Advances in Geoscience Modeling: Smart Modeling Frameworks, Self-Describing Models and the Role of Standardized Metadata

NASA Astrophysics Data System (ADS)

Peckham, Scott

2016-04-01

Over the last decade, model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that make it much easier for modelers to connect heterogeneous sets of process models in a plug-and-play manner to create composite "system models". These mechanisms greatly simplify code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing with standardized metadata. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can use the self description functions to learn about each process model in a collection to be coupled and then automatically call framework service components (e.g. regridders

A new universal dynamic model to describe eating rate and cumulative intake curves123

PubMed Central

Paynter, Jonathan; Peterson, Courtney M; Heymsfield, Steven B

2017-01-01

Background: Attempts to model cumulative intake curves with quadratic functions have not simultaneously taken gustatory stimulation, satiation, and maximal food intake into account. Objective: Our aim was to develop a dynamic model for cumulative intake curves that captures gustatory stimulation, satiation, and maximal food intake. Design: We developed a first-principles model describing cumulative intake that universally describes gustatory stimulation, satiation, and maximal food intake using 3 key parameters: 1) the initial eating rate, 2) the effective duration of eating, and 3) the maximal food intake. These model parameters were estimated in a study (n = 49) where eating rates were deliberately changed. Baseline data was used to determine the quality of model's fit to data compared with the quadratic model. The 3 parameters were also calculated in a second study consisting of restrained and unrestrained eaters. Finally, we calculated when the gustatory stimulation phase is short or absent. Results: The mean sum squared error for the first-principles model was 337.1 ± 240.4 compared with 581.6 ± 563.5 for the quadratic model, or a 43% improvement in fit. Individual comparison demonstrated lower errors for 94% of the subjects. Both sex (P = 0.002) and eating duration (P = 0.002) were associated with the initial eating rate (adjusted R2 = 0.23). Sex was also associated (P = 0.03 and P = 0.012) with the effective eating duration and maximum food intake (adjusted R2 = 0.06 and 0.11). In participants directed to eat as much as they could compared with as much as they felt comfortable with, the maximal intake parameter was approximately double the amount. The model found that certain parameter regions resulted in both stimulation and satiation phases, whereas others only produced a satiation phase. Conclusions: The first-principles model better quantifies interindividual differences in food intake, shows how aspects of food intake differ across subpopulations, and

Challenges in Developing Models Describing Complex Soil Systems

NASA Astrophysics Data System (ADS)

Simunek, J.; Jacques, D.

2014-12-01

Quantitative mechanistic models that consider basic physical, mechanical, chemical, and biological processes have the potential to be powerful tools to integrate our understanding of complex soil systems, and the soil science community has often called for models that would include a large number of these diverse processes. However, once attempts have been made to develop such models, the response from the community has not always been overwhelming, especially after it discovered that these models are consequently highly complex, requiring not only a large number of parameters, not all of which can be easily (or at all) measured and/or identified, and which are often associated with large uncertainties, but also requiring from their users deep knowledge of all/most of these implemented physical, mechanical, chemical and biological processes. Real, or perceived, complexity of these models then discourages users from using them even for relatively simple applications, for which they would be perfectly adequate. Due to the nonlinear nature and chemical/biological complexity of the soil systems, it is also virtually impossible to verify these types of models analytically, raising doubts about their applicability. Code inter-comparisons, which is then likely the most suitable method to assess code capabilities and model performance, requires existence of multiple models of similar/overlapping capabilities, which may not always exist. It is thus a challenge not only to developed models describing complex soil systems, but also to persuade the soil science community in using them. As a result, complex quantitative mechanistic models are still an underutilized tool in soil science research. We will demonstrate some of the challenges discussed above on our own efforts in developing quantitative mechanistic models (such as HP1/2) for complex soil systems.

A modeling approach to describe ZVI-based anaerobic system.

PubMed

Xiao, Xiao; Sheng, Guo-Ping; Mu, Yang; Yu, Han-Qing

2013-10-15

Zero-valent iron (ZVI) is increasingly being added into anaerobic reactors to enhance the biological conversion of various less biodegradable pollutants (LBPs). Our study aimed to establish a new structure model based on the Anaerobic Digestion Model No. 1 (ADM1) to simulate such a ZVI-based anaerobic reactor. Three new processes, i.e., electron release from ZVI corrosion, H2 formation from ZVI corrosion, and transformation of LBPs, were integrated into ADM1. The established model was calibrated and tested using the experimental data from one published study, and validated using the data from another work. A good relationship between the predicted and measured results indicates that the proposed model was appropriate to describe the performance of the ZVI-based anaerobic system. Our model could provide more precise strategies for the design, development, and application of anaerobic systems especially for treating various LBPs-containing wastewaters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chromatography modelling to describe protein adsorption at bead level.

PubMed

Gerontas, Spyridon; Shapiro, Michael S; Bracewell, Daniel G

2013-04-05

Chromatographic modelling can be used to describe and further understand the behaviour of biological species during their chromatography separation on adsorption resins. Current modelling approaches assume uniform rate parameters throughout the column. Software and hardware advances now allow us to consider what can be learnt from modelling at bead level, enabling simulation of heterogeneity in bead and packed bed structure due to design or due to changes during operation. In this paper, a model has been developed to simulate at bead level protein loading in 1.5 μl microfluidic columns. This model takes into account the heterogeneity in bead sizes and the spatial variations of the characteristics of a packed bed, such as bed void fraction and dispersion, thus offering a detailed description of the flow field and mass transfer phenomena. Simulations were shown to be in good agreement with published experimental data. Copyright © 2013 Elsevier B.V. All rights reserved.

A Model Describing Stable Coherent Synchrotron Radiation in Storage Rings

NASA Astrophysics Data System (ADS)

Sannibale, F.; Byrd, J. M.; Loftsdóttir, Á.; Venturini, M.; Abo-Bakr, M.; Feikes, J.; Holldack, K.; Kuske, P.; Wüstefeld, G.; Hübers, H.-W.; Warnock, R.

2004-08-01

We present a model describing high power stable broadband coherent synchrotron radiation (CSR) in the terahertz frequency region in an electron storage ring. The model includes distortion of bunch shape from the synchrotron radiation (SR), which enhances higher frequency coherent emission, and limits to stable emission due to an instability excited by the SR wakefield. It gives a quantitative explanation of several features of the recent observations of CSR at the BESSYII storage ring. We also use this model to optimize the performance of a source for stable CSR emission.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points, the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

A Model for Describing, Analysing and Investigating Cultural Understanding in EFL Reading Settings

ERIC Educational Resources Information Center

Porto, Melina

2013-01-01

This article describes a model used to explore cultural understanding in English as a foreign language reading in a developing country, namely Argentina. The model is designed to investigate, analyse and describe EFL readers' processes of cultural understanding in a specific context. Cultural understanding in reading is typically investigated…

A model to describe potential effects of chemotherapy on critical radiobiological treatments

NASA Astrophysics Data System (ADS)

Rodríguez-Pérez, D.; Desco, M. M.; Antoranz, J. C.

2016-08-01

Although chemo- and radiotherapy can annihilate tumors on their own. they are also used in coadjuvancy: improving local effects of radiotherapy using chemotherapy as a radiosensit.izer. The effects of radiotherapy are well described by current radiobiological models. The goal of this work is to describe a discrete radiotherapy model, that has been previously used describe high radiation dose response as well as unusual radio-responses of some types of tumors (e.g. prostate cancer), to obtain a model of chemo+radiotherapy that can describe how the outcome of their combination is a more efficient removal of the tumor. Our hypothesis is that, although both treatments haven different mechanisms, both affect similar key points of cell metabolism and regulation, that lead to cellular death. Hence, we will consider a discrete model where chemotherapy may affect a fraction of the same targets destroyed by radiotherapy. Although radiotherapy reaches all cells equally, chemotherapy diffuses through a tumor attaining lower concentration in its center and higher in its surface. With our simulations we study the enhanced effect of combined therapy treatment and how it depends on the tissue critical parameters (the parameters of the lion-extensive radiobiological model), the number of “targets” aimed at by chemotherapy, and the concentration and diffusion rate of the drug inside the tumor. The results show that an equivalent, cliemo-radio-dose can be computed that allows the prediction of the lower radiation dose that causes the same effect than a radio-only treatment.

Model describing the effect of employment of the United States military in a complex emergency.

PubMed

MacMillan, Donald S

2005-01-01

The end of the Cold War vastly altered the worldwide political landscape. With the loss of a main competitor, the United States (US) military has had to adapt its strategic, operational, and tactical doctrines to an ever-increasing variety of non-traditional missions, including humanitarian operations. Complex emergencies (CEs) are defined in this paper from a political and military perspective, various factors that contribute to their development are described, and issues resulting from the employment of US military forces are discussed. A model was developed to illustrate the course of a humanitarian emergency and the potential impact of a military response. The US intervention in Haiti, Northern Iraq, Kosovo, Somalia, Bosnia, and Rwanda serve as examples. A CE develops when there is civil conflict, loss of national governmental authority, a mass population movement, and massive economic failure, each leading to a general decline in food security. The military can alleviate a CE in four ways: (1) provide security for relief efforts; (2) enforce negotiated settlements; (3) provide security for non-combatants; and/or (4) employ logistical capabilities. The model incorporates Norton and Miskel's taxonomy of identifying failing states and helps illustrate the factors that lead to a CE. The model can be used to determine if and when military intervention will have the greatest impact. The model demonstrates that early military intervention and mission assignment within the core competencies of the forces can reverse the course of a CE. Further study will be needed to verify the model.

Extended nonlinear feedback model for describing episodes of high inflation

NASA Astrophysics Data System (ADS)

Szybisz, Martín A.; Szybisz, Leszek

2017-01-01

An extension of the nonlinear feedback (NLF) formalism to describe regimes of hyper- and high-inflation in economy is proposed in the present work. In the NLF model the consumer price index (CPI) exhibits a finite time singularity of the type 1 /(tc - t) (1 - β) / β, with β > 0, predicting a blow up of the economy at a critical time tc. However, this model fails in determining tc in the case of weak hyperinflation regimes like, e.g., that occurred in Israel. To overcome this trouble, the NLF model is extended by introducing a parameter γ, which multiplies all terms with past growth rate index (GRI). In this novel approach the solution for CPI is also analytic being proportional to the Gaussian hypergeometric function 2F1(1 / β , 1 / β , 1 + 1 / β ; z) , where z is a function of β, γ, and tc. For z → 1 this hypergeometric function diverges leading to a finite time singularity, from which a value of tc can be determined. This singularity is also present in GRI. It is shown that the interplay between parameters β and γ may produce phenomena of multiple equilibria. An analysis of the severe hyperinflation occurred in Hungary proves that the novel model is robust. When this model is used for examining data of Israel a reasonable tc is got. High-inflation regimes in Mexico and Iceland, which exhibit weaker inflations than that of Israel, are also successfully described.

Transferable atomistic model to describe the energetics of zirconia

NASA Astrophysics Data System (ADS)

Wilson, Mark; Schönberger, Uwe; Finnis, Michael W.

1996-10-01

We have investigated the energies of a number of phases of ZrO2 using models of an increasing degree of sophistication: the simple ionic model, the polarizable ion model, the compressible ion model, and finally a model including quadrupole polarizability of the oxygen ions. The three structures which are observed with increasing temperatures are monoclinic, tetragonal, and cubic (fluorite). Besides these we have studied some hypothetical structures which certain potentials erroneously predict or which occur in other oxides with this stoichiometry, e.g., the α-PbO2 structure and rutile. We have also performed ab initio density functional calculations with the full-potential linear combination of muffin-tin orbitals method to investigate the cubic-tetragonal distortion. A detailed comparison is made between the results using classical potentials, the experimental data, and our own and other ab initio results. The factors which stabilize the various structure are analyzed. We find the only genuinely transferable model is the one including compressible ions and anion polarizability to the quadrupole level.

Can the three pore model correctly describe peritoneal transport of protein?

PubMed

Waniewski, Jacek; Poleszczuk, Jan; Antosiewicz, Stefan; Baczynński, Daniel; Gałach, Magda; Pietribiasi, Mauro; Wanńkowicz, Zofia

2014-01-01

The three pore model (3PM) includes large pores for the description of protein leak to the peritoneal cavity during peritoneal dialysis. However, the reliability of this description has been not fully tested against clinical data yet. Peritoneal transport parameters were estimated using 3PM, extended 3p model (with estimation of fraction of large pores, ext3PM), ext3PM with modified size of pores and proteins (mext3PM), and simplified two pore (2PM, small and ultrasmall pores) models for 32 patients on peritoneal dialysis investigated using the sequential peritoneal equilibration test (consecutive peritoneal equilibration test [PET]: glucose 2.27%, 4 h, and miniPET: glucose 3.86%, 1 h). Urea, creatinine, glucose, sodium, phosphate, albumin, and IgM concentrations were measured in dialysis fluid and plasma. Ext3PM and mext3PM, with large pore fraction of about 0.14, provided a good description of fluid and small solute kinetics, but their predictions for albumin transport were less accurate. Two pore model precisely described the data on fluid and small solute transport. The 3p models could not describe the diffusive-convective transport of albumin as precisely as the transport of fluid, small solutes, and IgM. The 2p model (not applicable for proteins) was an efficient tool for modeling fluid and small solute transport.

Classroom Factors Affecting Students: Self-Evaluation: An Interactional Model.

ERIC Educational Resources Information Center

Marshall, Hermine H.; Weinstein, Rhona S.

1984-01-01

A complex interactional model of classroom factors that contribute to the development of students' self-evaluations is presented. Factors described are: (1) task structure; (2) grouping practices; (3) feedback and evaluation procedures and information about ability; (4) motivational strategies; (5) locus of responsibility for learning; and (6) the…

The remarkable ability of turbulence model equations to describe transition

NASA Technical Reports Server (NTRS)

Wilcox, David C.

1992-01-01

This paper demonstrates how well the k-omega turbulence model describes the nonlinear growth of flow instabilities from laminar flow into the turbulent flow regime. Viscous modifications are proposed for the k-omega model that yield close agreement with measurements and with Direct Numerical Simulation results for channel and pipe flow. These modifications permit prediction of subtle sublayer details such as maximum dissipation at the surface, k approximately y(exp 2) as y approaches 0, and the sharp peak value of k near the surface. With two transition specific closure coefficients, the model equations accurately predict transition for an incompressible flat-plate boundary layer. The analysis also shows why the k-epsilon model is so difficult to use for predicting transition.

Photometric model of diffuse surfaces described as a distribution of interfaced Lambertian facets.

PubMed

Simonot, Lionel

2009-10-20

The Lambertian model for diffuse reflection is widely used for the sake of its simplicity. Nevertheless, this model is known to be inaccurate in describing a lot of real-world objects, including those that present a matte surface. To overcome this difficulty, we propose a photometric model where the surfaces are described as a distribution of facets where each facet consists of a flat interface on a Lambertian background. Compared to the Lambertian model, it includes two additional physical parameters: an interface roughness parameter and the ratio between the refractive indices of the background binder and of the upper medium. The Torrance-Sparrow model--distribution of strictly specular facets--and the Oren-Nayar model--distribution of strictly Lambertian facets--appear as special cases.

A hybrid model describing ion induced kinetic electron emission

NASA Astrophysics Data System (ADS)

Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.

2015-06-01

We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.

A physiology-based model describing heterogeneity in glucose metabolism: the core of the Eindhoven Diabetes Education Simulator (E-DES).

PubMed

Maas, Anne H; Rozendaal, Yvonne J W; van Pul, Carola; Hilbers, Peter A J; Cottaar, Ward J; Haak, Harm R; van Riel, Natal A W

2015-03-01

Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control. © 2014 Diabetes Technology Society.

Modelling oxygen transfer using dynamic alpha factors.

PubMed

Jiang, Lu-Man; Garrido-Baserba, Manel; Nolasco, Daniel; Al-Omari, Ahmed; DeClippeleir, Haydee; Murthy, Sudhir; Rosso, Diego

2017-11-01

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diffusion model to describe osteogenesis within a porous titanium scaffold.

PubMed

Schmitt, M; Allena, R; Schouman, T; Frasca, S; Collombet, J M; Holy, X; Rouch, P

2016-01-01

In this study, we develop a two-dimensional finite element model, which is derived from an animal experiment and allows simulating osteogenesis within a porous titanium scaffold implanted in ewe's hemi-mandible during 12 weeks. The cell activity is described through diffusion equations and regulated by the stress state of the structure. We compare our model to (i) histological observations and (ii) experimental data obtained from a mechanical test done on sacrificed animal. We show that our mechano-biological approach provides consistent numerical results and constitutes a useful tool to predict osteogenesis pattern.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

The stay/switch model describes choice among magnitudes of reinforcers.

PubMed

MacDonall, James S

2008-06-01

The stay/switch model is an alternative to the generalized matching law for describing choice in concurrent procedures. The purpose of the present experiment was to extend this model to choice among magnitudes of reinforcers. Rats were exposed to conditions in which the magnitude of reinforcers (number of food pellets) varied for staying at alternative 1, switching from alternative 1, staying at alternative 2 and switching from alternative 2. A changeover delay was not used. The results showed that the stay/switch model provided a good account of the data overall, and deviations from fits of the generalized matching law to response allocation data were in the direction predicted by the stay/switch model. In addition, comparisons among specific conditions suggested that varying the ratio of obtained reinforcers, as in the generalized matching law, was not necessary to change the response and time allocations. Other comparisons suggested that varying the ratio of obtained reinforcers was not sufficient to change response allocation. Taken together these results provide additional support for the stay/switch model of concurrent choice.

Numerical model describing optimization of fibres winding process on open and closed frame

NASA Astrophysics Data System (ADS)

Petrů, M.; Mlýnek, J.; Martinec, T.

2016-08-01

This article discusses a numerical model describing optimization of fibres winding process on open and closed frame. The quality production of said type of composite frame depends primarily on the correct winding of fibers on a polyurethane core. It is especially needed to ensure the correct angles of the fibers winding on the polyurethane core and the homogeneity of individual winding layers. The article describes mathematical model for use an industrial robot in filament winding and how to calculate the trajectory of the robot. When winding fibers on the polyurethane core which is fastened to the robot-end-effector so that during the winding process goes through a fibre-processing head on the basis of the suitably determined robot-end-effector trajectory. We use the described numerical model and matrix calculus to enumerate the trajectory of the robot-end-effector to determine the desired passage of the frame through the fibre-processing head. The calculation of the trajectory was programmed in the Delphi development environment. Relations of the numerical model are important for use a real solving of the passage of a polyurethane core through fibre-processing head.

NOVEL MODEL DESCRIBING TRACE METAL CONCENTRATIONS IN THE EARTHWORM, EISENIA ANDREI

EPA Science Inventory

We developed a novel model describing Eisenia andrei body concentrations for Cd, Cu, Pb, and Zn as a function of pH, metals, and soluble organic carbon (SOC) in soil extracts for potential use in predicting values in contaminated field sites. Data from 17 moderately contaminated ...

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

An extended car-following model to describe connected traffic dynamics under cyberattacks

NASA Astrophysics Data System (ADS)

Wang, Pengcheng; Yu, Guizhen; Wu, Xinkai; Qin, Hongmao; Wang, Yunpeng

2018-04-01

In this paper, the impacts of the potential cyberattacks on vehicles are modeled through an extended car-following model. To better understand the mechanism of traffic disturbance under cyberattacks, the linear and nonlinear stability analysis are conducted respectively. Particularly, linear stability analysis is performed to obtain different neutral stability conditions with various parameters; and nonlinear stability analysis is carried out by using reductive perturbation method to derive the soliton solution of the modified Korteweg de Vries equation (mKdV) near the critical point, which is used to draw coexisting stability lines. Furthermore, by applying linear and nonlinear stability analysis, traffic flow state can be divided into three states, i.e., stable, metastable and unstable states which are useful to describe shockwave dynamics and driving behaviors under cyberattacks. The theoretical results show that the proposed car-following model is capable of successfully describing the car-following behavior of connected vehicles with cyberattacks. Finally, numerical simulation using real values has confirmed the validity of theoretical analysis. The results further demonstrate our model can be used to help avoid collisions and relieve traffic congestion with cybersecurity threats.

