Highly Variable Cycle Exhaust Model Test (HVC10)

NASA Technical Reports Server (NTRS)

Henderson, Brenda; Wernet, Mark; Podboy, Gary; Bozak, Rick

2010-01-01

Results from acoustic and flow-field studies using the Highly Variable Cycle Exhaust (HVC) model were presented. The model consisted of a lobed mixer on the core stream, an elliptic nozzle on the fan stream, and an ejector. For baseline comparisons, the fan nozzle was replaced with a round nozzle and the ejector doors were removed from the model. Acoustic studies showed far-field noise levels were higher for the HVC model with the ejector than for the baseline configuration. Results from Particle Image Velocimetry (PIV) studies indicated that large flow separation regions occurred along the ejector doors, thus restricting flow through the ejector. Phased array measurements showed noise sources located near the ejector doors for operating conditions where tones were present in the acoustic spectra.

An improved simulation based biomechanical model to estimate static muscle loadings

NASA Technical Reports Server (NTRS)

Rajulu, Sudhakar L.; Marras, William S.; Woolford, Barbara

1991-01-01

The objectives of this study are to show that the characteristics of an intact muscle are different from those of an isolated muscle and to describe a simulation based model. This model, unlike the optimization based models, accounts for the redundancy in the musculoskeletal system in predicting the amount of forces generated within a muscle. The results of this study show that the loading of the primary muscle is increased by the presence of other muscle activities. Hence, the previous models based on optimization techniques may underestimate the severity of the muscle and joint loadings which occur during manual material handling tasks.

Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values.

PubMed

Nicolas, Renaud; Sibon, Igor; Hiba, Bassem

2015-01-01

The diffusion-weighted-dependent attenuation of the MRI signal E(b) is extremely sensitive to microstructural features. The aim of this study was to determine which mathematical model of the E(b) signal most accurately describes it in the brain. The models compared were the monoexponential model, the stretched exponential model, the truncated cumulant expansion (TCE) model, the biexponential model, and the triexponential model. Acquisition was performed with nine b-values up to 2500 s/mm(2) in 12 healthy volunteers. The goodness-of-fit was studied with F-tests and with the Akaike information criterion. Tissue contrasts were differentiated with a multiple comparison corrected nonparametric analysis of variance. F-test showed that the TCE model was better than the biexponential model in gray and white matter. Corrected Akaike information criterion showed that the TCE model has the best accuracy and produced the most reliable contrasts in white matter among all models studied. In conclusion, the TCE model was found to be the best model to infer the microstructural properties of brain tissue.

"All in the Family" in Context: A Unified Model of Media Studies Applied to Television Criticism.

ERIC Educational Resources Information Center

Timberg, Bernard

Proposing the use of a single comprehensive communications model, the Circles of Context Model, for all forms of communication, this paper shows how the model can be used to identify different kinds of criticism of the television comedy series "All in the Family" and the ways in which that criticism shifted during the show's nine-year…

Estimating parameter values of a socio-hydrological flood model

NASA Astrophysics Data System (ADS)

Holkje Barendrecht, Marlies; Viglione, Alberto; Kreibich, Heidi; Vorogushyn, Sergiy; Merz, Bruno; Blöschl, Günter

2018-06-01

Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.

Quantitative structure activity relationship studies of piperazinyl phenylalanine derivatives as VLA-4/VCAM-1 inhibitors.

PubMed

Bhargava, Dinesh; Karthikeyan, C; Moorthy, N S H N; Trivedi, Piyush

2009-09-01

QSAR study was carried out for a series of piperazinyl phenylalanine derivatives exhibiting VLA-4/VCAM-1 inhibitory activity to find out the structural features responsible for the biological activity. The QSAR study was carried out on V-life Molecular Design Suite software and the derived best QSAR model by partial least square (forward) regression method showed 85.67% variation in biological activity. The statistically significant model with high correlation coefficient (r2=0.85) was selected for further study and the resulted validation parameters of the model, crossed squared correlation coefficient (q2=0.76 and pred_r2=0.42) show the model has good predictive ability. The model showed that the parameters SaaNEindex, SsClcount slogP,and 4PathCount are highly correlated with VLA-4/VCAM-1 inhibitory activity of piperazinyl phenylalanine derivatives. The result of the study suggests that the chlorine atoms in the molecule and fourth order fragmentation patterns in the molecular skeleton favour VLA-4/VCAM-1 inhibition shown by the title compounds whereas lipophilicity and nitrogen bonded to aromatic bond are not conducive for VLA-4/VCAM-1 inhibitory activity.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

ERIC Educational Resources Information Center

Lu, Yi

2016-01-01

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

NASA Astrophysics Data System (ADS)

Dukkipati, Ambedkar; Manathara, Joel George

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csisźar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Gröbner bases method to compute an implicit representation of minimum KL-divergence models.

Simulation model calibration and validation : phase II : development of implementation handbook and short course.

DOT National Transportation Integrated Search

2006-01-01

A previous study developed a procedure for microscopic simulation model calibration and validation and evaluated the procedure via two relatively simple case studies using three microscopic simulation models. Results showed that default parameters we...

Using Video Modeling to Increase Variation in the Conversation of Children with Autism

ERIC Educational Resources Information Center

Charlop, Marjorie H.; Gilmore, Laura; Chang, Gina T.

2009-01-01

The present study assessed the effects of video modeling on acquisition and generalization of variation in the conversational speech of two boys with autism. A video was made showing several versions of several topics of conversation, thus providing multiple exemplars of each conversation. Video modeling consisted of showing each child a video…

Modelling and validation land-atmospheric heat fluxes by using classical surface parameters over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Zhong, L.

2017-12-01

In this study, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in situ long-term CAMP/Tibet observations. Firstly our field observation sites will be introduced based on ITPCAS (Institute of Tibetan Plateau Research, Chinese Academy of Sciences). Then, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.

Psychometric Evaluation of the HIV Disclosure Belief Scale: A Rasch Model Approach.

PubMed

Hu, Jinxiang; Serovich, Julianne M; Chen, Yi-Hsin; Brown, Monique J; Kimberly, Judy A

2017-01-01

This study provides psychometric assessment of an HIV disclosure belief scale (DBS) among men who have sex with men (MSM). This study used baseline data from a clinical trial evaluating the effectiveness of an HIV serostatus disclosure intervention of 338 HIV-positive MSM. The Rasch model was used after unidimensionality and local independence assumptions were tested for application of the model. Results suggest that there was only one item that did not fit the model well. After removing the item, the DBS showed good model-data fit and high item and person reliabilities. This instrument showed measurement invariance across two different age groups, but some items showed differential item functioning between Caucasian and other minority groups. The findings suggest that the DBS is suitable for measuring the HIV disclosure beliefs, but it should be cautioned when the DBS is used to compare the disclosure beliefs between different racial/ethnic groups.

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

PubMed

Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

2015-03-01

A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

Studies of biaxial mechanical properties and nonlinear finite element modeling of skin.

PubMed

Shang, Xituan; Yen, Michael R T; Gaber, M Waleed

2010-06-01

The objective of this research is to conduct mechanical property studies of skin from two individual but potentially connected aspects. One is to determine the mechanical properties of the skin experimentally by biaxial tests, and the other is to use the finite element method to model the skin properties. Dynamic biaxial tests were performed on 16 pieces of abdominal skin specimen from rats. Typical biaxial stress-strain responses show that skin possesses anisotropy, nonlinearity and hysteresis. To describe the stress-strain relationship in forms of strain energy function, the material constants of each specimen were obtained and the results show a high correlation between theory and experiments. Based on the experimental results, a finite element model of skin was built to model the skin's special properties including anisotropy and nonlinearity. This model was based on Arruda and Boyce's eight-chain model and Bischoff et al.'s finite element model of skin. The simulation results show that the isotropic, nonlinear eight-chain model could predict the skin's anisotropic and nonlinear responses to biaxial loading by the presence of an anisotropic prestress state.

The Effects of Recycling and Response Sensitivity on the Acquisition of Social Studies Concepts.

ERIC Educational Resources Information Center

Ford, Mary Jane; McKinney, C. Warren

1986-01-01

Two studies are reported which investigate the concept learning of 116 sixth graders (study 1) and 107 second graders (study 2) depending on the model of concept presentation. Results showed no difference between the structured Merrill and Tennyson model and adaptations of the model which were responsive to student's questions or recycled missed…

Info-gap robust-satisficing model of foraging behavior: do foragers optimize or satisfice?

PubMed

Carmel, Yohay; Ben-Haim, Yakov

2005-11-01

In this note we compare two mathematical models of foraging that reflect two competing theories of animal behavior: optimizing and robust satisficing. The optimal-foraging model is based on the marginal value theorem (MVT). The robust-satisficing model developed here is an application of info-gap decision theory. The info-gap robust-satisficing model relates to the same circumstances described by the MVT. We show how these two alternatives translate into specific predictions that at some points are quite disparate. We test these alternative predictions against available data collected in numerous field studies with a large number of species from diverse taxonomic groups. We show that a large majority of studies appear to support the robust-satisficing model and reject the optimal-foraging model.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

A baseline-free procedure for transformation models under interval censorship.

PubMed

Gu, Ming Gao; Sun, Liuquan; Zuo, Guoxin

2005-12-01

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

Improved Model Fitting for the Empirical Green's Function Approach Using Hierarchical Models

NASA Astrophysics Data System (ADS)

Van Houtte, Chris; Denolle, Marine

2018-04-01

Stress drops calculated from source spectral studies currently show larger variability than what is implied by empirical ground motion models. One of the potential origins of the inflated variability is the simplified model-fitting techniques used in most source spectral studies. This study examines a variety of model-fitting methods and shows that the choice of method can explain some of the discrepancy. The preferred method is Bayesian hierarchical modeling, which can reduce bias, better quantify uncertainties, and allow additional effects to be resolved. Two case study earthquakes are examined, the 2016 MW7.1 Kumamoto, Japan earthquake and a MW5.3 aftershock of the 2016 MW7.8 Kaikōura earthquake. By using hierarchical models, the variation of the corner frequency, fc, and the falloff rate, n, across the focal sphere can be retrieved without overfitting the data. Other methods commonly used to calculate corner frequencies may give substantial biases. In particular, if fc was calculated for the Kumamoto earthquake using an ω-square model, the obtained fc could be twice as large as a realistic value.

Wavelet transform approach for fitting financial time series data

NASA Astrophysics Data System (ADS)

Ahmed, Amel Abdoullah; Ismail, Mohd Tahir

2015-10-01

This study investigates a newly developed technique; a combined wavelet filtering and VEC model, to study the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in daily data set of NASDAQ stock market of US, and three stock markets of Middle East and North Africa (MENA) region, namely, Egypt, Jordan, and Istanbul. The data covered is from 6/29/2001 to 5/5/2009. After that, the returns of generated series by wavelet filter and original series are analyzed by cointegration test and VEC model. The results show that the cointegration test affirms the existence of cointegration between the studied series, and there is a long-term relationship between the US, stock markets and MENA stock markets. A comparison between the proposed model and traditional model demonstrates that, the proposed model (DWT with VEC model) outperforms traditional model (VEC model) to fit the financial stock markets series well, and shows real information about these relationships among the stock markets.

Models Show Subsurface Cracking May Complicate Groundwater Cleanup at Hazardous Waste Sites

EPA Science Inventory

Chlorinated solvents like trichloroethylene contaminate groundwater at numerous sites nationwide. This modeling study, conducted at the Air Force Institute of Technology, shows that subsurface cracks, either natural or due to the presence of the contaminant itself, may result in...

Magneto-mechanical modeling of electrical steel sheets

NASA Astrophysics Data System (ADS)

Aydin, U.; Rasilo, P.; Martin, F.; Singh, D.; Daniel, L.; Belahcen, A.; Rekik, M.; Hubert, O.; Kouhia, R.; Arkkio, A.

2017-10-01

A simplified multiscale approach and a Helmholtz free energy based approach for modeling the magneto-mechanical behavior of electrical steel sheets are compared. The models are identified from uniaxial magneto-mechanical measurements of two different electrical steel sheets which show different magneto-elastic behavior. Comparison with the available measurement data of the materials shows that both models successfully model the magneto-mechanical behavior of one of the studied materials, whereas for the second material only the Helmholtz free energy based approach is successful.

A Simulation Model for Procedure Inference from a Mental Model for a Simple Device.

DTIC Science & Technology

1984-05-25

can flow to, and the indicator lights show where the power is present. According to these results, the critical information is the system topology...show the flow of power into the energon storage system. Maintenance of a collapsed energon ring requires a supply of vector bosons which is...model; in some tasks there is clearly no effect. The device model in that study was developed intuitivIy. But upon examining the model in light of the

Alcohol cold starting - A theoretical study

NASA Technical Reports Server (NTRS)

Browning, L. H.

1983-01-01

Two theoretical computer models have been developed to study cold starting problems with alcohol fuels. The first model, a droplet fall-out and sling-out model, shows that droplets must be smaller than 50 microns to enter the cylinder under cranking conditions without being slung-out in the intake manifold. The second model, which examines the fate of droplets during the compression process, shows that the heat of compression can be used to vaporize small droplets (less than 50 microns) producing flammable mixtures below freezing ambient temperatures. While droplet size has the greater effect on startability, a very high compression ratio can also aid cold starting.

The Challenge of Simulating the Regional Climate over Florida

NASA Astrophysics Data System (ADS)

Misra, V.; Mishra, A. K.

2015-12-01

In this study we show that the unique geography of the peninsular Florida with close proximity to strong mesoscale surface ocean currents among other factors warrants the use of relatively high resolution climate models to project Florida's hydroclimate. In the absence of such high resolution climate models we highlight the deficiencies of two relatively coarse spatial resolution CMIP5 models with respect to the warm western boundary current of the Gulf Stream. As a consequence it affects the coastal SST and the land-ocean contrast, affecting the rainy summer seasonal precipitation accumulation over peninsular Florida. We also show this through two sensitivity studies conducted with a regional coupled ocean atmosphere model with different bathymetries that dislocate and modulate the strength of the Gulf Stream that locally affects the SST in the two simulations. These studies show that a stronger and more easterly displaced Gulf Stream produces warmer coastal SST's along the Atlantic coast of Florida that enhances the precipitation over peninsular Florida relative to the other regional climate model simulation. However the regional model simulations indicate that variability of wet season rainfall variability in peninsular Florida becomes less dependent on the land-ocean contrast with a stronger Gulf Stream current.

Comparison of Virulence of Legionella longbeachae Strains in Guinea Pigs and U937 Macrophage-Like Cells

PubMed Central

Doyle, Robyn M.; Cianciotto, Nicholas P.; Banvi, Shaila; Manning, Paul A.; Heuzenroeder, Michael W.

2001-01-01

A guinea pig model of experimental legionellosis was established for assessment of virulence of isolates of Legionella longbeachae. The results showed that there were distinct virulence groupings of L. longbeachae serogroup 1 strains based on the severity of disease produced in this model. Statistical analysis of the animal model data suggests that Australian isolates of L. longbeachae may be inherently more virulent than non-Australian strains. Infection studies performed with U937 cells were consistent with the animal model studies and showed that isolates of this species were capable of multiplying within these phagocytic cells. Electron microscopy studies of infected lung tissue were also undertaken to determine the intracellular nature of L. longbeachae serogroup 1 infection. The data showed that phagosomes containing virulent L. longbeachae serogroup 1 appeared bloated, contained cellular debris and had an apparent rim of ribosomes while those containing avirulent L. longbeachae serogroup 1 were compact, clear and smooth. PMID:11500403

Reconnection in the Martian Magnetotail: Hall-MHD With Embedded Particle-in-Cell Simulations

NASA Astrophysics Data System (ADS)

Ma, Yingjuan; Russell, Christopher T.; Toth, Gabor; Chen, Yuxi; Nagy, Andrew F.; Harada, Yuki; McFadden, James; Halekas, Jasper S.; Lillis, Rob; Connerney, John E. P.; Espley, Jared; DiBraccio, Gina A.; Markidis, Stefano; Peng, Ivy Bo; Fang, Xiaohua; Jakosky, Bruce M.

2018-05-01

Mars Atmosphere and Volatile EvolutioN (MAVEN) mission observations show clear evidence of the occurrence of the magnetic reconnection process in the Martian plasma tail. In this study, we use sophisticated numerical models to help us understand the effects of magnetic reconnection in the plasma tail. The numerical models used in this study are (a) a multispecies global Hall-magnetohydrodynamic (HMHD) model and (b) a global HMHD model two-way coupled to an embedded fully kinetic particle-in-cell code. Comparison with MAVEN observations clearly shows that the general interaction pattern is well reproduced by the global HMHD model. The coupled model takes advantage of both the efficiency of the MHD model and the ability to incorporate kinetic processes of the particle-in-cell model, making it feasible to conduct kinetic simulations for Mars under realistic solar wind conditions for the first time. Results from the coupled model show that the Martian magnetotail is highly dynamic due to magnetic reconnection, and the resulting Mars-ward plasma flow velocities are significantly higher for the lighter ion fluid, which are quantitatively consistent with MAVEN observations. The HMHD with Embedded Particle-in-Cell model predicts that the ion loss rates are more variable but with similar mean values as compared with HMHD model results.

Empirical validation of an agent-based model of wood markets in Switzerland

PubMed Central

Hilty, Lorenz M.; Lemm, Renato; Thees, Oliver

2018-01-01

We present an agent-based model of wood markets and show our efforts to validate this model using empirical data from different sources, including interviews, workshops, experiments, and official statistics. Own surveys closed gaps where data was not available. Our approach to model validation used a variety of techniques, including the replication of historical production amounts, prices, and survey results, as well as a historical case study of a large sawmill entering the market and becoming insolvent only a few years later. Validating the model using this case provided additional insights, showing how the model can be used to simulate scenarios of resource availability and resource allocation. We conclude that the outcome of the rigorous validation qualifies the model to simulate scenarios concerning resource availability and allocation in our study region. PMID:29351300

Numerical simulation of terrain-induced mesoscale circulation in the Chiang Mai area, Thailand

NASA Astrophysics Data System (ADS)

Sathitkunarat, Surachai; Wongwises, Prungchan; Pan-Aram, Rudklao; Zhang, Meigen

2008-11-01

The regional atmospheric modeling system (RAMS) was applied to Chiang Mai province, a mountainous area in Thailand, to study terrain-induced mesoscale circulations. Eight cases in wet and dry seasons under different weather conditions were analyzed to show thermal and dynamic impacts on local circulations. This is the first study of RAMS in Thailand especially investigating the effect of mountainous area on the simulated meteorological data. Analysis of model results indicates that the model can reproduce major features of local circulation and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction, and temperature monitored at a meteorological tower. Comparison shows that the modeled values are generally in good agreement with observations and that the model captured many of the observed features.

A comprehensive adsorption study and modeling of antibiotics as a pharmaceutical waste by graphene oxide nanosheets.

PubMed

Rostamian, Rahele; Behnejad, Hassan

2018-01-01

The adsorption behavior of tetracycline (TCN), doxycycline (DCN) as the most common antibiotics in veterinary and ciprofloxacin (CPN) onto graphene oxide nanosheets (GOS) in aqueous solution was evaluated. The four factors influencing the adsorption of antibiotics (initial concentration, pH, temperature and contact time) were studied. The results showed that initial pH ∼ 6 to 7 and contact time ∼ 100 - 200min are optimum for each drug. The monolayer adsorption capacity was reduced with the increasing temperature from 25°C to 45°C. Non-linear regressions were carried out in order to define the best fit model for every system. To do this, eight error functions were applied to predict the optimum model. Among various models, Hill and Toth isotherm models represented the equilibrium adsorption data of antibiotics while the kinetic data were well fitted by pseudo second-order (PSO) kinetic model (DCN and TCN) and Elovich (CPN) models. The maximum adsorption capacity (q max ) is found to be in the following order: CPN > DCN > TCN, obtained from sips equation at the same temperature. The GOS shows highest adsorption capacity towards CPN up to 173.4mgg -1 . The study showed that GOS can be removed more efficiently from water solution. Copyright © 2017 Elsevier Inc. All rights reserved.

A novel approach for inventory problem in the pharmaceutical supply chain.

PubMed

Candan, Gökçe; Yazgan, Harun Reşit

2016-02-24

In pharmaceutical enterprises, keeping up with global market conditions is possible with properly selected supply chain management policies. Generally; demand-driven classical supply chain model is used in the pharmaceutical industry. In this study, a new mathematical model is developed to solve an inventory problem in the pharmaceutical supply chain. Unlike the studies in literature, the "shelf life and product transition times" constraints are considered, simultaneously, first time in the pharmaceutical production inventory problem. The problem is formulated as a mixed-integer linear programming (MILP) model with a hybrid time representation. The objective is to maximize total net profit. Effectiveness of the proposed model is illustrated considering a classical and a vendor managed inventory (VMI) supply chain on an experimental study. To show the effectiveness of the model, an experimental study is performed; which contains 2 different supply chain policy (Classical and VMI), 24 and 30 months planning horizon, 10 and 15 different cephalosporin products. Finally the mathematical model is compared to another model in literature and the results show that proposed model is superior. This study suggest a novel approach for solving pharmaceutical inventory problem. The developed model is maximizing total net profit while determining optimal production plan under shelf life and product transition constraints in the pharmaceutical industry. And we believe that the proposed model is much more closed to real life unlike the other studies in literature.

Sensitivity studies and a simple ozone perturbation experiment with a truncated two-dimensional model of the stratosphere

NASA Technical Reports Server (NTRS)

Stordal, Frode; Garcia, Rolando R.

1987-01-01

The 1-1/2-D model of Holton (1986), which is actually a highly truncated two-dimensional model, describes latitudinal variations of tracer mixing ratios in terms of their projections onto second-order Legendre polynomials. The present study extends the work of Holton by including tracers with photochemical production in the stratosphere (O3 and NOy). It also includes latitudinal variations in the photochemical sources and sinks, improving slightly the calculated global mean profiles for the long-lived tracers studied by Holton and improving substantially the latitudinal behavior of ozone. Sensitivity tests of the dynamical parameters in the model are performed, showing that the response of the model to changes in vertical residual meridional winds and horizontal diffusion coefficients is similar to that of a full two-dimensional model. A simple ozone perturbation experiment shows the model's ability to reproduce large-scale latitudinal variations in total ozone column depletions as well as ozone changes in the chemically controlled upper stratosphere.

Interaction of actin filaments with the plasma membrane in Amoeba proteus: studies using a cell model and isolated plasma membrane.

PubMed

Kawakatsu, T; Kikuchi, A; Shimmen, T; Sonobe, S

2000-08-01

We prepared a cell model of Amoeba proteus by mechanical bursting to study the interaction between actin filaments (AFs) and plasma membrane (PM). The cell model prepared in the absence of Ca2+ showed remarkable contraction upon addition of ATP. When the model was prepared in the presence of Ca2+, the cytoplasmic granules formed an aggregate in the central region, having moved away from PM. Although this model showed contraction upon addition of ATP in the presence of Ca2+, less contraction was noted. Staining with rhodamine-phalloidin revealed association of AFs with PM in the former model, and a lesser amount of association in the latter model. The interaction between AFs and PM was also studied using the isolated PM. AFs were associated with PM isolated in the absence of Ca2+, but were not when Ca2+ was present. These results suggest that the interaction between AFs and PM is regulated by Ca2+.

Estimating daily global solar radiation by day of the year in Algeria

NASA Astrophysics Data System (ADS)

Aoun, Nouar; Bouchouicha, Kada

2017-05-01

This study presents six empirical models based on the day-of-the-year number for estimating global solar radiation on a horizontal surface. For this case study, 21 years of experimental data sets for 21 cities over the whole Algerian territory are utilized to develop these models for each city and for all of Algeria. In this study, the territory of Algeria was divided into four different climatic zones, i.e., Arid, Semi-arid, Highlands and Mediterranean. The accuracy of the all-Algeria model was tested for each city and for each climate zone. To evaluate the accuracy of the models, the RMSE, rRMSE, MABE, MAPE, and R, which are the most commonly applied statistical parameters, were utilized. The results show that the six developed models provide excellent predictions for global solar radiation for each city and for all-Algeria. Furthermore, the model showing the greatest accuracy is the sine and cosine wave trigonometric model.

Mesoscopic modeling of DNA denaturation rates: Sequence dependence and experimental comparison

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

Dahlen, Oda, E-mail: oda.dahlen@ntnu.no; Erp, Titus S. van, E-mail: titus.van.erp@ntnu.no

Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimentalmore » data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones.« less

Gait kinematics of subjects with ankle instability using a multisegmented foot model.

PubMed

De Ridder, Roel; Willems, Tine; Vanrenterghem, Jos; Robinson, Mark; Pataky, Todd; Roosen, Philip

2013-11-01

Many patients who sustain an acute lateral ankle sprain develop chronic ankle instability (CAI). Altered ankle kinematics have been reported to play a role in the underlying mechanisms of CAI. In previous studies, however, the foot was modeled as one rigid segment, ignoring the complexity of the ankle and foot anatomy and kinematics. The purpose of this study was to evaluate stance phase kinematics of subjects with CAI, copers, and controls during walking and running using both a rigid and a multisegmented foot model. Foot and ankle kinematics of 77 subjects (29 subjects with self-reported CAI, 24 copers, and 24 controls) were measured during barefoot walking and running using a rigid foot model and a six-segment Ghent Foot Model. Data were collected on a 20-m-long instrumented runway embedded with a force plate and a six-camera optoelectronic system. Groups were compared using statistical parametric mapping. Both the CAI and the coper group showed similar differences during midstance and late stance compared with the control group (P < 0.05). The rigid foot segment showed a more everted position during walking compared with the control group. Based on the Ghent Foot Model, the rear foot also showed a more everted position during running. The medial forefoot showed a more inverted position for both running and walking compared with the control group. Our study revealed significant midstance and late stance differences in rigid foot, rear foot, and medial forefoot kinematics The multisegmented foot model demonstrated intricate behavior of the foot that is not detectable with rigid foot modeling. Further research using these models is necessary to expand knowledge of foot kinematics in subjects with CAI.

Multiple commodities in statistical microeconomics: Model and market

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

Psychosocial work environment and myocardial infarction: improving risk estimation by combining two complementary job stress models in the SHEEP Study

PubMed Central

Peter, R; Siegrist, J; Hallqvist, J; Reuterwall, C; Theorell, T

2002-01-01

Objectives: Associations between two alternative formulations of job stress derived from the effort-reward imbalance and the job strain model and first non-fatal acute myocardial infarction were studied. Whereas the job strain model concentrates on situational (extrinsic) characteristics the effort-reward imbalance model analyses distinct person (intrinsic) characteristics in addition to situational ones. In view of these conceptual differences the hypothesis was tested that combining information from the two models improves the risk estimation of acute myocardial infarction. Methods: 951 male and female myocardial infarction cases and 1147 referents aged 45–64 years of The Stockholm Heart Epidemiology (SHEEP) case-control study underwent a clinical examination. Information on job stress and health adverse behaviours was derived from standardised questionnaires. Results: Multivariate analysis showed moderately increased odds ratios for either model. Yet, with respect to the effort-reward imbalance model gender specific effects were found: in men the extrinsic component contributed to risk estimation, whereas this was the case with the intrinsic component in women. Controlling each job stress model for the other in order to test the independent effect of either approach did not show systematically increased odds ratios. An improved estimation of acute myocardial infarction risk resulted from combining information from the two models by defining groups characterised by simultaneous exposure to effort-reward imbalance and job strain (men: odds ratio 2.02 (95% confidence intervals (CI) 1.34 to 3.07); women odds ratio 2.19 (95% CI 1.11 to 4.28)). Conclusions: Findings show an improved risk estimation of acute myocardial infarction by combining information from the two job stress models under study. Moreover, gender specific effects of the two components of the effort-reward imbalance model were observed. PMID:11896138

Transition mixing study empirical model report

NASA Technical Reports Server (NTRS)

Srinivasan, R.; White, C.

1988-01-01

The empirical model developed in the NASA Dilution Jet Mixing Program has been extended to include the curvature effects of transition liners. This extension is based on the results of a 3-D numerical model generated under this contract. The empirical model results agree well with the numerical model results for all tests cases evaluated. The empirical model shows faster mixing rates compared to the numerical model. Both models show drift of jets toward the inner wall of a turning duct. The structure of the jets from the inner wall does not exhibit the familiar kidney-shaped structures observed for the outer wall jets or for jets injected in rectangular ducts.

Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model

NASA Astrophysics Data System (ADS)

Jiménez-Esteve, B.; Udina, M.; Soler, M. R.; Pepin, N.; Miró, J. R.

2018-04-01

Different types of land use (LU) have different physical properties which can change local energy balance and hence vertical fluxes of moisture, heat and momentum. This in turn leads to changes in near-surface temperature and moisture fields. Simulating atmospheric flow over complex terrain requires accurate local-scale energy balance and therefore model grid spacing must be sufficient to represent both topography and land-use. In this study we use both the Corine Land Cover (CLC) and United States Geological Survey (USGS) land use databases for use with the Weather Research and Forecasting (WRF) model and evaluate the importance of both land-use classification and horizontal resolution in contributing to successful modelling of surface temperatures and humidities observed from a network of 39 sensors over a 9 day period in summer 2013. We examine case studies of the effects of thermal inertia and soil moisture availability at individual locations. The scale at which the LU classification is observed influences the success of the model in reproducing observed patterns of temperature and moisture. Statistical validation of model output demonstrates model sensitivity to both the choice of LU database used and the horizontal resolution. In general, results show that on average, by a) using CLC instead of USGS and/or b) increasing horizontal resolution, model performance is improved. We also show that the sensitivity to these changes in the model performance shows a daily cycle.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

Hierarchical lattice models of hydrogen-bond networks in water

NASA Astrophysics Data System (ADS)

Dandekar, Rahul; Hassanali, Ali A.

2018-06-01

We develop a graph-based model of the hydrogen-bond network in water, with a view toward quantitatively modeling the molecular-level correlational structure of the network. The networks formed are studied by the constructing the model on two infinite-dimensional lattices. Our models are built bottom up, based on microscopic information coming from atomistic simulations, and we show that the predictions of the model are consistent with known results from ab initio simulations of liquid water. We show that simple entropic models can predict the correlations and clustering of local-coordination defects around tetrahedral waters observed in the atomistic simulations. We also find that orientational correlations between bonds are longer ranged than density correlations, determine the directional correlations within closed loops, and show that the patterns of water wires within these structures are also consistent with previous atomistic simulations. Our models show the existence of density and compressibility anomalies, as seen in the real liquid, and the phase diagram of these models is consistent with the singularity-free scenario previously proposed by Sastry and coworkers [Phys. Rev. E 53, 6144 (1996), 10.1103/PhysRevE.53.6144].

Deletion of Sarm1 gene is neuroprotective in two models of peripheral neuropathy.

PubMed

Turkiew, Elliot; Falconer, Debbie; Reed, Nicole; Höke, Ahmet

2017-09-01

Distal axon degeneration seen in many peripheral neuropathies is likely to share common molecular mechanisms with Wallerian degeneration. Although several studies in mouse models of peripheral neuropathy showed prevention of axon degeneration in the slow Wallerian degeneration (Wlds) mouse, the role of a recently identified player in Wallerian degeneration, Sarm1, has not been explored extensively. In this study, we show that mice lacking the Sarm1 gene are resistant to distal axonal degeneration in a model of chemotherapy induced peripheral neuropathy caused by paclitaxel and a model of high fat diet induced putative metabolic neuropathy. This study extends the role of Sarm1 to axon degeneration seen in peripheral neuropathies and identifies it as a likely target for therapeutic development. © 2017 Peripheral Nerve Society.

Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality.

PubMed

Tomperi, Jani; Leiviskä, Kauko

2018-06-01

Traditionally the modelling in an activated sludge process has been based on solely the process measurements, but as the interest to optically monitor wastewater samples to characterize the floc morphology has increased, in the recent years the results of image analyses have been more frequently utilized to predict the characteristics of wastewater. This study shows that the traditional process measurements or the automated optical monitoring variables by themselves are not capable of developing the best predictive models for the treated wastewater quality in a full-scale wastewater treatment plant, but utilizing these variables together the optimal models, which show the level and changes in the treated wastewater quality, are achieved. By this early warning, process operation can be optimized to avoid environmental damages and economic losses. The study also shows that specific optical monitoring variables are important in modelling a certain quality parameter, regardless of the other input variables available.

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model

PubMed Central

Choi, Soe Yoon; Venetis, Maria K.; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G.; Banerjee, Smita C.

2016-01-01

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed. PMID:27662447

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model.

PubMed

Choi, Soe Yoon; Venetis, Maria K; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G; Banerjee, Smita C

2016-11-16

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed.

Loading Deformation Characteristic Simulation Study of Engineering Vehicle Refurbished Tire

NASA Astrophysics Data System (ADS)

Qiang, Wang; Xiaojie, Qi; Zhao, Yang; Yunlong, Wang; Guotian, Wang; Degang, Lv

2018-05-01

The paper constructed engineering vehicle refurbished tire computer geometry model, mechanics model, contact model, finite element analysis model, did simulation study on load-deformation property of engineering vehicle refurbished tire by comparing with that of the new and the same type tire, got load-deformation of engineering vehicle refurbished tire under the working condition of static state and ground contact. The analysis result shows that change rules of radial-direction deformation and side-direction deformation of engineering vehicle refurbished tire are close to that of the new tire, radial-direction and side-direction deformation value is a little less than that of the new tire. When air inflation pressure was certain, radial-direction deformation linear rule of engineer vehicle refurbished tire would increase with load adding, however, side-direction deformation showed linear change rule, when air inflation pressure was low; and it would show increase of non-linear change rule, when air inflation pressure was very high.

A data-driven model for influenza transmission incorporating media effects.

PubMed

Mitchell, Lewis; Ross, Joshua V

2016-10-01

Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of 'big data' coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.

Informations in Models of Evolutionary Dynamics

NASA Astrophysics Data System (ADS)

Rivoire, Olivier

2016-03-01

Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.

Flocking of the Motsch-Tadmor Model with a Cut-Off Interaction Function

NASA Astrophysics Data System (ADS)

Jin, Chunyin

2018-04-01

In this paper, we study the flocking behavior of the Motsch-Tadmor model with a cut-off interaction function. Our analysis shows that connectedness is important for flocking of this kind of model. Fortunately, we get a sufficient condition imposed only on the model parameters and initial data to guarantee the connectedness of the neighbor graph associated with the system. Then we present a theoretical analysis for flocking, and show that the system achieves consensus at an exponential rate.

A Multidimensional Model of School Dropout from an 8-Year Longitudinal Study in a General High School Population

ERIC Educational Resources Information Center

Fortin, Laurier; Marcotte, Diane; Diallo, Thierno; Potvin, Pierre; Royer, Egide

2013-01-01

This study tests an empirical multidimensional model of school dropout, using data collected in the first year of an 8-year longitudinal study, with first year high school students aged 12-13 years. Structural equation modeling analyses show that five personal, family, and school latent factors together contribute to school dropout identified at…

Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

PubMed Central

Crawford, Alasdair O.; Hamerton, Ian; Cavalli, Gabriel; Howlin, Brendan J.

2012-01-01

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties. PMID:22970230

Turbulence Model Comparisons for Supersonic Transports at Transonic and Supersonic Conditions

NASA Technical Reports Server (NTRS)

Rivers, S. M. B.; Wahls, R. A.

2003-01-01

Results of turbulence model comparisons from two studies on supersonic transport configurations performed during the NASA High-speed Research program are given. Results are presented for both transonic conditions at Mach 0.90 and supersonic conditions at Mach 2.48. A feature of these two studies was the availability of higher Reynolds number wind tunnel data with which to compare the computational results. The transonic wind tunnel data was obtained in the National Transonic Facility at NASA Langley, and the supersonic data was obtained in the Boeing Polysonic Wind Tunnel. The computational data was acquired using a state of the art Navier-Stokes flow solver with a wide range of turbulence models implemented. The results show that the computed forces compare reasonably well with the experimental data, with the Baldwin- Lomax with Degani-Schiff modifications and the Baldwin-Barth models showing the best agreement for the transonic conditions and the Spalart-Allmaras model showing the best agreement for the supersonic conditions. The transonic results were more sensitive to the choice of turbulence model than were the supersonic results.

Gas Hydrate Estimation Using Rock Physics Modeling and Seismic Inversion

NASA Astrophysics Data System (ADS)

Dai, J.; Dutta, N.; Xu, H.

2006-05-01

ABSTRACT We conducted a theoretical study of the effects of gas hydrate saturation on the acoustic properties (P- and S- wave velocities, and bulk density) of host rocks, using wireline log data from the Mallik wells in the Mackenzie Delta in Northern Canada. We evaluated a number of gas hydrate rock physics models that correspond to different rock textures. Our study shows that, among the existing rock physics models, the one that treats gas hydrate as part of the solid matrix best fits the measured data. This model was also tested on gas hydrate hole 995B of ODP leg 164 drilling at Blake Ridge, which shows adequate match. Based on the understanding of rock models of gas hydrates and properties of shallow sediments, we define a procedure that quantifies gas hydrate using rock physics modeling and seismic inversion. The method allows us to estimate gas hydrate directly from seismic information only. This paper will show examples of gas hydrates quantification from both 1D profile and 3D volume in the deepwater of Gulf of Mexico.

Hydra effects in discrete-time models of stable communities.

PubMed

Cortez, Michael H

2016-12-21

A species exhibits a hydra effect when, counter-intuitively, increased mortality of the species causes an increase in its abundance. Hydra effects have been studied in many continuous time (differential equation) multispecies models, but only rarely have hydra effects been observed in or studied with discrete time (difference equation) multispecies models. In addition most discrete time theory focuses on single-species models. Thus, it is unclear what unifying characteristics determine when hydra effects arise in discrete time models. Here, using discrete time multispecies models (where total abundance is the single variable describing each population), I show that a species exhibits a hydra effect in a stable system only when fixing that species' density at its equilibrium density destabilizes the system. This general characteristic is referred to as subsystem instability. I apply this result to two-species models and identify specific mechanisms that cause hydra effects in stable communities, e.g., in host--parasitoid models, host Allee effects and saturating parasitoid functional responses can cause parasitoid hydra effects. I discuss how the general characteristic can be used to identify mechanisms causing hydra effects in communities with three or more species. I also show that the condition for hydra effects at stable equilibria implies the system is reactive (i.e., density perturbations can grow before ultimately declining). This study extends previous work on conditions for hydra effects in single-species models by identifying necessary conditions for stable systems and sufficient conditions for cyclic systems. In total, these results show that hydra effects can arise in many more communities than previously appreciated and that hydra effects were present, but unrecognized, in previously studied discrete time models. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Ab Initio Exciton Model Including Charge-Transfer Excited States

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

Li, Xin; Parrish, Robert M.; Liu, Fang

Here, the Frenkel exciton model is a useful tool for theoretical studies of multichromophore systems. We recently showed that the exciton model could be used to coarse-grain electronic structure in multichromophoric systems, focusing on singly excited exciton states. However, our previous implementation excluded charge-transfer excited states, which can play an important role in light-harvesting systems and near-infrared optoelectronic materials. Recent studies have also emphasized the significance of charge-transfer in singlet fission, which mediates the coupling between the locally excited states and the multiexcitonic states. In this work, we report on an ab initio exciton model that incorporates charge-transfer excited statesmore » and demonstrate that the model provides correct charge-transfer excitation energies and asymptotic behavior. Comparison with TDDFT and EOM-CC2 calculations shows that our exciton model is robust with respect to system size, screening parameter, and different density functionals. Inclusion of charge-transfer excited states makes the exciton model more useful for studies of singly excited states and provides a starting point for future construction of a model that also includes double-exciton states.« less

An Ab Initio Exciton Model Including Charge-Transfer Excited States

DOE PAGES

Li, Xin; Parrish, Robert M.; Liu, Fang; ...

2017-06-15

Here, the Frenkel exciton model is a useful tool for theoretical studies of multichromophore systems. We recently showed that the exciton model could be used to coarse-grain electronic structure in multichromophoric systems, focusing on singly excited exciton states. However, our previous implementation excluded charge-transfer excited states, which can play an important role in light-harvesting systems and near-infrared optoelectronic materials. Recent studies have also emphasized the significance of charge-transfer in singlet fission, which mediates the coupling between the locally excited states and the multiexcitonic states. In this work, we report on an ab initio exciton model that incorporates charge-transfer excited statesmore » and demonstrate that the model provides correct charge-transfer excitation energies and asymptotic behavior. Comparison with TDDFT and EOM-CC2 calculations shows that our exciton model is robust with respect to system size, screening parameter, and different density functionals. Inclusion of charge-transfer excited states makes the exciton model more useful for studies of singly excited states and provides a starting point for future construction of a model that also includes double-exciton states.« less

A cluster expansion model for predicting activation barrier of atomic processes

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

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit, E-mail: achatter@iitk.ac.in

2013-06-15

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEBmore » results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.« less

An Ab Initio Exciton Model Including Charge-Transfer Excited States.

PubMed

Li, Xin; Parrish, Robert M; Liu, Fang; Kokkila Schumacher, Sara I L; Martínez, Todd J

2017-08-08

The Frenkel exciton model is a useful tool for theoretical studies of multichromophore systems. We recently showed that the exciton model could be used to coarse-grain electronic structure in multichromophoric systems, focusing on singly excited exciton states [ Acc. Chem. Res. 2014 , 47 , 2857 - 2866 ]. However, our previous implementation excluded charge-transfer excited states, which can play an important role in light-harvesting systems and near-infrared optoelectronic materials. Recent studies have also emphasized the significance of charge-transfer in singlet fission, which mediates the coupling between the locally excited states and the multiexcitonic states. In this work, we report on an ab initio exciton model that incorporates charge-transfer excited states and demonstrate that the model provides correct charge-transfer excitation energies and asymptotic behavior. Comparison with TDDFT and EOM-CC2 calculations shows that our exciton model is robust with respect to system size, screening parameter, and different density functionals. Inclusion of charge-transfer excited states makes the exciton model more useful for studies of singly excited states and provides a starting point for future construction of a model that also includes double-exciton states.

Herding, minority game, market clearing and efficient markets in a simple spin model framework

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav; Vosvrda, Miloslav

2018-01-01

We present a novel approach towards the financial Ising model. Most studies utilize the model to find settings which generate returns closely mimicking the financial stylized facts such as fat tails, volatility clustering and persistence, and others. We tackle the model utility from the other side and look for the combination of parameters which yields return dynamics of the efficient market in the view of the efficient market hypothesis. Working with the Ising model, we are able to present nicely interpretable results as the model is based on only two parameters. Apart from showing the results of our simulation study, we offer a new interpretation of the Ising model parameters via inverse temperature and entropy. We show that in fact market frictions (to a certain level) and herding behavior of the market participants do not go against market efficiency but what is more, they are needed for the markets to be efficient.

Tall sections from non-minimal transformations

DOE PAGES

Morrison, David R.; Park, Daniel S.

2016-10-10

In previous study, we have shown that elliptic fibrations with two sections, or Mordell-Weil rank one, can always be mapped birationally to a Weierstrass model of a certain form, namely, the Jacobian of a P 112 model. Most constructions of elliptically fibered Calabi-Yau manifolds with two sections have been carried out assuming that the image of this birational map was a “minimal” Weierstrass model. In this paper, we show that for some elliptically fibered Calabi-Yau manifolds with Mordell-Weil rank-one, the Jacobian of the P 112 model is not minimal. Said another way, starting from a Calabi-Yau Weierstrass model, the totalmore » space must be blown up (thereby destroying the “Calabi-Yau” property) in order to embed the model into P 112. In particular, we show that the elliptic fibrations studied recently by Klevers and Taylor fall into this class of models.« less

Studying the Immunomodulatory Effects of Small Molecule Ras Inhibitors in Animal Models of Rheumatoid Arthritis

DTIC Science & Technology

2017-10-01

methotrexate (MTX) provides a superior protective effect compared to monotherapy. (iii) In the AIA model the FTS derivative, F-FTS, showed higher...therapeutic efficacy compared to FTS. (iv) The functional genomics studies showed that FTS therapy inhibits the in vivo TH17 immune response. (v) FTS semi... Description shall include pertinent data and graphs in sufficient detail to explain any significant results achieved. A succinct description of the

Note on the coefficient of variations of neuronal spike trains.

PubMed

Lengler, Johannes; Steger, Angelika

2017-08-01

It is known that many neurons in the brain show spike trains with a coefficient of variation (CV) of the interspike times of approximately 1, thus resembling the properties of Poisson spike trains. Computational studies have been able to reproduce this phenomenon. However, the underlying models were too complex to be examined analytically. In this paper, we offer a simple model that shows the same effect but is accessible to an analytic treatment. The model is a random walk model with a reflecting barrier; we give explicit formulas for the CV in the regime of excess inhibition. We also analyze the effect of probabilistic synapses in our model and show that it resembles previous findings that were obtained by simulation.

A hierarchical (multicomponent) model of in-group identification: examining in Russian samples.

PubMed

Lovakov, Andrey V; Agadullina, Elena R; Osin, Evgeny N

2015-06-03

The aim of this study was to examine the validity and reliability of Leach et al.'s (2008) model of in-group identification in two studies using Russian samples (overall N = 621). In Study 1, a series of multi-group confirmatory factor analysis revealed that the hierarchical model of in-group identification, which included two second-order factors, self-definition (individual self-stereotyping, and in-group homogeneity) and self-investment (satisfaction, solidarity, and centrality), fitted the data well for all four group identities (ethnic, religious, university, and gender) (CFI > .93, TLI > .92, RMSEA < .06, SRMR < .06) and demonstrated a better fit, compared to the alternative models. In Study 2, the construct validity and reliability of the Russian version of the in-group identification measure was examined. Results show that these measures have adequate psychometric properties. In short, our results show that Leach et al.'s model is reproduced in Russian culture. The Russian version of this measure can be recommended for use in future in-group research in Russian-speaking samples.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

PubMed Central

Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong

2016-01-01

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

PubMed

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

PubMed Central

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability. PMID:26941699

Projections of annual rainfall and surface temperature from CMIP5 models over the BIMSTEC countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Dalal, Mamta; Pattnayak, R. K.

2017-05-01

Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) comprising Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand brings together 21% of the world population. Thus the impact of climate change in this region is a major concern for all. To study the climate change, fifth phase of Climate Model Inter-comparison Project (CMIP5) models have been used to project the climate for the 21st century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 over the BIMSTEC countries for the period 1901 to 2100 (initial 105 years are historical period and the later 95 years are projected period). Climate change in the projected period has been examined with respect to the historical period. In order to validate the models, the mean annual rainfall has been compared with observations from multiple sources and temperature has been compared with the data from Climatic Research Unit (CRU) during the historical period. Comparison reveals that ensemble mean of the models is able to represent the observed spatial distribution of rainfall and temperature over the BIMSTEC countries. Therefore, data from these models may be used to study the future changes in the 21st century. Four out of six models show that the rainfall over India, Thailand and Myanmar has decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka show an increasing trend in both the RCP scenarios. In case of temperature, all the models show an increasing trend over all the BIMSTEC countries in both the scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. The rate of increase/decrease in rainfall and temperature are relatively more in RCP8.5 than RCP4.5 over all these countries. Inter-model comparison show that there are uncertainties within the CMIP5 model projections. More similar studies are required to be done for better understanding the model uncertainties in climate projections over this region.

Factors affecting yearly and monthly visits to Taipei Zoo

NASA Astrophysics Data System (ADS)

Su, Ai-Tsen; Lin, Yann-Jou

2018-02-01

This study investigated factors affecting yearly and monthly numbers of visits to Taipei Zoo. Both linear and nonlinear regression models were used to estimate yearly visits. The results of both models showed that the "opening effect" and "animal star effect" had a significantly positive effect on yearly visits, while a SARS outbreak had a negative effect. The number of years had a significant influence on yearly visits. Results showed that the nonlinear model had better explanatory power and fitted the variations of visits better. Results of monthly model showed that monthly visits were significantly influenced by time fluctuations, weather conditions, and the animal star effect. Chinese New Year, summer vacation, numbers of holidays, and animal star exhibitions increased the number of monthly visits, while the number of days with temperatures at or below 15 °C, the number of days with temperatures at or above 30 °C, and the number of rainy days had significantly negative effects. Furthermore, the model of monthly visits showed that the animal star effect could last for over two quarters. The results of this study clarify the factors affecting visits to an outdoor recreation site and confirm the importance of meteorological factors to recreation use.

Piecewise Polynomial Aggregation as Preprocessing for Data Numerical Modeling

NASA Astrophysics Data System (ADS)

Dobronets, B. S.; Popova, O. A.

2018-05-01

Data aggregation issues for numerical modeling are reviewed in the present study. The authors discuss data aggregation procedures as preprocessing for subsequent numerical modeling. To calculate the data aggregation, the authors propose using numerical probabilistic analysis (NPA). An important feature of this study is how the authors represent the aggregated data. The study shows that the offered approach to data aggregation can be interpreted as the frequency distribution of a variable. To study its properties, the density function is used. For this purpose, the authors propose using the piecewise polynomial models. A suitable example of such approach is the spline. The authors show that their approach to data aggregation allows reducing the level of data uncertainty and significantly increasing the efficiency of numerical calculations. To demonstrate the degree of the correspondence of the proposed methods to reality, the authors developed a theoretical framework and considered numerical examples devoted to time series aggregation.

Finite element strategies to satisfy clinical and engineering requirements in the field of percutaneous valves.

PubMed

Capelli, Claudio; Biglino, Giovanni; Petrini, Lorenza; Migliavacca, Francesco; Cosentino, Daria; Bonhoeffer, Philipp; Taylor, Andrew M; Schievano, Silvia

2012-12-01

Finite element (FE) modelling can be a very resourceful tool in the field of cardiovascular devices. To ensure result reliability, FE models must be validated experimentally against physical data. Their clinical application (e.g., patients' suitability, morphological evaluation) also requires fast simulation process and access to results, while engineering applications need highly accurate results. This study shows how FE models with different mesh discretisations can suit clinical and engineering requirements for studying a novel device designed for percutaneous valve implantation. Following sensitivity analysis and experimental characterisation of the materials, the stent-graft was first studied in a simplified geometry (i.e., compliant cylinder) and validated against in vitro data, and then in a patient-specific implantation site (i.e., distensible right ventricular outflow tract). Different meshing strategies using solid, beam and shell elements were tested. Results showed excellent agreement between computational and experimental data in the simplified implantation site. Beam elements were found to be convenient for clinical applications, providing reliable results in less than one hour in a patient-specific anatomical model. Solid elements remain the FE choice for engineering applications, albeit more computationally expensive (>100 times). This work also showed how information on device mechanical behaviour differs when acquired in a simplified model as opposed to a patient-specific model.

