anterior and overall Bolton ratios obtained by the three different modalities exhibited excellent agreement (> 0.970). The mean differences between the scanned digital models and physical models and between the CBCT images and scanned digital models for overall Bolton ratios were 0.41 ± 0.305% and 0.45 ± 0.456%, respectively; for anterior Bolton ratios, 0.59 ± 0.520% and 1.01 ± 0.780%, respectively. ICC results showed that intraexaminer error reliability was generally excellent (> 0.858 for all three diagnostic modalities), with < 1.45% discrepancy in the Bolton analysis. Laser scanned digital models are highly accurate compared to physical models and CBCT scans for assessing the spatial relationships of dental arches for orthodontic diagnosis.

Accuracy of Bolton analysis measured in laser scanned digital models compared with plaster models (gold standard) and cone-beam computer tomography images

PubMed Central

Kim, Jooseong

2016-01-01

Objective The aim of this study was to compare the accuracy of Bolton analysis obtained from digital models scanned with the Ortho Insight three-dimensional (3D) laser scanner system to those obtained from cone-beam computed tomography (CBCT) images and traditional plaster models. Methods CBCT scans and plaster models were obtained from 50 patients. Plaster models were scanned using the Ortho Insight 3D laser scanner; Bolton ratios were calculated with its software. CBCT scans were imported and analyzed using AVIZO software. Plaster models were measured with a digital caliper. Data were analyzed with descriptive statistics and the intraclass correlation coefficient (ICC). Results Anterior and overall Bolton ratios obtained by the three different modalities exhibited excellent agreement (> 0.970). The mean differences between the scanned digital models and physical models and between the CBCT images and scanned digital models for overall Bolton ratios were 0.41 ± 0.305% and 0.45 ± 0.456%, respectively; for anterior Bolton ratios, 0.59 ± 0.520% and 1.01 ± 0.780%, respectively. ICC results showed that intraexaminer error reliability was generally excellent (> 0.858 for all three diagnostic modalities), with < 1.45% discrepancy in the Bolton analysis. Conclusions Laser scanned digital models are highly accurate compared to physical models and CBCT scans for assessing the spatial relationships of dental arches for orthodontic diagnosis. PMID:26877978

Comparative analysis of economic models in selected solar energy computer programs

NASA Astrophysics Data System (ADS)

Powell, J. W.; Barnes, K. A.

1982-01-01

The economic evaluation models in five computer programs widely used for analyzing solar energy systems (F-CHART 3.0, F-CHART 4.0, SOLCOST, BLAST, and DOE-2) are compared. Differences in analysis techniques and assumptions among the programs are assessed from the point of view of consistency with the Federal requirements for life cycle costing (10 CFR Part 436), effect on predicted economic performance, and optimal system size, case of use, and general applicability to diverse systems types and building types. The FEDSOL program developed by the National Bureau of Standards specifically to meet the Federal life cycle cost requirements serves as a basis for the comparison. Results of the study are illustrated in test cases of two different types of Federally owned buildings: a single family residence and a low rise office building.

The effectiveness of physical models in teaching anatomy: a meta-analysis of comparative studies.

PubMed

Yammine, Kaissar; Violato, Claudio

2016-10-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively assess the effectiveness of such models based on comparative studies. Eight studies (7 randomized trials; 1 quasi-experimental) including 16 comparison arms and 820 learners met the inclusion criteria. Primary outcomes were defined as factual, spatial and overall percentage scores. The meta-analytical results are: educational methods using physical models yielded significantly better results when compared to all other educational methods for the overall knowledge outcome (p < 0.001) and for spatial knowledge acquisition (p < 0.001). Significantly better results were also found with regard to the long-retention knowledge outcome (p < 0.01). No significance was found for the factual knowledge acquisition outcome. The evidence in the present systematic review was found to have high internal validity and at least an acceptable strength. In conclusion, physical anatomical models offer a promising tool for teaching gross anatomy in 3D representation due to their easy accessibility and educational effectiveness. Such models could be a practical tool to bring up the learners' level of gross anatomy knowledge at low cost.

Comparative study on DuPont analysis and DEA models for measuring stock performance using financial ratio

NASA Astrophysics Data System (ADS)

Arsad, Roslah; Shaari, Siti Nabilah Mohd; Isa, Zaidi

2017-11-01

Determining stock performance using financial ratio is challenging for many investors and researchers. Financial ratio can indicate the strengths and weaknesses of a company's stock performance. There are five categories of financial ratios namely liquidity, efficiency, leverage, profitability and market ratios. It is important to interpret the ratio correctly for proper financial decision making. The purpose of this study is to compare the performance of listed companies in Bursa Malaysia using Data Envelopment Analysis (DEA) and DuPont analysis Models. The study is conducted in 2015 involving 116 consumer products companies listed in Bursa Malaysia. The estimation method of Data Envelopment Analysis computes the efficiency scores and ranks the companies accordingly. The Alirezaee and Afsharian's method of analysis based Charnes, Cooper and Rhodes (CCR) where Constant Return to Scale (CRS) is employed. The DuPont analysis is a traditional tool for measuring the operating performance of companies. In this study, DuPont analysis is used to evaluate three different aspects such as profitability, efficiency of assets utilization and financial leverage. Return on Equity (ROE) is also calculated in DuPont analysis. This study finds that both analysis models provide different rankings of the selected samples. Hypothesis testing based on Pearson's correlation, indicates that there is no correlation between rankings produced by DEA and DuPont analysis. The DEA ranking model proposed by Alirezaee and Asharian is unstable. The method cannot provide complete ranking because the values of Balance Index is equal and zero.

Comparative Protein Structure Modeling Using MODELLER

PubMed Central

Webb, Benjamin; Sali, Andrej

2016-01-01

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. PMID:27322406

Predicting Air Permeability of Handloom Fabrics: A Comparative Analysis of Regression and Artificial Neural Network Models

NASA Astrophysics Data System (ADS)

Mitra, Ashis; Majumdar, Prabal Kumar; Bannerjee, Debamalya

2013-03-01

This paper presents a comparative analysis of two modeling methodologies for the prediction of air permeability of plain woven handloom cotton fabrics. Four basic fabric constructional parameters namely ends per inch, picks per inch, warp count and weft count have been used as inputs for artificial neural network (ANN) and regression models. Out of the four regression models tried, interaction model showed very good prediction performance with a meager mean absolute error of 2.017 %. However, ANN models demonstrated superiority over the regression models both in terms of correlation coefficient and mean absolute error. The ANN model with 10 nodes in the single hidden layer showed very good correlation coefficient of 0.982 and 0.929 and mean absolute error of only 0.923 and 2.043 % for training and testing data respectively.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo

2011-01-01

Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…

Comparative Logic Modeling for Policy Analysis: The Case of HIV Testing Policy Change at the Department of Veterans Affairs

PubMed Central

Langer, Erika M; Gifford, Allen L; Chan, Kee

2011-01-01

Objective Logic models have been used to evaluate policy programs, plan projects, and allocate resources. Logic Modeling for policy analysis has been used rarely in health services research but can be helpful in evaluating the content and rationale of health policies. Comparative Logic Modeling is used here on human immunodeficiency virus (HIV) policy statements from the Department of Veterans Affairs (VA) and Centers for Disease Control and Prevention (CDC). We created visual representations of proposed HIV screening policy components in order to evaluate their structural logic and research-based justifications. Data Sources and Study Design We performed content analysis of VA and CDC HIV testing policy documents in a retrospective case study. Data Collection Using comparative Logic Modeling, we examined the content and primary sources of policy statements by the VA and CDC. We then quantified evidence-based causal inferences within each statement. Principal Findings VA HIV testing policy structure largely replicated that of the CDC guidelines. Despite similar design choices, chosen research citations did not overlap. The agencies used evidence to emphasize different components of the policies. Conclusion Comparative Logic Modeling can be used by health services researchers and policy analysts more generally to evaluate structural differences in health policies and to analyze research-based rationales used by policy makers. PMID:21689094

A comparative analysis of modeled and monitored ambient hazardous air pollutants in Texas: a novel approach using concordance correlation.

PubMed

Lupo, Philip J; Symanski, Elaine

2009-11-01

Often, in studies evaluating the health effects of hazardous air pollutants (HAPs), researchers rely on ambient air levels to estimate exposure. Two potential data sources are modeled estimates from the U.S. Environmental Protection Agency (EPA) Assessment System for Population Exposure Nationwide (ASPEN) and ambient air pollutant measurements from monitoring networks. The goal was to conduct comparisons of modeled and monitored estimates of HAP levels in the state of Texas using traditional approaches and a previously unexploited method, concordance correlation analysis, to better inform decisions regarding agreement. Census tract-level ASPEN estimates and monitoring data for all HAPs throughout Texas, available from the EPA Air Quality System, were obtained for 1990, 1996, and 1999. Monitoring sites were mapped to census tracts using U.S. Census data. Exclusions were applied to restrict the monitored data to measurements collected using a common sampling strategy with minimal missing values over time. Comparisons were made for 28 HAPs in 38 census tracts located primarily in urban areas throughout Texas. For each pollutant and by year of assessment, modeled and monitored air pollutant annual levels were compared using standard methods (i.e., ratios of model-to-monitor annual levels). Concordance correlation analysis was also used, which assesses linearity and agreement while providing a formal method of statistical inference. Forty-eight percent of the median model-to-monitor values fell between 0.5 and 2, whereas only 17% of concordance correlation coefficients were significant and greater than 0.5. On the basis of concordance correlation analysis, the findings indicate there is poorer agreement when compared with the previously applied ad hoc methods to assess comparability between modeled and monitored levels of ambient HAPs.

Comparative empirical analysis of flow-weighted transit route networks in R-space and evolution modeling

NASA Astrophysics Data System (ADS)

Huang, Ailing; Zang, Guangzhi; He, Zhengbing; Guan, Wei

2017-05-01

Urban public transit system is a typical mixed complex network with dynamic flow, and its evolution should be a process coupling topological structure with flow dynamics, which has received little attention. This paper presents the R-space to make a comparative empirical analysis on Beijing’s flow-weighted transit route network (TRN) and we found that both the Beijing’s TRNs in the year of 2011 and 2015 exhibit the scale-free properties. As such, we propose an evolution model driven by flow to simulate the development of TRNs with consideration of the passengers’ dynamical behaviors triggered by topological change. The model simulates that the evolution of TRN is an iterative process. At each time step, a certain number of new routes are generated driven by travel demands, which leads to dynamical evolution of new routes’ flow and triggers perturbation in nearby routes that will further impact the next round of opening new routes. We present the theoretical analysis based on the mean-field theory, as well as the numerical simulation for this model. The results obtained agree well with our empirical analysis results, which indicate that our model can simulate the TRN evolution with scale-free properties for distributions of node’s strength and degree. The purpose of this paper is to illustrate the global evolutional mechanism of transit network that will be used to exploit planning and design strategies for real TRNs.

A comparative analysis of hazard models for predicting debris flows in Madison County, VA

USGS Publications Warehouse

Morrissey, Meghan M.; Wieczorek, Gerald F.; Morgan, Benjamin A.

2001-01-01

During the rainstorm of June 27, 1995, roughly 330-750 mm of rain fell within a sixteen-hour period, initiating floods and over 600 debris flows in a small area (130 km2) of Madison County, Virginia. Field studies showed that the majority (70%) of these debris flows initiated with a thickness of 0.5 to 3.0 m in colluvium on slopes from 17 o to 41 o (Wieczorek et al., 2000). This paper evaluated and compared the approaches of SINMAP, LISA, and Iverson's (2000) transient response model for slope stability analysis by applying each model to the landslide data from Madison County. Of these three stability models, only Iverson's transient response model evaluated stability conditions as a function of time and depth. Iverson?s model would be the preferred method of the three models to evaluate landslide hazards on a regional scale in areas prone to rain-induced landslides as it considers both the transient and spatial response of pore pressure in its calculation of slope stability. The stability calculation used in SINMAP and LISA is similar and utilizes probability distribution functions for certain parameters. Unlike SINMAP that only considers soil cohesion, internal friction angle and rainfall-rate distributions, LISA allows the use of distributed data for all parameters, so it is the preferred model to evaluate slope stability over SINMAP. Results from all three models suggested similar soil and hydrologic properties for triggering the landslides that occurred during the 1995 storm in Madison County, Virginia. The colluvium probably had cohesion of less than 2KPa. The root-soil system is above the failure plane and consequently root strength and tree surcharge had negligible effect on slope stability. The result that the final location of the water table was near the ground surface is supported by the water budget analysis of the rainstorm conducted by Smith et al. (1996).

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

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

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by themore » observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.« less

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic

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

EPA Science Inventory

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...

Comparative Analysis.

DTIC Science & Technology

1987-11-01

differential qualita- tive (DQ) analysis, which solves the task, providing explanations suitable for use by design systems, automated diagnosis, intelligent...solves the task, providing explanations suitable for use by design systems, automated diagnosis, intelligent tutoring systems, and explanation based...comparative analysis as an important component; the explanation is used in many different ways. * One way method of automated design is the principlvd

Comparative Sensitivity Analysis of Muscle Activation Dynamics

PubMed Central

Günther, Michael; Götz, Thomas

2015-01-01

We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379

Linked Sensitivity Analysis, Calibration, and Uncertainty Analysis Using a System Dynamics Model for Stroke Comparative Effectiveness Research.

PubMed

Tian, Yuan; Hassmiller Lich, Kristen; Osgood, Nathaniel D; Eom, Kirsten; Matchar, David B

2016-11-01

As health services researchers and decision makers tackle more difficult problems using simulation models, the number of parameters and the corresponding degree of uncertainty have increased. This often results in reduced confidence in such complex models to guide decision making. To demonstrate a systematic approach of linked sensitivity analysis, calibration, and uncertainty analysis to improve confidence in complex models. Four techniques were integrated and applied to a System Dynamics stroke model of US veterans, which was developed to inform systemwide intervention and research planning: Morris method (sensitivity analysis), multistart Powell hill-climbing algorithm and generalized likelihood uncertainty estimation (calibration), and Monte Carlo simulation (uncertainty analysis). Of 60 uncertain parameters, sensitivity analysis identified 29 needing calibration, 7 that did not need calibration but significantly influenced key stroke outcomes, and 24 not influential to calibration or stroke outcomes that were fixed at their best guess values. One thousand alternative well-calibrated baselines were obtained to reflect calibration uncertainty and brought into uncertainty analysis. The initial stroke incidence rate among veterans was identified as the most influential uncertain parameter, for which further data should be collected. That said, accounting for current uncertainty, the analysis of 15 distinct prevention and treatment interventions provided a robust conclusion that hypertension control for all veterans would yield the largest gain in quality-adjusted life years. For complex health care models, a mixed approach was applied to examine the uncertainty surrounding key stroke outcomes and the robustness of conclusions. We demonstrate that this rigorous approach can be practical and advocate for such analysis to promote understanding of the limits of certainty in applying models to current decisions and to guide future data collection. © The Author(s) 2016.

Multi-criteria comparative evaluation of spallation reaction models

NASA Astrophysics Data System (ADS)

Andrianov, Andrey; Andrianova, Olga; Konobeev, Alexandr; Korovin, Yury; Kuptsov, Ilya

2017-09-01

This paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb.

Development of multivariate NTCP models for radiation-induced hypothyroidism: a comparative analysis.

PubMed

Cella, Laura; Liuzzi, Raffaele; Conson, Manuel; D'Avino, Vittoria; Salvatore, Marco; Pacelli, Roberto

2012-12-27

Hypothyroidism is a frequent late side effect of radiation therapy of the cervical region. Purpose of this work is to develop multivariate normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RHT) and to compare them with already existing NTCP models for RHT. Fifty-three patients treated with sequential chemo-radiotherapy for Hodgkin's lymphoma (HL) were retrospectively reviewed for RHT events. Clinical information along with thyroid gland dose distribution parameters were collected and their correlation to RHT was analyzed by Spearman's rank correlation coefficient (Rs). Multivariate logistic regression method using resampling methods (bootstrapping) was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). Models were tested against external published data on RHT and compared with other published NTCP models. If we express the thyroid volume exceeding X Gy as a percentage (Vx(%)), a two-variable NTCP model including V30(%) and gender resulted to be the optimal predictive model for RHT (Rs = 0.615, p < 0.001. AUC = 0.87). Conversely, if absolute thyroid volume exceeding X Gy (Vx(cc)) was analyzed, an NTCP model based on 3 variables including V30(cc), thyroid gland volume and gender was selected as the most predictive model (Rs = 0.630, p < 0.001. AUC = 0.85). The three-variable model performs better when tested on an external cohort characterized by large inter-individuals variation in thyroid volumes (AUC = 0.914, 95% CI 0.760-0.984). A comparable performance was found between our model and that proposed in the literature based on thyroid gland mean dose and volume (p = 0.264). The absolute volume of thyroid gland exceeding 30 Gy in combination with thyroid gland volume and gender provide an NTCP model for RHT with improved prediction capability not only within our patient population but also in an external

Comparative analysis of detection methods for congenital cytomegalovirus infection in a Guinea pig model.

PubMed

Park, Albert H; Mann, David; Error, Marc E; Miller, Matthew; Firpo, Matthew A; Wang, Yong; Alder, Stephen C; Schleiss, Mark R

2013-01-01

To assess the validity of the guinea pig as a model for congenital cytomegalovirus (CMV) infection by comparing the effectiveness of detecting the virus by real-time polymerase chain reaction (PCR) in blood, urine, and saliva. Case-control study. Academic research. Eleven pregnant Hartley guinea pigs. Blood, urine, and saliva samples were collected from guinea pig pups delivered from pregnant dams inoculated with guinea pig CMV. These samples were then evaluated for the presence of guinea pig CMV by real-time PCR assuming 100% transmission. Thirty-one pups delivered from 9 inoculated pregnant dams and 8 uninfected control pups underwent testing for guinea pig CMV and for auditory brainstem response hearing loss. Repeated-measures analysis of variance demonstrated no statistically significantly lower weight for the infected pups compared with the noninfected control pups. Six infected pups demonstrated auditory brainstem response hearing loss. The sensitivity and specificity of the real-time PCR assay on saliva samples were 74.2% and 100.0%, respectively. The sensitivity of the real-time PCR on blood and urine samples was significantly lower than that on saliva samples. Real-time PCR assays of blood, urine, and saliva revealed that saliva samples show high sensitivity and specificity for detecting congenital CMV infection in guinea pigs. This finding is consistent with recent screening studies in human newborns. The guinea pig may be a good animal model in which to compare different diagnostic assays for congenital CMV infection.

Comparative Analysis of Soft Computing Models in Prediction of Bending Rigidity of Cotton Woven Fabrics

NASA Astrophysics Data System (ADS)

Guruprasad, R.; Behera, B. K.

2015-10-01

Quantitative prediction of fabric mechanical properties is an essential requirement for design engineering of textile and apparel products. In this work, the possibility of prediction of bending rigidity of cotton woven fabrics has been explored with the application of Artificial Neural Network (ANN) and two hybrid methodologies, namely Neuro-genetic modeling and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling. For this purpose, a set of cotton woven grey fabrics was desized, scoured and relaxed. The fabrics were then conditioned and tested for bending properties. With the database thus created, a neural network model was first developed using back propagation as the learning algorithm. The second model was developed by applying a hybrid learning strategy, in which genetic algorithm was first used as a learning algorithm to optimize the number of neurons and connection weights of the neural network. The Genetic algorithm optimized network structure was further allowed to learn using back propagation algorithm. In the third model, an ANFIS modeling approach was attempted to map the input-output data. The prediction performances of the models were compared and a sensitivity analysis was reported. The results show that the prediction by neuro-genetic and ANFIS models were better in comparison with that of back propagation neural network model.

Statistical correlation analysis for comparing vibration data from test and analysis

NASA Technical Reports Server (NTRS)

Butler, T. G.; Strang, R. F.; Purves, L. R.; Hershfeld, D. J.

1986-01-01

A theory was developed to compare vibration modes obtained by NASTRAN analysis with those obtained experimentally. Because many more analytical modes can be obtained than experimental modes, the analytical set was treated as expansion functions for putting both sources in comparative form. The dimensional symmetry was developed for three general cases: nonsymmetric whole model compared with a nonsymmetric whole structural test, symmetric analytical portion compared with a symmetric experimental portion, and analytical symmetric portion with a whole experimental test. The theory was coded and a statistical correlation program was installed as a utility. The theory is established with small classical structures.

Comparative Modelling of the Spectra of Cool Giants

NASA Technical Reports Server (NTRS)

Lebzelter, T.; Heiter, U.; Abia, C.; Eriksson, K.; Ireland, M.; Neilson, H.; Nowotny, W; Maldonado, J; Merle, T.; Peterson, R.;

Comparative and Evolutionary Analysis of Grass Pollen Allergens Using Brachypodium distachyon as a Model System

PubMed Central

Sharma, Akanksha; Sharma, Niharika; Bhalla, Prem; Singh, Mohan

2017-01-01

Comparative genomics have facilitated the mining of biological information from a genome sequence, through the detection of similarities and differences with genomes of closely or more distantly related species. By using such comparative approaches, knowledge can be transferred from the model to non-model organisms and insights can be gained in the structural and evolutionary patterns of specific genes. In the absence of sequenced genomes for allergenic grasses, this study was aimed at understanding the structure, organisation and expression profiles of grass pollen allergens using the genomic data from Brachypodium distachyon as it is phylogenetically related to the allergenic grasses. Combining genomic data with the anther RNA-Seq dataset revealed 24 pollen allergen genes belonging to eight allergen groups mapping on the five chromosomes in B. distachyon. High levels of anther-specific expression profiles were observed for the 24 identified putative allergen-encoding genes in Brachypodium. The genomic evidence suggests that gene encoding the group 5 allergen, the most potent trigger of hay fever and allergic asthma originated as a pollen specific orphan gene in a common grass ancestor of Brachypodium and Triticiae clades. Gene structure analysis showed that the putative allergen-encoding genes in Brachypodium either lack or contain reduced number of introns. Promoter analysis of the identified Brachypodium genes revealed the presence of specific cis-regulatory sequences likely responsible for high anther/pollen-specific expression. With the identification of putative allergen-encoding genes in Brachypodium, this study has also described some important plant gene families (e.g. expansin superfamily, EF-Hand family, profilins etc) for the first time in the model plant Brachypodium. Altogether, the present study provides new insights into structural characterization and evolution of pollen allergens and will further serve as a base for their functional

Comparative and Evolutionary Analysis of Grass Pollen Allergens Using Brachypodium distachyon as a Model System.

PubMed

Sharma, Akanksha; Sharma, Niharika; Bhalla, Prem; Singh, Mohan

2017-01-01

Comparative genomics have facilitated the mining of biological information from a genome sequence, through the detection of similarities and differences with genomes of closely or more distantly related species. By using such comparative approaches, knowledge can be transferred from the model to non-model organisms and insights can be gained in the structural and evolutionary patterns of specific genes. In the absence of sequenced genomes for allergenic grasses, this study was aimed at understanding the structure, organisation and expression profiles of grass pollen allergens using the genomic data from Brachypodium distachyon as it is phylogenetically related to the allergenic grasses. Combining genomic data with the anther RNA-Seq dataset revealed 24 pollen allergen genes belonging to eight allergen groups mapping on the five chromosomes in B. distachyon. High levels of anther-specific expression profiles were observed for the 24 identified putative allergen-encoding genes in Brachypodium. The genomic evidence suggests that gene encoding the group 5 allergen, the most potent trigger of hay fever and allergic asthma originated as a pollen specific orphan gene in a common grass ancestor of Brachypodium and Triticiae clades. Gene structure analysis showed that the putative allergen-encoding genes in Brachypodium either lack or contain reduced number of introns. Promoter analysis of the identified Brachypodium genes revealed the presence of specific cis-regulatory sequences likely responsible for high anther/pollen-specific expression. With the identification of putative allergen-encoding genes in Brachypodium, this study has also described some important plant gene families (e.g. expansin superfamily, EF-Hand family, profilins etc) for the first time in the model plant Brachypodium. Altogether, the present study provides new insights into structural characterization and evolution of pollen allergens and will further serve as a base for their functional

Tuning supersymmetric models at the LHC: a comparative analysis at two-loop level.

NASA Astrophysics Data System (ADS)

Ghilencea, D. M.; Lee, H. M.; Park, M.

2012-07-01

We provide a comparative study of the fine tuning amount (Δ) at the two-loop leading log level in supersymmetric models commonly used in SUSY searches at the LHC. These are the constrained MSSM (CMSSM), non-universal Higgs masses models (NUHM1, NUHM2), non-universal gaugino masses model (NUGM) and GUT related gaugino masses models (NUGMd). Two definitions of the fine tuning are used, the first (Δmax) measures maximal fine-tuning w.r.t. individual parameters while the second (Δ q ) adds their contribution in "quadrature". As a direct consequence of two theoretical constraints (the EW minimum conditions), fine tuning (Δ q ) emerges at the mathematical level as a suppressing factor (effective prior) of the averaged likelihood ( L ) under the priors, under the integral of the global probability of measuring the data (Bayesian evidence p( D)). For each model, there is little difference between Δ q , Δmax in the region allowed by the data, with similar behaviour as functions of the Higgs, gluino, stop mass or SUSY scale ( {m_{{SUSY}}} = {( {{m_{{overline t 1}}}{m_{{overline t 2}}}} )^{{{{1} / {2} .}}}} ) or dark matter and g - 2 constraints. The analysis has the advantage that by replacing any of these mass scales or constraints by their latest bounds one easily infers for each model the value of Δ q , Δmax or vice versa. For all models, minimal fine tuning is achieved for M higgs near 115 GeV with a Δ q ≈ Δmax ≈ 10 to 100 depending on the model, and in the CMSSM this is actually a global minimum. Due to a strong (≈ exponential) dependence of Δ on M higgs, for a Higgs mass near 125 GeV, the above values of Δ q ≈ Δmax increase to between 500 and 1000. Possible corrections to these values are briefly discussed.

Comparing the High School English Curriculum in Turkey through Multi-Analysis

ERIC Educational Resources Information Center

Batdi, Veli

2017-01-01

This study aimed to compare the High School English Curriculum (HSEC) in accordance with Stufflebeam's context, input, process and product (CIPP) model through multi-analysis. The research includes both quantitative and qualitative aspects. A descriptive analysis was operated through Rasch Measurement Model; SPSS program for the quantitative…

BSM2 Plant-Wide Model construction and comparative analysis with other methodologies for integrated modelling.

PubMed

Grau, P; Vanrolleghem, P; Ayesa, E

2007-01-01

In this paper, a new methodology for integrated modelling of the WWTP has been used for the construction of the Benchmark Simulation Model N degrees 2 (BSM2). The transformations-approach proposed in this methodology does not require the development of specific transformers to interface unit process models and allows the construction of tailored models for a particular WWTP guaranteeing the mass and charge continuity for the whole model. The BSM2 PWM constructed as case study, is evaluated by means of simulations under different scenarios and its validity in reproducing water and sludge lines in WWTP is demonstrated. Furthermore the advantages that this methodology presents compared to other approaches for integrated modelling are verified in terms of flexibility and coherence.

Comparative Analysis of Vertebrate Diurnal/Circadian Transcriptomes

PubMed Central

Boyle, Greg; Richter, Kerstin; Priest, Henry D.; Traver, David; Mockler, Todd C.; Chang, Jeffrey T.; Kay, Steve A.

2017-01-01

From photosynthetic bacteria to mammals, the circadian clock evolved to track diurnal rhythms and enable organisms to anticipate daily recurring changes such as temperature and light. It orchestrates a broad spectrum of physiology such as the sleep/wake and eating/fasting cycles. While we have made tremendous advances in our understanding of the molecular details of the circadian clock mechanism and how it is synchronized with the environment, we still have rudimentary knowledge regarding its connection to help regulate diurnal physiology. One potential reason is the sheer size of the output network. Diurnal/circadian transcriptomic studies are reporting that around 10% of the expressed genome is rhythmically controlled. Zebrafish is an important model system for the study of the core circadian mechanism in vertebrate. As Zebrafish share more than 70% of its genes with human, it could also be an additional model in addition to rodent for exploring the diurnal/circadian output with potential for translational relevance. Here we performed comparative diurnal/circadian transcriptome analysis with established mouse liver and other tissue datasets. First, by combining liver tissue sampling in a 48h time series, transcription profiling using oligonucleotide arrays and bioinformatics analysis, we profiled rhythmic transcripts and identified 2609 rhythmic genes. The comparative analysis revealed interesting features of the output network regarding number of rhythmic genes, proportion of tissue specific genes and the extent of transcription factor family expression. Undoubtedly, the Zebrafish model system will help identify new vertebrate outputs and their regulators and provides leads for further characterization of the diurnal cis-regulatory network. PMID:28076377

Comparative analysis of model behaviour for flood prediction purposes using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Casper, M. C.; Grundmann, J.; Buchholz, O.

2009-03-01

Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing different aspects of the system behaviour equally well. Of course, this also applies to the reproduction of peak discharges by a simulation model which is of particular interest regarding the flood forecasting problem. In our study we use a Self-Organizing Map (SOM) in combination with index measures which are derived from the flow duration curve in order to examine the conditions under which three different distributed watershed models are capable of reproducing flood events present in the calibration data. These indices are specifically conceptualized to extract data on the peak discharge characteristics of model output time series which are obtained from Monte-Carlo simulations with the distributed watershed models NASIM, LARSIM and WaSIM-ETH. The SOM helps to analyze this data by producing a discretized mapping of their distribution in the index space onto a two dimensional plane such that their pattern and consequently the patterns of model behaviour can be conveyed in a comprehensive manner. It is demonstrated how the SOM provides useful information about details of model behaviour and also helps identifying the model parameters that are relevant for the reproduction of peak discharges and thus for flood prediction problems. It is further shown how the SOM can be used to identify those parameter sets from among the Monte-Carlo data that most closely approximate the peak discharges of a measured time series. The results represent the characteristics of the observed time series with partially superior accuracy than the reference simulation obtained by implementing a simple calibration strategy using the global optimization algorithm SCE-UA. The most prominent advantage of using SOM in the context of model analysis is that it allows to comparatively evaluating the

Comparative analysis of stress in a new proposal of dental implants.

PubMed

Valente, Mariana Lima da Costa; de Castro, Denise Tornavoi; Macedo, Ana Paula; Shimano, Antonio Carlos; Dos Reis, Andréa Cândido

2017-08-01

The purpose of this study was to compare, through photoelastic analysis, the stress distribution around conventional and modified external hexagon (EH) and morse taper (MT) dental implant connections. Four photoelastic models were prepared (n=1): Model 1 - conventional EH cylindrical implant (Ø 4.0mm×11mm - Neodent®), Model 2 - modified EH cylindrical implant, Model 3 - conventional MT Conical implant (Ø 4.3mm×10mm - Neodent®) and Model 4 - modified MT conical implant. 100 and 150N axial and oblique loads (30° tilt) were applied in the devices coupled to the implants. A plane transmission polariscope was used in the analysis of fringes and each position of interest was recorded by a digital camera. The Tardy method was used to quantify the fringe order (n), that calculates the maximum shear stress (τ) value in each selected point. The results showed lower stress concentration in the modified cylindrical implant (EH) compared to the conventional model, with application of 150N axial and 100N oblique loads. Lower stress was observed for the modified conical (MT) implant with the application of 100 and 150N oblique loads, which was not observed for the conventional implant model. The comparative analysis of the models showed that the new design proposal generates good stress distribution, especially in the cervical third, suggesting the preservation of bone tissue in the bone crest region. Copyright © 2017 Elsevier B.V. All rights reserved.

The aquatic animals' transcriptome resource for comparative functional analysis.

PubMed

Chou, Chih-Hung; Huang, Hsi-Yuan; Huang, Wei-Chih; Hsu, Sheng-Da; Hsiao, Chung-Der; Liu, Chia-Yu; Chen, Yu-Hung; Liu, Yu-Chen; Huang, Wei-Yun; Lee, Meng-Lin; Chen, Yi-Chang; Huang, Hsien-Da

2018-05-09

Aquatic animals have great economic and ecological importance. Among them, non-model organisms have been studied regarding eco-toxicity, stress biology, and environmental adaptation. Due to recent advances in next-generation sequencing techniques, large amounts of RNA-seq data for aquatic animals are publicly available. However, currently there is no comprehensive resource exist for the analysis, unification, and integration of these datasets. This study utilizes computational approaches to build a new resource of transcriptomic maps for aquatic animals. This aquatic animal transcriptome map database dbATM provides de novo assembly of transcriptome, gene annotation and comparative analysis of more than twenty aquatic organisms without draft genome. To improve the assembly quality, three computational tools (Trinity, Oases and SOAPdenovo-Trans) were employed to enhance individual transcriptome assembly, and CAP3 and CD-HIT-EST software were then used to merge these three assembled transcriptomes. In addition, functional annotation analysis provides valuable clues to gene characteristics, including full-length transcript coding regions, conserved domains, gene ontology and KEGG pathways. Furthermore, all aquatic animal genes are essential for comparative genomics tasks such as constructing homologous gene groups and blast databases and phylogenetic analysis. In conclusion, we establish a resource for non model organism aquatic animals, which is great economic and ecological importance and provide transcriptomic information including functional annotation and comparative transcriptome analysis. The database is now publically accessible through the URL http://dbATM.mbc.nctu.edu.tw/ .

Comparative study of two approaches to model the offshore fish cages

NASA Astrophysics Data System (ADS)

Zhao, Yun-peng; Wang, Xin-xin; Decew, Jud; Tsukrov, Igor; Bai, Xiao-dong; Bi, Chun-wei

2015-06-01

The goal of this paper is to provide a comparative analysis of two commonly used approaches to discretize offshore fish cages: the lumped-mass approach and the finite element technique. Two case studies are chosen to compare predictions of the LMA (lumped-mass approach) and FEA (finite element analysis) based numerical modeling techniques. In both case studies, we consider several loading conditions consisting of different uniform currents and monochromatic waves. We investigate motion of the cage, its deformation, and the resultant tension in the mooring lines. Both model predictions are sufficient close to the experimental data, but for the first experiment, the DUT-FlexSim predictions are slightly more accurate than the ones provided by Aqua-FE™. According to the comparisons, both models can be successfully utilized to the design and analysis of the offshore fish cages provided that an appropriate safety factor is chosen.