Kinetics model for initiation and promotion for describing tumor prevalence from HZE radiation

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Wilson, John W.

1994-01-01

A kinetics model for cellular repair and misrepair for multiple radiation-induced lesions (mutation-inactivation) is coupled to a two-mutation model of initiation and promotion in tissue to provide a parametric description of tumor prevalence in the Harderian gland in a mouse. Dose-response curves are described for gamma-rays and relativistic ions. The effects of nuclear fragmentation are also considered for high-energy proton and alpha particle exposures The model described provides a parametric description of age-dependent cancer induction for a wide range of radiation fields. We also consider the two hypotheses that radiation acts either solely as an initiator or as both initiator and promoter and make model calculations for fractionation exposures from gamma-rays and relativistic Fe ions. For fractionated Fe exposures, an inverse dose-rate effect is provided by a promotion hypothesis using a mutation rate for promotion typical of single-gene mutations.

A mathematical model describes the malignant transformation of low grade gliomas: Prognostic implications.

PubMed

Bogdańska, Magdalena U; Bodnar, Marek; Piotrowska, Monika J; Murek, Michael; Schucht, Philippe; Beck, Jürgen; Martínez-González, Alicia; Pérez-García, Víctor M

2017-01-01

Gliomas are the most frequent type of primary brain tumours. Low grade gliomas (LGGs, WHO grade II gliomas) may grow very slowly for the long periods of time, however they inevitably cause death due to the phenomenon known as the malignant transformation. This refers to the transition of LGGs to more aggressive forms of high grade gliomas (HGGs, WHO grade III and IV gliomas). In this paper we propose a mathematical model describing the spatio-temporal transition of LGGs into HGGs. Our modelling approach is based on two cellular populations with transitions between them being driven by the tumour microenvironment transformation occurring when the tumour cell density grows beyond a critical level. We show that the proposed model describes real patient data well. We discuss the relationship between patient prognosis and model parameters. We approximate tumour radius and velocity before malignant transformation as well as estimate the onset of this process.

Describing, using 'recognition cones'. [parallel-series model with English-like computer program

NASA Technical Reports Server (NTRS)

Uhr, L.

1973-01-01

A parallel-serial 'recognition cone' model is examined, taking into account the model's ability to describe scenes of objects. An actual program is presented in an English-like language. The concept of a 'description' is discussed together with possible types of descriptive information. Questions regarding the level and the variety of detail are considered along with approaches for improving the serial representations of parallel systems.

Hypothesized kinetic models for describing the growth of globular and encrusting demosponges.

PubMed

Sipkema, Detmer; Yosef, Nejla A M; Adamczewski, Marcin; Osinga, Ronald; Mendola, Dominick; Tramper, Johannes; Wijffels, René H

2006-01-01

The marine sponges Dysidea avara and Chondrosia reniformis (globular forms) were cultured in the laboratory on a diet of viable Phaeodactylum tricornutum cells and dissolved nutrients (algae and fish powders). Our growth data were combined with literature data for Pseudosuberites andrewsi (a globular sponge) and for the encrusting sponges Oscarella lobularis, Hemimycale columella, and Crambe crambe. The suitability of three growth models-linear, exponential, and radial accretive-for describing the growth of globular and encrusting sponges was assessed. Radial accretive growth was determined to be the best model to describe growth of both encrusting and globular sponges. Average growth rates of 0.051+/-0.016 and 0.019+/-0.003 mm/day (calculated as the increase of the radius of the sponge per day) were obtained experimentally for D. avara and C. reniformis, respectively.

Fitting mathematical models to describe the rheological behaviour of chocolate pastes

NASA Astrophysics Data System (ADS)

Barbosa, Carla; Diogo, Filipa; Alves, M. Rui

2016-06-01

The flow behavior is of utmost importance for the chocolate industry. The objective of this work was to study two mathematical models, Casson and Windhab models that can be used to fit chocolate rheological data and evaluate which better infers or previews the rheological behaviour of different chocolate pastes. Rheological properties (viscosity, shear stress and shear rates) were obtained with a rotational viscometer equipped with a concentric cylinder. The chocolate samples were white chocolate and chocolate with varying percentages in cacao (55%, 70% and 83%). The results showed that the Windhab model was the best to describe the flow behaviour of all the studied samples with higher determination coefficients (r2 > 0.9).

Comparison of different two-pathway models for describing the combined effect of DO and nitrite on the nitrous oxide production by ammonia-oxidizing bacteria.

PubMed

Lang, Longqi; Pocquet, Mathieu; Ni, Bing-Jie; Yuan, Zhiguo; Spérandio, Mathieu

2017-02-01

The aim of this work is to compare the capability of two recently proposed two-pathway models for predicting nitrous oxide (N 2 O) production by ammonia-oxidizing bacteria (AOB) for varying ranges of dissolved oxygen (DO) and nitrite. The first model includes the electron carriers whereas the second model is based on direct coupling of electron donors and acceptors. Simulations are confronted to extensive sets of experiments (43 batches) from different studies with three different microbial systems. Despite their different mathematical structures, both models could well and similarly describe the combined effect of DO and nitrite on N 2 O production rate and emission factor. The model-predicted contributions for nitrifier denitrification pathway and hydroxylamine pathway also matched well with the available isotopic measurements. Based on sensitivity analysis, calibration procedures are described and discussed for facilitating the future use of those models.

An Evolving Framework for Describing Student Engagement in Classroom Activities

ERIC Educational Resources Information Center

Azevedo, Flavio S.; diSessa, Andrea A.; Sherin, Bruce L.

2012-01-01

Student engagement in classroom activities is usually described as a function of factors such as human needs, affect, intention, motivation, interests, identity, and others. We take a different approach and develop a framework that models classroom engagement as a function of students' "conceptual competence" in the "specific content" (e.g., the…

Using the MWC model to describe heterotropic interactions in hemoglobin

PubMed Central

Rapp, Olga

2017-01-01

Hemoglobin is a classical model allosteric protein. Research on hemoglobin parallels the development of key cooperativity and allostery concepts, such as the ‘all-or-none’ Hill formalism, the stepwise Adair binding formulation and the concerted Monod-Wymann-Changuex (MWC) allosteric model. While it is clear that the MWC model adequately describes the cooperative binding of oxygen to hemoglobin, rationalizing the effects of H+, CO2 or organophosphate ligands on hemoglobin-oxygen saturation using the same model remains controversial. According to the MWC model, allosteric ligands exert their effect on protein function by modulating the quaternary conformational transition of the protein. However, data fitting analysis of hemoglobin oxygen saturation curves in the presence or absence of inhibitory ligands persistently revealed effects on both relative oxygen affinity (c) and conformational changes (L), elementary MWC parameters. The recent realization that data fitting analysis using the traditional MWC model equation may not provide reliable estimates for L and c thus calls for a re-examination of previous data using alternative fitting strategies. In the current manuscript, we present two simple strategies for obtaining reliable estimates for MWC mechanistic parameters of hemoglobin steady-state saturation curves in cases of both evolutionary and physiological variations. Our results suggest that the simple MWC model provides a reasonable description that can also account for heterotropic interactions in hemoglobin. The results, moreover, offer a general roadmap for successful data fitting analysis using the MWC model. PMID:28793329

A theoretical model to describe progressions and regressions for exercise rehabilitation.

PubMed

Blanchard, Sam; Glasgow, Phil

2014-08-01

This article aims to describe a new theoretical model to simplify and aid visualisation of the clinical reasoning process involved in progressing a single exercise. Exercise prescription is a core skill for physiotherapists but is an area that is lacking in theoretical models to assist clinicians when designing exercise programs to aid rehabilitation from injury. Historical models of periodization and motor learning theories lack any visual aids to assist clinicians. The concept of the proposed model is that new stimuli can be added or exchanged with other stimuli, either intrinsic or extrinsic to the participant, in order to gradually progress an exercise whilst remaining safe and effective. The proposed model maintains the core skills of physiotherapists by assisting clinical reasoning skills, exercise prescription and goal setting. It is not limited to any one pathology or rehabilitation setting and can adapted by any level of skilled clinician. Copyright © 2014 Elsevier Ltd. All rights reserved.

INCAS: an analytical model to describe displacement cascades

NASA Astrophysics Data System (ADS)

Jumel, Stéphanie; Claude Van-Duysen, Jean

2004-07-01

REVE (REactor for Virtual Experiments) is an international project aimed at developing tools to simulate neutron irradiation effects in Light Water Reactor materials (Fe, Ni or Zr-based alloys). One of the important steps of the project is to characterise the displacement cascades induced by neutrons. Accordingly, the Department of Material Studies of Electricité de France developed an analytical model based on the binary collision approximation. This model, called INCAS (INtegration of CAScades), was devised to be applied on pure elements; however, it can also be used on diluted alloys (reactor pressure vessel steels, etc.) or alloys composed of atoms with close atomic numbers (stainless steels, etc.). INCAS describes displacement cascades by taking into account the nuclear collisions and electronic interactions undergone by the moving atoms. In particular, it enables to determine the mean number of sub-cascades induced by a PKA (depending on its energy) as well as the mean energy dissipated in each of them. The experimental validation of INCAS requires a large effort and could not be carried out in the framework of the study. However, it was verified that INCAS results are in conformity with those obtained from other approaches. As a first application, INCAS was applied to determine the sub-cascade spectrum induced in iron by the neutron spectrum corresponding to the central channel of the High Flux Irradiation Reactor of Oak Ridge National Laboratory.

Using concept maps to describe undergraduate students’ mental model in microbiology course

NASA Astrophysics Data System (ADS)

Hamdiyati, Y.; Sudargo, F.; Redjeki, S.; Fitriani, A.

2018-05-01

The purpose of this research was to describe students’ mental model in a mental model based-microbiology course using concept map as assessment tool. Respondents were 5th semester of undergraduate students of Biology Education of Universitas Pendidikan Indonesia. The mental modelling instrument used was concept maps. Data were taken on Bacteria sub subject. A concept map rubric was subsequently developed with a maximum score of 4. Quantitative data was converted into a qualitative one to determine mental model level, namely: emergent = score 1, transitional = score 2, close to extended = score 3, and extended = score 4. The results showed that mental model level on bacteria sub subject before the implementation of mental model based-microbiology course was at the transitional level. After implementation of mental model based-microbiology course, mental model was at transitional level, close to extended, and extended. This indicated an increase in the level of students’ mental model after the implementation of mental model based-microbiology course using concept map as assessment tool.

Describing team development within a novel GP-led urgent care centre model: a qualitative study.

PubMed

Morton, Sarah; Ignatowicz, Agnieszka; Gnani, Shamini; Majeed, Azeem; Greenfield, Geva

2016-06-23

Urgent care centres (UCCs) co-located within an emergency department were developed to reduce the numbers of inappropriate emergency department admissions. Since then various UCC models have developed, including a novel general practitioner (GP)-led UCC that incorporates both GPs and emergency nurse practitioners (ENPs). Traditionally these two groups do not work alongside each other within an emergency setting. Although good teamwork is crucial to better patient outcomes, there is little within the literature about the development of a team consisting of different healthcare professionals in a novel healthcare setting. Our aim was therefore to describe staff members' perspectives of team development within the GP-led UCC model. Open-ended semistructured interviews, analysed using thematic content analysis. GP-led urgent care centres in two academic teaching hospitals in London. 15 UCC staff members including six GPs, four ENPs, two receptionists and three managers. Overall participants were positive about the interprofessional team that had developed and recognised that this process had taken time. Hierarchy within the UCC setting has diminished with time, although some residual hierarchical beliefs do appear to remain. Staff appreciated interdisciplinary collaboration was likely to improve patient care. Eight key facilitating factors for the team were identified: appointment of leaders, perception of fair workload, education on roles/skill sets and development of these, shared professional understanding, interdisciplinary working, ED collaboration, clinical guidelines and social interactions. A strong interprofessional team has evolved within the GP-led UCCs over time, breaking down traditional professional divides. Future implementation of UCC models should pro-actively incorporate the eight facilitating factors identified from the outset, to enable effective teams to develop more quickly. Published by the BMJ Publishing Group Limited. For permission to use

A novel model incorporating two variability sources for describing motor evoked potentials

PubMed Central

Goetz, Stefan M.; Luber, Bruce; Lisanby, Sarah H.; Peterchev, Angel V.

2014-01-01

Objective Motor evoked potentials (MEPs) play a pivotal role in transcranial magnetic stimulation (TMS), e.g., for determining the motor threshold and probing cortical excitability. Sampled across the range of stimulation strengths, MEPs outline an input–output (IO) curve, which is often used to characterize the corticospinal tract. More detailed understanding of the signal generation and variability of MEPs would provide insight into the underlying physiology and aid correct statistical treatment of MEP data. Methods A novel regression model is tested using measured IO data of twelve subjects. The model splits MEP variability into two independent contributions, acting on both sides of a strong sigmoidal nonlinearity that represents neural recruitment. Traditional sigmoidal regression with a single variability source after the nonlinearity is used for comparison. Results The distribution of MEP amplitudes varied across different stimulation strengths, violating statistical assumptions in traditional regression models. In contrast to the conventional regression model, the dual variability source model better described the IO characteristics including phenomena such as changing distribution spread and skewness along the IO curve. Conclusions MEP variability is best described by two sources that most likely separate variability in the initial excitation process from effects occurring later on. The new model enables more accurate and sensitive estimation of the IO curve characteristics, enhancing its power as a detection tool, and may apply to other brain stimulation modalities. Furthermore, it extracts new information from the IO data concerning the neural variability—information that has previously been treated as noise. PMID:24794287

A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption.

PubMed

Sharabi, Shirley; Kos, Bor; Last, David; Guez, David; Daniels, Dianne; Harnof, Sagi; Mardor, Yael; Miklavcic, Damijan

2016-03-01

Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending beyond IRE, thus enabling efficient drug penetration. The main objective of this study was to develop a statistical model predicting cell death and BBB disruption induced by electroporation. This model can be used for individual treatment planning. Cell death and BBB disruption models were developed based on the Peleg-Fermi model in combination with numerical models of the electric field. The model calculates the electric field thresholds for cell kill and BBB disruption and describes the dependence on the number of treatment pulses. The model was validated using in vivo experimental data consisting of rats brains MRIs post electroporation treatments. Linear regression analysis confirmed that the model described the IRE and BBB disruption volumes as a function of treatment pulses number (r(2) = 0.79; p < 0.008, r(2) = 0.91; p < 0.001). The results presented a strong plateau effect as the pulse number increased. The ratio between complete cell death and no cell death thresholds was relatively narrow (between 0.88-0.91) even for small numbers of pulses and depended weakly on the number of pulses. For BBB disruption, the ratio increased with the number of pulses. BBB disruption radii were on average 67% ± 11% larger than IRE volumes. The statistical model can be used to describe the dependence of treatment-effects on the number of pulses independent of the experimental setup.

A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption

PubMed Central

Sharabi, Shirley; Kos, Bor; Last, David; Guez, David; Daniels, Dianne; Harnof, Sagi; Miklavcic, Damijan

2016-01-01

Background Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending beyond IRE, thus enabling efficient drug penetration. The main objective of this study was to develop a statistical model predicting cell death and BBB disruption induced by electroporation. This model can be used for individual treatment planning. Material and methods Cell death and BBB disruption models were developed based on the Peleg-Fermi model in combination with numerical models of the electric field. The model calculates the electric field thresholds for cell kill and BBB disruption and describes the dependence on the number of treatment pulses. The model was validated using in vivo experimental data consisting of rats brains MRIs post electroporation treatments. Results Linear regression analysis confirmed that the model described the IRE and BBB disruption volumes as a function of treatment pulses number (r2 = 0.79; p < 0.008, r2 = 0.91; p < 0.001). The results presented a strong plateau effect as the pulse number increased. The ratio between complete cell death and no cell death thresholds was relatively narrow (between 0.88-0.91) even for small numbers of pulses and depended weakly on the number of pulses. For BBB disruption, the ratio increased with the number of pulses. BBB disruption radii were on average 67% ± 11% larger than IRE volumes. Conclusions The statistical model can be used to describe the dependence of treatment-effects on the number of pulses independent of the experimental setup. PMID:27069447

Ordinal regression models to describe tourist satisfaction with Sintra's world heritage

NASA Astrophysics Data System (ADS)

Mouriño, Helena

2013-10-01

In Tourism Research, ordinal regression models are becoming a very powerful tool in modelling the relationship between an ordinal response variable and a set of explanatory variables. In August and September 2010, we conducted a pioneering Tourist Survey in Sintra, Portugal. The data were obtained by face-to-face interviews at the entrances of the Palaces and Parks of Sintra. The work developed in this paper focus on two main points: tourists' perception of the entrance fees; overall level of satisfaction with this heritage site. For attaining these goals, ordinal regression models were developed. We concluded that tourist's nationality was the only significant variable to describe the perception of the admission fees. Also, Sintra's image among tourists depends not only on their nationality, but also on previous knowledge about Sintra's World Heritage status.

The mathematical research for the Kuramoto model of the describing neuronal synchrony in the brain

NASA Astrophysics Data System (ADS)

Lin, Chang; Lin, Mai-mai

2009-08-01

The Kuramoto model of the describing neuronal synchrony is mathematically investigated in the brain. A general analytical solutions (the most sententious description) for the Kuramoto model, incorporating the inclusion of a Ki,j (t) term to represent time-varying coupling strengths, have been obtained by using the precise mathematical approach. We derive an exact analytical expression, opening out the connotative and latent linear relation, for the mathematical character of the phase configurations in the Kuramoto model of the describing neuronal synchrony in the brain.

Communication skills training: describing a new conceptual model.

PubMed

Brown, Richard F; Bylund, Carma L

2008-01-01

Current research in communication in physician-patient consultations is multidisciplinary and multimethodological. As this research has progressed, a considerable body of evidence on the best practices in physician-patient communication has been amassed. This evidence provides a foundation for communication skills training (CST) at all levels of medical education. Although the CST literature has demonstrated that communication skills can be taught, one critique of this literature is that it is not always clear which skills are being taught and whether those skills are matched with those being assessed. The Memorial Sloan-Kettering Cancer Center Comskil Model for CST seeks to answer those critiques by explicitly defining the important components of a consultation, based on Goals, Plans, and Actions theories and sociolinguistic theory. Sequenced guidelines as a mechanism for teaching about particular communication challenges are adapted from these other methods. The authors propose that consultation communication can be guided by an overarching goal, which is achieved through the use of a set of predetermined strategies. Strategies are common in CST; however, strategies often contain embedded communication skills. These skills can exist across strategies, and the Comskil Model seeks to make them explicit in these contexts. Separate from the skills are process tasks and cognitive appraisals that need to be addressed in teaching. The authors also describe how assessment practices foster concordance between skills taught and those assessed through careful coding of trainees' communication encounters and direct feedback.

Parameter estimation in a human operator describing function model for a two-dimensional tracking task

NASA Technical Reports Server (NTRS)

Vanlunteren, A.

1977-01-01

A previously described parameter estimation program was applied to a number of control tasks, each involving a human operator model consisting of more than one describing function. One of these experiments is treated in more detail. It consisted of a two dimensional tracking task with identical controlled elements. The tracking errors were presented on one display as two vertically moving horizontal lines. Each loop had its own manipulator. The two forcing functions were mutually independent and consisted each of 9 sine waves. A human operator model was chosen consisting of 4 describing functions, thus taking into account possible linear cross couplings. From the Fourier coefficients of the relevant signals the model parameters were estimated after alignment, averaging over a number of runs and decoupling. The results show that for the elements in the main loops the crossover model applies. A weak linear cross coupling existed with the same dynamics as the elements in the main loops but with a negative sign.

Describing complex cells in primary visual cortex: a comparison of context and multi-filter LN models.