Investigations for Supersonic Transports at Transonic and Supersonic Conditions

NASA Technical Reports Server (NTRS)

Rivers, S. Melissa B.; Owens, Lewis R.; Wahls, Richard A.

2007-01-01

Several computational studies were conducted as part of NASA s High Speed Research Program. Results of turbulence model comparisons from two studies on supersonic transport configurations performed during the NASA High-Speed Research program are given. The effects of grid topology and the representation of the actual wind tunnel model geometry are also investigated. Results are presented for both transonic conditions at Mach 0.90 and supersonic conditions at Mach 2.48. A feature of these two studies was the availability of higher Reynolds number wind tunnel data with which to compare the computational results. The transonic wind tunnel data was obtained in the National Transonic Facility at NASA Langley, and the supersonic data was obtained in the Boeing Polysonic Wind Tunnel. The computational data was acquired using a state of the art Navier-Stokes flow solver with a wide range of turbulence models implemented. The results show that the computed forces compare reasonably well with the experimental data, with the Baldwin-Lomax with Degani-Schiff modifications and the Baldwin-Barth models showing the best agreement for the transonic conditions and the Spalart-Allmaras model showing the best agreement for the supersonic conditions. The transonic results were more sensitive to the choice of turbulence model than were the supersonic results.

Antibacterial effect of silver nanoparticles and the modeling of bacterial growth kinetics using a modified Gompertz model.

PubMed

Chatterjee, Tanaya; Chatterjee, Barun K; Majumdar, Dipanwita; Chakrabarti, Pinak

2015-02-01

An alternative to conventional antibiotics is needed to fight against emerging multiple drug resistant pathogenic bacteria. In this endeavor, the effect of silver nanoparticle (Ag-NP) has been studied quantitatively on two common pathogenic bacteria Escherichia coli and Staphylococcus aureus, and the growth curves were modeled. The effect of Ag-NP on bacterial growth kinetics was studied by measuring the optical density, and was fitted by non-linear regression using the Logistic and modified Gompertz models. Scanning Electron Microscopy and fluorescence microscopy were used to study the morphological changes of the bacterial cells. Generation of reactive oxygen species for Ag-NP treated cells were measured by fluorescence emission spectra. The modified Gompertz model, incorporating cell death, fits the observed data better than the Logistic model. With increasing concentration of Ag-NP, the growth kinetics of both bacteria shows a decline in growth rate with simultaneous enhancement of death rate constants. The duration of the lag phase was found to increase with Ag-NP concentration. SEM showed morphological changes, while fluorescence microscopy using DAPI showed compaction of DNA for Ag-NP-treated bacterial cells. E. coli was found to be more susceptible to Ag-NP as compared to S. aureus. The modified Gompertz model, using a death term, was found to be useful in explaining the non-monotonic nature of the growth curve. The modified Gompertz model derived here is of general nature and can be used to study any microbial growth kinetics under the influence of antimicrobial agents. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving Crop Productions Using the Irrigation & Crop Production Model Under Drought

NASA Astrophysics Data System (ADS)

Shin, Y.; Lee, T.; Lee, S. H.; Kim, J.; Jang, W.; Park, S.

2017-12-01

We aimed to improve crop productions by providing optimal irrigation water amounts (IWAs) for various soils and crops using the Irrigation & Crop Production (ICP) model under various hydro-climatic regions. We selected the Little Washita (LW 13/21) and Bangdong-ri sites in Oklahoma (United States of America) and Chuncheon (Republic of Korea) for the synthetic studies. Our results showed that the ICP model performed well for improving crop productions by providing optimal IWAs during the study period (2000 to 2016). Crop productions were significantly affected by the solar radiation and precipitation, but the maximum and minimum temperature showed less impact on crop productions. When we considerd that the weather variables cannot be adjusted by artifical activities, irrigation might be the only solution for improving crop productions under drought. Also, the presence of shallow ground water (SGW) table depths higlhy influences on crop production. Although certainties exist in the synthetic studies, our results showed the robustness of the ICP model for improving crop productions under the drought condition. Thus, the ICP model can contribute to efficient water management plans under drought in regions at where water availability is limited.

Decision on risk-averse dual-channel supply chain under demand disruption

NASA Astrophysics Data System (ADS)

Yan, Bo; Jin, Zijie; Liu, Yanping; Yang, Jianbo

2018-02-01

We studied dual-channel supply chains using centralized and decentralized decision-making models. We also conducted a comparative analysis of the decisions before and after demand disruption. The study shows that the amount of change in decision-making is a linear function of the amount of demand disruption, and it is independent of the risk-averse coefficient. The optimal sales volume decision of the disturbing supply chain is related to market share and demand disruption in the decentralized decision-making model. The optimal decision is only influenced by demand disruption in the centralized decision-making model. The stability of the sales volume of the two models is related to market share and demand disruption. The optimal system production of the two models shows robustness, but their stable internals are different.

Osteoarthritis: new insights in animal models.

PubMed

Longo, Umile Giuseppe; Loppini, Mattia; Fumo, Caterina; Rizzello, Giacomo; Khan, Wasim Sardar; Maffulli, Nicola; Denaro, Vincenzo

2012-01-01

Osteoarthritis (OA) is the most frequent and symptomatic health problem in the middle-aged and elderly population, with over one-half of all people over the age of 65 showing radiographic changes in painful knees. The aim of the present study was to perform an overview on the available animal models used in the research field on the OA. Discrepancies between the animal models and the human disease are present. As regards human 'idiopathic' OA, with late onset and slow progression, it is perhaps wise not to be overly enthusiastic about animal models that show severe chondrodysplasia and very early OA. Advantage by using genetically engineered mouse models, in comparison with other surgically induced models, is that molecular etiology is known. Find potential molecular markers for the onset of the disease and pay attention to the role of gender and environmental factors should be very helpful in the study of mice that acquire premature OA. Surgically induced destabilization of joint is the most widely used induction method. These models allow the temporal control of disease induction and follow predictable progression of the disease. In animals, ACL transection and meniscectomy show a speed of onset and severity of disease higher than in humans after same injury.

Crowdsourcing urban air temperatures through smartphone battery temperatures in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where traditional measurements are scarce. Earlier studies showed that smartphone battery temperature readings allow for estimating the daily and city-wide air temperature via a straightforward heat transfer model. This study advances these model estimations by studying spatially and temporally smaller scales. The accuracy of temperature retrievals as a function of the number of battery readings is also studied. An extensive dataset of over 10 million battery temperature readings is available for São Paulo (Brazil), for estimating hourly and daily air temperatures. The air temperature estimates are validated with air temperature measurements from a WMO station, an Urban Fluxnet site, and crowdsourced data from 7 hobby meteorologists' private weather stations. On a daily basis temperature estimates are good, and we show they improve by optimizing model parameters for neighbourhood scales as categorized in Local Climate Zones. Temperature differences between Local Climate Zones can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, initial results are poor, but are vastly improved by using a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The obtained results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.

Advances in nonmarket valuation econometrics: Spatial heterogeneity in hedonic pricing models and preference heterogeneity in stated preference models

NASA Astrophysics Data System (ADS)

Yoo, Jin Woo

In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania Counties. The spatial-lag (SLM), the spatial error (SEM) and the spatial error component (SEC) models were compared. A geographically weighted regression (GWR) model is estimated to study the spatial heterogeneity of the marginal implicit prices of ACE impact within each county. New hybrid spatial hedonic models, the GWR-SEC and a modified GWR-SEM, are estimated such that both spatial autocorrelation and heterogeneity are accounted. The results show that the coefficient of land under easement contract varies spatially within one county, but not within the other county studied. Also, ACE's are found to have both positive and negative impacts on the values of nearby residential properties. Among global spatial models, the SEM fit better than the SLM and the SEC. Statistical goodness of fit measures showed that the GWR-SEC model fit better than the GWR or the GWR-SEC model. Finally, the GWR-SEC showed spatial autocorrelation is stronger in one county than in the other county.

The gene therapy revolution in ophthalmology.

PubMed

Al-Saikhan, Fahad I

2013-04-01

The advances in gene therapy hold significant promise for the treatment of ophthalmic conditions. Several studies using animal models have been published. Animal models on retinitis pigmentosa, Leber's Congenital Amaurosis (LCA), and Stargardt disease have involved the use of adeno-associated virus (AAV) to deliver functional genes into mice and canines. Mice models have been used to show that a mutation in cGMP phosphodiesterase that results in retinitis pigmentosa can be corrected using rAAV vectors. Additionally, rAAV vectors have been successfully used to deliver ribozyme into mice with a subsequent improvement in autosomal dominant retinitis pigmentosa. By using dog models, researchers have made progress in studying X-linked retinitis pigmentosa which results from a RPGR gene mutation. Mouse and canine models have also been used in the study of LCA. The widely studied form of LCA is LCA2, resulting from a mutation in the gene RPE65. Mice and canines that were injected with normal copies of RPE65 gene showed signs such as improved retinal pigment epithelium transduction, visual acuity, and functional recovery. Studies on Stargardt disease have shown that mutations in the ABCA4 gene can be corrected with AAV vectors, or nanoparticles. Gene therapy for the treatment of red-green color blindness was successful in squirrel monkeys. Plans are at an advanced stage to begin clinical trials. Researchers have also proved that CD59 can be used with AMD. Gene therapy is also able to treat primary open angle glaucoma (POAG) in animal models, and studies show it is economically viable.

The gene therapy revolution in ophthalmology

PubMed Central

Al-Saikhan, Fahad I.

2013-01-01

The advances in gene therapy hold significant promise for the treatment of ophthalmic conditions. Several studies using animal models have been published. Animal models on retinitis pigmentosa, Leber’s Congenital Amaurosis (LCA), and Stargardt disease have involved the use of adeno-associated virus (AAV) to deliver functional genes into mice and canines. Mice models have been used to show that a mutation in cGMP phosphodiesterase that results in retinitis pigmentosa can be corrected using rAAV vectors. Additionally, rAAV vectors have been successfully used to deliver ribozyme into mice with a subsequent improvement in autosomal dominant retinitis pigmentosa. By using dog models, researchers have made progress in studying X-linked retinitis pigmentosa which results from a RPGR gene mutation. Mouse and canine models have also been used in the study of LCA. The widely studied form of LCA is LCA2, resulting from a mutation in the gene RPE65. Mice and canines that were injected with normal copies of RPE65 gene showed signs such as improved retinal pigment epithelium transduction, visual acuity, and functional recovery. Studies on Stargardt disease have shown that mutations in the ABCA4 gene can be corrected with AAV vectors, or nanoparticles. Gene therapy for the treatment of red–green color blindness was successful in squirrel monkeys. Plans are at an advanced stage to begin clinical trials. Researchers have also proved that CD59 can be used with AMD. Gene therapy is also able to treat primary open angle glaucoma (POAG) in animal models, and studies show it is economically viable. PMID:24227970

Student Background, School Climate, School Disorder, and Student Achievement: An Empirical Study of New York City's Middle Schools

ERIC Educational Resources Information Center

Chen, Greg; Weikart, Lynne A.

2008-01-01

This study develops and tests a school disorder and student achievement model based upon the school climate framework. The model was fitted to 212 New York City middle schools using the Structural Equations Modeling Analysis method. The analysis shows that the model fits the data well based upon test statistics and goodness of fit indices. The…

Self-organized Criticality in Hierarchical Brain Network

NASA Astrophysics Data System (ADS)

Yang, Qiu-Ying; Zhang, Ying-Yue; Chen, Tian-Lun

2008-11-01

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

Comparative mapping for bighead carp (Aristichthys nobilis) against model and non-model fishes provides insights into the genomic evolution of cyprinids.

PubMed

Zhu, Chuankun; Tong, Jingou; Yu, Xiaomu; Guo, Wenjie

2015-08-01

Comparative mapping provides an efficient method to connect genomes of non-model and model fishes. In this study, we used flanking sequences of the 659 microsatellites on a genetic map of bighead carp (Aristichthys nobilis) to comprehensively study syntenic relationships between bighead carp and nine model and non-model fishes. Of the five model and two food fishes with whole genome data, Cyprinus carpio showed the highest rate of positive BLAST hits (95.3 %) with bighead carp map, followed by Danio rerio (70.9 %), Oreochromis niloticus (21.7 %), Tetraodon nigroviridis (6.4 %), Gasterosteus aculeatus (5.2 %), Oryzias latipes (4.7 %) and Fugu rubripes (3.5 %). Chromosomal syntenic analyses showed that inversion was the basic chromosomal rearrangement during genomic evolution of cyprinids, and the extent of inversions and translocations was found to be positively correlated with evolutionary relationships among fishes studied. Among the five investigated cyprinids, linkage groups (LGs) of bighead carp, Hypophthalmichthys molitrix and Ctenopharyngodon idella exhibited a one-to-one relationship. Besides, LG 9 of bighead carp and homologous LGs of silver carp and grass carp all corresponded to the chromosomes 10 and 22 of zebrafish, suggesting that chromosomal fission may have occurred in the ancestor of zebrafish. On the other hand, LGs of bighead carp and common carp showed an approximate one-to-two relationship with extensive translocations, confirming the occurrence of a 4th whole genome duplication in common carp. This study provides insights into the understanding of genome evolution among cyprinids and would aid in transferring positional and functional information of genes from model fish like zebrafish to non-model fish like bighead carp.

Premium analysis for copula model: A case study for Malaysian motor insurance claims

NASA Astrophysics Data System (ADS)

Resti, Yulia; Ismail, Noriszura; Jaaman, Saiful Hafizah

2014-06-01

This study performs premium analysis for copula models with regression marginals. For illustration purpose, the copula models are fitted to the Malaysian motor insurance claims data. In this study, we consider copula models from Archimedean and Elliptical families, and marginal distributions of Gamma and Inverse Gaussian regression models. The simulated results from independent model, which is obtained from fitting regression models separately to each claim category, and dependent model, which is obtained from fitting copula models to all claim categories, are compared. The results show that the dependent model using Frank copula is the best model since the risk premiums estimated under this model are closely approximate to the actual claims experience relative to the other copula models.

Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

2015-04-01

In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.

Homology modeling, molecular docking and MD simulation studies to investigate role of cysteine protease from Xanthomonas campestris in degradation of Aβ peptide.

PubMed

Dhanavade, Maruti J; Jalkute, Chidambar B; Barage, Sagar H; Sonawane, Kailas D

2013-12-01

Cysteine protease is known to degrade amyloid beta peptide which is a causative agent of Alzheimer's disease. This cleavage mechanism has not been studied in detail at the atomic level. Hence, a three-dimensional structure of cysteine protease from Xanthomonas campestris was constructed by homology modeling using Geno3D, SWISS-MODEL, and MODELLER 9v7. All the predicted models were analyzed by PROCHECK and PROSA. Three-dimensional model of cysteine protease built by MODELLER 9v7 shows similarity with human cathepsin B crystal structure. This model was then used further for docking and simulation studies. The molecular docking study revealed that Cys17, His87, and Gln88 residues of cysteine protease form an active site pocket similar to human cathepsin B. Then the docked complex was refined by molecular dynamic simulation to confirm its stable behavior over the entire simulation period. The molecular docking and MD simulation studies showed that the sulfhydryl hydrogen atom of Cys17 of cysteine protease interacts with carboxylic oxygen of Lys16 of Aβ peptide indicating the cleavage site. Thus, the cysteine protease model from X. campestris having similarity with human cathepsin B crystal structure may be used as an alternate approach to cleave Aβ peptide a causative agent of Alzheimer's disease. © 2013 Elsevier Ltd. All rights reserved.

Geographical information system (GIS) application for flood prediction at Sungai Sembrong

NASA Astrophysics Data System (ADS)

Kamin, Masiri; Ahmad, Nor Farah Atiqah; Razali, Siti Nooraiin Mohd; Hilaham, Mashuda Mohamad; Rahman, Mohamad Abdul; Ngadiman, Norhayati; Sahat, Suhaila

2017-10-01

The occurrence of flood is one of natural disaster that often beset Malaysia. The latest incident that happened in 2007 was the worst occurrence of floods ever be set in Johor. Reporting floods mainly focused on rising water rising levels, so about once a focus on the area of flood delineation. A study focused on the effectiveness of using Geographic Information System (GIS) to predict the flood by taking Sg. Sembrong, Batu Pahat, Johor as study area. This study combined hydrological model and water balance model in the display to show the expected flood area for future reference. The minimum, maximum and average rainfall data for January 2007 at Sg Sembrong were used in this study. The data shows that flood does not occurs at the minimum and average rainfall of 17.2mm and 2mm respectively. At maximum rainfall, 203mm, shows the flood area was 9983 hectares with the highest level of the water depth was 2m. The result showed that the combination of hydrological models and water balance model in GIS is very suitable to be used as a tool to obtain preliminary information on flood immediately. Besides that, GIS system is a very powerful tool used in hydrology engineering to help the engineer and planner to imagine the real situation of flood events, doing flood analysis, problem solving and provide a rational, accurate and efficient decision making.

The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations

NASA Astrophysics Data System (ADS)

Miyoshi, Takemasa; Kunii, Masaru

2012-03-01

The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies. The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble members improves the analyses consistently.

Particle force model effects in a shock-driven multiphase instability

NASA Astrophysics Data System (ADS)

Black, W. J.; Denissen, N.; McFarland, J. A.

2018-05-01

This work presents simulations on a shock-driven multiphase instability (SDMI) at an initial particle volume fraction of 1% with the addition of a suite of particle force models applicable in dense flows. These models include pressure-gradient, added-mass, and interparticle force terms in an effort to capture the effects neighboring particles have in non-dilute flow regimes. Two studies are presented here: the first seeks to investigate the individual contributions of the force models, while the second study focuses on examining the effect of these force models on the hydrodynamic evolution of a SDMI with various particle relaxation times (particle sizes). In the force study, it was found that the pressure gradient and interparticle forces have little effect on the instability under the conditions examined, while the added-mass force decreases the vorticity deposition and alters the morphology of the instability. The relaxation-time study likewise showed a decrease in metrics associated with the evolution of the SDMI for all sizes when the particle force models were included. The inclusion of these models showed significant morphological differences in both the particle and carrier species fields, which increased as particle relaxation times increased.

Two Universality Classes for the Many-Body Localization Transition

NASA Astrophysics Data System (ADS)

Khemani, Vedika; Sheng, D. N.; Huse, David A.

2017-08-01

We provide a systematic comparison of the many-body localization (MBL) transition in spin chains with nonrandom quasiperiodic versus random fields. We find evidence suggesting that these belong to two separate universality classes: the first dominated by "intrinsic" intrasample randomness, and the second dominated by external intersample quenched randomness. We show that the effects of intersample quenched randomness are strongly growing, but not yet dominant, at the system sizes probed by exact-diagonalization studies on random models. Thus, the observed finite-size critical scaling collapses in such studies appear to be in a preasymptotic regime near the nonrandom universality class, but showing signs of the initial crossover towards the external-randomness-dominated universality class. Our results provide an explanation for why exact-diagonalization studies on random models see an apparent scaling near the transition while also obtaining finite-size scaling exponents that strongly violate Harris-Chayes bounds that apply to disorder-driven transitions. We also show that the MBL phase is more stable for the quasiperiodic model as compared to the random one, and the transition in the quasiperiodic model suffers less from certain finite-size effects.

The Role of Multimodel Combination in Improving Streamflow Prediction

NASA Astrophysics Data System (ADS)

Arumugam, S.; Li, W.

2008-12-01

Model errors are the inevitable part in any prediction exercise. One approach that is currently gaining attention to reduce model errors is by optimally combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictability. In this study, we present a new approach to combine multiple hydrological models by evaluating their predictability contingent on the predictor state. We combine two hydrological models, 'abcd' model and Variable Infiltration Capacity (VIC) model, with each model's parameter being estimated by two different objective functions to develop multimodel streamflow predictions. The performance of multimodel predictions is compared with individual model predictions using correlation, root mean square error and Nash-Sutcliffe coefficient. To quantify precisely under what conditions the multimodel predictions result in improved predictions, we evaluate the proposed algorithm by testing it against streamflow generated from a known model ('abcd' model or VIC model) with errors being homoscedastic or heteroscedastic. Results from the study show that streamflow simulated from individual models performed better than multimodels under almost no model error. Under increased model error, the multimodel consistently performed better than the single model prediction in terms of all performance measures. The study also evaluates the proposed algorithm for streamflow predictions in two humid river basins from NC as well as in two arid basins from Arizona. Through detailed validation in these four sites, the study shows that multimodel approach better predicts the observed streamflow in comparison to the single model predictions.

A role for subchondral bone changes in the process of osteoarthritis; a micro-CT study of two canine models.

PubMed

Sniekers, Yvonne H; Intema, Femke; Lafeber, Floris P J G; van Osch, Gerjo J V M; van Leeuwen, Johannes P T M; Weinans, Harrie; Mastbergen, Simon C

2008-02-12

This study evaluates changes in peri-articular bone in two canine models for osteoarthritis: the groove model and the anterior cruciate ligament transection (ACLT) model. Evaluation was performed at 10 and 20 weeks post-surgery and in addition a 3-weeks time point was studied for the groove model. Cartilage was analysed, and architecture of the subchondral plate and trabecular bone of epiphyses was quantified using micro-CT. At 10 and 20 weeks cartilage histology and biochemistry demonstrated characteristic features of osteoarthritis in both models (very mild changes at 3 weeks). The groove model presented osteophytes only at 20 weeks, whereas the ACLT model showed osteophytes already at 10 weeks. Trabecular bone changes in the groove model were small and not consistent. This contrasts the ACLT model in which bone volume fraction was clearly reduced at 10 and 20 weeks (15-20%). However, changes in metaphyseal bone indicate unloading in the ACLT model, not in the groove model. For both models the subchondral plate thickness was strongly reduced (25-40%) and plate porosity was strongly increased (25-85%) at all time points studied. These findings show differential regulation of subchondral trabecular bone in the groove and ACLT model, with mild changes in the groove model and more severe changes in the ACLT model. In the ACLT model, part of these changes may be explained by unloading of the treated leg. In contrast, subchondral plate thinning and increased porosity were very consistent in both models, independent of loading conditions, indicating that this thinning is an early response in the osteoarthritis process.

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models

PubMed Central

Govers, Coen; van der Meulen, Jan; van Hoef, Angeline; Stoopen, Geert; Hamers, Astrid; Hoekman, Arjan; de Vos, Ric; Bovee, Toine F. H.; Smits, Mari; Mes, Jurriaan J.

2016-01-01

Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, we explored the applicability of in vitro (human Caco-2 cells) and ex vivo intestine models (rat precision cut intestine slices and the pig in-situ small intestinal segment perfusion (SISP) technique) to study the effect of food compounds. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into which extent mode of actions depend on the model. The three intestine models shared 9,140 genes which were used to compare the responses to digested onions between the models. Unsupervised clustering analysis showed that genes up- or down-regulated by WOd in human Caco-2 cells and rat intestine slices were similarly regulated by YOd, indicating comparable modes of action for the two onion species. Highly variable responses to onion were found in the pig SISP model. By focussing only on genes with significant differential expression, in combination with a fold change > 1.5, 15 genes showed similar onion-induced expression in human Caco-2 cells and rat intestine slices and 2 overlapping genes were found between the human Caco-2 and pig SISP model. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions in all three models. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Taken together, our data indicate that each of the in vitro and ex vivo intestine models used in this study, taking into account their limitations, can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies. PMID:27631494

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models.

PubMed

de Wit, Nicole J W; Hulst, Marcel; Govers, Coen; van der Meulen, Jan; van Hoef, Angeline; Stoopen, Geert; Hamers, Astrid; Hoekman, Arjan; de Vos, Ric; Bovee, Toine F H; Smits, Mari; Mes, Jurriaan J; Hendriksen, Peter J M

2016-01-01

Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, we explored the applicability of in vitro (human Caco-2 cells) and ex vivo intestine models (rat precision cut intestine slices and the pig in-situ small intestinal segment perfusion (SISP) technique) to study the effect of food compounds. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into which extent mode of actions depend on the model. The three intestine models shared 9,140 genes which were used to compare the responses to digested onions between the models. Unsupervised clustering analysis showed that genes up- or down-regulated by WOd in human Caco-2 cells and rat intestine slices were similarly regulated by YOd, indicating comparable modes of action for the two onion species. Highly variable responses to onion were found in the pig SISP model. By focussing only on genes with significant differential expression, in combination with a fold change > 1.5, 15 genes showed similar onion-induced expression in human Caco-2 cells and rat intestine slices and 2 overlapping genes were found between the human Caco-2 and pig SISP model. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions in all three models. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Taken together, our data indicate that each of the in vitro and ex vivo intestine models used in this study, taking into account their limitations, can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies.

Inspiration or deflation? Feeling similar or dissimilar to slim and plus-size models affects self-evaluation of restrained eaters.

PubMed

Papies, Esther K; Nicolaije, Kim A H

2012-01-01

The present studies examined the effect of perceiving images of slim and plus-size models on restrained eaters' self-evaluation. While previous research has found that such images can lead to either inspiration or deflation, we argue that these inconsistencies can be explained by differences in perceived similarity with the presented model. The results of two studies (ns=52 and 99) confirmed this and revealed that restrained eaters with high (low) perceived similarity to the model showed more positive (negative) self-evaluations when they viewed a slim model, compared to a plus-size model. In addition, Study 2 showed that inducing in participants a similarities mindset led to more positive self-evaluations after viewing a slim compared to a plus-size model, but only among restrained eaters with a relatively high BMI. These results are discussed in the context of research on social comparison processes and with regard to interventions for protection against the possible detrimental effects of media images. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparative analysis of used car price evaluation models

NASA Astrophysics Data System (ADS)

Chen, Chuancan; Hao, Lulu; Xu, Cong

2017-05-01

An accurate used car price evaluation is a catalyst for the healthy development of used car market. Data mining has been applied to predict used car price in several articles. However, little is studied on the comparison of using different algorithms in used car price estimation. This paper collects more than 100,000 used car dealing records throughout China to do empirical analysis on a thorough comparison of two algorithms: linear regression and random forest. These two algorithms are used to predict used car price in three different models: model for a certain car make, model for a certain car series and universal model. Results show that random forest has a stable but not ideal effect in price evaluation model for a certain car make, but it shows great advantage in the universal model compared with linear regression. This indicates that random forest is an optimal algorithm when handling complex models with a large number of variables and samples, yet it shows no obvious advantage when coping with simple models with less variables.

Review and developments of dissemination models for airborne carbon fibers

NASA Technical Reports Server (NTRS)

Elber, W.

1980-01-01

Dissemination prediction models were reviewed to determine their applicability to a risk assessment for airborne carbon fibers. The review showed that the Gaussian prediction models using partial reflection at the ground agreed very closely with a more elaborate diffusion analysis developed for the study. For distances beyond 10,000 m the Gaussian models predicted a slower fall-off in exposure levels than the diffusion models. This resulting level of conservatism was preferred for the carbon fiber risk assessment. The results also showed that the perfect vertical-mixing models developed herein agreed very closely with the diffusion analysis for all except the most stable atmospheric conditions.

Study of Nonclassical Fields in Phase-Sensitive Reservoirs

NASA Technical Reports Server (NTRS)

Kim, Myung Shik; Imoto, Nobuyuki

1996-01-01

We show that the reservoir influence can be modeled by an infinite array of beam splitters. The superposition of the input fields in the beam splitter is discussed with the convolution laws for their quasiprobabilities. We derive the Fokker-Planck equation for the cavity field coupled with a phase-sensitive reservoir using the convolution law. We also analyze the amplification in the phase-sensitive reservoir with use of the modified beam splitter model. We show the similarities and differences between the dissipation and amplification models. We show that a super-Poissonian input field cannot become sub-Poissonian by the phase-sensitive amplification.

Bayesian evidences for dark energy models in light of current observational data

NASA Astrophysics Data System (ADS)

Lonappan, Anto. I.; Kumar, Sumit; Ruchika; Dinda, Bikash R.; Sen, Anjan A.

2018-02-01

We do a comprehensive study of the Bayesian evidences for a large number of dark energy models using a combination of latest cosmological data from SNIa, CMB, BAO, strong lensing time delay, growth measurements, measurements of Hubble parameter at different redshifts and measurements of angular diameter distance by Megamaser Cosmology Project. We consider a variety of scalar field models with different potentials as well as different parametrizations for the dark energy equation of state. Among 21 models that we consider in our study, we do not find strong evidences in favor of any evolving dark energy model compared to Λ CDM . For the evolving dark energy models, we show that purely nonphantom models have much better evidences compared to those models that allow both phantom and nonphantom behaviors. Canonical scalar field with exponential and tachyon field with square potential have highest evidences among all the models considered in this work. We also show that a combination of low redshift measurements decisively favors an accelerating Λ CDM model compared to a nonaccelerating power law model.

Novel Genetic Models to Study the Role of Inflammation in Brain Injury-Induced Alzheimer’s Pathology

DTIC Science & Technology

2014-12-01

AD_________________ Award Number: W81XWH-12-1-0629 TITLE: Novel Genetic Models to Study the Role...CONTRACT NUMBER Novel Genetic Models to Study the Role of Inflammation in Brain Injury-Induced Alzheimer’s Pathology 5b. GRANT NUMBER W81XWH-12-1...However, our laboratories have recently performed pioneering studies using genetic labels regulated by these chemokine-receptor promoters to show

The substorm loading-unloading cycle as reproduced by community-available global MHD magnetospheric models

NASA Astrophysics Data System (ADS)

Gordeev, Evgeny; Sergeev, Victor; Tsyganenko, Nikolay; Kuznetsova, Maria; Rastaetter, Lutz; Raeder, Joachim; Toth, Gabor; Lyon, John; Merkin, Vyacheslav; Wiltberger, Michael

2017-04-01

In this study we investigate how well the three community-available global MHD models, supported by the Community Coordinated Modeling Center (CCMC NASA), reproduce the global magnetospheric dynamics, including the loading-unloading substorm cycle. We found that in terms of global magnetic flux transport CCMC models display systematically different response to idealized 2-hour north then 2-hour south IMF Bz variation. The LFM model shows a depressed return convection in the tail plasma sheet and high rate of magnetic flux loading into the lobes during the growth phase, as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded/unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. BATSRUS and Open GGCM models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. Our study shows that different CCMC models under the same solar wind conditions (north to south IMF variation) produce essentially different solutions in terms of global magnetospheric convection.

Structural Acoustic Physics Based Modeling of Curved Composite Shells

DTIC Science & Technology

2017-09-19

Results show that the finite element computational models accurately match analytical calculations, and that the composite material studied in this...products. 15. SUBJECT TERMS Finite Element Analysis, Structural Acoustics, Fiber-Reinforced Composites, Physics-Based Modeling 16. SECURITY...2 4 FINITE ELEMENT MODEL DESCRIPTION

Smooth random change point models.

PubMed

van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

2011-03-15

Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Meeting models and mineralogy

NASA Astrophysics Data System (ADS)

Bridges, John C.

2018-03-01

A new geochemical study shows that short-lived warm and wet episodes during a globally cold early Mars could have formed the clay deposits detected on the Martian surface. This model can reconcile climate models with mineralogical and geomorphological evidence.

External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

PubMed

Lamain-de Ruiter, Marije; Kwee, Anneke; Naaktgeboren, Christiana A; de Groot, Inge; Evers, Inge M; Groenendaal, Floris; Hering, Yolanda R; Huisjes, Anjoke J M; Kirpestein, Cornel; Monincx, Wilma M; Siljee, Jacqueline E; Van 't Zelfde, Annewil; van Oirschot, Charlotte M; Vankan-Buitelaar, Simone A; Vonk, Mariska A A W; Wiegers, Therese A; Zwart, Joost J; Franx, Arie; Moons, Karel G M; Koster, Maria P H

2016-08-30

 To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy.  External validation of all published prognostic models in large scale, prospective, multicentre cohort study.  31 independent midwifery practices and six hospitals in the Netherlands.  Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded.  Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots.  3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit.  In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Stochastic approaches for time series forecasting of boron: a case study of Western Turkey.

PubMed

Durdu, Omer Faruk

2010-10-01

In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996-2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box-Whisker plots and Kendall's tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002-2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic statistics of observed data in terms of mean. The ARIMA modeling approach is recommended for predicting boron concentration series of a river.

Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

NASA Astrophysics Data System (ADS)

Pourghasemi, Hamid Reza; Rossi, Mauro

2017-10-01

Landslides are identified as one of the most important natural hazards in many areas throughout the world. The essential purpose of this study is to compare general linear model (GLM), general additive model (GAM), multivariate adaptive regression spline (MARS), and modified analytical hierarchy process (M-AHP) models and assessment of their performances for landslide susceptibility modeling in the west of Mazandaran Province, Iran. First, landslides were identified by interpreting aerial photographs, and extensive field works. In total, 153 landslides were identified in the study area. Among these, 105 landslides were randomly selected as training data (i.e. used in the models training) and the remaining 48 (30 %) cases were used for the validation (i.e. used in the models validation). Afterward, based on a deep literature review on 220 scientific papers (period between 2005 and 2012), eleven conditioning factors including lithology, land use, distance from rivers, distance from roads, distance from faults, slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, and profile curvature were selected. The Certainty Factor (CF) model was used for managing uncertainty in rule-based systems and evaluation of the correlation between the dependent (landslides) and independent variables. Finally, the landslide susceptibility zonation was produced using GLM, GAM, MARS, and M-AHP models. For evaluation of the models, the area under the curve (AUC) method was used and both success and prediction rate curves were calculated. The evaluation of models for GLM, GAM, and MARS showed 90.50, 88.90, and 82.10 % for training data and 77.52, 70.49, and 78.17 % for validation data, respectively. Furthermore, The AUC value of the produced landslide susceptibility map using M-AHP showed a training value of 77.82 % and validation value of 82.77 % accuracy. Based on the overall assessments, the proposed approaches showed reasonable results for landslide susceptibility mapping in the study area. Moreover, results obtained showed that the M-AHP model performed slightly better than the MARS, GLM, and GAM models in prediction. These algorithms can be very useful for landslide susceptibility and hazard mapping and land use planning in regional scale.

Models of science-policy interaction: exploring approaches to Bisphenol A management in the EU.

PubMed

Udovyk, O

2014-07-01

This study investigated science-policy interaction models and their limitations under conditions of uncertainty. In detail, it looked at the management of the suspected endocrine-disrupting chemical Bisphenol A (BPA). Despite growing evidence that BPA is hazardous to human and environmental health, the level of scientific uncertainty is still high and, as a result, there is significant disagreement on the actual extent and type of risk. Analysis of decision-making processes at different regulatory levels (EU, Sweden, and the Swedish municipality of Gothenburg) exposed chemicals risk management and associated science-policy interaction under uncertainty. The results of the study show that chemicals management and associated science-policy interaction follow the modern model of science-policy interaction, where science is assumed to 'speak truth to policy' and highlights existing limitations of this model under conditions of uncertainty. The study not only explores alternative models (precautionary, consensus, science-policy demarcation. and extended participation) but also shows their limitations. The study concludes that all models come with their particular underlying assumptions, strengths, and limitations. At the same time, by exposing serious limitations of the modern model, the study calls for a rethinking of the relationship between science, policy, and management. Copyright © 2014 Elsevier B.V. All rights reserved.

Future-year ozone prediction for the United States using updated models and inputs.

PubMed

Collet, Susan; Kidokoro, Toru; Karamchandani, Prakash; Shah, Tejas; Jung, Jaegun

2017-08-01

The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies. The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

Presenting Thin Media Models Affects Women's Choice of Diet or Normal Snacks

ERIC Educational Resources Information Center

Krahe, Barbara; Krause, Christina

2010-01-01

Our study explored the influence of thin- versus normal-size media models and of self-reported restrained eating behavior on women's observed snacking behavior. Fifty female undergraduates saw a set of advertisements for beauty products showing either thin or computer-altered normal-size female models, allegedly as part of a study on effective…

A wind-tunnel investigation of a B-52 model flutter suppression system

NASA Technical Reports Server (NTRS)

Redd, L. T.; Gilman, J., Jr.; Cooley, D. E.; Sevart, F. D.

1974-01-01

Flutter modeling techniques have been successfully extended to the difficult case of the active suppression of flutter. The demonstration was conducted in a transonic dynamics tunnel using a 1/30 scale, elastic, dynamic model of a Boeing B-52 control configured vehicle. The results from the study show that with the flutter suppression system operating there is a substantial increase in the damping associated with the critical flutter mode. The results also show good correlation between the damping characteristics of the model and the aircraft.

Automated finite element meshing of the lumbar spine: Verification and validation with 18 specimen-specific models.

PubMed

Campbell, J Q; Coombs, D J; Rao, M; Rullkoetter, P J; Petrella, A J

2016-09-06

The purpose of this study was to seek broad verification and validation of human lumbar spine finite element models created using a previously published automated algorithm. The automated algorithm takes segmented CT scans of lumbar vertebrae, automatically identifies important landmarks and contact surfaces, and creates a finite element model. Mesh convergence was evaluated by examining changes in key output variables in response to mesh density. Semi-direct validation was performed by comparing experimental results for a single specimen to the automated finite element model results for that specimen with calibrated material properties from a prior study. Indirect validation was based on a comparison of results from automated finite element models of 18 individual specimens, all using one set of generalized material properties, to a range of data from the literature. A total of 216 simulations were run and compared to 186 experimental data ranges in all six primary bending modes up to 7.8Nm with follower loads up to 1000N. Mesh convergence results showed less than a 5% difference in key variables when the original mesh density was doubled. The semi-direct validation results showed that the automated method produced results comparable to manual finite element modeling methods. The indirect validation results showed a wide range of outcomes due to variations in the geometry alone. The studies showed that the automated models can be used to reliably evaluate lumbar spine biomechanics, specifically within our intended context of use: in pure bending modes, under relatively low non-injurious simulated in vivo loads, to predict torque rotation response, disc pressures, and facet forces. Copyright © 2016 Elsevier Ltd. All rights reserved.

Watershed erosion modeling using the probability of sediment connectivity in a gently rolling system

NASA Astrophysics Data System (ADS)

Mahoney, David Tyler; Fox, James Forrest; Al Aamery, Nabil

2018-06-01

Sediment connectivity has been shown in recent years to explain how the watershed configuration controls sediment transport. However, we find no studies develop a watershed erosion modeling framework based on sediment connectivity, and few, if any, studies have quantified sediment connectivity for gently rolling systems. We develop a new predictive sediment connectivity model that relies on the intersecting probabilities for sediment supply, detachment, transport, and buffers to sediment transport, which is integrated in a watershed erosion model framework. The model predicts sediment flux temporally and spatially across a watershed using field reconnaissance results, a high-resolution digital elevation models, a hydrologic model, and shear-based erosion formulae. Model results validate the capability of the model to predict erosion pathways causing sediment connectivity. More notably, disconnectivity dominates the gently rolling watershed across all morphologic levels of the uplands, including, microtopography from low energy undulating surfaces across the landscape, swales and gullies only active in the highest events, karst sinkholes that disconnect drainage areas, and floodplains that de-couple the hillslopes from the stream corridor. Results show that sediment connectivity is predicted for about 2% or more the watershed's area 37 days of the year, with the remaining days showing very little or no connectivity. Only 12.8 ± 0.7% of the gently rolling watershed shows sediment connectivity on the wettest day of the study year. Results also highlight the importance of urban/suburban sediment pathways in gently rolling watersheds, and dynamic and longitudinal distributions of sediment connectivity might be further investigated in future work. We suggest the method herein provides the modeler with an added tool to account for sediment transport criteria and has the potential to reduce computational costs in watershed erosion modeling.

A Linear Stochastic Dynamical Model of ENSO. Part II: Analysis.

NASA Astrophysics Data System (ADS)

Thompson, C. J.; Battisti, D. S.

2001-02-01

In this study the behavior of a linear, intermediate model of ENSO is examined under stochastic forcing. The model was developed in a companion paper (Part I) and is derived from the Zebiak-Cane ENSO model. Four variants of the model are used whose stabilities range from slightly damped to moderately damped. Each model is run as a simulation while being perturbed by noise that is uncorrelated (white) in space and time. The statistics of the model output show the moderately damped models to be more realistic than the slightly damped models. The moderately damped models have power spectra that are quantitatively quite similar to observations, and a seasonal pattern of variance that is qualitatively similar to observations. All models produce ENSOs that are phase locked to the annual cycle, and all display the `spring barrier' characteristic in their autocorrelation patterns, though in the models this `barrier' occurs during the summer and is less intense than in the observations (inclusion of nonlinear effects is shown to partially remedy this deficiency). The more realistic models also show a decadal variability in the lagged autocorrelation pattern that is qualitatively similar to observations.Analysis of the models shows that the greatest part of the variability comes from perturbations that project onto the first singular vector, which then grow rapidly into the ENSO mode. Essentially, the model output represents many instances of the ENSO mode, with random phase and amplitude, stimulated by the noise through the optimal transient growth of the singular vectors.The limit of predictability for each model is calculated and it is shown that the more realistic (moderately damped) models have worse potential predictability (9-15 months) than the deterministic chaotic models that have been studied widely in the literature. The predictability limits are strongly correlated with the stability of the models' ENSO mode-the more highly damped models having much shorter limits of predictability. A comparison of the two most realistic models shows that even though these models have similar statistics, they have very different predictability limits. The models have a strong seasonal dependence to their predictability limits.The results of this study (with the companion paper) suggest that the linear, stable dynamical model of ENSO is indeed a plausible hypothesis for the observed ENSO. With very reasonable levels of stochastic forcing, the model produces realistic levels of variance, has a realistic spectrum, and qualitatively reproduces the observed seasonal pattern of variance, the autocorrelation pattern, and the ENSO-like decadal variability.

Modeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks.

PubMed

Curado, Leone F A; Musis, Carlo R DE; Cunha, Cristiano R DA; Rodrigues, Thiago R; Pereira, Vinicius M R; Nogueira, José S; Sanches, Luciana

2016-09-01

The study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the interaction of energy in the form of photosynthetically active radiation (PAR) in the Pantanal, a Brazilian wetland forest, by studying the variation of PAR reflectance and its interaction with local rainfall. The study site is located in Private Reserve of Natural Heritage, Mato Grosso State, Brazil, where the vegetation is a monodominant forest of Vochysia divergens Phol. The results showed a high correlation between the reflection of visible radiation and rainfall; however, the behavior was not the same at the three heights studied. An analysis of the hourly variation of the reflected waves also showed the seasonality of these phenomena in relation to the dry and rainy seasons. A predictive model for PAR was developed with a neural network that has a hidden layer, and it showed a determination coefficient of 0.938. This model showed that the Julian day and time of measurements had an inverse association with the wind profile and a direct association with the relative humidity profile.

Tropical disturbances in relation to general circulation modeling

NASA Technical Reports Server (NTRS)

Estoque, M. A.

1982-01-01

The initial results of an evaluation of the performance of the Goddard Laboratory of Atmospheric Simulation general circulation model depicting the tropical atmosphere during the summer are presented. Because the results show the existence of tropical wave disturbances throughout the tropics, the characteristics of synoptic disturbances over Africa were studied and a synoptic case study of a selected disturbance in this area was conducted. It is shown that the model is able to reproduce wave type synoptic disturbances in the tropics. The findings show that, in one of the summers simulated, the disturbances are predominantly closed vortices; in another summer, the predominant disturbances are open waves.

Structural validation of the Self-Compassion Scale with a German general population sample

PubMed Central

Kwakkenbos, Linda; Moran, Chelsea; Thombs, Brett; Albani, Cornelia; Bourkas, Sophia; Zenger, Markus; Brahler, Elmar; Körner, Annett

2018-01-01

Background Published validation studies have reported different factor structures for the Self-Compassion Scale (SCS). The objective of this study was to assess the factor structure of the SCS in a large general population sample representative of the German population. Methods A German population sample completed the SCS and other self-report measures. Confirmatory factor analysis (CFA) in MPlus was used to test six models previously found in factor analytic studies (unifactorial model, two-factor model, three-factor model, six-factor model, a hierarchical (second order) model with six first-order factors and two second-order factors, and a model with arbitrarily assigned items to six factors). In addition, three bifactor models were also tested: bifactor model #1 with two group factors (SCS positive items, called SCS positive) and SCS negative items, called SCS negative) and one general factor (overall SCS); bifactor model #2, which is a two-tier model with six group factors, three (SCS positive subscales) corresponding to one general dimension (SCS positive) and three (SCS negative subscales) corresponding to the second general dimension (SCS negative); bifactor model #3 with six group factors (six SCS subscales) and one general factor (overall SCS). Results The two-factor model, the six-factor model, and the hierarchical model showed less than ideal, but acceptable fit. The model fit indices for these models were comparable, with no apparent advantage of the six-factor model over the two-factor model. The one-factor model, the three-factor model, and bifactor model #3 showed poor fit. The other two bifactor models showed strong support for two factors: SCS positive and SCS negative. Conclusion The main results of this study are that, among the German general population, six SCS factors and two SCS factors fit the data reasonably well. While six factors can be modelled, the three negative factors and the three positive factors, respectively, did not reflect reliable or meaningful variance beyond the two summative positive and negative item factors. As such, we recommend the use of two subscale scores to capture a positive factor and a negative factor when administering the German SCS to general population samples and we strongly advise against the use of a total score across all SCS items. PMID:29408888

Modelling population distribution using remote sensing imagery and location-based data

NASA Astrophysics Data System (ADS)

Song, J.; Prishchepov, A. V.

2017-12-01

Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models, confirming that GWR models demonstrate better prediction accuracy. So this method provide detailed population density information for microscale citizen studies.

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

PubMed

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Nutrition, Balance and Fear of Falling as Predictors of Risk for Falls among Filipino Elderly in Nursing Homes: A Structural Equation Model (SEM)

ERIC Educational Resources Information Center

de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.

2013-01-01

While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…

Psychometric Properties and Validation of the Arabic Social Media Addiction Scale.

PubMed

Al-Menayes, Jamal

2015-01-01

This study investigated the psychometric properties of the Arabic version of the SMAS. SMAS is a variant of IAT customized to measure addiction to social media instead of the Internet as a whole. Using a self-report instrument on a cross-sectional sample of undergraduate students, the results revealed the following. First, the exploratory factor analysis showed that a three-factor model fits the data well. Second, concurrent validity analysis showed the SMAS to be a valid measure of social media addiction. However, further studies and data should verify the hypothesized model. Finally, this study showed that the Arabic version of the SMAS is a valid and reliable instrument for use in measuring social media addiction in the Arab world.

Psychometric Properties and Validation of the Arabic Social Media Addiction Scale

PubMed Central

Al-Menayes, Jamal

2015-01-01

This study investigated the psychometric properties of the Arabic version of the SMAS. SMAS is a variant of IAT customized to measure addiction to social media instead of the Internet as a whole. Using a self-report instrument on a cross-sectional sample of undergraduate students, the results revealed the following. First, the exploratory factor analysis showed that a three-factor model fits the data well. Second, concurrent validity analysis showed the SMAS to be a valid measure of social media addiction. However, further studies and data should verify the hypothesized model. Finally, this study showed that the Arabic version of the SMAS is a valid and reliable instrument for use in measuring social media addiction in the Arab world. PMID:26347848

A three-dimensional finite element analysis for overdenture attachments supported by teeth and/or mini dental implants.

PubMed

Fatalla, Abdalbseet A; Song, Ke; Du, Tianfeng; Cao, Yingguang

2012-12-01

The aim of this study was to establish the optimum design and attachment combination to support an overdenture with minimal stress and flexing produced in the alveolar bone surrounding any natural teeth and/or mini dental implants. Twelve models were included in the study: the six main models (A, B, C, D, E, and F) were categorized according to the support designs of the overdenture prosthesis, and each model was further subdivided according to the attachment combinations into model 1: with Dalbo elliptic and/or O-ring attachments only and model 2: with flexible acrylic attachments. Vertical loads (35 N) and 17.5 N lateral loads under static conditions were applied to the models to simulate the occlusal forces following the concept of lingualized occlusion. All conditions were created using a finite element software program. Maximum von Mises stress at the level of the attachments and at the bone support foundation interfaces were compared in all 12 models. The flexing of the mandible and the attachments were also compared qualitatively. Stress on these models was analyzed after the given loading condition. The results showed that the model with three freestanding mini dental implants and flexible acrylic attachments showed the lowest von Mises stress and flexing, while the models with four freestanding mini dental implants and O-ring attachments showed the highest von Mises stress. Three freestanding mini dental implants with flexible acrylic attachment systems supporting an overdenture were better choices than four mini dental implants with O-ring attachment systems, which showed the maximum flexing and stress values in this qualitative comparison. © 2012 by the American College of Prosthodontists.

Simple Statistical Model to Quantify Maximum Expected EMC in Spacecraft and Avionics Boxes

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Bremner, Paul

2014-01-01

This study shows cumulative distribution function (CDF) comparisons of composite a fairing electromagnetic field data obtained by computational electromagnetic 3D full wave modeling and laboratory testing. Test and model data correlation is shown. In addition, this presentation shows application of the power balance and extention of this method to predict the variance and maximum exptected mean of the E-field data. This is valuable for large scale evaluations of transmission inside cavities.

Estimating animal resource selection from telemetry data using point process models

USGS Publications Warehouse

Johnson, Devin S.; Hooten, Mevin B.; Kuhn, Carey E.