A Comparative Analysis of Financial Reporting Models for Private and Public Sector Organizations.

DTIC Science & Technology

1995-12-01

The objective of this thesis was to describe and compare different existing and evolving financial reporting models used in both the public and...private sector. To accomplish the objective, this thesis identified the existing financial reporting models for private sector business organizations...private sector nonprofit organizations, and state and local governments, as well as the evolving financial reporting model for the federal government

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures.

PubMed

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model-dimensional or discrete-as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (d IG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

Case Problems for Problem-Based Pedagogical Approaches: A Comparative Analysis

ERIC Educational Resources Information Center

Dabbagh, Nada; Dass, Susan

2013-01-01

A comparative analysis of 51 case problems used in five problem-based pedagogical models was conducted to examine whether there are differences in their characteristics and the implications of such differences on the selection and generation of ill-structured case problems. The five pedagogical models were: situated learning, goal-based scenario,…

Two-Year versus One-Year Head Start Program Impact: Addressing Selection Bias by Comparing Regression Modeling with Propensity Score Analysis

ERIC Educational Resources Information Center

Leow, Christine; Wen, Xiaoli; Korfmacher, Jon

2015-01-01

This article compares regression modeling and propensity score analysis as different types of statistical techniques used in addressing selection bias when estimating the impact of two-year versus one-year Head Start on children's school readiness. The analyses were based on the national Head Start secondary dataset. After controlling for…

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

PubMed Central

Hondula, David M.; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-01-01

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634 PMID:28885979

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

PubMed

Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-08-16

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

FINDING A METHOD FOR THE MADNESS: A COMPARATIVE ANALYSIS OF STRATEGIC DESIGN METHODOLOGIES

DTIC Science & Technology

2017-06-01

FINDING A METHOD FOR THE MADNESS: A COMPARATIVE ANALYSIS OF STRATEGIC DESIGN METHODOLOGIES BY AMANDA DONNELLY A THESIS...work develops a comparative model for strategic design methodologies, focusing on the primary elements of vision, time, process, communication and...collaboration, and risk assessment. My analysis dissects and compares three potential design methodologies including, net assessment, scenarios and

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

2012-01-01

Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897

Specialized stroke services: a meta-analysis comparing three models of care.

PubMed

Foley, Norine; Salter, Katherine; Teasell, Robert

2007-01-01

Using previously published data, the purpose of this study was to identify and discriminate between three different forms of inpatient stroke care based on timing and duration of treatment and to compare the results of clinically important outcomes. Randomized controlled trials, including a recent review of inpatient stroke unit/rehabilitation care, were identified and grouped into three models of care as follows: (a) acute stroke unit care (patients admitted within 36 h of stroke onset and remaining for up to 2 weeks; n = 5), (b) units combining acute and rehabilitative care (combined; n = 4), and (c) rehabilitation units where patients were transferred onto the service approximately 2 weeks following stroke (post-acute; n = 5). Pooled analyses for the outcomes of mortality, combined death and dependency and length of hospital stay were calculated for each model of care, compared to conventional care. All three models of care were associated with significant reductions in the odds of combined death and dependency; however, acute stroke units were not associated with significant reductions in mortality when this outcome was analyzed separately (OR 0.80; 95% CI: 0.61-1.03). Post-acute stroke units were associated with the greatest reduction in the odds of mortality (OR 0.60; 95% CI: 0.44-0.81). Significant reductions in length of hospital stay were associated with combined stroke units only (weighted mean difference -14 days; 95% CI: -27 to -2). Overall, specialized stroke services were associated with significant reductions in mortality, death and dependency and length of hospital stay although not every model of care was associated with equal benefit.

Emergent structures and understanding from a comparative uncertainty analysis of the FUSE rainfall-runoff modelling platform for >1,100 catchments

NASA Astrophysics Data System (ADS)

Freer, J. E.; Odoni, N. A.; Coxon, G.; Bloomfield, J.; Clark, M. P.; Greene, S.; Johnes, P.; Macleod, C.; Reaney, S. M.

2013-12-01

If we are to learn about catchments and their hydrological function then a range of analysis techniques can be proposed from analysing observations to building complex physically based models using detailed attributes of catchment characteristics. Decisions regarding which technique is fit for a specific purpose will depend on the data available, computing resources, and the underlying reasons for the study. Here we explore defining catchment function in a relatively general sense expressed via a comparison of multiple model structures within an uncertainty analysis framework. We use the FUSE (Framework for Understanding Structural Errors - Clark et al., 2008) rainfall-runoff modelling platform and the GLUE (Generalised Likelihood Uncertainty Estimation - Beven and Freer, 2001) uncertainty analysis framework. Using these techniques we assess two main outcomes: 1) Benchmarking our predictive capability using discharge performance metrics for a diverse range of catchments across the UK 2) evaluating emergent behaviour for each catchment and/or region expressed as ';best performing' model structures that may be equally plausible representations of catchment behaviour. We shall show how such comparative hydrological modelling studies show patterns of emergent behaviour linked both to seasonal responses and to different geoclimatic regions. These results have implications for the hydrological community regarding how models can help us learn about places as hypothesis testing tools. Furthermore we explore what the limits are to such an analysis when dealing with differing data quality and information content from ';pristine' to less well characterised and highly modified catchment domains. This research has been piloted in the UK as part of the Environmental Virtual Observatory programme (EVOp), funded by NERC to demonstrate the use of cyber-infrastructure and cloud computing resources to develop better methods of linking data and models and to support scenario analysis

Comparative analysis through probability distributions of a data set

NASA Astrophysics Data System (ADS)

Cristea, Gabriel; Constantinescu, Dan Mihai

2018-02-01

In practice, probability distributions are applied in such diverse fields as risk analysis, reliability engineering, chemical engineering, hydrology, image processing, physics, market research, business and economic research, customer support, medicine, sociology, demography etc. This article highlights important aspects of fitting probability distributions to data and applying the analysis results to make informed decisions. There are a number of statistical methods available which can help us to select the best fitting model. Some of the graphs display both input data and fitted distributions at the same time, as probability density and cumulative distribution. The goodness of fit tests can be used to determine whether a certain distribution is a good fit. The main used idea is to measure the "distance" between the data and the tested distribution, and compare that distance to some threshold values. Calculating the goodness of fit statistics also enables us to order the fitted distributions accordingly to how good they fit to data. This particular feature is very helpful for comparing the fitted models. The paper presents a comparison of most commonly used goodness of fit tests as: Kolmogorov-Smirnov, Anderson-Darling, and Chi-Squared. A large set of data is analyzed and conclusions are drawn by visualizing the data, comparing multiple fitted distributions and selecting the best model. These graphs should be viewed as an addition to the goodness of fit tests.

Laparoscopic versus open-component separation: a comparative analysis in a porcine model.

PubMed

Rosen, Michael J; Williams, Christina; Jin, Judy; McGee, Michael F; Schomisch, Steve; Marks, Jeffrey; Ponsky, Jeffrey

2007-09-01

The ideal surgical treatment for complicated ventral hernias remains elusive. Traditional component separation provides local advancement of native tissue for tension-free closure without prosthetic materials. This technique requires an extensive subcutaneous dissection with division of perforating vessels predisposing to skin-flap necrosis and complicated wound infections. A minimally invasive component separation may decrease wound complication rates; however, the adequacy of the myofascial advancement has not been studied. Five 25-kg pigs underwent bilateral laparoscopic component separation. A 10-mm incision was made lateral to the rectus abdominus muscle. The external oblique fascia was incised, and a dissecting balloon was inflated between the internal and external oblique muscles. Two additional ports were placed in the intermuscular space. The external oblique was incised from the costal margin to the inguinal ligament. The maximal abdominal wall advancement was recorded. A formal open-component separation was performed and maximal advancement 5 cm superior and 5 cm inferior to the umbilicus was recorded for comparison. Groups were compared using standard statistical analysis. The laparoscopic component separation was completed successfully in all animals, with a mean of 22 min/side. Laparoscopic component separation yielded 3.9 cm (SD 1.1) of fascial advancement above the umbilicus, whereas 4.4 cm (1.2) was obtained after open release (P = .24). Below the umbilicus, laparoscopic release achieved 5.0 cm (1.0) of advancement, whereas 5.8 cm (1.2) was gained after open release (P = .13). The minimally invasive component separation achieved an average of 86% of the myofascial advancement compared with a formal open release. The laparoscopic approach does not require extensive subcutaneous dissection and might theoretically result in a decreased incidence or decreased complexity of postoperative wound infections or skin-flap necrosis. Based on our preliminary

Comparative analysis of methods for modeling the penetration and plane-parallel motion of conical projectiles in soil

NASA Astrophysics Data System (ADS)

Bazhenov, V. G.; Bragov, A. M.; Konstantinov, A. Yu.; Kotov, V. L.

2015-05-01

This paper presents an analysis of the accuracy of known and new modeling methods using the hypothesis of local and plane sections for solution of problems of the impact and plane-parallel motion of conical bodies at an angle to the free surface of the half-space occupied by elastoplastic soil. The parameters of the local interaction model that is quadratic in velocity are determined by solving the one-dimensional problem of the expansion of a spherical cavity. Axisymmetric problems for each of the meridional section are solved simultaneously neglecting mass and momentum transfer in the circumferential direction and using an approach based on the hypothesis of plane sections. The dynamic and kinematic parameters of oblique penetration obtained using modified models are compared with the results of computer simulation in a three-dimensional formulation. The results obtained with regard to the contact stress distribution along the generator of the pointed cone are in satisfactory agreement.

Preservation of protein clefts in comparative models.

PubMed

Piedra, David; Lois, Sergi; de la Cruz, Xavier

2008-01-16

Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein. We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality - measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues. We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and applicability of his/her cleft models

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These

Least-Squares Regression and Spectral Residual Augmented Classical Least-Squares Chemometric Models for Stability-Indicating Analysis of Agomelatine and Its Degradation Products: A Comparative Study.

PubMed

Naguib, Ibrahim A; Abdelrahman, Maha M; El Ghobashy, Mohamed R; Ali, Nesma A

2016-01-01

Two accurate, sensitive, and selective stability-indicating methods are developed and validated for simultaneous quantitative determination of agomelatine (AGM) and its forced degradation products (Deg I and Deg II), whether in pure forms or in pharmaceutical formulations. Partial least-squares regression (PLSR) and spectral residual augmented classical least-squares (SRACLS) are two chemometric models that are being subjected to a comparative study through handling UV spectral data in range (215-350 nm). For proper analysis, a three-factor, four-level experimental design was established, resulting in a training set consisting of 16 mixtures containing different ratios of interfering species. An independent test set consisting of eight mixtures was used to validate the prediction ability of the suggested models. The results presented indicate the ability of mentioned multivariate calibration models to analyze AGM, Deg I, and Deg II with high selectivity and accuracy. The analysis results of the pharmaceutical formulations were statistically compared to the reference HPLC method, with no significant differences observed regarding accuracy and precision. The SRACLS model gives comparable results to the PLSR model; however, it keeps the qualitative spectral information of the classical least-squares algorithm for analyzed components.

Comparative Cognitive Task Analysis

DTIC Science & Technology

2007-01-01

is to perform a task analyses to determine how people operate in a specific domain on a specific task. Cognitive Task Analysis (CTA) is a set of...accomplish a task. In this chapter, we build on CTA methods by suggesting that comparative cognitive task analysis (C2TA) can help solve the aforementioned

Navigating the complexities of qualitative comparative analysis: case numbers, necessity relations, and model ambiguities.

PubMed

Thiem, Alrik

2014-12-01

In recent years, the method of Qualitative Comparative Analysis (QCA) has been enjoying increasing levels of popularity in evaluation and directly neighboring fields. Its holistic approach to causal data analysis resonates with researchers whose theories posit complex conjunctions of conditions and events. However, due to QCA's relative immaturity, some of its technicalities and objectives have not yet been well understood. In this article, I seek to raise awareness of six pitfalls of employing QCA with regard to the following three central aspects: case numbers, necessity relations, and model ambiguities. Most importantly, I argue that case numbers are irrelevant to the methodological choice of QCA or any of its variants, that necessity is not as simple a concept as it has been suggested by many methodologists, and that doubt must be cast on the determinacy of virtually all results presented in past QCA research. By means of empirical examples from published articles, I explain the background of these pitfalls and introduce appropriate procedures, partly with reference to current software, that help avoid them. QCA carries great potential for scholars in evaluation and directly neighboring areas interested in the analysis of complex dependencies in configurational data. If users beware of the pitfalls introduced in this article, and if they avoid mechanistic adherence to doubtful "standards of good practice" at this stage of development, then research with QCA will gain in quality, as a result of which a more solid foundation for cumulative knowledge generation and well-informed policy decisions will also be created. © The Author(s) 2014.

COMPARING THE UTILITY OF MULTIMEDIA MODELS FOR HUMAN AND ECOLOGICAL EXPOSURE ANALYSIS: TWO CASES

EPA Science Inventory

A number of models are available for exposure assessment; however, few are used as tools for both human and ecosystem risks. This discussion will consider two modeling frameworks that have recently been used to support human and ecological decision making. The study will compare ...

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures

PubMed Central

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model—dimensional or discrete—as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought. PMID:25926805

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

PubMed Central

Monir, Md. Mamun; Zhu, Jun

2017-01-01

Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101

Neo-Deterministic and Probabilistic Seismic Hazard Assessments: a Comparative Analysis

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Magrin, Andrea; Nekrasova, Anastasia; Kossobokov, Vladimir; Panza, Giuliano F.

2016-04-01

Objective testing is the key issue towards any reliable seismic hazard assessment (SHA). Different earthquake hazard maps must demonstrate their capability in anticipating ground shaking from future strong earthquakes before an appropriate use for different purposes - such as engineering design, insurance, and emergency management. Quantitative assessment of maps performances is an essential step also in scientific process of their revision and possible improvement. Cross-checking of probabilistic models with available observations and independent physics based models is recognized as major validation procedure. The existing maps from the classical probabilistic seismic hazard analysis (PSHA), as well as those from the neo-deterministic analysis (NDSHA), which have been already developed for several regions worldwide (including Italy, India and North Africa), are considered to exemplify the possibilities of the cross-comparative analysis in spotting out limits and advantages of different methods. Where the data permit, a comparative analysis versus the documented seismic activity observed in reality is carried out, showing how available observations about past earthquakes can contribute to assess performances of the different methods. Neo-deterministic refers to a scenario-based approach, which allows for consideration of a wide range of possible earthquake sources as the starting point for scenarios constructed via full waveforms modeling. The method does not make use of empirical attenuation models (i.e. Ground Motion Prediction Equations, GMPE) and naturally supplies realistic time series of ground shaking (i.e. complete synthetic seismograms), readily applicable to complete engineering analysis and other mitigation actions. The standard NDSHA maps provide reliable envelope estimates of maximum seismic ground motion from a wide set of possible scenario earthquakes, including the largest deterministically or historically defined credible earthquake. In addition

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study

PubMed Central

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias

2018-01-01

Abstract Objective To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) (“living” network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Design Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Data sources Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Eligibility criteria for study selection Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Outcomes and analysis Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. Results 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis

A comparative analysis of speed profile models for wrist pointing movements.

PubMed

Vaisman, Lev; Dipietro, Laura; Krebs, Hermano Igo

2013-09-01

Following two decades of design and clinical research on robot-mediated therapy for the shoulder and elbow, therapeutic robotic devices for other joints are being proposed: several research groups including ours have designed robots for the wrist, either to be used as stand-alone devices or in conjunction with shoulder and elbow devices. However, in contrast with robots for the shoulder and elbow which were able to take advantage of descriptive kinematic models developed in neuroscience for the past 30 years, design of wrist robots controllers cannot rely on similar prior art: wrist movement kinematics has been largely unexplored. This study aimed at examining speed profiles of fast, visually evoked, visually guided, target-directed human wrist pointing movements. One thousand three-hundred ninety-eight (1398) trials were recorded from seven unimpaired subjects who performed center-out flexion/extension and abduction/adduction wrist movements and fitted with 19 models previously proposed for describing reaching speed profiles. A nonlinear, least squares optimization procedure extracted parameters' sets that minimized error between experimental and reconstructed data. Models' performances were compared based on their ability to reconstruct experimental data. Results suggest that the support-bounded lognormal is the best model for speed profiles of fast, wrist pointing movements. Applications include design of control algorithms for therapeutic wrist robots and quantitative metrics of motor recovery.

Comparing flood loss models of different complexity

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno

2013-04-01

Any deliberation on flood risk requires the consideration of potential flood losses. In particular, reliable flood loss models are needed to evaluate cost-effectiveness of mitigation measures, to assess vulnerability, for comparative risk analysis and financial appraisal during and after floods. In recent years, considerable improvements have been made both concerning the data basis and the methodological approaches used for the development of flood loss models. Despite of that, flood loss models remain an important source of uncertainty. Likewise the temporal and spatial transferability of flood loss models is still limited. This contribution investigates the predictive capability of different flood loss models in a split sample cross regional validation approach. For this purpose, flood loss models of different complexity, i.e. based on different numbers of explaining variables, are learned from a set of damage records that was obtained from a survey after the Elbe flood in 2002. The validation of model predictions is carried out for different flood events in the Elbe and Danube river basins in 2002, 2005 and 2006 for which damage records are available from surveys after the flood events. The models investigated are a stage-damage model, the rule based model FLEMOps+r as well as novel model approaches which are derived using data mining techniques of regression trees and Bayesian networks. The Bayesian network approach to flood loss modelling provides attractive additional information concerning the probability distribution of both model predictions and explaining variables.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study.

PubMed

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias; Salanti, Georgia

2018-02-28

To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) ("living" network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10

Comparative Analysis on Nonlinear Models for Ron Gasoline Blending Using Neural Networks

NASA Astrophysics Data System (ADS)

Aguilera, R. Carreño; Yu, Wen; Rodríguez, J. C. Tovar; Mosqueda, M. Elena Acevedo; Ortiz, M. Patiño; Juarez, J. J. Medel; Bautista, D. Pacheco

The blending process always being a nonlinear process is difficult to modeling, since it may change significantly depending on the components and the process variables of each refinery. Different components can be blended depending on the existing stock, and the chemical characteristics of each component are changing dynamically, they all are blended until getting the expected specification in different properties required by the customer. One of the most relevant properties is the Octane, which is difficult to control in line (without the component storage). Since each refinery process is quite different, a generic gasoline blending model is not useful when a blending in line wants to be done in a specific process. A mathematical gasoline blending model is presented in this paper for a given process described in state space as a basic gasoline blending process description. The objective is to adjust the parameters allowing the blending gasoline model to describe a signal in its trajectory, representing in neural networks extreme learning machine method and also for nonlinear autoregressive-moving average (NARMA) in neural networks method, such that a comparative work be developed.

Comparative Analysis of Academic Grades in Compulsory Secondary Education in Spain Using Statistical Techniques

ERIC Educational Resources Information Center

Veas, Alejandro; Gilar, Raquel; Miñano, Pablo; Castejón, Juan Luis

2017-01-01

The present study, based on the construct comparability approach, performs a comparative analysis of general points average for seven courses, using exploratory factor analysis (EFA) and the Partial Credit model (PCM) with a sample of 1398 student subjects (M = 12.5, SD = 0.67) from 8 schools in the province of Alicante (Spain). EFA confirmed a…

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

NASA Astrophysics Data System (ADS)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

Modelling formulations using gene expression programming--a comparative analysis with artificial neural networks.

PubMed

Colbourn, E A; Roskilly, S J; Rowe, R C; York, P

2011-10-09

This study has investigated the utility and potential advantages of gene expression programming (GEP)--a new development in evolutionary computing for modelling data and automatically generating equations that describe the cause-and-effect relationships in a system--to four types of pharmaceutical formulation and compared the models with those generated by neural networks, a technique now widely used in the formulation development. Both methods were capable of discovering subtle and non-linear relationships within the data, with no requirement from the user to specify the functional forms that should be used. Although the neural networks rapidly developed models with higher values for the ANOVA R(2) these were black box and provided little insight into the key relationships. However, GEP, although significantly slower at developing models, generated relatively simple equations describing the relationships that could be interpreted directly. The results indicate that GEP can be considered an effective and efficient modelling technique for formulation data. Copyright © 2011 Elsevier B.V. All rights reserved.

A Comparative Study of Some Dynamic Stall Models

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Kaza, K. R. V.

1987-01-01

Three semi-empirical aerodynamic stall models are compared with respect to their lift and moment hysteresis loop prediction, limit cycle behavior, easy implementation, and feasibility in developing the parameters required for stall flutter prediction of advanced turbines. For the comparison of aeroelastic response prediction including stall, a typical section model and a plate structural model are considered. The response analysis includes both plunging and pitching motions of the blades. In model A, a correction to the angle of attack is applied when the angle of attack exceeds the static stall angle. In model B, a synthesis procedure is used for angles of attack above static stall angles and the time history effects are accounted through the Wagner function. In both models the life and moment coefficients for angle of attack below stall are obtained from tabular data for a given Mach number and angle of attack. In model C, referred to an the ONERA model, the life and moment coefficients are given in the form of two differential equations, one for angles below stall, and the other for angles above stall. The parameters of those equations are nonlinear functions of the angle of attack.

Comparative transcriptome analysis reveals vertebrate phylotypic period during organogenesis

PubMed Central

Irie, Naoki; Kuratani, Shigeru

2011-01-01

One of the central issues in evolutionary developmental biology is how we can formulate the relationships between evolutionary and developmental processes. Two major models have been proposed: the 'funnel-like' model, in which the earliest embryo shows the most conserved morphological pattern, followed by diversifying later stages, and the 'hourglass' model, in which constraints are imposed to conserve organogenesis stages, which is called the phylotypic period. Here we perform a quantitative comparative transcriptome analysis of several model vertebrate embryos and show that the pharyngula stage is most conserved, whereas earlier and later stages are rather divergent. These results allow us to predict approximate developmental timetables between different species, and indicate that pharyngula embryos have the most conserved gene expression profiles, which may be the source of the basic body plan of vertebrates. PMID:21427719

Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

NASA Astrophysics Data System (ADS)

Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

1998-11-01

Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

Policy Research Challenges in Comparing Care Models for Dual-Eligible Beneficiaries.

PubMed

Van Cleave, Janet H; Egleston, Brian L; Brosch, Sarah; Wirth, Elizabeth; Lawson, Molly; Sullivan-Marx, Eileen M; Naylor, Mary D

2017-05-01

Providing affordable, high-quality care for the 10 million persons who are dual-eligible beneficiaries of Medicare and Medicaid is an ongoing health-care policy challenge in the United States. However, the workforce and the care provided to dual-eligible beneficiaries are understudied. The purpose of this article is to provide a narrative of the challenges and lessons learned from an exploratory study in the use of clinical and administrative data to compare the workforce of two care models that deliver home- and community-based services to dual-eligible beneficiaries. The research challenges that the study team encountered were as follows: (a) comparing different care models, (b) standardizing data across care models, and (c) comparing patterns of health-care utilization. The methods used to meet these challenges included expert opinion to classify data and summative content analysis to compare and count data. Using descriptive statistics, a summary comparison of the two care models suggested that the coordinated care model workforce provided significantly greater hours of care per recipient than the integrated care model workforce. This likely represented the coordinated care model's focus on providing in-home services for one recipient, whereas the integrated care model focused on providing services in a day center with group activities. The lesson learned from this exploratory study is the need for standardized quality measures across home- and community-based services agencies to determine the workforce that best meets the needs of dual-eligible beneficiaries.

A Comparative Analysis on Models of Higher Education Massification

ERIC Educational Resources Information Center

Pan, Maoyuan; Luo, Dan

2008-01-01

Four financial models of massification of higher education are discussed in this essay. They are American model, Western European model, Southeast Asian and Latin American model and the transition countries model. The comparison of the four models comes to the conclusion that taking advantage of nongovernmental funding is fundamental to dealing…

Comparative Study on the Prediction of Aerodynamic Characteristics of Aircraft with Turbulence Models

NASA Astrophysics Data System (ADS)

Jang, Yujin; Huh, Jinbum; Lee, Namhun; Lee, Seungsoo; Park, Youngmin

2018-04-01

The RANS equations are widely used to analyze complex flows over aircraft. The equations require a turbulence model for turbulent flow analyses. A suitable turbulence must be selected for accurate predictions of aircraft aerodynamic characteristics. In this study, numerical analyses of three-dimensional aircraft are performed to compare the results of various turbulence models for the prediction of aircraft aerodynamic characteristics. A 3-D RANS solver, MSAPv, is used for the aerodynamic analysis. The four turbulence models compared are the Sparlart-Allmaras (SA) model, Coakley's q-ω model, Huang and Coakley's k-ɛ model, and Menter's k-ω SST model. Four aircrafts are considered: an ARA-M100, DLR-F6 wing-body, DLR-F6 wing-body-nacelle-pylon from the second drag prediction workshop, and a high wing aircraft with nacelles. The CFD results are compared with experimental data and other published computational results. The details of separation patterns, shock positions, and Cp distributions are discussed to find the characteristics of the turbulence models.

Color model comparative analysis for breast cancer diagnosis using H and E stained images

NASA Astrophysics Data System (ADS)

Li, Xingyu; Plataniotis, Konstantinos N.

2015-03-01

Digital cancer diagnosis is a research realm where signal processing techniques are used to analyze and to classify color histopathology images. Different from grayscale image analysis of magnetic resonance imaging or X-ray, colors in histopathology images convey large amount of histological information and thus play significant role in cancer diagnosis. Though color information is widely used in histopathology works, as today, there is few study on color model selections for feature extraction in cancer diagnosis schemes. This paper addresses the problem of color space selection for digital cancer classification using H and E stained images, and investigates the effectiveness of various color models (RGB, HSV, CIE L*a*b*, and stain-dependent H and E decomposition model) in breast cancer diagnosis. Particularly, we build a diagnosis framework as a comparison benchmark and take specific concerns of medical decision systems into account in evaluation. The evaluation methodologies include feature discriminate power evaluation and final diagnosis performance comparison. Experimentation on a publicly accessible histopathology image set suggests that the H and E decomposition model outperforms other assessed color spaces. For reasons behind various performance of color spaces, our analysis via mutual information estimation demonstrates that color components in the H and E model are less dependent, and thus most feature discriminate power is collected in one channel instead of spreading out among channels in other color spaces.

Analysis of model output and science data in the Virtual Model Repository (VMR).

NASA Astrophysics Data System (ADS)

De Zeeuw, D.; Ridley, A. J.

2014-12-01

Big scientific data not only includes large repositories of data from scientific platforms like satelites and ground observation, but also the vast output of numerical models. The Virtual Model Repository (VMR) provides scientific analysis and visualization tools for a many numerical models of the Earth-Sun system. Individual runs can be analyzed in the VMR and compared to relevant data through relevant metadata, but larger collections of runs can also now be studied and statistics generated on the accuracy and tendancies of model output. The vast model repository at the CCMC with over 1000 simulations of the Earth's magnetosphere was used to look at overall trends in accuracy when compared to satelites such as GOES, Geotail, and Cluster. Methodology for this analysis as well as case studies will be presented.

Ecological Footprint and Ecosystem Services Models: A Comparative Analysis of Environmental Carrying Capacity Calculation Approach in Indonesia

NASA Astrophysics Data System (ADS)

Subekti, R. M.; Suroso, D. S. A.

2018-05-01

Calculation of environmental carrying capacity can be done by various approaches. The selection of an appropriate approach determines the success of determining and applying environmental carrying capacity. This study aimed to compare the ecological footprint approach and the ecosystem services approach for calculating environmental carrying capacity. It attempts to describe two relatively new models that require further explanation if they are used to calculate environmental carrying capacity. In their application, attention needs to be paid to their respective advantages and weaknesses. Conceptually, the ecological footprint model is more complete than the ecosystem services model, because it describes the supply and demand of resources, including supportive and assimilative capacity of the environment, and measurable output through a resource consumption threshold. However, this model also has weaknesses, such as not considering technological change and resources beneath the earth’s surface, as well as the requirement to provide trade data between regions for calculating at provincial and district level. The ecosystem services model also has advantages, such as being in line with strategic environmental assessment (SEA) of ecosystem services, using spatial analysis based on ecoregions, and a draft regulation on calculation guidelines formulated by the government. Meanwhile, weaknesses are that it only describes the supply of resources, that the assessment of the different types of ecosystem services by experts tends to be subjective, and that the output of the calculation lacks a resource consumption threshold.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

PubMed Central

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50–65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases. PMID:28071683

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models.

PubMed

Stratton, Margaret D; Ehrlich, Hanna Y; Mor, Siobhan M; Naumova, Elena N

2017-01-10

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

NASA Astrophysics Data System (ADS)

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

Comparing Families of Dynamic Causal Models

PubMed Central

Penny, Will D.; Stephan, Klaas E.; Daunizeau, Jean; Rosa, Maria J.; Friston, Karl J.; Schofield, Thomas M.; Leff, Alex P.

2010-01-01

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data. PMID:20300649

Beauty and the beast: Some perspectives on efficient model analysis, surrogate models, and the future of modeling

NASA Astrophysics Data System (ADS)

Hill, M. C.; Jakeman, J.; Razavi, S.; Tolson, B.

2015-12-01

For many environmental systems model runtimes have remained very long as more capable computers have been used to add more processes and more time and space discretization. Scientists have also added more parameters and kinds of observations, and many model runs are needed to explore the models. Computational demand equals run time multiplied by number of model runs divided by parallelization opportunities. Model exploration is conducted using sensitivity analysis, optimization, and uncertainty quantification. Sensitivity analysis is used to reveal consequences of what may be very complex simulated relations, optimization is used to identify parameter values that fit the data best, or at least better, and uncertainty quantification is used to evaluate the precision of simulated results. The long execution times make such analyses a challenge. Methods for addressing this challenges include computationally frugal analysis of the demanding original model and a number of ingenious surrogate modeling methods. Both commonly use about 50-100 runs of the demanding original model. In this talk we consider the tradeoffs between (1) original model development decisions, (2) computationally frugal analysis of the original model, and (3) using many model runs of the fast surrogate model. Some questions of interest are as follows. If the added processes and discretization invested in (1) are compared with the restrictions and approximations in model analysis produced by long model execution times, is there a net benefit related of the goals of the model? Are there changes to the numerical methods that could reduce the computational demands while giving up less fidelity than is compromised by using computationally frugal methods or surrogate models for model analysis? Both the computationally frugal methods and surrogate models require that the solution of interest be a smooth function of the parameters or interest. How does the information obtained from the local methods typical

Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins

PubMed Central

Nema, Vijay; Pal, Sudhir Kumar

2013-01-01

Aim: This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)2-V2, Modweb were used for the comparison and model generation. Results: Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. Conclusion: This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure. PMID:24023424

Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins.

PubMed

Nema, Vijay; Pal, Sudhir Kumar

2013-01-01

This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)(2)-V(2), Modweb were used for the comparison and model generation. Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure.

Comparative Analysis and Modeling of the Severity of Steatohepatitis in DDC-Treated Mouse Strains

PubMed Central

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Background Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. Methodology and Results In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. Conclusions We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J

Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.

PubMed

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other.

Enabling comparative modeling of closely related genomes: Example genus Brucella

DOE PAGES

Faria, José P.; Edirisinghe, Janaka N.; Davis, James J.; ...

2014-03-08

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this study, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as wellmore » as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.« less

Enabling comparative modeling of closely related genomes: Example genus Brucella

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

Faria, José P.; Edirisinghe, Janaka N.; Davis, James J.

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this study, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as wellmore » as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.« less

Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

Comparative modeling without implicit sequence alignments.

PubMed

Kolinski, Andrzej; Gront, Dominik

2007-10-01

The number of known protein sequences is about thousand times larger than the number of experimentally solved 3D structures. For more than half of the protein sequences a close or distant structural analog could be identified. The key starting point in a classical comparative modeling is to generate the best possible sequence alignment with a template or templates. With decreasing sequence similarity, the number of errors in the alignments increases and these errors are the main causes of the decreasing accuracy of the molecular models generated. Here we propose a new approach to comparative modeling, which does not require the implicit alignment - the model building phase explores geometric, evolutionary and physical properties of a template (or templates). The proposed method requires prior identification of a template, although the initial sequence alignment is ignored. The model is built using a very efficient reduced representation search engine CABS to find the best possible superposition of the query protein onto the template represented as a 3D multi-featured scaffold. The criteria used include: sequence similarity, predicted secondary structure consistency, local geometric features and hydrophobicity profile. For more difficult cases, the new method qualitatively outperforms existing schemes of comparative modeling. The algorithm unifies de novo modeling, 3D threading and sequence-based methods. The main idea is general and could be easily combined with other efficient modeling tools as Rosetta, UNRES and others.

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

PubMed

Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

2010-10-29

Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

Modeling and Analysis of Space Based Transceivers

NASA Technical Reports Server (NTRS)

Reinhart, Richard C.; Liebetreu, John; Moore, Michael S.; Price, Jeremy C.; Abbott, Ben

2005-01-01

This paper presents the tool chain, methodology, and initial results of a study to provide a thorough, objective, and quantitative analysis of the design alternatives for space Software Defined Radio (SDR) transceivers. The approach taken was to develop a set of models and tools for describing communications requirements, the algorithm resource requirements, the available hardware, and the alternative software architectures, and generate analysis data necessary to compare alternative designs. The Space Transceiver Analysis Tool (STAT) was developed to help users identify and select representative designs, calculate the analysis data, and perform a comparative analysis of the representative designs. The tool allows the design space to be searched quickly while permitting incremental refinement in regions of higher payoff.