PubMed

Westö, Johan; May, Patrick J C

2018-05-02

Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multi-filter linear-nonlinear (LN) models and context models. Models are, however, never correct and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: First, we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions. Second, we evaluate context models and multi-filter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multi-filter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multi-filter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior.

An algorithm to detect and communicate the differences in computational models describing biological systems.

PubMed

Scharm, Martin; Wolkenhauer, Olaf; Waltemath, Dagmar

2016-02-15

Repositories support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available in repositories, such as the BioModels database or the Physiome Model Repository, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection not only allows users to study the history of models but also helps in the detection of errors and inconsistencies. Existing repositories lack algorithms to track a model's development over time. Focusing on SBML and CellML, we present an algorithm to accurately detect and describe differences between coexisting versions of a model with respect to (i) the models' encoding, (ii) the structure of biological networks and (iii) mathematical expressions. This algorithm is implemented in a comprehensive and open source library called BiVeS. BiVeS helps to identify and characterize changes in computational models and thereby contributes to the documentation of a model's history. Our work facilitates the reuse and extension of existing models and supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance. The workflow described in this article is implemented in BiVeS. BiVeS is freely available as source code and binary from sems.uni-rostock.de. The web interface BudHat demonstrates the capabilities of BiVeS at budhat.sems.uni-rostock.de. © The Author 2015. Published by Oxford University Press.

Describing litho-constrained layout by a high-resolution model filter

NASA Astrophysics Data System (ADS)

Tsai, Min-Chun

2008-05-01

A novel high-resolution model (HRM) filtering technique was proposed to describe litho-constrained layouts. Litho-constrained layouts are layouts that have difficulties to pattern or are highly sensitive to process-fluctuations under current lithography technologies. HRM applies a short-wavelength (or high NA) model simulation directly on the pre-OPC, original design layout to filter out low spatial-frequency regions, and retain high spatial-frequency components which are litho-constrained. Since no OPC neither mask-synthesis steps are involved, this new technique is highly efficient in run time and can be used in design stage to detect and fix litho-constrained patterns. This method has successfully captured all the hot-spots with less than 15% overshoots on a realistic 80 mm2 full-chip M1 layout in 65nm technology node. A step by step derivation of this HRM technique is presented in this paper.

Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

USGS Publications Warehouse

Woodward, Andrea; Torregrosa, Alicia; Madej, Mary Ann; Reichmuth, Michael; Fong, Darren

2014-01-01

The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a

FACTOR ANALYTIC MODELS OF CLUSTERED MULTIVARIATE DATA WITH INFORMATIVE CENSORING

EPA Science Inventory

This paper describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censorin...

Application of describing function analysis to a model of deep brain stimulation.

PubMed

Davidson, Clare Muireann; de Paor, Annraoi M; Lowery, Madeleine M

2014-03-01

Deep brain stimulation effectively alleviates motor symptoms of medically refractory Parkinson's disease, and also relieves many other treatment-resistant movement and affective disorders. Despite its relative success as a treatment option, the basis of its efficacy remains elusive. In Parkinson's disease, increased functional connectivity and oscillatory activity occur within the basal ganglia as a result of dopamine loss. A correlative relationship between pathological oscillatory activity and the motor symptoms of the disease, in particular bradykinesia, rigidity, and tremor, has been established. Suppression of the oscillations by either dopamine replacement or DBS also correlates with an improvement in motor symptoms. DBS parameters are currently chosen empirically using a "trial and error" approach, which can be time-consuming and costly. The work presented here amalgamates concepts from theories of neural network modeling with nonlinear control engineering to describe and analyze a model of synchronous neural activity and applied stimulation. A theoretical expression for the optimum stimulation parameters necessary to suppress oscillations is derived. The effect of changing stimulation parameters (amplitude and pulse duration) on induced oscillations is studied in the model. Increasing either stimulation pulse duration or amplitude enhanced the level of suppression. The predicted parameters were found to agree well with clinical measurements reported in the literature for individual patients. It is anticipated that the simplified model described may facilitate the development of protocols to aid optimum stimulation parameter choice on a patient by patient basis.

An extended model based on the modified Nernst-Planck equation for describing transdermal iontophoresis of weak electrolytes.

PubMed

Imanidis, Georgios; Luetolf, Peter

2006-07-01

An extended model for iontophoretic enhancement of transdermal drug permeation under constant voltage is described based on the previously modified Nernst-Planck equation, which included the effect of convective solvent flow. This model resulted in an analytical expression for the enhancement factor as a function of applied voltage, convective flow velocity due to electroosmosis, ratio of lipid to aqueous pathway passive permeability, and weighted average net ionic valence of the permeant in the aqueous epidermis domain. The shift of pH in the epidermis compared to bulk caused by the electrical double layer at the lipid-aqueous domain interface was evaluated using the Poisson-Boltzmann equation. This was solved numerically for representative surface charge densities and yielded pH differences between bulk and epidermal aqueous domain between 0.05 and 0.4 pH units. The developed model was used to analyze the experimental enhancement of an amphoteric weak electrolyte measured in vitro using human cadaver epidermis and a voltage of 250 mV at different pH values. Parameter values characterizing the involved factors were determined that yielded the experimental enhancement factors and passive permeability coefficients at all pH values. The model provided a very good agreement between experimental and calculated enhancement and passive permeability. The deduced parameters showed (i) that the pH shift in the aqueous permeation pathway had a notable effect on the ionic valence and the partitioning of the drug in this domain for a high surface charge density and depending on the pK(a) and pI of the drug in relation to the bulk pH; (ii) the magnitude and the direction of convective transport due to electroosmosis typically reflected the density and sign, respectively, of surface charge of the tissue and its effect on enhancement was substantial for bulk pH values differing from the pI of epidermal tissue; (iii) the aqueous pathway predominantly determined passive

A conceptual model of factors contributing to the development of muscle dysmorphia.

PubMed

Grieve, Frederick G

2007-01-01

Muscle dysmorphia is a recently described subcategory of Body Dysmorphic Disorder. It is most prevalent in males and has a number of cognitive, behavioral, socioenviornmental, emotional, and psychological factors that influence its expression. An etiological model describing these influences is presented for evaluation. Nine variables (body mass, media influences, ideal body internalization, low self-esteem, body dissatisfaction, health locus of control, negative affect, perfectionism, and body distortion) were identified through the use of extant literature on muscle dysmorphia and through extrapolation from literature involving women and eating disorders. The functional relationships among these variables are described and implications of the model are discussed.

Using a model comparison approach to describe the assembly pathway for histone H1

PubMed Central

Contreras, Carlos; Villasana, Minaya; Hendzel, Michael J.

2018-01-01

Histones H1 or linker histones are highly dynamic proteins that diffuse throughout the cell nucleus and associate with chromatin (DNA and associated proteins). This binding interaction of histone H1 with the chromatin is thought to regulate chromatin organization and DNA accessibility to transcription factors and has been proven to involve a kinetic process characterized by a population that associates weakly with chromatin and rapidly dissociates and another population that resides at a binding site for up to several minutes before dissociating. When considering differences between these two classes of interactions in a mathematical model for the purpose of describing and quantifying the dynamics of histone H1, it becomes apparent that there could be several assembly pathways that explain the kinetic data obtained in living cells. In this work, we model these different pathways using systems of reaction-diffusion equations and carry out a model comparison analysis using FRAP (fluorescence recovery after photobleaching) experimental data from different histone H1 variants to determine the most feasible mechanism to explain histone H1 binding to chromatin. The analysis favors four different chromatin assembly pathways for histone H1 which share common features and provide meaningful biological information on histone H1 dynamics. We show, using perturbation analysis, that the explicit consideration of high- and low-affinity associations of histone H1 with chromatin in the favored assembly pathways improves the interpretation of histone H1 experimental FRAP data. To illustrate the results, we use one of the favored models to assess the kinetic changes of histone H1 after core histone hyperacetylation, and conclude that this post-transcriptional modification does not affect significantly the transition of histone H1 from a weakly bound state to a tightly bound state. PMID:29352283

Smart Frameworks and Self-Describing Models: Model Metadata for Automated Coupling of Hydrologic Process Components (Invited)

NASA Astrophysics Data System (ADS)

Peckham, S. D.

2013-12-01

Model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that allow heterogeneous sets of process models to be assembled in a plug-and-play manner to create composite "system models". These mechanisms facilitate code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers, e.g. by requiring them to provide their output in specific forms that meet the input requirements of other models. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can compare the answers to these queries with similar answers from other process models in a collection and then automatically call framework

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity

NASA Astrophysics Data System (ADS)

Sadilek, Maximilian; Thurner, Stefan

2015-05-01

We derive a two-layer multiplex Kuramoto model from Wilson-Cowan type physiological equations that describe neural activity on a network of interconnected cortical regions. This is mathematically possible due to the existence of a unique, stable limit cycle, weak coupling, and inhibitory synaptic time delays. We study the phase diagram of this model numerically as a function of the inter-regional connection strength that is related to cerebral blood flow, and a phase shift parameter that is associated with synaptic GABA concentrations. We find three macroscopic phases of cortical activity: background activity (unsynchronized oscillations), epileptiform activity (highly synchronized oscillations) and resting-state activity (synchronized clusters/chaotic behaviour). Previous network models could hitherto not explain the existence of all three phases. We further observe a shift of the average oscillation frequency towards lower values together with the appearance of coherent slow oscillations at the transition from resting-state to epileptiform activity. This observation is fully in line with experimental data and could explain the influence of GABAergic drugs both on gamma oscillations and epileptic states. Compared to previous models for gamma oscillations and resting-state activity, the multiplex Kuramoto model not only provides a unifying framework, but also has a direct connection to measurable physiological parameters.

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity.

PubMed

Sadilek, Maximilian; Thurner, Stefan

2015-05-21

We derive a two-layer multiplex Kuramoto model from Wilson-Cowan type physiological equations that describe neural activity on a network of interconnected cortical regions. This is mathematically possible due to the existence of a unique, stable limit cycle, weak coupling, and inhibitory synaptic time delays. We study the phase diagram of this model numerically as a function of the inter-regional connection strength that is related to cerebral blood flow, and a phase shift parameter that is associated with synaptic GABA concentrations. We find three macroscopic phases of cortical activity: background activity (unsynchronized oscillations), epileptiform activity (highly synchronized oscillations) and resting-state activity (synchronized clusters/chaotic behaviour). Previous network models could hitherto not explain the existence of all three phases. We further observe a shift of the average oscillation frequency towards lower values together with the appearance of coherent slow oscillations at the transition from resting-state to epileptiform activity. This observation is fully in line with experimental data and could explain the influence of GABAergic drugs both on gamma oscillations and epileptic states. Compared to previous models for gamma oscillations and resting-state activity, the multiplex Kuramoto model not only provides a unifying framework, but also has a direct connection to measurable physiological parameters.

Bayes factors for the linear ballistic accumulator model of decision-making.

PubMed

Evans, Nathan J; Brown, Scott D

2018-04-01

Evidence accumulation models of decision-making have led to advances in several different areas of psychology. These models provide a way to integrate response time and accuracy data, and to describe performance in terms of latent cognitive processes. Testing important psychological hypotheses using cognitive models requires a method to make inferences about different versions of the models which assume different parameters to cause observed effects. The task of model-based inference using noisy data is difficult, and has proven especially problematic with current model selection methods based on parameter estimation. We provide a method for computing Bayes factors through Monte-Carlo integration for the linear ballistic accumulator (LBA; Brown and Heathcote, 2008), a widely used evidence accumulation model. Bayes factors are used frequently for inference with simpler statistical models, and they do not require parameter estimation. In order to overcome the computational burden of estimating Bayes factors via brute force integration, we exploit general purpose graphical processing units; we provide free code for this. This approach allows estimation of Bayes factors via Monte-Carlo integration within a practical time frame. We demonstrate the method using both simulated and real data. We investigate the stability of the Monte-Carlo approximation, and the LBA's inferential properties, in simulation studies.

The Five-Factor Model of personality disorder and DSM-5.

PubMed

Trull, Timothy J

2012-12-01

The Five-Factor Model of personality disorders (FFMPD; Widiger & Mullins-Sweatt, ) developed from the recognition that the popular Five-Factor Model (FFM) of personality could be used to describe and understand the official personality disorder (PD) constructs from the American Psychiatric Association's (APA) diagnostic manuals (e.g., DSM-IV-TR, APA, ). This article provides an overview of the FFM, highlighting its validity and utility in characterizing PDs as well as its ability to provide a comprehensive account of personality pathology in general. In 2013, DSM-5 is scheduled to appear, and the "hybrid" PD proposal will emphasize a 25-personality trait model. I present the current version of this new model, compare it to the FFMPD, and discuss issues related to the implementation of the FFMPD. © 2012 The Author. Journal of Personality © 2012, Wiley Periodicals, Inc.

A realistic host-vector transmission model for describing malaria prevalence pattern.

PubMed

Mandal, Sandip; Sinha, Somdatta; Sarkar, Ram Rup

2013-12-01

Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern.In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.

Conceptual modeling of postmortem evaluation findings to describe dairy cow deaths.

PubMed

McConnel, C S; Garry, F B; Hill, A E; Lombard, J E; Gould, D H

2010-01-01

Dairy cow mortality levels in the United States are excessive and increasing over time. To better define cause and effect and combat rising mortality, clearer definitions of the reasons that cows die need to be acquired through thorough necropsy-based postmortem evaluations. The current study focused on organizing information generated from postmortem evaluations into a monitoring system that is based on the fundamentals of conceptual modeling and that will potentially be translatable into on-farm relational databases. This observational study was conducted on 3 high-producing, commercial dairies in northern Colorado. Throughout the study period a thorough postmortem evaluation was performed by veterinarians on cows that died on each dairy. Postmortem data included necropsy findings, life-history features (e.g., birth date, lactation number, lactational and reproductive status), clinical history and treatments, and pertinent aspects of operational management that were subject to change and considered integral to the poor outcome. During this study, 174 postmortem evaluations were performed. Postmortem evaluation results were conceptually modeled to view each death within the context of the web of factors influencing the dairy and the cow. Categories were formulated describing mortality in terms of functional characteristics potentially amenable to easy performance evaluation, management oversight, and research. In total, 21 death categories with 7 category themes were created. Themes included specific disease processes with variable etiologies, failure of disease recognition or treatment, traumatic events, multifactorial failures linked to transition or negative energy balance issues, problems with feed management, miscellaneous events not amenable to prevention or treatment, and undetermined causes. Although postmortem evaluations provide the relevant information necessary for framing a cow's death, a restructuring of on-farm databases is needed to integrate this

Models to describe the thermal development rates of Cycloneda sanguinea L. (Coleoptera: Coccinelidae).

PubMed

Pachú, Jéssica Ks; Malaquias, José B; Godoy, Wesley Ac; de S Ramalho, Francisco; Almeida, Bruna R; Rossi, Fabrício

2018-04-01

Precise estimates of the lower (T min ) and higher (T max ) thermal thresholds as well as the temperature range that provides optimum performance (T opt ) enable to obtain the desired number of individuals in conservation systems, rearing and release of natural enemies. In this study, the relationship between the development rates of Cycloneda sanguinea L. (Coleoptera: Coccinelidae) and temperature was described using non-linear models developed by Analytis, Brière, Lactin, Lamb, Logan and Sharpe & DeMichele. There were differences between the models, considering the estimates of the parameters T min , T max , and T opt . All of the tested models were able to describe non-linear responses involving the development rates of C. sanguinea at constant temperatures. Lactin and Lamb gave the highest z weight for egg, while Analytis, Sharpe & DeMichele and Brière gave the highest values for larvae and pupae. The more realistic T opt estimated by the models varied from 29° to 31°C for egg, 27-28 °C for larvae and 28-29 °C for pupae. The Logan, Lactin and Analytis models estimated the T max for egg, larvae and pupae to be approximately 34 °C, while the T min estimated by the Analytis model was 16 °C for larvae and pupae. The information generated by our research will contribute towards improving the rearing and release of C. sanguinea in biological control programs, accurately controlling the rate of development in laboratory conditions or even scheduling the most favourable this species' release. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Mathematic concept model of accumulation of functional disorders associated with environmental factors].

PubMed

Zaĭtseva, N V; Trusov, P V; Kir'ianov, D A

2012-01-01

The mathematic concept model presented describes accumulation of functional disorders associated with environmental factors, plays predictive role and is designed for assessments of possible effects caused by heterogenous factors with variable exposures. Considering exposure changes with self-restoration process opens prospects of using the model to evaluate, analyse and manage occupational risks. To develop current theoretic approaches, the authors suggested a model considering age-related body peculiarities, systemic interactions of organs, including neuro-humoral regulation, accumulation of functional disorders due to external factors, rehabilitation of functions during treatment. General objective setting covers defining over a hundred unknow coefficients that characterize speed of various processes within the body. To solve this problem, the authors used iteration approach, successive identification, that starts from the certain primary approximation of the model parameters and processes subsequent updating on the basis of new theoretic and empirical knowledge.

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

Program to Produce Tabulated Data Set Describing NSWC Burn Model for Hydrodynamic Computations

DTIC Science & Technology

1990-09-11

helpful insights of Dr. Raafat Guirguis of the Naval Surface Warfare Center on how the NSWC Burn Model works, and Drs. Schittke and Feisler of...R. Guirguis ) 1 R13 (P. Miller ) 1 R13 (K. Kin) 2 R13 (C. Coffey) 1 R13 (H. Sandusky) 1 R13 (D. Tasker) 1 R13 (E. Lanar) 1 R13 (J. Forbes) 1 R13 (R...NAVSWC TR 90-364 AD-A238 710 PROGRAM TO PRODUCE TABULATED DATA SET DESCRIBING NSWC BURN MODEL FOR HYDRODYNAMIC COMPUTATIONS BY LEWIS C. HUDSON III

Muscle activation described with a differential equation model for large ensembles of locally coupled molecular motors.

PubMed

Walcott, Sam

2014-10-01

Molecular motors, by turning chemical energy into mechanical work, are responsible for active cellular processes. Often groups of these motors work together to perform their biological role. Motors in an ensemble are coupled and exhibit complex emergent behavior. Although large motor ensembles can be modeled with partial differential equations (PDEs) by assuming that molecules function independently of their neighbors, this assumption is violated when motors are coupled locally. It is therefore unclear how to describe the ensemble behavior of the locally coupled motors responsible for biological processes such as calcium-dependent skeletal muscle activation. Here we develop a theory to describe locally coupled motor ensembles and apply the theory to skeletal muscle activation. The central idea is that a muscle filament can be divided into two phases: an active and an inactive phase. Dynamic changes in the relative size of these phases are described by a set of linear ordinary differential equations (ODEs). As the dynamics of the active phase are described by PDEs, muscle activation is governed by a set of coupled ODEs and PDEs, building on previous PDE models. With comparison to Monte Carlo simulations, we demonstrate that the theory captures the behavior of locally coupled ensembles. The theory also plausibly describes and predicts muscle experiments from molecular to whole muscle scales, suggesting that a micro- to macroscale muscle model is within reach.

Modeling Ability Differentiation in the Second-Order Factor Model

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

2011-01-01

In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

2017-04-01

Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various

A model describing diffusion in prostate cancer.

PubMed

Gilani, Nima; Malcolm, Paul; Johnson, Glyn

2017-07-01

Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill-defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non-Gaussian behavior of tissue diffusion. The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two-compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10-fold cross-validation. Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature. A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316-326, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A Unique Computational Algorithm to Simulate Probabilistic Multi-Factor Interaction Model Complex Material Point Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2010-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points--the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

A mathematical model to describe the nonlinear elastic properties of the gastrocnemius tendon of chickens.