2013-01-01

To demonstrate the analysis of telemetry data with the point process approach, we analysed a data set of telemetry locations from northern fur seals (Callorhinus ursinus) in the Pribilof Islands, Alaska. Both a space–time and an aggregated space-only model were fitted. At the individual level, the space–time analysis showed little selection relative to the habitat covariates. However, at the study area level, the space-only model showed strong selection relative to the covariates.

General solutions of the supersymmetric ℂP{sup 2} sigma model and its generalisation to ℂP{sup N−1}

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

Delisle, L., E-mail: laurent.delisle@imj-prg.fr; Hussin, V., E-mail: hussin@dms.umontreal.ca; Centre de Recherches Mathématiques, Université de Montréal, C.P. 6128, Succ. Centre-ville, Montréal, Québec H3C 3J7

A new approach for the construction of finite action solutions of the supersymmetric ℂP{sup N−1} sigma model is presented. We show that this approach produces more non-holomorphic solutions than those obtained in previous approaches. We study the ℂP{sup 2} model in detail and present its solutions in an explicit form. We also show how to generalise this construction to N > 3.

Likelihood ratio decisions in memory: three implied regularities.

PubMed

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Astrophysical and Cosmological Consequences of the Dynamical Localization of Gravity

NASA Astrophysics Data System (ADS)

Germani, Cristiano

2003-11-01

In this thesis I review cosmological and astrophysical exact models for Randall-Sundrum-type braneworlds and their physical implications. I present new insights and show their analogies with quantum theories via the holographic idea. In astrophysics I study the two fundamental models of a spherically symmetric static star and spherically symmetric collapsing objects. I show how matching for the pressure of a static star encodes braneworld effects. In addition I study the problem of the vacuum exterior conjecturing a uniqueness theorem. Furthermore I show that a collapsing dust cloud in the braneworld has a non-static exterior, in contrast to the General Relativistic case. This non-static behaviour is linked to the presence of a "surplus potential energy" that must be released, producing a non-zero flux of energy. Via holography this can be connected with the Hawking process, giving an indirect measure of the brane tension. In cosmology I investigate the generalization of the Randall-Sundrum-type model obtained by introducing the Gauss-Bonnet combination into the action. I elucidate the junction conditions necessary to study the brane model and obtain the cosmological dynamics, showing that, even in the thin shell limit for the brane, the Gauss-Bonnet term implies a non-trivial internal structure for the matter and geometry distributions. Independently of the gravitational theory used, I show how to derive the modified Friedman equation and how it is related to the black hole solution of the theory. Via holography I also show how to interpret quantum mechanically the mass of this black hole from a four-dimensional perspective in the simplest Randall-Sundrum-type scenario.

Computational fluid dynamics analysis of cyclist aerodynamics: performance of different turbulence-modelling and boundary-layer modelling approaches.

PubMed

Defraeye, Thijs; Blocken, Bert; Koninckx, Erwin; Hespel, Peter; Carmeliet, Jan

2010-08-26

This study aims at assessing the accuracy of computational fluid dynamics (CFD) for applications in sports aerodynamics, for example for drag predictions of swimmers, cyclists or skiers, by evaluating the applied numerical modelling techniques by means of detailed validation experiments. In this study, a wind-tunnel experiment on a scale model of a cyclist (scale 1:2) is presented. Apart from three-component forces and moments, also high-resolution surface pressure measurements on the scale model's surface, i.e. at 115 locations, are performed to provide detailed information on the flow field. These data are used to compare the performance of different turbulence-modelling techniques, such as steady Reynolds-averaged Navier-Stokes (RANS), with several k-epsilon and k-omega turbulence models, and unsteady large-eddy simulation (LES), and also boundary-layer modelling techniques, namely wall functions and low-Reynolds number modelling (LRNM). The commercial CFD code Fluent 6.3 is used for the simulations. The RANS shear-stress transport (SST) k-omega model shows the best overall performance, followed by the more computationally expensive LES. Furthermore, LRNM is clearly preferred over wall functions to model the boundary layer. This study showed that there are more accurate alternatives for evaluating flow around bluff bodies with CFD than the standard k-epsilon model combined with wall functions, which is often used in CFD studies in sports. 2010 Elsevier Ltd. All rights reserved.

Overshoot in biological systems modelled by Markov chains: a non-equilibrium dynamic phenomenon.

PubMed

Jia, Chen; Qian, Minping; Jiang, Daquan

2014-08-01

A number of biological systems can be modelled by Markov chains. Recently, there has been an increasing concern about when biological systems modelled by Markov chains will perform a dynamic phenomenon called overshoot. In this study, the authors found that the steady-state behaviour of the system will have a great effect on the occurrence of overshoot. They showed that overshoot in general cannot occur in systems that will finally approach an equilibrium steady state. They further classified overshoot into two types, named as simple overshoot and oscillating overshoot. They showed that except for extreme cases, oscillating overshoot will occur if the system is far from equilibrium. All these results clearly show that overshoot is a non-equilibrium dynamic phenomenon with energy consumption. In addition, the main result in this study is validated with real experimental data.

Induced Pathogen Resistance in Bean Plants: A Model for Studying "Vaccination" in the Classroom.

ERIC Educational Resources Information Center

Goetsch, Emily; Mathias, Christine; Mosley, Sydnie; Shull, Meredith; Brock, David L.

2002-01-01

Shows how the tobacco mosaic virus can be used in conjunction with the common bean plant Phaseolus vulgaris to provide a discernable, experimental model that students can use to study induced resistance. (Contains 17 references.) (DDR)

Exploring different strategies for imbalanced ADME data problem: case study on Caco-2 permeability modeling.

PubMed

Pham-The, Hai; Casañola-Martin, Gerardo; Garrigues, Teresa; Bermejo, Marival; González-Álvarez, Isabel; Nguyen-Hai, Nam; Cabrera-Pérez, Miguel Ángel; Le-Thi-Thu, Huong

2016-02-01

In many absorption, distribution, metabolism, and excretion (ADME) modeling problems, imbalanced data could negatively affect classification performance of machine learning algorithms. Solutions for handling imbalanced dataset have been proposed, but their application for ADME modeling tasks is underexplored. In this paper, various strategies including cost-sensitive learning and resampling methods were studied to tackle the moderate imbalance problem of a large Caco-2 cell permeability database. Simple physicochemical molecular descriptors were utilized for data modeling. Support vector machine classifiers were constructed and compared using multiple comparison tests. Results showed that the models developed on the basis of resampling strategies displayed better performance than the cost-sensitive classification models, especially in the case of oversampling data where misclassification rates for minority class have values of 0.11 and 0.14 for training and test set, respectively. A consensus model with enhanced applicability domain was subsequently constructed and showed improved performance. This model was used to predict a set of randomly selected high-permeability reference drugs according to the biopharmaceutics classification system. Overall, this study provides a comparison of numerous rebalancing strategies and displays the effectiveness of oversampling methods to deal with imbalanced permeability data problems.

[A simulation study with finite element model on the unequal loss of peripheral vision caused by acceleration].

PubMed

Geng, Xiaoqi; Liu, Xiaoyu; Liu, Songyang; Xu, Yan; Zhao, Xianliang; Wang, Jie; Fan, Yubo

2017-04-01

An unequal loss of peripheral vision may happen with high sustaining multi-axis acceleration, leading to a great potential flight safety hazard. In the present research, finite element method was used to study the mechanism of unequal loss of peripheral vision. Firstly, a 3D geometric model of skull was developed based on the adult computer tomography (CT) images. The model of double eyes was created by mirroring with the previous right eye model. Then, the double-eye model was matched to the skull model, and fat was filled between eyeballs and skull. Acceleration loads of head-to-foot (G z ), right-to-left (G y ), chest-to-back (G x ) and multi-axis directions were applied to the current model to simulate dynamic response of retina by explicit dynamics solution. The results showed that the relative strain of double eyes was 25.7% under multi-axis acceleration load. Moreover, the strain distributions showed a significant difference among acceleration loaded in different directions. It indicated that a finite element model of double eyes was an effective means to study the mechanism of an unequal loss of peripheral vision at sustaining high multi-axis acceleration.

High scale impact in alignment and decoupling in two-Higgs-doublet models

NASA Astrophysics Data System (ADS)

Basler, Philipp; Ferreira, Pedro M.; Mühlleitner, Margarete; Santos, Rui

2018-05-01

The two-Higgs-doublet model (2HDM) provides an excellent benchmark to study physics beyond the Standard Model (SM). In this work, we discuss how the behavior of the model at high-energy scales causes it to have a scalar with properties very similar to those of the SM—which means the 2HDM can be seen to naturally favor a decoupling or alignment limit. For a type II 2HDM, we show that requiring the model to be theoretically valid up to a scale of 1 TeV, by studying the renormalization group equations (RGE) of the parameters of the model, causes a significant reduction in the allowed magnitude of the quartic couplings. This, combined with B -physics bounds, forces the model to be naturally decoupled. As a consequence, any nondecoupling limits in type II, like the wrong-sign scenario, are excluded. On the contrary, even with the very constraining limits for the Higgs couplings from the LHC, the type I model can deviate substantially from alignment. An RGE analysis similar to that made for type II shows, however, that requiring a single scalar to be heavier than about 500 GeV would be sufficient for the model to be decoupled. Finally, we show that the 2HDM is stable up to the Planck scale independently of which of the C P -even scalars is the discovered 125 GeV Higgs boson.

Projections of Rainfall and Temperature from CMIP5 Models over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Ragi, A. R.

2014-12-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

Projections of Rainfall and Surface Temperature from CMIP5 Models under RCP4.5 and 8.5 over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Charan Pattnayak, Kanhu; Kar, Sarat Chandra; Kumari Pattnayak, Rashmita

2015-04-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

Analysis on the crime model using dynamical approach

NASA Astrophysics Data System (ADS)

Mohammad, Fazliza; Roslan, Ummu'Atiqah Mohd

2017-08-01

A research is carried out to analyze a dynamical model of the spread crime system. A Simplified 2-Dimensional Model is used in this research. The objectives of this research are to investigate the stability of the model of the spread crime, to summarize the stability by using a bifurcation analysis and to study the relationship of basic reproduction number, R0 with the parameter in the model. Our results for stability of equilibrium points shows that we have two types of stability, which are asymptotically stable and saddle node. While the result for bifurcation analysis shows that the number of criminally active and incarcerated increases as we increase the value of a parameter in the model. The result for the relationship of R0 with the parameter shows that as the parameter increases, R0 increase too, and the rate of crime increase too.

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

The development of a probabilistic approach to forecast coastal change

USGS Publications Warehouse

Lentz, Erika E.; Hapke, Cheryl J.; Rosati, Julie D.; Wang, Ping; Roberts, Tiffany M.

2011-01-01

This study demonstrates the applicability of a Bayesian probabilistic model as an effective tool in predicting post-storm beach changes along sandy coastlines. Volume change and net shoreline movement are modeled for two study sites at Fire Island, New York in response to two extratropical storms in 2007 and 2009. Both study areas include modified areas adjacent to unmodified areas in morphologically different segments of coast. Predicted outcomes are evaluated against observed changes to test model accuracy and uncertainty along 163 cross-shore transects. Results show strong agreement in the cross validation of predictions vs. observations, with 70-82% accuracies reported. Although no consistent spatial pattern in inaccurate predictions could be determined, the highest prediction uncertainties appeared in locations that had been recently replenished. Further testing and model refinement are needed; however, these initial results show that Bayesian networks have the potential to serve as important decision-support tools in forecasting coastal change.

Validity of the Eating Attitude Test among Exercisers.

PubMed

Lane, Helen J; Lane, Andrew M; Matheson, Hilary

2004-12-01

Theory testing and construct measurement are inextricably linked. To date, no published research has looked at the factorial validity of an existing eating attitude inventory for use with exercisers. The Eating Attitude Test (EAT) is a 26-item measure that yields a single index of disordered eating attitudes. The original factor analysis showed three interrelated factors: Dieting behavior (13-items), oral control (7-items), and bulimia nervosa-food preoccupation (6-items). The primary purpose of the study was to examine the factorial validity of the EAT among a sample of exercisers. The second purpose was to investigate relationships between eating attitudes scores and selected psychological constructs. In stage one, 598 regular exercisers completed the EAT. Confirmatory factor analysis (CFA) was used to test the single-factor, a three-factor model, and a four-factor model, which distinguished bulimia from food pre-occupation. CFA of the single-factor model (RCFI = 0.66, RMSEA = 0.10), the three-factor-model (RCFI = 0.74; RMSEA = 0.09) showed poor model fit. There was marginal fit for the 4-factor model (RCFI = 0.91, RMSEA = 0.06). Results indicated five-items showed poor factor loadings. After these 5-items were discarded, the three models were re-analyzed. CFA results indicated that the single-factor model (RCFI = 0.76, RMSEA = 0.10) and three-factor model (RCFI = 0.82, RMSEA = 0.08) showed poor fit. CFA results for the four-factor model showed acceptable fit indices (RCFI = 0.98, RMSEA = 0.06). Stage two explored relationships between EAT scores, mood, self-esteem, and motivational indices toward exercise in terms of self-determination, enjoyment and competence. Correlation results indicated that depressed mood scores positively correlated with bulimia and dieting scores. Further, dieting was inversely related with self-determination toward exercising. Collectively, findings suggest that a 21-item four-factor model shows promising validity coefficients among exercise participants, and that future research is needed to investigate eating attitudes among samples of exercisers. Key PointsValidity of psychometric measures should be thoroughly investigated. Researchers should not assume that a scale validation on one sample will show the same validity coefficients in a different population.The Eating Attitude Test is a commonly used scale. The present study shows a revised 21-item scale was suitable for exercisers.Researchers using the Eating Attitude Test should use subscales of Dieting, Oral control, Food pre-occupation, and Bulimia.Future research should involve qualitative techniques and interview exercise participants to explore the nature of eating attitudes.

Bifactor Models Show a Superior Model Fit: Examination of the Factorial Validity of Parent-Reported and Self-Reported Symptoms of Attention-Deficit/Hyperactivity Disorders in Children and Adolescents.

PubMed

Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred

2016-01-01

Various studies have demonstrated that bifactor models yield better solutions than models with correlated factors. However, the kind of bifactor model that is most appropriate is yet to be examined. The current study is the first to test bifactor models across the full age range (11-18 years) of adolescents using self-reports, and the first to test bifactor models with German subjects and German questionnaires. The study sample included children and adolescents aged between 6 and 18 years recruited from a German clinical sample (n = 1,081) and a German community sample (n = 642). To examine the factorial validity, we compared unidimensional, correlated factors and higher-order and bifactor models and further tested a modified incomplete bifactor model for measurement invariance. Bifactor models displayed superior model fit statistics compared to correlated factor models or second-order models. However, a more parsimonious incomplete bifactor model with only 2 specific factors (inattention and impulsivity) showed a good model fit and a better factor structure than the other bifactor models. Scalar measurement invariance was given in most group comparisons. An incomplete bifactor model would suggest that the specific inattention and impulsivity factors represent entities separable from the general attention-deficit/hyperactivity disorder construct and might, therefore, give way to a new approach to subtyping of children beyond and above attention-deficit/hyperactivity disorder. © 2016 S. Karger AG, Basel.

Essential information: Uncertainty and optimal control of Ebola outbreaks

USGS Publications Warehouse

Li, Shou-Li; Bjornstad, Ottar; Ferrari, Matthew J.; Mummah, Riley; Runge, Michael C.; Fonnesbeck, Christopher J.; Tildesley, Michael J.; Probert, William J. M.; Shea, Katriona

2017-01-01

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Essential information: Uncertainty and optimal control of Ebola outbreaks.

PubMed

Li, Shou-Li; Bjørnstad, Ottar N; Ferrari, Matthew J; Mummah, Riley; Runge, Michael C; Fonnesbeck, Christopher J; Tildesley, Michael J; Probert, William J M; Shea, Katriona

2017-05-30

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models.

PubMed

Chen, Han; Wang, Chaolong; Conomos, Matthew P; Stilp, Adrienne M; Li, Zilin; Sofer, Tamar; Szpiro, Adam A; Chen, Wei; Brehm, John M; Celedón, Juan C; Redline, Susan; Papanicolaou, George J; Thornton, Timothy A; Laurie, Cathy C; Rice, Kenneth; Lin, Xihong

2016-04-07

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

A study of finite mixture model: Bayesian approach on financial time series data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

SEIIrR: Drug abuse model with rehabilitation

NASA Astrophysics Data System (ADS)

Sutanto, Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari

2017-05-01

Drug abuse in the world quite astonish and tend to increase. The increase and decrease on the number of drug abusers showed a pattern of spread that had the same characteristics with patterns of spread of infectious disease. The susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) epidemic models for infectious disease was developed to study social epidemic. In this paper, SEIR model for disease epidemic was developed to study drug abuse epidemic with rehabilitation treatment. The aims of this paper were to analogize susceptible exposed infected isolated recovered (SEIIrR) model on the drug abusers, to determine solutions of the model, to determine equilibrium point, and to do simulation on β. The solutions of SEIIrR model was determined by using fourth order of Runge-Kutta algorithm, equilibrium point obtained was free-drug equilibrium point. Solutions of SEIIrR showed that the model was able to suppress the spread of drug abuse. The increasing value of contact rate was not affect the number of infected individuals due to rehabilitation treatment.

FACTORS INFLUENCING PREDICTION OF BROMODICHLOROMETHANE (BDCM) IN EXHALED BREATH: FURTHER EVALUATION OF A HUMAN BDCM PBPK MODEL

EPA Science Inventory

Confidence in the predictive capability of a PBPK model is increased when the model is demonstrated to predict multiple pharmacokinetic outcomes from diverse studies under different exposure conditions. We previously showed that our multi-route human BDCM PBPK model adequately (w...

Black Model Appearance and Product Evaluations.

ERIC Educational Resources Information Center

Kerin, Roger A.

1979-01-01

Examines a study of how human models affect the impression conveyed by an advertisement, particularly the effect of a Black model's physical characteristics on product evaluations among Black and White females.Results show that the physical appearance of the model influenced impressions of product quality and suitability for personal use. (JMF)

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

ERIC Educational Resources Information Center

Mulder, Yvonne G.; Lazonder, Ard W.; de Jong, Ton; Anjewierden, Anjo; Bollen, Lars

2012-01-01

Model progression denotes the organization of the inquiry learning process in successive phases of increasing complexity. This study investigated the effectiveness of model progression in general, and explored the added value of either broadening or narrowing students' possibilities to change model progression phases. Results showed that…

On the Bayesian Nonparametric Generalization of IRT-Type Models

ERIC Educational Resources Information Center

San Martin, Ernesto; Jara, Alejandro; Rolin, Jean-Marie; Mouchart, Michel

2011-01-01

We study the identification and consistency of Bayesian semiparametric IRT-type models, where the uncertainty on the abilities' distribution is modeled using a prior distribution on the space of probability measures. We show that for the semiparametric Rasch Poisson counts model, simple restrictions ensure the identification of a general…

Nasal high flow clears anatomical dead space in upper airway models

PubMed Central

Celik, Gülnaz; Feng, Sheng; Bartenstein, Peter; Meyer, Gabriele; Eickelberg, Oliver; Schmid, Otmar; Tatkov, Stanislav

2015-01-01

Recent studies showed that nasal high flow (NHF) with or without supplemental oxygen can assist ventilation of patients with chronic respiratory and sleep disorders. The hypothesis of this study was to test whether NHF can clear dead space in two different models of the upper nasal airways. The first was a simple tube model consisting of a nozzle to simulate the nasal valve area, connected to a cylindrical tube to simulate the nasal cavity. The second was a more complex anatomically representative upper airway model, constructed from segmented CT-scan images of a healthy volunteer. After filling the models with tracer gases, NHF was delivered at rates of 15, 30, and 45 l/min. The tracer gas clearance was determined using dynamic infrared CO2 spectroscopy and 81mKr-gas radioactive gamma camera imaging. There was a similar tracer-gas clearance characteristic in the tube model and the upper airway model: clearance half-times were below 1.0 s and decreased with increasing NHF rates. For both models, the anterior compartments demonstrated faster clearance levels (half-times < 0.5 s) and the posterior sections showed slower clearance (half-times < 1.0 s). Both imaging methods showed similar flow-dependent tracer-gas clearance in the models. For the anatomically based model, there was complete tracer-gas removal from the nasal cavities within 1.0 s. The level of clearance in the nasal cavities increased by 1.8 ml/s for every 1.0 l/min increase in the rate of NHF. The study has demonstrated the fast-occurring clearance of nasal cavities by NHF therapy, which is capable of reducing of dead space rebreathing. PMID:25882385

[Establishment of a 3D finite element model of human skull using MSCT images and mimics software].

PubMed

Huang, Ping; Li, Zheng-dong; Shao, Yu; Zou, Dong-hua; Liu, Ning-guo; Li, Li; Chen, Yuan-yuan; Wan, Lei; Chen, Yi-jiu

2011-02-01

To establish a human 3D finite element skull model, and to explore its value in biomechanics analysis. The cadaveric head was scanned and then 3D skull model was created using Mimics software based on 2D CT axial images. The 3D skull model was optimized by preprocessor along with creation of the surface and volume meshes. The stress changes, after the head was struck by an object or the head hit the ground directly, were analyzed using ANSYS software. The original 3D skull model showed a large number of triangles with a poor quality and high similarity with the real head, while the optimized model showed high quality surface and volume meshes with a small number of triangles comparatively. The model could show the local and global stress changes effectively. The human 3D skull model can be established using MSCT and Mimics software and provides a good finite element model for biomechanics analysis. This model may also provide a base for the study of head stress changes following different forces.

Students’ mental model on heat convection concept and its relation with students conception on heat and temperature

NASA Astrophysics Data System (ADS)

Amalia, R.; Sari, I. M.; Sinaga, P.

2017-02-01

This research depended by previous studies that only to find out the misconceptions of students without figuring out the mechanism of the misconceptions. The mechanism of misconceptions can be studied more deeply with mental models. The purpose of this study was to find students ‘mental models of heat convection and its relation with students conception on heat and temperature. The method used in this study is exploratory mixed method design that implemented in one of the high schools in Bandung. The results showed that 7 mental models of heat convection in Chiou’s study (2013), only first model (diffusion-based convention), third model (evenly distributed convection) and fifth model (warmness topped convection II) were found and model hybrid convection as a new mental model. In addition, no specific relationship between mental models and categories of students’ conceptions on heat and temperature.

The contribution of CEOP data to the understanding and modeling of monsoon systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

The Contribution of CEOP Data to the Understanding and Modeling of Monsoon Systems

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2005-01-01

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validaintg models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of, key components of the convective and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variabillity, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Coexistence of Reward and Unsupervised Learning During the Operant Conditioning of Neural Firing Rates

PubMed Central

Kerr, Robert R.; Grayden, David B.; Thomas, Doreen A.; Gilson, Matthieu; Burkitt, Anthony N.

2014-01-01

A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditioning, are performed by the brain. Typical and well studied examples of operant conditioning, in which the firing rates of individual cortical neurons in monkeys are increased using rewards, provide an opportunity for insight into this. Studies of reward-modulated spike-timing-dependent plasticity (RSTDP), and of other models such as R-max, have reproduced this learning behavior, but they have assumed that no unsupervised learning is present (i.e., no learning occurs without, or independent of, rewards). We show that these models cannot elicit firing rate reinforcement while exhibiting both reward learning and ongoing, stable unsupervised learning. To fix this issue, we propose a new RSTDP model of synaptic plasticity based upon the observed effects that dopamine has on long-term potentiation and depression (LTP and LTD). We show, both analytically and through simulations, that our new model can exhibit unsupervised learning and lead to firing rate reinforcement. This requires that the strengthening of LTP by the reward signal is greater than the strengthening of LTD and that the reinforced neuron exhibits irregular firing. We show the robustness of our findings to spike-timing correlations, to the synaptic weight dependence that is assumed, and to changes in the mean reward. We also consider our model in the differential reinforcement of two nearby neurons. Our model aligns more strongly with experimental studies than previous models and makes testable predictions for future experiments. PMID:24475240

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

PubMed

Belem, Mahamadou; Saqalli, Mehdi

2017-11-01

This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

Water quality modeling for urban reach of Yamuna river, India (1999-2009), using QUAL2Kw

NASA Astrophysics Data System (ADS)

Sharma, Deepshikha; Kansal, Arun; Pelletier, Greg

2017-06-01

The study was to characterize and understand the water quality of the river Yamuna in Delhi (India) prior to an efficient restoration plan. A combination of collection of monitored data, mathematical modeling, sensitivity, and uncertainty analysis has been done using the QUAL2Kw, a river quality model. The model was applied to simulate DO, BOD, total coliform, and total nitrogen at four monitoring stations, namely Palla, Old Delhi Railway Bridge, Nizamuddin, and Okhla for 10 years (October 1999-June 2009) excluding the monsoon seasons (July-September). The study period was divided into two parts: monthly average data from October 1999-June 2004 (45 months) were used to calibrate the model and monthly average data from October 2005-June 2009 (45 months) were used to validate the model. The R2 for CBODf and TN lies within the range of 0.53-0.75 and 0.68-0.83, respectively. This shows that the model has given satisfactory results in terms of R2 for CBODf, TN, and TC. Sensitivity analysis showed that DO, CBODf, TN, and TC predictions are highly sensitive toward headwater flow and point source flow and quality. Uncertainty analysis using Monte Carlo showed that the input data have been simulated in accordance with the prevalent river conditions.

Effectiveness of Video Modeling Provided by Mothers in Teaching Play Skills to Children with Autism

ERIC Educational Resources Information Center

Besler, Fatma; Kurt, Onur

2016-01-01

Video modeling is an evidence-based practice that can be used to provide instruction to individuals with autism. Studies show that this instructional practice is effective in teaching many types of skills such as self-help skills, social skills, and academic skills. However, in previous studies, videos used in the video modeling process were…

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

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

Schalk, W.W. III

Early actions of emergency responders during hazardous material releases are intended to assess contamination and potential public exposure. As measurements are collected, an integration of model calculations and measurements can assist to better understand the situation. This study applied a high resolution version of the operational 3-D numerical models used by Lawrence Livermore National Laboratory to a limited meteorological and tracer data set to assist in the interpretation of the dispersion pattern on a 140 km scale. The data set was collected from a tracer release during the morning surface inversion and transition period in the complex terrain of themore » Snake River Plain near Idaho Falls, Idaho in November 1993 by the United States Air Force. Sensitivity studies were conducted to determine model input parameters that best represented the study environment. These studies showed that mixing and boundary layer heights, atmospheric stability, and rawinsonde data are the most important model input parameters affecting wind field generation and tracer dispersion. Numerical models and limited measurement data were used to interpret dispersion patterns through the use of data analysis, model input determination, and sensitivity studies. Comparison of the best-estimate calculation to measurement data showed that model results compared well with the aircraft data, but had moderate success with the few surface measurements taken. The moderate success of the surface measurement comparison, may be due to limited downward mixing of the tracer as a result of the model resolution determined by the domain size selected to study the overall plume dispersion. 8 refs., 40 figs., 7 tabs.« less

Modelling of groundwater quality using bicarbonate chemical parameter in Netravathi and Gurpur river confluence, India

NASA Astrophysics Data System (ADS)

Sylus, K. J.; H., Ramesh

2018-04-01

In the coastal aquifer, seawater intrusion considered the major problem which contaminates freshwater and reduces its quality for domestic use. In order to find seawater intrusion, the groundwater quality analysis for the different chemical parameter was considered as the basic method to find out contamination. This analysis was carried out as per Bureau of Indian standards (2012) and World Health Organisations (1996). In this study, Bicarbonate parameter was considered for groundwater quality analysis which ranges the permissible limit in between 200-600 mg/l. The groundwater system was modelled using Groundwater modelling software (GMS) in which the FEMWATER package used for flow and transport. The FEMWATER package works in the principle of finite element method. The base input data of model include elevation, Groundwater head, First bottom and second bottom of the study area. The modelling results show the spatial occurrence of contamination in the study area of Netravathi and Gurpur river confluence at the various time period. Further, the results of the modelling also show that the contamination occurs up to a distance of 519m towards the freshwater zone of the study area.

Comparison of Individualized Covert Modeling, Self-Control Desensitization, and Study Skills Training for Alleviation of Test Anxiety.

ERIC Educational Resources Information Center

Harris, Gina; Johhson, Suzanne Bennett

1980-01-01

Individualized covert modeling and self-control desensitization substantially reduced self-reported test anxiety. However, the individualized covert modeling group was the only treatment group that showed significant improvement in academic performance. (Author)

Numerical modelling of the flow in the resin infusion process on the REV scale: A feasibility study

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

Jabbari, M.; Spangenberg, J.; Hattel, J. H.

2016-06-08

The resin infusion process (RIP) has developed as a low cost method for manufacturing large fibre reinforced plastic parts. However, the process still presents some challenges to industry with regards to reliability and repeatability, resulting in expensive and inefficient trial and error development. In this paper, we show the implementation of 2D numerical models for the RIP using the open source simulator DuMu{sup X}. The idea of this study is to present a model which accounts for the interfacial forces coming from the capillary pressure on the so-called representative elementary volume (REV) scale. The model is described in detail andmore » three different test cases — a constant and a tensorial permeability as well as a preform/Balsa domain — are investigated. The results show that the developed model is very applicable for the RIP for manufacturing of composite parts. The idea behind this study is to test the developed model for later use in a real application, in which the preform medium has numerous layers with different material properties.« less

Finding Furfural Hydrogenation Catalysts via Predictive Modelling

PubMed Central

Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

2010-01-01

Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

Informing a hydrological model of the Ogooué with multi-mission remote sensing data

NASA Astrophysics Data System (ADS)

Kittel, Cecile; Bauer-Gottwein, Peter; Nielsen, Karina; Tøttrup, Christian

2017-04-01

Knowledge on hydrological regimes of river basins is crucial for water management. However, data requirements often limit the applicability of hydrological models in basins with scarce in-situ data. Remote sensing provides a unique possibility to acquire information on hydrological variables in these basins. This study explores how multi-mission remote sensing data can inform a hydrological model. The Ogooué basin in Gabon is used as study area. No previous modelling efforts have been conducted for the basin and only historical flow and precipitation observations are available. Publicly available remote sensing observations are used to parametrize, force, calibrate and validate a hydrological model of the Ogooué. The modelling framework used in the study, is a lumped conceptual rainfall-runoff model based on the Budyko framework coupled to a Muskingum routing scheme. Precipitation is a crucial driver of the land-surface water balance, therefore two satellite-based rainfall estimates, Tropical Rainfall Measuring Mission (TRMM) product 3B42 version 7 and Famine Early Warning System - Rainfall Estimate (FEWS-RFE), are compared. The comparison shows good seasonal and spatial agreement between the products; however, TRMM consistently predicts significantly more precipitation: 1726 mm on average per year against 1556 mm for FEWS-RFE. Best modeling results are obtained with the TRMM precipitation forcing. Model calibration combines historical in-situ flow observations and GRACE total water storage observations using the Jet Propulsion Laboratory (JPL) mascon solution in a multi-objective approach. The two models are calibrated using flow duration curves and climatology benchmarks to overcome the lack of simultaneity between simulated and observed discharge. The objectives are aggregated into a global objective function, and the models are calibrated using the Shuffled Complex Evolution Algorithm. Water height observations from drifting orbit altimetry missions are extracted along the river line, using a detailed water mask based on Sentinel-1 SAR imagery. 1399 single CryoSat-2 altimetry observations and 48 ICESat observations are acquired. Additionally, water heights have been measured by the repeat-orbit satellite missions Envisat and Jason-2 at 12 virtual stations along the river. The four missions show generally good agreement in terms of mean annual water height amplitudes. The altimetry observations are used to validate the hydrological model of the Ogooué River. By combining hydrological modelling and remote sensing, new information on an otherwise unstudied basin is obtained. The study shows the potential of using remote sensing observations to parameterize, force, calibrate and validate models of poorly gauged river basins. Specifically, the study shows how Sentinel-1 SAR imagery supports the extraction of satellite altimetry data over rivers. The model can be used to assess climate change scenarios, evaluate hydraulic infrastructure development projects and predict the impact of irrigation diversions.

(Re)evaluating the Implications of the Autoregressive Latent Trajectory Model Through Likelihood Ratio Tests of Its Initial Conditions.

PubMed

Ou, Lu; Chow, Sy-Miin; Ji, Linying; Molenaar, Peter C M

2017-01-01

The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's parameters. In this article, we show that some-but not all-of these interpretational difficulties may be clarified mathematically and tested explicitly via likelihood ratio tests (LRTs) imposed on the initial conditions of the model. We show analytically the nested relations among three variants of the ALT model and the constraints needed to establish equivalences. A Monte Carlo simulation study indicated that LRTs, particularly when used in combination with information criterion measures, can allow researchers to test targeted hypotheses about the functional forms of the change process under study. We further demonstrate when and how such tests may justifiably be used to facilitate our understanding of the underlying process of change using a subsample (N = 3,995) of longitudinal family income data from the National Longitudinal Survey of Youth.

Usefulness of high resolution coastal models for operational oil spill forecast: the Full City accident

NASA Astrophysics Data System (ADS)

Broström, G.; Carrasco, A.; Hole, L. R.; Dick, S.; Janssen, F.; Mattsson, J.; Berger, S.

2011-06-01

Oil spill modeling is considered to be an important decision support system (DeSS) useful for remedial action in case of accidents, as well as for designing the environmental monitoring system that is frequently set up after major accidents. Many accidents take place in coastal areas implying that low resolution basin scale ocean models is of limited use for predicting the trajectories of an oil spill. In this study, we target the oil spill in connection with the Full City accident on the Norwegian south coast and compare three different oil spill models for the area. The result of the analysis is that all models do a satisfactory job. The "standard" operational model for the area is shown to have severe flaws but including an analysis based on a higher resolution model (1.5 km resolution) for the area the model system show results that compare well with observations. The study also shows that an ensemble using three different models is useful when predicting/analyzing oil spill in coastal areas.

One- and multi-segment foot models lead to opposite results on ankle joint kinematics during gait: Implications for clinical assessment.

PubMed

Pothrat, Claude; Authier, Guillaume; Viehweger, Elke; Berton, Eric; Rao, Guillaume

2015-06-01

Biomechanical models representing the foot as a single rigid segment are commonly used in clinical or sport evaluations. However, neglecting internal foot movements could lead to significant inaccuracies on ankle joint kinematics. The present study proposed an assessment of 3D ankle kinematic outputs using two distinct biomechanical models and their application in the clinical flat foot case. Results of the Plug in Gait (one segment foot model) and the Oxford Foot Model (multisegment foot model) were compared for normal children (9 participants) and flat feet children (9 participants). Repeated measures of Analysis of Variance have been performed to assess the Foot model and Group effects on ankle joint kinematics. Significant differences were observed between the two models for each group all along the gait cycle. In particular for the flat feet group, opposite results between the Oxford Foot Model and the Plug in Gait were revealed at heelstrike, with the Plug in Gait showing a 4.7° ankle dorsal flexion and 2.7° varus where the Oxford Foot Model showed a 4.8° ankle plantar flexion and 1.6° valgus. Ankle joint kinematics of the flat feet group was more affected by foot modeling than normal group. Foot modeling appeared to have a strong influence on resulting ankle kinematics. Moreover, our findings showed that this influence could vary depending on the population. Studies involving ankle joint kinematic assessment should take foot modeling with caution. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

PubMed

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Cultural competence in mental health care: a review of model evaluations

PubMed Central

Bhui, Kamaldeep; Warfa, Nasir; Edonya, Patricia; McKenzie, Kwame; Bhugra, Dinesh

2007-01-01

Background Cultural competency is now a core requirement for mental health professionals working with culturally diverse patient groups. Cultural competency training may improve the quality of mental health care for ethnic groups. Methods A systematic review that included evaluated models of professional education or service delivery. Results Of 109 potential papers, only 9 included an evaluation of the model to improve the cultural competency practice and service delivery. All 9 studies were located in North America. Cultural competency included modification of clinical practice and organizational performance. Few studies published their teaching and learning methods. Only three studies used quantitative outcomes. One of these showed a change in attitudes and skills of staff following training. The cultural consultation model showed evidence of significant satisfaction by clinicians using the service. No studies investigated service user experiences and outcomes. Conclusion There is limited evidence on the effectiveness of cultural competency training and service delivery. Further work is required to evaluate improvement in service users' experiences and outcomes. PMID:17266765

External validation of EPIWIN biodegradation models.

PubMed

Posthumus, R; Traas, T P; Peijnenburg, W J G M; Hulzebos, E M

2005-01-01

The BIOWIN biodegradation models were evaluated for their suitability for regulatory purposes. BIOWIN includes the linear and non-linear BIODEG and MITI models for estimating the probability of rapid aerobic biodegradation and an expert survey model for primary and ultimate biodegradation estimation. Experimental biodegradation data for 110 newly notified substances were compared with the estimations of the different models. The models were applied separately and in combinations to determine which model(s) showed the best performance. The results of this study were compared with the results of other validation studies and other biodegradation models. The BIOWIN models predict not-readily biodegradable substances with high accuracy in contrast to ready biodegradability. In view of the high environmental concern of persistent chemicals and in view of the large number of not-readily biodegradable chemicals compared to the readily ones, a model is preferred that gives a minimum of false positives without a corresponding high percentage false negatives. A combination of the BIOWIN models (BIOWIN2 or BIOWIN6) showed the highest predictive value for not-readily biodegradability. However, the highest score for overall predictivity with lowest percentage false predictions was achieved by applying BIOWIN3 (pass level 2.75) and BIOWIN6.

A Comparative Study of Spectral Auroral Intensity Predictions From Multiple Electron Transport Models

NASA Astrophysics Data System (ADS)

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Hecht, James; Solomon, Stanley; Jahn, Jorg-Micha

2018-01-01

It is important to routinely examine and update models used to predict auroral emissions resulting from precipitating electrons in Earth's magnetotail. These models are commonly used to invert spectral auroral ground-based images to infer characteristics about incident electron populations when in situ measurements are unavailable. In this work, we examine and compare auroral emission intensities predicted by three commonly used electron transport models using varying electron population characteristics. We then compare model predictions to same-volume in situ electron measurements and ground-based imaging to qualitatively examine modeling prediction error. Initial comparisons showed differences in predictions by the GLobal airglOW (GLOW) model and the other transport models examined. Chemical reaction rates and radiative rates in GLOW were updated using recent publications, and predictions showed better agreement with the other models and the same-volume data, stressing that these rates are important to consider when modeling auroral processes. Predictions by each model exhibit similar behavior for varying atmospheric constants, energies, and energy fluxes. Same-volume electron data and images are highly correlated with predictions by each model, showing that these models can be used to accurately derive electron characteristics and ionospheric parameters based solely on multispectral optical imaging data.

Modeling of Protection in Dynamic Simulation Using Generic Relay Models and Settings

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

Samaan, Nader A.; Dagle, Jeffery E.; Makarov, Yuri V.

This paper shows how generic protection relay models available in planning tools can be augmented with settings that are based on NERC standards or best engineering practice. Selected generic relay models in Siemens PSS®E have been used in dynamic simulations in the proposed approach. Undervoltage, overvoltage, underfrequency, and overfrequency relays have been modeled for each generating unit. Distance-relay protection was modeled for transmission system protection. Two types of load-shedding schemes were modeled: underfrequency (frequency-responsive non-firm load shedding) and underfrequency and undervoltage firm load shedding. Several case studies are given to show the impact of protection devices on dynamic simulations. Thismore » is useful for simulating cascading outages.« less

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Syntheses of the current model applications for managing water and needs for experimental data and model improvements to enhance these applications

USDA-ARS?s Scientific Manuscript database

This volume of the Advances in Agricultural Systems Modeling series presents 14 different case studies of model applications to help make the best use of limited water in agriculture. These examples show that models have tremendous potential and value in enhancing site-specific water management for ...

[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.

Properties of Traffic Risk Coefficient

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Huang, Hai-Jun; Shang, Hua-Yan; Xue, Yu

2009-10-01

We use the model with the consideration of the traffic interruption probability (Physica A 387(2008)6845) to study the relationship between the traffic risk coefficient and the traffic interruption probability. The analytical and numerical results show that the traffic interruption probability will reduce the traffic risk coefficient and that the reduction is related to the density, which shows that this model can improve traffic security.

Resonant quantum kicked rotor with two internal levels

NASA Astrophysics Data System (ADS)

Hernández, Guzmán; Romanelli, Alejandro

2013-04-01

We study a system consisting of a quantum kicked rotor with an additional degree of freedom. We show analytically and numerically that this model is characterized by its quantum resonances with ballistic spreading and by the entanglement between the internal and momentum degrees of freedom. We conclude that the model shows certain interesting similarities with the standard quantum walk on the line.

Shell model description of heavy nuclei and abnormal collective motions

NASA Astrophysics Data System (ADS)

Qi, Chong

2018-05-01

In this contribution I present systematic calculations on the spectroscopy and electromagnetic transition properties of intermediate-mass and heavy nuclei around 100Sn and 208Pb. We employed the large-scale configuration interaction shell model approach with realistic interactions. Those nuclei are the longest isotopic chains that can be studied by the nuclear shell model. I will show that the yrast spectra of Te isotopes show a vibrational-like equally spaced pattern but the few known E2 transitions show rotational-like behaviour. These kinds of abnormal collective behaviors cannot be reproduced by standard collective models and provide excellent background to study the competition of single-particle and various collective degrees of freedom. Moreover, the calculated B(E2) values for neutron-deficient and heavier Te isotopes show contrasting different behaviours along the yrast line, which may be related to the enhanced neutron-proton correlation when approaching N=50. The deviations between theory and experiment concerning the energies and E2 transition properties of low-lying 0+ and 2+ excited states and isomeric states in those nuclei may provide a constraint on our understanding of nuclear deformation and intruder configuration in that region.

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

power grid modeling scenarios Study Shows Eastern U.S. Power Grid Can Support Upwards of 30% Wind and newly released Eastern Renewable Energy Integration Study (ERGIS) shows that the power grid of the -based study of four potential wind and PV futures and associated operational impacts in the Eastern

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Population pharmacokinetics of aripiprazole in healthy Korean subjects.

PubMed

Jeon, Ji-Young; Chae, Soo-Wan; Kim, Min-Gul

2016-04-01

Aripiprazole is widely used to treat schizophrenia and bipolar disorder. This study aimed to develop a combined population pharmacokinetic model for aripiprazole in healthy Korean subjects and to identify the significant covariates in the pharmacokinetic variability of aripiprazole. Aripiprazole plasma concentrations and demographic data were collected retrospectively from previous bioequivalence studies that were conducted in Chonbuk National University Hospital. Informed consent was obtained from subjects for cytochrome P450 (CYP) genotyping. The population pharmacokinetic parameters of aripiprazole were estimated using nonlinear mixed-effect modeling with first-order conditional estimation with interaction method. The effects of age, sex, weight, height, and CYP genotype were assessed as covariates. A total of 1,508 samples from 88 subjects in three bioequivalence studies were collected. The two-compartment model was adopted, and the final population model showed that the CYP2D6 genotype polymorphism, height and weight significantly affect aripiprazole disposition. The bootstrap and visual predictive check results were evaluated, showing that the accuracy of the pharmacokinetic model was acceptable. A population pharmacokinetic model of aripiprazole was developed for Korean subjects. CYP2D6 genotype polymorphism, weight, and height were included as significant factors affecting aripiprazole disposition. The population pharmacokinetic parameters of aripiprazole estimated in the present study may be useful for individualizing clinical dosages and for studying the concentration-effect relationship of the drug.

Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro.

PubMed

Yang, Yongji; Moser, Michael A J; Zhang, Edwin; Zhang, Wenjun; Zhang, Bing

2018-01-01

The aim of this study was to develop a statistical model for cell death by irreversible electroporation (IRE) and to show that the statistic model is more accurate than the electric field threshold model in the literature using cervical cancer cells in vitro. HeLa cell line was cultured and treated with different IRE protocols in order to obtain data for modeling the statistical relationship between the cell death and pulse-setting parameters. In total, 340 in vitro experiments were performed with a commercial IRE pulse system, including a pulse generator and an electric cuvette. Trypan blue staining technique was used to evaluate cell death after 4 hours of incubation following IRE treatment. Peleg-Fermi model was used in the study to build the statistical relationship using the cell viability data obtained from the in vitro experiments. A finite element model of IRE for the electric field distribution was also built. Comparison of ablation zones between the statistical model and electric threshold model (drawn from the finite element model) was used to show the accuracy of the proposed statistical model in the description of the ablation zone and its applicability in different pulse-setting parameters. The statistical models describing the relationships between HeLa cell death and pulse length and the number of pulses, respectively, were built. The values of the curve fitting parameters were obtained using the Peleg-Fermi model for the treatment of cervical cancer with IRE. The difference in the ablation zone between the statistical model and the electric threshold model was also illustrated to show the accuracy of the proposed statistical model in the representation of ablation zone in IRE. This study concluded that: (1) the proposed statistical model accurately described the ablation zone of IRE with cervical cancer cells, and was more accurate compared with the electric field model; (2) the proposed statistical model was able to estimate the value of electric field threshold for the computer simulation of IRE in the treatment of cervical cancer; and (3) the proposed statistical model was able to express the change in ablation zone with the change in pulse-setting parameters.

The Dynamics of School Change: Response to the Article "Comer's School Development Program in Prince George's Count, Maryland: A Theory-based Evaluation," by Thomas D. Cook et al.

ERIC Educational Resources Information Center

Comer, James P.; Haynes, Norris M.

1999-01-01

Comments on a study of Comer's School Development Model, indicating that the study, as conducted, was not a study of the model but a limited study of the effects of one application of the model's process. In addition, the evaluation was carried out over only 2 years for each group, when experience shows that at least 3 years are necessary to show…

Climate Shocks and Migration: An Agent-Based Modeling Approach.

PubMed

Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-09-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.

Modeling error distributions of growth curve models through Bayesian methods.

PubMed

Zhang, Zhiyong

2016-06-01

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.

Computational fluid dynamic on the temperature simulation of air preheat effect combustion in propane turbulent flame

NASA Astrophysics Data System (ADS)

Elwina; Yunardi; Bindar, Yazid

2018-04-01

this paper presents results obtained from the application of a computational fluid dynamics (CFD) code Fluent 6.3 to modelling of temperature in propane flames with and without air preheat. The study focuses to investigate the effect of air preheat temperature on the temperature of the flame. A standard k-ε model and Eddy Dissipation model are utilized to represent the flow field and combustion of the flame being investigated, respectively. The results of calculations are compared with experimental data of propane flame taken from literature. The results of the study show that a combination of the standard k-ε turbulence model and eddy dissipation model is capable of producing reasonable predictions of temperature, particularly in axial profile of all three flames. Both experimental works and numerical simulation showed that increasing the temperature of the combustion air significantly increases the flame temperature.

Examination of a lumbar spine biomechanical model for assessing axial compression, shear, and bending moment using selected Olympic lifts.

PubMed

Eltoukhy, Moataz; Travascio, Francesco; Asfour, Shihab; Elmasry, Shady; Heredia-Vargas, Hector; Signorile, Joseph

2016-09-01

Loading during concurrent bending and compression associated with deadlift, hang clean and hang snatch lifts carries the potential for injury to the intervertebral discs, muscles and ligaments. This study examined the capacity of a newly developed spinal model to compute shear and compressive forces, and bending moments in lumbar spine for each lift. Five male subjects participated in the study. The spine was modeled as a chain of rigid bodies (vertebrae) connected via the intervertebral discs. Each vertebral reference frame was centered in the center of mass of the vertebral body, and its principal directions were axial, anterior-posterior, and medial-lateral. The results demonstrated the capacity of this spinal model to assess forces and bending moments at and about the lumbar vertebrae by showing the variations among these variables with different lifting techniques. These results show the model's potential as a diagnostic tool.

Finite element modeling of mitral leaflet tissue using a layered shell approximation

PubMed Central

Ratcliffe, Mark B.; Guccione, Julius M.

2012-01-01

The current study presents a finite element model of mitral leaflet tissue, which incorporates the anisotropic material response and approximates the layered structure. First, continuum mechanics and the theory of layered composites are used to develop an analytical representation of membrane stress in the leaflet material. This is done with an existing anisotropic constitutive law from literature. Then, the concept is implemented in a finite element (FE) model by overlapping and merging two layers of transversely isotropic membrane elements in LS-DYNA, which homogenizes the response. The FE model is then used to simulate various biaxial extension tests and out-of-plane pressure loading. Both the analytical and FE model show good agreement with experimental biaxial extension data, and show good mutual agreement. This confirms that the layered composite approximation presented in the current study is able to capture the exponential stiffening seen in both the circumferential and radial directions of mitral leaflets. PMID:22971896

Climate Shocks and Migration: An Agent-Based Modeling Approach

PubMed Central

Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

An evaluation of the Johnson-Cook model to simulate puncture of 7075 aluminum plates.

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

Corona, Edmundo; Orient, George Edgar

The objective of this project was to evaluate the use of the Johnson-Cook strength and failure models in an adiabatic finite element model to simulate the puncture of 7075- T651 aluminum plates that were studied as part of an ASC L2 milestone by Corona et al (2012). The Johnson-Cook model parameters were determined from material test data. The results show a marked improvement, in particular in the calculated threshold velocity between no puncture and puncture, over those obtained in 2012. The threshold velocity calculated using a baseline model is just 4% higher than the mean value determined from experiment, inmore » contrast to 60% in the 2012 predictions. Sensitivity studies showed that the threshold velocity predictions were improved by calibrating the relations between the equivalent plastic strain at failure and stress triaxiality, strain rate and temperature, as well as by the inclusion of adiabatic heating.« less

Revised Atomistic Models of the Crystal Structure of C-S-H with high C/S Ratio

NASA Astrophysics Data System (ADS)

Kovačević, Goran; Nicoleau, Luc; Nonat, André; Veryazov, Valera

2016-09-01

The atomic structure of calcium-silicate-hydrate (C1.67-S-Hx) has been studied. Atomistic C-S-H models suggested in our previous study have been revised in order to perform a direct comparison of energetic stability of the different structures. An extensive set of periodic structures of C-S-H with variation of water content was created, and then optimized using molecular dynamics with reactive force field ReaxFF and quantum chemical semiempirical method PM6. All models show organization of water molecules inside the structure of C-S-H. The new geometries of C-S-H, reported in this paper, show lower relative energy with respect to the geometries from the original definition of C-S-H models. Model that corresponds to calcium enriched tobermorite structure has the lowest relative energy and the density closest to the experimental values.