Modeling and Analysis of Space Based Transceivers

NASA Technical Reports Server (NTRS)

Moore, Michael S.; Price, Jeremy C.; Abbott, Ben; Liebetreu, John; Reinhart, Richard C.; Kacpura, Thomas J.

2007-01-01

This paper presents the tool chain, methodology, and initial results of a study to provide a thorough, objective, and quantitative analysis of the design alternatives for space Software Defined Radio (SDR) transceivers. The approach taken was to develop a set of models and tools for describing communications requirements, the algorithm resource requirements, the available hardware, and the alternative software architectures, and generate analysis data necessary to compare alternative designs. The Space Transceiver Analysis Tool (STAT) was developed to help users identify and select representative designs, calculate the analysis data, and perform a comparative analysis of the representative designs. The tool allows the design space to be searched quickly while permitting incremental refinement in regions of higher payoff.

Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

NASA Astrophysics Data System (ADS)

Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

2017-02-01

The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

Comparing Results from Constant Comparative and Computer Software Methods: A Reflection about Qualitative Data Analysis

ERIC Educational Resources Information Center

Putten, Jim Vander; Nolen, Amanda L.

2010-01-01

This study compared qualitative research results obtained by manual constant comparative analysis with results obtained by computer software analysis of the same data. An investigated about issues of trustworthiness and accuracy ensued. Results indicated that the inductive constant comparative data analysis generated 51 codes and two coding levels…

Comparing Supply-Side Specifications in Models of Global Agriculture and the Food System

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

Robinson, Sherman; van Meijl, Hans; Willenbockel, Dirk

This paper compares the theoretical specification of production and technical change across the partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two modeling approaches have different theoretical underpinnings concerning the scope of economic activity they capture and how they represent technology and the behavior of supply and demand in markets. This paper focuses on their different specifications of technology and supply behavior, comparing their theoretical and empirical treatments. While the models differ widely in their specifications of technology, both within and between the PEmore » and CGE classes of models, we find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In particular, we compare the theoretical specification of supply in CGE models with neoclassical production functions and PE models that focus on land and crop yields in agriculture. In practice, however, comparability of results given parameter choices is an empirical question, and the models differ in their sensitivity to variations in specification. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.« less

Reliability of four models for clinical gait analysis.

PubMed

Kainz, Hans; Graham, David; Edwards, Julie; Walsh, Henry P J; Maine, Sheanna; Boyd, Roslyn N; Lloyd, David G; Modenese, Luca; Carty, Christopher P

2017-05-01

Three-dimensional gait analysis (3DGA) has become a common clinical tool for treatment planning in children with cerebral palsy (CP). Many clinical gait laboratories use the conventional gait analysis model (e.g. Plug-in-Gait model), which uses Direct Kinematics (DK) for joint kinematic calculations, whereas, musculoskeletal models, mainly used for research, use Inverse Kinematics (IK). Musculoskeletal IK models have the advantage of enabling additional analyses which might improve the clinical decision-making in children with CP. Before any new model can be used in a clinical setting, its reliability has to be evaluated and compared to a commonly used clinical gait model (e.g. Plug-in-Gait model) which was the purpose of this study. Two testers performed 3DGA in eleven CP and seven typically developing participants on two occasions. Intra- and inter-tester standard deviations (SD) and standard error of measurement (SEM) were used to compare the reliability of two DK models (Plug-in-Gait and a six degrees-of-freedom model solved using Vicon software) and two IK models (two modifications of 'gait2392' solved using OpenSim). All models showed good reliability (mean SEM of 3.0° over all analysed models and joint angles). Variations in joint kinetics were less in typically developed than in CP participants. The modified 'gait2392' model which included all the joint rotations commonly reported in clinical 3DGA, showed reasonable reliable joint kinematic and kinetic estimates, and allows additional musculoskeletal analysis on surgically adjustable parameters, e.g. muscle-tendon lengths, and, therefore, is a suitable model for clinical gait analysis. Copyright © 2017. Published by Elsevier B.V.

In vitro, ex vivo and in vivo models: A comparative analysis of Paracoccidioides spp. proteomic studies.

PubMed

Parente-Rocha, Juliana Alves; Tomazett, Mariana Vieira; Pigosso, Laurine Lacerda; Bailão, Alexandre Melo; Ferreira de Souza, Aparecido; Paccez, Juliano Domiraci; Baeza, Lilian Cristiane; Pereira, Maristela; Silva Bailão, Mirelle Garcia; Borges, Clayton Luiz; Maria de Almeida Soares, Célia

2018-06-01

Members of the Paracoccidioides complex are human pathogens that infect different anatomic sites in the host. The ability of Paracoccidioides spp. to infect host niches is putatively supported by a wide range of virulence factors, as well as fitness attributes that may comprise the transition from mycelia/conidia to yeast cells, response to deprivation of micronutrients in the host, expression of adhesins on the cell surface, response to oxidative and nitrosative stresses, as well as the secretion of hydrolytic enzymes in the host tissue. Our understanding of how those molecules can contribute to the infection establishment has been increasing significantly, through the utilization of several models, including in vitro, ex vivo and in vivo infection in animal models. In this review we present an update of our understanding on the strategies used by the pathogen to establish infection. Our results were obtained through a comparative proteomic analysis of Paracoccidioides spp. in models of infection. Copyright © 2017 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Comparative Analysis of Hybrid Models for Prediction of BP Reactivity to Crossed Legs.

PubMed

Kaur, Gurmanik; Arora, Ajat Shatru; Jain, Vijender Kumar

2017-01-01

Crossing the legs at the knees, during BP measurement, is one of the several physiological stimuli that considerably influence the accuracy of BP measurements. Therefore, it is paramount to develop an appropriate prediction model for interpreting influence of crossed legs on BP. This research work described the use of principal component analysis- (PCA-) fused forward stepwise regression (FSWR), artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS), and least squares support vector machine (LS-SVM) models for prediction of BP reactivity to crossed legs among the normotensive and hypertensive participants. The evaluation of the performance of the proposed prediction models using appropriate statistical indices showed that the PCA-based LS-SVM (PCA-LS-SVM) model has the highest prediction accuracy with coefficient of determination ( R 2 ) = 93.16%, root mean square error (RMSE) = 0.27, and mean absolute percentage error (MAPE) = 5.71 for SBP prediction in normotensive subjects. Furthermore, R 2  = 96.46%, RMSE = 0.19, and MAPE = 1.76 for SBP prediction and R 2  = 95.44%, RMSE = 0.21, and MAPE = 2.78 for DBP prediction in hypertensive subjects using the PCA-LSSVM model. This assessment presents the importance and advantages posed by hybrid computing models for the prediction of variables in biomedical research studies.

Comparative Analysis of Pain Behaviours in Humanized Mouse Models of Sickle Cell Anemia

PubMed Central

Lei, Jianxun; Benson, Barbara; Tran, Huy; Ofori-Acquah, Solomon F.; Gupta, Kalpna

2016-01-01

Pain is a hallmark feature of sickle cell anemia (SCA) but management of chronic as well as acute pain remains a major challenge. Mouse models of SCA are essential to examine the mechanisms of pain and develop novel therapeutics. To facilitate this effort, we compared humanized homozygous BERK and Townes sickle mice for the effect of gender and age on pain behaviors. Similar to previously characterized BERK sickle mice, Townes sickle mice show more mechanical, thermal, and deep tissue hyperalgesia with increasing age. Female Townes sickle mice demonstrate more hyperalgesia compared to males similar to that reported for BERK mice and patients with SCA. Mechanical, thermal and deep tissue hyperalgesia increased further after hypoxia/reoxygenation (H/R) treatment in Townes sickle mice. Together, these data show BERK sickle mice exhibit a significantly greater degree of hyperalgesia for all behavioral measures as compared to gender- and age-matched Townes sickle mice. However, the genetically distinct “knock-in” strategy of human α and β transgene insertion in Townes mice as compared to BERK mice, may provide relative advantage for further genetic manipulations to examine specific mechanisms of pain. PMID:27494522

Three-dimensional structure-activity relationship modeling of cocaine binding to two monoclonal antibodies by comparative molecular field analysis.

PubMed

Paula, Stefan; Tabet, Michael R; Keenan, Susan M; Welsh, William J; Ball, W James

2003-01-17

Successful immunotherapy of cocaine addiction and overdoses requires cocaine-binding antibodies with specific properties, such as high affinity and selectivity for cocaine. We have determined the affinities of two cocaine-binding murine monoclonal antibodies (mAb: clones 3P1A6 and MM0240PA) for cocaine and its metabolites by [3H]-radioligand binding assays. mAb 3P1A6 (K(d) = 0.22 nM) displayed a 50-fold higher affinity for cocaine than mAb MM0240PA (K(d) = 11 nM) and also had a greater specificity for cocaine. For the systematic exploration of both antibodies' binding specificities, we used a set of approximately 35 cocaine analogues as structural probes by determining their relative binding affinities (RBAs) using an enzyme-linked immunosorbent competition assay. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models on the basis of comparative molecular field analysis (CoMFA) techniques correlated the binding data with structural features of the ligands. The analysis indicated that despite the mAbs' differing specificities for cocaine, the relative contributions of the steric (approximately 80%) and electrostatic (approximately 20%) field interactions to ligand-binding were similar. Generated three-dimensional CoMFA contour plots then located the specific regions about cocaine where the ligand/receptor interactions occurred. While the overall binding patterns of the two mAbs had many features in common, distinct differences were observed about the phenyl ring and the methylester group of cocaine. Furthermore, using previously published data, a 3D-QSAR model was developed for cocaine binding to the dopamine reuptake transporter (DAT) that was compared to the mAb models. Although the relative steric and electrostatic field contributions were similar to those of the mAbs, the DAT cocaine-binding site showed a preference for negatively charged ligands. Besides establishing molecular level insight into the interactions that govern cocaine

International Space Station Model Correlation Analysis

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Fold assessment for comparative protein structure modeling.

PubMed

Melo, Francisco; Sali, Andrej

2007-11-01

Accurate and automated assessment of both geometrical errors and incompleteness of comparative protein structure models is necessary for an adequate use of the models. Here, we describe a composite score for discriminating between models with the correct and incorrect fold. To find an accurate composite score, we designed and applied a genetic algorithm method that searched for a most informative subset of 21 input model features as well as their optimized nonlinear transformation into the composite score. The 21 input features included various statistical potential scores, stereochemistry quality descriptors, sequence alignment scores, geometrical descriptors, and measures of protein packing. The optimized composite score was found to depend on (1) a statistical potential z-score for residue accessibilities and distances, (2) model compactness, and (3) percentage sequence identity of the alignment used to build the model. The accuracy of the composite score was compared with the accuracy of assessment by single and combined features as well as by other commonly used assessment methods. The testing set was representative of models produced by automated comparative modeling on a genomic scale. The composite score performed better than any other tested score in terms of the maximum correct classification rate (i.e., 3.3% false positives and 2.5% false negatives) as well as the sensitivity and specificity across the whole range of thresholds. The composite score was implemented in our program MODELLER-8 and was used to assess models in the MODBASE database that contains comparative models for domains in approximately 1.3 million protein sequences.

Power laws in microrheology experiments on living cells: Comparative analysis and modeling

NASA Astrophysics Data System (ADS)

Balland, Martial; Desprat, Nicolas; Icard, Delphine; Féréol, Sophie; Asnacios, Atef; Browaeys, Julien; Hénon, Sylvie; Gallet, François

2006-08-01

We compare and synthesize the results of two microrheological experiments on the cytoskeleton of single cells. In the first one, the creep function J(t) of a cell stretched between two glass plates is measured after applying a constant force step. In the second one, a microbead specifically bound to transmembrane receptors is driven by an oscillating optical trap, and the viscoelastic coefficient Ge(ω) is retrieved. Both J(t) and Ge(ω) exhibit power law behaviors: J(t)=A0(t/t0)α and ∣Ge(ω)∣=G0(ω/ω0)α , with the same exponent α≈0.2 . This power law behavior is very robust; α is distributed over a narrow range, and shows almost no dependence on the cell type, on the nature of the protein complex which transmits the mechanical stress, nor on the typical length scale of the experiment. On the contrary, the prefactors A0 and G0 appear very sensitive to these parameters. Whereas the exponents α are normally distributed over the cell population, the prefactors A0 and G0 follow a log-normal repartition. These results are compared with other data published in the literature. We propose a global interpretation, based on a semiphenomenological model, which involves a broad distribution of relaxation times in the system. The model predicts the power law behavior and the statistical repartition of the mechanical parameters, as experimentally observed for the cells. Moreover, it leads to an estimate of the largest response time in the cytoskeletal network: τm˜1000s .

Power laws in microrheology experiments on living cells: Comparative analysis and modeling.

PubMed

Balland, Martial; Desprat, Nicolas; Icard, Delphine; Féréol, Sophie; Asnacios, Atef; Browaeys, Julien; Hénon, Sylvie; Gallet, François

2006-08-01

We compare and synthesize the results of two microrheological experiments on the cytoskeleton of single cells. In the first one, the creep function J(t) of a cell stretched between two glass plates is measured after applying a constant force step. In the second one, a microbead specifically bound to transmembrane receptors is driven by an oscillating optical trap, and the viscoelastic coefficient Ge(omega) is retrieved. Both J(t) and Ge(omega) exhibit power law behaviors: J(t) = A0(t/t0)alpha and absolute value (Ge(omega)) = G0(omega/omega0)alpha, with the same exponent alpha approximately 0.2. This power law behavior is very robust; alpha is distributed over a narrow range, and shows almost no dependence on the cell type, on the nature of the protein complex which transmits the mechanical stress, nor on the typical length scale of the experiment. On the contrary, the prefactors A0 and G0 appear very sensitive to these parameters. Whereas the exponents alpha are normally distributed over the cell population, the prefactors A0 and G0 follow a log-normal repartition. These results are compared with other data published in the literature. We propose a global interpretation, based on a semiphenomenological model, which involves a broad distribution of relaxation times in the system. The model predicts the power law behavior and the statistical repartition of the mechanical parameters, as experimentally observed for the cells. Moreover, it leads to an estimate of the largest response time in the cytoskeletal network: tau(m) approximately 1000 s.

A comparative analysis of errors in long-term econometric forecasts

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

Tepel, R.

1986-04-01

The growing body of literature that documents forecast accuracy falls generally into two parts. The first is prescriptive and is carried out by modelers who use simulation analysis as a tool for model improvement. These studies are ex post, that is, they make use of known values for exogenous variables and generate an error measure wholly attributable to the model. The second type of analysis is descriptive and seeks to measure errors, identify patterns among errors and variables and compare forecasts from different sources. Most descriptive studies use an ex ante approach, that is, they evaluate model outputs based onmore » estimated (or forecasted) exogenous variables. In this case, it is the forecasting process, rather than the model, that is under scrutiny. This paper uses an ex ante approach to measure errors in forecast series prepared by Data Resources Incorporated (DRI), Wharton Econometric Forecasting Associates (Wharton), and Chase Econometrics (Chase) and to determine if systematic patterns of errors can be discerned between services, types of variables (by degree of aggregation), length of forecast and time at which the forecast is made. Errors are measured as the percent difference between actual and forecasted values for the historical period of 1971 to 1983.« less

Protein Dynamics from NMR: The Slowly Relaxing Local Structure Analysis Compared with Model-Free Analysis

PubMed Central

Meirovitch, Eva; Shapiro, Yury E.; Polimeno, Antonino; Freed, Jack H.

2009-01-01

15N-1H spin relaxation is a powerful method for deriving information on protein dynamics. The traditional method of data analysis is model-free (MF), where the global and local N-H motions are independent and the local geometry is simplified. The common MF analysis consists of fitting single-field data. The results are typically field-dependent, and multi-field data cannot be fit with standard fitting schemes. Cases where known functional dynamics has not been detected by MF were identified by us and others. Recently we applied to spin relaxation in proteins the Slowly Relaxing Local Structure (SRLS) approach which accounts rigorously for mode-mixing and general features of local geometry. SRLS was shown to yield MF in appropriate asymptotic limits. We found that the experimental spectral density corresponds quite well to the SRLS spectral density. The MF formulae are often used outside of their validity ranges, allowing small data sets to be force-fitted with good statistics but inaccurate best-fit parameters. This paper focuses on the mechanism of force-fitting and its implications. It is shown that MF force-fits the experimental data because mode-mixing, the rhombic symmetry of the local ordering and general features of local geometry are not accounted for. Combined multi-field multi-temperature data analyzed by MF may lead to the detection of incorrect phenomena, while conformational entropy derived from MF order parameters may be highly inaccurate. On the other hand, fitting to more appropriate models can yield consistent physically insightful information. This requires that the complexity of the theoretical spectral densities matches the integrity of the experimental data. As shown herein, the SRLS densities comply with this requirement. PMID:16821820

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment

PubMed Central

2010-01-01

Background Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. Results We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. Conclusions In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets. PMID:21034488

Comparative cost-benefit analysis of tele-homecare for community-dwelling elderly in Japan: Non-Government versus Government Supported Funding Models.

PubMed

Akiyama, Miki; Abraham, Chon

2017-08-01

Tele-homecare is gaining prominence as a viable care alternative, as evidenced by the increase in financial support from international governments to fund initiatives in their respective countries. The primary reason for the funding is to support efforts to reduce lags and increase capacity in access to care as well as to promote preventive measures that can avert costly emergent issues from arising. These efforts are especially important to super-aged and aging societies such as in Japan, many European countries, and the United States (US). However, to date and to our knowledge, a direct comparison of non-government vs. government-supported funding models for tele-homecare is particularly lacking in Japan. The aim of this study is to compare these operational models (i.e., non-government vs. government-supported funding) from a cost-benefit perspective. This simulation study applies to a Japanese hypothetical cohort with implications for other super-aged and aging societies abroad. We performed a cost-benefit analysis (CBA) on two operational models for enabling tele-homecare for elderly community-dwelling cohorts based on a decision tree model, which we created with parameters from published literature. The two models examined are (a) Model 1-non-government-supported funding that includes monthly fixed charges paid by users for a portion of the operating costs, and (b) Model 2-government-supported funding that includes startup and installation costs only (i.e., no operating costs) and no monthly user charges. We performed base case cost-benefit analysis and probabilistic cost-benefit analysis with a Monte Carlo simulation. We calculated net benefit and benefit-to-cost ratios (BCRs) from the societal perspective with a five-year time horizon applying a 3% discount rate for both cost and benefit values. The cost of tele-homecare included (a) the startup system expense, averaged over a five-year depreciation period, and (b) operation expenses (i.e., labor and non

Comparative Analysis of Smart Meters Deployment Business Models on the Example of the Russian Federation Markets

NASA Astrophysics Data System (ADS)

Daminov, Ildar; Tarasova, Ekaterina; Andreeva, Tatyana; Avazov, Artur

2016-02-01

This paper presents the comparison of smart meter deployment business models to determine the most suitable option providing smart meters deployment. Authors consider 3 main business model of companies: distribution grid company, energy supplier (energosbyt) and metering company. The goal of the article is to compare the business models of power companies from massive smart metering roll out in power system of Russian Federation.

Comparative modelling of the spectra of cool giants⋆⋆⋆

NASA Astrophysics Data System (ADS)

Lebzelter, T.; Heiter, U.; Abia, C.; Eriksson, K.; Ireland, M.; Neilson, H.; Nowotny, W.; Maldonado, J.; Merle, T.; Peterson, R.; Plez, B.; Short, C. I.; Wahlgren, G. M.; Worley, C.; Aringer, B.; Bladh, S.; de Laverny, P.; Goswami, A.; Mora, A.; Norris, R. P.; Recio-Blanco, A.; Scholz, M.; Thévenin, F.; Tsuji, T.; Kordopatis, G.; Montesinos, B.; Wing, R. F.

2012-11-01

Context. Our ability to extract information from the spectra of stars depends on reliable models of stellar atmospheres and appropriate techniques for spectral synthesis. Various model codes and strategies for the analysis of stellar spectra are available today. Aims: We aim to compare the results of deriving stellar parameters using different atmosphere models and different analysis strategies. The focus is set on high-resolution spectroscopy of cool giant stars. Methods: Spectra representing four cool giant stars were made available to various groups and individuals working in the area of spectral synthesis, asking them to derive stellar parameters from the data provided. The results were discussed at a workshop in Vienna in 2010. Most of the major codes currently used in the astronomical community for analyses of stellar spectra were included in this experiment. Results: We present the results from the different groups, as well as an additional experiment comparing the synthetic spectra produced by various codes for a given set of stellar parameters. Similarities and differences of the results are discussed. Conclusions: Several valid approaches to analyze a given spectrum of a star result in quite a wide range of solutions. The main causes for the differences in parameters derived by different groups seem to lie in the physical input data and in the details of the analysis method. This clearly shows how far from a definitive abundance analysis we still are. Based on observations obtained at the Bernard Lyot Telescope (TBL, Pic du Midi, France) of the Midi-Pyrénées Observatory, which is operated by the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France.Tables 6-11 are only available in electronic form at http://www.aanda.orgThe spectra of stars 1 to 4 used in the experiment presented here are only availalbe at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http

Comparative analysis of reflective sheeting.

DOT National Transportation Integrated Search

1981-01-01

A comparative analysis was made of the initial brightness of seibulite brand super engineering grade and scotchlite brand high intensity grade reflective sheeting under road conditions. Overhead and ground-mounted guide signs were analyzed. Human fac...

The Effectiveness of Physical Models in Teaching Anatomy: A Meta-Analysis of Comparative Studies

ERIC Educational Resources Information Center

Yammine, Kaissar; Violato, Claudio

2016-01-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively…

A comparative study of two prediction models for brain tumor progression

NASA Astrophysics Data System (ADS)

Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang

2015-03-01

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were

Autologous Stem Cell Transplantation in Patients With Multiple Myeloma: An Activity-based Costing Analysis, Comparing a Total Inpatient Model Versus an Early Discharge Model.

PubMed

Martino, Massimo; Console, Giuseppe; Russo, Letteria; Meliado', Antonella; Meliambro, Nicola; Moscato, Tiziana; Irrera, Giuseppe; Messina, Giuseppe; Pontari, Antonella; Morabito, Fortunato

2017-08-01

Activity-based costing (ABC) was developed and advocated as a means of overcoming the systematic distortions of traditional cost accounting. We calculated the cost of high-dose chemotherapy and autologous stem cell transplantation (ASCT) in patients with multiple myeloma using the ABC method, through 2 different care models: the total inpatient model (TIM) and the early-discharge outpatient model (EDOM) and compared this with the approved diagnosis related-groups (DRG) Italian tariffs. The TIM and EDOM models involved a total cost of €28,615.15 and €16,499.43, respectively. In the TIM model, the phase with the greatest economic impact was the posttransplant (recovery and hematologic engraftment) with 36.4% of the total cost, whereas in the EDOM model, the phase with the greatest economic impact was the pretransplant (chemo-mobilization, apheresis procedure, cryopreservation, and storage) phase, with 60.4% of total expenses. In an analysis of each episode, the TIM model comprised a higher absorption than the EDOM. In particular, the posttransplant represented 36.4% of the total costs in the TIM and 17.7% in EDOM model, respectively. The estimated reduction in cost per patient using an EDOM model was over €12,115.72. The repayment of the DRG in Calabrian Region for the ASCT procedure is €59,806. Given the real cost of the transplant, the estimated cost saving per patient is €31,190.85 in the TIM model and €43,306.57 in the EDOM model. In conclusion, the actual repayment of the DRG does not correspond to the real cost of the ASCT procedure in Italy. Moreover, using the EDOM, the cost of ASCT is approximately the half of the TIM model. Copyright © 2017 Elsevier Inc. All rights reserved.

The Evolution of the Solar Magnetic Field: A Comparative Analysis of Two Models

NASA Astrophysics Data System (ADS)

McMichael, K. D.; Karak, B. B.; Upton, L.; Miesch, M. S.; Vierkens, O.

2017-12-01

Understanding the complexity of the solar magnetic cycle is a task that has plagued scientists for decades. However, with the help of computer simulations, we have begun to gain more insight into possible solutions to the plethora of questions inside the Sun. STABLE (Surface Transport and Babcock Leighton) is a newly developed 3D dynamo model that can reproduce features of the solar cycle. In this model, the tilted bipolar sunspots are formed on the surface (based on the toroidal field at the bottom of the convection zone) and then decay and disperse, producing the poloidal field. Since STABLE is a 3D model, it is able to solve the full induction equation in the entirety of the solar convection zone as well as incorporate many free parameters (such as spot depth and turbulent diffusion) which are difficult to observe. In an attempt to constrain some of these free parameters, we compare STABLE to a surface flux transport model called AFT (Advective Flux Transport) which solves the radial component of the magnetic field on the solar surface. AFT is a state-of-the-art surface flux transport model that has a proven record of being able to reproduce solar observations with great accuracy. In this project, we implement synthetic bipolar sunspots into both models, using identical surface parameters, and run the models for comparison. We demonstrate that the 3D structure of the sunspots in the interior and the vertical diffusion of the sunspot magnetic field play an important role in establishing the surface magnetic field in STABLE. We found that when a sufficient amount of downward magnetic pumping is included in STABLE, the surface magnetic field from this model becomes insensitive to the internal structure of the sunspot and more consistent with that of AFT.

Model Performance Evaluation and Scenario Analysis ...

EPA Pesticide Factsheets

This tool consists of two parts: model performance evaluation and scenario analysis (MPESA). The model performance evaluation consists of two components: model performance evaluation metrics and model diagnostics. These metrics provides modelers with statistical goodness-of-fit measures that capture magnitude only, sequence only, and combined magnitude and sequence errors. The performance measures include error analysis, coefficient of determination, Nash-Sutcliffe efficiency, and a new weighted rank method. These performance metrics only provide useful information about the overall model performance. Note that MPESA is based on the separation of observed and simulated time series into magnitude and sequence components. The separation of time series into magnitude and sequence components and the reconstruction back to time series provides diagnostic insights to modelers. For example, traditional approaches lack the capability to identify if the source of uncertainty in the simulated data is due to the quality of the input data or the way the analyst adjusted the model parameters. This report presents a suite of model diagnostics that identify if mismatches between observed and simulated data result from magnitude or sequence related errors. MPESA offers graphical and statistical options that allow HSPF users to compare observed and simulated time series and identify the parameter values to adjust or the input data to modify. The scenario analysis part of the too

Comparative dynamics in a health investment model.

PubMed

Eisenring, C

1999-10-01

The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.

Monitoring anti-angiogenic therapy in colorectal cancer murine model using dynamic contrast-enhanced MRI: comparing pixel-by-pixel with region of interest analysis.

PubMed

Haney, C R; Fan, X; Markiewicz, E; Mustafi, D; Karczmar, G S; Stadler, W M

2013-02-01

Sorafenib is a multi-kinase inhibitor that blocks cell proliferation and angiogenesis. It is currently approved for advanced hepatocellular and renal cell carcinomas in humans, where its major mechanism of action is thought to be through inhibition of vascular endothelial growth factor and platelet-derived growth factor receptors. The purpose of this study was to determine whether pixel-by-pixel analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is better able to capture the heterogeneous response of Sorafenib in a murine model of colorectal tumor xenografts (as compared with region of interest analysis). MRI was performed on a 9.4 T pre-clinical scanner on the initial treatment day. Then either vehicle or drug were gavaged daily (3 days) up to the final image. Four days later, the mice were again imaged. The two-compartment model and reference tissue method of DCE-MRI were used to analyze the data. The results demonstrated that the contrast agent distribution rate constant (K(trans)) were significantly reduced (p < 0.005) at day-4 of Sorafenib treatment. In addition, the K(trans) of nearby muscle was also reduced after Sorafenib treatment. The pixel-by-pixel analysis (compared to region of interest analysis) was better able to capture the heterogeneity of the tumor and the decrease in K(trans) four days after treatment. For both methods, the volume of the extravascular extracellular space did not change significantly after treatment. These results confirm that parameters such as K(trans), could provide a non-invasive biomarker to assess the response to anti-angiogenic therapies such as Sorafenib, but that the heterogeneity of response across a tumor requires a more detailed analysis than has typically been undertaken.

Comparative analysis of multisensor satellite monitoring of Arctic sea-ice

USGS Publications Warehouse

Belchansky, G.I.; Mordvintsev, Ilia N.; Douglas, David C.

1999-01-01

This report represents comparative analysis of nearly coincident Russian OKEAN-01 polar orbiting satellite data, Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) imagery. OKEAN-01 ice concentration algorithms utilize active and passive microwave measurements and a linear mixture model for measured values of the brightness temperature and the radar backscatter. SSM/I and AVHRR ice concentrations were computed with NASA Team algorithm and visible and thermal-infrared wavelength AVHRR data, accordingly

Comparing models for perfluorooctanoic acid pharmacokinetics using Bayesian analysis

EPA Science Inventory

Selecting the appropriate pharmacokinetic (PK) model given the available data is investigated for perfluorooctanoic acid (PFOA), which has been widely analyzed with an empirical, one-compartment model. This research examined the results of experiments [Kemper R. A., DuPont Haskel...

A Comparative Test of Work-Family Conflict Models and Critical Examination of Work-Family Linkages

ERIC Educational Resources Information Center

Michel, Jesse S.; Mitchelson, Jacqueline K.; Kotrba, Lindsey M.; LeBreton, James M.; Baltes, Boris B.

2009-01-01

This paper is a comprehensive meta-analysis of over 20 years of work-family conflict research. A series of path analyses were conducted to compare and contrast existing work-family conflict models, as well as a new model we developed which integrates and synthesizes current work-family theory and research. This new model accounted for 40% of the…

Embedded Hyperchaotic Generators: A Comparative Analysis

NASA Astrophysics Data System (ADS)

Sadoudi, Said; Tanougast, Camel; Azzaz, Mohamad Salah; Dandache, Abbas

In this paper, we present a comparative analysis of FPGA implementation performances, in terms of throughput and resources cost, of five well known autonomous continuous hyperchaotic systems. The goal of this analysis is to identify the embedded hyperchaotic generator which leads to designs with small logic area cost, satisfactory throughput rates, low power consumption and low latency required for embedded applications such as secure digital communications between embedded systems. To implement the four-dimensional (4D) chaotic systems, we use a new structural hardware architecture based on direct VHDL description of the forth order Runge-Kutta method (RK-4). The comparative analysis shows that the hyperchaotic Lorenz generator provides attractive performances compared to that of others. In fact, its hardware implementation requires only 2067 CLB-slices, 36 multipliers and no block RAMs, and achieves a throughput rate of 101.6 Mbps, at the output of the FPGA circuit, at a clock frequency of 25.315 MHz with a low latency time of 316 ns. Consequently, these good implementation performances offer to the embedded hyperchaotic Lorenz generator the advantage of being the best candidate for embedded communications applications.

Comparative evaluation of urban storm water quality models

NASA Astrophysics Data System (ADS)

Vaze, J.; Chiew, Francis H. S.

2003-10-01

The estimation of urban storm water pollutant loads is required for the development of mitigation and management strategies to minimize impacts to receiving environments. Event pollutant loads are typically estimated using either regression equations or "process-based" water quality models. The relative merit of using regression models compared to process-based models is not clear. A modeling study is carried out here to evaluate the comparative ability of the regression equations and process-based water quality models to estimate event diffuse pollutant loads from impervious surfaces. The results indicate that, once calibrated, both the regression equations and the process-based model can estimate event pollutant loads satisfactorily. In fact, the loads estimated using the regression equation as a function of rainfall intensity and runoff rate are better than the loads estimated using the process-based model. Therefore, if only estimates of event loads are required, regression models should be used because they are simpler and require less data compared to process-based models.

Comparative analysis of numerical and experimental data of orthodontic mini-implants.

PubMed

Chatzigianni, Athina; Keilig, Ludger; Duschner, Heinz; Götz, Hermann; Eliades, Theodore; Bourauel, Christoph

2011-10-01

The purpose of this study was to compare numerical simulation data derived from finite element analysis (FEA) to experimental data on mini-implant loading. Nine finite element (FE) models of mini-implants and surrounding bone were derived from corresponding experimental specimens. The animal bone in the experiment consisted of bovine rib. The experimental groups were based on implant type, length, diameter, and angle of insertion. One experimental specimen was randomly selected from each group and was digitized in a microCT scanner. The FE models consisted of bone pieces containing Aarhus mini-implants with dimensions 1.5 × 7 mm and 1.5 × 9 mm or LOMAS mini-implants (dimensions 1.5 × 7 mm, 1.5 × 9 mm, and 2 × 7 mm). Mini-implants were inserted in two different ways, perpendicular to the bone surface or at 45 degrees to the direction of the applied load. Loading and boundary conditions in the FE models were adjusted to match the experimental situation, with the force applied on the neck of the mini-implants, along the mesio-distal direction up to a maximum of 0.5 N. Displacement and rotation of mini-implants after force application calculated by FEA were compared to previously recorded experimental deflections of the same mini-implants. Analysis of data with the Altman-Bland test and the Youden plot demonstrated good agreement between numerical and experimental findings (P = not significant) for the models selected. This study provides further evidence of the appropriateness of the FEA as an investigational tool in relevant research.

Modeling spatiotemporal covariance for magnetoencephalography or electroencephalography source analysis.

PubMed

Plis, Sergey M; George, J S; Jun, S C; Paré-Blagoev, J; Ranken, D M; Wood, C C; Schmidt, D M

2007-01-01

We propose a new model to approximate spatiotemporal noise covariance for use in neural electromagnetic source analysis, which better captures temporal variability in background activity. As with other existing formalisms, our model employs a Kronecker product of matrices representing temporal and spatial covariance. In our model, spatial components are allowed to have differing temporal covariances. Variability is represented as a series of Kronecker products of spatial component covariances and corresponding temporal covariances. Unlike previous attempts to model covariance through a sum of Kronecker products, our model is designed to have a computationally manageable inverse. Despite increased descriptive power, inversion of the model is fast, making it useful in source analysis. We have explored two versions of the model. One is estimated based on the assumption that spatial components of background noise have uncorrelated time courses. Another version, which gives closer approximation, is based on the assumption that time courses are statistically independent. The accuracy of the structural approximation is compared to an existing model, based on a single Kronecker product, using both Frobenius norm of the difference between spatiotemporal sample covariance and a model, and scatter plots. Performance of ours and previous models is compared in source analysis of a large number of single dipole problems with simulated time courses and with background from authentic magnetoencephalography data.