PubMed

Foutz, T L

1991-03-01

A phenomenological model was developed to describe the nonlinear elastic behavior of the avian gastrocnemius tendon. Quasistatic uniaxial tensile tests were used to apply a deformation and resulting load on the tendon at a deformation rate of 5 mm/min. Plots of deformation versus load indicated a nonlinear loading response. By calculating engineering stress and engineering strain, the experimental data were normalized for tendon shape. The elastic response was determined from stress-strain curves and was found to vary with engineering strain. The response to the applied engineering strain could best be described by a mathematical model that combined a linear function and a nonlinear function. Three parameters in the model were developed to represent the nonlinear elastic behavior of the tendon, thereby allowing analysis of elasticity without prior knowledge of engineering strain. This procedure reduced the amount of data needed for the statistical analysis of nonlinear elasticity.

Generalized Stoner-Wohlfarth model accurately describing the switching processes in pseudo-single ferromagnetic particles

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

Cimpoesu, Dorin, E-mail: cdorin@uaic.ro; Stoleriu, Laurentiu; Stancu, Alexandru

2013-12-14

We propose a generalized Stoner-Wohlfarth (SW) type model to describe various experimentally observed angular dependencies of the switching field in non-single-domain magnetic particles. Because the nonuniform magnetic states are generally characterized by complicated spin configurations with no simple analytical description, we maintain the macrospin hypothesis and we phenomenologically include the effects of nonuniformities only in the anisotropy energy, preserving as much as possible the elegance of SW model, the concept of critical curve and its geometric interpretation. We compare the results obtained with our model with full micromagnetic simulations in order to evaluate the performance and limits of our approach.

Development of a model and computer code to describe solar grade silicon production processes

NASA Technical Reports Server (NTRS)

Gould, R. K.; Srivastava, R.

1979-01-01

Two computer codes were developed for describing flow reactors in which high purity, solar grade silicon is produced via reduction of gaseous silicon halides. The first is the CHEMPART code, an axisymmetric, marching code which treats two phase flows with models describing detailed gas-phase chemical kinetics, particle formation, and particle growth. It can be used to described flow reactors in which reactants, mix, react, and form a particulate phase. Detailed radial gas-phase composition, temperature, velocity, and particle size distribution profiles are computed. Also, deposition of heat, momentum, and mass (either particulate or vapor) on reactor walls is described. The second code is a modified version of the GENMIX boundary layer code which is used to compute rates of heat, momentum, and mass transfer to the reactor walls. This code lacks the detailed chemical kinetics and particle handling features of the CHEMPART code but has the virtue of running much more rapidly than CHEMPART, while treating the phenomena occurring in the boundary layer in more detail.

Symmetry breaking in (gravitating) scalar field models describing interacting boson stars and Q-balls

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

Brihaye, Yves; Caebergs, Thierry; Hartmann, Betti

2009-09-15

We investigate the properties of interacting Q-balls and boson stars that sit on top of each other in great detail. The model that describes these solutions is essentially a (gravitating) two-scalar field model where both scalar fields are complex. We construct interacting Q-balls or boson stars with arbitrarily small charges but finite mass. We observe that in the interacting case--where the interaction can be either due to the potential or due to gravity--two types of solutions exist for equal frequencies: one for which the two-scalar fields are equal, but also one for which the two-scalar fields differ. This constitutes amore » symmetry breaking in the model. While for Q-balls asymmetric solutions have always corresponding symmetric solutions and are thus likely unstable to decay to symmetric solutions with lower energy, there exists a parameter regime for interacting boson stars, where only asymmetric solutions exist. We present the domain of existence for two interacting nonrotating solutions as well as for solutions describing the interaction between rotating and nonrotating Q-balls and boson stars, respectively.« less

Decompression sickness after air break in prebreathe described with a survival model.

PubMed

Conkin, Johnny

2011-06-01

A perception exists in aerospace that a brief interruption in a 100% oxygen prebreathe (PB) by breathing air has a substantial decompression sickness (DCS) consequence. The consequences of an air break during PB on the subsequent hypobaric DCS outcomes were evaluated. The hypothesis was that asymmetrical and not symmetrical nitrogen (N2) kinetics was best to model the distribution of subsequent DCS survival times after PBs that included air breaks. DCS survival times from 95 controls for a 60-min PB prior to 2- or 4-h exposures to 4.37 psia (9144 m; 30,000 ft) were analyzed along with 3 experimental conditions: 10-min air break (N = 40), 20-min air break (N = 40), or 60-min air break (N = 32) 30 min into the PB followed by 30 min of PB. Ascent rate was 1524 m x min(-1) and all 207 exposures included light exercise at 4.37 psia. Various computations of decompression dose were evaluated; either the difference or ratio of P1N2 and P2, where P1N2 was computed tissue N2 pressure to account for the PB and P2 was altitude pressure. Survival times were described with an accelerated log logistic model with asymmetrical N2 kinetics defining P1N2--P2 as best decompression dose. Exponential N2 uptake during the air break was described with a 10-min half time and N2 elimination during PB with a 60-min half time. A simple conclusion about compensation for air break is not possible because the duration and location of a break in a PB is variable. The resulting survival model is used to compute additional PB time to compensate for an air break in PB within the range of tested conditions.

The Transfer Function Model as a Tool to Study and Describe Space Weather Phenomena

NASA Technical Reports Server (NTRS)

Porter, Hayden S.; Mayr, Hans G.; Bhartia, P. K. (Technical Monitor)

2001-01-01

The Transfer Function Model (TFM) is a semi-analytical, linear model that is designed especially to describe thermospheric perturbations associated with magnetic storms and substorm. activity. It is a multi-constituent model (N2, O, He H, Ar) that accounts for wind induced diffusion, which significantly affects not only the composition and mass density but also the temperature and wind fields. Because the TFM adopts a semianalytic approach in which the geometry and temporal dependencies of the driving sources are removed through the use of height-integrated Green's functions, it provides physical insight into the essential properties of processes being considered, which are uncluttered by the accidental complexities that arise from particular source geometrie and time dependences. Extending from the ground to 700 km, the TFM eliminates spurious effects due to arbitrarily chosen boundary conditions. A database of transfer functions, computed only once, can be used to synthesize a wide range of spatial and temporal sources dependencies. The response synthesis can be performed quickly in real-time using only limited computing capabilities. These features make the TFM unique among global dynamical models. Given these desirable properties, a version of the TFM has been developed for personal computers (PC) using advanced platform-independent 3D visualization capabilities. We demonstrate the model capabilities with simulations for different auroral sources, including the response of ducted gravity waves modes that propagate around the globe. The thermospheric response is found to depend strongly on the spatial and temporal frequency spectra of the storm. Such varied behavior is difficult to describe in statistical empirical models. To improve the capability of space weather prediction, the TFM thus could be grafted naturally onto existing statistical models using data assimilation.

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

Suitability of parametric models to describe the hydraulic properties of an unsaturated coarse sand and gravel

USGS Publications Warehouse

Mace, Andy; Rudolph, David L.; Kachanoski , R. Gary

1998-01-01

The performance of parametric models used to describe soil water retention (SWR) properties and predict unsaturated hydraulic conductivity (K) as a function of volumetric water content (θ) is examined using SWR and K(θ) data for coarse sand and gravel sediments. Six 70 cm long, 10 cm diameter cores of glacial outwash were instrumented at eight depths with porous cup ten-siometers and time domain reflectometry probes to measure soil water pressure head (h) and θ, respectively, for seven unsaturated and one saturated steady-state flow conditions. Forty-two θ(h) and K(θ) relationships were measured from the infiltration tests on the cores. Of the four SWR models compared in the analysis, the van Genuchten (1980) equation with parameters m and n restricted according to the Mualem (m = 1 - 1/n) criterion is best suited to describe the θ(h) relationships. The accuracy of two models that predict K(θ) using parameter values derived from the SWR models was also evaluated. The model developed by van Genuchten (1980) based on the theoretical expression of Mualem (1976) predicted K(θ) more accurately than the van Genuchten (1980) model based on the theory of Burdine (1953). A sensitivity analysis shows that more accurate predictions of K(θ) are achieved using SWR model parameters derived with residual water content (θr) specified according to independent measurements of θ at values of h where θ/h ∼ 0 rather than model-fit θr values. The accuracy of the model K(θ) function improves markedly when at least one value of unsaturated K is used to scale the K(θ) function predicted using the saturated K. The results of this investigation indicate that the hydraulic properties of coarse-grained sediments can be accurately described using the parametric models. In addition, data collection efforts should focus on measuring at least one value of unsaturated hydraulic conductivity and as complete a set of SWR data as possible, particularly in the dry range.

Manufacturing and Cost Considerations in Multidisciplinary Aircraft Design (Research on Mathematical Modeling of Manufacturability Factors)

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

1996-01-01

The identification of airframe Manufacturability Factors/Cost Drivers (MFCD) and the method by which the relationships between MFCD and designer-controlled parameters could be properly modeled are described.

Mathematical model describing the thyroids-pituitary axis with distributed time delays in hormone transportation

NASA Astrophysics Data System (ADS)

Neamţu, Mihaela; Stoian, Dana; Navolan, Dan Bogdan

2014-12-01

In the present paper we provide a mathematical model that describe the hypothalamus-pituitary-thyroid axis in autoimmune (Hashimoto's) thyroiditis. Since there is a spatial separation between thyroid and pituitary gland in the body, time is needed for transportation of thyrotropin and thyroxine between the glands. Thus, the distributed time delays are considered as both weak and Dirac kernels. The delayed model is analyzed regarding the stability and bifurcation behavior. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.

The SAM framework: modeling the effects of management factors on human behavior in risk analysis.

PubMed

Murphy, D M; Paté-Cornell, M E

1996-08-01

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.

A mathematical model for describing the mechanical behaviour of root canal instruments.

PubMed

Zhang, E W; Cheung, G S P; Zheng, Y F

2011-01-01

The purpose of this study was to establish a general mathematical model for describing the mechanical behaviour of root canal instruments by combining a theoretical analytical approach with a numerical finite-element method. Mathematical formulas representing the longitudinal (taper, helical angle and pitch) and cross-sectional configurations and area, the bending and torsional inertia, the curvature of the boundary point and the (geometry of) loading condition were derived. Torsional and bending stresses and the resultant deformation were expressed mathematically as a function of these geometric parameters, modulus of elasticity of the material and the applied load. As illustrations, three brands of NiTi endodontic files of different cross-sectional configurations (ProTaper, Hero 642, and Mani NRT) were analysed under pure torsion and pure bending situation by entering the model into a finite-element analysis package (ANSYS). Numerical results confirmed that mathematical models were a feasible method to analyse the mechanical properties and predict the stress and deformation for root canal instruments during root canal preparation. Mathematical and numerical model can be a suitable way to examine mechanical behaviours as a criterion of the instrument design and to predict the stress and strain experienced by the endodontic instruments during root canal preparation. © 2010 International Endodontic Journal.

Heeeere's Johnny: A Case Study in the Five Factor Model of Personality

ERIC Educational Resources Information Center

Miserandino, Marianne

2007-01-01

I describe an assignment for personality psychology or introduction to psychology classes in which students used the Five Factor Model of personality to analyze the personality of entertainer Johnny Carson through his The New York Times obituary. Students evaluated this assignment highly: A majority indicated that the assignment was interesting,…

Using Metaphorical Models for Describing Glaciers

ERIC Educational Resources Information Center

Felzmann, Dirk

2014-01-01

To date, there has only been little conceptual change research regarding conceptions about glaciers. This study used the theoretical background of embodied cognition to reconstruct different metaphorical concepts with respect to the structure of a glacier. Applying the Model of Educational Reconstruction, the conceptions of students and scientists…

Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids

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

Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu

2015-12-28

The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF.more » We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.« less

ESTIMATING UNCERTAINITIES IN FACTOR ANALYTIC MODELS

EPA Science Inventory

When interpreting results from factor analytic models as used in receptor modeling, it is important to quantify the uncertainties in those results. For example, if the presence of a species on one of the factors is necessary to interpret the factor as originating from a certain ...

Relevance and limitations of crowding, fractal, and polymer models to describe nuclear architecture.

PubMed

Huet, Sébastien; Lavelle, Christophe; Ranchon, Hubert; Carrivain, Pascal; Victor, Jean-Marc; Bancaud, Aurélien

2014-01-01

Chromosome architecture plays an essential role for all nuclear functions, and its physical description has attracted considerable interest over the last few years among the biophysics community. These researches at the frontiers of physics and biology have been stimulated by the demand for quantitative analysis of molecular biology experiments, which provide comprehensive data on chromosome folding, or of live cell imaging experiments that enable researchers to visualize selected chromosome loci in living or fixed cells. In this review our goal is to survey several nonmutually exclusive models that have emerged to describe the folding of DNA in the nucleus, the dynamics of proteins in the nucleoplasm, or the movements of chromosome loci. We focus on three classes of models, namely molecular crowding, fractal, and polymer models, draw comparisons, and discuss their merits and limitations in the context of chromosome structure and dynamics, or nuclear protein navigation in the nucleoplasm. Finally, we identify future challenges in the roadmap to a unified model of the nuclear environment. © 2014 Elsevier Inc. All rights reserved.

Significance Testing in Confirmatory Factor Analytic Models.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Hocevar, Dennis

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…

Connections between Graphical Gaussian Models and Factor Analysis

ERIC Educational Resources Information Center

Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

2010-01-01

Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

How Mathematics Describes Life

NASA Astrophysics Data System (ADS)

Teklu, Abraham

2017-01-01

The circle of life is something we have all heard of from somewhere, but we don't usually try to calculate it. For some time we have been working on analyzing a predator-prey model to better understand how mathematics can describe life, in particular the interaction between two different species. The model we are analyzing is called the Holling-Tanner model, and it cannot be solved analytically. The Holling-Tanner model is a very common model in population dynamics because it is a simple descriptor of how predators and prey interact. The model is a system of two differential equations. The model is not specific to any particular set of species and so it can describe predator-prey species ranging from lions and zebras to white blood cells and infections. One thing all these systems have in common are critical points. A critical point is a value for both populations that keeps both populations constant. It is important because at this point the differential equations are equal to zero. For this model there are two critical points, a predator free critical point and a coexistence critical point. Most of the analysis we did is on the coexistence critical point because the predator free critical point is always unstable and frankly less interesting than the coexistence critical point. What we did is consider two regimes for the differential equations, large B and small B. B, A, and C are parameters in the differential equations that control the system where B measures how responsive the predators are to change in the population, A represents predation of the prey, and C represents the satiation point of the prey population. For the large B case we were able to approximate the system of differential equations by a single scalar equation. For the small B case we were able to predict the limit cycle. The limit cycle is a process of the predator and prey populations growing and shrinking periodically. This model has a limit cycle in the regime of small B, that we solved for

Analytic Couple Modeling Introducing Device Design Factor, Fin Factor, Thermal Diffusivity Factor, and Inductance Factor

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

A set of convenient thermoelectric device solutions have been derived in order to capture a number of factors which are previously only resolved with numerical techniques. The concise conversion efficiency equations derived from governing equations provide intuitive and straight-forward design guidelines. These guidelines allow for better device design without requiring detailed numerical modeling. The analytical modeling accounts for factors such as i) variable temperature boundary conditions, ii) lateral heat transfer, iii) temperature variable material properties, and iv) transient operation. New dimensionless parameters, similar to the figure of merit, are introduced including the device design factor, fin factor, thermal diffusivity factor, and inductance factor. These new device factors allow for the straight-forward description of phenomenon generally only captured with numerical work otherwise. As an example a device design factor of 0.38, which accounts for thermal resistance of the hot and cold shoes, can be used to calculate a conversion efficiency of 2.28 while the ideal conversion efficiency based on figure of merit alone would be 6.15. Likewise an ideal couple with efficiency of 6.15 will be reduced to 5.33 when lateral heat is accounted for with a fin factor of 1.0.

Species-free species distribution models describe macroecological properties of protected area networks.

PubMed

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have

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

NASA Technical Reports Server (NTRS)

Elrod, David Alan

1988-01-01

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

Gaussian and Lognormal Models of Hurricane Gust Factors

NASA Technical Reports Server (NTRS)

Merceret, Frank

2009-01-01

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

PubMed Central

Cook, Daniel L; Farley, Joel F; Tapscott, Stephen J

2001-01-01

Background: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. Results: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. Conclusions: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis. PMID:11305940

A Minimal Model Describing Hexapedal Interlimb Coordination: The Tegotae-Based Approach

PubMed Central

Owaki, Dai; Goda, Masashi; Miyazawa, Sakiko; Ishiguro, Akio

2017-01-01

Insects exhibit adaptive and versatile locomotion despite their minimal neural computing. Such locomotor patterns are generated via coordination between leg movements, i.e., an interlimb coordination, which is largely controlled in a distributed manner by neural circuits located in thoracic ganglia. However, the mechanism responsible for the interlimb coordination still remains elusive. Understanding this mechanism will help us to elucidate the fundamental control principle of animals' agile locomotion and to realize robots with legs that are truly adaptive and could not be developed solely by conventional control theories. This study aims at providing a “minimal" model of the interlimb coordination mechanism underlying hexapedal locomotion, in the hope that a single control principle could satisfactorily reproduce various aspects of insect locomotion. To this end, we introduce a novel concept we named “Tegotae,” a Japanese concept describing the extent to which a perceived reaction matches an expectation. By using the Tegotae-based approach, we show that a surprisingly systematic design of local sensory feedback mechanisms essential for the interlimb coordination can be realized. We also use a hexapod robot we developed to show that our mathematical model of the interlimb coordination mechanism satisfactorily reproduces various insects' gait patterns. PMID:28649197

Linear model describing three components of flow in karst aquifers using 18O data

USGS Publications Warehouse

Long, Andrew J.; Putnam, L.D.

2004-01-01

The stable isotope of oxygen, 18O, is used as a naturally occurring ground-water tracer. Time-series data for ??18O are analyzed to model the distinct responses and relative proportions of the conduit, intermediate, and diffuse flow components in karst aquifers. This analysis also describes mathematically the dynamics of the transient fluid interchange between conduits and diffusive networks. Conduit and intermediate flow are described by linear-systems methods, whereas diffuse flow is described by mass-balance methods. An automated optimization process estimates parameters of lognormal, Pearson type III, and gamma distributions, which are used as transfer functions in linear-systems analysis. Diffuse flow and mixing parameters also are estimated by these optimization methods. Results indicate the relative proximity of a well to a main conduit flowpath and can help to predict the movement and residence times of potential contaminants. The three-component linear model is applied to five wells, which respond to changes in the isotopic composition of point recharge water from a sinking stream in the Madison aquifer in the Black Hills of South Dakota. Flow velocities as much as 540 m/d and system memories of as much as 71 years are estimated by this method. Also, the mean, median, and standard deviation of traveltimes; time to peak response; and the relative fraction of flow for each of the three components are determined for these wells. This analysis infers that flow may branch apart and rejoin as a result of an anastomotic (or channeled) karst network.

Using logic model methods in systematic review synthesis: describing complex pathways in referral management interventions

PubMed Central

2014-01-01

Background There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods. Methods This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders. Results The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction. Conclusions The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies. Trial registration number PROSPERO registration number: CRD42013004037. PMID:24885751

Using logic model methods in systematic review synthesis: describing complex pathways in referral management interventions.

PubMed

Baxter, Susan K; Blank, Lindsay; Woods, Helen Buckley; Payne, Nick; Rimmer, Melanie; Goyder, Elizabeth

2014-05-10

There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods. This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders. The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction. The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies. PROSPERO registration number: CRD42013004037.