Activity of a social dynamics model

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Neves, Ubiraci P. C.

2015-10-01

Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.

Continuum modeling of three-dimensional truss-like space structures

NASA Technical Reports Server (NTRS)

Nayfeh, A. H.; Hefzy, M. S.

1978-01-01

A mathematical and computational analysis capability has been developed for calculating the effective mechanical properties of three-dimensional periodic truss-like structures. Two models are studied in detail. The first, called the octetruss model, is a three-dimensional extension of a two-dimensional model, and the second is a cubic model. Symmetry considerations are employed as a first step to show that the specific octetruss model has four independent constants and that the cubic model has two. The actual values of these constants are determined by averaging the contributions of each rod element to the overall structure stiffness. The individual rod member contribution to the overall stiffness is obtained by a three-dimensional coordinate transformation. The analysis shows that the effective three-dimensional elastic properties of both models are relatively close to each other.

Deterministic models for traffic jams

NASA Astrophysics Data System (ADS)

Nagel, Kai; Herrmann, Hans J.

1993-10-01

We study several deterministic one-dimensional traffic models. For integer positions and velocities we find the typical high and low density phases separated by a simple transition. If positions and velocities are continuous variables the model shows self-organized critically driven by the slowest car.

A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

ERIC Educational Resources Information Center

Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

2003-01-01

Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

Effect of nonlinearity in hybrid kinetic Monte Carlo-continuum models.

PubMed

Balter, Ariel; Lin, Guang; Tartakovsky, Alexandre M

2012-01-01

Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a kinetic Monte Carlo (KMC) model for a surface to a finite-difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition-dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition-dissolution model including competitive adsorption, which leads to a nonlinear rate, and show that in this case the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.

Effect of Nonlinearity in Hybrid Kinetic Monte Carlo-Continuum Models

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

Balter, Ariel I.; Lin, Guang; Tartakovsky, Alexandre M.

2012-04-23

Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a KMC model for a surface to a finite difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and also show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition/dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition/dissolution model including competitive adsorption, which leadsmore » to a nonlinear rate, and show that, in this case, the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.« less

Learning Model and Form of Assesment toward the Inferensial Statistical Achievement by Controlling Numeric Thinking Skills

ERIC Educational Resources Information Center

Widiana, I. Wayan; Jampel, I. Nyoman

2016-01-01

This study aimed to find out the effect of learning model and form of assessment toward inferential statistical achievement after controlling numeric thinking skills. This study was quasi experimental study with 130 students as the sample. The data analysis used ANCOVA. After controlling numeric thinking skills, the result of this study show that:…

Comparison of phenology models for predicting the onset of growing season over the Northern Hemisphere.

PubMed

Fu, Yang; Zhang, Haicheng; Dong, Wenjie; Yuan, Wenping

2014-01-01

Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS) a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2) product), we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model), 79% (the Biome-BGC phenology model), 73% (the Number of Growing Days model) and 68% (the Number of Chilling Days-Growing Degree Day model) of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD) showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models.

Comparison of Phenology Models for Predicting the Onset of Growing Season over the Northern Hemisphere

PubMed Central

Fu, Yang; Zhang, Haicheng; Dong, Wenjie; Yuan, Wenping

2014-01-01

Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS) a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2) product), we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model), 79% (the Biome-BGC phenology model), 73% (the Number of Growing Days model) and 68% (the Number of Chilling Days-Growing Degree Day model) of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD) showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models. PMID:25279567

A study of a diffusive model of asset returns and an empirical analysis of financial markets

NASA Astrophysics Data System (ADS)

Alejandro Quinones, Angel Luis

A diffusive model for market dynamics is studied and the predictions of the model are compared to real financial markets. The model has a non-constant diffusion coefficient which depends both on the asset value and the time. A general solution for the distribution of returns is obtained and shown to match the results of computer simulations for two simple cases, piecewise linear and quadratic diffusion. The effects of discreteness in the market dynamics on the model are also studied. For the quadratic diffusion case, a type of phase transition leading to fat tails is observed as the discrete distribution approaches the continuum limit. It is also found that the model captures some of the empirical stylized facts observed in real markets, including fat-tails and scaling behavior in the distribution of returns. An analysis of empirical data for the EUR/USD currency exchange rate and the S&P 500 index is performed. Both markets show time scaling behavior consistent with a value of 1/2 for the Hurst exponent. Finally, the results show that the distribution of returns for the two markets is well fitted by the model, and the corresponding empirical diffusion coefficients are determined.

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.

PubMed

Fredrikson, Matthew; Lantz, Eric; Jha, Somesh; Lin, Simon; Page, David; Ristenpart, Thomas

2014-08-01

We initiate the study of privacy in pharmacogenetics, wherein machine learning models are used to guide medical treatments based on a patient's genotype and background. Performing an in-depth case study on privacy in personalized warfarin dosing, we show that suggested models carry privacy risks, in particular because attackers can perform what we call model inversion : an attacker, given the model and some demographic information about a patient, can predict the patient's genetic markers. As differential privacy (DP) is an oft-proposed solution for medical settings such as this, we evaluate its effectiveness for building private versions of pharmacogenetic models. We show that DP mechanisms prevent our model inversion attacks when the privacy budget is carefully selected . We go on to analyze the impact on utility by performing simulated clinical trials with DP dosing models. We find that for privacy budgets effective at preventing attacks, patients would be exposed to increased risk of stroke, bleeding events, and mortality . We conclude that current DP mechanisms do not simultaneously improve genomic privacy while retaining desirable clinical efficacy, highlighting the need for new mechanisms that should be evaluated in situ using the general methodology introduced by our work.

Three-dimensional printing of Hela cells for cervical tumor model in vitro.

PubMed

Zhao, Yu; Yao, Rui; Ouyang, Liliang; Ding, Hongxu; Zhang, Ting; Zhang, Kaitai; Cheng, Shujun; Sun, Wei

2014-09-01

Advances in three-dimensional (3D) printing have enabled the direct assembly of cells and extracellular matrix materials to form in vitro cellular models for 3D biology, the study of disease pathogenesis and new drug discovery. In this study, we report a method of 3D printing for Hela cells and gelatin/alginate/fibrinogen hydrogels to construct in vitro cervical tumor models. Cell proliferation, matrix metalloproteinase (MMP) protein expression and chemoresistance were measured in the printed 3D cervical tumor models and compared with conventional 2D planar culture models. Over 90% cell viability was observed using the defined printing process. Comparisons of 3D and 2D results revealed that Hela cells showed a higher proliferation rate in the printed 3D environment and tended to form cellular spheroids, but formed monolayer cell sheets in 2D culture. Hela cells in 3D printed models also showed higher MMP protein expression and higher chemoresistance than those in 2D culture. These new biological characteristics from the printed 3D tumor models in vitro as well as the novel 3D cell printing technology may help the evolution of 3D cancer study.

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing

PubMed Central

Fredrikson, Matthew; Lantz, Eric; Jha, Somesh; Lin, Simon; Page, David; Ristenpart, Thomas

2014-01-01

We initiate the study of privacy in pharmacogenetics, wherein machine learning models are used to guide medical treatments based on a patient’s genotype and background. Performing an in-depth case study on privacy in personalized warfarin dosing, we show that suggested models carry privacy risks, in particular because attackers can perform what we call model inversion: an attacker, given the model and some demographic information about a patient, can predict the patient’s genetic markers. As differential privacy (DP) is an oft-proposed solution for medical settings such as this, we evaluate its effectiveness for building private versions of pharmacogenetic models. We show that DP mechanisms prevent our model inversion attacks when the privacy budget is carefully selected. We go on to analyze the impact on utility by performing simulated clinical trials with DP dosing models. We find that for privacy budgets effective at preventing attacks, patients would be exposed to increased risk of stroke, bleeding events, and mortality. We conclude that current DP mechanisms do not simultaneously improve genomic privacy while retaining desirable clinical efficacy, highlighting the need for new mechanisms that should be evaluated in situ using the general methodology introduced by our work. PMID:27077138

A novel grid-based mesoscopic model for evacuation dynamics

NASA Astrophysics Data System (ADS)

Shi, Meng; Lee, Eric Wai Ming; Ma, Yi

2018-05-01

This study presents a novel grid-based mesoscopic model for evacuation dynamics. In this model, the evacuation space is discretised into larger cells than those used in microscopic models. This approach directly computes the dynamic changes crowd densities in cells over the course of an evacuation. The density flow is driven by the density-speed correlation. The computation is faster than in traditional cellular automata evacuation models which determine density by computing the movements of each pedestrian. To demonstrate the feasibility of this model, we apply it to a series of practical scenarios and conduct a parameter sensitivity study of the effect of changes in time step δ. The simulation results show that within the valid range of δ, changing δ has only a minor impact on the simulation. The model also makes it possible to directly acquire key information such as bottleneck areas from a time-varied dynamic density map, even when a relatively large time step is adopted. We use the commercial software AnyLogic to evaluate the model. The result shows that the mesoscopic model is more efficient than the microscopic model and provides more in-situ details (e.g., pedestrian movement pattern) than the macroscopic models.

Treatment of oily waters using vermiculite.

PubMed

Mysore, Deepa; Viraraghavan, Thiruvenkatachari; Jin, Yee-Chung

2005-07-01

The main objective of this study was to examine the removal of oil from water by expanded and hydrophobized vermiculite. A pH of 9 showed a higher removal efficiency of oil by vermiculite. Oil removal efficiencies at pH 9 were found to be 79%, 93%, 90%, 57% for standard mineral oil (SMO), Canola oil (CO), Kutwell oil (KUT45), refinery effluent (RE), respectively, in the case of expanded vermiculite, and 56%, 58%, 47%, 43% for SMO, CO, KUT45 and RE, respectively, for hydrophobized vermiculite. Kinetic data satisfied both the Lagergren and Ho models. Equilibrium studies showed that the Langmuir isotherm was the best-fit isotherm for oil removal by both expanded and hydrophobized vermiculite. The data showed a higher adsorptive capacity by the expanded vermiculite compared to the hydrophobized vermiculite. Desorption studies showed that the expanded vermiculite did not desorb oil to the same extent compared to hydrophobized vermiculite. The Freundlich isotherm was the best-fit model for desorption. Expanded vermiculite showed better retention than hydrophobic vermiculite. The results showed that the expanded vermiculite had a greater affinity for oil than hydrophobized vermiculite.

A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq

NASA Astrophysics Data System (ADS)

Al-Abadi, Alaa M.; Al-Shamma'a, Ayser M.; Aljabbari, Mukdad H.

2017-03-01

In this study, intrinsic groundwater vulnerability for the shallow aquifer in northeastern Missan governorate, south of Iraq is evaluated using commonly used DRASTIC model in framework of GIS environment. Preparation of DRASTIC parameters is attained through gathering data from different sources including field survey, geological and meteorological data, a digital elevation model DEM of the study area, archival database, and published research. The different data used to build DRASTIC model are arranged in a geospatial database using spatial analyst extension of ArcGIS 10.2 software. The obtained results related to the vulnerability to general contaminants show that the study area is characterized by two vulnerability zones: low and moderate. Ninety-four percentage (94 %) of the study area has a low class of groundwater vulnerability to contamination, whereas a total of (6 %) of the study area has moderate vulnerability. The pesticides DRASTIC index map shows that the study area is also characterized by two zones of vulnerability: low and moderate. The DRASTIC map of this version clearly shows that small percentage (13 %) of the study area has low vulnerability to contamination, and most parts have moderate vulnerability (about 87 %). The final results indicate that the aquifer system in the interested area is relatively protected from contamination on the groundwater surface. To mitigate the contamination risks in the moderate vulnerability zones, a protective measure must be put before exploiting the aquifer and before comprehensive agricultural activities begin in the area.

E-Service Quality Evaluation on E-Government Website: Case Study BPJS Kesehatan Indonesia

NASA Astrophysics Data System (ADS)

Rasyid, A.; Alfina, I.

2017-01-01

This research intends to develop a model to evaluate the quality of e-services on e-government. The proposed model consists of seven dimensions: web design, reliability, responsiveness, privacy and security, personalization, information, and ease of use. The model is used to measure the quality of the e-registration of BPJS Kesehatan, an Indonesian government health insurance program. The validation and reliability testing show that of the seven dimensions proposed, only four that suitable for the case study. The result shows that the BPJS Kesehatan e-registration service is good in reliability and responsiveness dimensions, while from web design and ease of use dimensions the e-service still needs to be optimized.

Fast time variations of supernova neutrino signals from 3-dimensional models

DOE PAGES

Lund, Tina; Wongwathanarat, Annop; Janka, Hans -Thomas; ...

2012-11-19

Here, we study supernova neutrino flux variations in the IceCube detector, using 3D models based on a simplified neutrino transport scheme. The hemispherically integrated neutrino emission shows significantly smaller variations compared with our previous study of 2D models, largely because of the reduced activity of the standing accretion shock instability in this set of 3D models which we interpret as a pessimistic extreme. For the studied cases, intrinsic flux variations up to about 100 Hz frequencies could still be detected in a supernova closer than about 2 kpc.

Integrating technology readiness into the expectation-confirmation model: an empirical study of mobile services.

PubMed

Chen, Shih-Chih; Liu, Ming-Ling; Lin, Chieh-Peng

2013-08-01

The aim of this study was to integrate technology readiness into the expectation-confirmation model (ECM) for explaining individuals' continuance of mobile data service usage. After reviewing the ECM and technology readiness, an integrated model was demonstrated via empirical data. Compared with the original ECM, the findings of this study show that the integrated model may offer an ameliorated way to clarify what factors and how they influence the continuous intention toward mobile services. Finally, the major findings are summarized, and future research directions are suggested.

Association between glutathione S-transferase P1 Ile (105) Val gene polymorphism and chronic obstructive pulmonary disease: A meta-analysis based on seventeen case-control studies.

PubMed

Yang, Lingjing; Li, Xixia; Tong, Xiang; Fan, Hong

2015-12-01

Previous studies have shown that glutathione S-transferase P1 (GSTP1) was associated with chronic obstructive pulmonary disease (COPD). However, the association between GSTP1 Ile (105) Val gene polymorphism and COPD remains controversial. To drive a more precise estimation, we performed a meta-analysis based on published case-control studies. An electronic search of PubMed, EMBASE, Cochrane library, Web of Science and China Knowledge Resource Integrated (CNKI) Database for papers on GSTP1 Ile (105) Val gene polymorphism and COPD risk was performed. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association in the homozygote model, heterozygote model, dominant model, recessive model and an additive mode. Statistical heterogeneity, test of publication bias and sensitivity analysis was performed. The software STATA (Version 13.0) was used data analysis. Overall, seventeen studies with 1892 cases and 2012 controls were included in this meta-analysis. The GSTP1 Ile (105) Val polymorphism showed pooled odds ratios for the homozygote comparison (OR = 1.501, 95%CI [0.862, 2.614]), heterozygote comparison (OR = 0.924, 95%CI [0.733, 1.165]), dominant model (OR = 1.003, 95%CI [0.756, 1.331]), recessive model (OR = 1.510, 95%CI [0.934, 2.439]), and an additive model (OR = 1.072, 95%CI [0.822, 1.398]). In conclusion, the current meta-analysis, based on the most updated information, showed no significant association between GSTP1 Ile (105) Val gene polymorphism and COPD risk in any genetic models. The results of subgroup analysis also showed no significant association between GSTP1 Ile (105) Val gene polymorphism and COPD risk in Asian population and Caucasian population. Further studies involving large populations and careful control with age, sex, ethnicity, and cigarette smoking are greatly needed.

Association between glutathione S-transferase P1 Ile (105) Val gene polymorphism and chronic obstructive pulmonary disease: A meta-analysis based on seventeen case–control studies

PubMed Central

Yang, Lingjing; Li, Xixia; Tong, Xiang; Fan, Hong

2015-01-01

Introduction Previous studies have shown that glutathione S-transferase P1 (GSTP1) was associated with chronic obstructive pulmonary disease (COPD). However, the association between GSTP1 Ile (105) Val gene polymorphism and COPD remains controversial. To drive a more precise estimation, we performed a meta-analysis based on published case–control studies. Methods An electronic search of PubMed, EMBASE, Cochrane library, Web of Science and China Knowledge Resource Integrated (CNKI) Database for papers on GSTP1 Ile (105) Val gene polymorphism and COPD risk was performed. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association in the homozygote model, heterozygote model, dominant model, recessive model and an additive mode. Statistical heterogeneity, test of publication bias and sensitivity analysis was performed. The software STATA (Version 13.0) was used data analysis. Results Overall, seventeen studies with 1892 cases and 2012 controls were included in this meta-analysis. The GSTP1 Ile (105) Val polymorphism showed pooled odds ratios for the homozygote comparison (OR = 1.501, 95%CI [0.862, 2.614]), heterozygote comparison (OR = 0.924, 95%CI [0.733, 1.165]), dominant model (OR = 1.003, 95%CI [0.756, 1.331]), recessive model (OR = 1.510, 95%CI [0.934, 2.439]), and an additive model (OR = 1.072, 95%CI [0.822, 1.398]). Conclusions In conclusion, the current meta-analysis, based on the most updated information, showed no significant association between GSTP1 Ile (105) Val gene polymorphism and COPD risk in any genetic models. The results of subgroup analysis also showed no significant association between GSTP1 Ile (105) Val gene polymorphism and COPD risk in Asian population and Caucasian population. Further studies involving large populations and careful control with age, sex, ethnicity, and cigarette smoking are greatly needed. PMID:26504746

Potential effects of climate change on the distribution range of the main silicate sinker of the Southern Ocean.

PubMed

Pinkernell, Stefan; Beszteri, Bánk

2014-08-01

Fragilariopsis kerguelensis, a dominant diatom species throughout the Antarctic Circumpolar Current, is coined to be one of the main drivers of the biological silicate pump. Here, we study the distribution of this important species and expected consequences of climate change upon it, using correlative species distribution modeling and publicly available presence-only data. As experience with SDM is scarce for marine phytoplankton, this also serves as a pilot study for this organism group. We used the maximum entropy method to calculate distribution models for the diatom F. kerguelensis based on yearly and monthly environmental data (sea surface temperature, salinity, nitrate and silicate concentrations). Observation data were harvested from GBIF and the Global Diatom Database, and for further analyses also from the Hustedt Diatom Collection (BRM). The models were projected on current yearly and seasonal environmental data to study current distribution and its seasonality. Furthermore, we projected the seasonal model on future environmental data obtained from climate models for the year 2100. Projected on current yearly averaged environmental data, all models showed similar distribution patterns for F. kerguelensis. The monthly model showed seasonality, for example, a shift of the southern distribution boundary toward the north in the winter. Projections on future scenarios resulted in a moderately to negligibly shrinking distribution area and a change in seasonality. We found a substantial bias in the publicly available observation datasets, which could be reduced by additional observation records we obtained from the Hustedt Diatom Collection. Present-day distribution patterns inferred from the models coincided well with background knowledge and previous reports about F. kerguelensis distribution, showing that maximum entropy-based distribution models are suitable to map distribution patterns for oceanic planktonic organisms. Our scenario projections indicate moderate effects of climate change upon the biogeography of F. kerguelensis.

CFD Analysis of Evaporation-Condensation Phenomenon In an Evaporation Chamber of Natural Vacuum Solar Desalination

NASA Astrophysics Data System (ADS)

Ambarita, H.; Ronowikarto, A. D.; Siregar, R. E. T.; Setyawan, E. Y.

2018-01-01

Desalination technologies is one of solutions for water scarcity. With using renewable energy, like solar energy, wind energy, and geothermal energy, expected will reduce the energy demand. This required study on the modeling and transport parameters determination of natural vacuum solar desalination by using computational fluid dynamics (CFD) method to simulate the model. A three-dimensional case, two-phase model was developed for evaporation-condensation phenomenon in natural vacuum solar desalination. The CFD simulation results were compared with the avalaible experimental data. The simulation results shows inthat there is a phenomenon of evaporation-condensation in an evaporation chamber. From the simulation, the fresh water productivity is 2.21 litre, and from the experimental is 2.1 litre. This study shows there’s an error of magnitude 0.4%. The CFD results also show that, vacuum pressure will degrade the saturation temperature of sea water.

Modeling the Influence of Stitching on Delamination Growth in Stitched Warp-Knit Composite Lap Joints

NASA Technical Reports Server (NTRS)

Glaessgen, E. H.; Raju, I. S.; Poe, C. C., Jr.

1999-01-01

The effect of stitches on the failure of a single lap joint configuration was determined in a combined experimental and analytical study. The experimental study was conducted to determine debond growth under static monotonic loading. The stitches were shown to delay the initiation of the debond and provide load transfer beyond the load necessary to completely debond the stitched lap joint. The strain energy release rates at the debond front were calculated using a finite element-based technique. Models of the unstitched configuration showed significant values of modes I and II across the width of the joint and showed that mode III is zero at the centerline but increases near the free edge. Models of the stitched configuration showed that the stitches effectively reduced mode I to zero, but had less of an effect on modes II and III.

Biomechanical effects of hybrid stabilization on the risk of proximal adjacent-segment degeneration following lumbar spinal fusion using an interspinous device or a pedicle screw-based dynamic fixator.

PubMed

Lee, Chang-Hyun; Kim, Young Eun; Lee, Hak Joong; Kim, Dong Gyu; Kim, Chi Heon

2017-12-01

OBJECTIVE Pedicle screw-rod-based hybrid stabilization (PH) and interspinous device-based hybrid stabilization (IH) have been proposed to prevent adjacent-segment degeneration (ASD) and their effectiveness has been reported. However, a comparative study based on sound biomechanical proof has not yet been reported. The aim of this study was to compare the biomechanical effects of IH and PH on the transition and adjacent segments. METHODS A validated finite element model of the normal lumbosacral spine was used. Based on the normal model, a rigid fusion model was immobilized at the L4-5 level by a rigid fixator. The DIAM or NFlex model was added on the L3-4 segment of the fusion model to construct the IH and PH models, respectively. The developed models simulated 4 different loading directions using the hybrid loading protocol. RESULTS Compared with the intact case, fusion on L4-5 produced 18.8%, 9.3%, 11.7%, and 13.7% increments in motion at L3-4 under flexion, extension, lateral bending, and axial rotation, respectively. Additional instrumentation at L3-4 (transition segment) in hybrid models reduced motion changes at this level. The IH model showed 8.4%, -33.9%, 6.9%, and 2.0% change in motion at the segment, whereas the PH model showed -30.4%, -26.7%, -23.0%, and 12.9%. At L2-3 (adjacent segment), the PH model showed 14.3%, 3.4%, 15.0%, and 0.8% of motion increment compared with the motion in the IH model. Both hybrid models showed decreased intradiscal pressure (IDP) at the transition segment compared with the fusion model, but the pressure at L2-3 (adjacent segment) increased in all loading directions except under extension. CONCLUSIONS Both IH and PH models limited excessive motion and IDP at the transition segment compared with the fusion model. At the segment adjacent to the transition level, PH induced higher stress than IH model. Such differences may eventually influence the likelihood of ASD.

Longitudinal Effects of Embryonic Exposure to Cocaine on Morphology, Cardiovascular Physiology, and Behavior in Zebrafish.

PubMed

Mersereau, Eric J; Boyle, Cody A; Poitra, Shelby; Espinoza, Ana; Seiler, Joclyn; Longie, Robert; Delvo, Lisa; Szarkowski, Megan; Maliske, Joshua; Chalmers, Sarah; Darland, Diane C; Darland, Tristan

2016-05-31

A sizeable portion of the societal drain from cocaine abuse results from the complications of in utero drug exposure. Because of challenges in using humans and mammalian model organisms as test subjects, much debate remains about the impact of in utero cocaine exposure. Zebrafish offer a number of advantages as a model in longitudinal toxicology studies and are quite sensitive physiologically and behaviorally to cocaine. In this study, we have used zebrafish to model the effects of embryonic pre-exposure to cocaine on development and on subsequent cardiovascular physiology and cocaine-induced conditioned place preference (CPP) in longitudinal adults. Larval fish showed a progressive decrease in telencephalic size with increased doses of cocaine. These treated larvae also showed a dose dependent response in heart rate that persisted 24 h after drug cessation. Embryonic cocaine exposure had little effect on overall health of longitudinal adults, but subtle changes in cardiovascular physiology were seen including decreased sensitivity to isoproterenol and increased sensitivity to cocaine. These longitudinal adult fish also showed an embryonic dose-dependent change in CPP behavior, suggesting an increased sensitivity. These studies clearly show that pre-exposure during embryonic development affects subsequent cocaine sensitivity in longitudinal adults.

Hierarchical Bayesian spatial models for alcohol availability, drug "hot spots" and violent crime.

PubMed

Zhu, Li; Gorman, Dennis M; Horel, Scott

2006-12-07

Ecologic studies have shown a relationship between alcohol outlet densities, illicit drug use and violence. The present study examined this relationship in the City of Houston, Texas, using a sample of 439 census tracts. Neighborhood sociostructural covariates, alcohol outlet density, drug crime density and violent crime data were collected for the year 2000, and analyzed using hierarchical Bayesian models. Model selection was accomplished by applying the Deviance Information Criterion. The counts of violent crime in each census tract were modelled as having a conditional Poisson distribution. Four neighbourhood explanatory variables were identified using principal component analysis. The best fitted model was selected as the one considering both unstructured and spatial dependence random effects. The results showed that drug-law violation explained a greater amount of variance in violent crime rates than alcohol outlet densities. The relative risk for drug-law violation was 2.49 and that for alcohol outlet density was 1.16. Of the neighbourhood sociostructural covariates, males of age 15 to 24 showed an effect on violence, with a 16% decrease in relative risk for each increase the size of its standard deviation. Both unstructured heterogeneity random effect and spatial dependence need to be included in the model. The analysis presented suggests that activity around illicit drug markets is more strongly associated with violent crime than is alcohol outlet density. Unique among the ecological studies in this field, the present study not only shows the direction and magnitude of impact of neighbourhood sociostructural covariates as well as alcohol and illicit drug activities in a neighbourhood, it also reveals the importance of applying hierarchical Bayesian models in this research field as both spatial dependence and heterogeneity random effects need to be considered simultaneously.

Networked Ising-Sznajd AR-β Model

NASA Astrophysics Data System (ADS)

Nagao, Tomonori; Ohmiya, Mayumi

2009-09-01

The modified Ising-Sznajd model is studied to clarify the machanism of price formation in the stock market. The conventional Ising-Sznajd model is improved as a small world network with the rewireing probability β(t) which depends on the time. Numerical experiments show that phase transition, regarded as a economical crisis, is inevitable in this model.

The Negative Effects of Positive Reinforcement in Teaching Children with Developmental Delay.

ERIC Educational Resources Information Center

Biederman, Gerald B.; And Others

1994-01-01

This study compared the performance of 12 children (ages 4 to 10) with developmental delay, each trained in 2 tasks, one through interactive modeling (with or without verbal reinforcement) and the other through passive modeling. Results showed that passive modeling produced better rated performance than interactive modeling and that verbal…

Usefulness of high resolution coastal models for operational oil spill forecast: the "Full City" accident

NASA Astrophysics Data System (ADS)

Broström, G.; Carrasco, A.; Hole, L. R.; Dick, S.; Janssen, F.; Mattsson, J.; Berger, S.

2011-11-01

Oil spill modeling is considered to be an important part of a decision support system (DeSS) for oil spill combatment and is useful for remedial action in case of accidents, as well as for designing the environmental monitoring system that is frequently set up after major accidents. Many accidents take place in coastal areas, implying that low resolution basin scale ocean models are of limited use for predicting the trajectories of an oil spill. In this study, we target the oil spill in connection with the "Full City" accident on the Norwegian south coast and compare operational simulations from three different oil spill models for the area. The result of the analysis is that all models do a satisfactory job. The "standard" operational model for the area is shown to have severe flaws, but by applying ocean forcing data of higher resolution (1.5 km resolution), the model system shows results that compare well with observations. The study also shows that an ensemble of results from the three different models is useful when predicting/analyzing oil spill in coastal areas.

Students' Perceptions and Teachers' Self-Ratings of Modelling Civic Virtues: An Exploratory Empirical Study in Dutch Primary Schools

ERIC Educational Resources Information Center

Willems, Frank; Denessen, Eddie; Hermans, Chris; Vermeer, Paul

2012-01-01

This is a study of teachers' modelling of civic virtues in the classroom. It focusses on three virtues of good citizenship: justice, tolerance and solidarity. The aim is to explore the extent to which teachers can be regarded as models of these virtues. Questionnaires were developed for both students and teachers. Factor analyses showed that the…

Global attractivity of an almost periodic N-species nonlinear ecological competitive model

NASA Astrophysics Data System (ADS)

Xia, Yonghui; Han, Maoan; Huang, Zhenkun

2008-01-01

By using comparison theorem and constructing suitable Lyapunov functional, we study the following almost periodic nonlinear N-species competitive Lotka-Volterra model: A set of sufficient conditions is obtained for the existence and global attractivity of a unique positive almost periodic solution of the above model. As applications, some special competition models are studied again, our new results improve and generalize former results. Examples and their simulations show the feasibility of our main results.

Electrophysiological properties of computational human ventricular cell action potential models under acute ischemic conditions.

PubMed

Dutta, Sara; Mincholé, Ana; Quinn, T Alexander; Rodriguez, Blanca

2017-10-01

Acute myocardial ischemia is one of the main causes of sudden cardiac death. The mechanisms have been investigated primarily in experimental and computational studies using different animal species, but human studies remain scarce. In this study, we assess the ability of four human ventricular action potential models (ten Tusscher and Panfilov, 2006; Grandi et al., 2010; Carro et al., 2011; O'Hara et al., 2011) to simulate key electrophysiological consequences of acute myocardial ischemia in single cell and tissue simulations. We specifically focus on evaluating the effect of extracellular potassium concentration and activation of the ATP-sensitive inward-rectifying potassium current on action potential duration, post-repolarization refractoriness, and conduction velocity, as the most critical factors in determining reentry vulnerability during ischemia. Our results show that the Grandi and O'Hara models required modifications to reproduce expected ischemic changes, specifically modifying the intracellular potassium concentration in the Grandi model and the sodium current in the O'Hara model. With these modifications, the four human ventricular cell AP models analyzed in this study reproduce the electrophysiological alterations in repolarization, refractoriness, and conduction velocity caused by acute myocardial ischemia. However, quantitative differences are observed between the models and overall, the ten Tusscher and modified O'Hara models show closest agreement to experimental data. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bak-Sneppen model: Local equilibrium and critical value.

PubMed

Fraiman, Daniel

2018-04-01

The Bak-Sneppen (BS) model is a very simple model that exhibits all the richness of self-organized criticality theory. At the thermodynamic limit, the BS model converges to a situation where all particles have a fitness that is uniformly distributed between a critical value p_{c} and 1. The p_{c} value is unknown, as are the variables that influence and determine this value. Here we study the BS model in the case in which the lowest fitness particle interacts with an arbitrary even number of m nearest neighbors. We show that p_{c} verifies a simple local equilibrium relation. Based on this relation, we can determine bounds for p_{c} of the BS model and exact results for some BS-like models. Finally, we show how transformations of the original BS model can be done without altering the model's complex dynamics.

Bak-Sneppen model: Local equilibrium and critical value

NASA Astrophysics Data System (ADS)

Fraiman, Daniel

2018-04-01

The Bak-Sneppen (BS) model is a very simple model that exhibits all the richness of self-organized criticality theory. At the thermodynamic limit, the BS model converges to a situation where all particles have a fitness that is uniformly distributed between a critical value pc and 1. The pc value is unknown, as are the variables that influence and determine this value. Here we study the BS model in the case in which the lowest fitness particle interacts with an arbitrary even number of m nearest neighbors. We show that pc verifies a simple local equilibrium relation. Based on this relation, we can determine bounds for pc of the BS model and exact results for some BS-like models. Finally, we show how transformations of the original BS model can be done without altering the model's complex dynamics.

A review on Black-Scholes model in pricing warrants in Bursa Malaysia

NASA Astrophysics Data System (ADS)

Gunawan, Nur Izzaty Ilmiah Indra; Ibrahim, Siti Nur Iqmal; Rahim, Norhuda Abdul

2017-01-01

This paper studies the accuracy of the Black-Scholes (BS) model and the dilution-adjusted Black-Scholes (DABS) model to pricing some warrants traded in the Malaysian market. Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to compare the two models. Results show that the DABS model is more accurate than the BS model for the selected data.

Bayesian exponential random graph modelling of interhospital patient referral networks.

PubMed

Caimo, Alberto; Pallotti, Francesca; Lomi, Alessandro

2017-08-15

Using original data that we have collected on referral relations between 110 hospitals serving a large regional community, we show how recently derived Bayesian exponential random graph models may be adopted to illuminate core empirical issues in research on relational coordination among healthcare organisations. We show how a rigorous Bayesian computation approach supports a fully probabilistic analytical framework that alleviates well-known problems in the estimation of model parameters of exponential random graph models. We also show how the main structural features of interhospital patient referral networks that prior studies have described can be reproduced with accuracy by specifying the system of local dependencies that produce - but at the same time are induced by - decentralised collaborative arrangements between hospitals. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Holomorphic solutions of the susy Grassmannian σ-model and gauge invariance

NASA Astrophysics Data System (ADS)

Hussin, V.; Lafrance, M.; Yurduşen, İ.; Zakrzewski, W. J.

2018-05-01

We study the gauge invariance of the supersymmetric Grassmannian sigma model . It is richer then its purely bosonic submodel and we show how to use it in order to reduce some constant curvature holomorphic solutions of the model into simpler expressions.

An asymptotic Reissner-Mindlin plate model

NASA Astrophysics Data System (ADS)

Licht, Christian; Weller, Thibaut

2018-06-01

A mathematical study via variational convergence of a periodic distribution of classical linearly elastic thin plates softly abutted together shows that it is not necessary to use a different continuum model nor to make constitutive symmetry hypothesis as starting points to deduce the Reissner-Mindlin plate model.

A Componential IRT Model for Guilt.

ERIC Educational Resources Information Center

Smits, Dirk J. M.; De Boeck, Paul

2003-01-01

Studied the process structure of guilt with an adaptation of the Model with Internal Restrictions on Item Difficulty (R. Butter and others, 1998) administered to 270 high school students. Findings show that this kind of modeling is appropriate to investigate the structure of other emotions. (SLD)

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Evaluation of a Theory of Instructional Sequences for Physics Instruction

NASA Astrophysics Data System (ADS)

Wackermann, Rainer; Trendel, Georg; Fischer, Hans E.

2010-05-01

The background of the study is the theory of basis models of teaching and learning, a comprehensive set of models of learning processes which includes, for example, learning through experience and problem-solving. The combined use of different models of learning processes has not been fully investigated and it is frequently not clear under what circumstances a particular model should be used by teachers. In contrast, the theory under investigation here gives guidelines for choosing a particular model and provides instructional sequences for each model. The aim is to investigate the implementation of the theory applied to physics instruction and to show if possible effects for the students may be attributed to the use of the theory. Therefore, a theory-oriented education programme for 18 physics teachers was developed and implemented in the 2005/06 school year. The main features of the intervention consisted of coaching physics lessons and video analysis according to the theory. The study follows a pre-treatment-post design with non-equivalent control group. Findings of repeated-measures ANOVAs show large effects for teachers' subjective beliefs, large effects for classroom actions, and small to medium effects for student outcomes such as perceived instructional quality and student emotions. The teachers/classes that applied the theory especially well according to video analysis showed the larger effects. The results showed that differentiating between different models of learning processes improves physics instruction. Effects can be followed through to student outcomes. The education programme effect was clearer for classroom actions and students' outcomes than for teachers' beliefs.

Learner Satisfaction with Massive Open Online Courses

ERIC Educational Resources Information Center

Gameel, Bahaa G.

2017-01-01

This study investigates factors that influence learners' satisfaction with massive open online courses (MOOCs). Framed by the theory of independent learning and teaching, the three types of interaction model, and the technology acceptance model, this study analyzed data collected from 1,786 learners enrolled in four MOOCs. Results show that the…

The Equivalence of Regression Models Using Difference Scores and Models Using Separate Scores for Each Informant: Implications for the Study of Informant Discrepancies

ERIC Educational Resources Information Center

Laird, Robert D.; Weems, Carl F.

2011-01-01

Research on informant discrepancies has increasingly utilized difference scores. This article demonstrates the statistical equivalence of regression models using difference scores (raw or standardized) and regression models using separate scores for each informant to show that interpretations should be consistent with both models. First,…

Evaluation of biosurfactant obtained from Lactobacillus pentosus as foaming agent in froth flotation.

PubMed

Vecino, X; Devesa-Rey, R; Cruz, J M; Moldes, A B

2013-10-15

This study analyzes the kinetics of sediment sorption on two chemical surfactants (Tween 20 and SDS) and a biotechnologically produced surfactant (obtained from Lactobacillus pentosus). Biosurfactants were produced by fermentation of hemicellulosic sugars from vineyard pruning waste supplied as a substrate to L. pentosus. Results obtained showed that almost no SDS was adsorbed onto the sediments, whereas Tween 20 and biosurfactants from L. pentosus were absorbed after a few minutes. Kinetic models revealed that adsorption of surfactant onto riverbed sediments is governed not only by an intra-particle diffusion model (evaluated by the Weber and Morris model), but also by surface reaction models (evaluated by first, second, third order equations and Elovich equation), showing the best fit when employing the Elovich model. The adsorption properties showed by biosurfactant from L. pentosus onto sediments present it as a potential foaming agent in froth flotation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments

NASA Astrophysics Data System (ADS)

Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng

2016-11-01

To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.

Do Items that Measure Self-Perceived Physical Appearance Function Differentially across Gender Groups? An Application of the MACS Model

ERIC Educational Resources Information Center

Gonzalez-Roma, Vicente; Tomas, Ines; Ferreres, Doris; Hernandez, Ana

2005-01-01

The aims of this study were to investigate whether the 6 items of the Physical Appearance Scale (Marsh, Richards, Johnson, Roche, & Tremayne, 1994) show differential item functioning (DIF) across gender groups of adolescents, and to show how this can be done using the multigroup mean and covariance structure (MG-MACS) analysis model. Two samples…

Ocular hemodynamics and glaucoma: the role of mathematical modeling.

PubMed

Harris, Alon; Guidoboni, Giovanna; Arciero, Julia C; Amireskandari, Annahita; Tobe, Leslie A; Siesky, Brent A

2013-01-01

To discuss the role of mathematical modeling in studying ocular hemodynamics, with a focus on glaucoma. We reviewed recent literature on glaucoma, ocular blood flow, autoregulation, the optic nerve head, and the use of mathematical modeling in ocular circulation. Many studies suggest that alterations in ocular hemodynamics play a significant role in the development, progression, and incidence of glaucoma. Although there is currently a limited number of studies involving mathematical modeling of ocular blood flow, regulation, and diseases (such as glaucoma), preliminary modeling work shows the potential of mathematical models to elucidate the mechanisms that contribute most significantly to glaucoma progression. Mathematical modeling is a useful tool when used synergistically with clinical and laboratory data in the study of ocular blood flow and glaucoma. The development of models to investigate the relationship between ocular hemodynamic alterations and glaucoma progression will provide a unique and useful method for studying the pathophysiology of glaucoma.

Large-Signal Lyapunov-Based Stability Analysis of DC/AC Inverters and Inverter-Based Microgrids

NASA Astrophysics Data System (ADS)

Kabalan, Mahmoud

Microgrid stability studies have been largely based on small-signal linearization techniques. However, the validity and magnitude of the linearization domain is limited to small perturbations. Thus, there is a need to examine microgrids with large-signal nonlinear techniques to fully understand and examine their stability. Large-signal stability analysis can be accomplished by Lyapunov-based mathematical methods. These Lyapunov methods estimate the domain of asymptotic stability of the studied system. A survey of Lyapunov-based large-signal stability studies showed that few large-signal studies have been completed on either individual systems (dc/ac inverters, dc/dc rectifiers, etc.) or microgrids. The research presented in this thesis addresses the large-signal stability of droop-controlled dc/ac inverters and inverter-based microgrids. Dc/ac power electronic inverters allow microgrids to be technically feasible. Thus, as a prelude to examining the stability of microgrids, the research presented in Chapter 3 analyzes the stability of inverters. First, the 13 th order large-signal nonlinear model of a droop-controlled dc/ac inverter connected to an infinite bus is presented. The singular perturbation method is used to decompose the nonlinear model into 11th, 9th, 7th, 5th, 3rd and 1st order models. Each model ignores certain control or structural components of the full order model. The aim of the study is to understand the accuracy and validity of the reduced order models in replicating the performance of the full order nonlinear model. The performance of each model is studied in three different areas: time domain simulations, Lyapunov's indirect method and domain of attraction estimation. The work aims to present the best model to use in each of the three domains of study. Results show that certain reduced order models are capable of accurately reproducing the performance of the full order model while others can be used to gain insights into those three areas of study. This will enable future studies to save computational effort and produce the most accurate results according to the needs of the study being performed. Moreover, the effect of grid (line) impedance on the accuracy of droop control is explored using the 5th order model. Simulation results show that traditional droop control is valid up to R/X line impedance value of 2. Furthermore, the 3rd order nonlinear model improves the currently available inverter-infinite bus models by accounting for grid impedance, active power-frequency droop and reactive power-voltage droop. Results show the 3rd order model's ability to account for voltage and reactive power changes during a transient event. Finally, the large-signal Lyapunov-based stability analysis is completed for a 3 bus microgrid system (made up of 2 inverters and 1 linear load). The thesis provides a systematic state space large-signal nonlinear mathematical modeling method of inverter-based microgrids. The inverters include the dc-side dynamics associated with dc sources. The mathematical model is then used to estimate the domain of asymptotic stability of the 3 bus microgrid. The three bus microgrid system was used as a case study to highlight the design and optimization capability of a large-signal-based approach. The study explores the effect of system component sizing, load transient and generation variations on the asymptotic stability of the microgrid. Essentially, this advancement gives microgrid designers and engineers the ability to manipulate the domain of asymptotic stability depending on performance requirements. Especially important, this research was able to couple the domain of asymptotic stability of the ac microgrid with that of the dc side voltage source. Time domain simulations were used to demonstrate the mathematical nonlinear analysis results.

Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Quattrochi, Dale A.; Bounoua, Lahouari; Lachir, Asia; Zhang, Ping

2016-01-01

In this paper, we assessed and compared land surface temperature (LST) in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2). We also evaluated the sensitivity of the models LST to different land cover types, fractions (percentages), and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI) mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.

Electrical wave propagation in an anisotropic model of the left ventricle based on analytical description of cardiac architecture.

PubMed

Pravdin, Sergey F; Dierckx, Hans; Katsnelson, Leonid B; Solovyova, Olga; Markhasin, Vladimir S; Panfilov, Alexander V

2014-01-01

We develop a numerical approach based on our recent analytical model of fiber structure in the left ventricle of the human heart. A special curvilinear coordinate system is proposed to analytically include realistic ventricular shape and myofiber directions. With this anatomical model, electrophysiological simulations can be performed on a rectangular coordinate grid. We apply our method to study the effect of fiber rotation and electrical anisotropy of cardiac tissue (i.e., the ratio of the conductivity coefficients along and across the myocardial fibers) on wave propagation using the ten Tusscher-Panfilov (2006) ionic model for human ventricular cells. We show that fiber rotation increases the speed of cardiac activation and attenuates the effects of anisotropy. Our results show that the fiber rotation in the heart is an important factor underlying cardiac excitation. We also study scroll wave dynamics in our model and show the drift of a scroll wave filament whose velocity depends non-monotonically on the fiber rotation angle; the period of scroll wave rotation decreases with an increase of the fiber rotation angle; an increase in anisotropy may cause the breakup of a scroll wave, similar to the mother rotor mechanism of ventricular fibrillation.

MR Vascular Fingerprinting in Stroke and Brain Tumors Models

NASA Astrophysics Data System (ADS)

Lemasson, B.; Pannetier, N.; Coquery, N.; Boisserand, Ligia S. B.; Collomb, Nora; Schuff, N.; Moseley, M.; Zaharchuk, G.; Barbier, E. L.; Christen, T.

2016-11-01

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

Non-linear dual-phase-lag model for analyzing heat transfer phenomena in living tissues during thermal ablation.

PubMed

Kumar, P; Kumar, Dinesh; Rai, K N

2016-08-01

In this article, a non-linear dual-phase-lag (DPL) bio-heat transfer model based on temperature dependent metabolic heat generation rate is derived to analyze the heat transfer phenomena in living tissues during thermal ablation treatment. The numerical solution of the present non-linear problem has been done by finite element Runge-Kutta (4,5) method which combines the essence of Runge-Kutta (4,5) method together with finite difference scheme. Our study demonstrates that at the thermal ablation position temperature predicted by non-linear and linear DPL models show significant differences. A comparison has been made among non-linear DPL, thermal wave and Pennes model and it has been found that non-linear DPL and thermal wave bio-heat model show almost same nature whereas non-linear Pennes model shows significantly different temperature profile at the initial stage of thermal ablation treatment. The effect of Fourier number and Vernotte number (relaxation Fourier number) on temperature profile in presence and absence of externally applied heat source has been studied in detail and it has been observed that the presence of externally applied heat source term highly affects the efficiency of thermal treatment method. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling the energy balance of an anaerobic digester fed with cattle manure and renewable energy crops.

PubMed

Lübken, Manfred; Wichern, Marc; Schlattmann, Markus; Gronauer, Andreas; Horn, Harald

2007-10-01

Knowledge of the net energy production of anaerobic fermenters is important for reliable modelling of the efficiency of anaerobic digestion processes. By using the Anaerobic Digestion Model No. 1 (ADM1) the simulation of biogas production and composition is possible. This paper shows the application and modification of ADM1 to simulate energy production of the digestion of cattle manure and renewable energy crops. The paper additionally presents an energy balance model, which enables the dynamic calculation of the net energy production. The model was applied to a pilot-scale biogas reactor. It was found in a simulation study that a continuous feeding and splitting of the reactor feed into smaller heaps do not generally have a positive effect on the net energy yield. The simulation study showed that the ratio of co-substrate to liquid manure in the inflow determines the net energy production when the inflow load is split into smaller heaps. Mathematical equations are presented to calculate the increase of biogas and methane yield for the digestion of liquid manure and lipids for different feeding intervals. Calculations of different kinds of energy losses for the pilot-scale digester showed high dynamic variations, demonstrating the significance of using a dynamic energy balance model.

MR Vascular Fingerprinting in Stroke and Brain Tumors Models

PubMed Central

Lemasson, B.; Pannetier, N.; Coquery, N.; Boisserand, Ligia S. B.; Collomb, Nora; Schuff, N.; Moseley, M.; Zaharchuk, G.; Barbier, E. L.; Christen, T.

2016-01-01

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases. PMID:27883015

Analyzing and leveraging self-similarity for variable resolution atmospheric models

NASA Astrophysics Data System (ADS)

O'Brien, Travis; Collins, William

2015-04-01

Variable resolution modeling techniques are rapidly becoming a popular strategy for achieving high resolution in a global atmospheric models without the computational cost of global high resolution. However, recent studies have demonstrated a variety of resolution-dependent, and seemingly artificial, features. We argue that the scaling properties of the atmosphere are key to understanding how the statistics of an atmospheric model should change with resolution. We provide two such examples. In the first example we show that the scaling properties of the cloud number distribution define how the ratio of resolved to unresolved clouds should increase with resolution. We show that the loss of resolved clouds, in the high resolution region of variable resolution simulations, with the Community Atmosphere Model version 4 (CAM4) is an artifact of the model's treatment of condensed water (this artifact is significantly reduced in CAM5). In the second example we show that the scaling properties of the horizontal velocity field, combined with the incompressibility assumption, necessarily result in an intensification of vertical mass flux as resolution increases. We show that such an increase is present in a wide variety of models, including CAM and the regional climate models of the ENSEMBLES intercomparision. We present theoretical arguments linking this increase to the intensification of precipitation with increasing resolution.

Frequentist Model Averaging in Structural Equation Modelling.

PubMed

Jin, Shaobo; Ankargren, Sebastian

2018-06-04

Model selection from a set of candidate models plays an important role in many structural equation modelling applications. However, traditional model selection methods introduce extra randomness that is not accounted for by post-model selection inference. In the current study, we propose a model averaging technique within the frequentist statistical framework. Instead of selecting an optimal model, the contributions of all candidate models are acknowledged. Valid confidence intervals and a [Formula: see text] test statistic are proposed. A simulation study shows that the proposed method is able to produce a robust mean-squared error, a better coverage probability, and a better goodness-of-fit test compared to model selection. It is an interesting compromise between model selection and the full model.

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

On the modelling of scalar and mass transport in combustor flows

NASA Technical Reports Server (NTRS)

Nikjooy, M.; So, R. M. C.

1989-01-01

Results are presented of a numerical study of swirling and nonswirling combustor flows with and without density variations. Constant-density arguments are used to justify closure assumptions invoked for the transport equations for turbulent momentum and scalar fluxes, which are written in terms of density-weighted variables. Comparisons are carried out with measurements obtained from three different axisymmetric model combustor experiments covering recirculating flow, swirling flow, and variable-density swirling flow inside the model combustors. Results show that the Reynolds stress/flux models do a credible job of predicting constant-density swirling and nonswirling combustor flows with passive scalar transport. However, their improvements over algebraic stress/flux models are marginal. The extension of the constant-density models to variable-density flow calculations shows that the models are equally valid for such flows.

Joint modeling of longitudinal data and discrete-time survival outcome.