A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization.

PubMed

Hou, Zeyu; Lu, Wenxi; Xue, Haibo; Lin, Jin

2017-08-01

Surrogate-based simulation-optimization technique is an effective approach for optimizing the surfactant enhanced aquifer remediation (SEAR) strategy for clearing DNAPLs. The performance of the surrogate model, which is used to replace the simulation model for the aim of reducing computation burden, is the key of corresponding researches. However, previous researches are generally based on a stand-alone surrogate model, and rarely make efforts to improve the approximation accuracy of the surrogate model to the simulation model sufficiently by combining various methods. In this regard, we present set pair analysis (SPA) as a new method to build ensemble surrogate (ES) model, and conducted a comparative research to select a better ES modeling pattern for the SEAR strategy optimization problems. Surrogate models were developed using radial basis function artificial neural network (RBFANN), support vector regression (SVR), and Kriging. One ES model is assembling RBFANN model, SVR model, and Kriging model using set pair weights according their performance, and the other is assembling several Kriging (the best surrogate modeling method of three) models built with different training sample datasets. Finally, an optimization model, in which the ES model was embedded, was established to obtain the optimal remediation strategy. The results showed the residuals of the outputs between the best ES model and simulation model for 100 testing samples were lower than 1.5%. Using an ES model instead of the simulation model was critical for considerably reducing the computation time of simulation-optimization process and maintaining high computation accuracy simultaneously. Copyright © 2017 Elsevier B.V. All rights reserved.

Disability in Mexico: a comparative analysis between descriptive models and historical periods using a timeline.

PubMed

Sandoval, Hugo; Pérez-Neri, Iván; Martínez-Flores, Francisco; Valle-Cabrera, Martha Griselda Del; Pineda, Carlos

2017-01-01

Some interpretations frequently argue that three Disability Models (DM) (Charity, Medical/Rehabilitation, and Social) correspond to historical periods in terms of chronological succession. These views permeate a priori within major official documents on the subject in Mexico. This paper intends to test whether this association is plausible by applying a timeline method. A document search was made with inclusion and exclusion criteria in databases to select representative studies with which to depict milestones in the timelines for each period. The following is demonstrated: 1) models should be considered as categories of analysis and not as historical periods, in that the prevalence of elements of the three models is present to date, and 2) the association between disability models and historical periods results in teleological interpretations of the history of disability in Mexico.

DIDEM - An integrated model for comparative health damage costs calculation of air pollution

NASA Astrophysics Data System (ADS)

Ravina, Marco; Panepinto, Deborah; Zanetti, Maria Chiara

2018-01-01

Air pollution represents a continuous hazard to human health. Administration, companies and population need efficient indicators of the possible effects given by a change in decision, strategy or habit. The monetary quantification of health effects of air pollution through the definition of external costs is increasingly recognized as a useful indicator to support decision and information at all levels. The development of modelling tools for the calculation of external costs can provide support to analysts in the development of consistent and comparable assessments. In this paper, the DIATI Dispersion and Externalities Model (DIDEM) is presented. The DIDEM model calculates the delta-external costs of air pollution comparing two alternative emission scenarios. This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions. The model is based on the impact pathway method. It was designed to work with a fine spatial resolution and a local or national geographic scope. The modular structure allows users to input their own data sets. The DIDEM model was tested on a real case study, represented by a comparative analysis of the district heating system in Turin, Italy. Additional advantages and drawbacks of the tool are discussed in the paper. A comparison with other existing models worldwide is reported.

Transitions in state public health law: comparative analysis of state public health law reform following the Turning Point Model State Public Health Act.

PubMed

Meier, Benjamin Mason; Hodge, James G; Gebbie, Kristine M

2009-03-01

Given the public health importance of law modernization, we undertook a comparative analysis of policy efforts in 4 states (Alaska, South Carolina, Wisconsin, and Nebraska) that have considered public health law reform based on the Turning Point Model State Public Health Act. Through national legislative tracking and state case studies, we investigated how the Turning Point Act's model legal language has been considered for incorporation into state law and analyzed key facilitating and inhibiting factors for public health law reform. Our findings provide the practice community with a research base to facilitate further law reform and inform future scholarship on the role of law as a determinant of the public's health.

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

2013-08-01

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES

A Comparative Meta-Analysis of 5E and Traditional Approaches in Turkey

ERIC Educational Resources Information Center

Anil, Özgür; Batdi, Veli

2015-01-01

The aim of this study is to compare the 5E learning model with traditional learning methods in terms of their effect on students' academic achievement, retention and attitude scores. In this context, the meta-analytic method known as the "analysis of analyses" was used and a review undertaken of the studies and theses (N = 14) executed…

Model-based meta-analysis for comparing Vitamin D2 and D3 parent-metabolite pharmacokinetics.

PubMed

Ocampo-Pelland, Alanna S; Gastonguay, Marc R; Riggs, Matthew M

2017-08-01

Association of Vitamin D (D3 & D2) and its 25OHD metabolite (25OHD3 & 25OHD2) exposures with various diseases is an active research area. D3 and D2 dose-equivalency and each form's ability to raise 25OHD concentrations are not well-defined. The current work describes a population pharmacokinetic (PK) model for D2 and 25OHD2 and the use of a previously developed D3-25OHD3 PK model [1] for comparing D3 and D2-related exposures. Public-source D2 and 25OHD2 PK data in healthy or osteoporotic populations, including 17 studies representing 278 individuals (15 individual-level and 18 arm-level units), were selected using search criteria in PUBMED. Data included oral, single and multiple D2 doses (400-100,000 IU/d). Nonlinear mixed effects models were developed simultaneously for D2 and 25OHD2 PK (NONMEM v7.2) by considering 1- and 2-compartment models with linear or nonlinear clearance. Unit-level random effects and residual errors were weighted by arm sample size. Model simulations compared 25OHD exposures, following repeated D2 and D3 oral administration across typical dosing and baseline ranges. D2 parent and metabolite were each described by 2-compartment models with numerous parameter estimates shared with the D3-25OHD3 model [1]. Notably, parent D2 was eliminated (converted to 25OHD) through a first-order clearance whereas the previously published D3 model [1] included a saturable non-linear clearance. Similar to 25OHD3 PK model results [1], 25OHD2 was eliminated by a first-order clearance, which was almost twice as fast as the former. Simulations at lower baselines, following lower equivalent doses, indicated that D3 was more effective than D2 at raising 25OHD concentrations. Due to saturation of D3 clearance, however, at higher doses or baselines, the probability of D2 surpassing D3's ability to raise 25OHD concentrations increased substantially. Since 25OHD concentrations generally surpassed 75 nmol/L at these higher baselines by 3 months, there would be no

A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Gatien, Philippe; Renaud, Benoit; Brissette, François; Martel, Jean-Luc

2015-10-01

This study aims to test whether a weighted combination of several hydrological models can simulate flows more accurately than the models taken individually. In addition, the project attempts to identify the most efficient model averaging method and the optimal number of models to include in the weighting scheme. In order to address the first objective, streamflow was simulated using four lumped hydrological models (HSAMI, HMETS, MOHYSE and GR4J-6), each of which were calibrated with three different objective functions on 429 watersheds. The resulting 12 hydrographs (4 models × 3 metrics) were weighted and combined with the help of 9 averaging methods which are the simple arithmetic mean (SAM), Akaike information criterion (AICA), Bates-Granger (BGA), Bayes information criterion (BICA), Bayesian model averaging (BMA), Granger-Ramanathan average variant A, B and C (GRA, GRB and GRC) and the average by SCE-UA optimization (SCA). The same weights were then applied to the hydrographs in validation mode, and the Nash-Sutcliffe Efficiency metric was measured between the averaged and observed hydrographs. Statistical analyses were performed to compare the accuracy of weighted methods to that of individual models. A Kruskal-Wallis test and a multi-objective optimization algorithm were then used to identify the most efficient weighted method and the optimal number of models to integrate. Results suggest that the GRA, GRB, GRC and SCA weighted methods perform better than the individual members. Model averaging from these four methods were superior to the best of the individual members in 76% of the cases. Optimal combinations on all watersheds included at least one of each of the four hydrological models. None of the optimal combinations included all members of the ensemble of 12 hydrographs. The Granger-Ramanathan average variant C (GRC) is recommended as the best compromise between accuracy, speed of execution, and simplicity.

A comparative sensitivity analysis focused on wet deposition models for the Fukushima and Chernobyl atmospheric dispersion events

NASA Astrophysics Data System (ADS)

Quérel, Arnaud; Roustan, Yelva; Quélo, Denis; Bocquet, Marc; Winiarek, Victor

2014-05-01

In order to model the transport of radionuclides bound to atmospheric particles and the ground contamination at the synoptic scale, the wet deposition is a crucial point. Usually, the wet deposition is divided in two different mechanisms, the below-cloud scavenging (washout) and the in-cloud scavenging (rainout). Since the micro-physics of both deposition processes is not well known yet, the modeling of the wet deposition of particles at the synoptic scale is uncertain and difficult to validate. This leads to an abundance of wet deposition models, none of them being fully adequate. The existing models of particle scavenging can be distinguished by the nature and the number of physical parameters they rely on. For instance the scavenging coefficient variability can be determined only by the rainfall intensity or take into account the rainfall intensity and the particle size distribution. Beyond their intrinsic formulations, the deposition models are sensitive to the input data necessary to use them, cloud height for instance. Finally, the simulated ground deposition is more or less sensitive to the choices of the overall-models involved in the atmospheric transport of particles and the meteorology in general. For accidental atmospheric releases, the uncertainties linked to the source-term are for instance crucial, what justifies the use of different ones in the study. The Polyphemus air quality system is used to perform the simulations of the radioactive dispersion, considering Caesium-137 as particulate matter for the accidental releases from the Fukushima and Chernobyl nuclear power plants. In this study, two different approaches are used. In the first one, the influence of the different components taking part in the scavenging modeling are confronted separately (whether the scavenging models or the overall models). The second approach is a global sensitivity analysis computed both on the Chernobyl and Fukushima cases. It relies on simulations performed with

Royal London space analysis: plaster versus digital model assessment.

PubMed

Grewal, Balpreet; Lee, Robert T; Zou, Lifong; Johal, Ama

2017-06-01

With the advent of digital study models, the importance of being able to evaluate space requirements becomes valuable to treatment planning and the justification for any required extraction pattern. This study was undertaken to compare the validity and reliability of the Royal London space analysis (RLSA) undertaken on plaster as compared with digital models. A pilot study (n = 5) was undertaken on plaster and digital models to evaluate the feasibility of digital space planning. This also helped to determine the sample size calculation and as a result, 30 sets of study models with specified inclusion criteria were selected. All five components of the RLSA, namely: crowding; depth of occlusal curve; arch expansion/contraction; incisor antero-posterior advancement and inclination (assessed from the pre-treatment lateral cephalogram) were accounted for in relation to both model types. The plaster models served as the gold standard. Intra-operator measurement error (reliability) was evaluated along with a direct comparison of the measured digital values (validity) with the plaster models. The measurement error or coefficient of repeatability was comparable for plaster and digital space analyses and ranged from 0.66 to 0.95mm. No difference was found between the space analysis performed in either the upper or lower dental arch. Hence, the null hypothesis was accepted. The digital model measurements were consistently larger, albeit by a relatively small amount, than the plaster models (0.35mm upper arch and 0.32mm lower arch). No difference was detected in the RLSA when performed using either plaster or digital models. Thus, digital space analysis provides a valid and reproducible alternative method in the new era of digital records. © The Author 2016. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

Python package for model STructure ANalysis (pySTAN)

NASA Astrophysics Data System (ADS)

Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

2013-04-01

The selection and identification of a suitable hydrological model structure is more than fitting parameters of a model structure to reproduce a measured hydrograph. The procedure is highly dependent on various criteria, i.e. the modelling objective, the characteristics and the scale of the system under investigation as well as the available data. Rigorous analysis of the candidate model structures is needed to support and objectify the selection of the most appropriate structure for a specific case (or eventually justify the use of a proposed ensemble of structures). This holds both in the situation of choosing between a limited set of different structures as well as in the framework of flexible model structures with interchangeable components. Many different methods to evaluate and analyse model structures exist. This leads to a sprawl of available methods, all characterized by different assumptions, changing conditions of application and various code implementations. Methods typically focus on optimization, sensitivity analysis or uncertainty analysis, with backgrounds from optimization, machine-learning or statistics amongst others. These methods also need an evaluation metric (objective function) to compare the model outcome with some observed data. However, for current methods described in literature, implementations are not always transparent and reproducible (if available at all). No standard procedures exist to share code and the popularity (and amount of applications) of the methods is sometimes more dependent on the availability than the merits of the method. Moreover, new implementations of existing methods are difficult to verify and the different theoretical backgrounds make it difficult for environmental scientists to decide about the usefulness of a specific method. A common and open framework with a large set of methods can support users in deciding about the most appropriate method. Hence, it enables to simultaneously apply and compare different

Comparative study: TQ and Lean Production ownership models in health services

PubMed Central

Eiro, Natalia Yuri; Torres-Junior, Alvair Silveira

2015-01-01

Objective: compare the application of Total Quality (TQ) models used in processes of a health service, cases of lean healthcare and literature from another institution that has also applied this model. Method: this is a qualitative research that was conducted through a descriptive case study. Results: through critical analysis of the institutions studied it was possible to make a comparison between the traditional quality approach checked in one case and the theoretical and practice lean production approach used in another case and the specifications are described below. Conclusion: the research identified that the lean model was better suited for people that work systemically and generate the flow. It also pointed towards some potential challenges in the introduction and implementation of lean methods in health. PMID:26487134

Nursing home quality: a comparative analysis using CMS Nursing Home Compare data to examine differences between rural and nonrural facilities.

PubMed

Lutfiyya, May Nawal; Gessert, Charles E; Lipsky, Martin S

2013-08-01

Advances in medicine and an aging US population suggest that there will be an increasing demand for nursing home services. Although nursing homes are highly regulated and scrutinized, their quality remains a concern and may be a greater issue to those living in rural communities. Despite this, few studies have investigated differences in the quality of nursing home care across the rural-urban continuum. The purpose of this study was to compare the quality of rural and nonrural nursing homes by using aggregated rankings on multiple quality measures calculated by the Centers for Medicare and Medicaid Services and reported on their Nursing Home Compare Web site. Independent-sample t tests were performed to compare the mean ratings on the reported quality measures of rural and nonrural nursing homes. A linear mixed binary logistic regression model controlling for state was performed to determine if the covariates of ownership, number of beds, and geographic locale were associated with a higher overall quality rating. Of the 15,177 nursing homes included in the study sample, 69.2% were located in nonrural areas and 30.8% in rural areas. The t test analysis comparing the overall, health inspection, staffing, and quality measure ratings of rural and nonrural nursing homes yielded statistically significant results for 3 measures, 2 of which (overall ratings and health inspections) favored rural nursing homes. Although a higher percentage of nursing homes (44.8%-42.2%) received a 4-star or higher rating, regression analysis using an overall rating of 4 stars or higher as the dependent variable revealed that when controlling for state and adjusting for size and ownership, rural nursing homes were less likely to have a 4-star or higher rating when compared with nonrural nursing homes (OR = .901, 95% CI 0.824-0.986). Mixed model logistic regression analysis suggested that rural nursing home quality was not comparable to that of nonrural nursing homes. When controlling for

Skull Development, Ossification Pattern, and Adult Shape in the Emerging Lizard Model Organism Pogona vitticeps: A Comparative Analysis With Other Squamates.

PubMed

Ollonen, Joni; Da Silva, Filipe O; Mahlow, Kristin; Di-Poï, Nicolas

2018-01-01

The rise of the Evo-Devo field and the development of multidisciplinary research tools at various levels of biological organization have led to a growing interest in researching for new non-model organisms. Squamates (lizards and snakes) are particularly important for understanding fundamental questions about the evolution of vertebrates because of their high diversity and evolutionary innovations and adaptations that portrait a striking body plan change that reached its extreme in snakes. Yet, little is known about the intricate connection between phenotype and genotype in squamates, partly due to limited developmental knowledge and incomplete characterization of embryonic development. Surprisingly, squamate models have received limited attention in comparative developmental studies, and only a few species examined so far can be considered as representative and appropriate model organism for mechanistic Evo-Devo studies. Fortunately, the agamid lizard Pogona vitticeps (central bearded dragon) is one of the most popular, domesticated reptile species with both a well-established history in captivity and key advantages for research, thus forming an ideal laboratory model system and justifying his recent use in reptile biology research. We first report here the complete post-oviposition embryonic development for P. vitticeps based on standardized staging systems and external morphological characters previously defined for squamates. Whereas the overall morphological development follows the general trends observed in other squamates, our comparisons indicate major differences in the developmental sequence of several tissues, including early craniofacial characters. Detailed analysis of both embryonic skull development and adult skull shape, using a comparative approach integrating CT-scans and gene expression studies in P. vitticeps as well as comparative embryology and 3D geometric morphometrics in a large dataset of lizards and snakes, highlights the extreme adult

Skull Development, Ossification Pattern, and Adult Shape in the Emerging Lizard Model Organism Pogona vitticeps: A Comparative Analysis With Other Squamates

PubMed Central

Ollonen, Joni; Da Silva, Filipe O.; Mahlow, Kristin; Di-Poï, Nicolas

2018-01-01

The rise of the Evo-Devo field and the development of multidisciplinary research tools at various levels of biological organization have led to a growing interest in researching for new non-model organisms. Squamates (lizards and snakes) are particularly important for understanding fundamental questions about the evolution of vertebrates because of their high diversity and evolutionary innovations and adaptations that portrait a striking body plan change that reached its extreme in snakes. Yet, little is known about the intricate connection between phenotype and genotype in squamates, partly due to limited developmental knowledge and incomplete characterization of embryonic development. Surprisingly, squamate models have received limited attention in comparative developmental studies, and only a few species examined so far can be considered as representative and appropriate model organism for mechanistic Evo-Devo studies. Fortunately, the agamid lizard Pogona vitticeps (central bearded dragon) is one of the most popular, domesticated reptile species with both a well-established history in captivity and key advantages for research, thus forming an ideal laboratory model system and justifying his recent use in reptile biology research. We first report here the complete post-oviposition embryonic development for P. vitticeps based on standardized staging systems and external morphological characters previously defined for squamates. Whereas the overall morphological development follows the general trends observed in other squamates, our comparisons indicate major differences in the developmental sequence of several tissues, including early craniofacial characters. Detailed analysis of both embryonic skull development and adult skull shape, using a comparative approach integrating CT-scans and gene expression studies in P. vitticeps as well as comparative embryology and 3D geometric morphometrics in a large dataset of lizards and snakes, highlights the extreme adult

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

Comparative molecular analysis of early and late cancer cachexia-induced muscle wasting in mouse models.

PubMed

Sun, Rulin; Zhang, Santao; Lu, Xing; Hu, Wenjun; Lou, Ning; Zhao, Yan; Zhou, Jia; Zhang, Xiaoping; Yang, Hongmei

2016-12-01

Cancer-induced muscle wasting, which commonly occurs in cancer cachexia, is characterized by impaired quality of life and poor patient survival. To identify an appropriate treatment, research on the mechanism underlying muscle wasting is essential. Thus far, studies on muscle wasting using cancer cachectic models have generally focused on early cancer cachexia (ECC), before severe body weight loss occurs. In the present study, we established models of ECC and late cancer cachexia (LCC) and compared different stages of cancer cachexia using two cancer cachectic mouse models induced by colon-26 (C26) adenocarcinoma or Lewis lung carcinoma (LLC). In each model, tumor-bearing (TB) and control (CN) mice were injected with cancer cells and PBS, respectively. The TB and CN mice, which were euthanized on the 24th day or the 36th day after injection, were defined as the ECC and ECC-CN mice or the LCC and LCC-CN mice. In addition, the tissues were harvested and analyzed. We found that both the ECC and LCC mice developed cancer cachexia. The amounts of muscle loss differed between the ECC and LCC mice. Moreover, the expression of some molecules was altered in the muscles from the LCC mice but not in those from the ECC mice compared with their CN mice. In conclusion, the molecules with altered expression in the muscles from the ECC and LCC mice were not exactly the same. These findings may provide some clues for therapy which could prevent the muscle wasting in cancer cachexia from progression to the late stage.

Comparative Analysis of Four Manpower Nursing Requirements Models. Health Manpower References. [Nurse Planning Information Series, No. 6].

ERIC Educational Resources Information Center

Deane, Robert T.; Ro, Kong-Kyun

The analysis and description of four manpower nursing requirements models-- the Pugh-Roberts, the Vector, the Community Systems Foundation (CSF), and the Western Interstate Commission of Higher Education (WICHE)--are presented in this report. The introduction provides an overview of the project which was designed to analyze these different models.…

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Transitions in State Public Health Law: Comparative Analysis of State Public Health Law Reform Following the Turning Point Model State Public Health Act

PubMed Central

Meier, Benjamin Mason; Gebbie, Kristine M.

2009-01-01

Given the public health importance of law modernization, we undertook a comparative analysis of policy efforts in 4 states (Alaska, South Carolina, Wisconsin, and Nebraska) that have considered public health law reform based on the Turning Point Model State Public Health Act. Through national legislative tracking and state case studies, we investigated how the Turning Point Act's model legal language has been considered for incorporation into state law and analyzed key facilitating and inhibiting factors for public health law reform. Our findings provide the practice community with a research base to facilitate further law reform and inform future scholarship on the role of law as a determinant of the public's health. PMID:19150900

A general numerical model for wave rotor analysis

NASA Technical Reports Server (NTRS)

Paxson, Daniel W.

1992-01-01

Wave rotors represent one of the promising technologies for achieving very high core temperatures and pressures in future gas turbine engines. Their operation depends upon unsteady gas dynamics and as such, their analysis is quite difficult. This report describes a numerical model which has been developed to perform such an analysis. Following a brief introduction, a summary of the wave rotor concept is given. The governing equations are then presented, along with a summary of the assumptions used to obtain them. Next, the numerical integration technique is described. This is an explicit finite volume technique based on the method of Roe. The discussion then focuses on the implementation of appropriate boundary conditions. Following this, some results are presented which first compare the numerical approximation to the governing differential equations and then compare the overall model to an actual wave rotor experiment. Finally, some concluding remarks are presented concerning the limitations of the simplifying assumptions and areas where the model may be improved.

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

PubMed

Halevy, Tomer; Urbach, Achia

2014-10-24

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

A comparative analysis of prognostic factor models for follicular lymphoma based on a phase III trial of CHOP-rituximab versus CHOP + 131iodine--tositumomab.

PubMed

Press, Oliver W; Unger, Joseph M; Rimsza, Lisa M; Friedberg, Jonathan W; LeBlanc, Michael; Czuczman, Myron S; Kaminski, Mark; Braziel, Rita M; Spier, Catherine; Gopal, Ajay K; Maloney, David G; Cheson, Bruce D; Dakhil, Shaker R; Miller, Thomas P; Fisher, Richard I

2013-12-01

There is currently no consensus on optimal frontline therapy for patients with follicular lymphoma. We analyzed a phase III randomized intergroup trial comparing six cycles of CHOP-R (cyclophosphamide-Adriamycin-vincristine-prednisone (Oncovin)-rituximab) with six cycles of CHOP followed by iodine-131 tositumomab radioimmunotherapy (RIT) to assess whether any subsets benefited more from one treatment or the other, and to compare three prognostic models. We conducted univariate and multivariate Cox regression analyses of 532 patients enrolled on this trial and compared the prognostic value of the FLIPI (follicular lymphoma international prognostic index), FLIPI2, and LDH + β2M (lactate dehydrogenase + β2-microglobulin) models. Outcomes were excellent, but not statistically different between the two study arms [5-year progression-free survival (PFS) of 60% with CHOP-R and 66% with CHOP-RIT (P = 0.11); 5-year overall survival (OS) of 92% with CHOP-R and 86% with CHOP-RIT (P = 0.08); overall response rate of 84% for both arms]. The only factor found to potentially predict the impact of treatment was serum β2M; among patients with normal β2M, CHOP-RIT patients had better PFS compared with CHOP-R patients, whereas among patients with high serum β2M, PFS by arm was similar (interaction P value = 0.02). All three prognostic models (FLIPI, FLIPI2, and LDH + β2M) predicted both PFS and OS well, though the LDH + β2M model is easiest to apply and identified an especially poor risk subset. In an exploratory analysis using the latter model, there was a statistically significant trend suggesting that low-risk patients had superior observed PFS if treated with CHOP-RIT, whereas high-risk patients had a better PFS with CHOP-R. ©2013 AACR.

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

PubMed

Zhai, Peng; Yang, Longshu; Guo, Xiao; Wang, Zhe; Guo, Jiangtao; Wang, Xiaoqi; Zhu, Huaiqiu

2017-10-02

During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis

Bayesian analysis of CCDM models

NASA Astrophysics Data System (ADS)

Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

2017-09-01

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

Beware the black box: investigating the sensitivity of FEA simulations to modelling factors in comparative biomechanics.

PubMed

Walmsley, Christopher W; McCurry, Matthew R; Clausen, Phillip D; McHenry, Colin R

2013-01-01

Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be 'reasonable' are often assumed to have little influence on the results and their interpretation. HERE WE REPORT AN EXTENSIVE SENSITIVITY ANALYSIS WHERE HIGH RESOLUTION FINITE ELEMENT (FE) MODELS OF MANDIBLES FROM SEVEN SPECIES OF CROCODILE WERE ANALYSED UNDER LOADS TYPICAL FOR COMPARATIVE ANALYSIS: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets would

Beware the black box: investigating the sensitivity of FEA simulations to modelling factors in comparative biomechanics

PubMed Central

McCurry, Matthew R.; Clausen, Phillip D.; McHenry, Colin R.

2013-01-01

Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be ‘reasonable’ are often assumed to have little influence on the results and their interpretation. Here we report an extensive sensitivity analysis where high resolution finite element (FE) models of mandibles from seven species of crocodile were analysed under loads typical for comparative analysis: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets

Using multiple group modeling to test moderators in meta-analysis.

PubMed

Schoemann, Alexander M

2016-12-01

Meta-analysis is a popular and flexible analysis that can be fit in many modeling frameworks. Two methods of fitting meta-analyses that are growing in popularity are structural equation modeling (SEM) and multilevel modeling (MLM). By using SEM or MLM to fit a meta-analysis researchers have access to powerful techniques associated with SEM and MLM. This paper details how to use one such technique, multiple group analysis, to test categorical moderators in meta-analysis. In a multiple group meta-analysis a model is fit to each level of the moderator simultaneously. By constraining parameters across groups any model parameter can be tested for equality. Using multiple groups to test for moderators is especially relevant in random-effects meta-analysis where both the mean and the between studies variance of the effect size may be compared across groups. A simulation study and the analysis of a real data set are used to illustrate multiple group modeling with both SEM and MLM. Issues related to multiple group meta-analysis and future directions for research are discussed. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparative analysis of remotely-sensed data products via ecological niche modeling of avian influenza case occurrences in Middle Eastern poultry.

PubMed

Bodbyl-Roels, Sarah; Peterson, A Townsend; Xiao, Xiangming

2011-03-28

Ecological niche modeling integrates known sites of occurrence of species or phenomena with data on environmental variation across landscapes to infer environmental spaces potentially inhabited (i.e., the ecological niche) to generate predictive maps of potential distributions in geographic space. Key inputs to this process include raster data layers characterizing spatial variation in environmental parameters, such as vegetation indices from remotely sensed satellite imagery. The extent to which ecological niche models reflect real-world distributions depends on a number of factors, but an obvious concern is the quality and content of the environmental data layers. We assessed ecological niche model predictions of H5N1 avian flu presence quantitatively within and among four geographic regions, based on models incorporating two means of summarizing three vegetation indices derived from the MODIS satellite. We evaluated our models for predictive ability using partial ROC analysis and GLM ANOVA to compare performance among indices and regions. We found correlations between vegetation indices to be high, such that they contain information that overlaps broadly. Neither the type of vegetation index used nor method of summary affected model performance significantly. However, the degree to which model predictions had to be transferred (i.e., projected onto landscapes and conditions not represented on the landscape of training) impacted predictive strength greatly (within-region model predictions far out-performed models projected among regions). Our results provide the first quantitative tests of most appropriate uses of different remotely sensed data sets in ecological niche modeling applications. While our testing did not result in a decisive "best" index product or means of summarizing indices, it emphasizes the need for careful evaluation of products used in modeling (e.g. matching temporal dimensions and spatial resolution) for optimum performance, instead of

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Regression Model Optimization for the Analysis of Experimental Data

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2009-01-01

A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.

High Altitude Long Endurance UAV Analysis Model Development and Application Study Comparing Solar Powered Airplane and Airship Station-Keeping Capabilities

NASA Technical Reports Server (NTRS)

Ozoroski, Thomas A.; Nickol, Craig L.; Guynn, Mark D.

2015-01-01

There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on

Comparing the Discrete and Continuous Logistic Models

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2008-01-01

The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)

Comparative Study Of Four Models Of Turbulence

NASA Technical Reports Server (NTRS)

Menter, Florian R.

1996-01-01

Report presents comparative study of four popular eddy-viscosity models of turbulence. Computations reported for three different adverse pressure-gradient flowfields. Detailed comparison of numerical results and experimental data given. Following models tested: Baldwin-Lomax, Johnson-King, Baldwin-Barth, and Wilcox.

Comparative analysis on the probability of being a good payer

NASA Astrophysics Data System (ADS)

Mihova, V.; Pavlov, V.

2017-10-01

Credit risk assessment is crucial for the bank industry. The current practice uses various approaches for the calculation of credit risk. The core of these approaches is the use of multiple regression models, applied in order to assess the risk associated with the approval of people applying for certain products (loans, credit cards, etc.). Based on data from the past, these models try to predict what will happen in the future. Different data requires different type of models. This work studies the causal link between the conduct of an applicant upon payment of the loan and the data that he completed at the time of application. A database of 100 borrowers from a commercial bank is used for the purposes of the study. The available data includes information from the time of application and credit history while paying off the loan. Customers are divided into two groups, based on the credit history: Good and Bad payers. Linear and logistic regression are applied in parallel to the data in order to estimate the probability of being good for new borrowers. A variable, which contains value of 1 for Good borrowers and value of 0 for Bad candidates, is modeled as a dependent variable. To decide which of the variables listed in the database should be used in the modelling process (as independent variables), a correlation analysis is made. Due to the results of it, several combinations of independent variables are tested as initial models - both with linear and logistic regression. The best linear and logistic models are obtained after initial transformation of the data and following a set of standard and robust statistical criteria. A comparative analysis between the two final models is made and scorecards are obtained from both models to assess new customers at the time of application. A cut-off level of points, bellow which to reject the applications and above it - to accept them, has been suggested for both the models, applying the strategy to keep the same Accept Rate as

A GIS-based approach for comparative analysis of potential fire risk assessment

NASA Astrophysics Data System (ADS)

Sun, Ying; Hu, Lieqiu; Liu, Huiping

2007-06-01

Urban fires are one of the most important sources of property loss and human casualty and therefore it is necessary to assess the potential fire risk with consideration of urban community safety. Two evaluation models are proposed, both of which are integrated with GIS. One is the single factor model concerning the accessibility of fire passage and the other is grey clustering approach based on the multifactor system. In the latter model, fourteen factors are introduced and divided into four categories involving security management, evacuation facility, construction resistance and fire fighting capability. A case study on campus of Beijing Normal University is presented to express the potential risk assessment models in details. A comparative analysis of the two models is carried out to validate the accuracy. The results are approximately consistent with each other. Moreover, modeling with GIS promotes the efficiency the potential risk assessment.

Comparative Numerical Analysis of Different Strengthening Systems of Historical Brick Arches

NASA Astrophysics Data System (ADS)

Zielińska, M.

2017-05-01

The article presents a comparative numerical analysis of various ways to strengthen historical brick arches. Five ways of strengthening brick arches with steel tie-rods have been proposed. Two of these involve the use of braces wrapped around pillars supporting the arch connected with a tie-rod; the other two ways involve the use of the tie-rods with welded metal sheets of different sizes; the latter involves the use of a tie-rod glued with the use of an epoxy adhesive. The collected data were compared with the reference model of the arch left without any interference. The results make it possible to evaluate the effectiveness of the methods by comparing displacements in the vertical and horizontal direction and stresses. The article indicates the direction of proper planning and design of the arch strengthening in brick structures in historical buildings.

Comparing Models of Spontaneous Variations, Maneuvers and Indexes to Assess Dynamic Cerebral Autoregulation.