FTIRI Parameters describing Acid Phosphate Substitution in Biologic Hydroxyapatite

PubMed Central

Spevak, Lyudmila; Flach, Carol R.; Hunter, Tracey; Mendelsohn, Richard; Boskey, Adele

2013-01-01

Acid phosphate substitution into mineralized tissue is an important determinant of their mechanical properties and their response to treatment. This study identifies and validates Fourier Transform Infrared Spectroscopic Imaging (FTIRI) spectral parameters that provide information on the acid phosphate (HPO4) substitution into hydroxyapatite in developing mineralized tissues. Curve fitting and Fourier self-deconvolution were used to identify subband positions in model compounds (with and without HPO4). The intensity of subbands at 1127 cm−1 and 1110 cm−1 correlated with the acid phosphate content in these models. Peak height ratios of these subbands to the ν3 vibration at 1096 cm−1 found in stoichiometric apatite, were evaluated in the model compounds and mixtures thereof. FTIRI spectra of bones and teeth at different developmental ages were analyzed using these spectral parameters. Factor analysis (a chemometric technique) was also conducted on the tissue samples and resulted in factor loadings with spectral features corresponding to the HPO4 vibrations described above. Images of both factor correlation coefficients and the peak height ratios 1127cm−1/1096cm−1 and 1112cm−1/1096cm−1 demonstrated higher acid phosphate content in younger vs. more mature regions in the same specimen. Maps of the distribution of acid phosphate content will be useful for characterizing the extent of new bone formation, areas of potential decreased strength, and the effects of therapies such as those used in metabolic bone diseases (osteoporosis, chronic kidney disease) on mineral composition. Because of the wider range of values obtained with the 1127 cm−1/1096 cm−1 parameter compared to the 1110 cm−1/1096 cm−1 parameter, and the smaller scatter in the slope, it is suggested that this ratio should be the parameter of choice. PMID:23380987

Is there a reliable factorial structure in the 20-item Toronto Alexithymia Scale? A comparison of factor models in clinical and normal adult samples.

PubMed

Müller, Jochen; Bühner, Markus; Ellgring, Heiner

2003-12-01

The 20-item Toronto Alexithymia Scale (TAS-20) is the most widely used instrument for measuring alexithymia. However, different studies did not always yield identical factor structures of this scale. The present study aims at clarifying some discrepant results. Maximum likelihood confirmatory factor analyses of a German version of the TAS-20 were conducted on data from a clinical sample (N=204) and a sample of normal adults (N=224). Five different models with one to four factors were compared. A four-factor model with factors (F1) "Difficulty identifying feelings" (F2), "Difficulty describing feelings" (F3), "Low importance of emotion" and (F4) "Pragmatic thinking" and a three-factor model with the combined factor "Difficulties in identifying and describing feelings" described the data best. Factors related to "externally oriented thinking" provided no acceptable level of reliability. Results from the present and other studies indicate that the factorial structure of the TAS-20 may vary across samples. Whether factor structures different from the common three-factor structure are an exception in some mainly clinical populations or a common phenomenon outside student populations has still to be determined. For a further exploration of the factor structure of the TAS-20 in different populations, it would be important not only to test the fit of the common three-factor model, but also to consider other competing solutions like the models of the present study.

Multiple robustness in factorized likelihood models.

PubMed

Molina, J; Rotnitzky, A; Sued, M; Robins, J M

2017-09-01

We consider inference under a nonparametric or semiparametric model with likelihood that factorizes as the product of two or more variation-independent factors. We are interested in a finite-dimensional parameter that depends on only one of the likelihood factors and whose estimation requires the auxiliary estimation of one or several nuisance functions. We investigate general structures conducive to the construction of so-called multiply robust estimating functions, whose computation requires postulating several dimension-reducing models but which have mean zero at the true parameter value provided one of these models is correct.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

Predicting dimensions of personality disorder from domains and facets of the Five-Factor Model.

PubMed

Reynolds, S K; Clark, L A

2001-04-01

We compared the utility of several trait models for describing personality disorder in a heterogeneous clinical sample (N = 94). Participants completed the Schedule for Nonadaptive and Adaptive Personality (SNAP; Clark, 1993b), a self-report measure that assesses traits relevant to personality disorder, and two measures of the Five-Factor Model: the Revised NEO Personality Inventory (NEO-PI-R; Costa and McCrae, 1992) and the Big Five Inventory (BFI; John, Donahue, & Kentle, 1991). Regression analyses indicated substantial overlap between the SNAP scales and the NEO-PI-R facets. In addition, use of the NEO-PI-R facets afforded substantial improvement over the Five-Factor Model domains in predicting interview-based ratings of DSM-IV personality disorder (American Psychiatric Association, 1994), such that the NEO facets and the SNAP scales demonstrated roughly equivalent levels of predictive power. Results support assessment of the full range of NEO-PI-R facets over the Five-Factor Model domains for both research and clinical use.

Decompression Sickness After Air Break in Prebreathe Described with a Survival Model

NASA Technical Reports Server (NTRS)

Conkin, J.; Pilmanis, A. A.

2010-01-01

Data from Brooks City-Base show the decompression sickness (DCS) and venous gas emboli (VGE) consequences of air breaks in a resting 100% O2 prebreathe (PB) prior to a hypobaric exposure. METHODS: DCS and VGE survival times from 95 controls for a 60 min PB prior to 2-hr or 4-hr exposures to 4.37 psia are statistically compared to 3 break in PB conditions: a 10 min (n=40), 20 min (n=40), or 60 min break (n=32) 30 min into the PB followed by 30 min of PB. Ascent rate was 1,524 meters / min and all exposures included light exercise and 4 min of VGE monitoring of heart chambers at 16 min intervals. DCS survival time for combined control and air breaks were described with an accelerated log logistic model where exponential N2 washin during air break was described with a 10 min half-time and washout during PB with a 60 min half-time. RESULTS: There was no difference in VGE or DCS survival times among 3 different air breaks, or when air breaks were compared to control VGE times. However, 10, 20, and 60 min air breaks had significantly earlier survival times compared to control DCS times, certainly early in the exposures. CONCLUSION: Air breaks of 10, 20, and 60 min after 30 min of a 60 min PB reduced DCS survival time. The survival model combined discrete comparisons into a global description mechanistically linked to asymmetrical N2 washin and washout kinetics based on inspired pN2. Our unvalidated regression is used to compute additional PB time needed to compensate for an air break in PB within the range of tested conditions.

A spatial age-structured model for describing sea lamprey (Petromyzon marinus) population dynamics

USGS Publications Warehouse

Robinson, Jason M.; Wilberg, Michael J.; Adams, Jean V.; Jones, Michael L.

2013-01-01

The control of invasive sea lampreys (Petromyzon marinus) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.

Identification and synthetic modeling of factors affecting American black duck populations

USGS Publications Warehouse

Conroy, Michael J.; Miller, Mark W.; Hines, James E.

2002-01-01

We reviewed the literature on factors potentially affecting the population status of American black ducks (Anas rupribes). Our review suggests that there is some support for the influence of 4 major, continental-scope factors in limiting or regulating black duck populations: 1) loss in the quantity or quality of breeding habitats; 2) loss in the quantity or quality of wintering habitats; 3) harvest, and 4) interactions (competition, hybridization) with mallards (Anas platyrhychos) during the breeding and/or wintering periods. These factors were used as the basis of an annual life cycle model in which reproduction rates and survival rates were modeled as functions of the above factors, with parameters of the model describing the strength of these relationships. Variation in the model parameter values allows for consideration of scientific uncertainty as to the degree each of these factors may be contributing to declines in black duck populations, and thus allows for the investigation of the possible effects of management (e.g., habitat improvement, harvest reductions) under different assumptions. We then used available, historical data on black duck populations (abundance, annual reproduction rates, and survival rates) and possible driving factors (trends in breeding and wintering habitats, harvest rates, and abundance of mallards) to estimate model parameters. Our estimated reproduction submodel included parameters describing negative density feedback of black ducks, positive influence of breeding habitat, and negative influence of mallard densities; our survival submodel included terms for positive influence of winter habitat on reproduction rates, and negative influences of black duck density (i.e., compensation to harvest mortality). Individual models within each group (reproduction, survival) involved various combinations of these factors, and each was given an information theoretic weight for use in subsequent prediction. The reproduction model with highest

Development of a Model and Computer Code to Describe Solar Grade Silicon Production Processes

NASA Technical Reports Server (NTRS)

Srivastava, R.; Gould, R. K.

1979-01-01

Mathematical models and computer codes based on these models, which allow prediction of the product distribution in chemical reactors for converting gaseous silicon compounds to condensed-phase silicon were developed. The following tasks were accomplished: (1) formulation of a model for silicon vapor separation/collection from the developing turbulent flow stream within reactors of the Westinghouse (2) modification of an available general parabolic code to achieve solutions to the governing partial differential equations (boundary layer type) which describe migration of the vapor to the reactor walls, (3) a parametric study using the boundary layer code to optimize the performance characteristics of the Westinghouse reactor, (4) calculations relating to the collection efficiency of the new AeroChem reactor, and (5) final testing of the modified LAPP code for use as a method of predicting Si(1) droplet sizes in these reactors.

Describing different brain computer interface systems through a unique model: a UML implementation.

PubMed

Quitadamo, Lucia Rita; Marciani, Maria Grazia; Cardarilli, Gian Carlo; Bianchi, Luigi

2008-01-01

All the protocols currently implemented in brain computer interface (BCI) experiments are characterized by different structural and temporal entities. Moreover, due to the lack of a unique descriptive model for BCI systems, there is not a standard way to define the structure and the timing of a BCI experimental session among different research groups and there is also great discordance on the meaning of the most common terms dealing with BCI, such as trial, run and session. The aim of this paper is to provide a unified modeling language (UML) implementation of BCI systems through a unique dynamic model which is able to describe the main protocols defined in the literature (P300, mu-rhythms, SCP, SSVEP, fMRI) and demonstrates to be reasonable and adjustable according to different requirements. This model includes a set of definitions of the typical entities encountered in a BCI, diagrams which explain the structural correlations among them and a detailed description of the timing of a trial. This last represents an innovation with respect to the models already proposed in the literature. The UML documentation and the possibility of adapting this model to the different BCI systems built to date, make it a basis for the implementation of new systems and a mean for the unification and dissemination of resources. The model with all the diagrams and definitions reported in the paper are the core of the body language framework, a free set of routines and tools for the implementation, optimization and delivery of cross-platform BCI systems.

Developing a broad categorisation scheme to describe risk factors for mental illness, for use in prevention policy and planning.

PubMed

Furber, Gareth; Leach, Matthew; Guy, Sophie; Segal, Leonie

2017-03-01

The prevention of mental illness involves identifying and modifying those characteristics and exposures of an individual that threaten their mental health - commonly referred to as risk factors. Existing categorisations of risk factors for mental illness are either limited in their scope or oversimplified in their description. As part of a large mental health workforce and service planning project, we set out to develop a more detailed and comprehensive categorisation scheme to describe risk factors for mental illness. We conducted a rapid review of MEDLINE and Google Scholar for meta-analytic studies that examined the characteristics and exposures that typify the population with mental illness in order to identify and categorise potential risk factors. The search uncovered 1628 relevant studies, from which 10 primary and 23 secondary categories of risk factors were identified, ranging from genetic and biomedical to psychological and sociocultural. The review revealed interesting distortions in the focus of the literature, with the majority of studies focused on a few disorders (schizophrenia, depression and neurodegenerative disorders) and genetic, psychological and physiological risks. In contrast, environmental (e.g. media exposure) and occupational (e.g. employee health) were under-represented. The categorisation scheme developed in this paper is a step towards a more detailed taxonomy of risk factors for mental illness; this will be most useful in guiding clinicians, researchers and policy-makers in driving the prevention agenda forward.

Development of biomechanical models for human factors evaluations

NASA Technical Reports Server (NTRS)

Woolford, Barbara; Pandya, Abhilash; Maida, James

1993-01-01

Computer aided design (CAD) techniques are now well established and have become the norm in many aspects of aerospace engineering. They enable analytical studies, such as finite element analysis, to be performed to measure performance characteristics of the aircraft or spacecraft long before a physical model is built. However, because of the complexity of human performance, CAD systems for human factors are not in widespread use. The purpose of such a program would be to analyze the performance capability of a crew member given a particular environment and task. This requires the design capabilities to describe the environment's geometry and to describe the task's requirements, which may involve motion and strength. This in turn requires extensive data on human physical performance which can be generalized to many different physical configurations. PLAID is developing into such a program. Begun at Johnson Space Center in 1977, it was started to model only the geometry of the environment. The physical appearance of a human body was generated, and the tool took on a new meaning as fit, access, and reach could be checked. Specification of fields-of-view soon followed. This allowed PLAID to be used to predict what the Space Shuttle cameras or crew could see from a given point.

In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

PubMed

Liu, Jun-Jun; Xiang, Yu

2011-01-01

WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

A model describing intra-granular fission gas behaviour in oxide fuel for advanced engineering tools

NASA Astrophysics Data System (ADS)

Pizzocri, D.; Pastore, G.; Barani, T.; Magni, A.; Luzzi, L.; Van Uffelen, P.; Pitts, S. A.; Alfonsi, A.; Hales, J. D.

2018-04-01

The description of intra-granular fission gas behaviour is a fundamental part of any model for the prediction of fission gas release and swelling in nuclear fuel. In this work we present a model describing the evolution of intra-granular fission gas bubbles in terms of bubble number density and average size, coupled to gas release to grain boundaries. The model considers the fundamental processes of single gas atom diffusion, gas bubble nucleation, re-solution and gas atom trapping at bubbles. The model is derived from a detailed cluster dynamics formulation, yet it consists of only three differential equations in its final form; hence, it can be efficiently applied in engineering fuel performance codes while retaining a physical basis. We discuss improvements relative to previous single-size models for intra-granular bubble evolution. We validate the model against experimental data, both in terms of bubble number density and average bubble radius. Lastly, we perform an uncertainty and sensitivity analysis by propagating the uncertainties in the parameters to model results.

A standardised graphic method for describing data privacy frameworks in primary care research using a flexible zone model.

PubMed

Kuchinke, Wolfgang; Ohmann, Christian; Verheij, Robert A; van Veen, Evert-Ben; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C

2014-12-01

To develop a model describing core concepts and principles of data flow, data privacy and confidentiality, in a simple and flexible way, using concise process descriptions and a diagrammatic notation applied to research workflow processes. The model should help to generate robust data privacy frameworks for research done with patient data. Based on an exploration of EU legal requirements for data protection and privacy, data access policies, and existing privacy frameworks of research projects, basic concepts and common processes were extracted, described and incorporated into a model with a formal graphical representation and a standardised notation. The Unified Modelling Language (UML) notation was enriched by workflow and own symbols to enable the representation of extended data flow requirements, data privacy and data security requirements, privacy enhancing techniques (PET) and to allow privacy threat analysis for research scenarios. Our model is built upon the concept of three privacy zones (Care Zone, Non-care Zone and Research Zone) containing databases, data transformation operators, such as data linkers and privacy filters. Using these model components, a risk gradient for moving data from a zone of high risk for patient identification to a zone of low risk can be described. The model was applied to the analysis of data flows in several general clinical research use cases and two research scenarios from the TRANSFoRm project (e.g., finding patients for clinical research and linkage of databases). The model was validated by representing research done with the NIVEL Primary Care Database in the Netherlands. The model allows analysis of data privacy and confidentiality issues for research with patient data in a structured way and provides a framework to specify a privacy compliant data flow, to communicate privacy requirements and to identify weak points for an adequate implementation of data privacy. Copyright © 2014 Elsevier Ireland Ltd. All rights

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

2016-08-01

The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

Replica Analysis for Portfolio Optimization with Single-Factor Model

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-06-01

In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking?

PubMed

Sznitman, Sharon R; Zlotnick, Cheryl; Harel-Fisch, Yossi

2016-07-01

The multiple risk model postulates that accumulating risk factors increase adolescent drunkenness and smoking. The normalisation theory adds to this by arguing that the relation between accumulative risk and drunkenness and smoking is dependent on the distribution of these behaviours in the larger population. More concretely, normalisation theory predicts that: (i) when population level use increases, low risk adolescents will be more likely to use alcohol and cigarettes; and (ii) adolescents facing multiple risk factors will be equally likely to use alcohol and cigarettes, regardless of trends in population level use. The current study empirically tests these assumptions on five waves of nationally representative samples of Israeli Jewish youth. Five cross-sectional waves of data from the Israeli Health Behaviour in School-aged Children survey for Jewish 10th graders were used. Logistic regression models measured the impact of changes in population level use across waves on drunkenness and smoking, and their association with differing levels of risk factors. Between zero and two risk factors, the risk of drunkenness and smoking increases for each additional risk factor. When reaching two risk factors, added risk does not significantly increase the likelihood of smoking and drunkenness. Changes in population level drunkenness and smoking did not systematically relate to changes in the individual level relationship between risk factors and smoking and drunkenness. The pattern of results in this study provides strong evidence for the multiple risk factor model and inconsistent evidence for the normalisation theory. [Sznitman SR, Zlotnick C, Harel-Fisch Y. Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking? Drug Alcohol Rev 2016;35:424-432]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

The mathematical model that describes the periodic spouting of a geyser induced by boiling

NASA Astrophysics Data System (ADS)

Kagami, Hiroyuki

2017-04-01

We have derived and modified the dynamical model of a geyser induced by gas inflow and regular or irregular spouting dynamics of geysers induced by gas inflow has been reproduced by the model. On the other hand, though we have derived the dynamical model of a geyser induced by boiling, periodic change between the spouting state and the pause state has not been adequately modeled by the model. In this connection, concerning a geyser induced by gas inflow we have proposed the model as described below. Because pressure in the spouting tube decreases obeying to the Bernoulli's theorem when the spouting state begins and water in the spouting tube begins to flow, inflow of groundwater into the spouting tube occurs. When the amount of this inflow reaches a certain amount, the spouting state transforms to the pause state. In this study, by applying this idea to the dynamical model of a geyser induced by boiling, the periodic change between the spouting state and the pause state could be reappeared. As a result, the whole picture of the spouting mechanism of a geyser induced by boiling became clear. This research results would give hints on engineering repair in order to prevent the weakening or the depletion of the geyser. And this study would be also useful for protection of geysers as tourism and environmental resources.

Factor weighting in DRASTIC modeling.

PubMed

Pacheco, F A L; Pires, L M G R; Santos, R M B; Sanches Fernandes, L F

2015-02-01

Evaluation of aquifer vulnerability comprehends the integration of very diverse data, including soil characteristics (texture), hydrologic settings (recharge), aquifer properties (hydraulic conductivity), environmental parameters (relief), and ground water quality (nitrate contamination). It is therefore a multi-geosphere problem to be handled by a multidisciplinary team. The DRASTIC model remains the most popular technique in use for aquifer vulnerability assessments. The algorithm calculates an intrinsic vulnerability index based on a weighted addition of seven factors. In many studies, the method is subject to adjustments, especially in the factor weights, to meet the particularities of the studied regions. However, adjustments made by different techniques may lead to markedly different vulnerabilities and hence to insecurity in the selection of an appropriate technique. This paper reports the comparison of 5 weighting techniques, an enterprise not attempted before. The studied area comprises 26 aquifer systems located in Portugal. The tested approaches include: the Delphi consensus (original DRASTIC, used as reference), Sensitivity Analysis, Spearman correlations, Logistic Regression and Correspondence Analysis (used as adjustment techniques). In all cases but Sensitivity Analysis, adjustment techniques have privileged the factors representing soil characteristics, hydrologic settings, aquifer properties and environmental parameters, by leveling their weights to ≈4.4, and have subordinated the factors describing the aquifer media by downgrading their weights to ≈1.5. Logistic Regression predicts the highest and Sensitivity Analysis the lowest vulnerabilities. Overall, the vulnerability indices may be separated by a maximum value of 51 points. This represents an uncertainty of 2.5 vulnerability classes, because they are 20 points wide. Given this ambiguity, the selection of a weighting technique to integrate a vulnerability index may require additional

Stochastic model of transcription factor-regulated gene expression

NASA Astrophysics Data System (ADS)

Karmakar, Rajesh; Bose, Indrani

2006-09-01

We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes, gene A and gene B, which synthesize the TFs and the target gene proteins, respectively. We show through analytic calculations that the TF fluctuations have a significant effect on the distribution of the target gene protein levels when the mean TF level falls in the highest sensitive region of the dose-response curve. We further study the effect of reducing the copy number of gene A from two to one. The enhanced TF fluctuations yield results different from those in the deterministic case. The probability that the target gene protein level exceeds a threshold value is calculated with the knowledge of the probability density functions associated with the TF and target gene protein levels. Numerical simulation results for a more detailed stochastic model are shown to be in agreement with those obtained through analytic calculations. The relevance of these results in the context of the genetic disorder haploinsufficiency is pointed out. Some experimental observations on the haploinsufficiency of the tumour suppressor gene, Nkx 3.1, are explained with the help of the stochastic model of TF-regulated gene expression.