PubMed

Qiu, Feiyou; Stein, Catherine M; Elston, Robert C

2016-08-01

A predictive joint shared parameter model is proposed for discrete time-to-event and longitudinal data. A discrete survival model with frailty and a generalized linear mixed model for the longitudinal data are joined to predict the probability of events. This joint model focuses on predicting discrete time-to-event outcome, taking advantage of repeated measurements. We show that the probability of an event in a time window can be more precisely predicted by incorporating the longitudinal measurements. The model was investigated by comparison with a two-step model and a discrete-time survival model. Results from both a study on the occurrence of tuberculosis and simulated data show that the joint model is superior to the other models in discrimination ability, especially as the latent variables related to both survival times and the longitudinal measurements depart from 0. © The Author(s) 2013.

New particle formation in the sulfuric acid-dimethylamine-water system: reevaluation of CLOUD chamber measurements and comparison to an aerosol nucleation and growth model

NASA Astrophysics Data System (ADS)

Kürten, Andreas; Li, Chenxi; Bianchi, Federico; Curtius, Joachim; Dias, António; Donahue, Neil M.; Duplissy, Jonathan; Flagan, Richard C.; Hakala, Jani; Jokinen, Tuija; Kirkby, Jasper; Kulmala, Markku; Laaksonen, Ari; Lehtipalo, Katrianne; Makhmutov, Vladimir; Onnela, Antti; Rissanen, Matti P.; Simon, Mario; Sipilä, Mikko; Stozhkov, Yuri; Tröstl, Jasmin; Ye, Penglin; McMurry, Peter H.

2018-01-01

A recent CLOUD (Cosmics Leaving OUtdoor Droplets) chamber study showed that sulfuric acid and dimethylamine produce new aerosols very efficiently and yield particle formation rates that are compatible with boundary layer observations. These previously published new particle formation (NPF) rates are reanalyzed in the present study with an advanced method. The results show that the NPF rates at 1.7 nm are more than a factor of 10 faster than previously published due to earlier approximations in correcting particle measurements made at a larger detection threshold. The revised NPF rates agree almost perfectly with calculated rates from a kinetic aerosol model at different sizes (1.7 and 4.3 nm mobility diameter). In addition, modeled and measured size distributions show good agreement over a wide range of sizes (up to ca. 30 nm). Furthermore, the aerosol model is modified such that evaporation rates for some clusters can be taken into account; these evaporation rates were previously published from a flow tube study. Using this model, the findings from the present study and the flow tube experiment can be brought into good agreement for the high base-to-acid ratios (˜ 100) relevant for this study. This confirms that nucleation proceeds at rates that are compatible with collision-controlled (a.k.a. kinetically controlled) NPF for the conditions during the CLOUD7 experiment (278 K, 38 % relative humidity, sulfuric acid concentration between 1 × 106 and 3 × 107 cm-3, and dimethylamine mixing ratio of ˜ 40 pptv, i.e., 1 × 109 cm-3).

Gender-related model for mobile-based learning

NASA Astrophysics Data System (ADS)

Simanjuntak, R. R.; Dewi, U. P.; Rifai, I.

2018-03-01

The study investigates gender influence on mobile-based learning. This case study of university students in Jakarta involved 235 students (128 male, 97 female). Results of this qualitative study showed 96% preference for mobile-based learning. A further 94% showed the needs for collaboration and authenticity for 92%. Hofstede’s cultural dimensions were used to identify the gender aspects of MALL. Preference for Masculinity (65%) was showed rather than Femininity (35%), even among the female respondents (70% of the population). Professions and professionalism received strongest preference (70%) while Individuality and Collectivism had equal preferences among students. Both female and male respondents requested Indulgence (84%) for mobile-based learning with more male respondents opted for Indulgence. The study provided a model for this gender sensitive mobile-based learning. Implications of implementing mobile-based learning as an ideal alternative for well-accommodated education are is also discussed.

Quantum coherence of planar spin models with Dzyaloshinsky-Moriya interaction

NASA Astrophysics Data System (ADS)

Radhakrishnan, Chandrashekar; Ermakov, Igor; Byrnes, Tim

2017-07-01

The quantum coherence of one-dimensional planar spin models with Dzyaloshinsky-Moriya interaction is investigated. The anisotropic XY model, the isotropic XX model, and the transverse field model are studied in the large N limit using two qubit reduced density matrices and two point correlation functions. From our investigations we find that the coherence as measured using Jensen-Shannon divergence can be used to detect quantum phase transitions and quantum critical points. The derivative of coherence shows nonanalytic behavior at critical points, leading to the conclusion that these transitions are of second order. Further, we show that the presence of Dzyaloshinsky-Moriya coupling suppresses the phase transition due to residual ferromagnetism, which is caused by spin canting.

Modeling vaccination in a heterogeneous metapopulation system

NASA Astrophysics Data System (ADS)

Lachiany, Menachem

2016-09-01

We present here a multicity SIS epidemic model with vaccination. The model describes the dynamics of heterogeneous metapopulations that contain imperfectly vaccinated individuals. The effect of vaccination on heterogeneous multicity models has not been previously studied. We show that under very generic conditions, the epidemic threshold does not depend on the diffusion coefficient of the vaccinated individuals, but it does depend on the diffusion coefficient of the infected population. We then show, using a novel methodology, that the reproduction number is determined by the homogeneous model parameters and by the maximal number of neighbors a city can have, when the diffusion coefficient of the infected population is low. Finally, we present numerical simulations to support the analytical results.

Gravitational baryogenesis in running vacuum models

NASA Astrophysics Data System (ADS)

Oikonomou, V. K.; Pan, Supriya; Nunes, Rafael C.

2017-08-01

We study the gravitational baryogenesis mechanism for generating baryon asymmetry in the context of running vacuum models. Regardless of whether these models can produce a viable cosmological evolution, we demonstrate that they produce a nonzero baryon-to-entropy ratio even if the universe is filled with conformal matter. This is a sound difference between the running vacuum gravitational baryogenesis and the Einstein-Hilbert one, since in the latter case, the predicted baryon-to-entropy ratio is zero. We consider two well known and most used running vacuum models and show that the resulting baryon-to-entropy ratio is compatible with the observational data. Moreover, we also show that the mechanism of gravitational baryogenesis may constrain the running vacuum models.

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

Management of organisational changes in a case of de-institutionalisation.

PubMed

Parlalis, Stavros K

2011-01-01

This paper seeks to explore the development of a discharge programme in one learning disability hospital in Scotland. The study aims to concentrate on organisational developmental changes in that institution. The model of the management during the discharge programme was investigated. The aim of the study is to explore how the discharge programme developed, as seen under the lens of organisational change, in order to find out what kind of model of management is more suitable in similar programmes. A case study was employed. Data were collected by means of interviews. The interviews followed a structured format. The sample of the study had to be a purposive sample and the method of snowball sampling was used; finally, 28 interviews were conducted. A grounded approach was adopted for the data analysis. The software program QSR "NUD*IST" (version "N6") was used as a technical tool, in order to facilitate the data analysis. The findings of this study show that various management models were adopted in the four phases of the discharge programme. These different models represent a "quest" by the institution's management regarding the most appropriate model for managing the discharge programme. This study shows that this goes on continuously in organisations under transition until they settle down to a more permanent state. It was concluded that management models, which are composed of characteristics from the organic theory of organisational management, could apply in discharge programmes. The data gathered enabled the researcher to arrive at a model of management which is suitable for managing organisational changes in discharge programmes, the named "stakeholder management model".

Lagrange multiplier and Wess-Zumino variable as extra dimensions in the torus universe

NASA Astrophysics Data System (ADS)

Nejad, Salman Abarghouei; Dehghani, Mehdi; Monemzadeh, Majid

2018-01-01

We study the effect of the simplest geometry which is imposed via the topology of the universe by gauging non-relativistic particle model on torus and 3-torus with the help of symplectic formalism of constrained systems. Also, we obtain generators of gauge transformations for gauged models. Extracting corresponding Poisson structure of existed constraints, we show the effect of the shape of the universe on canonical structure of phase-spaces of models and suggest some phenomenology to prove the topology of the universe and probable non-commutative structure of the space. In addition, we show that the number of extra dimensions in the phase-spaces of gauged embedded models are exactly two. Moreover, in classical form, we talk over modification of Newton's second law in order to study the origin of the terms appeared in the gauged theory.

Non-invasive brain stimulation and computational models in post-stroke aphasic patients: single session of transcranial magnetic stimulation and transcranial direct current stimulation. A randomized clinical trial.

PubMed

Santos, Michele Devido Dos; Cavenaghi, Vitor Breseghello; Mac-Kay, Ana Paula Machado Goyano; Serafim, Vitor; Venturi, Alexandre; Truong, Dennis Quangvinh; Huang, Yu; Boggio, Paulo Sérgio; Fregni, Felipe; Simis, Marcel; Bikson, Marom; Gagliardi, Rubens José

2017-01-01

Patients undergoing the same neuromodulation protocol may present different responses. Computational models may help in understanding such differences. The aims of this study were, firstly, to compare the performance of aphasic patients in naming tasks before and after one session of transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS) and sham, and analyze the results between these neuromodulation techniques; and secondly, through computational model on the cortex and surrounding tissues, to assess current flow distribution and responses among patients who received tDCS and presented different levels of results from naming tasks. Prospective, descriptive, qualitative and quantitative, double blind, randomized and placebo-controlled study conducted at Faculdade de Ciências Médicas da Santa Casa de São Paulo. Patients with aphasia received one session of tDCS, TMS or sham stimulation. The time taken to name pictures and the response time were evaluated before and after neuromodulation. Selected patients from the first intervention underwent a computational model stimulation procedure that simulated tDCS. The results did not indicate any statistically significant differences from before to after the stimulation.The computational models showed different current flow distributions. The present study did not show any statistically significant difference between tDCS, TMS and sham stimulation regarding naming tasks. The patients'responses to the computational model showed different patterns of current distribution.

Sensitivity of snowpack storage to precipitation and temperature using spatial and temporal analog models

NASA Astrophysics Data System (ADS)

Luce, Charles H.; Lopez-Burgos, Viviana; Holden, Zachary

2014-12-01

Empirical sensitivity analyses are important for evaluation of the effects of a changing climate on water resources and ecosystems. Although mechanistic models are commonly applied for evaluation of climate effects for snowmelt, empirical relationships provide a first-order validation of the various postulates required for their implementation. Previous studies of empirical sensitivity for April 1 snow water equivalent (SWE) in the western United States were developed by regressing interannual variations in SWE to winter precipitation and temperature. This offers a temporal analog for climate change, positing that a warmer future looks like warmer years. Spatial analogs are used to hypothesize that a warmer future may look like warmer places, and are frequently applied alternatives for complex processes, or states/metrics that show little interannual variability (e.g., forest cover). We contrast spatial and temporal analogs for sensitivity of April 1 SWE and the mean residence time of snow (SRT) using data from 524 Snowpack Telemetry (SNOTEL) stations across the western U.S. We built relatively strong models using spatial analogs to relate temperature and precipitation climatology to snowpack climatology (April 1 SWE, R2=0.87, and SRT, R2=0.81). Although the poorest temporal analog relationships were in areas showing the highest sensitivity to warming, spatial analog models showed consistent performance throughout the range of temperature and precipitation. Generally, slopes from the spatial relationships showed greater thermal sensitivity than the temporal analogs, and high elevation stations showed greater vulnerability using a spatial analog than shown in previous modeling and sensitivity studies. The spatial analog models provide a simple perspective to evaluate potential futures and may be useful in further evaluation of snowpack with warming.

The use of dispersion modeling to determine the feasibility of vegetative environmental buffers (VEBS) at controlling odor dispersion

NASA Astrophysics Data System (ADS)

Weber, Eric E.

Concentrated animal feeding operations (CAFOs) have been experiencing increased resistance from surrounding residents making construction of new facilities or expansion of existing ones increasingly limited (Jacobson et al., 2002). Such concerns often include the impact of nuisance odor on peoples’ lives and on the environment (Huang and Miller, 2006). Vegetative environmental buffers (VEBs) have been suggested as a possible odor control technology. They have been found to impact odor plume dispersion and have shown the possibility of being an effective tool for odor abatement when used alone or in combination with other technologies (Lin et al., 2006). The main objective of this study was to use Gaussian-type dispersion modeling to determine the feasibility of use and the effectiveness of a VEB at controlling the spread of odor from a swine feeding operation. First, wind tunnel NH3 dispersion trends were compared to model generated dispersion trends to determine the accuracy of the model at handling VEB dispersion. Next, facility-scale (northern Missouri specific) model simulations with and without a VEB were run to determine its viability as an option for dispersion reduction. Finally, dispersion forecasts that integrated numerical weather forecasts were developed and compared to collected concentration data to determine forecast accuracy. The results of this study found that dispersion models can be used to simulate dispersion around a VEB. AERMOD-generated dispersion trends were found to follow similar patterns of decreasing downwind concentration to those of both wind tunnel simulations and previous research. This shows that a VEB can be incorporated into AERMOD and that the model can be used to determine its effectiveness as an odor control option. The results of this study also showed that a VEB has an effect on odor dispersion by reducing downwind concentrations. This was confirmed by both wind tunnel and AERMOD simulations of dispersion displaying decreased downwind concentrations from a control scenario. This shows that VEBs have the potential to act as an odor control option for CAFOs. This study also found that a forecast method that integrated numerical weather prediction into dispersion models could be developed to forecast areas of high concentration. Model-forecasted dispersion trends had a high spatial correlation with collected concentrations for days when the facility was emitting. This shows that dispersion models can accurately predict high concentration areas using forecasted weather data. The information provided by this study may ultimately prove useful for this particular facility and others and may help to lower tensions with surrounding residents.

Assessment of orthodontic treatment need: a comparison of study models and facial photographs.

PubMed

Sherlock, Joseph M; Cobourne, Martyn T; McDonald, Fraser

2008-02-01

The current study aims to examine how orthodontic treatment need is prioritized depending upon whether dental study models or facial photographs are used as the means of assessment. A group of three orthodontists and three postgraduate orthodontic students assessed: (i) dental attractiveness; and (ii) need for orthodontic treatment in 40 subjects (19 males, 21 females). The 40 subjects displayed a range of malocclusions. Separate assessments were made from study models and facial photographs. There was a bias towards higher scores for dental attractiveness from facial photographs compared with assessment of study casts, for all examiners. This was statistically significant for five of the six examiners (P = 0.001-0.101). The need for orthodontic treatment was rated as 20% higher from study models compared with facial photographs (P < 0.001); overall the level of need for orthodontic treatment was rated as 18.9% higher from study models compared with facial photographs (P < 0.001). Reproducibility analyses showed that there was a considerable variation in the intra- and inter-examiner agreement. This study shows that a group of three orthodontists and three postgraduate students in orthodontics: (i) rated orthodontic treatment need higher from study models compared with facial photographs and; (ii) rated dental attractiveness higher from facial photographs compared with study models. It is suggested that the variable intra-examiner agreement may result from the assessment of orthodontic treatment need and dental attractiveness in the absence of any specific assessment criteria. The poor reproducibility of assessment of orthodontic treatment need and dental attractiveness in the absence of strict criteria may suggest the need to use an appropriate index.

Stochastic Robust Mathematical Programming Model for Power System Optimization

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

Liu, Cong; Changhyeok, Lee; Haoyong, Chen

2016-01-01

This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Understanding Elementary Astronomy by Making Drawing-Based Models

NASA Astrophysics Data System (ADS)

van Joolingen, W. R.; Aukes, Annika V. A.; Gijlers, H.; Bollen, L.

2015-04-01

Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a drawing-based model of the solar system. The results show that children in the target age group are capable of creating a drawing-based model of the solar system and can use it to show the situations in which eclipses occur. Structural equation modeling predicting post-test knowledge scores based on learners' pre-test knowledge scores, the quality of their drawings and motivational aspects yielded some evidence that such drawing contributes to learning. Consequences for using modeling with young children are considered.

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

PubMed

Bonnafous, Fanny; Fievet, Ghislain; Blanchet, Nicolas; Boniface, Marie-Claude; Carrère, Sébastien; Gouzy, Jérôme; Legrand, Ludovic; Marage, Gwenola; Bret-Mestries, Emmanuelle; Munos, Stéphane; Pouilly, Nicolas; Vincourt, Patrick; Langlade, Nicolas; Mangin, Brigitte

2018-02-01

This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

Absence of “Warm-Up” during Active Avoidance Learning in a Rat Model of Anxiety Vulnerability: Insights from Computational Modeling

PubMed Central

Myers, Catherine E.; Smith, Ian M.; Servatius, Richard J.; Beck, Kevin D.

2014-01-01

Avoidance behaviors, in which a learned response causes omission of an upcoming punisher, are a core feature of many psychiatric disorders. While reinforcement learning (RL) models have been widely used to study the development of appetitive behaviors, less attention has been paid to avoidance. Here, we present a RL model of lever-press avoidance learning in Sprague-Dawley (SD) rats and in the inbred Wistar Kyoto (WKY) rat, which has been proposed as a model of anxiety vulnerability. We focus on “warm-up,” transiently decreased avoidance responding at the start of a testing session, which is shown by SD but not WKY rats. We first show that a RL model can correctly simulate key aspects of acquisition, extinction, and warm-up in SD rats; we then show that WKY behavior can be simulated by altering three model parameters, which respectively govern the tendency to explore new behaviors vs. exploit previously reinforced ones, the tendency to repeat previous behaviors regardless of reinforcement, and the learning rate for predicting future outcomes. This suggests that several, dissociable mechanisms may contribute independently to strain differences in behavior. The model predicts that, if the “standard” inter-session interval is shortened from 48 to 24 h, SD rats (but not WKY) will continue to show warm-up; we confirm this prediction in an empirical study with SD and WKY rats. The model further predicts that SD rats will continue to show warm-up with inter-session intervals as short as a few minutes, while WKY rats will not show warm-up, even with inter-session intervals as long as a month. Together, the modeling and empirical data indicate that strain differences in warm-up are qualitative rather than just the result of differential sensitivity to task variables. Understanding the mechanisms that govern expression of warm-up behavior in avoidance may lead to better understanding of pathological avoidance, and potential pathways to modify these processes. PMID:25183956

Integrated and spectral energetics of the GLAS general circulation model

NASA Technical Reports Server (NTRS)

Tenenbaum, J.

1982-01-01

Integrated and spectral error energetics of the GLAS General circulation model are compared with observations for periods in January 1975, 1976, and 1977. For two cases the model shows significant skill in predicting integrated energetics quantities out to two weeks, and for all three cases, the integrated monthly mean energetics show qualitative improvements over previous versions of the model in eddy kinetic energy and barotropic conversions. Fundamental difficulties remain with leakage of energy to the stratospheric level, particularly above strong initial jet streams associated in part with regions of steep terrain. The spectral error growth study represents the first comparison of general circulation model spectral energetics predictions with the corresponding observational spectra on a day by day basis. The major conclusion is that eddy kinetics energy can be correct while significant errors occur in the kinetic energy of wavenumber 3. Both the model and observations show evidence of single wavenumber dominance in eddy kinetic energy and the correlation of spectral kinetics and potential energy.

Epidemics in adaptive networks with community structure

NASA Astrophysics Data System (ADS)

Shaw, Leah; Tunc, Ilker

2010-03-01

Models for epidemic spread on static social networks do not account for changes in individuals' social interactions. Recent studies of adaptive networks have modeled avoidance behavior, as non-infected individuals try to avoid contact with infectives. Such models have not generally included realistic social structure. Here we study epidemic spread on an adaptive network with community structure. We model the effect of heterogeneous communities on infection levels and epidemic extinction. We also show how an epidemic can alter the community structure.

Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

PubMed

Arnold, Matthias

2017-12-02

The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

Analysis of injury severity of drivers involved in single- and two-vehicle crashes on highways in Ontario.

PubMed

Lee, Chris; Li, Xuancheng

2014-10-01

This study analyzes driver's injury severity in single- and two-vehicle crashes and compares the effects of explanatory variables among various types of crashes. The study identified factors affecting injury severity and their effects on severity levels using 5-year crash records for provincial highways in Ontario, Canada. Considering heteroscedasticity in the effects of explanatory variables on injury severity, the heteroscedastic ordered logit (HOL) models were developed for single- and two-vehicle crashes separately. The results of the models show that there exists heteroscedasticity for young drivers (≤30), safety equipment and ejection in the single-vehicle crash model, and female drivers, safety equipment and head-on collision in the two-vehicle crash models. The results also show that young car drivers have opposite effects between single-car and car-car crashes, and sideswipe crashes have opposite effects between car-car and truck-truck crashes. The study demonstrates that separate HOL models for single-vehicle and different types of two-vehicle crashes can identify differential effects of factors on driver's injury severity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Implementation and comparative analysis of the optimisations produced by evolutionary algorithms for the parameter extraction of PSP MOSFET model

NASA Astrophysics Data System (ADS)

Hadia, Sarman K.; Thakker, R. A.; Bhatt, Kirit R.

2016-05-01

The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (ABC), variant ABC and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that ABC algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic ABC algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant ABC and basic ABC algorithm for the parameter extraction of the MOSFET model; also the implementation of the ABC algorithm is shown to be simpler than that of the PSO algorithm.

Fluctuations in the DNA double helix

NASA Astrophysics Data System (ADS)

Peyrard, M.; López, S. C.; Angelov, D.

2007-08-01

DNA is not the static entity suggested by the famous double helix structure. It shows large fluctuational openings, in which the bases, which contain the genetic code, are temporarily open. Therefore it is an interesting system to study the effect of nonlinearity on the physical properties of a system. A simple model for DNA, at a mesoscopic scale, can be investigated by computer simulation, in the same spirit as the original work of Fermi, Pasta and Ulam. These calculations raise fundamental questions in statistical physics because they show a temporary breaking of equipartition of energy, regions with large amplitude fluctuations being able to coexist with regions where the fluctuations are very small, even when the model is studied in the canonical ensemble. This phenomenon can be related to nonlinear excitations in the model. The ability of the model to describe the actual properties of DNA is discussed by comparing theoretical and experimental results for the probability that base pairs open an a given temperature in specific DNA sequences. These studies give us indications on the proper description of the effect of the sequence in the mesoscopic model.

Global estimation of ocean tides in deep and shallow waters from TOPEX/POSEIDON and numerical models with applications to geophysics, oceanography, and precision altimetry

NASA Astrophysics Data System (ADS)

Tierney, Craig Cristy

Presented here are several investigations of ocean tides derived from TOPEX/POSEIDON (T/P) altimetry and numerical models. The purpose of these investigations is to study the short wavelength features in the T/P data and to preserve these wavelengths in global ocean tide models that are accurate in shallow and deep waters. With these new estimates, effects of the tides on loading, Earth's rotation, and tidal energetics are studied. To preserve tidal structure, tides have been estimated along the ground track of T/P by the harmonic and response methods using 4.5 years of data. Results show the two along-track (AT) estimates agree with each other and with other tide models for those components with minimal aliasing problems. Comparisons to global models show that there is tidal structure in the T/P data that is not preserved with current gridding methods. Error estimates suggest there is accurate information in the T/P data from shallow waters that can be used to improve tidal models. It has been shown by Ray and Mitchum (1996) that the first mode baroclinic tide can be separated from AT tide estimates by filtering. This method has been used to estimate the first mode semidiurnal baroclinic tides globally. Estimates for M2 show good correlation with known regions of baroclinic tide generation. Using gridded, filtered AT estimates, a lower bound on the energy contained in the M2 baroclinic tide is 50 PJ. Inspired by the structure found in the AT estimates, a gridding method is presented that preserves tidal structure in the T/P data. These estimates are assimilated into a nonlinear, finite difference, global barotropic tidal model. Results from the 8 major tidal constituents show the model performs equivalently to other models in the deep waters, and is significantly better in the shallow waters. Crossover variance is reduced from 14 cm to 10 cm in the shallow waters. Comparisons to Earth rotation show good agreement to results from VLBI data. Tidal energetics computed from the models show good agreement with previous results. PE/KE ratios and quality factors are more consistent in each frequency band than in previous results.

Biased assimilation, homophily, and the dynamics of polarization

PubMed Central

Dandekar, Pranav; Goel, Ashish; Lee, David T.

2013-01-01

We study the issue of polarization in society through a model of opinion formation. We say an opinion formation process is polarizing if it results in increased divergence of opinions. Empirical studies have shown that homophily, i.e., greater interaction between like-minded individuals, results in polarization. However, we show that DeGroot’s well-known model of opinion formation based on repeated averaging can never be polarizing, even if individuals are arbitrarily homophilous. We generalize DeGroot’s model to account for a phenomenon well known in social psychology as biased assimilation: When presented with mixed or inconclusive evidence on a complex issue, individuals draw undue support for their initial position, thereby arriving at a more extreme opinion. We show that in a simple model of homophilous networks, our biased opinion formation process results in polarization if individuals are sufficiently biased. In other words, homophily alone, without biased assimilation, is not sufficient to polarize society. Quite interestingly, biased assimilation also provides a framework to analyze the polarizing effect of Internet-based recommender systems that show us personalized content. PMID:23536293

Generalized semiparametric varying-coefficient models for longitudinal data

NASA Astrophysics Data System (ADS)

Qi, Li

In this dissertation, we investigate the generalized semiparametric varying-coefficient models for longitudinal data that can flexibly model three types of covariate effects: time-constant effects, time-varying effects, and covariate-varying effects, i.e., the covariate effects that depend on other possibly time-dependent exposure variables. First, we consider the model that assumes the time-varying effects are unspecified functions of time while the covariate-varying effects are parametric functions of an exposure variable specified up to a finite number of unknown parameters. The estimation procedures are developed using multivariate local linear smoothing and generalized weighted least squares estimation techniques. The asymptotic properties of the proposed estimators are established. The simulation studies show that the proposed methods have satisfactory finite sample performance. ACTG 244 clinical trial of HIV infected patients are applied to examine the effects of antiretroviral treatment switching before and after HIV developing the 215-mutation. Our analysis shows benefit of treatment switching before developing the 215-mutation. The proposed methods are also applied to the STEP study with MITT cases showing that they have broad applications in medical research.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

Prediction of Return-to-original-work after an Industrial Accident Using Machine Learning and Comparison of Techniques

PubMed Central

2018-01-01

Background Many studies have tried to develop predictors for return-to-work (RTW). However, since complex factors have been demonstrated to predict RTW, it is difficult to use them practically. This study investigated whether factors used in previous studies could predict whether an individual had returned to his/her original work by four years after termination of the worker's recovery period. Methods An initial logistic regression analysis of 1,567 participants of the fourth Panel Study of Worker's Compensation Insurance yielded odds ratios. The participants were divided into two subsets, a training dataset and a test dataset. Using the training dataset, logistic regression, decision tree, random forest, and support vector machine models were established, and important variables of each model were identified. The predictive abilities of the different models were compared. Results The analysis showed that only earned income and company-related factors significantly affected return-to-original-work (RTOW). The random forest model showed the best accuracy among the tested machine learning models; however, the difference was not prominent. Conclusion It is possible to predict a worker's probability of RTOW using machine learning techniques with moderate accuracy. PMID:29736160

Monte Carlo modeling of a conventional X-ray computed tomography scanner for gel dosimetry purposes.

PubMed

Hayati, Homa; Mesbahi, Asghar; Nazarpoor, Mahmood

2016-01-01

Our purpose in the current study was to model an X-ray CT scanner with the Monte Carlo (MC) method for gel dosimetry. In this study, a conventional CT scanner with one array detector was modeled with use of the MCNPX MC code. The MC calculated photon fluence in detector arrays was used for image reconstruction of a simple water phantom as well as polyacrylamide polymer gel (PAG) used for radiation therapy. Image reconstruction was performed with the filtered back-projection method with a Hann filter and the Spline interpolation method. Using MC results, we obtained the dose-response curve for images of irradiated gel at different absorbed doses. A spatial resolution of about 2 mm was found for our simulated MC model. The MC-based CT images of the PAG gel showed a reliable increase in the CT number with increasing absorbed dose for the studied gel. Also, our results showed that the current MC model of a CT scanner can be used for further studies on the parameters that influence the usability and reliability of results, such as the photon energy spectra and exposure techniques in X-ray CT gel dosimetry.

Building a Better Applicant Pool--A Case Study of the Use of Predictive Modeling and Market Segmentation to Build and Enroll Better Pools of Students

ERIC Educational Resources Information Center

Herridge, Bart; Heil, Robert

2003-01-01

Predictive modeling has been a popular topic in higher education for the last few years. This case study shows an example of an effective use of modeling combined with market segmentation to strategically divide large, unmanageable prospect and inquiry pools and convert them into applicants, and eventually, enrolled students. (Contains 6 tables.)

The Implementation of Character Education Model Based on Empowerment Theatre for Primary School Students

ERIC Educational Resources Information Center

Anggraini, Purwati; Kusniarti, Tuti

2016-01-01

This study aimed at constructing character education model implemented in primary school. The research method was qualitative with five samples in total, comprising primary schools in Malang city/regency and one school as a pilot model. The pilot model was instructed by theatre coach teacher, parents, and school society. The result showed that…

Satisfiers and Dissatisfiers: A Two-Factor Model for Website Design and Evaluation.

ERIC Educational Resources Information Center

Zhang, Ping; von Dran, Gisela M.

2000-01-01

Investigates Web site design factors and their impact from a theoretical perspective. Presents a two-factor model that can guide Web site design and evaluation. According to the model, there are two types of design factors: hygiene and motivator. Results showed that the two-factor model provides a means for Web-user interface studies. Provides…

Evolution of Forms of Representation in a Modelling Activity: A Case Study

ERIC Educational Resources Information Center

Garuti, Rossella; Dapueto, Carlo; Boero, Paolo

2003-01-01

The report describes a mathematical modelling activity of a natural phenomenon (transmission of hereditary characters in a codominance case) using the concept of model as a theoretical instrument. The chosen tool enables us to show how the construction of a link between reality and a model is related to the evolution of the graphical…

Nanoindentation of virus capsids in a molecular model

NASA Astrophysics Data System (ADS)

Cieplak, Marek; Robbins, Mark O.

2010-01-01

A molecular-level model is used to study the mechanical response of empty cowpea chlorotic mottle virus (CCMV) and cowpea mosaic virus (CPMV) capsids. The model is based on the native structure of the proteins that constitute the capsids and is described in terms of the Cα atoms. Nanoindentation by a large tip is modeled as compression between parallel plates. Plots of the compressive force versus plate separation for CCMV are qualitatively consistent with continuum models and experiments, showing an elastic region followed by an irreversible drop in force. The mechanical response of CPMV has not been studied, but the molecular model predicts an order of magnitude higher stiffness and a much shorter elastic region than for CCMV. These large changes result from small structural changes that increase the number of bonds by only 30% and would be difficult to capture in continuum models. Direct comparison of local deformations in continuum and molecular models of CCMV shows that the molecular model undergoes a gradual symmetry breaking rotation and accommodates more strain near the walls than the continuum model. The irreversible drop in force at small separations is associated with rupturing nearly all of the bonds between capsid proteins in the molecular model, while a buckling transition is observed in continuum models.

Spiral-Wave Dynamics in a Mathematical Model of Human Ventricular Tissue with Myocytes and Fibroblasts

PubMed Central

Nayak, Alok Ranjan; Shajahan, T. K.; Panfilov, A. V.; Pandit, Rahul

2013-01-01

Cardiac fibroblasts, when coupled functionally with myocytes, can modulate the electrophysiological properties of cardiac tissue. We present systematic numerical studies of such modulation of electrophysiological properties in mathematical models for (a) single myocyte-fibroblast (MF) units and (b) two-dimensional (2D) arrays of such units; our models build on earlier ones and allow for zero-, one-, and two-sided MF couplings. Our studies of MF units elucidate the dependence of the action-potential (AP) morphology on parameters such as , the fibroblast resting-membrane potential, the fibroblast conductance , and the MF gap-junctional coupling . Furthermore, we find that our MF composite can show autorhythmic and oscillatory behaviors in addition to an excitable response. Our 2D studies use (a) both homogeneous and inhomogeneous distributions of fibroblasts, (b) various ranges for parameters such as , and , and (c) intercellular couplings that can be zero-sided, one-sided, and two-sided connections of fibroblasts with myocytes. We show, in particular, that the plane-wave conduction velocity decreases as a function of , for zero-sided and one-sided couplings; however, for two-sided coupling, decreases initially and then increases as a function of , and, eventually, we observe that conduction failure occurs for low values of . In our homogeneous studies, we find that the rotation speed and stability of a spiral wave can be controlled either by controlling or . Our studies with fibroblast inhomogeneities show that a spiral wave can get anchored to a local fibroblast inhomogeneity. We also study the efficacy of a low-amplitude control scheme, which has been suggested for the control of spiral-wave turbulence in mathematical models for cardiac tissue, in our MF model both with and without heterogeneities. PMID:24023798

How sensitive are estimates of carbon fixation in agricultural models to input data?

PubMed Central

2012-01-01

Background Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products. Results For our case study analysis we selected two different process based models: the Environmental Policy Integrated Climate (EPIC) and the Biosphere Energy Transfer Hydrology (BETHY/DLR) model. Both process models show a congruent pattern to changes in input data. The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing major input datasets. However, EPIC is less sensitive to meteorological input data than BETHY/DLR. The ECMWF maximum temperatures show a systematic pattern. Temperatures above 20°C are overestimated, whereas temperatures below 20°C are underestimated, resulting in an overall underestimation of NPP in both models. Besides, BETHY/DLR is sensitive to the choice and accuracy of the land cover product. Discussion This study shows that the impact of input data uncertainty on modelling results need to be assessed: whenever the models are applied under new conditions, local data should be used for both input and result comparison. PMID:22296931

Effects of fluid structure interaction in a three dimensional model of the spinal subarachnoid space.

PubMed

Cheng, Shaokoon; Fletcher, David; Hemley, Sarah; Stoodley, Marcus; Bilston, Lynne

2014-08-22

It is unknown whether spinal cord motion has a significant effect on cerebrospinal fluid (CSF) pressure and therefore the importance of including fluid structure interaction (FSI) in computational fluid dynamics models (CFD) of the spinal subarachnoid space (SAS) is unclear. This study aims to determine the effects of FSI on CSF pressure and spinal cord motion in a normal and in a stenosis model of the SAS. A three-dimensional patient specific model of the SAS and spinal cord were constructed from MR anatomical images and CSF flow rate measurements obtained from a healthy human being. The area of SAS at spinal level T4 was constricted by 20% to represent the stenosis model. FSI simulations in both models were performed by running ANSYS CFX and ANSYS Mechanical in tandem. Results from this study show that the effect of FSI on CSF pressure is only about 1% in both the normal and stenosis models and therefore show that FSI has a negligible effect on CSF pressure. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Study of subgrid-scale velocity models for reacting and nonreacting flows

NASA Astrophysics Data System (ADS)

Langella, I.; Doan, N. A. K.; Swaminathan, N.; Pope, S. B.

2018-05-01

A study is conducted to identify advantages and limitations of existing large-eddy simulation (LES) closures for the subgrid-scale (SGS) kinetic energy using a database of direct numerical simulations (DNS). The analysis is conducted for both reacting and nonreacting flows, different turbulence conditions, and various filter sizes. A model, based on dissipation and diffusion of momentum (LD-D model), is proposed in this paper based on the observed behavior of four existing models. Our model shows the best overall agreements with DNS statistics. Two main investigations are conducted for both reacting and nonreacting flows: (i) an investigation on the robustness of the model constants, showing that commonly used constants lead to a severe underestimation of the SGS kinetic energy and enlightening their dependence on Reynolds number and filter size; and (ii) an investigation on the statistical behavior of the SGS closures, which suggests that the dissipation of momentum is the key parameter to be considered in such closures and that dilatation effect is important and must be captured correctly in reacting flows. Additional properties of SGS kinetic energy modeling are identified and discussed.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

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

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

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

Wang, Y. B.; Zhu, X. W., E-mail: xiaowuzhu1026@znufe.edu.cn; Dai, H. H.

Though widely used in modelling nano- and micro- structures, Eringen’s differential model shows some inconsistencies and recent study has demonstrated its differences between the integral model, which then implies the necessity of using the latter model. In this paper, an analytical study is taken to analyze static bending of nonlocal Euler-Bernoulli beams using Eringen’s two-phase local/nonlocal model. Firstly, a reduction method is proved rigorously, with which the integral equation in consideration can be reduced to a differential equation with mixed boundary value conditions. Then, the static bending problem is formulated and four types of boundary conditions with various loadings aremore » considered. By solving the corresponding differential equations, exact solutions are obtained explicitly in all of the cases, especially for the paradoxical cantilever beam problem. Finally, asymptotic analysis of the exact solutions reveals clearly that, unlike the differential model, the integral model adopted herein has a consistent softening effect. Comparisons are also made with existing analytical and numerical results, which further shows the advantages of the analytical results obtained. Additionally, it seems that the once controversial nonlocal bar problem in the literature is well resolved by the reduction method.« less

Social comparison and perceived breach of psychological contract: their effects on burnout in a multigroup analysis.

PubMed

Cantisano, Gabriela Topa; Domínguez, J Francisco Morales; García, J Luis Caeiro

2007-05-01

This study focuses on the mediator role of social comparison in the relationship between perceived breach of psychological contract and burnout. A previous model showing the hypothesized effects of perceived breach on burnout, both direct and mediated, is proposed. The final model reached an optimal fit to the data and was confirmed through multigroup analysis using a sample of Spanish teachers (N = 401) belonging to preprimary, primary, and secondary schools. Multigroup analyses showed that the model fit all groups adequately.

Model-based active control of a continuous structure subjected to moving loads

NASA Astrophysics Data System (ADS)

Stancioiu, D.; Ouyang, H.

2016-09-01

Modelling of a structure is an important preliminary step of structural control. The main objectives of the modelling, which are almost always antagonistic are accuracy and simplicity of the model. The first part of this study focuses on the experimental and theoretical modelling of a structure subjected to the action of one or two decelerating moving carriages modelled as masses. The aim of this part is to obtain a simple but accurate model which will include not only the structure-moving load interaction but also the actuators dynamics. A small scale rig is designed to represent a four-span continuous metallic bridge structure with miniature guiding rails. A series of tests are run subjecting the structure to the action of one or two minicarriages with different loads that were launched along the structure at different initial speeds. The second part is dedicated to model based control design where a feedback controller is designed and tested against the validated model. The study shows that a positive position feedback is able to improve system dynamics but also shows some of the limitations of state- space methods for this type of system.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

NASA Astrophysics Data System (ADS)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

Using Set Model for Learning Addition of Integers

ERIC Educational Resources Information Center

Lestari, Umi Puji; Putri, Ratu Ilma Indra; Hartono, Yusuf

2015-01-01

This study aims to investigate how set model can help students' understanding of addition of integers in fourth grade. The study has been carried out to 23 students and a teacher of IVC SD Iba Palembang in January 2015. This study is a design research that also promotes PMRI as the underlying design context and activity. Results showed that the…

[Validation of a path model on adolescents' suicidal ideation and violent behavior].

PubMed

Park, Hyun Sook

2007-10-01

This study examined the fitness of a path model on the relationship among stress, self-esteem, aggression, depression, suicidal ideation, and violent behavior for adolescents. The subjects consisted of 1,177 adolescents. Data was collected through self-report questionnaires. The data was analyzed by the SPSS and AMOS programs. Stress, self-esteem, aggression, and depression showed a direct effect on suicidal ideation for adolescents, while stress, self-esteem, and aggression showed an indirect effect on suicidal ideation for adolescents. Stress, self-esteem, aggression, and suicidal ideation showed a direct effect on violent behavior for adolescents, while stress, self-esteem, aggression, and depression showed an indirect effect on violent behavior for adolescents. The modified path model of adolescent's suicidal ideation and violent behavior was proven correct. These results suggest that adolescent's suicidal ideation and violent behavior can be decreased by reducing stress, aggression, and depression and increasing self-esteem. Based on the outcomes of this study, it is necessary to design an intervention program that emphasizes reducing stress, aggression, and depression and increasing self-esteem in order to decrease adolescents' suicide ideation and violence.

A fast wind-farm boundary-layer model to investigate gravity wave effects and upstream flow deceleration

NASA Astrophysics Data System (ADS)

Allaerts, Dries; Meyers, Johan

2017-11-01

Wind farm design and control often relies on fast analytical wake models to predict turbine wake interactions and associated power losses. Essential input to these models are the inflow velocity and turbulent intensity at hub height, which come from prior measurement campaigns or wind-atlas data. Recent LES studies showed that in some situations large wind farms excite atmospheric gravity waves, which in turn affect the upstream wind conditions. In the current study, we develop a fast boundary-layer model that computes the excitation of gravity waves and the perturbation of the boundary-layer flow in response to an applied force. The core of the model is constituted by height-averaged, linearised Navier-Stokes equations for the inner and outer layer, and the effect of atmospheric gravity waves (excited by the boundary-layer displacement) is included via the pressure gradient. Coupling with analytical wake models allows us to study wind-farm wakes and upstream flow deceleration in various atmospheric conditions. Comparison with wind-farm LES results shows excellent agreement in terms of pressure and boundary-layer displacement levels. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471).

Molecular Docking, Pharmacophore, and 3D-QSAR Approach: Can Adenine Derivatives Exhibit Significant Inhibitor Towards Ebola Virus?

PubMed Central

Rai, Amit; Aboumanei, Mohamed H.; Verma, Suraj P.; Kumar, Sachidanand; Raj, Vinit

2017-01-01

Introduction: Ebola Virus Disease (EVD) is caused by Ebola virus, which is often accompanied by fatal hemorrhagic fever upon infection in humans. This virus has caused the majority of deaths in human. There are no proper vaccinations and medications available for EVD. It is pivoting the attraction of scientist to develop the potent vaccination or novel lead to inhibit Ebola virus. Methods & Materials: In the present study, we developed 3D-QSAR and the pharmacophoric model from the previous reported potent compounds for the Ebola virus. Results & Discussion: Results & Discussion: The pharmacophoric model AAAP.116 was generated with better survival value and selectivity. Moreover, the 3D-QSAR model also showed the best r2 value 0.99 using PLS factor. Thereby, we found the higher F value, which demonstrated the statistical significance of both the models. Furthermore, homological modeling and molecular docking study were performed to analyze the affinity of the potent lead. This showed the best binding energy and bond formation with targeted protein. Conclusion: Finally, all the results of this study concluded that 3D-QSAR and Pharmacophore models may be helpful to search potent lead for EVD treatment in future. PMID:29387271

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

NASA Astrophysics Data System (ADS)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Factors associated with parasite dominance in fishes from Brazil.

PubMed

Amarante, Cristina Fernandes do; Tassinari, Wagner de Souza; Luque, Jose Luis; Pereira, Maria Julia Salim

2016-06-14

The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

Using a Novel Transgenic Mouse Model to Study c-Myc Oncogenic Pathway in Castration Resistance and Chemoresistance of Prostate Cancer

DTIC Science & Technology

2017-12-01

AWARD NUMBER: W81XWH-13-1-0162 TITLE: Using a Novel Transgenic Mouse Model to Study c-Myc Oncogenic Pathway in Castration Resistance and...DATES COVERED 15Sept2013 - 14Sept2017 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Using a Novel Transgenic Mouse Model to Study c-Myc Oncogenic...for concisely studying castration response and CRPC. However, most mice never developed significant tumors. Here, we showed that ablation of p53 in this

Design, synthesis and molecular modeling studies of novel thiazolidine-2,4-dione derivatives as potential anti-cancer agents

NASA Astrophysics Data System (ADS)

Asati, Vivek; Bharti, Sanjay Kumar

2018-02-01

A series of novel thiazolidine-2,4-dione derivatives 4a-x have been designed, synthesized and evaluated for potential anti-cancer activity. The anti-cancer activity of synthesized compounds 4a-x were evaluated against selected human cancer cell line of breast (MCF-7) using sulforhodamine B (SRB) method. Among the synthesized compounds, 4x having 2-cyano phenyl group showed significant cytotoxic activity which is comparable to that of adriamycin as standard anti-cancer drug. The SAR study revealed that the substituted phenyl group on oxadiazole ring attached to thiazolidine-2,4-dione moiety showed significant growth inhibitory activity against MCF-7 cell line. The result of molecular modeling studies showed that compounds 4f, 4o and 4x having similar structural alignment as crystal ligand of protein.

On the kinetics of anaerobic power

PubMed Central

2012-01-01

Background This study investigated two different mathematical models for the kinetics of anaerobic power. Model 1 assumes that the work power is linear with the work rate, while Model 2 assumes a linear relationship between the alactic anaerobic power and the rate of change of the aerobic power. In order to test these models, a cross country skier ran with poles on a treadmill at different exercise intensities. The aerobic power, based on the measured oxygen uptake, was used as input to the models, whereas the simulated blood lactate concentration was compared with experimental results. Thereafter, the metabolic rate from phosphocreatine break down was calculated theoretically. Finally, the models were used to compare phosphocreatine break down during continuous and interval exercises. Results Good similarity was found between experimental and simulated blood lactate concentration during steady state exercise intensities. The measured blood lactate concentrations were lower than simulated for intensities above the lactate threshold, but higher than simulated during recovery after high intensity exercise when the simulated lactate concentration was averaged over the whole lactate space. This fit was improved when the simulated lactate concentration was separated into two compartments; muscles + internal organs and blood. Model 2 gave a better behavior of alactic energy than Model 1 when compared against invasive measurements presented in the literature. During continuous exercise, Model 2 showed that the alactic energy storage decreased with time, whereas Model 1 showed a minimum value when steady state aerobic conditions were achieved. During interval exercise the two models showed similar patterns of alactic energy. Conclusions The current study provides useful insight on the kinetics of anaerobic power. Overall, our data indicate that blood lactate levels can be accurately modeled during steady state, and suggests a linear relationship between the alactic anaerobic power and the rate of change of the aerobic power. PMID:22830586

Spreading of nonmotile bacteria on a hard agar plate: Comparison between agent-based and stochastic simulations

NASA Astrophysics Data System (ADS)

Rana, Navdeep; Ghosh, Pushpita; Perlekar, Prasad

2017-11-01

We study spreading of a nonmotile bacteria colony on a hard agar plate by using agent-based and continuum models. We show that the spreading dynamics depends on the initial nutrient concentration, the motility, and the inherent demographic noise. Population fluctuations are inherent in an agent-based model, whereas for the continuum model we model them by using a stochastic Langevin equation. We show that the intrinsic population fluctuations coupled with nonlinear diffusivity lead to a transition from a diffusion limited aggregation type of morphology to an Eden-like morphology on decreasing the initial nutrient concentration.

Bayesian learning and the psychology of rule induction

PubMed Central

Endress, Ansgar D.

2014-01-01

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data. PMID:23454791

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

Hybrid lattice gas simulations of flow through porous media

NASA Astrophysics Data System (ADS)

Becklehimer, Jeffrey Lynn

1997-10-01

This study introduces a suite of models designed to investigate transport phenomena in simulated porous media such as rigid or quenched sediment and clay-like deformable environments. This is achieved by using a variety of techniques that are borrowed from the field of statistical physics. These techniques include percolation, lattice gas, and cellular automata. A percolation-based model is used to study a porous medium by using rods and chains of various shapes and sizes to model the porous media formed by sediments. This is further extended to model clay-like deformable media by interacting heavy sediment particles. An interacting lattice gas computer simulation model based on the Metropolis algorithm is used to study the transport properties of fluid particles and permeability of a porous sediment. Finally, a hybrid lattice gas model is introduced by combining the Metropolis Monte Carlo method with a direct simulation which involves the collision rules as in cellular automata. This model is then used to study shock propagation in a fluid filled porous medium. This study is then extended to study shock propagation through in a fluid filled elastic porous medium. Several interesting and new results were obtained. These results show that for rigid chain percolation the percolation threshold shows a dependence on the chain length of pc~ Lc-1/2 and the jamming coverage decreases with the chain length as Lc- 1/3. For the random SAW-like chains the percolation threshold decays with the chain length as Lc- 0.01 and the jamming coverage as Lc-1/3. The fluid flow model shows that permeability depends nonmonotonically on the concentration of the fluid. For some fluids at a fixed porosity, the permeability increases on increasing the bias until a certain value Bc above which it decreases. Also, it was found that a shock propagates in a drift-like fashion when in a rigid porous medium when the porosity is high; low porosity damps out the shock front very quickly. For a shock propagating in a clay-like porous medium an unusually super-fast power-law behavior is observed for the RMS displacements of the fluid and clay particles.

Molecular modeling studies of 1,4-dihydro-4-oxoquinoline ribonucleosides with anti-HSV-1 activity

NASA Astrophysics Data System (ADS)

Yoneda, Julliane Diniz; Albuquerque, Magaly Girão; Leal, Kátia Zaccur; Seidl, Peter Rudolf; de Alencastro, Ricardo Bicca

2011-12-01

Eight human herpes viruses ( e.g., herpes simplex, varicella-zoster, Epstein-Barr, cytomegalovirus, Kaposi's sarcoma) are responsible for several diseases from sub-clinic manifestations to fatal infections, mostly in immunocompromised patients. The major limitations of the currently available antiviral drug therapy are drug resistance, host toxicity, and narrow spectrum of activity. However, some non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives ( e.g., PNU-183792) [4] shows broad spectrum antiviral activity. We have developed molecular modeling studies, including molecular docking and molecular dynamics simulations, based on a model proposed by Liu and co-workers [14] in order to understand the mechanism of action of a 6-chloro substituted 1,4-dihydro-4-oxoquinoline ribonucleoside, synthesized by the synthetic group, which showed anti-HSV-1 activity [9]. The molecular docking simulations confirmed the Liu's model showing that the ligand needs to dislocate template residues from the active site in order to interact with the viral DNA polymerase enzyme, reinforcing that the interaction with the Val823 residue is pivotal for the inhibitory activity of non-nucleoside 1,4-dihydro-4-oxoquinoline derivatives, such as PNU-183792, with the HSV-1. The molecular dynamics simulations showed that the 6-chloro-benzyl group of PNU-183792 maintains its interaction with residues of the HSV-1 DNA polymerase hydrophobic pocket, considered important according to the Liu's model, and also showed that the methyl group bounded to the nitrogen atom from PNU-183792 is probably contributing to a push-pull effect with the carbonyl group.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862

Assessment of groundwater vulnerability by applying the modified DRASTIC model in Beihai City, China.