PubMed

Chacón, Max; Noh, Sun-Ho; Landerretche, Jean; Jara, José L

2018-01-01

We analyzed the performance of linear and nonlinear models to assess dynamic cerebral autoregulation (dCA) from spontaneous variations in healthy subjects and compared it with the use of two known maneuvers to abruptly change arterial blood pressure (BP): thigh cuffs and sit-to-stand. Cerebral blood flow velocity and BP were measured simultaneously at rest and while the maneuvers were performed in 20 healthy subjects. To analyze the spontaneous variations, we implemented two types of models using support vector machine (SVM): linear and nonlinear finite impulse response models. The classic autoregulation index (ARI) and the more recently proposed model-free ARI (mfARI) were used as measures of dCA. An ANOVA analysis was applied to compare the different methods and the coefficient of variation was calculated to evaluate their variability. There are differences between indexes, but not between models and maneuvers. The mfARI index with the sit-to-stand maneuver shows the least variability. Support vector machine modeling of spontaneous variation with the mfARI index could be used for the assessment of dCA as an alternative to maneuvers to introduce large BP fluctuations.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue

CRITICA: coding region identification tool invoking comparative analysis

NASA Technical Reports Server (NTRS)

Badger, J. H.; Olsen, G. J.; Woese, C. R. (Principal Investigator)

1999-01-01

Gene recognition is essential to understanding existing and future DNA sequence data. CRITICA (Coding Region Identification Tool Invoking Comparative Analysis) is a suite of programs for identifying likely protein-coding sequences in DNA by combining comparative analysis of DNA sequences with more common noncomparative methods. In the comparative component of the analysis, regions of DNA are aligned with related sequences from the DNA databases; if the translation of the aligned sequences has greater amino acid identity than expected for the observed percentage nucleotide identity, this is interpreted as evidence for coding. CRITICA also incorporates noncomparative information derived from the relative frequencies of hexanucleotides in coding frames versus other contexts (i.e., dicodon bias). The dicodon usage information is derived by iterative analysis of the data, such that CRITICA is not dependent on the existence or accuracy of coding sequence annotations in the databases. This independence makes the method particularly well suited for the analysis of novel genomes. CRITICA was tested by analyzing the available Salmonella typhimurium DNA sequences. Its predictions were compared with the DNA sequence annotations and with the predictions of GenMark. CRITICA proved to be more accurate than GenMark, and moreover, many of its predictions that would seem to be errors instead reflect problems in the sequence databases. The source code of CRITICA is freely available by anonymous FTP (rdp.life.uiuc.edu in/pub/critica) and on the World Wide Web (http:/(/)rdpwww.life.uiuc.edu).

A comparative study of mixture cure models with covariate

NASA Astrophysics Data System (ADS)

Leng, Oh Yit; Khalid, Zarina Mohd

2017-05-01

In survival analysis, the survival time is assumed to follow a non-negative distribution, such as the exponential, Weibull, and log-normal distributions. In some cases, the survival time is influenced by some observed factors. The absence of these observed factors may cause an inaccurate estimation in the survival function. Therefore, a survival model which incorporates the influences of observed factors is more appropriate to be used in such cases. These observed factors are included in the survival model as covariates. Besides that, there are cases where a group of individuals who are cured, that is, not experiencing the event of interest. Ignoring the cure fraction may lead to overestimate in estimating the survival function. Thus, a mixture cure model is more suitable to be employed in modelling survival data with the presence of a cure fraction. In this study, three mixture cure survival models are used to analyse survival data with a covariate and a cure fraction. The first model includes covariate in the parameterization of the susceptible individuals survival function, the second model allows the cure fraction to depend on covariate, and the third model incorporates covariate in both cure fraction and survival function of susceptible individuals. This study aims to compare the performance of these models via a simulation approach. Therefore, in this study, survival data with varying sample sizes and cure fractions are simulated and the survival time is assumed to follow the Weibull distribution. The simulated data are then modelled using the three mixture cure survival models. The results show that the three mixture cure models are more appropriate to be used in modelling survival data with the presence of cure fraction and an observed factor.

Modeling corrosion inhibition efficacy of small organic molecules as non-toxic chromate alternatives using comparative molecular surface analysis (CoMSA).

PubMed

Fernandez, Michael; Breedon, Michael; Cole, Ivan S; Barnard, Amanda S

2016-10-01

Traditionally many structural alloys are protected by primer coatings loaded with corrosion inhibiting additives. Strontium Chromate (or other chromates) have been shown to be extremely effectively inhibitors, and find extensive use in protective primer formulations. Unfortunately, hexavalent chromium which imbues these coatings with their corrosion inhibiting properties is also highly toxic, and their use is being increasingly restricted by legislation. In this work we explore a novel tridimensional Quantitative-Structure Property Relationship (3D-QSPR) approach, comparative molecular surface analysis (CoMSA), which was developed to recognize "high-performing" corrosion inhibitor candidates from the distributions of electronegativity, polarizability and van der Waals volume on the molecular surfaces of 28 small organic molecules. Multivariate statistical analysis identified five prototypes molecules, which are capable of explaining 71% of the variance within the inhibitor data set; whilst a further five molecules were also identified as archetypes, describing 75% of data variance. All active corrosion inhibitors, at a 80% threshold, were successfully recognized by the CoMSA model with adequate specificity and precision higher than 70% and 60%, respectively. The model was also capable of identifying structural patterns, that revealed reasonable starting points for where structural changes may augment corrosion inhibition efficacy. The presented methodology can be applied to other functional molecules and extended to cover structure-activity studies in a diverse range of areas such as drug design and novel material discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and application of a comparative fatty acid analysis method to investigate voriconazole-induced hepatotoxicity.

PubMed

Chen, Guan-yuan; Chiu, Huai-hsuan; Lin, Shu-wen; Tseng, Yufeng Jane; Tsai, Sung-jeng; Kuo, Ching-hua

2015-01-01

As fatty acids play an important role in biological regulation, the profiling of fatty acid expression has been used to discover various disease markers and to understand disease mechanisms. This study developed an effective and accurate comparative fatty acid analysis method using differential labeling to speed up the metabolic profiling of fatty acids. Fatty acids were derivatized with unlabeled (D0) or deuterated (D3) methanol, followed by GC-MS analysis. The comparative fatty acid analysis method was validated using a series of samples with different ratios of D0/D3-labeled fatty acid standards and with mouse liver extracts. Using a lipopolysaccharide (LPS)-treated mouse model, we found that the fatty acid profiles after LPS treatment were similar between the conventional single-sample analysis approach and the proposed comparative approach, with a Pearson's correlation coefficient of approximately 0.96. We applied the comparative method to investigate voriconazole-induced hepatotoxicity and revealed the toxicity mechanism as well as the potential of using fatty acids as toxicity markers. In conclusion, the comparative fatty acid profiling technique was determined to be fast and accurate and allowed the discovery of potential fatty acid biomarkers in a more economical and efficient manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

Comparative promoter analysis allows de novo identification of specialized cell junction-associated proteins.

PubMed

Cohen, Clemens D; Klingenhoff, Andreas; Boucherot, Anissa; Nitsche, Almut; Henger, Anna; Brunner, Bodo; Schmid, Holger; Merkle, Monika; Saleem, Moin A; Koller, Klaus-Peter; Werner, Thomas; Gröne, Hermann-Josef; Nelson, Peter J; Kretzler, Matthias

2006-04-11

Shared transcription factor binding sites that are conserved in distance and orientation help control the expression of gene products that act together in the same biological context. New bioinformatics approaches allow the rapid characterization of shared promoter structures and can be used to find novel interacting molecules. Here, these principles are demonstrated by using molecules linked to the unique functional unit of the glomerular slit diaphragm. An evolutionarily conserved promoter model was generated by comparative genomics in the proximal promoter regions of the slit diaphragm-associated molecule nephrin. Phylogenetic promoter fingerprints of known elements of the slit diaphragm complex identified the nephrin model in the promoter region of zonula occludens-1 (ZO-1). Genome-wide scans using this promoter model effectively predicted a previously unrecognized slit diaphragm molecule, cadherin-5. Nephrin, ZO-1, and cadherin-5 mRNA showed stringent coexpression across a diverse set of human glomerular diseases. Comparative promoter analysis can identify regulatory pathways at work in tissue homeostasis and disease processes.

Comparative biology of cystic fibrosis animal models.

PubMed

Fisher, John T; Zhang, Yulong; Engelhardt, John F

2011-01-01

Animal models of human diseases are critical for dissecting mechanisms of pathophysiology and developing therapies. In the context of cystic fibrosis (CF), mouse models have been the dominant species by which to study CF disease processes in vivo for the past two decades. Although much has been learned through these CF mouse models, limitations in the ability of this species to recapitulate spontaneous lung disease and several other organ abnormalities seen in CF humans have created a need for additional species on which to study CF. To this end, pig and ferret CF models have been generated by somatic cell nuclear transfer and are currently being characterized. These new larger animal models have phenotypes that appear to closely resemble human CF disease seen in newborns, and efforts to characterize their adult phenotypes are ongoing. This chapter will review current knowledge about comparative lung cell biology and cystic fibrosis transmembrane conductance regulator (CFTR) biology among mice, pigs, and ferrets that has implications for CF disease modeling in these species. We will focus on methods used to compare the biology and function of CFTR between these species and their relevance to phenotypes seen in the animal models. These cross-species comparisons and the development of both the pig and the ferret CF models may help elucidate pathophysiologic mechanisms of CF lung disease and lead to new therapeutic approaches.

Howard University: A Comparative Fiscal Analysis.

ERIC Educational Resources Information Center

Inman, Deborah; And Others

This report presents a fiscal analysis of Howard University (District of Columbia) including: (1) general education revenues; (2) education and general expenditures; and (3) faculty salaries. The study compared Howard University to four different groups of higher education institutions: similar private institutions with hospitals; public…

Comparative assessment of turbulence model in predicting airflow over a NACA 0010 airfoil

NASA Astrophysics Data System (ADS)

Panday, Shoyon; Khan, Nafiz Ahmed; Rasel, Md; Faisal, Kh. Md.; Salam, Md. Abdus

2017-06-01

Nowadays the role of computational fluid dynamics to predict the flow behavior over airfoil is quite prominent. Most often a 2-D subsonic flow simulation is carried out over an airfoil at a certain Reynolds number and various angles of attack obtained by different turbulence models those are based on governing equations. The commonly used turbulence models are K-ɛpsilon, K-omega, Spalart Allmaras etc. Variation in turbulence model effectively influences the result of analysis. Here a comparative study is represented to show the effect of different turbulence models for a 2-D flow analysis over a National Advisory Committee for Aeronautics (NACA) airfoil 0010. This airfoil was analysed at 200000 Re number in 10 different angle of attacks at a constant speed of 21.6 m/s. Numbers of two dimensional flow simulation was run by changing the turbulence model, for each AOA. In accordance with the variation of result for different turbulence model, it was also found that for which model, attained result is close enough to experimental outcome from a low subsonic wind tunnel AF100. This paper also documents the effect of high and low angle of attack on the flow behaviour over an airfoil.

Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

PubMed

Chen, Hongming; Carlsson, Lars; Eriksson, Mats; Varkonyi, Peter; Norinder, Ulf; Nilsson, Ingemar

2013-06-24

A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

Comparing the cognitive differences resulting from modeling instruction: Using computer microworld and physical object instruction to model real world problems

NASA Astrophysics Data System (ADS)

Oursland, Mark David

This study compared the modeling achievement of students receiving mathematical modeling instruction using the computer microworld, Interactive Physics, and students receiving instruction using physical objects. Modeling instruction included activities where students applied the (a) linear model to a variety of situations, (b) linear model to two-rate situations with a constant rate, (c) quadratic model to familiar geometric figures. Both quantitative and qualitative methods were used to analyze achievement differences between students (a) receiving different methods of modeling instruction, (b) with different levels of beginning modeling ability, or (c) with different levels of computer literacy. Student achievement was analyzed quantitatively through a three-factor analysis of variance where modeling instruction, beginning modeling ability, and computer literacy were used as the three independent factors. The SOLO (Structure of the Observed Learning Outcome) assessment framework was used to design written modeling assessment instruments to measure the students' modeling achievement. The same three independent factors were used to collect and analyze the interviews and observations of student behaviors. Both methods of modeling instruction used the data analysis approach to mathematical modeling. The instructional lessons presented problem situations where students were asked to collect data, analyze the data, write a symbolic mathematical equation, and use equation to solve the problem. The researcher recommends the following practice for modeling instruction based on the conclusions of this study. A variety of activities with a common structure are needed to make explicit the modeling process of applying a standard mathematical model. The modeling process is influenced strongly by prior knowledge of the problem context and previous modeling experiences. The conclusions of this study imply that knowledge of the properties about squares improved the students

Model-Based Safety Analysis

NASA Technical Reports Server (NTRS)

Joshi, Anjali; Heimdahl, Mats P. E.; Miller, Steven P.; Whalen, Mike W.

2006-01-01

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Highly comparative time-series analysis: the empirical structure of time series and their methods.

PubMed

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Highly comparative time-series analysis: the empirical structure of time series and their methods

PubMed Central

Fulcher, Ben D.; Little, Max A.; Jones, Nick S.

2013-01-01

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines. PMID:23554344

An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models

ERIC Educational Resources Information Center

Cho, Sun-Joo; Suh, Youngsuk; Lee, Woo-yeol

2016-01-01

The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called…

National Launch System comparative economic analysis

NASA Technical Reports Server (NTRS)

Prince, A.

1992-01-01

Results are presented from an analysis of economic benefits (or losses), in the form of the life cycle cost savings, resulting from the development of the National Launch System (NLS) family of launch vehicles. The analysis was carried out by comparing various NLS-based architectures with the current Shuttle/Titan IV fleet. The basic methodology behind this NLS analysis was to develop a set of annual payload requirements for the Space Station Freedom and LEO, to design launch vehicle architectures around these requirements, and to perform life-cycle cost analyses on all of the architectures. A SEI requirement was included. Launch failure costs were estimated and combined with the relative reliability assumptions to measure the effects of losses. Based on the analysis, a Shuttle/NLS architecture evolving into a pressurized-logistics-carrier/NLS architecture appears to offer the best long-term cost benefit.

A Statistical Test for Comparing Nonnested Covariance Structure Models.

ERIC Educational Resources Information Center

Levy, Roy; Hancock, Gregory R.

While statistical procedures are well known for comparing hierarchically related (nested) covariance structure models, statistical tests for comparing nonhierarchically related (nonnested) models have proven more elusive. While isolated attempts have been made, none exists within the commonly used maximum likelihood estimation framework, thereby…

Mental Models about Seismic Effects: Students' Profile Based Comparative Analysis

ERIC Educational Resources Information Center

Moutinho, Sara; Moura, Rui; Vasconcelos, Clara

2016-01-01

Nowadays, meaningful learning takes a central role in science education and is based in mental models that allow the representation of the real world by individuals. Thus, it is essential to analyse the student's mental models by promoting an easier reconstruction of scientific knowledge, by allowing them to become consistent with the curricular…

Small-molecule ligand docking into comparative models with Rosetta

PubMed Central

Combs, Steven A; DeLuca, Samuel L; DeLuca, Stephanie H; Lemmon, Gordon H; Nannemann, David P; Nguyen, Elizabeth D; Willis, Jordan R; Sheehan, Jonathan H; Meiler, Jens

2017-01-01

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5–7 h, with additional time allocated for computer generation of models. PMID:23744289

A Comparative Analysis of Spatial Visualization Ability and Drafting Models for Industrial and Technology Education Students

ERIC Educational Resources Information Center

Katsioloudis, Petros; Jovanovic, Vukica; Jones, Mildred

2014-01-01

The main purpose of this study was to determine significant positive effects among the use of three different types of drafting models, and to identify whether any differences exist towards promotion of spatial visualization ability for students in Industrial Technology and Technology Education courses. In particular, the study compared the use of…

Biomechanical analysis comparing natural and alloplastic temporomandibular joint replacement using a finite element model.

PubMed

Mesnard, Michel; Ramos, Antonio; Ballu, Alex; Morlier, Julien; Cid, M; Simoes, J A

2011-04-01

Prosthetic materials and bone present quite different mechanical properties. Consequently, mandible reconstruction with metallic materials (or a mandible condyle implant) modifies the physiologic behavior of the mandible (stress, strain patterns, and condyle displacements). The changing of bone strain distribution results in an adaptation of the temporomandibular joint, including articular contacts. Using a validated finite element model, the natural mandible strains and condyle displacements were evaluated. Modifications of strains and displacements were then assessed for 2 different temporomandibular joint implants. Because materials and geometry play important key roles, mechanical properties of cortical bone were taken into account in models used in finite element analysis. The finite element model allowed verification of the worst loading configuration of the mandibular condyle. Replacing the natural condyle by 1 of the 2 tested implants, the results also show the importance of the implant geometry concerning biomechanical mandibular behavior. The implant geometry and stiffness influenced mainly strain distribution. The different forces applied to the mandible by the elevator muscles, teeth, and joint loads indicate that the finite element model is a relevant tool to optimize implant geometry or, in a subsequent study, to choose a more suitable distribution of the screws. Bone screws (number and position) have a significant influence on mandibular behavior and on implant stress pattern. Stress concentration and implant fracture must be avoided. Copyright © 2011 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Comparative analysis of ventricular assist devices (POLVAD and POLVAD_EXT) based on multiscale FEM model.

PubMed

Milenin, Andrzej; Kopernik, Magdalena

2011-01-01

The prosthesis - pulsatory ventricular assist device (VAD) - is made of polyurethane (PU) and biocompatible TiN deposited by pulsed laser deposition (PLD) method. The paper discusses the numerical modelling and computer-aided design of such an artificial organ. Two types of VADs: POLVAD and POLVAD_EXT are investigated. The main tasks and assumptions of the computer program developed are presented. The multiscale model of VAD based on finite element method (FEM) is introduced and the analysis of the stress-strain state in macroscale for the blood chamber in both versions of VAD is shown, as well as the verification of the results calculated by applying ABAQUS, a commercial FEM code. The FEM code developed is based on a new approach to the simulation of multilayer materials obtained by using PLD method. The model in microscale includes two components, i.e., model of initial stresses (residual stress) caused by the deposition process and simulation of active loadings observed in the blood chamber of POLVAD and POLVAD_EXT. The computed distributions of stresses and strains in macro- and microscales are helpful in defining precisely the regions of blood chamber, which can be defined as the failure-source areas.

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

NASA Astrophysics Data System (ADS)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

Comparative Genome Analysis of Enterobacter cloacae

PubMed Central

Liu, Wing-Yee; Wong, Chi-Fat; Chung, Karl Ming-Kar; Jiang, Jing-Wei; Leung, Frederick Chi-Ching

2013-01-01

The Enterobacter cloacae species includes an extremely diverse group of bacteria that are associated with plants, soil and humans. Publication of the complete genome sequence of the plant growth-promoting endophytic E. cloacae subsp. cloacae ENHKU01 provided an opportunity to perform the first comparative genome analysis between strains of this dynamic species. Examination of the pan-genome of E. cloacae showed that the conserved core genome retains the general physiological and survival genes of the species, while genomic factors in plasmids and variable regions determine the virulence of the human pathogenic E. cloacae strain; additionally, the diversity of fimbriae contributes to variation in colonization and host determination of different E. cloacae strains. Comparative genome analysis further illustrated that E. cloacae strains possess multiple mechanisms for antagonistic action against other microorganisms, which involve the production of siderophores and various antimicrobial compounds, such as bacteriocins, chitinases and antibiotic resistance proteins. The presence of Type VI secretion systems is expected to provide further fitness advantages for E. cloacae in microbial competition, thus allowing it to survive in different environments. Competition assays were performed to support our observations in genomic analysis, where E. cloacae subsp. cloacae ENHKU01 demonstrated antagonistic activities against a wide range of plant pathogenic fungal and bacterial species. PMID:24069314

Modified optimal control pilot model for computer-aided design and analysis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1992-01-01

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

An efficient current-based logic cell model for crosstalk delay analysis

NASA Astrophysics Data System (ADS)

Nazarian, Shahin; Das, Debasish

2013-04-01

Logic cell modelling is an important component in the analysis and design of CMOS integrated circuits, mostly due to nonlinear behaviour of CMOS cells with respect to the voltage signal at their input and output pins. A current-based model for CMOS logic cells is presented, which can be used for effective crosstalk noise and delta delay analysis in CMOS VLSI circuits. Existing current source models are expensive and need a new set of Spice-based characterisation, which is not compatible with typical EDA tools. In this article we present Imodel, a simple nonlinear logic cell model that can be derived from the typical cell libraries such as NLDM, with accuracy much higher than NLDM-based cell delay models. In fact, our experiments show an average error of 3% compared to Spice. This level of accuracy comes with a maximum runtime penalty of 19% compared to NLDM-based cell delay models on medium-sized industrial designs.

General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters.

PubMed

Hadfield, J D; Nakagawa, S

2010-03-01

Although many of the statistical techniques used in comparative biology were originally developed in quantitative genetics, subsequent development of comparative techniques has progressed in relative isolation. Consequently, many of the new and planned developments in comparative analysis already have well-tested solutions in quantitative genetics. In this paper, we take three recent publications that develop phylogenetic meta-analysis, either implicitly or explicitly, and show how they can be considered as quantitative genetic models. We highlight some of the difficulties with the proposed solutions, and demonstrate that standard quantitative genetic theory and software offer solutions. We also show how results from Bayesian quantitative genetics can be used to create efficient Markov chain Monte Carlo algorithms for phylogenetic mixed models, thereby extending their generality to non-Gaussian data. Of particular utility is the development of multinomial models for analysing the evolution of discrete traits, and the development of multi-trait models in which traits can follow different distributions. Meta-analyses often include a nonrandom collection of species for which the full phylogenetic tree has only been partly resolved. Using missing data theory, we show how the presented models can be used to correct for nonrandom sampling and show how taxonomies and phylogenies can be combined to give a flexible framework with which to model dependence.

Entrance and exit region friction factor models for annular seal analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Elrod, David Alan

1988-01-01

The Mach number definition and boundary conditions in Nelson's nominally-centered, annular gas seal analysis are revised. A method is described for determining the wall shear stress characteristics of an annular gas seal experimentally. Two friction factor models are developed for annular seal analysis; one model is based on flat-plate flow theory; the other uses empirical entrance and exit region friction factors. The friction factor predictions of the models are compared to experimental results. Each friction model is used in an annular gas seal analysis. The seal characteristics predicted by the two seal analyses are compared to experimental results and to the predictions of Nelson's analysis. The comparisons are for smooth-rotor seals with smooth and honeycomb stators. The comparisons show that the analysis which uses empirical entrance and exit region shear stress models predicts the static and stability characteristics of annular gas seals better than the other analyses. The analyses predict direct stiffness poorly.

Categorical Data Analysis Using a Skewed Weibull Regression Model

NASA Astrophysics Data System (ADS)

Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano

2018-03-01

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.

Choice-Based Conjoint Analysis: Classification vs. Discrete Choice Models

NASA Astrophysics Data System (ADS)

Giesen, Joachim; Mueller, Klaus; Taneva, Bilyana; Zolliker, Peter

Conjoint analysis is a family of techniques that originated in psychology and later became popular in market research. The main objective of conjoint analysis is to measure an individual's or a population's preferences on a class of options that can be described by parameters and their levels. We consider preference data obtained in choice-based conjoint analysis studies, where one observes test persons' choices on small subsets of the options. There are many ways to analyze choice-based conjoint analysis data. Here we discuss the intuition behind a classification based approach, and compare this approach to one based on statistical assumptions (discrete choice models) and to a regression approach. Our comparison on real and synthetic data indicates that the classification approach outperforms the discrete choice models.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Sentiments Analysis of Reviews Based on ARCNN Model

NASA Astrophysics Data System (ADS)

Xu, Xiaoyu; Xu, Ming; Xu, Jian; Zheng, Ning; Yang, Tao

2017-10-01

The sentiments analysis of product reviews is designed to help customers understand the status of the product. The traditional method of sentiments analysis relies on the input of a fixed feature vector which is performance bottleneck of the basic codec architecture. In this paper, we propose an attention mechanism with BRNN-CNN model, referring to as ARCNN model. In order to have a good analysis of the semantic relations between words and solves the problem of dimension disaster, we use the GloVe algorithm to train the vector representations for words. Then, ARCNN model is proposed to deal with the problem of deep features training. Specifically, BRNN model is proposed to investigate non-fixed-length vectors and keep time series information perfectly and CNN can study more connection of deep semantic links. Moreover, the attention mechanism can automatically learn from the data and optimize the allocation of weights. Finally, a softmax classifier is designed to complete the sentiment classification of reviews. Experiments show that the proposed method can improve the accuracy of sentiment classification compared with benchmark methods.

The digital storytelling process: A comparative analysis from various experts

NASA Astrophysics Data System (ADS)

Hussain, Hashiroh; Shiratuddin, Norshuhada

2016-08-01

Digital Storytelling (DST) is a method of delivering information to the audience. It combines narrative and digital media content infused with the multimedia elements. In order for the educators (i.e the designers) to create a compelling digital story, there are sets of processes introduced by experts. Nevertheless, the experts suggest varieties of processes to guide them; of which some are redundant. The main aim of this study is to propose a single guide process for the creation of DST. A comparative analysis is employed where ten DST models from various experts are analysed. The process can also be implemented in other multimedia materials that used the concept of DST.

Network Analysis in Comparative Social Sciences

ERIC Educational Resources Information Center

Vera, Eugenia Roldan; Schupp, Thomas

2006-01-01

This essay describes the pertinence of Social Network Analysis (SNA) for the social sciences in general, and discusses its methodological and conceptual implications for comparative research in particular. The authors first present a basic summary of the theoretical and methodological assumptions of SNA, followed by a succinct overview of its…

Statistical Power of Alternative Structural Models for Comparative Effectiveness Research: Advantages of Modeling Unreliability.

PubMed

Coman, Emil N; Iordache, Eugen; Dierker, Lisa; Fifield, Judith; Schensul, Jean J; Suggs, Suzanne; Barbour, Russell

2014-05-01

The advantages of modeling the unreliability of outcomes when evaluating the comparative effectiveness of health interventions is illustrated. Adding an action-research intervention component to a regular summer job program for youth was expected to help in preventing risk behaviors. A series of simple two-group alternative structural equation models are compared to test the effect of the intervention on one key attitudinal outcome in terms of model fit and statistical power with Monte Carlo simulations. Some models presuming parameters equal across the intervention and comparison groups were underpowered to detect the intervention effect, yet modeling the unreliability of the outcome measure increased their statistical power and helped in the detection of the hypothesized effect. Comparative Effectiveness Research (CER) could benefit from flexible multi-group alternative structural models organized in decision trees, and modeling unreliability of measures can be of tremendous help for both the fit of statistical models to the data and their statistical power.

Surface Modeling, Solid Modeling and Finite Element Modeling. Analysis Capabilities of Computer-Assisted Design and Manufacturing Systems.

ERIC Educational Resources Information Center

Nee, John G.; Kare, Audhut P.

1987-01-01

Explores several concepts in computer assisted design/computer assisted manufacturing (CAD/CAM). Defines, evaluates, reviews and compares advanced computer-aided geometric modeling and analysis techniques. Presents the results of a survey to establish the capabilities of minicomputer based-systems with the CAD/CAM packages evaluated. (CW)

Initial implementation of a comparative data analysis ontology.

PubMed

Prosdocimi, Francisco; Chisham, Brandon; Pontelli, Enrico; Thompson, Julie D; Stoltzfus, Arlin

2009-07-03

Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species) are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: "Operational Taxonomic Units" (OTUs), representing the entities to be compared; "character-state data" representing the observations compared among OTUs; "phylogenetic tree", representing the historical path of evolution among the entities; and "transitions", the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL), we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO). CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc.) that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

Comparative Modeling Studies of Boreal Water and Carbon Balance

NASA Technical Reports Server (NTRS)

Coughlan, J.; Peterson, David L. (Technical Monitor)

1997-01-01

The coordination of the modeling and field efforts for an Intensive Field Campaign (IFC) may resemble the chicken and egg dilemma. This session's theme advocates that early and proactive involvement by modeling teams can produce a scientific and operational benefit for the IFC and Experiment. This talk will provide some examples and suggestions originating from the NASA funded IFC's of the FIFE First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment, Oregon Transect Ecosystem Research (OTTER) and predominately Boreal Ecosystem-Atmosphere Study (BOREAS) Experiments. In February 1994 and prior to the final selection of the BOREAS study sites, a group of funded BOREAS investigators agreed to run their models with data for five community types representing the proposed tower flux sites. All participating models were given identical initial values and boundary conditions and driven with identical climate data. The objectives of the intercomparison exercise were: 1) compare simulation results of participating terrestrial, hydrological, and atmospheric models over selected time frames; 2) learn about model behavior and sensitivity to estimated boreal site and vegetation definitions; 3) prioritize BOREAS field data collection efforts supporting modeling studies; 4) identify individual model deficiencies as early as possible. Out of these objectives evolved some important coordination and science issues for the BOREAS Experiment that can be generalized to IFCs and long term archiving of the data. Some problems are acceptable because they are endemic to maintaining fair and open competition prior to the peer review process. Others are logistical and addressable through application of planning, management, and information sciences. This investigator has identified one source of measurement and model incompatibility that is manifest in the IFC scaling approach. Although intuitively obvious, scaling problems are already more formally defined in

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

Comparative genome analysis in the integrated microbial genomes (IMG) system.

PubMed

Markowitz, Victor M; Kyrpides, Nikos C

2007-01-01

Comparative genome analysis is critical for the effective exploration of a rapidly growing number of complete and draft sequences for microbial genomes. The Integrated Microbial Genomes (IMG) system (img.jgi.doe.gov) has been developed as a community resource that provides support for comparative analysis of microbial genomes in an integrated context. IMG allows users to navigate the multidimensional microbial genome data space and focus their analysis on a subset of genes, genomes, and functions of interest. IMG provides graphical viewers, summaries, and occurrence profile tools for comparing genes, pathways, and functions (terms) across specific genomes. Genes can be further examined using gene neighborhoods and compared with sequence alignment tools.

Comparative lipidomic analysis of synovial fluid in human and canine osteoarthritis.

PubMed

Kosinska, M K; Mastbergen, S C; Liebisch, G; Wilhelm, J; Dettmeyer, R B; Ishaque, B; Rickert, M; Schmitz, G; Lafeber, F P; Steinmeyer, J

2016-08-01

The lipid profile of synovial fluid (SF) is related to the health status of joints. The early stages of human osteoarthritis (OA) are poorly understood, which larger animals are expected to be able to model closely. This study examined whether the canine groove model of OA represents early OA in humans based on the changes in the lipid species profile in SF. Furthermore, the SF lipidomes of humans and dogs were compared to determine how closely canine lipid species profiles reflect the human lipidome. Lipids were extracted from cell- and cellular debris-free knee SF from nine donors with healthy joints, 17 patients with early and 13 patients with late osteoarthritic changes, and nine dogs with knee OA and healthy contralateral joints. Lipid species were quantified by electrospray ionization tandem mass spectrometry (ESI-MS/MS). Compared with control canine SF most lipid species were elevated in canine OA SF. Moreover, the lipid species profiles in the canine OA model resembled early OA profiles in humans. The SF lipidomes between dog and human were generally similar, with differences in certain lipid species in the phosphatidylcholine (PC), lysophosphatidylcholine (LPC) and sphingomyelin (SM) classes. Our lipidomic analysis demonstrates that SF in the canine OA model closely mimics the early osteoarthritic changes that occur in humans. Further, the canine SF lipidome often reflects normal human lipid metabolism. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Comparative analysis on the selection of number of clusters in community detection

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro; Kabashima, Yoshiyuki

2018-02-01

We conduct a comparative analysis on various estimates of the number of clusters in community detection. An exhaustive comparison requires testing of all possible combinations of frameworks, algorithms, and assessment criteria. In this paper we focus on the framework based on a stochastic block model, and investigate the performance of greedy algorithms, statistical inference, and spectral methods. For the assessment criteria, we consider modularity, map equation, Bethe free energy, prediction errors, and isolated eigenvalues. From the analysis, the tendency of overfit and underfit that the assessment criteria and algorithms have becomes apparent. In addition, we propose that the alluvial diagram is a suitable tool to visualize statistical inference results and can be useful to determine the number of clusters.

A comparative analysis of biclustering algorithms for gene expression data

PubMed Central

Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.

2013-01-01

The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837

A Bayesian Framework for Analysis of Pseudo-Spatial Models of Comparable Engineered Systems with Application to Spacecraft Anomaly Prediction Based on Precedent Data

NASA Astrophysics Data System (ADS)

Ndu, Obibobi Kamtochukwu

To ensure that estimates of risk and reliability inform design and resource allocation decisions in the development of complex engineering systems, early engagement in the design life cycle is necessary. An unfortunate constraint on the accuracy of such estimates at this stage of concept development is the limited amount of high fidelity design and failure information available on the actual system under development. Applying the human ability to learn from experience and augment our state of knowledge to evolve better solutions mitigates this limitation. However, the challenge lies in formalizing a methodology that takes this highly abstract, but fundamentally human cognitive, ability and extending it to the field of risk analysis while maintaining the tenets of generalization, Bayesian inference, and probabilistic risk analysis. We introduce an integrated framework for inferring the reliability, or other probabilistic measures of interest, of a new system or a conceptual variant of an existing system. Abstractly, our framework is based on learning from the performance of precedent designs and then applying the acquired knowledge, appropriately adjusted based on degree of relevance, to the inference process. This dissertation presents a method for inferring properties of the conceptual variant using a pseudo-spatial model that describes the spatial configuration of the family of systems to which the concept belongs. Through non-metric multidimensional scaling, we formulate the pseudo-spatial model based on rank-ordered subjective expert perception of design similarity between systems that elucidate the psychological space of the family. By a novel extension of Kriging methods for analysis of geospatial data to our "pseudo-space of comparable engineered systems", we develop a Bayesian inference model that allows prediction of the probabilistic measure of interest.

Comparing the Cognitive Process of Circular Causality in Two Patients with Strokes through Qualitative Analysis.

PubMed

Derakhshanrad, Seyed Alireza; Piven, Emily; Ghoochani, Bahareh Zeynalzadeh

2017-10-01

Walter J. Freeman pioneered the neurodynamic model of brain activity when he described the brain dynamics for cognitive information transfer as the process of circular causality at intention, meaning, and perception (IMP) levels. This view contributed substantially to establishment of the Intention, Meaning, and Perception Model of Neuro-occupation in occupational therapy. As described by the model, IMP levels are three components of the brain dynamics system, with nonlinear connections that enable cognitive function to be processed in a circular causality fashion, known as Cognitive Process of Circular Causality (CPCC). Although considerable research has been devoted to study the brain dynamics by sophisticated computerized imaging techniques, less attention has been paid to study it through investigating the adaptation process of thoughts and behaviors. To explore how CPCC manifested thinking and behavioral patterns, a qualitative case study was conducted on two matched female participants with strokes, who were of comparable ages, affected sides, and other characteristics, except for their resilience and motivational behaviors. CPCC was compared by matrix analysis between two participants, using content analysis with pre-determined categories. Different patterns of thinking and behavior may have happened, due to disparate regulation of CPCC between two participants.