A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

PubMed Central

2014-01-01

Background Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. Results To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

A Reactive-Transport Model Describing Methanogen Growth and Methane Production in Diffuse Flow Vents at Axial Seamount

NASA Astrophysics Data System (ADS)

Algar, C. K.

2015-12-01

Hydrogenotrophic methanogenesis is an important mode of metabolism in deep-sea hydrothermal vents. Diffuse vent fluids often show a depletion in hydrogen with a corresponding increase in methane relative to pure-mixing of end member fluid and seawater, and genomic surveys show an enrichment in genetic sequences associated with known methanogens. However, because we cannot directly sample the subseafloor habitat where these organisms are living, constraining the size and activity of these populations remains a challenge and limits our ability to quantify the role they play in vent biogeochemistry. Reactive-transport modeling may provide a useful tool for approaching this problem. Here we present a reactive-transport model describing methane production along the flow-path of hydrothermal fluid from its high temperature end-member to diffuse venting at the seafloor. The model is set up to reflect conditions at several diffuse vents in the Axial Seamount. The model describes the growth of the two dominant thermophilic methanogens, Methanothermococcus and Methanocaldococcus, observed at Axial seamount. Monod and Arrhenius constants for Methanothermococcus thermolithotrophicus and Methanocaldococcus jannaschii were obtained for the model using chemostat and bottle experiments at varying temperatures. The model is used to investigate the influence of different mixing regimes on the subseafloor populations of these methanogens. By varying the model flow path length and subseafloor cell concentrations, and fitting to observed hydrogen and methane concentrations in the venting fluid, the subseafloor biomass, fluid residence time, and methane production rate can be constrained.

Neuropathology and Animal Models of Autism: Genetic and Environmental Factors

PubMed Central

Gadad, Bharathi S.; Young, Keith A.; German, Dwight C.

2013-01-01

Autism is a heterogeneous behaviorally defined neurodevelopmental disorder. It is defined by the presence of marked social deficits, specific language abnormalities, and stereotyped repetitive patterns of behavior. Because of the variability in the behavioral phenotype of the disorder among patients, the term autism spectrum disorder has been established. In the first part of this review, we provide an overview of neuropathological findings from studies of autism postmortem brains and identify the cerebellum as one of the key brain regions that can play a role in the autism phenotype. We review research findings that indicate possible links between the environment and autism including the role of mercury and immune-related factors. Because both genes and environment can alter the structure of the developing brain in different ways, it is not surprising that there is heterogeneity in the behavioral and neuropathological phenotypes of autism spectrum disorders. Finally, we describe animal models of autism that occur following insertion of different autism-related genes and exposure to environmental factors, highlighting those models which exhibit both autism-like behavior and neuropathology. PMID:24151553

Digital Materials - Evaluation of the Possibilities of using Selected Hyperelastic Models to Describe Constitutive Relations

NASA Astrophysics Data System (ADS)

Mańkowski, J.; Lipnicki, J.

2017-08-01

The authors tried to identify the parameters of numerical models of digital materials, which are a kind of composite resulting from the manufacture of the product in 3D printers. With the arrangement of several heads of the printer, the new material can result from mixing of materials with radically different properties, during the process of producing single layer of the product. The new material has properties dependent on the base materials properties and their proportions. Digital materials tensile characteristics are often non-linear and qualify to be described by hyperelastic materials models. The identification was conducted based on the results of tensile tests models, its various degrees coefficients of the polynomials to various degrees coefficients of the polynomials. The Drucker's stability criterion was also examined. Fourteen different materials were analyzed.

Performance of soil particle-size distribution models for describing deposited soils adjacent to constructed dams in the China Loess Plateau

NASA Astrophysics Data System (ADS)

Zhao, Pei; Shao, Ming-an; Horton, Robert

2011-02-01

Soil particle-size distributions (PSD) have been used to estimate soil hydraulic properties. Various parametric PSD models have been proposed to describe the soil PSD from sparse experimental data. It is important to determine which PSD model best represents specific soils. Fourteen PSD models were examined in order to determine the best model for representing the deposited soils adjacent to dams in the China Loess Plateau; these were: Skaggs (S-1, S-2, and S-3), fractal (FR), Jaky (J), Lima and Silva (LS), Morgan (M), Gompertz (G), logarithm (L), exponential (E), log-exponential (LE), Weibull (W), van Genuchten type (VG) as well as Fredlund (F) models. Four-hundred and eighty samples were obtained from soils deposited in the Liudaogou catchment. The coefficient of determination (R 2), the Akaike's information criterion (AIC), and the modified AIC (mAIC) were used. Based upon R 2 and AIC, the three- and four-parameter models were both good at describing the PSDs of deposited soils, and the LE, FR, and E models were the poorest. However, the mAIC in conjunction with R 2 and AIC results indicated that the W model was optimum for describing PSD of the deposited soils for emphasizing the effect of parameter number. This analysis was also helpful for finding out which model is the best one. Our results are applicable to the China Loess Plateau.

Early Childhood Teacher Preparation: A Tale of Authors and Multimedia, A Model of Technology Integration Described.

ERIC Educational Resources Information Center

Wetzel, Keith; McLean, S. V.

1997-01-01

Describes collaboration of two teacher educators, one in early childhood language arts and one in computers in education. Discusses advantages and disadvantages and extensions of this model, including how a college-wide survey revealed that students in teamed courses are better prepared to teach and learn with technology. (DR)

Brownian Motion at Lipid Membranes: A Comparison of Hydrodynamic Models Describing and Experiments Quantifying Diffusion within Lipid Bilayers.

PubMed

Block, Stephan

2018-05-22

The capability of lipid bilayers to exhibit fluid-phase behavior is a fascinating property, which enables, for example, membrane-associated components, such as lipids (domains) and transmembrane proteins, to diffuse within the membrane. These diffusion processes are of paramount importance for cells, as they are for example involved in cell signaling processes or the recycling of membrane components, but also for recently developed analytical approaches, which use differences in the mobility for certain analytical purposes, such as in-membrane purification of membrane proteins or the analysis of multivalent interactions. Here, models describing the Brownian motion of membrane inclusions (lipids, peptides, proteins, and complexes thereof) in model bilayers (giant unilamellar vesicles, black lipid membranes, supported lipid bilayers) are summarized and model predictions are compared with the available experimental data, thereby allowing for evaluating the validity of the introduced models. It will be shown that models describing the diffusion in freestanding (Saffman-Delbrück and Hughes-Pailthorpe-White model) and supported bilayers (the Evans-Sackmann model) are well supported by experiments, though only few experimental studies have been published so far for the latter case, calling for additional tests to reach the same level of experimental confirmation that is currently available for the case of freestanding bilayers.

A poroelastic model describing nutrient transport and cell stresses within a cyclically strained collagen hydrogel.

PubMed

Vaughan, Benjamin L; Galie, Peter A; Stegemann, Jan P; Grotberg, James B

2013-11-05

In the creation of engineered tissue constructs, the successful transport of nutrients and oxygen to the contained cells is a significant challenge. In highly porous scaffolds subject to cyclic strain, the mechanical deformations can induce substantial fluid pressure gradients, which affect the transport of solutes. In this article, we describe a poroelastic model to predict the solid and fluid mechanics of a highly porous hydrogel subject to cyclic strain. The model was validated by matching the predicted penetration of a bead into the hydrogel from the model with experimental observations and provides insight into nutrient transport. Additionally, the model provides estimates of the wall-shear stresses experienced by the cells embedded within the scaffold. These results provide insight into the mechanics of and convective nutrient transport within a cyclically strained hydrogel, which could lead to the improved design of engineered tissues. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A physiological pharmacokinetic model describing the disposition of lycopene in healthy men.

PubMed

Diwadkar-Navsariwala, Veda; Novotny, Janet A; Gustin, David M; Sosman, Jeffery A; Rodvold, Keith A; Crowell, James A; Stacewicz-Sapuntzakis, Maria; Bowen, Phyllis E

2003-10-01

A physiological pharmacokinetic model was developed to describe the disposition of lycopene, delivered as a tomato beverage formulation in five graded doses (10, 30, 60, 90, or 120 mg), for a phase I study in healthy male subjects (five per dose). Blood was collected before dose administration (0 h) and at scheduled intervals until 672 h. Serum concentrations of carotenoids and vitamins were measured by high performance liquid chromatography analysis. The model was comprised of seven compartments: gastrointestinal tract, enterocytes, chylomicrons, plasma lipoproteins, fast-turnover liver, slow-turnover tissues, and a delay compartment before the enterocytes. As predicted, the percent absorption at the 10 mg dose (33.9 +/- 8.1%) was significantly greater than at the higher doses; however, the amount of lycopene absorbed (mg) was not statistically different (mean: 4.69 +/- 0.55 mg) between doses, suggesting a possible saturation of absorptive mechanisms. The slow-turnover tissue compartment served as a slow-depleting reservoir for lycopene, and the liver represented the fast-turnover pool. Independent of dose, 80% of the subjects absorbed less than 6 mg of lycopene. This may have important implications for planning clinical trials with pharmacological doses of lycopene in cancer control and prevention if absorption saturation occurs at levels that are already being consumed in the population.

[Individual tree diameter increment model for natural Betula platyphylla forests based on meteorological factors].

PubMed

Zhang, Hai Ping; Li, Feng Ri; Dong, Li Hu; Liu, Qiang

2017-06-18

Based on the 212 re-measured permanent plots for natural Betula platyphylla fore-sts in Daxing'an Mountains and Xiaoxing'an Mountains and 30 meteorological stations data, an individual tree growth model based on meteorological factors was constructed. The differences of stand and meteorological factors between Daxing'an Mountains and Xiaoxing'an Mountains were analyzed and the diameter increment model including the regional effects was developed by dummy variable approach. The results showed that the minimum temperature (T g min ) and mean precipitation (P g m ) in growing season were the main meteorological factors which affected the diameter increment in the two study areas. T g min and P g m were positively correlated with the diameter increment, but the influence strength of T g min was obviously different between the two research areas. The adjusted coefficient of determination (R a 2 ) of the diameter increment model with meteorological factors was 0.56 and had an 11% increase compared to the one without meteorological factors. It was concluded that meteorological factors could well explain the diameter increment of B. platyphylla. R a 2 of the model with regional effects was 0.59, and increased by 18% compared to the one without regional effects, and effectively solved the incompatible problem of parameters between the two research areas. The validation results showed that the individual tree diameter growth model with regional effect had the best prediction accuracy in estimating the diameter increment of B. platyphylla. The mean error, mean absolute error, mean error percent and mean prediction error percent were 0.0086, 0.4476, 5.8% and 20.0%, respectively. Overall, dummy variable model of individual tree diameter increment based on meteorological factors could well describe the diameter increment process of natural B. platyphylla in Daxing'an Mountains and Xiaoxing'an Mountains.

Introducing mixotrophy into a biogeochemical model describing an eutrophied coastal ecosystem: The Southern North Sea

NASA Astrophysics Data System (ADS)

Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie

2017-04-01

Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates, for the first time, the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mole N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3 to 32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. The effect of non-constitutive mixotrophy depends on light and affects the ecosystem functioning in terms of annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that different forms of mixotrophy have different impacts on system dynamics and it is thus important to

Yeast for Mathematicians: A Ferment of Discovery and Model Competition to Describe Data.

PubMed

Lewis, Matthew; Powell, James

2017-02-01

In addition to the memorization, algorithmic skills and vocabulary which are the default focus in many mathematics classrooms, professional mathematicians are expected to creatively apply known techniques, construct new mathematical approaches and communicate with and about mathematics. We propose that students can learn these professional, higher-level skills through Laboratory Experiences in Mathematical Biology which put students in the role of mathematics researcher creating mathematics to describe and understand biological data. Here we introduce a laboratory experience centered on yeast (Saccharomyces cerevisiae) growing in a small capped flask with a jar to collect carbon dioxide created during yeast growth and respiration. The lab requires no specialized equipment and can easily be run in the context of a college math class. Students collect data and develop mathematical models to explain the data. To help place instructors in the role of mentor/collaborator (as opposed to jury/judge), we facilitate the lab using model competition judged via Bayesian Information Criterion. This article includes details about the class activity conducted, student examples and pedagogical strategies for success.

LiveDescribe: Can Amateur Describers Create High-Quality Audio Description?

ERIC Educational Resources Information Center

Branje, Carmen J.; Fels, Deborah I.

2012-01-01

Introduction: The study presented here evaluated the usability of the audio description software LiveDescribe and explored the acceptance rates of audio description created by amateur describers who used LiveDescribe to facilitate the creation of their descriptions. Methods: Twelve amateur describers with little or no previous experience with…

Charge-exchange plasma environment for an ion drive spacecraft. [a model for describing mercury ion engines and its effect on spacecraft subsystems

NASA Technical Reports Server (NTRS)

Kaufman, H. R.; Carruth, M. R., Jr.

1979-01-01

The charge exchange plasma environment around a spacecraft that uses mercury ion thrusters for propulsion is described. The interactions between the plasma environment and the spacecraft are determined and a model which describes the propagation of the mercury charge exchange plasma is discussed. The model is extended to describe the flow of the molybdenum component of the charge exchange plasma. The uncertainties in the models for various conditions are discussed and current drain to the solar array, charge exchange plasma material deposition, and the effects of space plasma on the charge exchange plasma propagation are addressed.

Rapid-relocation model for describing high-fluence retention of rare gases implanted in solids

NASA Astrophysics Data System (ADS)

Wittmaack, K.

2009-09-01

to be due to bombardment induced relocation and reemission, only the remaining 10% (or less) can be attributed to sputter erosion. The relocation efficiency is interpreted as the 'speed' of radiation enhanced diffusion towards the surface. The directionality of diffusion is attributed to the gradient of the defect density on the large-depth side of the damage distribution where most of the implanted rare gas atoms come to rest. Based on SRIM calculations, two representative parameters are defined, the peak number of lattice displacements, Nd,m, and the spacing, △ zr,d, between the peaks of the range and the damage distributions. Support in favour of rapid rare gas relocation by radiation enhanced diffusion is provided by the finding that the relocation efficiencies for Ar and Xe, which vary by up to one order of magnitude, scale as Ψ=kN/Δz, independent to the implantation energy (10-80 keV Ar, 10-500 keV Xe), within an error margin of only ± 15%. The parameter k contains the properties of the implanted rare gas atoms. A recently described computer simulation model, which assumed that the pressure established by the implanted gas drives reemission, is shown to reproduce measured Xe profiles quite well, but only at that energy at which the fitting parameter of the model was determined (140 keV). Using the same parameter at other energies, deviations by up to a factor of four are observed.

Phosphate adsorption on hematite, kaolinite, and kaolinite-hematite (k-h) systems as described by a constant capacitance model

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

Ioannou, A.; Dimirkou, A.

1997-08-01

The constant capacitance model was used to describe phosphate adsorption on hematite, kaolinite, and a kaolinite-hematite system (k-h). The model assumes a ligand exchange mechanism and considers the charge on both adsorbate and adsorbent. The model is shown to provide a quantitative description of phosphate adsorption on these, including the effect of varying pH values. The computer program Ma-Za 2, a program that fits equilibrium constants to experimental data using an optimization technique, was used to obtain optimal values for the anion surface complexation constants on hematite, kaolinite, and a kaolinite-hematite system, while the PC program Ma-Za 1 in Q-Basicmore » language was used for the application of the constant capacitance model. The model represented adsorption of phosphate anions well over the entire pH range studied (3.8--9.0). The main advantage of the model is its ability to represent changes in anion adsorption occurring with changes in pH. Extension of the model to describe phosphate adsorption in a mixed system, such as the kaolinite-hematite system, using the surface protonation-dissociation constant of hematite was qualitatively successful. In mixed system the model reproduced the shape of the adsorption isotherms well over the pH range 3.8--9.0. However, phosphate adsorption was overestimated. The hematite and the kaolinite-hematite system were synthesized and identified by X-ray, NMR, and FT-IR spectroscopy.« less

Vibrational energy transport in acetylbenzonitrile described by an ab initio-based quantum tier model

NASA Astrophysics Data System (ADS)

Fujisaki, Hiroshi; Yagi, Kiyoshi; Kikuchi, Hiroto; Takami, Toshiya; Stock, Gerhard

2017-01-01

Performing comprehensive quantum-chemical calculations, a vibrational Hamiltonian of acetylbenzonitrile is constructed, on the basis of which a quantum-mechanical "tier model" is developed that describes the vibrational dynamics following excitation of the CN stretch mode. Taking into account 36 vibrational modes and cubic and quartic anharmonic couplings between up to three different modes, the tier model calculations are shown to qualitatively reproduce the main findings of the experiments of Rubtsov and coworkers (2011), including the energy relaxation of the initially excited CN mode and the structure-dependent vibrational transport. Moreover, the calculations suggest that the experimentally measured cross-peak among the CN and CO modes does not correspond to direct excitation of the CO normal mode but rather reflects excited low-frequency vibrations that anharmonically couple to the CO mode. Complementary quasiclassical trajectory calculations are found to be in good overall agreement with the quantum calculations.

A visual metaphor describing neural dynamics in schizophrenia.

PubMed

van Beveren, Nico J M; de Haan, Lieuwe

2008-07-09

In many scientific disciplines the use of a metaphor as an heuristic aid is not uncommon. A well known example in somatic medicine is the 'defense army metaphor' used to characterize the immune system. In fact, probably a large part of the everyday work of doctors consists of 'translating' scientific and clinical information (i.e. causes of disease, percentage of success versus risk of side-effects) into information tailored to the needs and capacities of the individual patient. The ability to do so in an effective way is at least partly what makes a clinician a good communicator. Schizophrenia is a severe psychiatric disorder which affects approximately 1% of the population. Over the last two decades a large amount of molecular-biological, imaging and genetic data have been accumulated regarding the biological underpinnings of schizophrenia. However, it remains difficult to understand how the characteristic symptoms of schizophrenia such as hallucinations and delusions are related to disturbances on the molecular-biological level. In general, psychiatry seems to lack a conceptual framework with sufficient explanatory power to link the mental- and molecular-biological domains. Here, we present an essay-like study in which we propose to use visualized concepts stemming from the theory on dynamical complex systems as a 'visual metaphor' to bridge the mental- and molecular-biological domains in schizophrenia. We first describe a computer model of neural information processing; we show how the information processing in this model can be visualized, using concepts from the theory on complex systems. We then describe two computer models which have been used to investigate the primary theory on schizophrenia, the neurodevelopmental model, and show how disturbed information processing in these two computer models can be presented in terms of the visual metaphor previously described. Finally, we describe the effects of dopamine neuromodulation, of which disturbances have

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878

A new settling velocity model to describe secondary sedimentation.

PubMed

Ramin, Elham; Wágner, Dorottya S; Yde, Lars; Binning, Philip J; Rasmussen, Michael R; Mikkelsen, Peter Steen; Plósz, Benedek Gy

2014-12-01

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Testing alternative factor models of PTSD and the robustness of the dysphoria factor.