PubMed

Wu, Xiaoyu; Li, Bin; Ma, Chuanming

2018-05-01

This study assesses vulnerability of groundwater to pollution in Beihai City, China, as a support of groundwater resource protection. The assessment result not only objectively reflects potential possibility of groundwater to contamination but also provides scientific basis for the planning and utilization of groundwater resources. This study optimizes the parameters consisting of natural factors and human factors upon the DRASTIC model and modifies the ratings of these parameters, based on the local environmental conditions for the study area. And a weight of each parameter is assigned by the analytic hierarchy process (AHP) to reduce the subjectivity of humans to vulnerability assessment. The resulting scientific ratings and weights of modified DRASTIC model (AHP-DRASTLE model) contribute to obtain the more realistic assessment of vulnerability of groundwater to contaminant. The comparison analysis validates the accuracy and rationality of the AHP-DRASTLE model and shows it suits the particularity of the study area. The new assessment method (AHP-DRASTLE model) can provide a guide for other scholars to assess the vulnerability of groundwater to contamination. The final vulnerability map for the AHP-DRASTLE model shows four classes: highest (2%), high (29%), low (55%), and lowest (14%). The vulnerability map serves as a guide for decision makers on groundwater resource protection and land use planning at the regional scale and that it is adapted to a specific area.

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

NASA Astrophysics Data System (ADS)

Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.

2018-01-01

In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

PubMed

Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

2007-01-01

Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

A comparative simulation study of AR(1) estimators in short time series.

PubMed

Krone, Tanja; Albers, Casper J; Timmerman, Marieke E

2017-01-01

Various estimators of the autoregressive model exist. We compare their performance in estimating the autocorrelation in short time series. In Study 1, under correct model specification, we compare the frequentist r 1 estimator, C-statistic, ordinary least squares estimator (OLS) and maximum likelihood estimator (MLE), and a Bayesian method, considering flat (B f ) and symmetrized reference (B sr ) priors. In a completely crossed experimental design we vary lengths of time series (i.e., T = 10, 25, 40, 50 and 100) and autocorrelation (from -0.90 to 0.90 with steps of 0.10). The results show a lowest bias for the B sr , and a lowest variability for r 1 . The power in different conditions is highest for B sr and OLS. For T = 10, the absolute performance of all measurements is poor, as expected. In Study 2, we study robustness of the methods through misspecification by generating the data according to an ARMA(1,1) model, but still analysing the data with an AR(1) model. We use the two methods with the lowest bias for this study, i.e., B sr and MLE. The bias gets larger when the non-modelled moving average parameter becomes larger. Both the variability and power show dependency on the non-modelled parameter. The differences between the two estimation methods are negligible for all measurements.

Stereotype content model explains prejudice for an envied outgroup: Scale of anti-Asian American Stereotypes.

PubMed

Lin, Monica H; Kwan, Virginia S Y; Cheung, Anna; Fiske, Susan T

2005-01-01

The Stereotype Content Model hypothesizes anti-Asian American stereotypes differentiating two dimensions: (excessive) competence and (deficient) sociability. The Scale of Anti-Asian American Stereotypes (SAAAS) shows this envious mixed prejudice in six studies. Study 1 began with 131 racial attitude items. Studies 2 and 3 tested 684 respondents on a focused 25-item version. Studies 4 and 5 tested the final 25-item SAAAS on 222 respondents at three campuses; scores predicted outgroup friendships, cultural experiences, and (over)estimated campus presence. Study 6 showed that allegedly low sociability, rather than excessively high competence, drives rejection of Asian Americans, consistent with system justification theory. The SAAAS demonstrates mixed, envious anti-Asian American prejudice, contrasting with more-often-studied contemptuous racial prejudices (i.e., against Blacks).

ILS Localizer Performance Study : Part I. Dallas/Fort Worth Regional Airport and Model Validation - Syracuse Hancock Airport

DOT National Transportation Integrated Search

1972-07-01

The TSC electromagnetic scattering model has been used to predict the course deviation indications (CDI) at the planned Dallas Fort Worth Regional Airport. The results show that the CDI due to scattering from the modeled airport structures are within...

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

NASA Astrophysics Data System (ADS)

Rogelis, María Carolina; Werner, Micha

2018-02-01

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361

Effects of Partial Beef Fat Replacement with Gelled Emulsion on Functional and Quality Properties of Model System Meat Emulsions

PubMed Central

2016-01-01

The objective of this study was to investigate the effects of partial beef fat replacement (0, 30, 50, 100%) with gelled emulsion (GE) prepared with olive oil on functional and quality properties of model system meat emulsion (MSME). GE consisted of inulin and gelatin as gelling agent and characteristics of gelled and model system meat emulsions were investigated. GE showed good initial stability against centrifugation forces and thermal stability at different temperatures. GE addition decreased the pH with respect to increase in GE concentration. Addition of GE increased lightness and yellowness but reduced redness compared to control samples. The results of the study showed that partial replacement of beef fat with GE could be used for improving cooking yield without negative effects on water holding capacity and emulsion stability compared to C samples when replacement level is up to 50%. The presence of GE significantly affected textural behaviors of samples (p<0.05). In conclusion, our study showed that GE have promising impacts on developing healthier meat product formulations besides improving technological characteristics. PMID:28115885

Effects of Partial Beef Fat Replacement with Gelled Emulsion on Functional and Quality Properties of Model System Meat Emulsions.

PubMed

Serdaroğlu, Meltem; Nacak, Berker; Karabıyıkoğlu, Merve; Keser, Gökçen

2016-01-01

The objective of this study was to investigate the effects of partial beef fat replacement (0, 30, 50, 100%) with gelled emulsion (GE) prepared with olive oil on functional and quality properties of model system meat emulsion (MSME). GE consisted of inulin and gelatin as gelling agent and characteristics of gelled and model system meat emulsions were investigated. GE showed good initial stability against centrifugation forces and thermal stability at different temperatures. GE addition decreased the pH with respect to increase in GE concentration. Addition of GE increased lightness and yellowness but reduced redness compared to control samples. The results of the study showed that partial replacement of beef fat with GE could be used for improving cooking yield without negative effects on water holding capacity and emulsion stability compared to C samples when replacement level is up to 50%. The presence of GE significantly affected textural behaviors of samples ( p <0.05). In conclusion, our study showed that GE have promising impacts on developing healthier meat product formulations besides improving technological characteristics.

Sex and Self-Control Theory: The Measures and Causal Model May Be Different

ERIC Educational Resources Information Center

Higgins, George E.; Tewksbury, Richard

2006-01-01

This study examines the distribution differences across sexes in key measures of self-control theory and differences in a causal model. Using cross-sectional data from juveniles ("n" = 1,500), the study shows mean-level differences in many of the self-control, risky behavior, and delinquency measures. Structural equation modeling…

Lack of Norovirus Replication and Histo-Blood Group Antigen Expression in 3-Dimensional Intestinal Epithelial Cells

PubMed Central

Radtke, Andrea L.; Lay, Margarita K.; Hjelm, Brooke E.; Bolick, Alice N.; Sarker, Shameema S.; Atmar, Robert L.; Kingsley, David H.; Arntzen, Charles J.; Estes, Mary K.; Nickerson, Cheryl A.

2013-01-01

Noroviruses (NoVs) are a leading cause of gastroenteritis worldwide. An in vitro model for NoV replication remains elusive, making study of the virus difficult. A previous study, which used a 3-dimensional (3-D) intestinal model derived from INT-407 cells reported NoV replication and extensive cytopathic effects (CPE). Using the same 3-D model, but with highly purified Norwalk virus (NV), we attempted to replicate this study. Our results showed no evidence of NV replication by real-time PCR of viral RNA or by immunocytochemical detection of viral structural and nonstructural proteins. Immunocytochemical analysis of the 3-D cultures also showed no detectable presence of histo-blood group antigens that participate in NV binding and host tropism. To determine the potential cause of CPE observed in the previous study, we exposed 3-D cultures to lipopolysaccharide concentrations consistent with contaminated stool samples and observed morphologic features similar to CPE. We conclude that the 3-D INT-407 model does not support NV replication. PMID:23622517

Bioengineered humanized livers as better three-dimensional drug testing model system.

PubMed

Vishwakarma, Sandeep Kumar; Bardia, Avinash; Lakkireddy, Chandrakala; Nagarapu, Raju; Habeeb, Md Aejaz; Khan, Aleem Ahmed

2018-01-27

To develop appropriate humanized three-dimensional ex-vivo model system for drug testing. Bioengineered humanized livers were developed in this study using human hepatic stem cells repopulation within the acellularized liver scaffolds which mimics with the natural organ anatomy and physiology. Six cytochrome P-450 probes were used to enable efficient identification of drug metabolism in bioengineered humanized livers. The drug metabolism study in bioengineered livers was evaluated to identify the absorption, distribution, metabolism, excretion and toxicity responses. The bioengineered humanized livers showed cellular and molecular characteristics of human livers. The bioengineered liver showed three-dimensional natural architecture with intact vasculature and extra-cellular matrix. Human hepatic cells were engrafted similar to the human liver. Drug metabolism studies provided a suitable platform alternative to available ex-vivo and in vivo models for identifying cellular and molecular dynamics of pharmacological drugs. The present study paves a way towards the development of suitable humanized preclinical model systems for pharmacological testing. This approach may reduce the cost and time duration of preclinical drug testing and further overcomes on the anatomical and physiological variations in xenogeneic systems.

Investigating How German Biology Teachers Use Three-Dimensional Physical Models in Classroom Instruction: a Video Study

NASA Astrophysics Data System (ADS)

Werner, Sonja; Förtsch, Christian; Boone, William; von Kotzebue, Lena; Neuhaus, Birgit J.

2017-07-01

To obtain a general understanding of science, model use as part of National Education Standards is important for instruction. Model use can be characterized by three aspects: (1) the characteristics of the model, (2) the integration of the model into instruction, and (3) the use of models to foster scientific reasoning. However, there were no empirical results describing the implementation of National Education Standards in science instruction concerning the use of models. Therefore, the present study investigated the implementation of different aspects of model use in German biology instruction. Two biology lessons on the topic neurobiology in grade nine of 32 biology teachers were videotaped (N = 64 videos). These lessons were analysed using an event-based coding manual according to three aspects of model described above. Rasch analysis of the coded categories was conducted and showed reliable measurement. In the first analysis, we identified 68 lessons where a total of 112 different models were used. The in-depth analysis showed that special aspects of an elaborate model use according to several categories of scientific reasoning were rarely implemented in biology instruction. A critical reflection of the used model (N = 25 models; 22.3%) and models to demonstrate scientific reasoning (N = 26 models; 23.2%) were seldom observed. Our findings suggest that pre-service biology teacher education and professional development initiatives in Germany have to focus on both aspects.

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

PubMed

Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

Dynamical quantum phase transitions in extended transverse Ising models

NASA Astrophysics Data System (ADS)

Bhattacharjee, Sourav; Dutta, Amit

2018-04-01

We study the dynamical quantum phase transitions (DQPTs) manifested in the subsequent unitary dynamics of an extended Ising model with an additional three spin interactions following a sudden quench. Revisiting the equilibrium phase diagram of the model, where different quantum phases are characterized by different winding numbers, we show that in some situations the winding number may not change across a gap closing point in the energy spectrum. Although, usually there exists a one-to-one correspondence between the change in winding number and the number of critical time scales associated with DQPTs, we show that the extended nature of interactions may lead to unusual situations. Importantly, we show that in the limit of the cluster Ising model, three critical modes associated with DQPTs become degenerate, thereby leading to a single critical time scale for a given sector of Fisher zeros.

Role of damping in spin Seebeck effect in yttrium iron garnet thin films

PubMed Central

Chang, Houchen; Praveen Janantha, P. A.; Ding, Jinjun; Liu, Tao; Cline, Kevin; Gelfand, Joseph N.; Li, Wei; Marconi, Mario C.; Wu, Mingzhong

2017-01-01

The role of damping in the spin Seebeck effect (SSE) was studied experimentally for the first time. The experiments used Y3Fe5O12 (YIG)/Pt bilayered structures where the YIG films exhibit very similar structural and static magnetic properties but very different damping. The data show that a decrease in the damping gives rise to an increase in the SSE coefficient, which is qualitatively consistent with some of the theoretical models. This response also shows quasi-linear behavior, which was not predicted explicitly by previous studies. The data also indicate that the SSE coefficient shows no notable correlations with the enhanced damping due to spin pumping, which can be understood in the frame of two existing models. PMID:28435873

Molecular modeling and biological evaluation of 2-N,N-dimethylaminecyclohexyl 1-N‧,N‧-dimethylcarbamate isomers and their methylsulfate salts as cholinesterases inhibitors

NASA Astrophysics Data System (ADS)

Bocca, Cleverson C.; Rittner, Roberto; Höehr, Nelci F.; Pinheiro, Glaucia M. S.; Abiko, Layara A.; Basso, Ernani A.

2010-11-01

This work presents a detailed theoretical and experimental study on the inhibitory properties of 2- N,N-dimethylaminecyclohexyl 1- N',N'-dimethylcarbamate isomers and their methylsulfate salts against the cholinesterases enzymes. The in vitro inhibition test performed by the Ellman's method showed that the salt form compounds were more active than the neutral ones in cholinesterases inhibition. The trans salt showed good selectivity towards the inhibition of erythrocyte cholinesterase with a maximum limit around 90% and 55% for the plasma cholinesterase inhibition. Molecular modeling, docking and experimental results performed in this study showed to be important initial steps toward the development of a novel pharmaceuticals in the fight against Alzheimer's disease.

Dynamics of Nearest-Neighbour Competitions on Graphs

NASA Astrophysics Data System (ADS)

Rador, Tonguç

2017-10-01

Considering a collection of agents representing the vertices of a graph endowed with integer points, we study the asymptotic dynamics of the rate of the increase of their points according to a very simple rule: we randomly pick an an edge from the graph which unambiguously defines two agents we give a point the the agent with larger point with probability p and to the lagger with probability q such that p+q=1. The model we present is the most general version of the nearest-neighbour competition model introduced by Ben-Naim, Vazquez and Redner. We show that the model combines aspects of hyperbolic partial differential equations—as that of a conservation law—graph colouring and hyperplane arrangements. We discuss the properties of the model for general graphs but we confine in depth study to d-dimensional tori. We present a detailed study for the ring graph, which includes a chemical potential approximation to calculate all its statistics that gives rather accurate results. The two-dimensional torus, not studied in depth as the ring, is shown to possess critical behaviour in that the asymptotic speeds arrange themselves in two-coloured islands separated by borders of three other colours and the size of the islands obey power law distribution. We also show that in the large d limit the d-dimensional torus shows inverse sine law for the distribution of asymptotic speeds.

Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partial antagonism

NASA Astrophysics Data System (ADS)

Kurmyshev, Evguenii; Juárez, Héctor A.; González-Silva, Ricardo A.

2011-08-01

Bounded confidence models of opinion dynamics in social networks have been actively studied in recent years, in particular, opinion formation and extremism propagation along with other aspects of social dynamics. In this work, after an analysis of limitations of the Deffuant-Weisbuch (DW) bounded confidence, relative agreement model, we propose the mixed model that takes into account two psychological types of individuals. Concord agents (C-agents) are friendly people; they interact in a way that their opinions always get closer. Agents of the other psychological type show partial antagonism in their interaction (PA-agents). Opinion dynamics in heterogeneous social groups, consisting of agents of the two types, was studied on different social networks: Erdös-Rényi random graphs, small-world networks and complete graphs. Limit cases of the mixed model, pure C- and PA-societies, were also studied. We found that group opinion formation is, qualitatively, almost independent of the topology of networks used in this work. Opinion fragmentation, polarization and consensus are observed in the mixed model at different proportions of PA- and C-agents, depending on the value of initial opinion tolerance of agents. As for the opinion formation and arising of “dissidents”, the opinion dynamics of the C-agents society was found to be similar to that of the DW model, except for the rate of opinion convergence. Nevertheless, mixed societies showed dynamics and bifurcation patterns notably different to those of the DW model. The influence of biased initial conditions over opinion formation in heterogeneous social groups was also studied versus the initial value of opinion uncertainty, varying the proportion of the PA- to C-agents. Bifurcation diagrams showed an impressive evolution of collective opinion, in particular, radical changes of left to right consensus or vice versa at an opinion uncertainty value equal to 0.7 in the model with the PA/C mixture of population near 50/50.

Experimental Research on the Dense CFB's Riser and the Simulation Based on the EMMS Model

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Wang, S. D.; Fan, B. G.; Liao, L. L.; Jiang, F.; Xu, X.; Wu, X. Z.; Xiao, Y. H.

2010-03-01

The flow structure in the CFB (circulating fluidized bed) riser has been investigated. Experimental studies were performed in a cold square section unit with 270 mm×270 mm×10 m. Since the drag force model based on homogeneous two-phase flow such as the Gidaspow drag model could not depict the heterogeneous structures of the gas-solid flow, the structure-dependent energy-minimization multi-scale (EMMS) model based on the heterogenerity was applied in the paper and a revised drag force model based on the EMMS model was proposed. A 2D two-fluid model was used to simulate a bench-scale square cross-section riser of a cold CFB. The typical core-annulus structure and the back-mixing near the wall of the riser were observed and the assembly and fragmentation processes of clusters were captured. By comparing with the Gidaspow drag model, the results obtained by the revised drag model based on EMMS shows better consistency with the experimental data. The model can also depict the difference from the two exit configurations. This study once again proves the key role of drag force in CFD (Computational Fluid Dynamics) simulation and also shows the availability of the revised drag model to describe the gas-solid flow in CFB risers.

3D printed alendronate-releasing poly(caprolactone) porous scaffolds enhance osteogenic differentiation and bone formation in rat tibial defects.

PubMed

Kim, Sung Eun; Yun, Young-Pil; Shim, Kyu-Sik; Kim, Hak-Jun; Park, Kyeongsoon; Song, Hae-Ryong

2016-09-29

The aim of this study was to evaluate the in vitro osteogenic effects and in vivo new bone formation of three-dimensional (3D) printed alendronate (Aln)-releasing poly(caprolactone) (PCL) (Aln/PCL) scaffolds in rat tibial defect models. 3D printed Aln/PCL scaffolds were fabricated via layer-by-layer deposition. The fabricated Aln/PCL scaffolds had high porosity and an interconnected pore structure and showed sustained Aln release. In vitro studies showed that MG-63 cells seeded on the Aln/PCL scaffolds displayed increased alkaline phosphatase (ALP) activity and calcium content in a dose-dependent manner when compared with cell cultures in PCL scaffolds. In addition, in vivo animal studies and histologic evaluation showed that Aln/PCL scaffolds implanted in a rat tibial defect model markedly increased new bone formation and mineralized bone tissues in a dose-dependent manner compared to PCL-only scaffolds. Our results show that 3D printed Aln/PCL scaffolds are promising templates for bone tissue engineering applications.

Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.

Contribution of parents' adult attachment and separation attitudes to parent-adolescent conflict resolution.

PubMed

García-Ruiz, Marta; Rodrigo, María José; Hernández-Cabrera, Juan A; Máiquez, María Luisa

2013-12-01

This study examined the contribution to parent-adolescent conflict resolution of parental adult attachment styles and attitudes toward adolescent separation. Questionnaires were completed by 295 couples with early to late adolescent children. Structural equation models were used to test self and partner influences on conflict resolution for three attachment orientations: confidence (model A), anxiety (model B) and avoidance (model C). Model A showed self influences between parents' confidence orientation and negotiation and also via positive attitudes towards separation. Also, the fathers' use of negotiation was facilitated by the mothers' confidence orientation and vice versa, indicating partner influences as well. Model B showed self influences between parents' anxiety orientation and the use of dominance and withdrawal and also via negative attitudes towards separation. Model C showed self influences between parents' avoidance orientation and dominance and withdrawal, and a partner influence between fathers' avoidance and mothers' use of dominance. The results indicated that the parents' adult attachment system and the parenting system were related in the area of conflict resolution, and that self influences were stronger than partner influences. © 2013 The Scandinavian Psychological Associations.

A characterization of the ZFL cell line and primary hepatocytes as in vitro liver cell models for the zebrafish (Danio rerio).

PubMed

Eide, Marta; Rusten, Marte; Male, Rune; Jensen, Knut Helge Midtbø; Goksøyr, Anders

2014-02-01

The zebrafish (Danio rerio) is a widely used model species in biomedical research. The ZFL cell line, established from zebrafish liver, and freshly isolated primary hepatocytes from zebrafish have been used in several toxicological studies. However, no previous report has compared and characterized these two systems at the level of gene expression. The aim of this study was to evaluate the ZFL cell line in comparison to primary hepatocytes as in vitro models for studying effects of environmental contaminants in zebrafish liver. Using quantitative real-time PCR, the basal level and transcriptional induction potential of key genes involved in toxic responses in the ZFL cell line, primary hepatocytes and whole liver from zebrafish were compared. The study showed that the ZFL cells have lower levels of mRNA of most selected genes compared to zebrafish liver. The induced gene transcription following exposure to ligand was much lower in ZFL cells compared to zebrafish primary hepatocytes at the doses tested. Importantly, oestrogen receptor and vitellogenin genes showed low basal transcription and no induction response in the ZFL cell line. In conclusion, it appears that primary hepatocytes are well suited for studying environmental contaminants including xenoestrogens, but may show large sex-dependent differences in gene transcription. The ZFL cell line shows potential in toxicological studies involving the aryl hydrocarbon receptor pathway. However, low potential for transcriptional induction of genes in general should be expected, especially notable when studying estrogenic responses. Copyright © 2013 Elsevier B.V. All rights reserved.

Source emission and model evaluation of formaldehyde from composite and solid wood furniture in a full-scale chamber

NASA Astrophysics Data System (ADS)

Liu, Xiaoyu; Mason, Mark A.; Guo, Zhishi; Krebs, Kenneth A.; Roache, Nancy F.

2015-12-01

This paper describes the measurement and model evaluation of formaldehyde source emissions from composite and solid wood furniture in a full-scale chamber at different ventilation rates for up to 4000 h using ASTM D 6670-01 (2007). Tests were performed on four types of furniture constructed of different materials and from different manufacturers. The data were used to evaluate two empirical emission models, i.e., a first-order and power-law decay model. The experimental results showed that some furniture tested in this study, made only of solid wood and with less surface area, had low formaldehyde source emissions. The effect of ventilation rate on formaldehyde emissions was also examined. Model simulation results indicated that the power-law decay model showed better agreement than the first-order decay model for the data collected from the tests, especially for long-term emissions. This research was limited to a laboratory study with only four types of furniture products tested. It was not intended to comprehensively test or compare the large number of furniture products available in the market place. Therefore, care should be taken when applying the test results to real-world scenarios. Also, it was beyond the scope of this study to link the emissions to human exposure and potential health risks.

Adsorptive removal of dissolved organic matter (DOM) in landfill leachate by iron oxide nanoparticles (FeONPs)

NASA Astrophysics Data System (ADS)

Ghani, Zaidi Ab; Yusoff, Mohd Suffian; Zaman, Nastaein Qamaruz; Andas, Jeyashelly; Aziz, Hamidi Abdul

2017-10-01

A study was conducted to investigate the efficiency of iron oxide nanoparticle (FeONPs) adsorption for removing of DOM in landfill leachate. FeONPs was directly prepared via sodium borohydride (KBH4) reduction method. Adsorption kinetics, isotherm and thermodynamic studies were developed to design the model for DOM removal. Pseudo first-order and pseudo second-order model have been studied to fit the experimental data. The regression results showed that the adsorption kinetics were more accurately represented by a pseudo second-order model. The Weber-Morris intraparticle diffusion model was used to analyze the adsorption kinetics data. The plot of qt versus t1/2 represents multi linearity, which showed that the adsorption processes occurred in more than one step. Adsorption isotherms were analyzed by Langmuir, Freundlich, Tempkin and Dubinin-Radushkevich, isotherms model. Equilibrium data were well fitted to the Dubinin- Radushkevich isotherm model. Maximum monolayer adsorption based on Langmuir was calculated to be 21.74 mg/g. Thermodynamic parameters such as free energy changes (ΔG°), enthalpy (ΔH°) and entropy (ΔS°) were evaluated between temperatures of 25 °C and 40 °C. The ΔG° was noticed progressively decrease from -9.620 -9.820 -10.021, and -10.222 kJ/mol as the temperature increase. The ΔH° and ΔS° values were found to be 2.350 kJ/mol and 40.165 J/mol.K respectively. The results showed that the overall adsorption process was endothermic and spontaneous. The results from this study suggested that FeNPs could be a viable adsorbent in managing higher DOM problems associated with landfill leachate.

Gastroprotective effect of Senecio candicans DC on experimental ulcer models.

PubMed

Hariprasath, Lakshmanan; Raman, Jegadeesh; Nanjian, Raaman

2012-03-06

Senecio candicans DC (Asteraceae) is used as a remedy for gastric ulcer and stomach pain in the Nilgiris district, Tamil Nadu for which no scientific evidence exists. The present study was performed to evaluate the gastroprotective effects and acute oral toxicity of aqueous leaf extract of Senecio candicans (AESC) in experimental models. The antiulcerogenic activity of AESC was performed in two different ulcer models viz., pylorus-ligated model and ethanol-induced model using Wistar albino rats. Acute toxicity study was also performed to get information on the admissible dose for treatment of ulcer. Preliminary phytochemical screening of AESC was performed to find the active principles present, which are thus responsible for the antiulcerogenic activity. DPPH assay was performed to confirm the antioxidant activity of AESC. The acute toxicity study did not show any mortality up to 2500mg/kg b.w. of AESC. Both the ulcer models showed gastroprotective effect comparable to that of the standard Omeprazole. The results of antioxidant enzymes, histopathology sections, ATPase and mucus content of gastric secretion showed that several mechanisms are involved in the gastroprotective effect. The preliminary phytochemical screening revealed the presence of alkaloids, flavonoids and steroids in AESC. The DPPH assay confirmed the antioxidant activity of AESC. The traditional consumption of AESC for the treatment of gastric ulcer is thus true, the antioxidant constituents present in the extract plays a major role in the gastroprotective activity, but since Senecio species are known for the presence of pyrrolizidine alkaloids, a detailed study in future is required to describe the safe dose for a prolonged period. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Unification theory of optimal life histories and linear demographic models in internal stochasticity.

PubMed

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of "Stochastic Control Theory" in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path-integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models.

Effects of CYP2D6 Status on Harmaline Metabolism, Pharmacokinetics and Pharmacodynamics, and a Pharmacogenetics-Based Pharmacokinetic Model

PubMed Central

Wu, Chao; Jiang, Xi-Ling; Shen, Hong-Wu; Yu, Ai-Ming

2009-01-01

Harmaline is a β-carboline alkaloid showing neuroprotective and neurotoxic properties. Our recent studies have revealed an important role for cytochrome P450 2D6 (CYP2D6) in harmaline O-demethylation. This study, therefore, aimed to delineate the effects of CYP2D6 phenotype/genotype on harmaline metabolism, pharmacokinetics (PK) and pharmacodynamics (PD), and to develop a pharmacogenetics mechanism-based compartmental PK model. In vitro kinetic studies on metabolite formation in human CYP2D6 extensive metabolizer (EM) and poor metabolizer (PM) hepatocytes indicated that harmaline O-demethylase activity (Vmax/Km) was about 9-fold higher in EM hepatocytes. Substrate depletion showed mono-exponential decay trait, and estimated in vitro harmaline clearance (CLint, μL/min/106 cells) was significantly lower in PM hepatocytes (28.5) than EM hepatocytes (71.1). In vivo studies in CYP2D6-humanized and wild-type mouse models showed that wild-type mice were subjected to higher and longer exposure to harmaline (5 and 15 mg/kg; i.v. and i.p.), and more severe hypothermic responses. The PK/PD data were nicely described by our pharmacogenetics-based PK model involving the clearance of drug by CYP2D6 (CLCYP2D6) and other mechanisms (CLother), and an indirect response PD model, respectively. Wild-type mice were also more sensitive to harmaline in marble-burying tests, as manifested by significantly lower ED50 and steeper Hill slope. These findings suggest that distinct CYP2D6 status may cause considerable variations in harmaline metabolism, PK and PD. In addition, the pharmacogenetics-based PK model may be extended to define PK difference caused by other polymorphic drug-metabolizing enzyme in different populations. PMID:19445902

Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity

PubMed Central

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

A Heterogeneous In Vitro Three Dimensional Model of Tumour-Stroma Interactions Regulating Sprouting Angiogenesis

PubMed Central

Correa de Sampaio, Pedro; Auslaender, David; Krubasik, Davia; Failla, Antonio Virgilio; Skepper, Jeremy N.; Murphy, Gillian; English, William R.

2012-01-01

Angiogenesis, the formation of new blood vessels, is an essential process for tumour progression and is an area of significant therapeutic interest. Different in vitro systems and more complex in vivo systems have been described for the study of tumour angiogenesis. However, there are few human 3D in vitro systems described to date which mimic the cellular heterogeneity and complexity of angiogenesis within the tumour microenvironment. In this study we describe the Minitumour model – a 3 dimensional human spheroid-based system consisting of endothelial cells and fibroblasts in co-culture with the breast cancer cell line MDA-MB-231, for the study of tumour angiogenesis in vitro. After implantation in collagen-I gels, Minitumour spheroids form quantifiable endothelial capillary-like structures. The endothelial cell pre-capillary sprouts are supported by the fibroblasts, which act as mural cells, and their growth is increased by the presence of cancer cells. Characterisation of the Minitumour model using small molecule inhibitors and inhibitory antibodies show that endothelial sprout formation is dependent on growth factors and cytokines known to be important for tumour angiogenesis. The model also shows a response to anti-angiogenic agents similar to previously described in vivo data. We demonstrate that independent manipulation of the different cell types is possible, using common molecular techniques, before incorporation into the model. This aspect of Minitumour spheroid analysis makes this model ideal for high content studies of gene function in individual cell types, allowing for the dissection of their roles in cell-cell interactions. Finally, using this technique, we were able to show the requirement of the metalloproteinase MT1-MMP in endothelial cells and fibroblasts, but not cancer cells, for sprouting angiogenesis. PMID:22363483

Thermo-Mechanical Modeling of a Glacier-Permafrost System in Spitsbergen, Implications for Subglacial Hydrology

NASA Astrophysics Data System (ADS)

Roux, N.; Grenier, C.; Marlin, C.; Delangle, E.; Saintenoy, A.; Friedt, J.-M.; Griselin, M.

2012-04-01

To study the hydro-glaciological response of glaciers impacted by recent climate change, the Austre Lovenbreen polar glacierized watershed (10 km2 located in West Spitsbergen, 79°N) was monitored. Field surveys show winter water discharges causing large icings. A 2D modeling approach along the main axis of the system is developed to study the thermal evolution of the glacier-bed system. Two codes are chained (cf. Pimentel et al. (2010) for the Thermo-Mechanical evolution of the glacier and Cast3M for the Thermal evolution of the substrate - www-cast3m.cea.fr). Transient reconstructions confirm radar study conclusions showing that the glacier is polythermal with a cold based terminus. Moreover, its rapid retreat (ca. 18 m.a-1) should lead to a cold glacier within decades to a century. Simulations further show that permafrost development in the substrate precedes glacier retreat (thin glacier tongue with -5°C MAAT at Ny Alesund) while in the mountainous part, a somewhat stable glacier position allowed permafrost to develop deeper over longer times. Prospective simulations of permafrost development show that the unfrozen soil extension below the glacier will progressively reduce probably causing the disappearance or a strong reduction of winter discharges within the next century. Further experimental and modeling studies are contemplated to understand the major processes controlling subglacial permafrost development, winter flows as well as their future evolution.

Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances

PubMed Central

2018-01-01

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework. PMID:29533657

Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances.

PubMed

Deetman, Sebastiaan; Pauliuk, Stefan; van Vuuren, Detlef P; van der Voet, Ester; Tukker, Arnold

2018-04-17

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Applying the Technology Acceptance Model and flow theory to Cyworld user behavior: implication of the Web2.0 user acceptance.

PubMed

Shin, Dong-Hee; Kim, Won-Yong; Kim, Won-Young

2008-06-01

This study explores attitudinal and behavioral patterns when using Cyworld by adopting an expanded Technology Acceptance Model (TAM). A model for Cyworld acceptance is used to examine how various factors modified from the TAM influence acceptance and its antecedents. This model is examined through an empirical study involving Cyworld users using structural equation modeling techniques. The model shows reasonably good measurement properties and the constructs are validated. The results not only confirm the model but also reveal general factors applicable to Web2.0. A set of constructs in the model can be the Web2.0-specific factors, playing as enhancing factor to attitudes and intention.

Simple universal models capture all classical spin physics.

PubMed

De las Cuevas, Gemma; Cubitt, Toby S

2016-03-11

Spin models are used in many studies of complex systems because they exhibit rich macroscopic behavior despite their microscopic simplicity. Here, we prove that all the physics of every classical spin model is reproduced in the low-energy sector of certain "universal models," with at most polynomial overhead. This holds for classical models with discrete or continuous degrees of freedom. We prove necessary and sufficient conditions for a spin model to be universal and show that one of the simplest and most widely studied spin models, the two-dimensional Ising model with fields, is universal. Our results may facilitate physical simulations of Hamiltonians with complex interactions. Copyright © 2016, American Association for the Advancement of Science.

Exploiting the functional and taxonomic structure of genomic data by probabilistic topic modeling.

PubMed

Chen, Xin; Hu, Xiaohua; Lim, Tze Y; Shen, Xiajiong; Park, E K; Rosen, Gail L

2012-01-01

In this paper, we present a method that enable both homology-based approach and composition-based approach to further study the functional core (i.e., microbial core and gene core, correspondingly). In the proposed method, the identification of major functionality groups is achieved by generative topic modeling, which is able to extract useful information from unlabeled data. We first show that generative topic model can be used to model the taxon abundance information obtained by homology-based approach and study the microbial core. The model considers each sample as a “document,” which has a mixture of functional groups, while each functional group (also known as a “latent topic”) is a weight mixture of species. Therefore, estimating the generative topic model for taxon abundance data will uncover the distribution over latent functions (latent topic) in each sample. Second, we show that, generative topic model can also be used to study the genome-level composition of “N-mer” features (DNA subreads obtained by composition-based approaches). The model consider each genome as a mixture of latten genetic patterns (latent topics), while each functional pattern is a weighted mixture of the “N-mer” features, thus the existence of core genomes can be indicated by a set of common N-mer features. After studying the mutual information between latent topics and gene regions, we provide an explanation of the functional roles of uncovered latten genetic patterns. The experimental results demonstrate the effectiveness of proposed method.

Systematic review: The model for end-stage liver disease--should it replace Child-Pugh's classification for assessing prognosis in cirrhosis?

PubMed

Cholongitas, E; Papatheodoridis, G V; Vangeli, M; Terreni, N; Patch, D; Burroughs, A K

2005-12-01

Prognosis in cirrhotic patients has had a resurgence of interest because of liver transplantation and new therapies for complications of end-stage cirrhosis. The model for end-stage liver disease score is now used for allocation in liver transplantation waiting lists, replacing Child-Turcotte-Pugh score. However, there is debate as whether it is better in other settings of cirrhosis. To review studies comparing the accuracy of model for end-stage liver disease score vs. Child-Turcotte-Pugh score in non-transplant settings. Transjugular intrahepatic portosystemic shunt studies (with 1360 cirrhotics) only one of five, showed model for end-stage liver disease to be superior to Child-Turcotte-Pugh to predict 3-month mortality, but not for 12-month mortality. Prognosis of cirrhosis studies (with 2569 patients) none of four showed significant differences between the two scores for either short- or long-term prognosis whereas no differences for variceal bleeding studies (with 411 cirrhotics). Modified Child-Turcotte-Pugh score, by adding creatinine, performed similarly to model for end-stage liver disease score. Hepatic encephalopathy and hyponatraemia (as an index of ascites), both components of Child-Turcotte-Pugh score, add to the prognostic performance of model for end-stage liver disease score. Based on current literature, model for end-stage liver disease score does not perform better than Child-Turcotte-Pugh score in non-transplant settings. Modified Child-Turcotte-Pugh and model for end-stage liver disease scores need further evaluation.

A simple model for strong ground motions and response spectra

USGS Publications Warehouse

Safak, Erdal; Mueller, Charles; Boatwright, John

1988-01-01

A simple model for the description of strong ground motions is introduced. The model shows that response spectra can be estimated by using only four parameters of the ground motion, the RMS acceleration, effective duration and two corner frequencies that characterize the effective frequency band of the motion. The model is windowed band-limited white noise, and is developed by studying the properties of two functions, cumulative squared acceleration in the time domain, and cumulative squared amplitude spectrum in the frequency domain. Applying the methods of random vibration theory, the model leads to a simple analytical expression for the response spectra. The accuracy of the model is checked by using the ground motion recordings from the aftershock sequences of two different earthquakes and simulated accelerograms. The results show that the model gives a satisfactory estimate of the response spectra.

Biofilm Community Diversity after Exposure to 0.4% Stannous Fluoride Gels

PubMed Central

Reilly, Cavan; Rasmussen, Karin; Selberg, Tieg; Stevens, Justin; Jones, Robert S.

2015-01-01

Aims To test the effect of %0.4 stannous fluoride (SnF2) glycerin based gels on the bacterial ecology in both a clinical observational study and in vitro polymicobial biofilm model. Methods and Results The influence of stannous fluoride (0.4% SnF2) gels on bacteria was tested in both an observational study in children 6-12 years of age (n=20) and an in vitro biofilm model system. The plaque derived multi-species bacterial biofilm model was based on clinical bacterial strains derived directly from the clinical study. Potential changes in the plaque ecology were determined through the Human Oral Microbial Identification Microarray-HOMIM (n=10). The semiquantitative data resulting from this system were analyzed with cumulative logit models for each bacterial strain and Bonferroni adjustments were employed to correct for multiple hypothesis testing. Both hierarchical biclustering and principal components analysis were used to graphically assess reproducibility within subjects over time. Mixed effects models were used to examine changes in plaque scores and numbers of bacterial strains found in the various conditions. Conclusions Both the observational clinical study and the biofilm model showed that short-term use of 0.4% SnF2 gel has little effect on the bacterial plaque ecology. The amount of plaque accumulation on a subject's teeth, which was measured by plaque index scores failed to show statistical significant changes over the two baselines or after treatment (p=0.9928). The in vitro results were similar when examining the effect of 0.4% SnF2 gels on biofilm adherence through a crystal violet assay (p= 0.1157). Significance and Impact of the Study The bacteria within the dental biofilms showed resilience in maintaining the overall community diversity after exposure to 0.4% Stannous Fluoride Gels. The study supports that the immediate benefits of using these gels each night to manage caries in children may be strictly from fluoride ions inhibiting tooth demineralization. PMID:25263195

Sci-Sat AM(2): Brachy-05: Dosimetry effects of the TG-43 approximations for two iodine seeds in LDR brachytherapy.

PubMed

Furstoss, C; Bertrand, M J; Poon, E; Reniers, B; Pignol, J P; Carrier, J F; Beaulieu, L; Verhaegen, F

2008-07-01

This work consists of studying the interseed and tissue composition effects for two model iodine seeds: the IBt Interseed-125 and the 6711 model seed. Three seeds were modeled with the MCNP MC code in a water sphere to evaluate the interseed effect. The dose calculated at different distances from the centre was compared to the dose summed when the seeds were simulated separately. The tissue composition effect was studied calculating the radial dose function for different tissues. Before carrying out post-implant studies, the absolute dose calculated by MC was compared to experiment results: with LiF TLDs in an acrylic breast phantom and with an EBT Gafchromic film placed in a water tank. Afterwards, the TG-43 approximation effects were studied for a prostate and breast post-implant. The interseed effect study shows that this effect is more important for model 6711 (15%) than for IBt (10%) due to the silver rod in 6711. For both seed models the variations of the radial dose function as a function of the tissue composition are quasi similar. The absolute dose comparisons between MC calculations and experiments give good agreement (inferior to 3% in general). For the prostate and breast post-implant studies, a 10% difference between MC calculations and the TG-43 is found for both models of seeds. This study shows that the differences in dose distributions between TG43 and MC are quite similar for the two models of seeds and are about 10% for the studied post-implant treatments. © 2008 American Association of Physicists in Medicine.

A non-isotropic multiple-scale turbulence model

NASA Technical Reports Server (NTRS)

Chen, C. P.

1990-01-01

A newly developed non-isotropic multiple scale turbulence model (MS/ASM) is described for complex flow calculations. This model focuses on the direct modeling of Reynolds stresses and utilizes split-spectrum concepts for modeling multiple scale effects in turbulence. Validation studies on free shear flows, rotating flows and recirculating flows show that the current model perform significantly better than the single scale k-epsilon model. The present model is relatively inexpensive in terms of CPU time which makes it suitable for broad engineering flow applications.

Mouse Model for the Preclinical Study of Metastatic Disease | NCI Technology Transfer Center | TTC

Cancer.gov

The Laboratory of Cancer Biology and Genetics, National Cancer Institute seeks partners for collaborative research to co-develop a mouse model that shows preclinical therapeutic response of residual metastatic disease.

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

USGS Publications Warehouse

Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M. G.; Pam Struffolino,; Loftin, Keith A.

2015-11-06

The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Geochemical study of stream waters affected by mining activities in the SE Spain

NASA Astrophysics Data System (ADS)

Garcia-Lorenzo, Maria Luz; Perez-Sirvent, Carmen; Martinez-Sanchez, Maria Jose; Bech, Jaime

2015-04-01

Water pollution by dissolved metals in mining areas has mainly been associated with the oxidation of sulphide-bearing minerals exposed to weathering conditions, resulting in low quality effluents of acidic pH and containing a high level of dissolved metals. According to transport process, three types of pollution could be established: a) Primary contamination, formed by residues placed close to the contamination sources; b) Secondary contamination, produced as a result of transport out of its production areas; c) Tertiary contamination. The aim of this work was to study trace element in water samples affected by mining activities and to apply the MINTEQ model for calculating aqueous geochemical equilibria. The studied area constituted an important mining centre for more than 2500 years, ceasing activity in 1991. The ore deposits of this zone have iron, lead and zinc as the main metal components. As a result, a lot of contaminations sources, formed by mining steriles, waste piles and foundry residues are present. For this study, 36 surficial water samples were collected after a rain episode in 4 different areas. In these samples, the trace element content was determined by by flame atomic absorption spectrometry (Fe and Zn), electrothermal atomization atomic absorption spectrometry (Pb and Cd), atomic fluorescence spectrometry (As) and ICP-MS for Al. MINTEQA2 is a geochemical equilibrium speciation model capable of computing equilibria among the dissolved, adsorbed, solid, and gas phases in an environmental setting and was applied to collected waters. Zone A: A5 is strongly influenced by tailing dumps and showed high trace element content. In addition, is influenced by the sea water and then showed high bromide, chloride, sodium and magnesium content, together with a basic pH. The MINTEQ model application suggested that Zn and Cd could precipitate as carbonate (hidrocincite, smithsonite and otavite). A9 also showed acid pH and high trace element content; is influenced by tailing dumps and also by waters from gully watercourses, transporting materials from Sierra Minera. The MINTEQ simulation showed that Pb and Ca could precipitate as sulphates (anglesite and gypsum). Waters affected by secondary contamination have been mixed with carbonate materials, present in the zone increasing the pH. Some elements have precipitated, such as Cu and Pb, while Cd, Zn and As are soluble. The MINTEQ model results showed that in A10 and A14, Al could precipitate as diaspore but also carbonates could be formed, particularly dolomite. These model in A12 sample showed that soluble Zn could precipitate as carbonate and Al as oxyhydroxide, similarly than in A13. A2 and A6 waters are affected by tertiary contamination and showed basic pH, soluble carbonates and lower trace element content. Only Zn, Cd and Al are present. The speciation model showed that in A2, Cd and Zn could precipitate as carbonates while Al as oxihydroxide. In A6, the model suggested that soluble Pb could precipitate as carbonate (hidrocerusite and cerusite) or as hydroxide; Al as diaspore, Ca as calcite and Fe as hematite. Zone B: All waters are strongly affected by mining activities and showed acid pH, high trace element content and high content of soluble sulphates. The MINTEQ results showed that in B8, Fe could precipitate as hydroxychloride and in B12 could form alunite. In B9, B10, B13 y B14, the model estimates the precipitation of anglesite, gypsum and Fe hydroxichloride (B9 and B10), diaspore in B13 and B14, and gypsum and Fe hydroxychloride in B13. All the sampling points collected in Zone C are affected by primary contamination, because there are a lot of tailing dumps. C1 showed high trace element content because is a reception point of a lot of tailing dumps. Water samples from C3 to C8 also had acid pH and high trace element content, particularly As, Zn and Cd. In addition, they showed high soluble sulphates. C2 water showed neutral pH, soluble carbonate and low trace element content because is influenced by a stabilised tailing dump. In all samples, except C2, the MINTEQ model showed that a lot of efflorescences could be formed, mainly sulphates. Zone D: All waters collected in this zone showed acid pH and high trace element content, mainly Zn, Cd and As. MINTEQ model results showed that elements could precipitate as jarosite but also anglesite in D8 and gypsum in D9, D11 and D12. D1 is affected by secondary contamination, which showed higher pH (still acid) and lower content in soluble salts and trace elements. The MINTEQ model suggested that Al could precipitate as diaspore, gibbsite and alunite. The applied model is an appropriate tool for the analysis of waters affected by mining activities. The obtained simulations confirm natural attenuation processes.

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Complexity analysis of dual-channel game model with different managers' business objectives

NASA Astrophysics Data System (ADS)

Li, Ting; Ma, Junhai

2015-01-01

This paper considers dual-channel game model with bounded rationality, using the theory of bifurcations of dynamical system. The business objectives of retailers are assumed to be different, which is closer to reality than previous studies. We study the local stable region of Nash equilibrium point and find that business objectives can expand the stable region and play an important role in price strategy. One interesting finding is that a fiercer competition tends to stabilize the Nash equilibrium. Simulation shows the complex behavior of two dimensional dynamic system, we find period doubling bifurcation and chaos phenomenon. We measure performances of the model in different period by using the index of average profit. The results show that unstable behavior in economic system is often an unfavorable outcome. So this paper discusses the application of adaptive adjustment mechanism when the model exhibits chaotic behavior and then allows the retailers to eliminate the negative effects.

Statistical models and time series forecasting of sulfur dioxide: a case study Tehran.

PubMed

Hassanzadeh, S; Hosseinibalam, F; Alizadeh, R

2009-08-01

This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.

[Histologic study on impeding leukoplakia carcinogenesis of golden hamster cheek pouch about Erigeron breviscapus (Vant) Hand-Mazz].

PubMed

Zhou, C T; Zhong, W J; Hua, L; Hu, H F; Jin, Z G

2000-06-01

To observe the effect of Erigeron breviscapus (Vant) Hand Mazz (HEr) in impeding oral leukoplakia carcinogenesis, and to seek effective Chinese herb medicine that can impede precarcinoma of oral mucosas. 132 golden hamsters were randomly divided into model group (60 animals), HEr group (60 animals), and control group 12 animals. Salley's leukoplakia carcinogenesis model of golden hamster cheek pouch was used in this study. HEr was injected into the stomach to impede evolution of carcinogenesis. Pathological specimens were observed via naked eye and light microscope between model group and HEr group. Results were compared. Observation via naked-eye showed that leukoplakia rate of HEr group (18.2%) was lower than that of model group (27.3%). Observation via light microscope showed that carcinogenesis rate descended one fold and displasia rate descended 0.4 fold in HEr group. HEr has exact effect in impeding leukoplakia carcinogenesis.

A study of hearing function and histopathologic changes in the cochlea of the type 2 diabetes model Tsumura Suzuki obese diabetes mouse.

PubMed

Tsuda, Junko; Sugahara, Kazuma; Hori, Takeshi; Kanagawa, Eiju; Takaki, Eiichi; Fujimoto, Mitsuaki; Nakai, Akira; Yamashita, Hiroshi

2016-11-01

This study used Tsumura Suzuki Obese Diabetes (TSOD) mice as a spontaneous type 2 diabetes model and Tsumura Suzuki Non-obesity (TSNO) mice as controls to investigate factors involved in the onset of hearing impairment. Body weight, blood glucose levels, and auditory brainstem responses (ABRs) were measured. The cochleae were excised and evaluated histopathologically. The TSOD mice showed significant hyperglycemia at 2-7 months and severe obesity at 5-10 months; significantly elevated ABR thresholds at 8-10 months; and the capillary lumens in the cochlea stria vascularis were narrower in the TSOD mice than in the TSNO mice. At 17 months, India ink vascular staining of the TSOD mice's cochleae revealed decreased capillary density in the stria vascularis. The vascular area of capillaries in the stria vascularis and the vascular area were significantly smaller in TSOD mice. Histopathological analysis showed vessel wall thickening in the modiolus and narrowed capillaries in the stria vascularis, suggesting reduced blood flow to the inner ear. The diabetes mice model used in our study showed early age-associated hearing loss, and histopathology showed findings of vessel wall thickening in the modiolus, narrowing of capillaries in the stria vascularis, and chronically reduced blood flow in the cochlea.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

Generalized theory of semiflexible polymers.

PubMed

Wiggins, Paul A; Nelson, Philip C

2006-03-01

DNA bending on length scales shorter than a persistence length plays an integral role in the translation of genetic information from DNA to cellular function. Quantitative experimental studies of these biological systems have led to a renewed interest in the polymer mechanics relevant for describing the conformational free energy of DNA bending induced by protein-DNA complexes. Recent experimental results from DNA cyclization studies have cast doubt on the applicability of the canonical semiflexible polymer theory, the wormlike chain (WLC) model, to DNA bending on biologically relevant length scales. This paper develops a theory of the chain statistics of a class of generalized semiflexible polymer models. Our focus is on the theoretical development of these models and the calculation of experimental observables. To illustrate our methods, we focus on a specific, illustrative model of DNA bending. We show that the WLC model generically describes the long-length-scale chain statistics of semiflexible polymers, as predicted by renormalization group arguments. In particular, we show that either the WLC or our present model adequately describes force-extension, solution scattering, and long-contour-length cyclization experiments, regardless of the details of DNA bend elasticity. In contrast, experiments sensitive to short-length-scale chain behavior can in principle reveal dramatic departures from the linear elastic behavior assumed in the WLC model. We demonstrate this explicitly by showing that our toy model can reproduce the anomalously large short-contour-length cyclization factors recently measured by Cloutier and Widom. Finally, we discuss the applicability of these models to DNA chain statistics in the context of future experiments.