A Comparative Analysis of a Generalized Lanchester Equation Model and a Stochastic Computer Simulation Model.

DTIC Science & Technology

1987-03-01

model is one in which words or numerical descriptions are used to represent an entity or process. An example of a symbolic model is a mathematical ...are the third type of model used in modeling combat attrition. Analytical models are symbolic models which use mathematical symbols and equations to...simplicity and the ease of tracing through the mathematical computations. In this section I will discuss some of the shortcoming which have been

Subject-specific longitudinal shape analysis by coupling spatiotemporal shape modeling with medial analysis

NASA Astrophysics Data System (ADS)

Hong, Sungmin; Fishbaugh, James; Rezanejad, Morteza; Siddiqi, Kaleem; Johnson, Hans; Paulsen, Jane; Kim, Eun Young; Gerig, Guido

2017-02-01

Modeling subject-specific shape change is one of the most important challenges in longitudinal shape analysis of disease progression. Whereas anatomical change over time can be a function of normal aging, anatomy can also be impacted by disease related degeneration. Anatomical shape change may also be affected by structural changes from neighboring shapes, which may cause non-linear variations in pose. In this paper, we propose a framework to analyze disease related shape changes by coupling extrinsic modeling of the ambient anatomical space via spatiotemporal deformations with intrinsic shape properties from medial surface analysis. We compare intrinsic shape properties of a subject-specific shape trajectory to a normative 4D shape atlas representing normal aging to isolate shape changes related to disease. The spatiotemporal shape modeling establishes inter/intra subject anatomical correspondence, which in turn enables comparisons between subjects and the 4D shape atlas, and also quantitative analysis of disease related shape change. The medial surface analysis captures intrinsic shape properties related to local patterns of deformation. The proposed framework jointly models extrinsic longitudinal shape changes in the ambient anatomical space, as well as intrinsic shape properties to give localized measurements of degeneration. Six high risk subjects and six controls are randomly sampled from a Huntington's disease image database for qualitative and quantitative comparison.

The Indecision Model of Psychophysical Performance in Dual-Presentation Tasks: Parameter Estimation and Comparative Analysis of Response Formats

PubMed Central

García-Pérez, Miguel A.; Alcalá-Quintana, Rocío

2017-01-01

Psychophysical data from dual-presentation tasks are often collected with the two-alternative forced-choice (2AFC) response format, asking observers to guess when uncertain. For an analytical description of performance, psychometric functions are then fitted to data aggregated across the two orders/positions in which stimuli were presented. Yet, order effects make aggregated data uninterpretable, and the bias with which observers guess when uncertain precludes separating sensory from decisional components of performance. A ternary response format in which observers are also allowed to report indecision should fix these problems, but a comparative analysis with the 2AFC format has never been conducted. In addition, fitting ternary data separated by presentation order poses serious challenges. To address these issues, we extended the indecision model of psychophysical performance to accommodate the ternary, 2AFC, and same–different response formats in detection and discrimination tasks. Relevant issues for parameter estimation are also discussed along with simulation results that document the superiority of the ternary format. These advantages are demonstrated by fitting the indecision model to published detection and discrimination data collected with the ternary, 2AFC, or same–different formats, which had been analyzed differently in the sources. These examples also show that 2AFC data are unsuitable for testing certain types of hypotheses. matlab and R routines written for our purposes are available as Supplementary Material, which should help spread the use of the ternary format for dependable collection and interpretation of psychophysical data. PMID:28747893

Do Breast Implants Influence Breastfeeding? A Meta-Analysis of Comparative Studies.

PubMed

Cheng, Fengrui; Dai, Shuiping; Wang, Chiyi; Zeng, Shaoxue; Chen, Junjie; Cen, Ying

2018-06-01

Aesthetic breast implant augmentation surgery is the most popular plastic surgery worldwide. Many women choose to receive breast implants during their reproductive ages, although the long-term effects are still controversial. Research aim: We conducted a meta-analysis to assess the influence of aesthetic breast augmentation on breastfeeding. We also compared the exclusive breastfeeding rates of periareolar versus inframammary incision. A systematic search for comparative studies about breast implants and breastfeeding was performed in PubMed, MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, ScienceDirect, Scopus, and Web of Science through May 2018. Meta-analysis was conducted with a random-effects model (or fixed effects, if heterogeneity was absent). Four cohorts and one cross-sectional study were included. There was a significant reduction in the exclusive breastfeeding rate for women with breast implants compared with women without implants, pooled relative risk = 0.63, 95% confidence interval [0.46, 0.86], as well as the breastfeeding rate, pooled relative risk = 0.88, 95% confidence interval [0.81, 0.95]. There was no evidence that periareolar incision was associated with a reduction in the exclusive breastfeeding rate, pooled relative risk = 0.84, 95% confidence interval [0.45, 1.58]. Participants with breast implants are less likely to establish breastfeeding, especially exclusive breastfeeding. Periareolar incision does not appear to reduce the exclusive breastfeeding rate.

Rural and Urban Crashes: A Comparative Analysis

DOT National Transportation Integrated Search

1996-08-01

National Highway Traffic Safety Administration's National Center for Statistics : and Analysis (NCSA) recently completed a study comparing the characteristics of : crashes occurring in rural areas to the characteristics of crashes occurring in : urba...

Comparative analysis of tumor spheroid generation techniques for differential in vitro drug toxicity

PubMed Central

Raghavan, Shreya; Rowley, Katelyn R.; Mehta, Geeta

2016-01-01

Multicellular tumor spheroids are powerful in vitro models to perform preclinical chemosensitivity assays. We compare different methodologies to generate tumor spheroids in terms of resultant spheroid morphology, cellular arrangement and chemosensitivity. We used two cancer cell lines (MCF7 and OVCAR8) to generate spheroids using i) hanging drop array plates; ii) liquid overlay on ultra-low attachment plates; iii) liquid overlay on ultra-low attachment plates with rotating mixing (nutator plates). Analysis of spheroid morphometry indicated that cellular compaction was increased in spheroids generated on nutator and hanging drop array plates. Collagen staining also indicated higher compaction and remodeling in tumor spheroids on nutator and hanging drop arrays compared to conventional liquid overlay. Consequently, spheroids generated on nutator or hanging drop plates had increased chemoresistance to cisplatin treatment (20-60% viability) compared to spheroids on ultra low attachment plates (10-20% viability). Lastly, we used a mathematical model to demonstrate minimal changes in oxygen and cisplatin diffusion within experimentally generated spheroids. Our results demonstrate that in vitro methods of tumor spheroid generation result in varied cellular arrangement and chemosensitivity. PMID:26918944

On the applications of nanofluids to enhance the performance of solar collectors: A comparative analysis of Atangana-Baleanu and Caputo-Fabrizio fractional models

NASA Astrophysics Data System (ADS)

Sheikh, Nadeem Ahmad; Ali, Farhad; Khan, Ilyas; Gohar, Madeha; Saqib, Muhammad

2017-12-01

In the modern era, solar energy has gained the consideration of researchers to a great deal. Apparently, the reasons are twofold: firstly, the researchers are concerned to design new devices like solar collectors, solar water heaters, etc. Secondly, the use of new approaches to improve the performance of solar energy equipment. The aim of this paper is to model the problem of the enhancement of heat transfer rate of solar energy devices, using nanoparticles and to find the exact solutions of the considered problem. The classical model is transformed to a generalized model using two different types of time-fractional derivatives, namely the Caputo-Fabrizio and Atangana-Baleanu derivatives and their comparative analysis has been presented. The solutions for the flow profile and heat transfer are presented using the Laplace transform method. The variation in the heat transfer rate has been observed for different nanoparticles and their different volume fractions. Theoretical results show that by adding aluminum oxide nanoparticles, the efficiency of solar collectors may be enhanced by 5.2%. Furthermore, the effect of volume friction of nanoparticles on velocity distribution has been discussed in graphical illustrations. The solutions are reduced to the corresponding classical model of nanofluid.

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over

rCAD: A Novel Database Schema for the Comparative Analysis of RNA.

PubMed

Ozer, Stuart; Doshi, Kishore J; Xu, Weijia; Gutell, Robin R

2011-12-31

Beyond its direct involvement in protein synthesis with mRNA, tRNA, and rRNA, RNA is now being appreciated for its significance in the overall metabolism and regulation of the cell. Comparative analysis has been very effective in the identification and characterization of RNA molecules, including the accurate prediction of their secondary structure. We are developing an integrative scalable data management and analysis system, the RNA Comparative Analysis Database (rCAD), implemented with SQL Server to support RNA comparative analysis. The platformagnostic database schema of rCAD captures the essential relationships between the different dimensions of information for RNA comparative analysis datasets. The rCAD implementation enables a variety of comparative analysis manipulations with multiple integrated data dimensions for advanced RNA comparative analysis workflows. In this paper, we describe details of the rCAD schema design and illustrate its usefulness with two usage scenarios.

rCAD: A Novel Database Schema for the Comparative Analysis of RNA

PubMed Central

Ozer, Stuart; Doshi, Kishore J.; Xu, Weijia; Gutell, Robin R.

2013-01-01

Beyond its direct involvement in protein synthesis with mRNA, tRNA, and rRNA, RNA is now being appreciated for its significance in the overall metabolism and regulation of the cell. Comparative analysis has been very effective in the identification and characterization of RNA molecules, including the accurate prediction of their secondary structure. We are developing an integrative scalable data management and analysis system, the RNA Comparative Analysis Database (rCAD), implemented with SQL Server to support RNA comparative analysis. The platformagnostic database schema of rCAD captures the essential relationships between the different dimensions of information for RNA comparative analysis datasets. The rCAD implementation enables a variety of comparative analysis manipulations with multiple integrated data dimensions for advanced RNA comparative analysis workflows. In this paper, we describe details of the rCAD schema design and illustrate its usefulness with two usage scenarios. PMID:24772454

Value Frameworks in Oncology: Comparative Analysis and Implications to the Pharmaceutical Industry.

PubMed

Slomiany, Mark; Madhavan, Priya; Kuehn, Michael; Richardson, Sasha

2017-07-01

As the cost of oncology care continues to rise, composite value models that variably capture the diverse concerns of patients, physicians, payers, policymakers, and the pharmaceutical industry have begun to take shape. To review the capabilities and limitations of 5 of the most notable value frameworks in oncology that have emerged in recent years and to compare their relative value and application among the intended stakeholders. We compared the methodology of the American Society of Clinical Oncology (ASCO) Value Framework (version 2.0), the National Comprehensive Cancer Network Evidence Blocks, Memorial Sloan Kettering Cancer Center DrugAbacus, the Institute for Clinical and Economic Review Value Assessment Framework, and the European Society for Medical Oncology Magnitude of Clinical Benefit Scale, using a side-by-side comparative approach in terms of the input, scoring methodology, and output of each framework. In addition, we gleaned stakeholder insights about these frameworks and their potential real-world applications through dialogues with physicians and payers, as well as through secondary research and an aggregate analysis of previously published survey results. The analysis identified several framework-specific themes in their respective focus on clinical trial elements, breadth of evidence, evidence weighting, scoring methodology, and value to stakeholders. Our dialogues with physicians and our aggregate analysis of previous surveys revealed a varying level of awareness of, and use of, each of the value frameworks in clinical practice. For example, although the ASCO Value Framework appears nascent in clinical practice, physicians believe that the frameworks will be more useful in practice in the future as they become more established and as their outputs are more widely accepted. Along with patients and payers, who bear the burden of treatment costs, physicians and policymakers have waded into the discussion of defining value in oncology care, as well

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Comparative analysis of early ontogeny in Bursatella leachii and Aplysia californica

PubMed Central

Vue, Zer; Capo, Thomas R.; Bardales, Ana T.

2014-01-01

Opisthobranch molluscs exhibit fascinating body plans associated with the evolution of shell loss in multiple lineages. Sea hares in particular are interesting because Aplysia californica is a well-studied model organism that offers a large suite of genetic tools. Bursatella leachii is a related tropical sea hare that lacks a shell as an adult and therefore lends itself to comparative analysis with A. californica. We have established an enhanced culturing procedure for B. leachii in husbandry that enabled the study of shell formation and loss in this lineage with respect to A. californica life staging. PMID:25538871

White matter degeneration in schizophrenia: a comparative diffusion tensor analysis

NASA Astrophysics Data System (ADS)

Ingalhalikar, Madhura A.; Andreasen, Nancy C.; Kim, Jinsuh; Alexander, Andrew L.; Magnotta, Vincent A.

2010-03-01

Schizophrenia is a serious and disabling mental disorder. Diffusion tensor imaging (DTI) studies performed on schizophrenia have demonstrated white matter degeneration either due to loss of myelination or deterioration of fiber tracts although the areas where the changes occur are variable across studies. Most of the population based studies analyze the changes in schizophrenia using scalar indices computed from the diffusion tensor such as fractional anisotropy (FA) and relative anisotropy (RA). The scalar measures may not capture the complete information from the diffusion tensor. In this paper we have applied the RADTI method on a group of 9 controls and 9 patients with schizophrenia. The RADTI method converts the tensors to log-Euclidean space where a linear regression model is applied and hypothesis testing is performed between the control and patient groups. Results show that there is a significant difference in the anisotropy between patients and controls especially in the parts of forceps minor, superior corona radiata, anterior limb of internal capsule and genu of corpus callosum. To check if the tensor analysis gives a better idea of the changes in anisotropy, we compared the results with voxelwise FA analysis as well as voxelwise geodesic anisotropy (GA) analysis.

Comparative study of Sperm Motility Analysis System and conventional microscopic semen analysis

PubMed Central

KOMORI, KAZUHIKO; ISHIJIMA, SUMIO; TANJAPATKUL, PHANU; FUJITA, KAZUTOSHI; MATSUOKA, YASUHIRO; TAKAO, TETSUYA; MIYAGAWA, YASUSHI; TAKADA, SHINGO; OKUYAMA, AKIHIKO

2006-01-01

Background and Aim:  Conventional manual sperm analysis still shows variations in structure, process and outcome although World Health Organization (WHO) guidelines present an appropriate method for sperm analysis. In the present study a new system for sperm analysis, Sperm Motility Analysis System (SMAS), was compared with manual semen analysis based on WHO guidelines. Materials and methods:  Samples from 30 infertility patients and 21 healthy volunteers were subjected to manual microscopic analysis and SMAS analysis, simultaneously. We compared these two methods with respect to sperm concentration and percent motility. Results:  Sperm concentrations obtained by SMAS (Csmas) and manual microscopic analyses on WHO guidelines (Cwho) were strongly correlated (Cwho = 1.325 × Csmas; r = 0.95, P < 0.001). If we excluded subjects with Csmas values >30 × 106 sperm/mL, the results were more similar (Cwho = 1.022 × Csmas; r = 0.81, P < 0.001). Percent motility obtained by SMAS (Msmas) and manual analysis on WHO guidelines (Mwho) were strongly correlated (Mwho = 1.214 × Msmas; r = 0.89, P < 0.001). Conclusions:  The data indicate that the results of SMAS and those of manual microscopic sperm analyses based on WHO guidelines are strongly correlated. SMAS is therefore a promising system for sperm analysis. (Reprod Med Biol 2006; 5: 195–200) PMID:29662398

Comparing Internet Probing Methodologies Through an Analysis of Large Dynamic Graphs

DTIC Science & Technology

2014-06-01

comparable Internet topologies in less time. We compare these by modeling union of traceroute outputs as graphs, and using standard graph theoretical...topologies in less time. We compare these by modeling union of traceroute outputs as graphs, and using standard graph theoretical measurements as well...We compare these by modeling union of traceroute outputs as graphs, and study the graphs by using vertex and edge count, average vertex degree

Modeller's attitude in catchment modelling: a comparative study

NASA Astrophysics Data System (ADS)

Battista Chirico, Giovanni

2010-05-01

Ten modellers have been invited to predict, independently from each other, the discharge of the artificial Chicken Creek catchment in North-East Germany for simulation period of three years, providing them only soil texture, terrain and meteorological data. No data concerning the discharge or other sources of state variables and fluxes within the catchment have been provided. Modellers had however the opportunity to visit the experimental catchment and inspect areal photos of the catchments since its initial development stage. This study has been a unique comparative study focussing on how different modellers deal with the key issues in predicting the discharge in ungauged catchments: 1) choice of the model structure; 2) identification of model parameters; 3) identification of model initial and boundary conditions. The first general lesson learned during this study was that the modeller is just part of the entire modelling process and has a major bearing on the model results, particularly in ungauged catchments where there are more degrees of freedom in making modelling decisions. Modellers' attitudes during the stages of the model implementation and parameterisation have been deeply influenced by their own experience from previous modelling studies. A common outcome was that modellers have been mainly oriented to apply process-based models able to exploit the available data concerning the physical properties of the catchment and therefore could be more suitable to cope with the lack of data concerning state variables or fluxes. The second general lesson learned during this study was the role of dominant processes. We believed that the modelling task would have been much easier in an artificial catchment, where heterogeneity were expected to be negligible and processes simpler, than in catchments that have evolved over a longer time period. The results of the models were expected to converge, and this would have been a good starting point to proceed for a model

Comparison of composite rotor blade models: A coupled-beam analysis and an MSC/NASTRAN finite-element model

NASA Technical Reports Server (NTRS)

Hodges, Robert V.; Nixon, Mark W.; Rehfield, Lawrence W.

1987-01-01

A methodology was developed for the structural analysis of composite rotor blades. This coupled-beam analysis is relatively simple to use compared with alternative analysis techniques. The beam analysis was developed for thin-wall single-cell rotor structures and includes the effects of elastic coupling. This paper demonstrates the effectiveness of the new composite-beam analysis method through comparison of its results with those of an established baseline analysis technique. The baseline analysis is an MSC/NASTRAN finite-element model built up from anisotropic shell elements. Deformations are compared for three linear static load cases of centrifugal force at design rotor speed, applied torque, and lift for an ideal rotor in hover. A D-spar designed to twist under axial loading is the subject of the analysis. Results indicate the coupled-beam analysis is well within engineering accuracy.

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics.

PubMed

Christakos, G; Olea, R A; Yu, H-L

2007-09-01

This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the Indian epidemic, the disease

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

USGS Publications Warehouse

Christakos, G.; Olea, R.A.; Yu, H.-L.

2007-01-01

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

PubMed

Agrawal, Sonia; Arze, Cesar; Adkins, Ricky S; Crabtree, Jonathan; Riley, David; Vangala, Mahesh; Galens, Kevin; Fraser, Claire M; Tettelin, Hervé; White, Owen; Angiuoli, Samuel V; Mahurkar, Anup; Fricke, W Florian

2017-04-27

The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

Robust Linear Models for Cis-eQTL Analysis.

PubMed

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

PubMed

Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

2014-06-01

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

Comparative analysis of the modified enclosed energy metric for self-focusing holograms from digital lensless holographic microscopy.

PubMed

Trujillo, Carlos; Garcia-Sucerquia, Jorge

2015-06-01

A comparative analysis of the performance of the modified enclosed energy (MEE) method for self-focusing holograms recorded with digital lensless holographic microscopy is presented. Notwithstanding the MEE analysis previously published, no extended analysis of its performance has been reported. We have tested the MEE in terms of the minimum axial distance allowed between the set of reconstructed holograms to search for the focal plane and the elapsed time to obtain the focused image. These parameters have been compared with those for some of the already reported methods in the literature. The MEE achieves better results in terms of self-focusing quality but at a higher computational cost. Despite its longer processing time, the method remains within a time frame to be technologically attractive. Modeled and experimental holograms have been utilized in this work to perform the comparative study.

Comparing estimates of genetic variance across different relationship models.

PubMed

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Parmodel: a web server for automated comparative modeling of proteins.

PubMed

Uchôa, Hugo Brandão; Jorge, Guilherme Eberhart; Freitas Da Silveira, Nelson José; Camera, João Carlos; Canduri, Fernanda; De Azevedo, Walter Filgueira

2004-12-24

Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models for a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at .

Comparative study of turbulence models in predicting hypersonic inlet flows

NASA Technical Reports Server (NTRS)

Kapoor, Kamlesh; Anderson, Bernhard H.; Shaw, Robert J.

1992-01-01

A numerical study was conducted to analyze the performance of different turbulence models when applied to the hypersonic NASA P8 inlet. Computational results from the PARC2D code, which solves the full two-dimensional Reynolds-averaged Navier-Stokes equation, were compared with experimental data. The zero-equation models considered for the study were the Baldwin-Lomax model, the Thomas model, and a combination of the Baldwin-Lomax and Thomas models; the two-equation models considered were the Chien model, the Speziale model (both low Reynolds number), and the Launder and Spalding model (high Reynolds number). The Thomas model performed best among the zero-equation models, and predicted good pressure distributions. The Chien and Speziale models compared wery well with the experimental data, and performed better than the Thomas model near the walls.

Comparative study of turbulence models in predicting hypersonic inlet flows

NASA Technical Reports Server (NTRS)

Kapoor, Kamlesh; Anderson, Bernhard H.; Shaw, Robert J.

1992-01-01

A numerical study was conducted to analyze the performance of different turbulence models when applied to the hypersonic NASA P8 inlet. Computational results from the PARC2D code, which solves the full two-dimensional Reynolds-averaged Navier-Stokes equation, were compared with experimental data. The zero-equation models considered for the study were the Baldwin-Lomax model, the Thomas model, and a combination of the Baldwin-Lomax and Thomas models; the two-equation models considered were the Chien model, the Speziale model (both low Reynolds number), and the Launder and Spalding model (high Reynolds number). The Thomas model performed best among the zero-equation models, and predicted good pressure distributions. The Chien and Speziale models compared very well with the experimental data, and performed better than the Thomas model near the walls.

In vitro comparative optical bench analysis of a spherical and aspheric optic design of the same IOL model.

PubMed

Tandogan, Tamer; Auffarth, Gerd U; Choi, Chul Y; Liebing, Stephanie; Mayer, Christian; Khoramnia, Ramin

2017-02-08

To analyse objective optical properties of the spherical and aspheric design of the same intraocular lens (IOL) model using optical bench analysis. This study entailed a comparative analysis of 10 spherical C-flex 570 C and 10 aspheric C-flex 970 C IOLs (Rayner Intraocular Lenses Ltd., Hove, UK) of 26 diopters [D] using an optical bench (OptiSpheric, Trioptics, Germany). In all lenses, we evaluated the modulation transfer function (MTF) at 50 lp/mm and 100 lp/mm and the Strehl Ratio using a 3-mm (photopic) and 4.5-mm (mesopic) aperture. At 50 lp/mm, the MTF values were 0.713/0.805 (C-flex 570 C/C-flex 970 C) for a 3-mm aperture and 0.294/0.591 for a 4.5-mm aperture. At 100 lp/mm, the MTF values were 0.524/0.634 for a 3-mm aperture and 0.198/0.344 for a 4.5-mm aperture. The Strehl Ratio was 0.806/0.925 and 0.237/0.479 for a 3-mm and 4.5-mm aperture respectively. A Mann-Whitney U test revealed all intergroup differences to be statistically significant (p < 0.01). The aspheric IOL design achieved higher MTF values than the spherical design of the same IOL for both apertures. Moreover, the differences between the two designs of the IOL were more prominent for larger apertures. This suggests that the evaluated IOL provides enhanced optical quality to patients with larger pupils or working under mesopic conditions.

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Comparative proteomics analysis of oral cancer cell lines: identification of cancer associated proteins

PubMed Central

2014-01-01

Background A limiting factor in performing proteomics analysis on cancerous cells is the difficulty in obtaining sufficient amounts of starting material. Cell lines can be used as a simplified model system for studying changes that accompany tumorigenesis. This study used two-dimensional gel electrophoresis (2DE) to compare the whole cell proteome of oral cancer cell lines vs normal cells in an attempt to identify cancer associated proteins. Results Three primary cell cultures of normal cells with a limited lifespan without hTERT immortalization have been successfully established. 2DE was used to compare the whole cell proteome of these cells with that of three oral cancer cell lines. Twenty four protein spots were found to have changed in abundance. MALDI TOF/TOF was then used to determine the identity of these proteins. Identified proteins were classified into seven functional categories – structural proteins, enzymes, regulatory proteins, chaperones and others. IPA core analysis predicted that 18 proteins were related to cancer with involvements in hyperplasia, metastasis, invasion, growth and tumorigenesis. The mRNA expressions of two proteins – 14-3-3 protein sigma and Stress-induced-phosphoprotein 1 – were found to correlate with the corresponding proteins’ abundance. Conclusions The outcome of this analysis demonstrated that a comparative study of whole cell proteome of cancer versus normal cell lines can be used to identify cancer associated proteins. PMID:24422745

Model parameter uncertainty analysis for an annual field-scale P loss model

NASA Astrophysics Data System (ADS)

Bolster, Carl H.; Vadas, Peter A.; Boykin, Debbie

2016-08-01

Phosphorous (P) fate and transport models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. Because all models are simplifications of complex systems, there will exist an inherent amount of uncertainty associated with their predictions. It is therefore important that efforts be directed at identifying, quantifying, and communicating the different sources of model uncertainties. In this study, we conducted an uncertainty analysis with the Annual P Loss Estimator (APLE) model. Our analysis included calculating parameter uncertainties and confidence and prediction intervals for five internal regression equations in APLE. We also estimated uncertainties of the model input variables based on values reported in the literature. We then predicted P loss for a suite of fields under different management and climatic conditions while accounting for uncertainties in the model parameters and inputs and compared the relative contributions of these two sources of uncertainty to the overall uncertainty associated with predictions of P loss. Both the overall magnitude of the prediction uncertainties and the relative contributions of the two sources of uncertainty varied depending on management practices and field characteristics. This was due to differences in the number of model input variables and the uncertainties in the regression equations associated with each P loss pathway. Inspection of the uncertainties in the five regression equations brought attention to a previously unrecognized limitation with the equation used to partition surface-applied fertilizer P between leaching and runoff losses. As a result, an alternate equation was identified that provided similar predictions with much less uncertainty. Our results demonstrate how a thorough uncertainty and model residual analysis can be used to identify limitations with a model. Such insight can then be used to guide future data collection and model

Mental health network governance: comparative analysis across Canadian regions

PubMed Central

Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

2010-01-01

Objective Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Methods Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Results Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. Discussion In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration. PMID:21289999

Mental health network governance: comparative analysis across Canadian regions.

PubMed

Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

2010-10-26

Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration.

Structural modeling and docking studies of ribose 5-phosphate isomerase from Leishmania major and Homo sapiens: a comparative analysis for Leishmaniasis treatment.

PubMed

Capriles, Priscila V S Z; Baptista, Luiz Phillippe R; Guedes, Isabella A; Guimarães, Ana Carolina R; Custódio, Fabio L; Alves-Ferreira, Marcelo; Dardenne, Laurent E

2015-02-01

Leishmaniases are caused by protozoa of the genus Leishmania and are considered the second-highest cause of death worldwide by parasitic infection. The drugs available for treatment in humans are becoming ineffective mainly due to parasite resistance; therefore, it is extremely important to develop a new chemotherapy against these parasites. A crucial aspect of drug design development is the identification and characterization of novel molecular targets. In this work, through an in silico comparative analysis between the genomes of Leishmania major and Homo sapiens, the enzyme ribose 5-phosphate isomerase (R5PI) was indicated as a promising molecular target. R5PI is an important enzyme that acts in the pentose phosphate pathway and catalyzes the interconversion of d-ribose-5-phosphate (R5P) and d-ribulose-5-phosphate (5RP). R5PI activity is found in two analogous groups of enzymes called RpiA (found in H. sapiens) and RpiB (found in L. major). Here, we present the first report of the three-dimensional (3D) structures and active sites of RpiB from L. major (LmRpiB) and RpiA from H. sapiens (HsRpiA). Three-dimensional models were constructed by applying a hybrid methodology that combines comparative and ab initio modeling techniques, and the active site was characterized based on docking studies of the substrates R5P (furanose and ring-opened forms) and 5RP. Our comparative analyses show that these proteins are structural analogs and that distinct residues participate in the interconversion of R5P and 5RP. We propose two distinct reaction mechanisms for the reversible isomerization of R5P to 5RP, which is catalyzed by LmRpiB and HsRpiA. We expect that the present results will be important in guiding future molecular modeling studies to develop new drugs that are specially designed to inhibit the parasitic form of the enzyme without significant effects on the human analog. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparison of the occlusal contact area of virtual models and actual models: a comparative in vitro study on Class I and Class II malocclusion models.

PubMed

Lee, Hyemin; Cha, Jooly; Chun, Youn-Sic; Kim, Minji

2018-06-19

The occlusal registration of virtual models taken by intraoral scanners sometimes shows patterns which seem much different from the patients' occlusion. Therefore, this study aims to evaluate the accuracy of virtual occlusion by comparing virtual occlusal contact area with actual occlusal contact area using a plaster model in vitro. Plaster dental models, 24 sets of Class I models and 20 sets of Class II models, were divided into a Molar, Premolar, and Anterior group. The occlusal contact areas calculated by the Prescale method and the virtual occlusion by scanning method were compared, and the ratio of the molar and incisor area were compared in order to find any particular tendencies. There was no significant difference between the Prescale results and the scanner results in both the molar and premolar groups (p = 0.083 and 0.053, respectively). On the other hand, there was a significant difference between the Prescale and the scanner results in the anterior group with the scanner results presenting overestimation of the occlusal contact points (p < 0.05). In Molars group, the regression analysis shows that the two variables express linear correlation and has a linear equation with a slope of 0.917. R 2 is 0.930. Groups of Premolars and Anteriors had a week linear relationship and greater dispersion. Difference between the actual and virtual occlusion revealed in the anterior portion, where overestimation was observed in the virtual model obtained from the scanning method. Nevertheless, molar and premolar areas showed relatively accurate occlusal contact area in the virtual model.

Comparative Study of Lectin Domains in Model Species: New Insights into Evolutionary Dynamics

PubMed Central

Van Holle, Sofie; De Schutter, Kristof; Eggermont, Lore; Tsaneva, Mariya; Dang, Liuyi; Van Damme, Els J. M.

2017-01-01

Lectins are present throughout the plant kingdom and are reported to be involved in diverse biological processes. In this study, we provide a comparative analysis of the lectin families from model species in a phylogenetic framework. The analysis focuses on the different plant lectin domains identified in five representative core angiosperm genomes (Arabidopsis thaliana, Glycine max, Cucumis sativus, Oryza sativa ssp. japonica and Oryza sativa ssp. indica). The genomes were screened for genes encoding lectin domains using a combination of Basic Local Alignment Search Tool (BLAST), hidden Markov models, and InterProScan analysis. Additionally, phylogenetic relationships were investigated by constructing maximum likelihood phylogenetic trees. The results demonstrate that the majority of the lectin families are present in each of the species under study. Domain organization analysis showed that most identified proteins are multi-domain proteins, owing to the modular rearrangement of protein domains during evolution. Most of these multi-domain proteins are widespread, while others display a lineage-specific distribution. Furthermore, the phylogenetic analyses reveal that some lectin families evolved to be similar to the phylogeny of the plant species, while others share a closer evolutionary history based on the corresponding protein domain architecture. Our results yield insights into the evolutionary relationships and functional divergence of plant lectins. PMID:28587095

Modeling energy/economy interactions for conservation and renewable energy-policy analysis

NASA Astrophysics Data System (ADS)

Groncki, P. J.

Energy policy and the implications for policy analysis and the methodological tools are discussed. The evolution of one methodological approach and the combined modeling system of the component models, their evolution in response to changing analytic needs, and the development of the integrated framework are reported. The analyses performed over the past several years are summarized. The current philosophy behind energy policy is discussed and compared to recent history. Implications for current policy analysis and methodological approaches are drawn.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

PubMed

Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

Modeling time-to-event (survival) data using classification tree analysis.

PubMed

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

Data warehouse model design technology analysis and research

NASA Astrophysics Data System (ADS)

Jiang, Wenhua; Li, Qingshui

2012-01-01

Existing data storage format can not meet the needs of information analysis, data warehouse onto the historical stage, the data warehouse is to support business decision making and the creation of specially designed data collection. With the data warehouse, the companies will all collected information is stored in the data warehouse. The data warehouse is organized according to some, making information easy to access and has value. This paper focuses on the establishment of data warehouse and analysis, design, data warehouse, two barrier models, and compares them.

The multiple complex exponential model and its application to EEG analysis

NASA Astrophysics Data System (ADS)

Chen, Dao-Mu; Petzold, J.

The paper presents a novel approach to the analysis of the EEG signal, which is based on a multiple complex exponential (MCE) model. Parameters of the model are estimated using a nonharmonic Fourier expansion algorithm. The central idea of the algorithm is outlined, and the results, estimated on the basis of simulated data, are presented and compared with those obtained by the conventional methods of signal analysis. Preliminary work on various application possibilities of the MCE model in EEG data analysis is described. It is shown that the parameters of the MCE model reflect the essential information contained in an EEG segment. These parameters characterize the EEG signal in a more objective way because they are closer to the recent supposition of the nonlinear character of the brain's dynamic behavior.

Comparative transcriptome analysis between planarian Dugesia japonica and other platyhelminth species.