PubMed

Elklit, Ask; Armour, Cherie; Shevlin, Mark

2010-01-01

This study first aimed to examine the structure of self-reported posttraumatic stress disorder (PTSD) symptoms using three different samples. The second aim of the paper was to test the robustness of the factor analytic model when depression scores were controlled for. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The best fitting model was subsequently re-fitted to the data after including a depression variable. The analyses were based on responses from 973 participants across three samples. Sample 1 consisted of 633 parents who were members of 'The National Association of Infant Death' and who had lost a child. Sample 2 consisted of 227 victims of rape, who completed a questionnaire within 4 weeks of the rape. Each respondent had been in contact with the Centre for Rape Victims (CRV) at the Aarhus University Hospital, Denmark. Sample 3 consisted of 113 refugees resident in Denmark. All participants had been referred to a treatment centre which focused on rehabilitating refugees through treatment for psychosocial integration problems (RRCF: Rehabliterings og Revliderings Centre for Flygtninge). In total 500 participants received a diagnosis of PTSD/sub-clinical PTSD (Sample 1, N=214; 2, N=176; 3, N=110). A correlated four-factor model with re-experiencing, avoidance, dysphoria, and arousal factors provided the best fit to the sample data. The average attenuation in the factor loadings was highest for the dysphoria factor (M=-.26, SD=.11) compared to the re-experiencing (M=-.14, SD=.18), avoidance (M=-.10, SD=.21), and arousal (M=-.09, SD=.13) factors. With regards to the best fitting factor model these results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings. The attenuation of dysphoria factor loadings suggests that dysphoria is a non-specific component of

A comprehensive model for diagnosing the causes of individual medical performance problems: skills, knowledge, internal, past and external factors (SKIPE).

PubMed

Norfolk, Tim; Siriwardena, A Niroshan

2013-01-01

This discussion paper describes a new and comprehensive model for diagnosing the causes of individual medical performance problems: SKIPE (skills, knowledge, internal, past and external factors). This builds on a previous paper describing a unifying theory of clinical practice, the RDM-p model, which captures the primary skill sets required for effective medical performance (relationship, diagnostics and management), and the professionalism that needs to underpin them. The SKIPE model is currently being used, in conjunction with the RDM-p model, for the in-depth assessment and management of doctors whose performance is a cause for concern.

The asset pricing model of musharakah factors

NASA Astrophysics Data System (ADS)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

2015-02-01

The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

Homogeneous Diffusion Solid Model as a Realistic Approach to Describe Adsorption onto Materials with Different Geometries.

PubMed

Sabio, E; Zamora, F; González-García, C M; Ledesma, B; Álvarez-Murillo, A; Román, S

2016-12-01

In this work, the adsorption kinetics of p-nitrophenol (PNP) onto several commercial activated carbons (ACs) with different textural and geometrical characteristics was studied. For this aim, a homogeneous diffusion solid model (HDSM) was used, which does take the adsorbent shape into account. The HDSM was solved by means of the finite element method (FEM) using the commercial software COMSOL. The different kinetic patterns observed in the experiments carried out can be described by the developed model, which shows that the sharp drop of adsorption rate observed in some samples is caused by the formation of a concentration wave. The model allows one to visualize the changes in concentration taking place in both liquid and solid phases, which enables us to link the kinetic behaviour with the main features of the carbon samples.

Introducing mixotrophy into a biogeochemical model describing an eutrophied coastal ecosystem: The Southern North Sea

NASA Astrophysics Data System (ADS)

Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie

2017-09-01

Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mol N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3-32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. Under high irradiance, non-constitutive mixotrophy appreciably increases annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. In this ecosystem, non-constitutive mixotrophy is also observed to have an indirect stimulating effect on diatoms. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that contrasting forms of mixotrophy have different

Stochastic GARCH dynamics describing correlations between stocks

NASA Astrophysics Data System (ADS)

Prat-Ortega, G.; Savel'ev, S. E.

2014-09-01

The ARCH and GARCH processes have been successfully used for modelling price dynamics such as stock returns or foreign exchange rates. Analysing the long range correlations between stocks, we propose a model, based on the GARCH process, which is able to describe the main characteristics of the stock price correlations, including the mean, variance, probability density distribution and the noise spectrum.

Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy

PubMed Central

Melén, Erik; Bergström, Anna; Torabi Moghadam, Behrooz; Pulkkinen, Ville; Acevedo, Nathalie; Orsmark Pietras, Christina; Ege, Markus; Braun-Fahrländer, Charlotte; Riedler, Josef; Doekes, Gert; Kabesch, Michael; van Hage, Marianne; Kere, Juha; Scheynius, Annika; Söderhäll, Cilla; Pershagen, Göran; Komorowski, Jan

2013-01-01

Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children) and BAMSE (a Swedish birth-cohort including 2033 children), genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6) and 3.2 (95% CI 2.0-5.0) in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0) of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies of etiological

Can a Linear Sigma Model Describe Walking Gauge Theories at Low Energies?

NASA Astrophysics Data System (ADS)

Gasbarro, Andrew

2018-03-01

In recent years, many investigations of confining Yang Mills gauge theories near the edge of the conformal window have been carried out using lattice techniques. These studies have revealed that the spectrum of hadrons in nearly conformal ("walking") gauge theories differs significantly from the QCD spectrum. In particular, a light singlet scalar appears in the spectrum which is nearly degenerate with the PNGBs at the lightest currently accessible quark masses. This state is a viable candidate for a composite Higgs boson. Presently, an acceptable effective field theory (EFT) description of the light states in walking theories has not been established. Such an EFT would be useful for performing chiral extrapolations of lattice data and for serving as a bridge between lattice calculations and phenomenology. It has been shown that the chiral Lagrangian fails to describe the IR dynamics of a theory near the edge of the conformal window. Here we assess a linear sigma model as an alternate EFT description by performing explicit chiral fits to lattice data. In a combined fit to the Goldstone (pion) mass and decay constant, a tree level linear sigma model has a Χ2/d.o.f. = 0.5 compared to Χ2/d.o.f. = 29.6 from fitting nextto-leading order chiral perturbation theory. When the 0++ (σ) mass is included in the fit, Χ2/d.o.f. = 4.9. We remark on future directions for providing better fits to the σ mass.

A dynamic social systems model for considering structural factors in HIV prevention and detection

PubMed Central

Latkin, Carl; Weeks, Margaret; Glasman, Laura; Galletly, Carol; Albarracin, Dolores

2010-01-01

We present a model for HIV-related behaviors that emphasizes the dynamic and social nature of the structural factors that influence HIV prevention and detection. Key structural dimensions of the model include resources, science and technology, formal social control, informal social influences and control, social interconnectedness, and settings. These six dimensions can be conceptualized on macro, meso, and micro levels. Given the inherent complexity of structural factors and their interrelatedness, HIV prevention interventions may focus on different levels and dimensions. We employ a systems perspective to describe the interconnected and dynamic processes of change among social systems and their components. The topics of HIV testing and safer injection facilities are analyzed using this structural framework. Finally, we discuss methodological issues in the development and evaluation of structural interventions for HIV prevention and detection. PMID:20838871

Hierarchical and coupling model of factors influencing vessel traffic flow.

PubMed

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Factors Affecting Retention Behavior: A Model To Predict At-Risk Students. AIR 1997 Annual Forum Paper.

ERIC Educational Resources Information Center

Sadler, William E.; Cohen, Frederic L.; Kockesen, Levent

This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

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

Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V., E-mail: Yu.Kuyanov@gmail.com

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description ofmore » data are schematically shown. The DaMoScope codes are freely available.« less

Hierarchical and coupling model of factors influencing vessel traffic flow

PubMed Central

Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747

Pharmacodynamic Model To Describe the Concentration-Dependent Selection of Cefotaxime-Resistant Escherichia coli

PubMed Central

Olofsson, Sara K.; Geli, Patricia; Andersson, Dan I.; Cars, Otto

2005-01-01

Antibiotic dosing regimens may vary in their capacity to select mutants. Our hypothesis was that selection of a more resistant bacterial subpopulation would increase with the time within a selective window (SW), i.e., when drug concentrations fall between the MICs of two strains. An in vitro kinetic model was used to study the selection of two Escherichia coli strains with different susceptibilities to cefotaxime. The bacterial mixtures were exposed to cefotaxime for 24 h and SWs of 1, 2, 4, 8, and 12 h. A mathematical model was developed that described the selection of preexisting and newborn mutants and the post-MIC effect (PME) as functions of pharmacokinetic parameters. Our main conclusions were as follows: (i) the selection between preexisting mutants increased with the time within the SW; (ii) the emergence and selection of newborn mutants increased with the time within the SW (with a short time, only 4% of the preexisting mutants were replaced by newborn mutants, compared to the longest times, where 100% were replaced); and (iii) PME increased with the area under the concentration-time curve (AUC) and was slightly more pronounced with a long elimination half-life (T1/2) than with a short T1/2 situation, when AUC is fixed. We showed that, in a dynamic competition between strains with different levels of resistance, the appearance of newborn high-level resistant mutants from the parental strains and the PME can strongly affect the outcome of the selection and that pharmacodynamic models can be used to predict the outcome of resistance development. PMID:16304176

An alternative method for centrifugal compressor loading factor modelling

NASA Astrophysics Data System (ADS)

Galerkin, Y.; Drozdov, A.; Rekstin, A.; Soldatova, K.

2017-08-01

The loading factor at design point is calculated by one or other empirical formula in classical design methods. Performance modelling as a whole is out of consideration. Test data of compressor stages demonstrates that loading factor versus flow coefficient at the impeller exit has a linear character independent of compressibility. Known Universal Modelling Method exploits this fact. Two points define the function - loading factor at design point and at zero flow rate. The proper formulae include empirical coefficients. A good modelling result is possible if the choice of coefficients is based on experience and close analogs. Earlier Y. Galerkin and K. Soldatova had proposed to define loading factor performance by the angle of its inclination to the ordinate axis and by the loading factor at zero flow rate. Simple and definite equations with four geometry parameters were proposed for loading factor performance calculated for inviscid flow. The authors of this publication have studied the test performance of thirteen stages of different types. The equations are proposed with universal empirical coefficients. The calculation error lies in the range of plus to minus 1,5%. The alternative model of a loading factor performance modelling is included in new versions of the Universal Modelling Method.

Evaluation of a cross contamination model describing transfer of Salmonella spp. and Listeria monocytogenes during grinding of pork and beef.

PubMed

Møller, C O A; Sant'Ana, A S; Hansen, S K H; Nauta, M J; Silva, L P; Alvarenga, V O; Maffei, D; Silva, F F P; Lopes, J T; Franco, B D G M; Aabo, S; Hansen, T B

2016-06-02

In a previous study, a model was developed to describe the transfer and survival of Salmonella during grinding of pork (Møller, C.O.A., Nauta, M.J., Christensen, B.B., Dalgaard, P., Hansen, T.B., 2012. Modelling transfer of Salmonella typhimurium DT104 during simulation of grinding of pork. Journal of Applied Microbiology 112 (1), 90-98). The robustness of this model is now evaluated by studying its performance for predicting the transfer and survival of Salmonella spp. and Listeria monocytogenes during grinding of different types of meat (pork and beef), using two different grinders, different sizes and different numbers of pieces of meats to be ground. A total of 19 grinding trials were collected. Acceptable Simulation Zone (ASZ), visual inspection of the data, Quantitative Microbiological Risk Assessment (QMRA), as well as the Total Transfer Potential (TTP) were used as approaches to evaluate model performance and to access the quality of the cross contamination model predictions. Using the ASZ approach and considering that 70% of the observed counts have to be inside a defined acceptable zone of ±0.5 log10CFU per portion, it was found that the cross contamination parameters suggested by Møller et al. (2012) were not able to describe all 19 trials. However, for each of the collected grinding trials, the transfer event was well described when fitted to the model structure proposed by Møller et al. (2012). Parameter estimates obtained by fitting observed trials performed at different conditions, such as size and number of pieces of meat to be ground, may not be applied to describe cross contamination of unlike processing. Nevertheless, the risk estimates, as well as the TTP, revealed that the risk of disease may be reduced when the grinding of meat is performed in a grinder made of stainless steel (for all surfaces in contact with the meat), using a well-sharpened knife and holding at room temperatures lower than 4°C. Copyright © 2016 Elsevier B.V. All

Model error estimation for distributed systems described by elliptic equations

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1983-01-01

A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.

A Dynamic Energy Budget (DEB) model to describe Laternula elliptica (King, 1832) seasonal feeding and metabolism

PubMed Central

Ahn, In-Young; Guillaumot, Charlène; Danis, Bruno

2017-01-01

Antarctic marine organisms are adapted to an extreme environment, characterized by a very low but stable temperature and a strong seasonality in food availability arousing from variations in day length. Ocean organisms are particularly vulnerable to global climate change with some regions being impacted by temperature increase and changes in primary production. Climate change also affects the biotic components of marine ecosystems and has an impact on the distribution and seasonal physiology of Antarctic marine organisms. Knowledge on the impact of climate change in key species is highly important because their performance affects ecosystem functioning. To predict the effects of climate change on marine ecosystems, a holistic understanding of the life history and physiology of Antarctic key species is urgently needed. DEB (Dynamic Energy Budget) theory captures the metabolic processes of an organism through its entire life cycle as a function of temperature and food availability. The DEB model is a tool that can be used to model lifetime feeding, growth, reproduction, and their responses to changes in biotic and abiotic conditions. In this study, we estimate the DEB model parameters for the bivalve Laternula elliptica using literature-extracted and field data. The DEB model we present here aims at better understanding the biology of L. elliptica and its levels of adaptation to its habitat with a special focus on food seasonality. The model parameters describe a metabolism specifically adapted to low temperatures, with a low maintenance cost and a high capacity to uptake and mobilise energy, providing this organism with a level of energetic performance matching that of related species from temperate regions. It was also found that L. elliptica has a large energy reserve that allows enduring long periods of starvation. Additionally, we applied DEB parameters to time-series data on biological traits (organism condition, gonad growth) to describe the effect of a

A Dynamic Energy Budget (DEB) model to describe Laternula elliptica (King, 1832) seasonal feeding and metabolism.

PubMed

Agüera, Antonio; Ahn, In-Young; Guillaumot, Charlène; Danis, Bruno

2017-01-01

Antarctic marine organisms are adapted to an extreme environment, characterized by a very low but stable temperature and a strong seasonality in food availability arousing from variations in day length. Ocean organisms are particularly vulnerable to global climate change with some regions being impacted by temperature increase and changes in primary production. Climate change also affects the biotic components of marine ecosystems and has an impact on the distribution and seasonal physiology of Antarctic marine organisms. Knowledge on the impact of climate change in key species is highly important because their performance affects ecosystem functioning. To predict the effects of climate change on marine ecosystems, a holistic understanding of the life history and physiology of Antarctic key species is urgently needed. DEB (Dynamic Energy Budget) theory captures the metabolic processes of an organism through its entire life cycle as a function of temperature and food availability. The DEB model is a tool that can be used to model lifetime feeding, growth, reproduction, and their responses to changes in biotic and abiotic conditions. In this study, we estimate the DEB model parameters for the bivalve Laternula elliptica using literature-extracted and field data. The DEB model we present here aims at better understanding the biology of L. elliptica and its levels of adaptation to its habitat with a special focus on food seasonality. The model parameters describe a metabolism specifically adapted to low temperatures, with a low maintenance cost and a high capacity to uptake and mobilise energy, providing this organism with a level of energetic performance matching that of related species from temperate regions. It was also found that L. elliptica has a large energy reserve that allows enduring long periods of starvation. Additionally, we applied DEB parameters to time-series data on biological traits (organism condition, gonad growth) to describe the effect of a

Review of Railgun Modeling Techniques: The Computation of Railgun Force and Other Key Factors

NASA Astrophysics Data System (ADS)

Eckert, Nathan James

Currently, railgun force modeling either uses the simple "railgun force equation" or finite element methods. It is proposed here that a middle ground exists that does not require the solution of partial differential equations, is more readily implemented than finite element methods, and is more accurate than the traditional force equation. To develop this method, it is necessary to examine the core railgun factors: power supply mechanisms, the distribution of current in the rails and in the projectile which slides between them (called the armature), the magnetic field created by the current flowing through these rails, the inductance gradient (a key factor in simplifying railgun analysis, referred to as L'), the resultant Lorentz force, and the heating which accompanies this action. Common power supply technologies are investigated, and the shape of their current pulses are modeled. The main causes of current concentration are described, and a rudimentary method for computing current distribution in solid rails and a rectangular armature is shown to have promising accuracy with respect to outside finite element results. The magnetic field is modeled with two methods using the Biot-Savart law, and generally good agreement is obtained with respect to finite element methods (5.8% error on average). To get this agreement, a factor of 2 is added to the original formulation after seeing a reliable offset with FEM results. Three inductance gradient calculations are assessed, and though all agree with FEM results, the Kerrisk method and a regression analysis method developed by Murugan et al. (referred to as the LRM here) perform the best. Six railgun force computation methods are investigated, including the traditional railgun force equation, an equation produced by Waindok and Piekielny, and four methods inspired by the work of Xu et al. Overall, good agreement between the models and outside data is found, but each model's accuracy varies significantly between

Application of interleaving models to describe intrusive layers in the Deep Polar Water of the Arctic Basin

NASA Astrophysics Data System (ADS)

Zhurbas, Nataliya; Kuzmina, Natalia; Lyzhkov, Dmitry; Izvekova, Yulia N.

2016-04-01

Interleaving models of pure thermohaline and baroclinic frontal zones of finite width are applied to describe intrusions at the fronts found in the upper part of the Deep Polar Water, the Eurasian basin, under stable-stable thermohaline stratification. It is assumed that differential mixing is the main mechanism of the intrusion formation. Different parameterizations of differential mixing (Merrryfield, 2002; Kuzmina et al., 2011) are used in the models. Important parameters of interleaving such as the growth rate, vertical scale, and slope of the most unstable modes are calculated. It is found that the interleaving model of a pure thermohaline front can satisfactory describe the important parameters of intrusions observed at a thermohaline, very low baroclinicity front in the Eurasian basin, just in accordance to Merryfield (2002) findings. In the case of baroclinic front, satisfactory agreement over all the interleaving parameters is found between the model calculations and observations provided that the vertical momentum diffusivity significantly exceeds the corresponding mass diffusivity. Under specific (reasonable) constraints of the vertical momentum diffusivity, the most unstable mode has a vertical scale approximately two-three times smaller than the vertical scale of the observed intrusions. A thorough discussion of the results is presented. References Kuzmina N., Rudels B., Zhurbas V., Stipa T. On the structure and dynamical features of intrusive layering in the Eurasian Basin in the Arctic Ocean. J. Geophys. Res., 2011, 116, C00D11, doi:10.1029/2010JC006920. Merryfield W. J. Intrusions in Double-Diffusively Stable Arctic Waters: Evidence for Differential mixing? J. Phys. Oceanogr., 2002, 32, 1452-1439.

Matematical modeling of galophytic plants productivity taking into account the temperature factor and soil salinity level

NASA Astrophysics Data System (ADS)

Natalia, Slyusar; Pisman, Tamara; Pechurkin, Nikolai S.

Among the most challenging tasks faced by contemporary ecology is modeling of biological production process in different plant communities. The difficulty of the task is determined by the complexity of the study material. Models showing the influence of climate and climate change on plant growth, which would also involve soil site parameters, could be of both practical and theoretical interest. In this work a mathematical model has been constructed to describe the growth dynamics of different plant communities of halophytic meadows as dependent upon the temperature factor and soil salinity level, which could be further used to predict yields of these plant communities. The study was performed on plants of halophytic meadows in the coastal area of Lake of the Republic of Khakasia in 2004 - 2006. Every plant community grew on the soil of a different level of salinity - the amount of the solid residue of the saline soil aqueous extract. The mathematical model was analyzed using field data of 2004 and 2006, the years of contrasting air temperatures. Results of model investigations show that there is a correlation between plant growth and the temperature of the air for plant communities growing on soils containing the lowest (0.1Thus, results of our study, in which we used a mathematical model describing the development of plant communities of halophytic meadows and field measurements, suggest that both climate conditions (temperature) and ecological factors of the plants' habitat (soil salinity level) should be taken into account when constructing models for predicting crop yields.

A biokinetic model to describe consequences of inhibition/stimulation in DNA-proofreading and repair-1. Development of the model.