The Presentation of Science in Everyday Life: The Science Show

ERIC Educational Resources Information Center

Watermeyer, Richard

2013-01-01

This paper constitutes a case-study of the "science show" model of public engagement employed by a company of science communicators focused on the popularization of science, technology, engineering and mathematics (STEM) subject disciplines with learner constituencies. It examines the potential of the science show to foster the interest…

Load carrying capacity of RCC beams by replacing steel reinforcement bars with shape memory alloy bars

NASA Astrophysics Data System (ADS)

Bajoria, Kamal M.; Kaduskar, Shreya S.

2016-04-01

In this paper the structural behavior of reinforced concrete (RC) beams with smart rebars under two point loading system has been numerically studied, using Finite Element Method. The material used in this study is Super-elastic Shape Memory Alloys (SE SMAs) which contains nickel and titanium. In this study, different quantities of steel and SMA rebars have been used for reinforcement and the behavior of these models under two point bending loading system is studied. A comparison of load carrying capacity for the model between steel reinforced concrete beam and the beam reinforced with S.M.A and steel are performed. The results show that RC beams reinforced with combination of shape memory alloy and steel show better performance.

Metabolomic and pharmacokinetic study on the mechanism underlying the lipid-lowering effect of oral-administrated berberine

PubMed Central

Gu, Shenghua; Cao, Bei; Sun, Runbin; Tang, Yueqing; Paletta, Janice L.; Wu, Xiao-Lei; Liu, Linsheng; Zha, Weibin; Zhao, Chunyan; Li, Yan; Radlon, Jason M.; Hylemon, Phillip B.; Zhou, Huiping; Aa, Jiye; Wang, Guangji

2014-01-01

Clinic and animal studies demonstrated that oral-administrated berberine had distinct lipid-lowering effect. However, pharmacokinetic studies showed berberine was poorly absorbed into the body so that the levels of berberine in the blood and target tissues were far below the effective concentrations revealed. To probe the underlying mechanism, the effect of berberine on biological system was studied on a high-fat-diet-induced hamster hyperlipidemia model. Our results showed that intragastric-administered berberine was poorly absorbed into circulation and most berberine accumulated in gut content. Although the bioavailability for intragastric-administered berberine was much lower than that of intraperitoneal-administered berberine, it had stronger lipid-lowing effect, indicating gastrointestinal is a potential target for hypolipidemic effect of berberine. Metabolomic study on both serum and gut content showed that oral-administrated berberine significantly regulated molecules involved in lipid metabolism, and increased the generation of bile acids in the hyperlipidemic model. DNA analysis revealed that the oral-administered berberine modulated the gut microbiota, and BBR showed a significant inhibition on the 7α-dehydroxylation conversion of cholic acid to deoxycholic acid, indicating a decreased elimination of bile acids in the gut. However, in model hamsters, elevated bile acids failed to down-regulate the expression and function of CYP7A1 in a negative feed-back way. It was suggested that the hypocholesterolemic effect for oral-administrated berberine is involved in its effect on modulating the turnover of bile acids and farnesoid X receptor signal pathway. PMID:25411028

Radon-222 as a test of convective transport in a general circulation model

NASA Technical Reports Server (NTRS)

Jacob, Daniel J.; Prather, Michael J.

1990-01-01

A three-dimensional tracer model based on the Goddard Institude of Space Studies GCM is used to simulate the distribution of Rn-222 over North America to test the ability of the model to describe the transport of pollutants in the boundary layer and the exchange of mass between the boundary layer and the free troposphere. The model results are compared with surface observations from five sites in the U.S., showing that Rn-222 concentrations are primarily regulated by dry convection. The simulations show satisfactory agreement with observations although the model underpredicts observations at night and the simulated Rn-222 concentrations over the northeastern U.S. are too high in the spring and too low in the fall.

(2 + 1)-dimensional interacting model of two massless spin-2 fields as a bi-gravity model

NASA Astrophysics Data System (ADS)

Hoseinzadeh, S.; Rezaei-Aghdam, A.

2018-06-01

We propose a new group-theoretical (Chern-Simons) formulation for the bi-metric theory of gravity in (2 + 1)-dimensional spacetime which describe two interacting massless spin-2 fields. Our model has been formulated in terms of two dreibeins rather than two metrics. We obtain our Chern-Simons gravity model by gauging mixed AdS-AdS Lie algebra and show that it has a two dimensional conformal field theory (CFT) at the boundary of the anti de Sitter (AdS) solution. We show that the central charge of the dual CFT is proportional to the mass of the AdS solution. We also study cosmological implications of our massless bi-gravity model.

Ferromagnetic Potts models with multisite interaction

NASA Astrophysics Data System (ADS)

Schreiber, Nir; Cohen, Reuven; Haber, Simi

2018-03-01

We study the q -state Potts model with four-site interaction on a square lattice. Based on the asymptotic behavior of lattice animals, it is argued that when q ≤4 the system exhibits a second-order phase transition and when q >4 the transition is first order. The q =4 model is borderline. We find 1 /lnq to be an upper bound on Tc, the exact critical temperature. Using a low-temperature expansion, we show that 1 /(θ lnq ) , where θ >1 is a q -dependent geometrical term, is an improved upper bound on Tc. In fact, our findings support Tc=1 /(θ lnq ) . This expression is used to estimate the finite correlation length in first-order transition systems. These results can be extended to other lattices. Our theoretical predictions are confirmed numerically by an extensive study of the four-site interaction model using the Wang-Landau entropic sampling method for q =3 ,4 ,5 . In particular, the q =4 model shows an ambiguous finite-size pseudocritical behavior.

Quality by design: scale-up of freeze-drying cycles in pharmaceutical industry.

PubMed

Pisano, Roberto; Fissore, Davide; Barresi, Antonello A; Rastelli, Massimo

2013-09-01

This paper shows the application of mathematical modeling to scale-up a cycle developed with lab-scale equipment on two different production units. The above method is based on a simplified model of the process parameterized with experimentally determined heat and mass transfer coefficients. In this study, the overall heat transfer coefficient between product and shelf was determined by using the gravimetric procedure, while the dried product resistance to vapor flow was determined through the pressure rise test technique. Once model parameters were determined, the freeze-drying cycle of a parenteral product was developed via dynamic design space for a lab-scale unit. Then, mathematical modeling was used to scale-up the above cycle in the production equipment. In this way, appropriate values were determined for processing conditions, which allow the replication, in the industrial unit, of the product dynamics observed in the small scale freeze-dryer. This study also showed how inter-vial variability, as well as model parameter uncertainty, can be taken into account during scale-up calculations.

Tetraodon nigroviridis as a nonlethal model of infectious spleen and kidney necrosis virus (ISKNV) infection

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

Xu Xiaopeng; Huang Lichao; Weng Shaoping

Infectious spleen and kidney necrosis virus (ISKNV) is the type species of the genus Megalocytivirus, family Iridoviridae. We have previously established a high mortality ISKNV infection model of zebrafish (Danio rerio). In this study, a nonlethal Tetraodon nigroviridis model of ISKNV infection was established. ISKNV infection did not cause lethal disease in Tetraodon but could infect almost all the organs of this species. Electron microscopy showed ISKNV particles were present in infected tissues. Immunofluorescence and quantitative real-time PCR analysis showed that nearly all the virions and infected cells were cleared at 14 d postinfection. The expression profiles of interferon-{gamma} andmore » tumor necrosis factor-{alpha} gene in response to ISKNV infection were significantly different in Tetraodon and zebrafish. The establishment of the nonlethal Tetraodon model of ISKNV infection can offer a valuable tool complementary to the zebrafish infection model for studying megalocytivirus disease, fish immune systems, and viral tropism.« less

An effective model of DNA like helicoidal structure: with length fluctuation nonlinearity

NASA Astrophysics Data System (ADS)

Tseytlin, Y. M.

2011-03-01

One of the natural helicoidal nanostructure, which thermomechanical features are studied carefully with the help of different mechanical models, is a DNA cell / molecule. Our study proves that the experimentally determined nonlinear fluctuations of the molecular length of DNA can be better understood by modeling the molecule as a helicoidal pretwisted nanostrip sensor with nonlinear function. The calculations presented here are in good agreement with the experimental data within 10%. Other used by many researchers mechanical models such as an elastic rod, wormlike chain (WLC), accordion bellows, or an elastic core wrapped with rigid wires do not show the possible variance nonlinearity of thermomechanical DNA molecular length fluctuations. We have found that the nonlinear variance of the length fluctuations is an intrinsic property of the micro-nano-sensors with helicoidal shape. This model allows us to estimate the persistence length and twist-stretch coupling of a DNA molecule as well. It also shows the molecule's overwinding possibility at initial stretching with correct numerical representation.

BPS sectors of the Skyrme model and their non-BPS extensions

NASA Astrophysics Data System (ADS)

Adam, C.; Foster, D.; Krusch, S.; Wereszczynski, A.

2018-02-01

Two recently found coupled Bogomol'nyi-Prasad-Sommerfield (BPS) submodels of the Skyrme model are further analyzed. First, we provide a geometrical formulation of the submodels in terms of the eigenvalues of the strain tensor. Second, we study their thermodynamical properties and show that the mean-field equations of state coincide at high pressure and read p =ρ ¯/3 . We also provide evidence that matter described by the first BPS submodel has some similarity with a Bose-Einstein condensate. Moreover, we show that extending the second submodel to a non-BPS model by including certain additional terms of the full Skyrme model does not spoil the respective ansatz, leading to an ordinary differential equation for the profile of the Skymion, for any value of the topological charge. This allows for an almost analytical description of the properties of Skyrmions in this model. In particular, we analytically study the breaking and restoration of the BPS property. Finally, we provide an explanation of the success of the rational map ansatz.

Collective thermal transport in pure and alloy semiconductors.

PubMed

Torres, Pol; Mohammed, Amr; Torelló, Àlvar; Bafaluy, Javier; Camacho, Juan; Cartoixà, Xavier; Shakouri, Ali; Alvarez, F Xavier

2018-03-07

Conventional models for predicting thermal conductivity of alloys usually assume a pure kinetic regime as alloy scattering dominates normal processes. However, some discrepancies between these models and experiments at very small alloy concentrations have been reported. In this work, we use the full first principles kinetic collective model (KCM) to calculate the thermal conductivity of Si 1-x Ge x and In x Ga 1-x As alloys. The calculated thermal conductivities match well with the experimental data for all alloy concentrations. The model shows that the collective contribution must be taken into account at very low impurity concentrations. For higher concentrations, the collective contribution is suppressed, but normal collisions have the effect of significantly reducing the kinetic contribution. The study thus shows the importance of the proper inclusion of normal processes even for alloys for accurate modeling of thermal transport. Furthermore, the phonon spectral distribution of the thermal conductivity is studied in the framework of KCM, providing insights to interpret the superdiffusive regime introduced in the truncated Lévy flight framework.

Prediction of South China sea level using seasonal ARIMA models

NASA Astrophysics Data System (ADS)

Fernandez, Flerida Regine; Po, Rodolfo; Montero, Neil; Addawe, Rizavel

2017-11-01

Accelerating sea level rise is an indicator of global warming and poses a threat to low-lying places and coastal countries. This study aims to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model to the time series obtained from the TOPEX and Jason series of satellite radar altimetries of the South China Sea from the year 2008 to 2015. With altimetric measurements taken in a 10-day repeat cycle, monthly averages of the satellite altimetry measurements were taken to compose the data set used in the study. SARIMA models were then tried and fitted to the time series in order to find the best-fit model. Results show that the SARIMA(1,0,0)(0,1,1)12 model best fits the time series and was used to forecast the values for January 2016 to December 2016. The 12-month forecast using SARIMA(1,0,0)(0,1,1)12 shows that the sea level gradually increases from January to September 2016, and decreases until December 2016.

[Does the GHQ-12 scoring system affect its factor structure? An exploratory study of Ibero American students].

PubMed

Urzúa, Alfonso; Caqueo-Urízar, Alejandra; Bargsted, Mariana; Irarrázaval, Matías

2015-06-01

This study aimed to evaluate whether the scoring system of the General Health Questionnaire (GHQ-12) alters the instrument's factor structure. The method considered 1,972 university students from nine Ibero American countries. Modeling was performed with structural equations for 1, 2, and 3 latent factors. The mechanism for scoring the questions was analyzed within each type of structure. The results indicate that models with 2 and 3 factors show better goodness-of-fit. In relation to scoring mechanisms, procedure 0-1-1-1 for models with 2 and 3 factors showed the best fit. In conclusion, there appears to be a relationship between the response format and the number of factors identified in the instrument's structure. The model with the best fit was 3-factor 0-1-1-1-formatted, but 0-1-2-3 has acceptable and more stable indicators and provides a better format for two- and three-dimensional models.

Computational complexity of symbolic dynamics at the onset of chaos

NASA Astrophysics Data System (ADS)

Lakdawala, Porus

1996-05-01

In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

NASA Astrophysics Data System (ADS)

Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong

2017-12-01

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

PubMed

Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

2016-06-01

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.

The Power of Exclusion using Automated Osteometric Sorting: Pair-Matching.

PubMed

Lynch, Jeffrey James; Byrd, John; LeGarde, Carrie B

2018-03-01

This study compares the original pair-matching osteometric sorting model (J Forensic Sci 2003;48:717) against two new models providing validation and performance testing across three samples. The samples include the Forensic Data Bank, USS Oklahoma, and the osteometric sorting reference used within the Defense POW/MIA Accounting Agency. A computer science solution to generating dynamic statistical models across a commingled assemblage is presented. The issue of normality is investigated showing the relative robustness against non-normality and a data transformation to control for normality. A case study is provided showing the relative exclusion power of all three models from an active commingled case within the Defense POW/MIA Accounting Agency. In total, 14,357,220 osteometric t-tests were conducted. The results indicate that osteometric sorting performs as expected despite reference samples deviating from normality. The two new models outperform the original, and one of those is recommended to supersede the original for future osteometric sorting work. © 2017 American Academy of Forensic Sciences.

Using variable rate models to identify genes under selection in sequence pairs: their validity and limitations for EST sequences.

PubMed

Church, Sheri A; Livingstone, Kevin; Lai, Zhao; Kozik, Alexander; Knapp, Steven J; Michelmore, Richard W; Rieseberg, Loren H

2007-02-01

Using likelihood-based variable selection models, we determined if positive selection was acting on 523 EST sequence pairs from two lineages of sunflower and lettuce. Variable rate models are generally not used for comparisons of sequence pairs due to the limited information and the inaccuracy of estimates of specific substitution rates. However, previous studies have shown that the likelihood ratio test (LRT) is reliable for detecting positive selection, even with low numbers of sequences. These analyses identified 56 genes that show a signature of selection, of which 75% were not identified by simpler models that average selection across codons. Subsequent mapping studies in sunflower show four of five of the positively selected genes identified by these methods mapped to domestication QTLs. We discuss the validity and limitations of using variable rate models for comparisons of sequence pairs, as well as the limitations of using ESTs for identification of positively selected genes.

A Cross-Cultural Test of the Work-Family Interface in 48 Countries

ERIC Educational Resources Information Center

Jeffrey Hill, E.; Yang, Chongming; Hawkins, Alan J.; Ferris, Maria

2004-01-01

This study tests a cross-cultural model of the work-family interface. Using multigroup structural equation modeling with IBM survey responses from 48 countries (N= 25,380), results show that the same work-family interface model that fits the data globally also fits the data in a four-group model composed of culturally related groups of countries,…

The role of finite displacements in vocal fold modeling.

PubMed

Chang, Siyuan; Tian, Fang-Bao; Luo, Haoxiang; Doyle, James F; Rousseau, Bernard

2013-11-01

Human vocal folds experience flow-induced vibrations during phonation. In previous computational models, the vocal fold dynamics has been treated with linear elasticity theory in which both the strain and the displacement of the tissue are assumed to be infinitesimal (referred to as model I). The effect of the nonlinear strain, or geometric nonlinearity, caused by finite displacements is yet not clear. In this work, a two-dimensional model is used to study the effect of geometric nonlinearity (referred to as model II) on the vocal fold and the airflow. The result shows that even though the deformation is under 1 mm, i.e., less than 10% of the size of the vocal fold, the geometric nonlinear effect is still significant. Specifically, model I underpredicts the gap width, the flow rate, and the impact stress on the medial surfaces as compared to model II. The study further shows that the differences are caused by the contact mechanics and, more importantly, the fluid-structure interaction that magnifies the error from the small-displacement assumption. The results suggest that using the large-displacement formulation in a computational model would be more appropriate for accurate simulations of the vocal fold dynamics.

A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant.

PubMed

Chun, Ting Sie; Malek, M A; Ismail, Amelia Ritahani

2015-01-01

The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a well-established method - namely the least-square support vector machine (LS-SVM) as a baseline model. The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. The CSA approach shows that fewer control and training parameters are required for model simulation as compared with the LS-SVM approach. The ability of a CSA approach in resolving limited data samples, non-linear sample function and multidimensional pattern recognition makes it a powerful tool in modelling the prediction of effluent removals in an SSTP.

Predicting brain acceleration during heading of soccer ball

NASA Astrophysics Data System (ADS)

Taha, Zahari; Hasnun Arif Hassan, Mohd; Azri Aris, Mohd; Anuar, Zulfika

2013-12-01

There has been a long debate whether purposeful heading could cause harm to the brain. Studies have shown that repetitive heading could lead to degeneration of brain cells, which is similarly found in patients with mild traumatic brain injury. A two-degree of freedom linear mathematical model was developed to study the impact of soccer ball to the brain during ball-to-head impact in soccer. From the model, the acceleration of the brain upon impact can be obtained. The model is a mass-spring-damper system, in which the skull is modelled as a mass and the neck is modelled as a spring-damper system. The brain is a mass with suspension characteristics that are also defined by a spring and a damper. The model was validated by experiment, in which a ball was dropped from different heights onto an instrumented dummy skull. The validation shows that the results obtained from the model are in a good agreement with the brain acceleration measured from the experiment. This findings show that a simple linear mathematical model can be useful in giving a preliminary insight on what human brain endures during a ball-to-head impact.

Exact solutions for the static bending of Euler-Bernoulli beams using Eringen's two-phase local/nonlocal model

NASA Astrophysics Data System (ADS)

Wang, Y. B.; Zhu, X. W.; Dai, H. H.

2016-08-01

Though widely used in modelling nano- and micro- structures, Eringen's differential model shows some inconsistencies and recent study has demonstrated its differences between the integral model, which then implies the necessity of using the latter model. In this paper, an analytical study is taken to analyze static bending of nonlocal Euler-Bernoulli beams using Eringen's two-phase local/nonlocal model. Firstly, a reduction method is proved rigorously, with which the integral equation in consideration can be reduced to a differential equation with mixed boundary value conditions. Then, the static bending problem is formulated and four types of boundary conditions with various loadings are considered. By solving the corresponding differential equations, exact solutions are obtained explicitly in all of the cases, especially for the paradoxical cantilever beam problem. Finally, asymptotic analysis of the exact solutions reveals clearly that, unlike the differential model, the integral model adopted herein has a consistent softening effect. Comparisons are also made with existing analytical and numerical results, which further shows the advantages of the analytical results obtained. Additionally, it seems that the once controversial nonlocal bar problem in the literature is well resolved by the reduction method.

Modified chloride diffusion model for concrete under the coupling effect of mechanical load and chloride salt environment

NASA Astrophysics Data System (ADS)

Lei, Mingfeng; Lin, Dayong; Liu, Jianwen; Shi, Chenghua; Ma, Jianjun; Yang, Weichao; Yu, Xiaoniu

2018-03-01

For the purpose of investigating lining concrete durability, this study derives a modified chloride diffusion model for concrete based on the odd continuation of boundary conditions and Fourier transform. In order to achieve this, the linear stress distribution on a sectional structure is considered, detailed procedures and methods are presented for model verification and parametric analysis. Simulation results show that the chloride diffusion model can reflect the effects of linear stress distribution of the sectional structure on the chloride diffusivity with reliable accuracy. Along with the natural environmental characteristics of practical engineering structures, reference value ranges of model parameters are provided. Furthermore, a chloride diffusion model is extended for the consideration of multi-factor coupling of linear stress distribution, chloride concentration and diffusion time. Comparison between model simulation and typical current research results shows that the presented model can produce better considerations with a greater universality.

Exactly solvable models of growing interfaces and lattice gases: the Arcetri models, ageing and logarithmic sub-ageing

NASA Astrophysics Data System (ADS)

Durang, Xavier; Henkel, Malte

2017-12-01

Motivated by an analogy with the spherical model of a ferromagnet, the three Arcetri models are defined. They present new universality classes, either for the growth of interfaces, or else for lattice gases. They are distinct from the common Edwards-Wilkinson and Kardar-Parisi-Zhang universality classes. Their non-equilibrium evolution can be studied by the exact computation of their two-time correlators and responses. In both interpretations, the first model has a critical point in any dimension and shows simple ageing at and below criticality. The exact universal exponents are found. The second and third model are solved at zero temperature, in one dimension, where both show logarithmic sub-ageing, of which several distinct types are identified. Physically, the second model describes a lattice gas and the third model describes interface growth. A clear physical picture on the subsequent time and length scales of the sub-ageing process emerges.

Mid-tropospheric Spectral Length-scale Analysis of Many Constituents from Aircraft, Satellite and Model Results During the 2013 SENEX Field Study.

NASA Astrophysics Data System (ADS)

McKeen, S. A.; Angevine, W. M.; Ahmadov, R.; Frost, G. J.; Kim, S. W.; Cui, Y.; McDonald, B.; Trainer, M.; Holloway, J. S.; Ryerson, T. B.; Peischl, J.; Gambacorta, A.; Barnet, C. D.; Smith, N.; Pierce, R. B.

2016-12-01

This study presents preliminary comparisons of satellite, aircraft, and model variance spectra for meteorological, thermodynamic and gas-phase species collected during the 2013 Southeastern Nexus Air Quality Experiment (SENEX). Fourier analysis of 8 constituents collected at 1 Hz by the NOAA W-P3 aircraft in the 25 to 200 km length-scale range exhibit properties consistent with previous scale dependence studies: when spectra are averaged over several 500 mb flight legs, very linear dependence is found on log-log plots of spectral density versus inverse length-scale. Derived slopes for wind speed, temperature, H2O, CO, CO2, CH4, NOy and O3 all fall within ±30% and close to the slope of -5/3 predicted from dimensional scaling theory of isotropic turbulence. Qualitative differences are seen when a similar analysis, without quality control, is applied to a preliminary set of NUCAPS satellite retrievals over the continental U.S. during SENEX. While 500mb water vapor and column integrated water show slopes close to the -5/3 value in the 200 to 1000 km length-scale range, other quantities show significantly shallower slopes, suggesting the need for rigorous quality control. Results from WRF-Chem regional air quality model simulations at 500mb show the model is unable to account for variance on length-scales less than 6ΔX, where ΔX is the model horizontal resolution (12km). Comparisons with satellite data in the 200 to 1000km range show slopes consistent with the -5/3 power law for species such as CO, CH4 and CO2 that do not undergo reinitialization, suggesting potential for future application.

Docosahexaenoic acid modifies the clustering and size of lipid rafts and the lateral organization and surface expression of MHC class I of EL4 cells.

PubMed

Shaikh, Saame Raza; Rockett, Benjamin Drew; Salameh, Muhammad; Carraway, Kristen

2009-09-01

An emerging molecular mechanism by which docosahexaenoic acid (DHA) exerts its effects is modification of lipid raft organization. The biophysical model, based on studies with liposomes, shows that DHA avoids lipid rafts because of steric incompatibility between DHA and cholesterol. The model predicts that DHA does not directly modify rafts; rather, it incorporates into nonrafts to modify the lateral organization and/or conformation of membrane proteins, such as the major histocompatibility complex (MHC) class I. Here, we tested predictions of the model at a cellular level by incorporating oleic acid, eicosapentaenoic acid (EPA), and DHA, compared with a bovine serum albumin (BSA) control, into the membranes of EL4 cells. Quantitative microscopy showed that DHA, but not EPA, treatment, relative to the BSA control diminished lipid raft clustering and increased their size. Approximately 30% of DHA was incorporated directly into rafts without changing the distribution of cholesterol between rafts and nonrafts. Quantification of fluorescence colocalization images showed that DHA selectively altered MHC class I lateral organization by increasing the fraction of the nonraft protein into rafts compared with BSA. Both DHA and EPA treatments increased antibody binding to MHC class I compared with BSA. Antibody titration showed that DHA and EPA did not change MHC I conformation but increased total surface levels relative to BSA. Taken together, our findings are not in agreement with the biophysical model. Therefore, we propose a model that reconciles contradictory viewpoints from biophysical and cellular studies to explain how DHA modifies lipid rafts on several length scales. Our study supports the notion that rafts are an important target of DHA's mode of action.

Study Circles at the Pharmacy--A New Model for Diabetes Education in Groups.

ERIC Educational Resources Information Center

Sarkadi, Anna; Rosenqvist, Urban

1999-01-01

Tests the feasibility of a one-year group education model for patients with type 2 diabetes in Sweden. Within study circles led by pharmacists, participants learned to self-monitor glucose, to interpret the results and to act upon them. Results show that study circles held at pharmacies are a feasible way of education persons with type 2 diabetes.…

Development of soy lecithin based novel self-assembled emulsion hydrogels.

PubMed

Singh, Vinay K; Pandey, Preeti M; Agarwal, Tarun; Kumar, Dilip; Banerjee, Indranil; Anis, Arfat; Pal, Kunal

2015-03-01

The current study reports the development and characterization of soy lecithin based novel self-assembled emulsion hydrogels. Sesame oil was used as the representative oil phase. Emulsion gels were formed when the concentration of soy lecithin was >40% w/w. Metronidazole was used as the model drug for the drug release and the antimicrobial tests. Microscopic study showed the apolar dispersed phase in an aqueous continuum phase, suggesting the formation of emulsion hydrogels. FTIR study indicated the formation of intermolecular hydrogen bonding, whereas, the XRD study indicated predominantly amorphous nature of the emulsion gels. Composition dependent mechanical and drug release properties of the emulsion gels were observed. In-depth analyses of the mechanical studies were done using Ostwald-de Waele power-law, Kohlrausch and Weichert models, whereas, the drug release profiles were modeled using Korsmeyer-Peppas and Peppas-Sahlin models. The mechanical analyses indicated viscoelastic nature of the emulsion gels. The release of the drug from the emulsion gels was diffusion mediated. The drug loaded emulsion gels showed good antimicrobial activity. The biocompatibility test using HaCaT cells (human keratinocytes) suggested biocompatibility of the emulsion gels. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.

A Miniature Swine Model for Stem Cell-Based De Novo Regeneration of Dental Pulp and Dentin-Like Tissue.

PubMed

Zhu, Xiaofei; Liu, Jie; Yu, Zongdong; Chen, Chao-An; Aksel, Hacer; Azim, Adham A; Huang, George T-J

2018-02-01

The goal of this study was to establish mini-swine as a large animal model for stem cell-based pulp regeneration studies. Swine dental pulp stem cells (sDPSCs) were isolated from mini-swine and characterized in vitro. For in vivo studies, we first employed both ectopic and semi-orthotopic study models using severe combined immunodeficiency mice. One is hydroxyapatite-tricalcium phosphate (HA/TCP) model for pulp-dentin complex formation, and the other is tooth fragment model for complete pulp regeneration with new dentin depositing along the canal walls. We found that sDPSCs are similar to their human counterparts exhibiting mesenchymal stem cell characteristics with ability to form colony forming unit-fibroblastic and odontogenic differentiation potential. sDPSCs formed pulp-dentin complex in the HA/TCP model and showed pulp regeneration capacity in the tooth fragment model. We then tested orthotopic pulp regeneration on mini-swine including the use of multi-rooted teeth. Using autologous sDPSCs carried by hydrogel and transplanted into the mini-swine root canal space, we observed regeneration of vascularized pulp-like tissue with a layer of newly deposited dentin-like (rD) tissue or osteodentin along the canal walls. In some cases, dentin bridge-like structure was observed. Immunohistochemical analysis detected the expression of nestin, dentin sialophosphoprotein, dentin matrix protein 1, and bone sialoprotein in odontoblast-like cells lining against the produced rD. We also tested the use of allogeneic sDPSCs for the same procedures. Similar findings were observed in allogeneic transplantation. This study is the first to show an establishment of mini-swine as a suitable large animal model utilizing multi-rooted teeth for further cell-based pulp regeneration studies.

Effect of health belief model and health promotion model on breast cancer early diagnosis behavior: a systematic review.

PubMed

Ersin, Fatma; Bahar, Zuhal

2011-01-01

Breast cancer is an important public health problem on the grounds that it is frequently seen and it is a fatal disease. The objective of this systematic analysis is to indicate the effects of interventions performed by nurses by using the Health Belief Model (HBM) and Health Promotion Model (HPM) on the breast cancer early diagnosis behaviors and on the components of the Health Belief Model and Health Promotion Model. The reveiw was created in line with the Centre for Reviews and Dissemination guide dated 2009 (CRD) and developed by York University National Institute of Health Researches. Review was conducted by using PUBMED, OVID, EBSCO and COCHRANE databases. Six hundred seventy eight studies (PUBMED: 236, OVID: 162, EBSCO: 175, COCHRANE:105) were found in total at the end of the review. Abstracts and full texts of these six hundred seventy eight studies were evaluated in terms of inclusion and exclusion criteria and 9 studies were determined to meet the criteria. Samplings of the studies varied between ninety four and one thousand six hundred fifty five. It was detected in the studies that educations provided by taking the theories as basis became effective on the breast cancer early diagnosis behaviors. When the literature is examined, it is observed that the experimental researches which compare the concepts of Health Belief Model (HBM) and Health Promotion Model (HPM) preoperatively and postoperatively and show the effect of these concepts on education and are conducted by nurses are limited in number. Randomized controlled studies which compare HBM and HPM concepts preoperatively and postoperatively and show the efficiency of the interventions can be useful in evaluating the efficiency of the interventions.

Statistical and dynamical forecast of regional precipitation after mature phase of ENSO

NASA Astrophysics Data System (ADS)

Sohn, S.; Min, Y.; Lee, J.; Tam, C.; Ahn, J.

2010-12-01

While the seasonal predictability of general circulation models (GCMs) has been improved, the current model atmosphere in the mid-latitude does not respond correctly to external forcing such as tropical sea surface temperature (SST), particularly over the East Asia and western North Pacific summer monsoon regions. In addition, the time-scale of prediction scope is considerably limited and the model forecast skill still is very poor beyond two weeks. Although recent studies indicate that coupled model based multi-model ensemble (MME) forecasts show the better performance, the long-lead forecasts exceeding 9 months still show a dramatic decrease of the seasonal predictability. This study aims at diagnosing the dynamical MME forecasts comprised of the state of art 1-tier models as well as comparing them with the statistical model forecasts, focusing on the East Asian summer precipitation predictions after mature phase of ENSO. The lagged impact of El Nino as major climate contributor on the summer monsoon in model environments is also evaluated, in the sense of the conditional probabilities. To evaluate the probability forecast skills, the reliability (attributes) diagram and the relative operating characteristics following the recommendations of the World Meteorological Organization (WMO) Standardized Verification System for Long-Range Forecasts are used in this study. The results should shed light on the prediction skill for dynamical model and also for the statistical model, in forecasting the East Asian summer monsoon rainfall with a long-lead time.

A sensitivity analysis of regional and small watershed hydrologic models

NASA Technical Reports Server (NTRS)

Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

1975-01-01

Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

An Empirical Study of Enterprise Conceptual Modeling

NASA Astrophysics Data System (ADS)

Anaby-Tavor, Ateret; Amid, David; Fisher, Amit; Ossher, Harold; Bellamy, Rachel; Callery, Matthew; Desmond, Michael; Krasikov, Sophia; Roth, Tova; Simmonds, Ian; de Vries, Jacqueline

Business analysts, business architects, and solution consultants use a variety of practices and methods in their quest to understand business. The resulting work products could end up being transitioned into the formal world of software requirement definitions or as recommendations for all kinds of business activities. We describe an empirical study about the nature of these methods, diagrams, and home-grown conceptual models as reflected in real practice at IBM. We identify the models as artifacts of "enterprise conceptual modeling". We study important features of these models, suggest practical classifications, and discuss their usage. Our survey shows that the "enterprise conceptual modeling" arena presents a variety of descriptive models, each used by a relatively small group of colleagues. Together they form a "long tail" that extends from "drawings" on one end to "standards" on the other.

Systematization of the Mechanism by Which Plasma Irradiation Causes Cell Growth and Tumor Cell Death

NASA Astrophysics Data System (ADS)

Shimizu, Nobuyuki

2015-09-01

New methods and technologies have improved minimally invasive surgical treatment and saved numerous patients. Recently, plasma irradiation has been demonstrated that might be useful in medical field and the plasma irradiation device is expected to become practically applicable. Mild plasma coagulator showed some advantages such as hemostasis and adhesion reduction in experimental animal model, but the mechanism of plasma irradiation remains unclear. Our study group aim to clarify the mechanism of plasma irradiation effects, mainly focusing on oxidative stress using cultured cell lines and small animal model. First, a study using cultured cell lines showed that the culture medium that was activated by plasma irradiation (we called this kind of medium as ``PAM'' -plasma activated medium-) induced tumor cell death. Although this effect was mainly found to be due to hydrogen peroxide, the remaining portion was considered as the specific effect of the plasma irradiation and we are now studying focusing on this effect. Second, we established a mouse intra-peritoneal adhesion model and checked biological reaction that occurred in the adhesion part. Histopathological study showed inflammatory cells infiltration into adhesion part and the expression of PTX3 that might involve tissue repair around adhesion part. We also confirmed that cytokines IL-6 and IL-10 might be useful as a marker of adhesion formation in this model. Applying ``PAM'' or mild plasma irradiation in this model, we examine the effects of plasma on inflamed cells. The samples in these experiments would be applied to targeted proteomics analysis, and we aim to demonstrate the systematization of the cell's reaction by plasma irradiation.

A field and statistical modeling study to estimate irrigation water use at Benchmark Farms study sites in southwestern Georgia, 1995-96

USGS Publications Warehouse

Fanning, Julia L.; Schwarz, Gregory E.; Lewis, William C.

2001-01-01

A benchmark irrigation monitoring network of farms located in a 32-county area in southwestern Georgia was established in 1995 to improve estimates of irrigation water use. A stratified random sample of 500 permitted irrigators was selected from a data base--maintained by the Georgia Department of Natural Resources, Georgia Environmental Protection Division, Water Resources Management Branch--to obtain 180 voluntary participants in the study area. Site-specific irrigation data were collected at each farm using running-time totalizers and noninvasive flowmeters. Data were collected and compiled for 50 farms for 1995 and 130 additional farms for the 1996 growing season--a total of 180 farms. Irrigation data collected during the 1996 growing season were compiled for 180 benchmark farms and used to develop a statistical model to estimate irrigation water use in 32 counties in southwestern Georgia. The estimates derived were developed from using a statistical approach know as "bootstrap analysis" that allows for the estimation of precision. Five model components--whether-to-irrigate, acres irrigated, crop selected, seasonal-irrigation scheduling, and the amount of irrigation applied--compose the irrigation model and were developed to reflect patterns in the data collected at Benchmark Farms Study area sites. The model estimated that peak irrigation for all counties in the study area occurred during July with significant irrigation also occurring during May, June, and August. Irwin and Tift were the most irrigated and Schley and Houston were the least irrigated counties in the study area. High irrigation intensity primarily was located along the eastern border of the study area; whereas, low irrigation intensity was located in the southwestern quadrant where ground water was the dominant irrigation source. Crop-level estimates showed sizable variations across crops and considerable uncertainty for all crops other than peanuts and pecans. Counties having the most irrigated acres showed higher variations in annual irrigation than counties having the least irrigated acres. The Benchmark Farms Study model estimates were higher than previous irrigation estimates, with 20 percent of the bias a result of underestimating irrigation acreage in earlier studies. Model estimates showed evidence of an upward bias of about 15 percent with the likely cause being a misrepresented inches-applied model. A better understanding of the causes of bias in the model could be determined with a larger irrigation sample size and increased substantially by automating the reporting of monthly totalizer amounts.

A Novel Wind Speed Forecasting Model for Wind Farms of Northwest China

NASA Astrophysics Data System (ADS)

Wang, Jian-Zhou; Wang, Yun

2017-01-01

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon's Signed-Rank test, and Morgan-Granger-Newbold test tell us that the proposed model is different from the compared models.

DSMC Simulation and Experimental Validation of Shock Interaction in Hypersonic Low Density Flow

PubMed Central

2014-01-01

Direct simulation Monte Carlo (DSMC) of shock interaction in hypersonic low density flow is developed. Three collision molecular models, including hard sphere (HS), variable hard sphere (VHS), and variable soft sphere (VSS), are employed in the DSMC study. The simulations of double-cone and Edney's type IV hypersonic shock interactions in low density flow are performed. Comparisons between DSMC and experimental data are conducted. Investigation of the double-cone hypersonic flow shows that three collision molecular models can predict the trend of pressure coefficient and the Stanton number. HS model shows the best agreement between DSMC simulation and experiment among three collision molecular models. Also, it shows that the agreement between DSMC and experiment is generally good for HS and VHS models in Edney's type IV shock interaction. However, it fails in the VSS model. Both double-cone and Edney's type IV shock interaction simulations show that the DSMC errors depend on the Knudsen number and the models employed for intermolecular interaction. With the increase in the Knudsen number, the DSMC error is decreased. The error is the smallest in HS compared with those in the VHS and VSS models. When the Knudsen number is in the level of 10−4, the DSMC errors, for pressure coefficient, the Stanton number, and the scale of interaction region, are controlled within 10%. PMID:24672360

Evaluation of a prognostic scoring system for dogs managed with hemodialysis.

PubMed

Perondi, Francesca; Lippi, Ilaria; Ceccherini, Gianila; Marchetti, Veronica; Bernicchi, Lucrezia; Guidi, Grazia

2018-06-24

To investigate prognostic models in a cohort of dogs with acute kidney injury (AKI) and acute on chronic kidney disease (AKI/CKD) managed by hemodialysis. Retrospective study from July 2011 to November 2014. University Veterinary Teaching Hospital. Forty dogs with historical, clinical, imaging, and laboratory findings consistent with AKI or AKI/CKD managed with intermittent hemodialysis were included. Scoring system models previously established by Segev et al for outcome prediction in dogs with AKI were applied to all dogs. Models A, B, and C correctly classified outcomes in 68%, 83%, and 85% of cases, respectively. In our cohort Model A showed sensitivity of 58% and specificity of 86%, Model B showed sensitivity of 79% and specificity of 87%, Model C showed sensitivity of 86% and specificity of 84%. The presence of anuria (P < 0.0002), respiratory complications (P < 0.0001), disseminated intravascular coagulation (DIC) (P = 0.0004), grade of AKI (P = 0.0023), pancreatitis (P = 0.0001), and systemic inflammatory response syndrome (SIRS) (P = 0.0001) was significantly higher in nonsurvivors compared with survivors. In our cohort of patients, Segev's model C showed the best sensitivity and specificity for predicting prognosis, while model A had lower sensitivity. In our cohort of dialysis patients, the presence of respiratory complications, DIC, SIRS, and pancreatitis at hospitalization, were correlated with a poor prognosis. © Veterinary Emergency and Critical Care Society 2018.

[Study on the nutrition of alpine meadow based on hyperspectral data].

PubMed

Wang, Xun; Liu, Shu-Jie; Jia, Hai-Feng; Chai, Sha-Tuo; Dang, An-Rong; Liu, Xue-Hua; Hao, Li-Zhuang; Cui, Zhan-Hong

2012-10-01

Remote sensing monitoring of alpine grassland nutritional status is a key factor of grassland reasonable utilization, also a difficulty for dynamic vegetation monitoring. The present paper studies the correlations between vegetation nutrition and hyperspectral data. The results showed that two band ratio models have a significant correlation with biomass, air-DM, P, CF, and CP. MAXR models have a significant correlation with most of nutrition index when selected wavebands equaled five. On the whole, the MAXR model precedes two band ratio models. Using MAXR models to estimate air-DM, P and CF can obtain higher accuracy.

Malignant infarction of the middle cerebral artery in a porcine model. A pilot study.

PubMed

Arikan, Fuat; Martínez-Valverde, Tamara; Sánchez-Guerrero, Ángela; Campos, Mireia; Esteves, Marielle; Gandara, Dario; Torné, Ramon; Castro, Lidia; Dalmau, Antoni; Tibau, Joan; Sahuquillo, Juan

2017-01-01

Interspecies variability and poor clinical translation from rodent studies indicate that large gyrencephalic animal stroke models are urgently needed. We present a proof-of-principle study describing an alternative animal model of malignant infarction of the middle cerebral artery (MCA) in the common pig and illustrate some of its potential applications. We report on metabolic patterns, ionic profile, brain partial pressure of oxygen (PtiO2), expression of sulfonylurea receptor 1 (SUR1), and the transient receptor potential melastatin 4 (TRPM4). A 5-hour ischemic infarct of the MCA territory was performed in 5 2.5-to-3-month-old female hybrid pigs (Large White x Landrace) using a frontotemporal approach. The core and penumbra areas were intraoperatively monitored to determine the metabolic and ionic profiles. To determine the infarct volume, 2,3,5-triphenyltetrazolium chloride staining and immunohistochemistry analysis was performed to determine SUR1 and TRPM4 expression. PtiO2 monitoring showed an abrupt reduction in values close to 0 mmHg after MCA occlusion in the core area. Hourly cerebral microdialysis showed that the infarcted tissue was characterized by reduced concentrations of glucose (0.03 mM) and pyruvate (0.003 mM) and increases in lactate levels (8.87mM), lactate-pyruvate ratio (4202), glycerol levels (588 μM), and potassium concentration (27.9 mmol/L). Immunohistochemical analysis showed increased expression of SUR1-TRPM4 channels. The aim of the present proof-of-principle study was to document the feasibility of a large animal model of malignant MCA infarction by performing transcranial occlusion of the MCA in the common pig, as an alternative to lisencephalic animals. This model may be useful for detailed studies of cerebral ischemia mechanisms and the development of neuroprotective strategies.

ForCent model development and testing using the Enriched Background Isotope Study experiment

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

Parton, W.J.; Hanson, P. J.; Swanston, C.

The ForCent forest ecosystem model was developed by making major revisions to the DayCent model including: (1) adding a humus organic pool, (2) incorporating a detailed root growth model, and (3) including plant phenological growth patterns. Observed plant production and soil respiration data from 1993 to 2000 were used to demonstrate that the ForCent model could accurately simulate ecosystem carbon dynamics for the Oak Ridge National Laboratory deciduous forest. A comparison of ForCent versus observed soil pool {sup 14}C signature ({Delta} {sup 14}C) data from the Enriched Background Isotope Study {sup 14}C experiment (1999-2006) shows that the model correctly simulatesmore » the temporal dynamics of the {sup 14}C label as it moved from the surface litter and roots into the mineral soil organic matter pools. ForCent model validation was performed by comparing the observed Enriched Background Isotope Study experimental data with simulated live and dead root biomass {Delta} {sup 14}C data, and with soil respiration {Delta} {sup 14}C (mineral soil, humus layer, leaf litter layer, and total soil respiration) data. Results show that the model correctly simulates the impact of the Enriched Background Isotope Study {sup 14}C experimental treatments on soil respiration {Delta} {sup 14}C values for the different soil organic matter pools. Model results suggest that a two-pool root growth model correctly represents root carbon dynamics and inputs to the soil. The model fitting process and sensitivity analysis exposed uncertainty in our estimates of the fraction of mineral soil in the slow and passive pools, dissolved organic carbon flux out of the litter layer into the mineral soil, and mixing of the humus layer into the mineral soil layer.« less

ForCent Model Development and Testing using the Enriched Background Isotope Study (EBIS) Experiment

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

Parton, William; Hanson, Paul J; Swanston, Chris

The ForCent forest ecosystem model was developed by making major revisions to the DayCent model including: (1) adding a humus organic pool, (2) incorporating a detailed root growth model, and (3) including plant phenological growth patterns. Observed plant production and soil respiration data from 1993 to 2000 were used to demonstrate that the ForCent model could accurately simulate ecosystem carbon dynamics for the Oak Ridge National Laboratory deciduous forest. A comparison of ForCent versus observed soil pool 14C signature (? 14C) data from the Enriched Background Isotope Study 14C experiment (1999-2006) shows that the model correctly simulates the temporal dynamicsmore » of the 14C label as it moved from the surface litter and roots into the mineral soil organic matter pools. ForCent model validation was performed by comparing the observed Enriched Background Isotope Study experimental data with simulated live and dead root biomass ? 14C data, and with soil respiration ? 14C (mineral soil, humus layer, leaf litter layer, and total soil respiration) data. Results show that the model correctly simulates the impact of the Enriched Background Isotope Study 14C experimental treatments on soil respiration ? 14C values for the different soil organic matter pools. Model results suggest that a two-pool root growth model correctly represents root carbon dynamics and inputs to the soil. The model fitting process and sensitivity analysis exposed uncertainty in our estimates of the fraction of mineral soil in the slow and passive pools, dissolved organic carbon flux out of the litter layer into the mineral soil, and mixing of the humus layer into the mineral soil layer.« less

Theoretical study of liquid droplet dispersion in a venturi scrubber.

PubMed

Fathikalajahi, J; Talaie, M R; Taheri, M

1995-03-01

The droplet concentration distribution in an atomizing scrubber was calculated based on droplet eddy diffusion by a three-dimensional dispersion model. This model is also capable of predicting the liquid flowing on the wall. The theoretical distribution of droplet concentration agrees well with experimental data given by Viswanathan et al. for droplet concentration distribution in a venturi-type scrubber. The results obtained by the model show a non-uniform distribution of drops over the cross section of the scrubber, as noted by the experimental data. While the maximum of droplet concentration distribution may depend on many operating parameters of the scrubber, the results of this study show that the highest uniformity of drop distribution will be reached when penetration length is approximately equal to one-fourth of the depth of the scrubber. The results of this study can be applied to evaluate the removal efficiency of a venturi scrubber.

Generic Science Skills Enhancement of Students through Implementation of IDEAL Problem Solving Model on Genetic Information Course

NASA Astrophysics Data System (ADS)

Zirconia, A.; Supriyanti, F. M. T.; Supriatna, A.

2018-04-01

This study aims to determine generic science skills enhancement of students through implementation of IDEAL problem-solving model on genetic information course. Method of this research was mixed method, with pretest-posttest nonequivalent control group design. Subjects of this study were chemistry students enrolled in biochemistry course, consisted of 22 students in the experimental class and 19 students in control class. The instrument in this study was essayed involves 6 indicators generic science skills such as indirect observation, causality thinking, logical frame, self-consistent thinking, symbolic language, and developing concept. The results showed that genetic information course using IDEAL problem-solving model have been enhancing generic science skills in low category with of 20,93%. Based on result for each indicator, showed that there are indicators of generic science skills classified in the high category.

Analysis of perceived risk among construction workers: a cross-cultural study and reflection on the Hofstede model.

PubMed

Martinez-Fiestas, Myriam; Rodríguez-Garzón, Ignacio; Delgado-Padial, Antonio; Lucas-Ruiz, Valeriano

2017-09-01

This article presents a cross-cultural study on perceived risk in the construction industry. Worker samples from three different countries were studied: Spain, Peru and Nicaragua. The main goal was to explain how construction workers perceive their occupational hazard and to analyze how this is related to their national culture. The model used to measure perceived risk was the psychometric paradigm. The results show three very similar profiles, indicating that risk perception is independent of nationality. A cultural analysis was conducted using the Hofstede model. The results of this analysis and the relation to perceived risk showed that risk perception in construction is independent of national culture. Finally, a multiple lineal regression analysis was conducted to determine what qualitative attributes could predict the global quantitative size of risk perception. All of the findings have important implications regarding the management of safety in the workplace.

Pressure Distribution on Inner Wall of Parabolic Nozzle in Laser Propulsion with Single Pulse

NASA Astrophysics Data System (ADS)

Cui, Cunyan; Hong, Yanji; Wen, Ming; Song, Junling; Fang, Juan

2011-11-01

A system based of dynamic pressure sensors was established to study the time resolved pressure distribution on the inner wall of a parabolic nozzle in laser propulsion. Dynamic calibration and static calibration of the test system were made and the results showed that frequency response was up to 412 kHz and linear error was less than 10%. Experimental model was a parabolic nozzle and three test points were preset along one generating line. This study showed that experimental results agreed well with those obtained by numerical calculation way in pressure evolution tendency. The peak value of the calculation was higher than that of the experiment at each tested orifice because of the limitation of the numerical models. The results of this study were very useful for analyzing the energy deposition in laser propulsion and modifying numerical models.

Species survival emerge from rare events of individual migration

NASA Astrophysics Data System (ADS)

Zelnik, Yuval R.; Solomon, Sorin; Yaari, Gur

2015-01-01

Ecosystems greatly vary in their species composition and interactions, yet they all show remarkable resilience to external influences. Recent experiments have highlighted the significant effects of spatial structure and connectivity on the extinction and survival of species. It has also been emphasized lately that in order to study extinction dynamics reliably, it is essential to incorporate stochasticity, and in particular the discrete nature of populations, into the model. Accordingly, we applied a bottom-up modeling approach that includes both spatial features and stochastic interactions to study survival mechanisms of species. Using the simplest spatial extension of the Lotka-Volterra predator-prey model with competition, subject to demographic and environmental noise, we were able to systematically study emergent properties of this rich system. By scanning the relevant parameter space, we show that both survival and extinction processes often result from a combination of habitat fragmentation and individual rare events of recolonization.