PubMed

Nishimura, Osamu; Hirao, Yukako; Tarui, Hiroshi; Agata, Kiyokazu

2012-06-29

Planarians are considered to be among the extant animals close to one of the earliest groups of organisms that acquired a central nervous system (CNS) during evolution. Planarians have a bilobed brain with nine lateral branches from which a variety of external signals are projected into different portions of the main lobes. Various interneurons process different signals to regulate behavior and learning/memory. Furthermore, planarians have robust regenerative ability and are attracting attention as a new model organism for the study of regeneration. Here we conducted large-scale EST analysis of the head region of the planarian Dugesia japonica to construct a database of the head-region transcriptome, and then performed comparative analyses among related species. A total of 54,752 high-quality EST reads were obtained from a head library of the planarian Dugesia japonica, and 13,167 unigene sequences were produced by de novo assembly. A new method devised here revealed that proteins related to metabolism and defense mechanisms have high flexibility of amino-acid substitutions within the planarian family. Eight-two CNS-development genes were found in the planarian (cf. C. elegans 3; chicken 129). Comparative analysis revealed that 91% of the planarian CNS-development genes could be mapped onto the schistosome genome, but one-third of these shared genes were not expressed in the schistosome. We constructed a database that is a useful resource for comparative planarian transcriptome studies. Analysis comparing homologous genes between two planarian species showed that the potential of genes is important for accumulation of amino-acid substitutions. The presence of many CNS-development genes in our database supports the notion that the planarian has a fundamental brain with regard to evolution and development at not only the morphological/functional, but also the genomic, level. In addition, our results indicate that the planarian CNS-development genes already existed

Comparing models for growth and management of forest tracts

Treesearch

J.J. Colbert; Michael Schuckers; Desta Fekedulegn

2003-01-01

The Stand Damage Model (SDM) is a PC-based model that is easily installed, calibrated and initialized for use in exploring the future growth and management of forest stands or small wood lots. We compare the basic individual tree growth model incorporated in this model with alternative models that predict the basal area growth of trees. The SDM is a gap-type simulator...

Comparability of river suspended-sediment sampling and laboratory analysis methods

USGS Publications Warehouse

Groten, Joel T.; Johnson, Gregory D.

2018-03-06

Accurate measurements of suspended sediment, a leading water-quality impairment in many Minnesota rivers, are important for managing and protecting water resources; however, water-quality standards for suspended sediment in Minnesota are based on grab field sampling and total suspended solids (TSS) laboratory analysis methods that have underrepresented concentrations of suspended sediment in rivers compared to U.S. Geological Survey equal-width-increment or equal-discharge-increment (EWDI) field sampling and suspended sediment concentration (SSC) laboratory analysis methods. Because of this underrepresentation, the U.S. Geological Survey, in collaboration with the Minnesota Pollution Control Agency, collected concurrent grab and EWDI samples at eight sites to compare results obtained using different combinations of field sampling and laboratory analysis methods.Study results determined that grab field sampling and TSS laboratory analysis results were biased substantially low compared to EWDI sampling and SSC laboratory analysis results, respectively. Differences in both field sampling and laboratory analysis methods caused grab and TSS methods to be biased substantially low. The difference in laboratory analysis methods was slightly greater than field sampling methods.Sand-sized particles had a strong effect on the comparability of the field sampling and laboratory analysis methods. These results indicated that grab field sampling and TSS laboratory analysis methods fail to capture most of the sand being transported by the stream. The results indicate there is less of a difference among samples collected with grab field sampling and analyzed for TSS and concentration of fines in SSC. Even though differences are present, the presence of strong correlations between SSC and TSS concentrations provides the opportunity to develop site specific relations to address transport processes not captured by grab field sampling and TSS laboratory analysis methods.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

NASA Astrophysics Data System (ADS)

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia.

PubMed

Tan, Shi Yang; Dutta, Avirup; Jakubovics, Nicholas S; Ang, Mia Yang; Siow, Cheuk Chuen; Mutha, Naresh Vr; Heydari, Hamed; Wee, Wei Yee; Wong, Guat Jah; Choo, Siew Woh

2015-01-16

Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity. To facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the

Anatomical knowledge gain through a clay-modeling exercise compared to live and video observations.

PubMed

Kooloos, Jan G M; Schepens-Franke, Annelieke N; Bergman, Esther M; Donders, Rogier A R T; Vorstenbosch, Marc A T M

2014-01-01

Clay modeling is increasingly used as a teaching method other than dissection. The haptic experience during clay modeling is supposed to correspond to the learning effect of manipulations during exercises in the dissection room involving tissues and organs. We questioned this assumption in two pretest-post-test experiments. In these experiments, the learning effects of clay modeling were compared to either live observations (Experiment I) or video observations (Experiment II) of the clay-modeling exercise. The effects of learning were measured with multiple choice questions, extended matching questions, and recognition of structures on illustrations of cross-sections. Analysis of covariance with pretest scores as the covariate was used to elaborate the results. Experiment I showed a significantly higher post-test score for the observers, whereas Experiment II showed a significantly higher post-test score for the clay modelers. This study shows that (1) students who perform clay-modeling exercises show less gain in anatomical knowledge than students who attentively observe the same exercise being carried out and (2) performing a clay-modeling exercise is better in anatomical knowledge gain compared to the study of a video of the recorded exercise. The most important learning effect seems to be the engagement in the exercise, focusing attention and stimulating time on task. © 2014 American Association of Anatomists.

ModelMate - A graphical user interface for model analysis

USGS Publications Warehouse

Banta, Edward R.

2011-01-01

ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

Population Pharmacokinetic and Pharmacodynamic Model-Based Comparability Assessment of a Recombinant Human Epoetin Alfa and the Biosimilar HX575

PubMed Central

Yan, Xiaoyu; Lowe, Philip J.; Fink, Martin; Berghout, Alexander; Balser, Sigrid; Krzyzanski, Wojciech

2012-01-01

The aim of this study was to develop an integrated pharmacokinetic and pharmacodynamic (PK/PD) model and assess the comparability between epoetin alfa HEXAL/Binocrit (HX575) and a comparator epoetin alfa by a model-based approach. PK/PD data—including serum drug concentrations, reticulocyte counts, red blood cells, and hemoglobin levels—were obtained from 2 clinical studies. In sum, 149 healthy men received multiple intravenous or subcutaneous doses of HX575 (100 IU/kg) and the comparator 3 times a week for 4 weeks. A population model based on pharmacodynamics-mediated drug disposition and cell maturation processes was used to characterize the PK/PD data for the 2 drugs. Simulations showed that due to target amount changes, total clearance may increase up to 2.4-fold as compared with the baseline. Further simulations suggested that once-weekly and thrice-weekly subcutaneous dosing regimens would result in similar efficacy. The findings from the model-based analysis were consistent with previous results using the standard noncompartmental approach demonstrating PK/PD comparability between HX575 and comparator. However, due to complexity of the PK/PD model, control of random effects was not straightforward. Whereas population PK/PD model-based analyses are suited for studying complex biological systems, such models have their limitations (statistical), and their comparability results should be interpreted carefully. PMID:22162538

Canis familiaris As a Model for Non-Invasive Comparative Neuroscience.

PubMed

Bunford, Nóra; Andics, Attila; Kis, Anna; Miklósi, Ádám; Gácsi, Márta

2017-07-01

There is an ongoing need to improve animal models for investigating human behavior and its biological underpinnings. The domestic dog (Canis familiaris) is a promising model in cognitive neuroscience. However, before it can contribute to advances in this field in a comparative, reliable, and valid manner, several methodological issues warrant attention. We review recent non-invasive canine neuroscience studies, primarily focusing on (i) variability among dogs and between dogs and humans in cranial characteristics, and (ii) generalizability across dog and dog-human studies. We argue not for methodological uniformity but for functional comparability between methods, experimental designs, and neural responses. We conclude that the dog may become an innovative and unique model in comparative neuroscience, complementing more traditional models. Copyright © 2017 Elsevier Ltd. All rights reserved.

MODBASE, a database of annotated comparative protein structure models

PubMed Central

Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C.; Ilyin, Valentin A.; Sali, Andrej

2002-01-01

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10–4) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server. PMID:11752309

A Lumped Computational Model for Sodium Sulfur Battery Analysis

NASA Astrophysics Data System (ADS)

Wu, Fan

Due to the cost of materials and time consuming testing procedures, development of new batteries is a slow and expensive practice. The purpose of this study is to develop a computational model and assess the capabilities of such a model designed to aid in the design process and control of sodium sulfur batteries. To this end, a transient lumped computational model derived from an integral analysis of the transport of species, energy and charge throughout the battery has been developed. The computation processes are coupled with the use of Faraday's law, and solutions for the species concentrations, electrical potential and current are produced in a time marching fashion. Properties required for solving the governing equations are calculated and updated as a function of time based on the composition of each control volume. The proposed model is validated against multi- dimensional simulations and experimental results from literatures, and simulation results using the proposed model is presented and analyzed. The computational model and electrochemical model used to solve the equations for the lumped model are compared with similar ones found in the literature. The results obtained from the current model compare favorably with those from experiments and other models.

Video analysis of the flight of a model aircraft

NASA Astrophysics Data System (ADS)

Tarantino, Giovanni; Fazio, Claudio

2011-11-01

A video-analysis software tool has been employed in order to measure the steady-state values of the kinematics variables describing the longitudinal behaviour of a radio-controlled model aircraft during take-off, climbing and gliding. These experimental results have been compared with the theoretical steady-state configurations predicted by the phugoid model for longitudinal flight. A comparison with the parameters and performance of the full-size aircraft has also been outlined.

Evaluation of an experimental rat model for comparative studies of bleaching agents.

PubMed

Cintra, Luciano Tavares Angelo; Benetti, Francine; Ferreira, Luciana Louzada; Rahal, Vanessa; Ervolino, Edilson; Jacinto, Rogério de Castilho; Gomes Filho, João Eduardo; Briso, André Luiz Fraga

2016-04-01

Dental materials in general are tested in different animal models prior to the clinical use in humans, except for bleaching agents. Objectives To evaluate an experimental rat model for comparative studies of bleaching agents, by investigating the influence of different concentrations and application times of H2O2 gel in the pulp tissue during in-office bleaching of rats' vital teeth. Material and Methods The right and left maxillary molars of 50 Wistar rats were bleached with 20% and 35% H2O2 gels, respectively, for 5, 10, 15, 30, or 45 min (n=10 rats/group). Ten animals were untreated (control). The rats were killed after 2 or 30 days, and the maxillae were examined by light microscopy. Inflammation was evaluated through histomorphometric analysis with inflammatory cell count in the coronal and radicular thirds of the pulp. Fibroblasts were also counted. Scores were attributed to odontoblastic layer and vascular changes. Tertiary dentin area and pulp chamber central area were measured histomorphometrically. Data were compared by analysis of variance and Kruskal-Wallis test (p<0.05). Results After 2 days, the amount of inflammatory cells increased in the coronal pulp occlusal third up to the 15-min application groups of each bleaching gel. In the groups exposed to each concentration for 30 and 45 min, the number of inflammatory cells decreased along with the appearance of necrotic areas. After 30 days, reduction on the pulp chamber central area and enlargement of the tertiary dentin area were observed, without the detection of inflammation areas. Conclusion The rat model of extracoronal bleaching showed to be adequate for studies of bleaching protocols, as it was possible to observe alterations in the pulp tissues and tooth structure caused by different concentrations and application periods of bleaching agents.

Evaluation of an experimental rat model for comparative studies of bleaching agents

PubMed Central

Cintra, Luciano Tavares Angelo; Benetti, Francine; Ferreira, Luciana Lousada; Rahal, Vanessa; Ervolino, Edilson; Jacinto, Rogério de Castilho; Gomes, João Eduardo; Briso, André Luiz Fraga

2016-01-01

ABSTRACT Dental materials, in general, are tested in different animal models prior to their clinical use in humans, except for bleaching agents. Objectives To evaluate an experimental rat model for comparative studies of bleaching agents by investigating the influence of different concentrations and application times of H2O2 gel in the pulp tissue during in-office bleaching of rats’ vital teeth. Material and methods The right and left maxillary molars of 50 Wistar rats were bleached with 20% and 35% H2O2 gels, respectively, for 5, 10, 15, 30, or 45 min (n=10 rats/group). Ten animals (control) were untreated. The rats were killed after 2 or 30 days, and the maxillae were examined by light microscopy. Inflammation was evaluated by histomorphometric analysis with inflammatory cell counting in the coronal and radicular thirds of the pulp. The counting of fibroblasts was also performed. Scores were attributed to the odontoblastic layer and to vascular changes. The tertiary dentin area and the pulp chamber central area were histomorphometrically measured. Data were compared by the analysis of variance and the Kruskal-Wallis test (p<0.05). Results After 2 days, the amount of inflammatory cells increased in the occlusal third of the coronal pulp until the time of 15 min for both concentrations of bleaching gels. In 30 and 45 min groups of each concentration, the number of inflammatory cells decreased along with the appearance of necrotic areas. After 30 days, a reduction in the pulp chamber central area and an enlargement of tertiary dentin area were observed without the detection of inflammation areas. Conclusion The rat model of extra coronal bleaching showed to be adequate for bleaching protocols studies, as it was possible to observe alterations in the pulp tissues and in the tooth structure caused by different concentrations and periods of application of bleaching agents. PMID:27008262

Evaluation of an experimental rat model for comparative studies of bleaching agents

PubMed Central

CINTRA, Luciano Tavares Angelo; BENETTI, Francine; FERREIRA, Luciana Louzada; RAHAL, Vanessa; ERVOLINO, Edilson; JACINTO, Rogério de Castilho; GOMES, João Eduardo; BRISO, André Luiz Fraga

2016-01-01

ABSTRACT Dental materials in general are tested in different animal models prior to the clinical use in humans, except for bleaching agents. Objectives To evaluate an experimental rat model for comparative studies of bleaching agents, by investigating the influence of different concentrations and application times of H2O2 gel in the pulp tissue during in-office bleaching of rats’ vital teeth. Material and Methods The right and left maxillary molars of 50 Wistar rats were bleached with 20% and 35% H2O2 gels, respectively, for 5, 10, 15, 30, or 45 min (n=10 rats/group). Ten animals were untreated (control). The rats were killed after 2 or 30 days, and the maxillae were examined by light microscopy. Inflammation was evaluated through histomorphometric analysis with inflammatory cell count in the coronal and radicular thirds of the pulp. Fibroblasts were also counted. Scores were attributed to odontoblastic layer and vascular changes. Tertiary dentin area and pulp chamber central area were measured histomorphometrically. Data were compared by analysis of variance and Kruskal-Wallis test (p<0.05). Results After 2 days, the amount of inflammatory cells increased in the coronal pulp occlusal third up to the 15-min application groups of each bleaching gel. In the groups exposed to each concentration for 30 and 45 min, the number of inflammatory cells decreased along with the appearance of necrotic areas. After 30 days, reduction on the pulp chamber central area and enlargement of the tertiary dentin area were observed, without the detection of inflammation areas. Conclusion The rat model of extracoronal bleaching showed to be adequate for studies of bleaching protocols, as it was possible to observe alterations in the pulp tissues and tooth structure caused by different concentrations and application periods of bleaching agents. PMID:27119766

Evaluation of an experimental rat model for comparative studies of bleaching agents.

PubMed

Cintra, Luciano Tavares Angelo; Benetti, Francine; Ferreira, Luciana Lousada; Rahal, Vanessa; Ervolino, Edilson; Jacinto, Rogério de Castilho; Gomes Filho, João Eduardo; Briso, André Luiz Fraga

2016-01-01

Dental materials, in general, are tested in different animal models prior to their clinical use in humans, except for bleaching agents. To evaluate an experimental rat model for comparative studies of bleaching agents by investigating the influence of different concentrations and application times of H2O2 gel in the pulp tissue during in-office bleaching of rats' vital teeth. The right and left maxillary molars of 50 Wistar rats were bleached with 20% and 35% H2O2 gels, respectively, for 5, 10, 15, 30, or 45 min (n=10 rats/group). Ten animals (control) were untreated. The rats were killed after 2 or 30 days, and the maxillae were examined by light microscopy. Inflammation was evaluated by histomorphometric analysis with inflammatory cell counting in the coronal and radicular thirds of the pulp. The counting of fibroblasts was also performed. Scores were attributed to the odontoblastic layer and to vascular changes. The tertiary dentin area and the pulp chamber central area were histomorphometrically measured. Data were compared by the analysis of variance and the Kruskal-Wallis test (p<0.05). After 2 days, the amount of inflammatory cells increased in the occlusal third of the coronal pulp until the time of 15 min for both concentrations of bleaching gels. In 30 and 45 min groups of each concentration, the number of inflammatory cells decreased along with the appearance of necrotic areas. After 30 days, a reduction in the pulp chamber central area and an enlargement of tertiary dentin area were observed without the detection of inflammation areas. The rat model of extra coronal bleaching showed to be adequate for bleaching protocols studies, as it was possible to observe alterations in the pulp tissues and in the tooth structure caused by different concentrations and periods of application of bleaching agents.

Comparing the line broadened quasilinear model to Vlasov code

NASA Astrophysics Data System (ADS)

Ghantous, K.; Berk, H. L.; Gorelenkov, N. N.

2014-03-01

The Line Broadened Quasilinear (LBQ) model is revisited to study its predicted saturation level as compared with predictions of a Vlasov solver BOT [Lilley et al., Phys. Rev. Lett. 102, 195003 (2009) and M. Lilley, BOT Manual. The parametric dependencies of the model are modified to achieve more accuracy compared to the results of the Vlasov solver both in regards to a mode amplitude's time evolution to a saturated state and its final steady state amplitude in the parameter space of the model's applicability. However, the regions of stability as predicted by LBQ model and BOT are found to significantly differ from each other. The solutions of the BOT simulations are found to have a larger region of instability than the LBQ simulations.

Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey

USGS Publications Warehouse

Sauer, John R.; Zimmerman, Guthrie S.; Klimstra, Jon D.; Link, William A.

2014-01-01

We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic

A comparative Thermal Analysis of conventional parabolic receiver tube and Cavity model tube in a Solar Parabolic Concentrator

NASA Astrophysics Data System (ADS)

Arumugam, S.; Ramakrishna, P.; Sangavi, S.

2018-02-01

Improvements in heating technology with solar energy is gaining focus, especially solar parabolic collectors. Solar heating in conventional parabolic collectors is done with the help of radiation concentration on receiver tubes. Conventional receiver tubes are open to atmosphere and loose heat by ambient air currents. In order to reduce the convection losses and also to improve the aperture area, we designed a tube with cavity. This study is a comparative performance behaviour of conventional tube and cavity model tube. The performance formulae were derived for the cavity model based on conventional model. Reduction in overall heat loss coefficient was observed for cavity model, though collector heat removal factor and collector efficiency were nearly same for both models. Improvement in efficiency was also observed in the cavity model’s performance. The approach towards the design of a cavity model tube as the receiver tube in solar parabolic collectors gave improved results and proved as a good consideration.

Comparative analysis of European bat lyssavirus 1 pathogenicity in the mouse model.

PubMed

Eggerbauer, Elisa; Pfaff, Florian; Finke, Stefan; Höper, Dirk; Beer, Martin; Mettenleiter, Thomas C; Nolden, Tobias; Teifke, Jens-Peter; Müller, Thomas; Freuling, Conrad M

2017-06-01

European bat lyssavirus 1 is responsible for most bat rabies cases in Europe. Although EBLV-1 isolates display a high degree of sequence identity, different sublineages exist. In individual isolates various insertions and deletions have been identified, with unknown impact on viral replication and pathogenicity. In order to assess whether different genetic features of EBLV-1 isolates correlate with phenotypic changes, different EBLV-1 variants were compared for pathogenicity in the mouse model. Groups of three mice were infected intracranially (i.c.) with 102 TCID50/ml and groups of six mice were infected intramuscularly (i.m.) with 105 TCID50/ml and 102 TCID50/ml as well as intranasally (i.n.) with 102 TCID50/ml. Significant differences in survival following i.m. inoculation with low doses as well as i.n. inoculation were observed. Also, striking variations in incubation periods following i.c. inoculation and i.m. inoculation with high doses were seen. Hereby, the clinical picture differed between general symptoms, spasms and aggressiveness depending on the inoculation route. Immunohistochemistry of mouse brains showed that the virus distribution in the brain depended on the inoculation route. In conclusion, different EBLV-1 isolates differ in pathogenicity indicating variation which is not reflected in studies of single isolates.

Comparative analysis of European bat lyssavirus 1 pathogenicity in the mouse model

PubMed Central

Eggerbauer, Elisa; Pfaff, Florian; Finke, Stefan; Höper, Dirk; Beer, Martin; Mettenleiter, Thomas C.; Nolden, Tobias; Teifke, Jens-Peter; Müller, Thomas

2017-01-01

European bat lyssavirus 1 is responsible for most bat rabies cases in Europe. Although EBLV-1 isolates display a high degree of sequence identity, different sublineages exist. In individual isolates various insertions and deletions have been identified, with unknown impact on viral replication and pathogenicity. In order to assess whether different genetic features of EBLV-1 isolates correlate with phenotypic changes, different EBLV-1 variants were compared for pathogenicity in the mouse model. Groups of three mice were infected intracranially (i.c.) with 102 TCID50/ml and groups of six mice were infected intramuscularly (i.m.) with 105 TCID50/ml and 102 TCID50/ml as well as intranasally (i.n.) with 102 TCID50/ml. Significant differences in survival following i.m. inoculation with low doses as well as i.n. inoculation were observed. Also, striking variations in incubation periods following i.c. inoculation and i.m. inoculation with high doses were seen. Hereby, the clinical picture differed between general symptoms, spasms and aggressiveness depending on the inoculation route. Immunohistochemistry of mouse brains showed that the virus distribution in the brain depended on the inoculation route. In conclusion, different EBLV-1 isolates differ in pathogenicity indicating variation which is not reflected in studies of single isolates. PMID:28628617

Comparing five modelling techniques for predicting forest characteristics

Treesearch

Gretchen G. Moisen; Tracey S. Frescino

2002-01-01

Broad-scale maps of forest characteristics are needed throughout the United States for a wide variety of forest land management applications. Inexpensive maps can be produced by modelling forest class and structure variables collected in nationwide forest inventories as functions of satellite-based information. But little work has been directed at comparing modelling...

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Advancing team-based primary health care: a comparative analysis of policies in western Canada.

PubMed

Suter, Esther; Mallinson, Sara; Misfeldt, Renee; Boakye, Omenaa; Nasmith, Louise; Wong, Sabrina T

2017-07-17

We analyzed and compared primary health care (PHC) policies in British Columbia, Alberta and Saskatchewan to understand how they inform the design and implementation of team-based primary health care service delivery. The goal was to develop policy imperatives that can advance team-based PHC in Canada. We conducted comparative case studies (n = 3). The policy analysis included: Context review: We reviewed relevant information (2007 to 2014) from databases and websites. Policy review and comparative analysis: We compared and contrasted publically available PHC policies. Key informant interviews: Key informants (n = 30) validated narratives prepared from the comparative analysis by offering contextual information on potential policy imperatives. Advisory group and roundtable: An expert advisory group guided this work and a key stakeholder roundtable event guided prioritization of policy imperatives. The concept of team-based PHC varies widely across and within the three provinces. We noted policy gaps related to team configuration, leadership, scope of practice, role clarity and financing of team-based care; few policies speak explicitly to monitoring and evaluation of team-based PHC. We prioritized four policy imperatives: (1) alignment of goals and policies at different system levels; (2) investment of resources for system change; (3) compensation models for all members of the team; and (4) accountability through collaborative practice metrics. Policies supporting team-based PHC have been slow to emerge, lacking a systematic and coordinated approach. Greater alignment with specific consideration of financing, reimbursement, implementation mechanisms and performance monitoring could accelerate systemic transformation by removing some well-known barriers to team-based care.

PSAMM: A Portable System for the Analysis of Metabolic Models

PubMed Central

Steffensen, Jon Lund; Dufault-Thompson, Keith; Zhang, Ying

2016-01-01

The genome-scale models of metabolic networks have been broadly applied in phenotype prediction, evolutionary reconstruction, community functional analysis, and metabolic engineering. Despite the development of tools that support individual steps along the modeling procedure, it is still difficult to associate mathematical simulation results with the annotation and biological interpretation of metabolic models. In order to solve this problem, here we developed a Portable System for the Analysis of Metabolic Models (PSAMM), a new open-source software package that supports the integration of heterogeneous metadata in model annotations and provides a user-friendly interface for the analysis of metabolic models. PSAMM is independent of paid software environments like MATLAB, and all its dependencies are freely available for academic users. Compared to existing tools, PSAMM significantly reduced the running time of constraint-based analysis and enabled flexible settings of simulation parameters using simple one-line commands. The integration of heterogeneous, model-specific annotation information in PSAMM is achieved with a novel format of YAML-based model representation, which has several advantages, such as providing a modular organization of model components and simulation settings, enabling model version tracking, and permitting the integration of multiple simulation problems. PSAMM also includes a number of quality checking procedures to examine stoichiometric balance and to identify blocked reactions. Applying PSAMM to 57 models collected from current literature, we demonstrated how the software can be used for managing and simulating metabolic models. We identified a number of common inconsistencies in existing models and constructed an updated model repository to document the resolution of these inconsistencies. PMID:26828591

Methods of international health technology assessment agencies for economic evaluations--a comparative analysis.

PubMed

Mathes, Tim; Jacobs, Esther; Morfeld, Jana-Carina; Pieper, Dawid

2013-09-30

The number of Health Technology Assessment (HTA) agencies increases. One component of HTAs are economic aspects. To incorporate economic aspects commonly economic evaluations are performed. A convergence of recommendations for methods of health economic evaluations between international HTA agencies would facilitate the adaption of results to different settings and avoid unnecessary expense. A first step in this direction is a detailed analysis of existing similarities and differences in recommendations to identify potential for harmonization. The objective is to provide an overview and comparison of the methodological recommendations of international HTA agencies for economic evaluations. The webpages of 127 international HTA agencies were searched for guidelines containing recommendations on methods for the preparation of economic evaluations. Additionally, the HTA agencies were requested information on methods for economic evaluations. Recommendations of the included guidelines were extracted in standardized tables according to 13 methodological aspects. All process steps were performed independently by two reviewers. Finally 25 publications of 14 HTA agencies were included in the analysis. Methods for economic evaluations vary widely. The greatest accordance could be found for the type of analysis and comparator. Cost-utility-analyses or cost-effectiveness-analyses are recommended. The comparator should continuously be usual care. Again the greatest differences were shown in the recommendations on the measurement/sources of effects, discounting and in the analysis of sensitivity. The main difference regarding effects is the focus either on efficacy or effectiveness. Recommended discounting rates range from 1.5%-5% for effects and 3%-5% for costs whereby it is mostly recommended to use the same rate for costs and effects. With respect to the analysis of sensitivity the main difference is that oftentimes the probabilistic or deterministic approach is recommended

[Comparative analysis of Andean and Caribbean region health systems].

PubMed

Gómez-Camelo, Diana

2005-01-01

Carrying out a comparative analysis of Andean and Caribbean health systems contributing towards the general panorama of Andean and Caribbean region health care system experience. This study was aimed at carrying out a comparative analysis of health systems in Bolivia, Colombia, Ecuador, Peru, Venezuela, the Dominican Republic and Cuba between 1990 and 2004. Documentary information from secondary sources was used. Reform and changes during the aforementioned period were compared, as well as the systems' current configurations. Described typologies were used for studying the health systems. Different organisational designs were found for the systems: a national health system (NHS), segmented systems and systems based on mandatory insurance. The trend of reforms introduced in the 1990s and current proposals in almost all systems are directed towards adopting mandatory insurance via a basic packet of services and strengthening competition in providing services through a public and private mix. The organisation and structure of most systems studied have introduced and continue to introduce changes in line with international guidelines. The generality of these structures means that efforts must still be made to adopt designs strengthening them as instruments improving populations' quality of life. Comparative analysis is a tool leading to studying health systems and producing information which can nourish debate regarding current sector reform. This work took shape during the first approach to a comparative study of Andean region and Caribbean health systems.

Probabilistic bias analysis in pharmacoepidemiology and comparative effectiveness research: a systematic review.

PubMed

Hunnicutt, Jacob N; Ulbricht, Christine M; Chrysanthopoulou, Stavroula A; Lapane, Kate L

2016-12-01

We systematically reviewed pharmacoepidemiologic and comparative effectiveness studies that use probabilistic bias analysis to quantify the effects of systematic error including confounding, misclassification, and selection bias on study results. We found articles published between 2010 and October 2015 through a citation search using Web of Science and Google Scholar and a keyword search using PubMed and Scopus. Eligibility of studies was assessed by one reviewer. Three reviewers independently abstracted data from eligible studies. Fifteen studies used probabilistic bias analysis and were eligible for data abstraction-nine simulated an unmeasured confounder and six simulated misclassification. The majority of studies simulating an unmeasured confounder did not specify the range of plausible estimates for the bias parameters. Studies simulating misclassification were in general clearer when reporting the plausible distribution of bias parameters. Regardless of the bias simulated, the probability distributions assigned to bias parameters, number of simulated iterations, sensitivity analyses, and diagnostics were not discussed in the majority of studies. Despite the prevalence and concern of bias in pharmacoepidemiologic and comparative effectiveness studies, probabilistic bias analysis to quantitatively model the effect of bias was not widely used. The quality of reporting and use of this technique varied and was often unclear. Further discussion and dissemination of the technique are warranted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.

PubMed

Liu, Zhichao; Kelly, Reagan; Fang, Hong; Ding, Don; Tong, Weida

2011-07-18

The primary testing strategy to identify nongenotoxic carcinogens largely relies on the 2-year rodent bioassay, which is time-consuming and labor-intensive. There is an increasing effort to develop alternative approaches to prioritize the chemicals for, supplement, or even replace the cancer bioassay. In silico approaches based on quantitative structure-activity relationships (QSAR) are rapid and inexpensive and thus have been investigated for such purposes. A slightly more expensive approach based on short-term animal studies with toxicogenomics (TGx) represents another attractive option for this application. Thus, the primary questions are how much better predictive performance using short-term TGx models can be achieved compared to that of QSAR models, and what length of exposure is sufficient for high quality prediction based on TGx. In this study, we developed predictive models for rodent liver carcinogenicity using gene expression data generated from short-term animal models at different time points and QSAR. The study was focused on the prediction of nongenotoxic carcinogenicity since the genotoxic chemicals can be inexpensively removed from further development using various in vitro assays individually or in combination. We identified 62 chemicals whose hepatocarcinogenic potential was available from the National Center for Toxicological Research liver cancer database (NCTRlcdb). The gene expression profiles of liver tissue obtained from rats treated with these chemicals at different time points (1 day, 3 days, and 5 days) are available from the Gene Expression Omnibus (GEO) database. Both TGx and QSAR models were developed on the basis of the same set of chemicals using the same modeling approach, a nearest-centroid method with a minimum redundancy and maximum relevancy-based feature selection with performance assessed using compound-based 5-fold cross-validation. We found that the TGx models outperformed QSAR in every aspect of modeling. For example, the

Cost-Effectiveness Analysis of Stereotactic Body Radiation Therapy Compared With Radiofrequency Ablation for Inoperable Colorectal Liver Metastases

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

Kim, Hayeon, E-mail: kimh2@upmc.edu; Gill, Beant; Beriwal, Sushil

Purpose: To conduct a cost-effectiveness analysis to determine whether stereotactic body radiation therapy (SBRT) is a cost-effective therapy compared with radiofrequency ablation (RFA) for patients with unresectable colorectal cancer (CRC) liver metastases. Methods and Materials: A cost-effectiveness analysis was conducted using a Markov model and 1-month cycle over a lifetime horizon. Transition probabilities, quality of life utilities, and costs associated with SBRT and RFA were captured in the model on the basis of a comprehensive literature review and Medicare reimbursements in 2014. Strategies were compared using the incremental cost-effectiveness ratio, with effectiveness measured in quality-adjusted life years (QALYs). To account formore » model uncertainty, 1-way and probabilistic sensitivity analyses were performed. Strategies were evaluated with a willingness-to-pay threshold of $100,000 per QALY gained. Results: In base case analysis, treatment costs for 3 fractions of SBRT and 1 RFA procedure were $13,000 and $4397, respectively. Median survival was assumed the same for both strategies (25 months). The SBRT costs $8202 more than RFA while gaining 0.05 QALYs, resulting in an incremental cost-effectiveness ratio of $164,660 per QALY gained. In 1-way sensitivity analyses, results were most sensitive to variation of median survival from both treatments. Stereotactic body radiation therapy was economically reasonable if better survival was presumed (>1 month gain) or if used for large tumors (>4 cm). Conclusions: If equal survival is assumed, SBRT is not cost-effective compared with RFA for inoperable colorectal liver metastases. However, if better local control leads to small survival gains with SBRT, this strategy becomes cost-effective. Ideally, these results should be confirmed with prospective comparative data.« less

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These

Flows of the Tycho Crater type, comparative analysis

NASA Astrophysics Data System (ADS)

Bratkov, Yury

Some embeddings of the Tycho Crater type flow or, more generally, of the Tycho Butterfly type flow, are demonstrated, and comparative analysis is given. Additionally, identity of the Earthen World Ocean and the Moon Global Ocean is demonstrated. Supersonic flows (jets, shock waves, Mach stems) are comparatively studied [1]. References: [1] Bratkov Yu.N., Caspian Seas, http://viXra.org/abs/1211.0067, 12 Nov 2012

Analysis of Magnitude Correlations in a Self-Similar model of Seismicity

NASA Astrophysics Data System (ADS)

Zambrano, A.; Joern, D.

2017-12-01

A recent model of seismicity that incorporates a self-similar Omori-Utsu relation, which is used to describe the temporal evolution of earthquake triggering, has been shown to provide a more accurate description of seismicity in Southern California when compared to epidemic type aftershock sequence models. Forecasting of earthquakes is an active research area where one of the debated points is whether magnitude correlations of earthquakes exist within real world seismic data. Prior to this work, the analysis of magnitude correlations of the aforementioned self-similar model had not been addressed. Here we present statistical properties of the magnitude correlations for the self-similar model along with an analytical analysis of the branching ratio and criticality parameters.

Neutral model analysis of landscape patterns from mathematical morphology

Treesearch

Kurt H. Riitters; Peter Vogt; Pierre Soille; Jacek Kozak; Christine Estreguil

2007-01-01

Mathematical morphology encompasses methods for characterizing land-cover patterns in ecological research and biodiversity assessments. This paper reports a neutral model analysis of patterns in the absence of a structuring ecological process, to help set standards for comparing and interpreting patterns identified by mathematical morphology on real land-cover maps. We...

A comparative analysis of 7.0-Tesla magnetic resonance imaging and histology measurements of knee articular cartilage in a canine posterolateral knee injury model: a preliminary analysis.

PubMed

Pepin, Scott R; Griffith, Chad J; Wijdicks, Coen A; Goerke, Ute; McNulty, Margaret A; Parker, Josh B; Carlson, Cathy S; Ellermann, Jutta; LaPrade, Robert F

2009-11-01

There has recently been increased interest in the use of 7.0-T magnetic resonance imaging for evaluating articular cartilage degeneration and quantifying the progression of osteoarthritis. The purpose of this study was to evaluate articular cartilage cross-sectional area and maximum thickness in the medial compartment of intact and destabilized canine knees using 7.0-T magnetic resonance images and compare these results with those obtained from the corresponding histologic sections. Controlled laboratory study. Five canines had a surgically created unilateral grade III posterolateral knee injury that was followed for 6 months before euthanasia. The opposite, noninjured knee was used as a control. At necropsy, 3-dimensional gradient echo images of the medial tibial plateau of both knees were obtained using a 7.0-T magnetic resonance imaging scanner. Articular cartilage area and maximum thickness in this site were digitally measured on the magnetic resonance images. The proximal tibias were processed for routine histologic analysis with hematoxylin and eosin staining. Articular cartilage area and maximum thickness were measured in histologic sections corresponding to the sites of the magnetic resonance slices. The magnetic resonance imaging results revealed an increase in articular cartilage area and maximum thickness in surgical knees compared with control knees in all specimens; these changes were significant for both parameters (P <.05 for area; P <.01 for thickness). The average increase in area was 14.8% and the average increase in maximum thickness was 15.1%. The histologic results revealed an average increase in area of 27.4% (P = .05) and an average increase in maximum thickness of 33.0% (P = .06). Correlation analysis between the magnetic resonance imaging and histology data revealed that the area values were significantly correlated (P < .01), but the values for thickness obtained from magnetic resonance imaging were not significantly different from the

Genome-wide comparative analysis of four Indian Drosophila species.

PubMed

Mohanty, Sujata; Khanna, Radhika

2017-12-01

Comparative analysis of multiple genomes of closely or distantly related Drosophila species undoubtedly creates excitement among evolutionary biologists in exploring the genomic changes with an ecology and evolutionary perspective. We present herewith the de novo assembled whole genome sequences of four Drosophila species, D. bipectinata, D. takahashii, D. biarmipes and D. nasuta of Indian origin using Next Generation Sequencing technology on an Illumina platform along with their detailed assembly statistics. The comparative genomics analysis, e.g. gene predictions and annotations, functional and orthogroup analysis of coding sequences and genome wide SNP distribution were performed. The whole genome of Zaprionus indianus of Indian origin published earlier by us and the genome sequences of previously sequenced 12 Drosophila species available in the NCBI database were included in the analysis. The present work is a part of our ongoing genomics project of Indian Drosophila species.

High-resolution comparative modeling with RosettaCM.

PubMed

Song, Yifan; DiMaio, Frank; Wang, Ray Yu-Ruei; Kim, David; Miles, Chris; Brunette, Tj; Thompson, James; Baker, David

2013-10-08

We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ∼15%. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact of model-based risk analysis for liver surgery planning.

PubMed

Hansen, C; Zidowitz, S; Preim, B; Stavrou, G; Oldhafer, K J; Hahn, H K

2014-05-01

A model-based risk analysis for oncologic liver surgery was described in previous work (Preim et al. in Proceedings of international symposium on computer assisted radiology and surgery (CARS), Elsevier, Amsterdam, pp. 353–358, 2002; Hansen et al. Int I Comput Assist Radiol Surg 4(5):469–474, 2009). In this paper, we present an evaluation of this method. To prove whether and how the risk analysis facilitates the process of liver surgery planning, an explorative user study with 10 liver experts was conducted. The purpose was to compare and analyze their decision-making. The results of the study show that model-based risk analysis enhances the awareness of surgical risk in the planning stage. Participants preferred smaller resection volumes and agreed more on the safety margins’ width in case the risk analysis was available. In addition, time to complete the planning task and confidence of participants were not increased when using the risk analysis. This work shows that the applied model-based risk analysis may influence important planning decisions in liver surgery. It lays a basis for further clinical evaluations and points out important fields for future research.

Cost-effectiveness analysis of a new 8% capsaicin patch compared to existing therapies for postherpetic neuralgia.

PubMed

Armstrong, Edward P; Malone, Daniel C; McCarberg, Bill; Panarites, Christopher J; Pham, Sissi V

2011-05-01

The purpose of this study was to compare the cost effectiveness of a new 8% capsaicin patch, compared to the current treatments for postherpetic neuralgia (PHN), including tricyclic antidepressants (TCAs), topical lidocaine patches, duloxetine, gabapentin, and pregabalin. A 1-year Markov model was constructed for PHN with monthly cycles, including dose titration and management of adverse events. The perspective of the analysis was from a payer perspective, managed-care organization. Clinical trials were used to determine the proportion of patients achieving at least a 30% improvement in PHN pain, the efficacy parameter. The outcome was cost per quality-adjusted life-year (QALY); second-order probabilistic sensitivity analyses were conducted. The effectiveness results indicated that 8% capsaicin patch and topical lidocaine patch were significantly more effective than the oral PHN products. TCAs were least costly and significantly less costly than duloxetine, pregabalin, topical lidocaine patch, 8% capsaicin patch, but not gabapentin. The incremental cost-effectiveness ratio for the 8% capsaicin patch overlapped with the topical lidocaine patch and was within the accepted threshold of cost per QALY gained compared to TCAs, duloxetine, gabapentin, and pregablin. The frequency of the 8% capsaicin patch retreatment assumption significantly impacts its cost-effectiveness results. There are several limitations to this analysis. Since no head-to-head studies were identified, this model used inputs from multiple clinical trials. Also, a last observation carried forward process was assumed to have continued for the duration of the model. Additionally, the trials with duloxetine may have over-predicted its efficacy in PHN. Although a 30% improvement in pain is often an endpoint in clinical trials, some patients may require greater or less improvement in pain to be considered a clinical success. The effectiveness results demonstrated that 8% capsaicin and topical lidocaine

Methods and theory in bone modeling drift: comparing spatial analyses of primary bone distributions in the human humerus.

PubMed

Maggiano, Corey M; Maggiano, Isabel S; Tiesler, Vera G; Chi-Keb, Julio R; Stout, Sam D

2016-01-01

This study compares two novel methods quantifying bone shaft tissue distributions, and relates observations on human humeral growth patterns for applications in anthropological and anatomical research. Microstructural variation in compact bone occurs due to developmental and mechanically adaptive circumstances that are 'recorded' by forming bone and are important for interpretations of growth, health, physical activity, adaptation, and identity in the past and present. Those interpretations hinge on a detailed understanding of the modeling process by which bones achieve their diametric shape, diaphyseal curvature, and general position relative to other elements. Bone modeling is a complex aspect of growth, potentially causing the shaft to drift transversely through formation and resorption on opposing cortices. Unfortunately, the specifics of modeling drift are largely unknown for most skeletal elements. Moreover, bone modeling has seen little quantitative methodological development compared with secondary bone processes, such as intracortical remodeling. The techniques proposed here, starburst point-count and 45° cross-polarization hand-drawn histomorphometry, permit the statistical and populational analysis of human primary tissue distributions and provide similar results despite being suitable for different applications. This analysis of a pooled archaeological and modern skeletal sample confirms the importance of extreme asymmetry in bone modeling as a major determinant of microstructural variation in diaphyses. Specifically, humeral drift is posteromedial in the human humerus, accompanied by a significant rotational trend. In general, results encourage the usage of endocortical primary bone distributions as an indicator and summary of bone modeling drift, enabling quantitative analysis by direction and proportion in other elements and populations. © 2015 Anatomical Society.

Comparative Analysis of AhR-Mediated TCDD-Elicited Gene Expression in Human Liver Adult Stem Cells

PubMed Central

Kim, Suntae; Dere, Edward; Burgoon, Lyle D.; Chang, Chia-Cheng; Zacharewski, Timothy R.

2009-01-01

Time course and dose-response studies were conducted in HL1-1 cells, a human liver cell line with stem cell–like characteristics, to assess the differential gene expression elicited by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) compared with other established models. Cells were treated with 0.001, 0.01, 0.1, 1, 10, or 100nM TCDD or dimethyl sulfoxide vehicle control for 12 h for the dose-response study, or with 10nM TCDD or vehicle for 1, 2, 4, 8, 12, 24, or 48 h for the time course study. Elicited changes were monitored using a human cDNA microarray with 6995 represented genes. Empirical Bayes analysis identified 144 genes differentially expressed at one or more time points following treatment. Most genes exhibited dose-dependent responses including CYP1A1, CYP1B1, ALDH1A3, and SLC7A5 genes. Comparative analysis of HL1-1 differential gene expression to human HepG2 data identified 74 genes with comparable temporal expression profiles including 12 putative primary responses. HL1-1–specific changes were related to lipid metabolism and immune responses, consistent with effects elicited in vivo. Furthermore, comparative analysis of HL1-1 cells with mouse Hepa1c1c7 hepatoma cell lines and C57BL/6 hepatic tissue identified 18 and 32 commonly regulated orthologous genes, respectively, with functions associated with signal transduction, transcriptional regulation, metabolism and transport. Although some common pathways are affected, the results suggest that TCDD elicits species- and model-specific gene expression profiles. PMID:19684285

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

PubMed

Stock, Kristin; Estrada, Marta F; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph

2016-07-01

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery

PubMed Central

Stock, Kristin; Estrada, Marta F.; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E.; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C.; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph

2016-01-01

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models. PMID:27364600

Digital model as an alternative to plaster model in assessment of space analysis

PubMed Central

Kumar, A. Anand; Phillip, Abraham; Kumar, Sathesh; Rawat, Anuradha; Priya, Sakthi; Kumaran, V.

2015-01-01

Introduction: Digital three-dimensional models are widely used for orthodontic diagnosis. The purpose of this study was to appraise the accuracy of digital models obtained from computer-aided design/computer-aided manufacturing (CAD/CAM) and cone-beam computed tomography (CBCT) for tooth-width measurements and the Bolton analysis. Materials and Methods: Digital models (CAD/CAM, CBCT) and plaster model were made for each of 50 subjects. Tooth-width measurements on the digital models (CAD/CAM, CBCT) were compared with those on the corresponding plaster models. The anterior and overall Bolton ratios were calculated for each participant and for each method. The paired t-test was applied to determine the validity. Results: Tooth-width measurements, anterior, and overall Bolton ratio of digital models of CAD/CAM and CBCT did not differ significantly from those on the plaster models. Conclusion: Hence, both CBCT and CAD/CAM are trustable and promising technique that can replace plaster models due to its overwhelming advantages. PMID:26538899

Comparing and improving proper orthogonal decomposition (POD) to reduce the complexity of groundwater models

NASA Astrophysics Data System (ADS)

Gosses, Moritz; Nowak, Wolfgang; Wöhling, Thomas

2017-04-01

Physically-based modeling is a wide-spread tool in understanding and management of natural systems. With the high complexity of many such models and the huge amount of model runs necessary for parameter estimation and uncertainty analysis, overall run times can be prohibitively long even on modern computer systems. An encouraging strategy to tackle this problem are model reduction methods. In this contribution, we compare different proper orthogonal decomposition (POD, Siade et al. (2010)) methods and their potential applications to groundwater models. The POD method performs a singular value decomposition on system states as simulated by the complex (e.g., PDE-based) groundwater model taken at several time-steps, so-called snapshots. The singular vectors with the highest information content resulting from this decomposition are then used as a basis for projection of the system of model equations onto a subspace of much lower dimensionality than the original complex model, thereby greatly reducing complexity and accelerating run times. In its original form, this method is only applicable to linear problems. Many real-world groundwater models are non-linear, tough. These non-linearities are introduced either through model structure (unconfined aquifers) or boundary conditions (certain Cauchy boundaries, like rivers with variable connection to the groundwater table). To date, applications of POD focused on groundwater models simulating pumping tests in confined aquifers with constant head boundaries. In contrast, POD model reduction either greatly looses accuracy or does not significantly reduce model run time if the above-mentioned non-linearities are introduced. We have also found that variable Dirichlet boundaries are problematic for POD model reduction. An extension to the POD method, called POD-DEIM, has been developed for non-linear groundwater models by Stanko et al. (2016). This method uses spatial interpolation points to build the equation system in the

Combining Static Analysis and Model Checking for Software Analysis

NASA Technical Reports Server (NTRS)

Brat, Guillaume; Visser, Willem; Clancy, Daniel (Technical Monitor)

2003-01-01

We present an iterative technique in which model checking and static analysis are combined to verify large software systems. The role of the static analysis is to compute partial order information which the model checker uses to reduce the state space. During exploration, the model checker also computes aliasing information that it gives to the static analyzer which can then refine its analysis. The result of this refined analysis is then fed back to the model checker which updates its partial order reduction. At each step of this iterative process, the static analysis computes optimistic information which results in an unsafe reduction of the state space. However we show that the process converges to a fired point at which time the partial order information is safe and the whole state space is explored.

Engine System Loads Analysis Compared to Hot-Fire Data

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Jennings, John M.; Mims, Katherine; Brunty, Joseph; Christensen, Eric R.; McConnaughey, Paul R. (Technical Monitor)

2002-01-01

Early implementation of structural dynamics finite element analyses for calculation of design loads is considered common design practice for high volume manufacturing industries such as automotive and aeronautical industries. However with the rarity of rocket engine development programs starts, these tools are relatively new to the design of rocket engines. In the NASA MC-1 engine program, the focus was to reduce the cost-to-weight ratio. The techniques for structural dynamics analysis practices, were tailored in this program to meet both production and structural design goals. Perturbation of rocket engine design parameters resulted in a number of MC-1 load cycles necessary to characterize the impact due to mass and stiffness changes. Evolution of loads and load extraction methodologies, parametric considerations and a discussion of load path sensitivities are important during the design and integration of a new engine system. During the final stages of development, it is important to verify the results of an engine system model to determine the validity of the results. During the final stages of the MC-1 program, hot-fire test results were obtained and compared to the structural design loads calculated by the engine system model. These comparisons are presented in this paper.

The comparative kinetic analysis of Acetocell and Lignoboost® lignin pyrolysis: the estimation of the distributed reactivity models.

PubMed

Janković, Bojan

2011-10-01

The non-isothermal pyrolysis kinetics of Acetocell (the organosolv) and Lignoboost® (kraft) lignins, in an inert atmosphere, have been studied by thermogravimetric analysis. Using isoconversional analysis, it was concluded that the apparent activation energy for all lignins strongly depends on conversion, showing that the pyrolysis of lignins is not a single chemical process. It was identified that the pyrolysis process of Acetocell and Lignoboost® lignin takes place over three reaction steps, which was confirmed by appearance of the corresponding isokinetic relationships (IKR). It was found that major pyrolysis stage of both lignins is characterized by stilbene pyrolysis reactions, which were subsequently followed by decomposition reactions of products derived from the stilbene pyrolytic process. It was concluded that non-isothermal pyrolysis of Acetocell and Lignoboost® lignins can be best described by n-th (n>1) reaction order kinetics, using the Weibull mixture model (as distributed reactivity model) with alternating shape parameters. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluating the risks of clinical research: direct comparative analysis.

PubMed

Rid, Annette; Abdoler, Emily; Roberson-Nay, Roxann; Pine, Daniel S; Wendler, David

2014-09-01

Many guidelines and regulations allow children and adolescents to be enrolled in research without the prospect of clinical benefit when it poses minimal risk. However, few systematic methods exist to determine when research risks are minimal. This situation has led to significant variation in minimal risk judgments, raising concern that some children are not being adequately protected. To address this concern, we describe a new method for implementing the widely endorsed "risks of daily life" standard for minimal risk. This standard defines research risks as minimal when they do not exceed the risks posed by daily life activities or routine examinations. This study employed a conceptual and normative analysis, and use of an illustrative example. Different risks are composed of the same basic elements: Type, likelihood, and magnitude of harm. Hence, one can compare the risks of research and the risks of daily life by comparing the respective basic elements with each other. We use this insight to develop a systematic method, direct comparative analysis, for implementing the "risks of daily life" standard for minimal risk. The method offers a way of evaluating research procedures that pose the same types of risk as daily life activities, such as the risk of experiencing anxiety, stress, or other psychological harm. We thus illustrate how direct comparative analysis can be applied in practice by using it to evaluate whether the anxiety induced by a respiratory CO2 challenge poses minimal or greater than minimal risks in children and adolescents. Direct comparative analysis is a systematic method for applying the "risks of daily life" standard for minimal risk to research procedures that pose the same types of risk as daily life activities. It thereby offers a method to protect children and adolescents in research, while ensuring that important studies are not blocked because of unwarranted concerns about research risks.

[Cost-effectiveness analysis of etanercept compared with other biologic therapies in the treatment of rheumatoid arthritis].

PubMed

Salinas-Escudero, Guillermo; Vargas-Valencia, Juan; García-García, Erika Gabriela; Munciño-Ortega, Emilio; Galindo-Suárez, Rosa María

2013-01-01

to conduct cost-effectiveness analysis of etanercept compared with other biologic therapies in the treatment of moderate or severe rheumatoid arthritis in patients with previous unresponse to immune selective anti-inflammatory derivatives failure. a pharmacoeconomic model based on decision analysis to assess the clinical outcome after giving etanercept, infliximab, adalimumab or tocilizumab to treat moderate or severe rheumatoid arthritis was employed. Effectiveness of medications was assessed with improvement rates of 20 % or 70 % of the parameters established by the American College of Rheumatology (ACR 20 and ACR 70). the model showed that etanercept had the most effective therapeutic response rate: 79.7 % for ACR 20 and 31.4 % for ACR 70, compared with the response to other treatments. Also, etanercept had the lowest cost ($149,629.10 per patient) and had the most cost-effective average ($187,740.40 for clinical success for ACR 20 and $476,525.80 for clinical success for ACR 70) than the other biologic therapies. we demonstrated that treatment with etanercept is more effective and less expensive compared to the other drugs, thus making it more efficient therapeutic option both in terms of means and incremental cost-effectiveness ratios for the treatment of rheumatoid arthritis.

Cost-effectiveness of unicondylar versus total knee arthroplasty: a Markov model analysis.

PubMed

Peersman, Geert; Jak, Wouter; Vandenlangenbergh, Tom; Jans, Christophe; Cartier, Philippe; Fennema, Peter

2014-01-01

Unicondylar knee arthroplasty (UKA) is believed to lead to less morbidity and enhanced functional outcomes when compared with total knee arthroplasty (TKA). Conversely, UKA is also associated with a higher revision risk than TKA. In order to further clarify the key differences between these separate procedures, the current study assessing the cost-effectiveness of UKA versus TKA was undertaken. A state-transition Markov model was developed to compare the cost-effectiveness of UKA versus TKA for unicondylar osteoarthritis using a Belgian payer's perspective. The model was designed to include the possibility of two revision procedures. Model estimates were obtained through literature review and revision rates were based on registry data. Threshold analysis and probabilistic sensitivity analysis were performed to assess the model's robustness. UKA was associated with a cost reduction of €2,807 and a utility gain of 0.04 quality-adjusted life years in comparison with TKA. Analysis determined that the model is sensitive to clinical effectiveness, and that a marginal reduction in the clinical performance of UKA would lead to TKA being the more cost-effective solution. UKA yields clear advantages in terms of costs and marginal advantages in terms of health effects, in comparison with TKA. © 2014 Elsevier B.V. All rights reserved.

Estimating, Testing, and Comparing Specific Effects in Structural Equation Models: The Phantom Model Approach

ERIC Educational Resources Information Center

Macho, Siegfried; Ledermann, Thomas

2011-01-01

The phantom model approach for estimating, testing, and comparing specific effects within structural equation models (SEMs) is presented. The rationale underlying this novel method consists in representing the specific effect to be assessed as a total effect within a separate latent variable model, the phantom model that is added to the main…

Cost-effectiveness analysis of a randomized trial comparing care models for chronic kidney disease.

PubMed

Hopkins, Robert B; Garg, Amit X; Levin, Adeera; Molzahn, Anita; Rigatto, Claudio; Singer, Joel; Soltys, George; Soroka, Steven; Parfrey, Patrick S; Barrett, Brendan J; Goeree, Ron

2011-06-01

Potential cost and effectiveness of a nephrologist/nurse-based multifaceted intervention for stage 3 to 4 chronic kidney disease are not known. This study examines the cost-effectiveness of a chronic disease management model for chronic kidney disease. Cost and cost-effectiveness were prospectively gathered alongside a multicenter trial. The Canadian Prevention of Renal and Cardiovascular Endpoints Trial (CanPREVENT) randomized 236 patients to receive usual care (controls) and another 238 patients to multifaceted nurse/nephrologist-supported care that targeted factors associated with development of kidney and cardiovascular disease (intervention). Cost and outcomes over 2 years were examined to determine the incremental cost-effectiveness of the intervention. Base-case analysis included disease-related costs, and sensitivity analysis included all costs. Consideration of all costs produced statistically significant differences. A lower number of days in hospital explained most of the cost difference. For both base-case and sensitivity analyses with all costs included, the intervention group required fewer resources and had higher quality of life. The direction of the results was unchanged to inclusion of various types of costs, consideration of payer or societal perspective, changes to the discount rate, and levels of GFR. The nephrologist/nurse-based multifaceted intervention represents good value for money because it reduces costs without reducing quality of life for patients with chronic kidney disease.

Cost Utility Analysis of Topical Steroids Compared With Dietary Elimination for Treatment of Eosinophilic Esophagitis.

PubMed

Cotton, Cary C; Erim, Daniel; Eluri, Swathi; Palmer, Sarah H; Green, Daniel J; Wolf, W Asher; Runge, Thomas M; Wheeler, Stephanie; Shaheen, Nicholas J; Dellon, Evan S

2017-06-01

Topical corticosteroids or dietary elimination are recommended as first-line therapies for eosinophilic esophagitis, but data to directly compare these therapies are scant. We performed a cost utility comparison of topical corticosteroids and the 6-food elimination diet (SFED) in treatment of eosinophilic esophagitis, from the payer perspective. We used a modified Markov model based on current clinical guidelines, in which transition between states depended on histologic response simulated at the individual cohort-member level. Simulation parameters were defined by systematic review and meta-analysis to determine the base-case estimates and bounds of uncertainty for sensitivity analysis. Meta-regression models included adjustment for differences in study and cohort characteristics. In the base-case scenario, topical fluticasone was about as effective as SFED but more expensive at a 5-year time horizon ($9261.58 vs $5719.72 per person). SFED was more effective and less expensive than topical fluticasone and topical budesonide in the base-case scenario. Probabilistic sensitivity analysis revealed little uncertainty in relative treatment effectiveness. There was somewhat greater uncertainty in the relative cost of treatments; most simulations found SFED to be less expensive. In a cost utility analysis comparing topical corticosteroids and SFED for first-line treatment of eosinophilic esophagitis, the therapies were similar in effectiveness. SFED was on average less expensive, and more cost effective in most simulations, than topical budesonide and topical fluticasone, from a payer perspective and not accounting for patient-level costs or quality of life. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Comparing soil moisture memory in satellite observations and models

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

2013-04-01

A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

Viscosity models for pure hydrocarbons at extreme conditions: A review and comparative study

DOE PAGES

Baled, Hseen O.; Gamwo, Isaac K.; Enick, Robert M.; ...

2018-01-12

Here, viscosity is a critical fundamental property required in many applications in the chemical and oil industries. In this review the performance of seven select viscosity models, representative of various predictive and correlative approaches, is discussed and evaluated by comparison to experimental data of 52 pure hydrocarbons including straight-chain alkanes, branched alkanes, cycloalkanes, and aromatics. This analysis considers viscosity data to extremely high-temperature, high-pressure conditions up to 573 K and 300 MPa. Unsatisfactory results are found, particularly at high pressures, with the Chung-Ajlan-Lee-Starling, Pedersen-Fredenslund, and Lohrenz-Bray-Clark models commonly used for oil reservoir simulation. If sufficient experimental viscosity data are readilymore » available to determine model-specific parameters, the free volume theory and the expanded fluid theory models provide generally comparable results that are superior to those obtained with the friction theory, particularly at pressures higher than 100 MPa. Otherwise, the entropy scaling method by Lötgering-Lin and Gross is recommended as the best predictive model.« less

Viscosity models for pure hydrocarbons at extreme conditions: A review and comparative study

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

Baled, Hseen O.; Gamwo, Isaac K.; Enick, Robert M.

Here, viscosity is a critical fundamental property required in many applications in the chemical and oil industries. In this review the performance of seven select viscosity models, representative of various predictive and correlative approaches, is discussed and evaluated by comparison to experimental data of 52 pure hydrocarbons including straight-chain alkanes, branched alkanes, cycloalkanes, and aromatics. This analysis considers viscosity data to extremely high-temperature, high-pressure conditions up to 573 K and 300 MPa. Unsatisfactory results are found, particularly at high pressures, with the Chung-Ajlan-Lee-Starling, Pedersen-Fredenslund, and Lohrenz-Bray-Clark models commonly used for oil reservoir simulation. If sufficient experimental viscosity data are readilymore » available to determine model-specific parameters, the free volume theory and the expanded fluid theory models provide generally comparable results that are superior to those obtained with the friction theory, particularly at pressures higher than 100 MPa. Otherwise, the entropy scaling method by Lötgering-Lin and Gross is recommended as the best predictive model.« less

Observed & Modeled Changes in the Onset of Spring: A Preliminary Comparative Analysis by Geographic Regions of the USA

NASA Astrophysics Data System (ADS)

Enquist, C.

2012-12-01

Phenology, the study of seasonal life cycle events in plants and animals, is a well-recognized indicator of climate change impacts on people and nature. Models, experiments, and observational studies show changes in plant and animal phenology as a function of environmental change. Current research aims to improve our understanding of changes by enhancing existing models, analyzing observations, synthesizing previous research, and comparing outputs. Local to regional climatology is a critical driver of phenological variation of organisms across scales. Because plants respond to the cumulative effects of daily weather over an extended period, timing of life cycle events are effective integrators of climate data. One specific measure, leaf emergence, is particularly important because it often shows a strong response to temperature change, and is crucial for assessment of processes related to start and duration of the growing season. Schwartz et al. (2006) developed a suite of models (the "Spring Indices") linking plant development from historical data from leafing and flowering of cloned lilac and honeysuckle with basic climatic drivers to monitor changes related to the start of the spring growing season. These models can be generated at any location that has daily max-min temperature time series. The new version of these models is called the "Extended Spring Indices," or SI-x (Schwartz et al. in press). The SI-x model output (first leaf date and first bloom date) are produced similarly to the original models (SI-o), but do not incorporate accumulated chilling hours; rather energy accumulation starts for all stations on January 1. This change extends the locations SI model output can be generated into the sub-tropics, allowing full coverage of the conterminous USA. Both SI model versions are highly correlated, with mean bias and mean absolute differences around two days or less, and a similar bias and absolute errors when compared to cloned lilac data. To

Jump Model / Comparability Ratio Model — Joinpoint Help System 4.4.0.0

Cancer.gov

The Jump Model / Comparability Ratio Model in the Joinpoint software provides a direct estimation of trend data (e.g. cancer rates) where there is a systematic scale change, which causes a “jump” in the rates, but is assumed not to affect the underlying trend.

A selection model for accounting for publication bias in a full network meta-analysis.

PubMed

Mavridis, Dimitris; Welton, Nicky J; Sutton, Alex; Salanti, Georgia

2014-12-30

Copas and Shi suggested a selection model to explore the potential impact of publication bias via sensitivity analysis based on assumptions for the probability of publication of trials conditional on the precision of their results. Chootrakool et al. extended this model to three-arm trials but did not fully account for the implications of the consistency assumption, and their model is difficult to generalize for complex network structures with more than three treatments. Fitting these selection models within a frequentist setting requires maximization of a complex likelihood function, and identification problems are common. We have previously presented a Bayesian implementation of the selection model when multiple treatments are compared with a common reference treatment. We now present a general model suitable for complex, full network meta-analysis that accounts for consistency when adjusting results for publication bias. We developed a design-by-treatment selection model to describe the mechanism by which studies with different designs (sets of treatments compared in a trial) and precision may be selected for publication. We fit the model in a Bayesian setting because it avoids the numerical problems encountered in the frequentist setting, it is generalizable with respect to the number of treatments and study arms, and it provides a flexible framework for sensitivity analysis using external knowledge. Our model accounts for the additional uncertainty arising from publication bias more successfully compared to the standard Copas model or its previous extensions. We illustrate the methodology using a published triangular network for the failure of vascular graft or arterial patency. Copyright © 2014 John Wiley & Sons, Ltd.

Cost-Effectiveness Analysis Comparing Pre-Diagnosis Autism Spectrum Disorder (ASD)-Targeted Intervention with Ontario's Autism Intervention Program

ERIC Educational Resources Information Center

Penner, Melanie; Rayar, Meera; Bashir, Naazish; Roberts, S. Wendy; Hancock-Howard, Rebecca L.; Coyte, Peter C.

2015-01-01

Novel management strategies for autism spectrum disorder (ASD) propose providing interventions before diagnosis. We performed a cost-effectiveness analysis comparing the costs and dependency-free life years (DFLYs) generated by pre-diagnosis intensive Early Start Denver Model (ESDM-I); pre-diagnosis parent-delivered ESDM (ESDM-PD); and the Ontario…

Conceptual Models of Depression in Primary Care Patients: A Comparative Study

PubMed Central

Karasz, Alison; Garcia, Nerina; Ferri, Lucia

2009-01-01

Conventional psychiatric treatment models are based on a biopsychiatric model of depression. A plausible explanation for low rates of depression treatment utilization among ethnic minorities and the poor is that members of these communities do not share the cultural assumptions underlying the biopsychiatric model. The study examined conceptual models of depression among depressed patients from various ethnic groups, focusing on the degree to which patients’ conceptual models ‘matched’ a biopsychiatric model of depression. The sample included 74 primary care patients from three ethnic groups screening positive for depression. We administered qualitative interviews assessing patients’ conceptual representations of depression. The analysis proceeded in two phases. The first phase involved a strategy called ‘quantitizing’ the qualitative data. A rating scheme was developed and applied to the data by a rater blind to study hypotheses. The data was subjected to statistical analyses. The second phase of the analysis involved the analysis of thematic data using standard qualitative techniques. Study hypotheses were largely supported. The qualitative analysis provided a detailed picture of primary care patients’ conceptual models of depression and suggested interesting directions for future research. PMID:20182550

"Plateau"-related summary statistics are uninformative for comparing working memory models.

PubMed

van den Berg, Ronald; Ma, Wei Ji

2014-10-01

Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.

Comparing fluid mechanics models with experimental data.

PubMed Central

Spedding, G R

2003-01-01

The art of modelling the physical world lies in the appropriate simplification and abstraction of the complete problem. In fluid mechanics, the Navier-Stokes equations provide a model that is valid under most circumstances germane to animal locomotion, but the complexity of solutions provides strong incentive for the development of further, more simplified practical models. When the flow organizes itself so that all shearing motions are collected into localized patches, then various mathematical vortex models have been very successful in predicting and furthering the physical understanding of many flows, particularly in aerodynamics. Experimental models have the significant added convenience that the fluid mechanics can be generated by a real fluid, not a model, provided the appropriate dimensionless groups have similar values. Then, analogous problems can be encountered in making intelligible but independent descriptions of the experimental results. Finally, model predictions and experimental results may be compared if, and only if, numerical estimates of the likely variations in the tested quantities are provided. Examples from recent experimental measurements of wakes behind a fixed wing and behind a bird in free flight are used to illustrate these principles. PMID:14561348

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

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

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

DOE PAGES

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish; ...

2015-06-04

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

A comparative analysis of readmission rates after outpatient cosmetic surgery.

PubMed

Mioton, Lauren M; Alghoul, Mohammed S; Kim, John Y S

2014-02-01

Despite the increasing scrutiny of surgical procedures, outpatient cosmetic surgery has an established record of safety and efficacy. A key measure in assessing surgical outcomes is the examination of readmission rates. However, there is a paucity of data on unplanned readmission following cosmetic surgery procedures. The authors studied readmission rates for outpatient cosmetic surgery and compared the data with readmission rates for other surgical procedures. The 2011 National Surgical Quality Improvement Program (NSQIP) data set was queried for all outpatient procedures. Readmission rates were calculated for the 5 surgical specialties with the greatest number of outpatient procedures and for the overall outpatient cosmetic surgery population. Subgroup analysis was performed on the 5 most common cosmetic surgery procedures. Multivariate regression models were used to determine predictors of readmission for cosmetic surgery patients. The 2879 isolated outpatient cosmetic surgery cases had an associated 0.90% unplanned readmission rate. The 5 specialties with the highest number of outpatient surgical procedures were general, orthopedic, gynecologic, urologic, and otolaryngologic surgery; their unplanned readmission rates ranged from 1.21% to 3.73%. The 5 most common outpatient cosmetic surgery procedures and their associated readmission rates were as follows: reduction mammaplasty, 1.30%; mastopexy, 0.31%; liposuction, 1.13%; abdominoplasty, 1.78%; and breast augmentation, 1.20%. Multivariate regression analysis demonstrated that operating time (in hours) was an independent predictor of readmission (odds ratio, 1.40; 95% confidence interval, 1.08-1.81; P=.010). Rates of unplanned readmission with outpatient cosmetic surgery are low and compare favorably to those of other outpatient surgeries.