Experiment and simulation study on unidirectional carbon fiber composite component under dynamic 3 point bending loading

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

Zhou, Guowei; Sun, Qingping; Zeng, Danielle

In current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic 3 point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-Dyna for more detailed study. The simulation results show that the delamination plays an important role during dynamic 3 point bending test. Based on the analysis with high speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, current material model cannot capture the postmore » failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonable well.« less

Fine structure of the amide i band in acetanilide

NASA Astrophysics Data System (ADS)

Careri, G.; Gratton, E.; Shyamsunder, E.

1988-05-01

Their absorption spectrum of both single crystals and powdered samples of acetanilide (a model system for proteins) has been studied in the amide i region, where a narrow band has been identified as a highly trapped soliton state. The powder-sample spectra have been decomposed using four Lorentzian bands. A strong temperature dependence has been found for the intensity of two of the subbands, which also show a complementary behavior. Polarization studies performed on thin crystals have shown that the subbands have the same polarization. Low-temperature spectra of partially deuterated samples show the presence of the subbands at the same absorption frequencies found using the fitting procedure in the spectra of nondeuterated samples. The soliton model currently proposed to explain the origin of the anomalous amide i component at 1650 cm-1 still holds, but some modification of the model is required to account for the new features revealed by this study.

Impact of airway morphological changes on pulmonary flows in scoliosis

NASA Astrophysics Data System (ADS)

Farrell, James; Garrido, Enrique; Valluri, Prashant

2016-11-01

The relationship between thoracic deformity in scoliosis and lung function is poorly understood. In a pilot study, we reviewed computed tomography (CT) routine scans of patients undergoing scoliosis surgery. The CT scans were processed to segment the anatomy of the airways, lung and spine. A three-dimensional model was created to study the anatomical relationship. Preliminary analysis showed significant airway morphological differences depending on the anterior position of the spine. A computational fluid dynamics (CFD) study was also conducted on the airway geometry using the inspiratory scans. The CFD model assuming non-compliant airway walls was capable of showing pressure drops in areas of high airway resistance, but was unable to predict regional ventilation differences. Our results indicate a dependence between the dynamic deformation of the airway during breathing and lung function. Dynamic structural deformation must therefore be incorporated within any modelling approaches to guide clinicians on the decision to perform surgical correction of the scoliosis.

Species survival emerge from rare events of individual migration.

PubMed

Zelnik, Yuval R; Solomon, Sorin; Yaari, Gur

2015-01-19

Ecosystems greatly vary in their species composition and interactions, yet they all show remarkable resilience to external influences. Recent experiments have highlighted the significant effects of spatial structure and connectivity on the extinction and survival of species. It has also been emphasized lately that in order to study extinction dynamics reliably, it is essential to incorporate stochasticity, and in particular the discrete nature of populations, into the model. Accordingly, we applied a bottom-up modeling approach that includes both spatial features and stochastic interactions to study survival mechanisms of species. Using the simplest spatial extension of the Lotka-Volterra predator-prey model with competition, subject to demographic and environmental noise, we were able to systematically study emergent properties of this rich system. By scanning the relevant parameter space, we show that both survival and extinction processes often result from a combination of habitat fragmentation and individual rare events of recolonization.

Effect of suspension kinematic on 14 DOF vehicle model

NASA Astrophysics Data System (ADS)

Wongpattananukul, T.; Chantharasenawong, C.

2017-12-01

Computer simulations play a major role in shaping modern science and engineering. They reduce time and resource consumption in new studies and designs. Vehicle simulations have been studied extensively to achieve a vehicle model used in minimum lap time solution. Simulation result accuracy depends on the abilities of these models to represent real phenomenon. Vehicles models with 7 degrees of freedom (DOF), 10 DOF and 14 DOF are normally used in optimal control to solve for minimum lap time. However, suspension kinematics are always neglected on these models. Suspension kinematics are defined as wheel movements with respect to the vehicle body. Tire forces are expressed as a function of wheel slip and wheel position. Therefore, the suspension kinematic relation is appended to the 14 DOF vehicle model to investigate its effects on the accuracy of simulate trajectory. Classical 14 DOF vehicle model is chosen as baseline model. Experiment data is collected from formula student style car test runs as baseline data for simulation and comparison between baseline model and model with suspension kinematic. Results show that in a single long turn there is an accumulated trajectory error in baseline model compared to model with suspension kinematic. While in short alternate turns, the trajectory error is much smaller. These results show that suspension kinematic had an effect on the trajectory simulation of vehicle. Which optimal control that use baseline model will result in inaccuracy control scheme.

Vibration acceleration promotes bone formation in rodent models

PubMed Central

Uchida, Ryohei; Nakata, Ken; Kawano, Fuminori; Yonetani, Yasukazu; Ogasawara, Issei; Nakai, Naoya; Mae, Tatsuo; Matsuo, Tomohiko; Tachibana, Yuta; Yokoi, Hiroyuki; Yoshikawa, Hideki

2017-01-01

All living tissues and cells on Earth are subject to gravitational acceleration, but no reports have verified whether acceleration mode influences bone formation and healing. Therefore, this study was to compare the effects of two acceleration modes, vibration and constant (centrifugal) accelerations, on bone formation and healing in the trunk using BMP 2-induced ectopic bone formation (EBF) mouse model and a rib fracture healing (RFH) rat model. Additionally, we tried to verify the difference in mechanism of effect on bone formation by accelerations between these two models. Three groups (low- and high-magnitude vibration and control-VA groups) were evaluated in the vibration acceleration study, and two groups (centrifuge acceleration and control-CA groups) were used in the constant acceleration study. In each model, the intervention was applied for ten minutes per day from three days after surgery for eleven days (EBF model) or nine days (RFH model). All animals were sacrificed the day after the intervention ended. In the EBF model, ectopic bone was evaluated by macroscopic and histological observations, wet weight, radiography and microfocus computed tomography (micro-CT). In the RFH model, whole fracture-repaired ribs were excised with removal of soft tissue, and evaluated radiologically and histologically. Ectopic bones in the low-magnitude group (EBF model) had significantly greater wet weight and were significantly larger (macroscopically and radiographically) than those in the other two groups, whereas the size and wet weight of ectopic bones in the centrifuge acceleration group showed no significant difference compared those in control-CA group. All ectopic bones showed calcified trabeculae and maturated bone marrow. Micro-CT showed that bone volume (BV) in the low-magnitude group of EBF model was significantly higher than those in the other two groups (3.1±1.2mm3 v.s. 1.8±1.2mm3 in high-magnitude group and 1.3±0.9mm3 in control-VA group), but BV in the centrifuge acceleration group had no significant difference compared those in control-CA group. Union rate and BV in the low-magnitude group of RFH model were also significantly higher than those in the other groups (Union rate: 60% v.s. 0% in the high-magnitude group and 10% in the control-VA group, BV: 0.69±0.30mm3 v.s. 0.15±0.09mm3 in high-magnitude group and 0.22±0.17mm3 in control-VA group). BV/TV in the low-magnitude group of RFH model was significantly higher than that in control-VA group (59.4±14.9% v.s. 35.8±13.5%). On the other hand, radiographic union rate (10% in centrifuge acceleration group v.s. 20% in control-CA group) and micro-CT parameters in RFH model were not significantly different between two groups in the constant acceleration studies. Radiographic images of non-union rib fractures showed cartilage at the fracture site and poor new bone formation, whereas union samples showed only new bone. In conclusion, low-magnitude vibration acceleration promoted bone formation at the trunk in both BMP-induced ectopic bone formation and rib fracture healing models. However, the micro-CT parameters were not similar between two models, which suggested that there might be difference in the mechanism of effect by vibration between two models. PMID:28264058

Vibration acceleration promotes bone formation in rodent models.

PubMed

Uchida, Ryohei; Nakata, Ken; Kawano, Fuminori; Yonetani, Yasukazu; Ogasawara, Issei; Nakai, Naoya; Mae, Tatsuo; Matsuo, Tomohiko; Tachibana, Yuta; Yokoi, Hiroyuki; Yoshikawa, Hideki

2017-01-01

All living tissues and cells on Earth are subject to gravitational acceleration, but no reports have verified whether acceleration mode influences bone formation and healing. Therefore, this study was to compare the effects of two acceleration modes, vibration and constant (centrifugal) accelerations, on bone formation and healing in the trunk using BMP 2-induced ectopic bone formation (EBF) mouse model and a rib fracture healing (RFH) rat model. Additionally, we tried to verify the difference in mechanism of effect on bone formation by accelerations between these two models. Three groups (low- and high-magnitude vibration and control-VA groups) were evaluated in the vibration acceleration study, and two groups (centrifuge acceleration and control-CA groups) were used in the constant acceleration study. In each model, the intervention was applied for ten minutes per day from three days after surgery for eleven days (EBF model) or nine days (RFH model). All animals were sacrificed the day after the intervention ended. In the EBF model, ectopic bone was evaluated by macroscopic and histological observations, wet weight, radiography and microfocus computed tomography (micro-CT). In the RFH model, whole fracture-repaired ribs were excised with removal of soft tissue, and evaluated radiologically and histologically. Ectopic bones in the low-magnitude group (EBF model) had significantly greater wet weight and were significantly larger (macroscopically and radiographically) than those in the other two groups, whereas the size and wet weight of ectopic bones in the centrifuge acceleration group showed no significant difference compared those in control-CA group. All ectopic bones showed calcified trabeculae and maturated bone marrow. Micro-CT showed that bone volume (BV) in the low-magnitude group of EBF model was significantly higher than those in the other two groups (3.1±1.2mm3 v.s. 1.8±1.2mm3 in high-magnitude group and 1.3±0.9mm3 in control-VA group), but BV in the centrifuge acceleration group had no significant difference compared those in control-CA group. Union rate and BV in the low-magnitude group of RFH model were also significantly higher than those in the other groups (Union rate: 60% v.s. 0% in the high-magnitude group and 10% in the control-VA group, BV: 0.69±0.30mm3 v.s. 0.15±0.09mm3 in high-magnitude group and 0.22±0.17mm3 in control-VA group). BV/TV in the low-magnitude group of RFH model was significantly higher than that in control-VA group (59.4±14.9% v.s. 35.8±13.5%). On the other hand, radiographic union rate (10% in centrifuge acceleration group v.s. 20% in control-CA group) and micro-CT parameters in RFH model were not significantly different between two groups in the constant acceleration studies. Radiographic images of non-union rib fractures showed cartilage at the fracture site and poor new bone formation, whereas union samples showed only new bone. In conclusion, low-magnitude vibration acceleration promoted bone formation at the trunk in both BMP-induced ectopic bone formation and rib fracture healing models. However, the micro-CT parameters were not similar between two models, which suggested that there might be difference in the mechanism of effect by vibration between two models.

On the application of the PFEM to droplet dynamics modeling in fuel cells

NASA Astrophysics Data System (ADS)

Ryzhakov, Pavel B.; Jarauta, Alex; Secanell, Marc; Pons-Prats, Jordi

2017-07-01

The Particle Finite Element Method (PFEM) is used to develop a model to study two-phase flow in fuel cell gas channels. First, the PFEM is used to develop the model of free and sessile droplets. The droplet model is then coupled to an Eulerian, fixed-grid, model for the airflow. The resulting coupled PFEM-Eulerian algorithm is used to study droplet oscillations in an air flow and droplet growth in a low-temperature fuel cell gas channel. Numerical results show good agreement with predicted frequencies of oscillation, contact angle, and deformation of injected droplets in gas channels. The PFEM-based approach provides a novel strategy to study droplet dynamics in fuel cells.

Modeling dolomitized carbonate-ramp reservoirs: A case study of the Seminole San Andres unit. Part 2 -- Seismic modeling, reservoir geostatistics, and reservoir simulation

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

Wang, F.P.; Dai, J.; Kerans, C.

1998-11-01

In part 1 of this paper, the authors discussed the rock-fabric/petrophysical classes for dolomitized carbonate-ramp rocks, the effects of rock fabric and pore type on petrophysical properties, petrophysical models for analyzing wireline logs, the critical scales for defining geologic framework, and 3-D geologic modeling. Part 2 focuses on geophysical and engineering characterizations, including seismic modeling, reservoir geostatistics, stochastic modeling, and reservoir simulation. Synthetic seismograms of 30 to 200 Hz were generated to study the level of seismic resolution required to capture the high-frequency geologic features in dolomitized carbonate-ramp reservoirs. Outcrop data were collected to investigate effects of sampling interval andmore » scale-up of block size on geostatistical parameters. Semivariogram analysis of outcrop data showed that the sill of log permeability decreases and the correlation length increases with an increase of horizontal block size. Permeability models were generated using conventional linear interpolation, stochastic realizations without stratigraphic constraints, and stochastic realizations with stratigraphic constraints. Simulations of a fine-scale Lawyer Canyon outcrop model were used to study the factors affecting waterflooding performance. Simulation results show that waterflooding performance depends strongly on the geometry and stacking pattern of the rock-fabric units and on the location of production and injection wells.« less

Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations

NASA Astrophysics Data System (ADS)

Ichii, K.; Suzuki, T.; Kato, T.; Ito, A.; Hajima, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.; Ohtani, Y.; Takagi, K.

2010-07-01

Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine - based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four eddy flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and a modified model (based on model parameter tuning using eddy flux data). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

Experimental study of overland flow resistance coefficient model of grassland based on BP neural network

NASA Astrophysics Data System (ADS)

Jiao, Peng; Yang, Er; Ni, Yong Xin

2018-06-01

The overland flow resistance on grassland slope of 20° was studied by using simulated rainfall experiments. Model of overland flow resistance coefficient was established based on BP neural network. The input variations of model were rainfall intensity, flow velocity, water depth, and roughness of slope surface, and the output variations was overland flow resistance coefficient. Model was optimized by Genetic Algorithm. The results show that the model can be used to calculate overland flow resistance coefficient, and has high simulation accuracy. The average prediction error of the optimized model of test set is 8.02%, and the maximum prediction error was 18.34%.

Modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia-A generalised linear model with break-point analysis.

PubMed

Alkhaldy, Ibrahim

2017-04-01

The aim of this study was to examine the role of environmental factors in the temporal distribution of dengue fever in Jeddah, Saudi Arabia. The relationship between dengue fever cases and climatic factors such as relative humidity and temperature was investigated during 2006-2009 to determine whether there is any relationship between dengue fever cases and climatic parameters in Jeddah City, Saudi Arabia. A generalised linear model (GLM) with a break-point was used to determine how different levels of temperature and relative humidity affected the distribution of the number of cases of dengue fever. Break-point analysis was performed to modelled the effect before and after a break-point (change point) in the explanatory parameters under various scenarios. Akaike information criterion (AIC) and cross validation (CV) were used to assess the performance of the models. The results showed that maximum temperature and mean relative humidity are most probably the better predictors of the number of dengue fever cases in Jeddah. In this study three scenarios were modelled: no time lag, 1-week lag and 2-weeks lag. Among these scenarios, the 1-week lag model using mean relative humidity as an explanatory variable showed better performance. This study showed a clear relationship between the meteorological variables and the number of dengue fever cases in Jeddah. The results also demonstrated that meteorological variables can be successfully used to estimate the number of dengue fever cases for a given period of time. Break-point analysis provides further insight into the association between meteorological parameters and dengue fever cases by dividing the meteorological parameters into certain break-points. Copyright © 2016 Elsevier B.V. All rights reserved.

a Study about Terrestrial Laser Scanning for Reconstruction of Precast Concrete to Support Qlassic Assessment

NASA Astrophysics Data System (ADS)

Aziz, M. A.; Idris, K. M.; Majid, Z.; Ariff, M. F. M.; Yusoff, A. R.; Luh, L. C.; Abbas, M. A.; Chong, A. K.

2016-09-01

Nowadays, terrestrial laser scanning shows the potential to improve construction productivity by measuring the objects changes using real-time applications. This paper presents the process of implementation of an efficient framework for precast concrete using terrestrial laser scanning that enables contractors to acquire accurate data and support Quality Assessment System in Construction (QLASSIC). Leica Scanstation C10, black/white target, Autodesk Revit and Cyclone software were used in this study. The results were compared with the dimensional of based model precast concrete given by the company as a reference with the AutoDesk Revit model from the terrestrial laser scanning data and conventional method (measuring tape). To support QLASSIC, the tolerance dimensions of cast in-situ & precast elements is +10mm / -5mm. The results showed that the root mean square error for a Revit model is 2.972mm while using measuring tape is 13.687mm. The accuracy showed that terrestrial laser scanning has an advantage in construction jobs to support QLASSIC.

Boundary-layer diabatic processes, the virtual effect, and convective self-aggregation

NASA Astrophysics Data System (ADS)

Yang, D.

2017-12-01

The atmosphere can self-organize into long-lasting large-scale overturning circulations over an ocean surface with uniform temperature. This phenomenon is referred to as convective self-aggregation and has been argued to be important for tropical weather and climate systems. Here we use a 1D shallow water model and a 2D cloud-resolving model (CRM) to show that boundary-layer diabatic processes are essential for convective self-aggregation. We will show that boundary-layer radiative cooling, convective heating, and surface buoyancy flux help convection self-aggregate because they generate available potential energy (APE), which sustains the overturning circulation. We will also show that evaporative cooling in the boundary layer (cold pool) inhibits convective self-aggregation by reducing APE. Both the shallow water model and CRM results suggest that the enhanced virtual effect of water vapor can lead to convective self-aggregation, and this effect is mainly in the boundary layer. This study proposes new dynamical feedbacks for convective self-aggregation and complements current studies that focus on thermodynamic feedbacks.

DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation.

PubMed

Zhang, Laobing; Landucci, Gabriele; Reniers, Genserik; Khakzad, Nima; Zhou, Jianfeng

2017-12-19

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases. © 2017 Society for Risk Analysis.

Validity of using ad hoc methods to analyze secondary traits in case-control association studies.

PubMed

Yung, Godwin; Lin, Xihong

2016-12-01

Case-control association studies often collect from their subjects information on secondary phenotypes. Reusing the data and studying the association between genes and secondary phenotypes provide an attractive and cost-effective approach that can lead to discovery of new genetic associations. A number of approaches have been proposed, including simple and computationally efficient ad hoc methods that ignore ascertainment or stratify on case-control status. Justification for these approaches relies on the assumption of no covariates and the correct specification of the primary disease model as a logistic model. Both might not be true in practice, for example, in the presence of population stratification or the primary disease model following a probit model. In this paper, we investigate the validity of ad hoc methods in the presence of covariates and possible disease model misspecification. We show that in taking an ad hoc approach, it may be desirable to include covariates that affect the primary disease in the secondary phenotype model, even though these covariates are not necessarily associated with the secondary phenotype. We also show that when the disease is rare, ad hoc methods can lead to severely biased estimation and inference if the true disease model follows a probit model instead of a logistic model. Our results are justified theoretically and via simulations. Applied to real data analysis of genetic associations with cigarette smoking, ad hoc methods collectively identified as highly significant (P<10-5) single nucleotide polymorphisms from over 10 genes, genes that were identified in previous studies of smoking cessation. © 2016 WILEY PERIODICALS, INC.

A systematic review of 3-D printing in cardiovascular and cerebrovascular diseases

PubMed Central

Sun, Zhonghua; Lee, Shen-Yuan

2017-01-01

Objective: The application of 3-D printing has been increasingly used in medicine, with research showing many applications in cardiovascular disease. This systematic review analyzes those studies published about the applications of 3-D printed, patient-specific models in cardiovascular and cerebrovascular diseases. Methods: A search of PubMed/Medline and Scopus databases was performed to identify studies investigating the 3-D printing in cardiovascular and cerebrovascular diseases. Only studies based on patient’s medical images were eligible for review, while reports on in vitro phantom or review articles were excluded. Results: A total of 48 studies met selection criteria for inclusion in the review. A range of patient-specific 3-D printed models of different cardiovascular and cerebrovascular diseases were generated in these studies with most of them being developed using cardiac CT and MRI data, less commonly with 3-D invasive angiographic or echocardiographic images. The review of these studies showed high accuracy of 3-D printed, patient-specific models to represent complex anatomy of the cardiovascular and cerebrovascular system and depict various abnormalities, especially congenital heart diseases and valvular pathologies. Further, 3-D printing can serve as a useful education tool for both parents and clinicians, and a valuable tool for pre-surgical planning and simulation. Conclusion: This systematic review shows that 3-D printed models based on medical imaging modalities can accurately replicate complex anatomical structures and pathologies of the cardiovascular and cerebrovascular system. 3-D printing is a useful tool for both education and surgical planning in these diseases. PMID:28430115

Academic Outcome Measures of a Dedicated Education Unit Over Time: Help or Hinder?

PubMed

Smyer, Tish; Gatlin, Tricia; Tan, Rhigel; Tejada, Marianne; Feng, Du

2015-01-01

Critical thinking, nursing process, quality and safety measures, and standardized RN exit examination scores were compared between students (n = 144) placed in a dedicated education unit (DEU) and those in a traditional clinical model. Standardized test scores showed that differences between the clinical groups were not statistically significant. This study shows that the DEU model is 1 approach to clinical education that can enhance students' academic outcomes.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.

Undergraduate Research: Mathematical Modeling of Mortgages

ERIC Educational Resources Information Center

Choi, Youngna; Spero, Steven

2010-01-01

In this article, we study financing in the real estate market and show how various types of mortgages can be modeled and analyzed. With only an introductory level of interest theory, finance, and calculus, we model and analyze three types of popular mortgages with real life examples that explain the background and inevitable outcome of the current…

The Cognitive-Miser Response Model: Testing for Intuitive and Deliberate Reasoning

ERIC Educational Resources Information Center

Bockenholt, Ulf

2012-01-01

In a number of psychological studies, answers to reasoning vignettes have been shown to result from both intuitive and deliberate response processes. This paper utilizes a psychometric model to separate these two response tendencies. An experimental application shows that the proposed model facilitates the analysis of dual-process item responses…

Modeling Classroom Discourse: Do Models That Predict Dialogic Instruction Properties Generalize across Populations?

ERIC Educational Resources Information Center

Samei, Borhan; Olney, Andrew M.; Kelly, Sean; Nystrand, Martin; D'Mello, Sidney; Blanchard, Nathan; Graesser, Art

2015-01-01

It has previously been shown that the effective use of dialogic instruction has a positive impact on student achievement. In this study, we investigate whether linguistic features used to classify properties of classroom discourse generalize across different subpopulations. Results showed that the machine learned models perform equally well when…

Periodic and Aperiodic Close Packing: A Spontaneous Hard-Sphere Model.

ERIC Educational Resources Information Center

van de Waal, B. W.

1985-01-01

Shows how to make close-packed models from balloons and table tennis balls to illustrate structural features of clusters and organometallic cluster-compounds (which are of great interest in the study of chemical reactions). These models provide a very inexpensive and tactile illustration of the organization of matter for concrete operational…

An Application of the Social Support Deterioration Deterrence Model to Rescue Workers

ERIC Educational Resources Information Center

Prati, Gabriele; Pietrantoni, Luca

2010-01-01

This study examined the role of social support in promoting quality of life in the aftermath of critical incidents involvement. Participants were a sample of 586 Italian rescue workers. Structural equation modelling was used to test the social support deterioration deterrence model. Results showed that the impact of critical incident involvement…

A Causal Model of Teacher Acceptance of Technology

ERIC Educational Resources Information Center

Chang, Jui-Ling; Lieu, Pang-Tien; Liang, Jung-Hui; Liu, Hsiang-Te; Wong, Seng-lee

2012-01-01

This study proposes a causal model for investigating teacher acceptance of technology. We received 258 effective replies from teachers at public and private universities in Taiwan. A questionnaire survey was utilized to test the proposed model. The Lisrel was applied to test the proposed hypotheses. The result shows that computer self-efficacy has…

The study of human venous system dynamics using hybrid computer modeling

NASA Technical Reports Server (NTRS)

Snyder, M. F.; Rideout, V. C.

1972-01-01

A computer-based model of the cardiovascular system was created emphasizing effects on the systemic venous system. Certain physiological aspects were emphasized: effects of heart rate, tilting, changes in respiration, and leg muscular contractions. The results from the model showed close correlation with findings previously reported in the literature.

The HPT Model Applied to a Kayak Company's Registration Process

ERIC Educational Resources Information Center

Martin, Florence; Hall, Herman A., IV; Blakely, Amanda; Gayford, Matthew C.; Gunter, Erin

2009-01-01

This case study describes the step-by-step application of the traditional human performance technology (HPT) model at a premier kayak company located on the coast of North Carolina. The HPT model was applied to address lost revenues related to three specific business issues: misinformed customers, dissatisfied customers, and guides not showing up…

Evaluation of Lightning Induced Effects in a Graphite Composite Fairing Structure. Parts 1 and 2

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Stanley, James E.; Wahid, Parveen F.

2011-01-01

Defining the electromagnetic environment inside a graphite composite fairing due to lightning is of interest to spacecraft developers. This paper is the first in a two part series and studies the shielding effectiveness of a graphite composite model fairing using derived equivalent properties. A frequency domain Method of Moments (MoM) model is developed and comparisons are made with shielding test results obtained using a vehicle-like composite fairing. The comparison results show that the analytical models can adequately predict the test results. Both measured and model data indicate that graphite composite fairings provide significant attenuation to magnetic fields as frequency increases. Diffusion effects are also discussed. Part 2 examines the time domain based effects through the development of a loop based induced field testing and a Transmission-Line-Matrix (TLM) model is developed in the time domain to study how the composite fairing affects lightning induced magnetic fields. Comparisons are made with shielding test results obtained using a vehicle-like composite fairing in the time domain. The comparison results show that the analytical models can adequately predict the test and industry results.

Improved estimation of hydraulic conductivity by combining stochastically simulated hydrofacies with geophysical data.

PubMed

Zhu, Lin; Gong, Huili; Chen, Yun; Li, Xiaojuan; Chang, Xiang; Cui, Yijiao

2016-03-01

Hydraulic conductivity is a major parameter affecting the output accuracy of groundwater flow and transport models. The most commonly used semi-empirical formula for estimating conductivity is Kozeny-Carman equation. However, this method alone does not work well with heterogeneous strata. Two important parameters, grain size and porosity, often show spatial variations at different scales. This study proposes a method for estimating conductivity distributions by combining a stochastic hydrofacies model with geophysical methods. The Markov chain model with transition probability matrix was adopted to re-construct structures of hydrofacies for deriving spatial deposit information. The geophysical and hydro-chemical data were used to estimate the porosity distribution through the Archie's law. Results show that the stochastic simulated hydrofacies model reflects the sedimentary features with an average model accuracy of 78% in comparison with borehole log data in the Chaobai alluvial fan. The estimated conductivity is reasonable and of the same order of magnitude of the outcomes of the pumping tests. The conductivity distribution is consistent with the sedimentary distributions. This study provides more reliable spatial distributions of the hydraulic parameters for further numerical modeling.

Dust Storm Monitoring Using Satellite Observatory and Numerical Modeling Analysis

NASA Astrophysics Data System (ADS)

Taghavi, Farahnaz

In recent years, the frequency of dust pollution events in the Iran Southwest are increased which caused huge damage and imposed a negative impacts on air quality, airport traffic and people daily life in local areas. Dust storms in this area usually start with the formation of a low-pressure center over the Arabian Peninsula. The main objectives of this study is to asses and monitor the movement of aerosols and pollutions from origin source to local areas using satellite imagery and numerical modeling analysis. Observational analyses from NCEP such as synoptic data (Uwind,Vwind,Vorticity and Divergence Fields), upper air radiosonde, measured visibility distributions, land cover data are also used in model comparisons to show differences in occurrence of dust events. The evolution and dynamics of this phenomena are studied on the based a method to modify the initial state of NWP output using discrepancies between dynamic fields and WV imagery in a grid. Results show that satellite images offers a means to control the behavior of numeric models and also the model using land cover data improving the wind-blown dust modeling.

Analysing and controlling the tax evasion dynamics via majority-vote model

NASA Astrophysics Data System (ADS)

Lima, F. W. S.

2010-09-01

Within the context of agent-based Monte-Carlo simulations, we study the well-known majority-vote model (MVM) with noise applied to tax evasion on simple square lattices, Voronoi-Delaunay random lattices, Barabasi-Albert networks, and Erdös-Rényi random graphs. In the order to analyse and to control the fluctuations for tax evasion in the economics model proposed by Zaklan, MVM is applied in the neighborhod of the noise critical qc to evolve the Zaklan model. The Zaklan model had been studied recently using the equilibrium Ising model. Here we show that the Zaklan model is robust because this can be studied using equilibrium dynamics of Ising model also through the nonequilibrium MVM and on various topologies cited above giving the same behavior regardless of dynamic or topology used here.

The Effects of Panax ginseng and Panax quinquefolius on Thermoregulation in Animal Models

PubMed Central

Hong, Bin Na; Do, Moon Ho; Her, You Ri

2015-01-01

We devised a study using animal models of hyperthermia and hypothermia and also attempted to accurately assess the effects of Panax ginseng (PG) and Panax quinquefolius (PQ) on body temperature using these models. In addition, we investigated the effects of PG and PQ in our animal models in high and low temperature environments. The results of our experiments show that mice with normothermia, hyperthermia, and hypothermia maintained their body temperatures after a certain period in accordance with the condition of each animal model. In our experiments of body temperature change in models of normal, low, or high room temperature, the hyperthermic model did not show any body temperature change in either the PG- or PQ-administered group. In the normal and low room temperature models, the group administered PG maintained body temperature, while the body temperature of the PQ-administered group was lower than or similar to that of the control group. In conclusion, the fact that PG increases body temperature could not be verified until now. We also showed that the effect of maintaining body temperature in the PG-administered group was superior in a hypothermia-prone low temperature environment. PMID:25709709

Parsimonious estimation of the Wechsler Memory Scale, Fourth Edition demographically adjusted index scores: immediate and delayed memory.

PubMed

Miller, Justin B; Axelrod, Bradley N; Schutte, Christian

2012-01-01

The recent release of the Wechsler Memory Scale Fourth Edition contains many improvements from a theoretical and administration perspective, including demographic corrections using the Advanced Clinical Solutions. Although the administration time has been reduced from previous versions, a shortened version may be desirable in certain situations given practical time limitations in clinical practice. The current study evaluated two- and three-subtest estimations of demographically corrected Immediate and Delayed Memory index scores using both simple arithmetic prorating and regression models. All estimated values were significantly associated with observed index scores. Use of Lin's Concordance Correlation Coefficient as a measure of agreement showed a high degree of precision and virtually zero bias in the models, although the regression models showed a stronger association than prorated models. Regression-based models proved to be more accurate than prorated estimates with less dispersion around observed values, particularly when using three subtest regression models. Overall, the present research shows strong support for estimating demographically corrected index scores on the WMS-IV in clinical practice with an adequate performance using arithmetically prorated models and a stronger performance using regression models to predict index scores.

Development of a subway operation incident delay model using accelerated failure time approaches.

PubMed

Weng, Jinxian; Zheng, Yang; Yan, Xuedong; Meng, Qiang

2014-12-01

This study aims to develop a subway operational incident delay model using the parametric accelerated time failure (AFT) approach. Six parametric AFT models including the log-logistic, lognormal and Weibull models, with fixed and random parameters are built based on the Hong Kong subway operation incident data from 2005 to 2012, respectively. In addition, the Weibull model with gamma heterogeneity is also considered to compare the model performance. The goodness-of-fit test results show that the log-logistic AFT model with random parameters is most suitable for estimating the subway incident delay. First, the results show that a longer subway operation incident delay is highly correlated with the following factors: power cable failure, signal cable failure, turnout communication disruption and crashes involving a casualty. Vehicle failure makes the least impact on the increment of subway operation incident delay. According to these results, several possible measures, such as the use of short-distance and wireless communication technology (e.g., Wifi and Zigbee) are suggested to shorten the delay caused by subway operation incidents. Finally, the temporal transferability test results show that the developed log-logistic AFT model with random parameters is stable over time. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis.

PubMed

Xie, Yuanchang; Lord, Dominique; Zhang, Yunlong

2007-09-01

Statistical models have frequently been used in highway safety studies. They can be utilized for various purposes, including establishing relationships between variables, screening covariates and predicting values. Generalized linear models (GLM) and hierarchical Bayes models (HBM) have been the most common types of model favored by transportation safety analysts. Over the last few years, researchers have proposed the back-propagation neural network (BPNN) model for modeling the phenomenon under study. Compared to GLMs and HBMs, BPNNs have received much less attention in highway safety modeling. The reasons are attributed to the complexity for estimating this kind of model as well as the problem related to "over-fitting" the data. To circumvent the latter problem, some statisticians have proposed the use of Bayesian neural network (BNN) models. These models have been shown to perform better than BPNN models while at the same time reducing the difficulty associated with over-fitting the data. The objective of this study is to evaluate the application of BNN models for predicting motor vehicle crashes. To accomplish this objective, a series of models was estimated using data collected on rural frontage roads in Texas. Three types of models were compared: BPNN, BNN and the negative binomial (NB) regression models. The results of this study show that in general both types of neural network models perform better than the NB regression model in terms of data prediction. Although the BPNN model can occasionally provide better or approximately equivalent prediction performance compared to the BNN model, in most cases its prediction performance is worse than the BNN model. In addition, the data fitting performance of the BPNN model is consistently worse than the BNN model, which suggests that the BNN model has better generalization abilities than the BPNN model and can effectively alleviate the over-fitting problem without significantly compromising the nonlinear approximation ability. The results also show that BNNs could be used for other useful analyses in highway safety, including the development of accident modification factors and for improving the prediction capabilities for evaluating different highway design alternatives.

MLS Multipath Studies. Phase 3. Volume I. Overview and Propagation Model Validation/Refinement Studies.

DTIC Science & Technology

1979-04-25

Airport (Bedford, MA ) and Ft. Devens, MA. (2) validation of the models for building reflections based on elevation field measurements at JFK airport and...angles. 2-60 III. BUILDING REFLECTIONS A. Van Measurements at John F. Kennedy (JFK) International Airport, New York Figure 3-1 shows a map of JFK airport with

The Use of an Expectancy-Value Model in Studying a University's Image. AIR Forum 1982 Paper.

ERIC Educational Resources Information Center

Muffo, John A.; Whipple, Thomas W.

The use of an expectancy-value model, common to consumer marketing studies, in analyzing the market position of Cleveland State University was investigated. Attention was focused on showing how consumer attitude concepts and methodologies can be used in developing a strategic marketing plan. Six populations were identified as groups important to…

What? Another Form? The Process of Measuring and Comparing Service Utilization in a Community Mental Health Program Model.

ERIC Educational Resources Information Center

Dewa, Carolyn S.; Horgan, Salinda; Russell, Marc; Keates, Jane

2001-01-01

Describes experiences in developing a multi-program economic evaluation and costing study of Assertive Community Treatment (ACT), a widely studied community mental health treatment model. The project description shows how the worlds of research and service delivery can collaborate to come to symbiotic resolutions. (Author/SLD)

An Analysis of Computer-Mediated Communication between Middle School Students and Scientist Role Models: A Pilot Study.

ERIC Educational Resources Information Center

Murfin, Brian

1994-01-01

Reports on a study of the effectiveness of computer-mediated communication (CMC) in providing African American and female middle school students with scientist role models. Quantitative and qualitative data gathered by analyzing messages students and scientists posted on a shared electronic bulletin board showed that CMC could be an effective…

Modern anti-Semitism and anti-Israeli attitudes.

PubMed

Cohen, Florette; Jussim, Lee; Harber, Kent D; Bhasin, Gautam

2009-08-01

Anti-Semitism is resurgent throughout much of the world. A new theoretical model of anti-Semitism is presented and tested in 3 experiments. The model proposes that mortality salience increases anti-Semitism and that anti-Semitism often manifests as hostility toward Israel. Study 1 showed that mortality salience led to greater levels of anti-Semitism and lowered support for Israel. This effect occurred only in a bogus pipeline condition, indicating that social desirability masks hostility toward Jews and Israel. Study 2 showed that mortality salience caused Israel, but no other country, to perceptually loom large. Study 3 showed that mortality salience increased punitiveness toward Israel's human rights violations more than it increased hostility toward the identical human rights violations committed by Russia or India. Collectively, results suggest that Jews constitute a unique cultural threat to many people's worldviews, that anti-Semitism causes hostility to Israel, and that hostility to Israel may feed back to increase anti-Semitism.

Assertive community treatment and associations with delinquency.

PubMed

van Vugt, Maaike D; Kroon, Hans; Delespaul, Philippe A E G; Mulder, Cornelis L

This article draws on a prospective longitudinal study in which Assertive Community Treatment (ACT) model fidelity and patient outcomes were assessed in twenty outpatient treatment teams. 530 severely mentally ill patients participated in the study. Delinquency outcomes were assessed three times during a two-year follow-up period. At baseline, 49% of the patients had a recent criminal history, meaning that they had at least one reported contact with the police and/or the justice system in the past year. Patients with a recent criminal history had more serious psychosocial problems at baseline compared to those without a recent criminal history. Delinquency outcomes showed improvement over time, but this was not associated with ACT model fidelity. The study shows an association for homelessness and criminal activity. The persistent criminal activities of some of the patients showed that for this group extra interventions are needed that specifically target reduction of criminal behavior. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adsorption performance of coconut shell activated carbon for the removal of chlorate from chlor-alkali brine stream.

PubMed

Lakshmanan, Shyam; Murugesan, Thanapalan

2016-12-01

Activated carbon from coconut shell was used to investigate the adsorption of chlorate from a chlor-alkali plant's brine stream. The effect of pH, flowrate, chlorate and chloride concentration on the breakthrough curves were studied in small-scale column trials. The results obtained show enhanced adsorption at low flowrates, higher chlorate concentrations, and at a pH of 10. These studies show that introducing an activated carbon adsorption column just before the saturator would remove sufficient quantities of chlorate to allow more of the chlor-alkali plant's brine stream to be reused. From column dynamic studies, the Thomas model showed close approximation when the chlorate in the effluent was higher than breakthrough concentrations and there was close correlation at high influent concentration. The q o (maximum adsorption capacity) values were close to those obtained experimentally, indicating close representation of the breakthrough curve by the Thomas model.

Electrical Wave Propagation in an Anisotropic Model of the Left Ventricle Based on Analytical Description of Cardiac Architecture

PubMed Central

Pravdin, Sergey F.; Dierckx, Hans; Katsnelson, Leonid B.; Solovyova, Olga; Markhasin, Vladimir S.; Panfilov, Alexander V.

2014-01-01

We develop a numerical approach based on our recent analytical model of fiber structure in the left ventricle of the human heart. A special curvilinear coordinate system is proposed to analytically include realistic ventricular shape and myofiber directions. With this anatomical model, electrophysiological simulations can be performed on a rectangular coordinate grid. We apply our method to study the effect of fiber rotation and electrical anisotropy of cardiac tissue (i.e., the ratio of the conductivity coefficients along and across the myocardial fibers) on wave propagation using the ten Tusscher–Panfilov (2006) ionic model for human ventricular cells. We show that fiber rotation increases the speed of cardiac activation and attenuates the effects of anisotropy. Our results show that the fiber rotation in the heart is an important factor underlying cardiac excitation. We also study scroll wave dynamics in our model and show the drift of a scroll wave filament whose velocity depends non-monotonically on the fiber rotation angle; the period of scroll wave rotation decreases with an increase of the fiber rotation angle; an increase in anisotropy may cause the breakup of a scroll wave, similar to the mother rotor mechanism of ventricular fibrillation. PMID:24817308

Pathways of paracetamol absorption from layered excipient suppositories: artificial intelligence approach.

PubMed

Belic, A; Grabnar, I; Karba, R; Mrhar, A

2003-01-01

When studying paracetamol availability after rectal administration, the differences between slower and faster release suppositories were discovered. Approach with modelling and simulation of compartment-based models was used to explore the differences. A study of paracetamol from layered excipient suppositories shows that many different mechanisms are involved in the drug pharmacokinetics. There is also a large number of articles, each dealing with only one or with a few of the mechanisms. However, there is little information available on how the mechanisms interact in the organism and thus govern the pharmacokinetics of the drug, which means that systemic view in the expert knowledge is missing. In the case of paracetamol rectal availability the use of partially fuzzyfied model allowed systemic combination of all described mechanisms found in the literature and measured data. In spite of non-identifiability, the model showed that patterns that explained differences in bioavailabilities of the two formulations of suppositories could be found. Results of modelling and simulation show that "in vivo" there is practically no difference in cumulative release profiles between the two formulations. However, due to higher content of mono-di-glycerides in a slower release formulation, the extent of absorption is augmented both by absorption-enhancing effect of mono-di-glycerides and the liver bypass mechanism via diminished viscosity.

Study of Gas Flow Characteristics in Tight Porous Media with a Microscale Lattice Boltzmann Model

PubMed Central

Zhao, Jianlin; Yao, Jun; Zhang, Min; Zhang, Lei; Yang, Yongfei; Sun, Hai; An, Senyou; Li, Aifen

2016-01-01

To investigate the gas flow characteristics in tight porous media, a microscale lattice Boltzmann (LB) model with the regularization procedure is firstly adopted to simulate gas flow in three-dimensional (3D) digital rocks. A shale digital rock and a sandstone digital rock are reconstructed to study the effects of pressure, temperature and pore size on microscale gas flow. The simulation results show that because of the microscale effect in tight porous media, the apparent permeability is always higher than the intrinsic permeability, and with the decrease of pressure or pore size, or with the increase of temperature, the difference between apparent permeability and intrinsic permeability increases. In addition, the Knudsen numbers under different conditions are calculated and the results show that gas flow characteristics in the digital rocks under different Knudsen numbers are quite different. With the increase of Knudsen number, gas flow in the digital rocks becomes more uniform and the effect of heterogeneity of the porous media on gas flow decreases. Finally, two commonly used apparent permeability calculation models are evaluated by the simulation results and the Klinkenberg model shows better accuracy. In addition, a better proportionality factor in Klinkenberg model is proposed according to the simulation results. PMID:27587293

Suffering by comparison: Twitter users' reactions to the Victoria's Secret Fashion Show.

PubMed

Chrisler, Joan C; Fung, Kaitlin T; Lopez, Alexandra M; Gorman, Jennifer A

2013-09-01

Social comparison theory suggests that evaluating the self in comparison with others (e.g., peers, celebrities, models) can influence body image. Experimental studies that have tested effects of viewing idealized images in the media often show that women feel worse about themselves after seeing images that illustrate the beauty ideal. Twitter presents a naturally occurring opportunity to study viewers' reactions. An analysis was conducted of 977 tweets sent immediately before and during the 2011 Victoria's Secret Fashion Show that reference the show. Although the majority were idiosyncratic remarks, many tweets contain evidence of upward social comparisons to the fashion models. There were tweets about body image, eating disorders, weight, desires for food or alcohol, and thoughts about self-harm. The results support social comparison theory, and suggest that vulnerable viewers could experience negative affect, or even engage in harmful behaviors, during or after viewing the show or others like it. Copyright © 2013 Elsevier Ltd. All rights reserved.

Wavepacket revivals in monolayer and bilayer graphene rings.

PubMed

García, Trinidad; Rodríguez-Bolívar, Salvador; Cordero, Nicolás A; Romera, Elvira

2013-06-12

We have studied the existence of quantum revivals in graphene quantum rings within a simplified model. The time evolution of a Gaussian-populated wavepacket shows revivals in monolayer and bilayer graphene rings. We have also studied this behavior for quantum rings in a perpendicular magnetic field. We have found that revival time is an observable that shows different values for monolayer and bilayer graphene quantum rings. In addition, the revival time shows valley degeneracy breaking.

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling.

PubMed

Pourghasemi, Hamid Reza; Yousefi, Saleh; Kornejady, Aiding; Cerdà, Artemi

2017-12-31

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion susceptibility in Aghemam watershed, Iran. To this aim, a gully inventory map along with sixteen gully conditioning factors was used. A 70:30% randomly partitioned sets were used to assess goodness-of-fit and prediction power of the models. The robustness, as the stability of models' performance in response to changes in the dataset, was assessed through three training/test replicates. As a result, conducted preliminary statistical tests showed that ANN has the highest concordance and spatial differentiation with a chi-square value of 36,656 at 95% confidence level, while the ME appeared to have the lowest concordance (1772). The ME model showed an impractical result where 45% of the study area was introduced as highly susceptible to gullying, in contrast, ANN-SVM indicated a practical result with focusing only on 34% of the study area. Through all three replicates, the ANN-SVM ensemble showed the highest goodness-of-fit and predictive power with a respective values of 0.897 (area under the success rate curve) and 0.879 (area under the prediction rate curve), on average, and correspondingly the highest robustness. This attests the important role of ensemble modeling in congruently building accurate and generalized models which emphasizes the necessity to examine different models integrations. The result of this study can prepare an outline for further biophysical designs on gullies scattered in the study area. Copyright © 2017 Elsevier B.V. All rights reserved.

A one-dimensional stochastic approach to the study of cyclic voltammetry with adsorption effects

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

Samin, Adib J.

In this study, a one-dimensional stochastic model based on the random walk approach is used to simulate cyclic voltammetry. The model takes into account mass transport, kinetics of the redox reactions, adsorption effects and changes in the morphology of the electrode. The model is shown to display the expected behavior. Furthermore, the model shows consistent qualitative agreement with a finite difference solution. This approach allows for an understanding of phenomena on a microscopic level and may be useful for analyzing qualitative features observed in experimentally recorded signals.

A one-dimensional stochastic approach to the study of cyclic voltammetry with adsorption effects

NASA Astrophysics Data System (ADS)

Samin, Adib J.

2016-05-01

In this study, a one-dimensional stochastic model based on the random walk approach is used to simulate cyclic voltammetry. The model takes into account mass transport, kinetics of the redox reactions, adsorption effects and changes in the morphology of the electrode. The model is shown to display the expected behavior. Furthermore, the model shows consistent qualitative agreement with a finite difference solution. This approach allows for an understanding of phenomena on a microscopic level and may be useful for analyzing qualitative features observed in experimentally recorded signals.

Social learning across psychological distance.

PubMed

Kalkstein, David A; Kleiman, Tali; Wakslak, Cheryl J; Liberman, Nira; Trope, Yaacov

2016-01-01

While those we learn from are often close to us, more and more our learning environments are shifting to include more distant and dissimilar others. The question we examine in 5 studies is how whom we learn from influences what we learn and how what we learn influences from whom we choose to learn it. In Study 1, we show that social learning, in and of itself, promotes higher level (more abstract) learning than does learning based on one's own direct experience. In Studies 2 and 3, we show that when people learn from and emulate others, they tend to do so at a higher level when learning from a distant model than from a near model. Studies 4 and 5 show that thinking about learning at a higher (compared to a lower) level leads individuals to expand the range of others that they will consider learning from. Study 6 shows that when given an actual choice, people prefer to learn low-level information from near sources and high-level information from distant sources. These results demonstrate a basic link between level of learning and psychological distance in social learning processes. (c) 2016 APA, all rights reserved).

A regional scale modeling framework combining biogeochemical model with life cycle and economic analysis for integrated assessment of cropping systems.

PubMed

Tabatabaie, Seyed Mohammad Hossein; Bolte, John P; Murthy, Ganti S

2018-06-01

The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO 2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO 2 -eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point. Copyright © 2017 Elsevier B.V. All rights reserved.

A transplantable TH-MYCN transgenic tumor model in C57Bl/6 mice for preclinical immunological studies in neuroblastoma.

PubMed

Kroesen, Michiel; Nierkens, Stefan; Ansems, Marleen; Wassink, Melissa; Orentas, Rimas J; Boon, Louis; den Brok, Martijn H; Hoogerbrugge, Peter M; Adema, Gosse J

2014-03-15

Current multimodal treatments for patients with neuroblastoma (NBL), including anti-disialoganglioside (GD2) monoclonal antibody (mAb) based immunotherapy, result in a favorable outcome in around only half of the patients with advanced disease. To improve this, novel immunocombinational strategies need to be developed and tested in autologous preclinical NBL models. A genetically well-explored autologous mouse model for NBL is the TH-MYCN model. However, the immunobiology of the TH-MYCN model remains largely unexplored. We developed a mouse model using a transplantable TH-MYCN cell line in syngeneic C57Bl/6 mice and characterized the immunobiology of this model. In this report, we show the relevance and opportunities of this model to study immunotherapy for human NBL. Similar to human NBL cells, syngeneic TH-MYCN-derived 9464D cells endogenously express the tumor antigen GD2 and low levels of MHC Class I. The presence of the adaptive immune system had little or no influence on tumor growth, showing the low immunogenicity of the NBL cells. In contrast, depletion of NK1.1+ cells resulted in enhanced tumor outgrowth in both wild-type and Rag1(-/-) mice, showing an important role for NK cells in the natural anti-NBL immune response. Analysis of the tumor infiltrating leukocytes ex vivo revealed the presence of both tumor associated myeloid cells and T regulatory cells, thus mimicking human NBL tumors. Finally, anti-GD2 mAb mediated NBL therapy resulted in ADCC in vitro and delayed tumor outgrowth in vivo. We conclude that the transplantable TH-MYCN model represents a relevant model for the development of novel immunocombinatorial approaches for NBL patients. © 2013 UICC.

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.

Intercomparison of terrestrial carbon fluxes and carbon use efficiency simulated by CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Kim, Dongmin; Lee, Myong-In; Jeong, Su-Jong; Im, Jungho; Cha, Dong Hyun; Lee, Sanggyun

2017-12-01

This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

A discrete epidemic model for bovine Babesiosis disease and tick populations

NASA Astrophysics Data System (ADS)

Aranda, Diego F.; Trejos, Deccy Y.; Valverde, Jose C.

2017-06-01

In this paper, we provide and study a discrete model for the transmission of Babesiosis disease in bovine and tick populations. This model supposes a discretization of the continuous-time model developed by us previously. The results, here obtained by discrete methods as opposed to continuous ones, show that similar conclusions can be obtained for the discrete model subject to the assumption of some parametric constraints which were not necessary in the continuous case. We prove that these parametric constraints are not artificial and, in fact, they can be deduced from the biological significance of the model. Finally, some numerical simulations are given to validate the model and verify our theoretical study.