PubMed

Haschke, H

2001-10-21

A biokinetic model is described which deals with the mathematical consequences of the inhibition or stimulation of DNA proofreading. It demonstrates the development of the number of DNA mismatch-dependent cells (e.g. cells with a malignant phenotype), where such mismatches arise by the in situ interaction of various substances with nucleotides of the DNA. The model can test for consequences by a logic gating on an "if-then" type of analysis in relation to the separate and consecutive processes of proofreading and repair. In particular, the consequences are considered in cases where either (i) the efficacy of proofreading and repair are reduced/prevented (inhibited) or (ii) are increased by some form of stimulation. On the chosen kinetic parameters, the model is accessible to manipulation as new data arising from further investigations become available and are introduced. The model is based on recently published data which show that an increased "mutant fraction" (see note on terms) arises in DNA replication when intracellular nucleotide pools show "asymmetries" (see note on terms). Extraordinarily high mutant fractions can be predicted/have been recorded in the presence of proofreading inhibitors. The model expresses data in mathematical terms of the competition between the development of mismatch-dependent cells and those with authentic genetic information. (Feedback and metastasis-effects and those of wild-type replicates are included.) A computerized (numerical) integration of the corresponding set of differential equations is offered. (A diskette with the program CANCER.xls is available upon request.) Copyright 2001 Academic Press

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Human Factors Model

NASA Technical Reports Server (NTRS)

1993-01-01

Jack is an advanced human factors software package that provides a three dimensional model for predicting how a human will interact with a given system or environment. It can be used for a broad range of computer-aided design applications. Jack was developed by the computer Graphics Research Laboratory of the University of Pennsylvania with assistance from NASA's Johnson Space Center, Ames Research Center and the Army. It is the University's first commercial product. Jack is still used for academic purposes at the University of Pennsylvania. Commercial rights were given to Transom Technologies, Inc.

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models.

PubMed

Flores-Alsina, Xavier; Kazadi Mbamba, Christian; Solon, Kimberly; Vrecko, Darko; Tait, Stephan; Batstone, Damien J; Jeppsson, Ulf; Gernaey, Krist V

2015-11-15

There is a growing interest within the Wastewater Treatment Plant (WWTP) modelling community to correctly describe physico-chemical processes after many years of mainly focusing on biokinetics. Indeed, future modelling needs, such as a plant-wide phosphorus (P) description, require a major, but unavoidable, additional degree of complexity when representing cationic/anionic behaviour in Activated Sludge (AS)/Anaerobic Digestion (AD) systems. In this paper, a plant-wide aqueous phase chemistry module describing pH variations plus ion speciation/pairing is presented and interfaced with industry standard models. The module accounts for extensive consideration of non-ideality, including ion activities instead of molar concentrations and complex ion pairing. The general equilibria are formulated as a set of Differential Algebraic Equations (DAEs) instead of Ordinary Differential Equations (ODEs) in order to reduce the overall stiffness of the system, thereby enhancing simulation speed. Additionally, a multi-dimensional version of the Newton-Raphson algorithm is applied to handle the existing multiple algebraic inter-dependencies. The latter is reinforced with the Simulated Annealing method to increase the robustness of the solver making the system not so dependent of the initial conditions. Simulation results show pH predictions when describing Biological Nutrient Removal (BNR) by the activated sludge models (ASM) 1, 2d and 3 comparing the performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) treatment plant configuration under different anaerobic/anoxic/aerobic conditions. The same framework is implemented in the Benchmark Simulation Model No. 2 (BSM2) version of the Anaerobic Digestion Model No. 1 (ADM1) (WWTP3) as well, predicting pH values at different cationic/anionic loads. In this way, the general applicability/flexibility of the proposed approach is demonstrated, by implementing the aqueous phase chemistry module in some

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis.

PubMed

Kulakovskiy, Ivan V; Vorontsov, Ilya E; Yevshin, Ivan S; Sharipov, Ruslan N; Fedorova, Alla D; Rumynskiy, Eugene I; Medvedeva, Yulia A; Magana-Mora, Arturo; Bajic, Vladimir B; Papatsenko, Dmitry A; Kolpakov, Fedor A; Makeev, Vsevolod J

2018-01-04

We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Application of a Mathematical Model to Describe the Effects of Chlorpyrifos on Caenorhabditis elegans Development

PubMed Central

Boyd, Windy A.; Smith, Marjolein V.; Kissling, Grace E.; Rice, Julie R.; Snyder, Daniel W.; Portier, Christopher J.; Freedman, Jonathan H.

2009-01-01

Background The nematode Caenorhabditis elegans is being assessed as an alternative model organism as part of an interagency effort to develop better means to test potentially toxic substances. As part of this effort, assays that use the COPAS Biosort flow sorting technology to record optical measurements (time of flight (TOF) and extinction (EXT)) of individual nematodes under various chemical exposure conditions are being developed. A mathematical model has been created that uses Biosort data to quantitatively and qualitatively describe C. elegans growth, and link changes in growth rates to biological events. Chlorpyrifos, an organophosphate pesticide known to cause developmental delays and malformations in mammals, was used as a model toxicant to test the applicability of the growth model for in vivo toxicological testing. Methodology/Principal Findings L1 larval nematodes were exposed to a range of sub-lethal chlorpyrifos concentrations (0–75 µM) and measured every 12 h. In the absence of toxicant, C. elegans matured from L1s to gravid adults by 60 h. A mathematical model was used to estimate nematode size distributions at various times. Mathematical modeling of the distributions allowed the number of measured nematodes and log(EXT) and log(TOF) growth rates to be estimated. The model revealed three distinct growth phases. The points at which estimated growth rates changed (change points) were constant across the ten chlorpyrifos concentrations. Concentration response curves with respect to several model-estimated quantities (numbers of measured nematodes, mean log(TOF) and log(EXT), growth rates, and time to reach change points) showed a significant decrease in C. elegans growth with increasing chlorpyrifos concentration. Conclusions Effects of chlorpyrifos on C. elegans growth and development were mathematically modeled. Statistical tests confirmed a significant concentration effect on several model endpoints. This confirmed that chlorpyrifos affects C

A simple polymeric model describes cell nuclear mechanical response

NASA Astrophysics Data System (ADS)

Banigan, Edward; Stephens, Andrew; Marko, John

The cell nucleus must continually resist inter- and intracellular mechanical forces, and proper mechanical response is essential to basic cell biological functions as diverse as migration, differentiation, and gene regulation. Experiments probing nuclear mechanics reveal that the nucleus stiffens under strain, leading to two characteristic regimes of force response. This behavior depends sensitively on the intermediate filament protein lamin A, which comprises the outer layer of the nucleus, and the properties of the chromatin interior. To understand these mechanics, we study a simulation model of a polymeric shell encapsulating a semiflexible polymer. This minimalistic model qualitatively captures the typical experimental nuclear force-extension relation and observed nuclear morphologies. Using a Flory-like theory, we explain the simulation results and mathematically estimate the force-extension relation. The model and experiments suggest that chromatin organization is a dominant contributor to nuclear mechanics, while the lamina protects cell nuclei from large deformations.

A holistic conceptual framework model to describe medication adherence in and guide interventions in diabetes mellitus.

PubMed

Jaam, Myriam; Awaisu, Ahmed; Mohamed Ibrahim, Mohamed Izham; Kheir, Nadir

2018-04-01

Nonadherence to medications in patients with diabetes, which results in poor treatment outcomes and increased healthcare costs, is commonly reported globally. Factors associated with medication adherence have also been widely studied. However, a clear and comprehensive, disease-specific conceptual framework model that captures all possible factors has not been established. This study aimed to develop a conceptual framework that addresses the complex network of barriers to medication adherence in patients with diabetes. Fourteen databases and grey literature sources were systematically searched for systematic reviews reporting barriers to medication adherence in patients with diabetes. A thematic approach was used to categorize all identified barriers from the reviews and to create a matrix representing the complex network and relations of the different barriers. Eighteen systematic reviews were identified and used for the development of the conceptual framework. Overall, six major themes emerged: patient-, medication-, disease-, provider-, system-, and societal-related factors. Each of these themes was further classified into different sub-categories. It was noted that most interactions were identified to be within the patient-related factors, which not only interact with other themes but also within the same theme. Patient's demographics as well as cultural beliefs were the most notable factors in terms of interactions with other categories and themes. The intricate network and interaction of factors identified between different themes and within individual themes indicate the complexity of the problem of adherence. This framework will potentially enhance the understanding of the complex relation between different barriers for medication adherence in diabetes and will facilitate design of more effective interventions. Future interventions for enhancing medication adherence should look at the overall factors and target multiple themes of barriers to improve patient

q-deformed Einstein's model to describe specific heat of solid

NASA Astrophysics Data System (ADS)

Guha, Atanu; Das, Prasanta Kumar

2018-04-01

Realistic phenomena can be described more appropriately using generalized canonical ensemble, with proper parameter sets involved. We have generalized the Einstein's theory for specific heat of solid in Tsallis statistics, where the temperature fluctuation is introduced into the theory via the fluctuation parameter q. At low temperature the Einstein's curve of the specific heat in the nonextensive Tsallis scenario exactly lies on the experimental data points. Consequently this q-modified Einstein's curve is found to be overlapping with the one predicted by Debye. Considering only the temperature fluctuation effect(even without considering more than one mode of vibration is being triggered) we found that the CV vs T curve is as good as obtained by considering the different modes of vibration as suggested by Debye. Generalizing the Einstein's theory in Tsallis statistics we found that a unique value of the Einstein temperature θE along with a temperature dependent deformation parameter q(T) , can well describe the phenomena of specific heat of solid i.e. the theory is equivalent to Debye's theory with a temperature dependent θD.

Describing Technological Paradigm Transitions: A Methodological Exploration.

ERIC Educational Resources Information Center

Wallace, Danny P.; Van Fleet, Connie

1997-01-01

Presents a humorous treatment of the "sessio taurino" (or humanistic inquiry) technique for describing changes in technological models. The fundamental tool of "sessio taurino" is a loosely-structured event known as the session, which is of indeterminate length, involves a flexible number of participants, and utilizes a…

A simple model of universe describing the early inflation and the late accelerated expansion in a symmetric manner

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

Chavanis, Pierre-Henri

We construct a simple model of universe which 'unifies' vacuum energy and radiation on the one hand, and matter and dark energy on the other hand in the spirit of a generalized Chaplygin gas model. Specifically, the phases of early inflation and late accelerated expansion are described by a generalized equation of state p/c{sup 2} = αρ+kρ{sup 1+1/n} having a linear component p = αρc{sup 2} and a polytropic component p = kρ{sup 1+1/n}c{sup 2}. For α= 1/3, n= 1 and k=−4/(3ρ{sub P}), where ρ{sub P}= 5.1610{sup 99} g/m{sup 3} is the Planck density, this equation of state describes themore » transition between the vacuum energy era and the radiation era. For t≥ 0, the universe undergoes an inflationary expansion that brings it from the Planck size l{sub P}= 1.6210{sup −35} m to a size a{sub 1}= 2.6110{sup −6} m on a timescale of about 23.3 Planck times t{sub P}= 5.3910{sup −44} s (early inflation). When t > t{sub 1}= 23.3t{sub P}, the universe decelerates and enters in the radiation era. We interpret the transition from the vacuum energy era to the radiation era as a second order phase transition where the Planck constant ℏ plays the role of finite size effects (the standard Big Bang theory is recovered for ℏ= 0). For α= 0, n=−1 and k=−ρ{sub Λ}, where ρ{sub Λ}= 7.0210{sup −24} g/m{sup 3} is the cosmological density, the equation of state p/c{sup 2} = αρ+kρ{sup 1+1/n} describes the transition from a decelerating universe dominated by pressureless matter (baryonic and dark matter) to an accelerating universe dominated by dark energy (late inflation). This transition takes place at a size a{sub 2}= 0.204l{sub Λ}. corresponding to a time t{sub 2}= 0.203t{sub Λ} where l{sub Λ}= 4.38 10{sup 26} m is the cosmological length and t{sub Λ}= 1.46 10{sup 18} s the cosmological time. The present universe turns out to be just at the transition between these two periods (t{sub 0}∼t{sub 2}). Our model gives the same results as the standard �

Why College Students Cheat: A Conceptual Model of Five Factors

ERIC Educational Resources Information Center

Yu, Hongwei; Glanzer, Perry L.; Johnson, Byron R.; Sriram, Rishi; Moore, Brandon

2018-01-01

Though numerous studies have identified factors associated with academic misconduct, few have proposed conceptual models that could make sense of multiple factors. In this study, we used structural equation modeling (SEM) to test a conceptual model of five factors using data from a relatively large sample of 2,503 college students. The results…

LANDPLANER (LANDscape, Plants, LANdslide and ERosion): a model to describe the dynamic response of slopes (or basins) under different changing scenarios

NASA Astrophysics Data System (ADS)

Rossi, Mauro; Torri, Dino; Santi, Elisa; Bacaro, Giovanni; Marchesini, Ivan

2014-05-01

approaches have been proposed to model separately landslide and erosion processes, only few attempts were made to model both jointly, mostly integrating pre-existing models. To overcome this limitation we develop a new model called LANDPLANER (LANDscape, Plants, LANdslide and ERosion), specifically design to describe the dynamic response of slopes (or basins) under different changing scenarios including: (i) changes of meteorological factors, (ii) changes of vegetation or land-use, (iii) and changes of slope morphology. The was applied in different study area in order to check its basic assumptions, and to test its general operability and applicability. Results show a reasonable model behaviors and confirm its easy applicability in real cases.

Direct construction of predictive models for describing growth Salmonella enteritidis in liquid eggs – a one-step approach

USDA-ARS?s Scientific Manuscript database

The objective of this study was to develop a new approach using a one-step approach to directly construct predictive models for describing the growth of Salmonella Enteritidis (SE) in liquid egg white (LEW) and egg yolk (LEY). A five-strain cocktail of SE, induced to resist rifampicin at 100 mg/L, ...

Default Bayes Factors for Model Selection in Regression

ERIC Educational Resources Information Center

Rouder, Jeffrey N.; Morey, Richard D.

2012-01-01

In this article, we present a Bayes factor solution for inference in multiple regression. Bayes factors are principled measures of the relative evidence from data for various models or positions, including models that embed null hypotheses. In this regard, they may be used to state positive evidence for a lack of an effect, which is not possible…

A 3-factor model for the FACIT-Sp.

PubMed

Canada, Andrea L; Murphy, Patricia E; Fitchett, George; Peterman, Amy H; Schover, Leslie R

2008-09-01

The 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale (FACIT-Sp) is a popular measure of the religious/spiritual (R/S) components of quality of life (QoL) in patients with cancer. The original factor analyses of the FACIT-Sp supported two factors: Meaning/Peace and Faith. Because Meaning suggests a cognitive aspect of R/S and Peace an affective component, we hypothesized a 3-factor solution: Meaning, Peace, and Faith. Participants were 240 long-term female survivors of cancer who completed the FACIT-Sp, the SF-12, and the BSI 18. We used confirmatory factor analysis to compare the 2- and 3-factor models of the FACIT-Sp and subsequently assessed associations between the resulting solutions and QoL domains. Survivors averaged 44 years of age and 10 years post-diagnosis. A 3-factor solution of the FACIT-Sp significantly improved the fit of the model to the data over the original 2-factor structure (Delta chi(2)=72.36, df=2, p<0.001). Further adjustments to the 3-factor model resulted in a final solution with even better goodness-of-fit indices (chi(2)=59.11, df=1, p=0.13, CFI=1.00, SMRM=0.05).The original Meaning/Peace factor controlling for Faith was associated with mental (r=0.63, p<0.000) and physical (r=0.22, p<0.01) health on the SF-12, and the original Faith factor controlling for Meaning/Peace was negatively associated with mental health (r=-0.15, p<0.05). The 3-factor model was more informative. Specifically, using partial correlations, the Peace factor was only related to mental health (r=0.53, p<0.001); Meaning was related to both physical (r=0.18, p<0.01) and mental (r=0.17, p<0.01) health; and Faith was negatively associated with mental health (r=-0.17, p<0.05). The results of this study support a 3-factor solution of the FACIT-Sp. The new solution not only represents a psychometric improvement over the original, but also enables a more detailed examination of the contribution of different dimensions of R/S to QoL. (c

A model framework to describe growth-linked biodegradation of trace-level pollutants in the presence of coincidental carbon substrates and microbes.

PubMed

Liu, Li; Helbling, Damian E; Kohler, Hans-Peter E; Smets, Barth F

2014-11-18

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (μg L(-1) and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.

Fourier transform infrared spectroscopic imaging parameters describing acid phosphate substitution in biologic hydroxyapatite.

PubMed

Spevak, Lyudmila; Flach, Carol R; Hunter, Tracey; Mendelsohn, Richard; Boskey, Adele

2013-05-01

Acid phosphate substitution into mineralized tissues is an important determinant of their mechanical properties and their response to treatment. This study identifies and validates Fourier transform infrared spectroscopic imaging (FTIRI) spectral parameters that provide information on the acid phosphate (HPO4) substitution into hydroxyapatite in developing mineralized tissues. Curve fitting and Fourier self-deconvolution were used to identify subband positions in model compounds (with and without HPO4). The intensity of subbands at 1127 and 1110 cm(-1) correlated with the acid phosphate content in these models. Peak height ratios of these subbands to the ν3 vibration at 1096 cm(-1) found in stoichiometric apatite were evaluated in the model compounds and mixtures thereof. FTIRI spectra of bones and teeth at different developmental ages were analyzed using these spectral parameters. Factor analysis (a chemometric technique) was also conducted on the tissue samples and resulted in factor loadings with spectral features corresponding to the HPO4 vibrations described above. Images of both factor correlation coefficients and the peak height ratios 1127/1096 and 1112/1096 cm(-1) demonstrated higher acid phosphate content in younger vs. more mature regions in the same specimen. Maps of the distribution of acid phosphate content will be useful for characterizing the extent of new bone formation, the areas of potential decreased strength, and the effects of therapies such as those used in metabolic bone diseases (osteoporosis, chronic kidney disease) on mineral composition. Because of the wider range of values obtained with the 1127/1096 cm(-1) parameter compared to the 1110/1096 cm(-1) parameter and the smaller scatter in the slope, it is suggested that this ratio should be the parameter of choice.

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

PubMed Central

Pasma, Jantsje H.; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C.

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot.

PubMed

Pasma, Jantsje H; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This

Biomechanical factors associated with mandibular cantilevers: analysis with three-dimensional finite element models.

PubMed

Gonda, Tomoya; Yasuda, Daiisa; Ikebe, Kazunori; Maeda, Yoshinobu

2014-01-01

Although the risks of using a cantilever to treat missing teeth have been described, the mechanisms remain unclear. This study aimed to reveal these mechanisms from a biomechanical perspective. The effects of various implant sites, number of implants, and superstructural connections on stress distribution in the marginal bone were analyzed with three-dimensional finite element models based on mandibular computed tomography data. Forces from the masseter, temporalis, and internal pterygoid were applied as vectors. Two three-dimensional finite element models were created with the edentulous mandible showing severe and relatively modest residual ridge resorption. Cantilevers of the premolar and molar were simulated in the superstructures in the models. The following conditions were also included as factors in the models to investigate changes: poor bone quality, shortened dental arch, posterior occlusion, lateral occlusion, double force of the masseter, and short implant. Multiple linear regression analysis with a forced-entry method was performed with stress values as the objective variable and the factors as the explanatory variable. When bone mass was high, stress around the implant caused by differences in implantation sites was reduced. When bone mass was low, the presence of a cantilever was a possible risk factor. The stress around the implant increased significantly if bone quality was poor or if increased force (eg, bruxism) was applied. The addition of a cantilever to the superstructure increased stress around implants. When large muscle forces were applied to a superstructure with cantilevers or if bone quality was poor, stress around the implants increased.

Linear mixed-effects models to describe length-weight relationships for yellow croaker (Larimichthys Polyactis) along the north coast of China.

PubMed

Ma, Qiuyun; Jiao, Yan; Ren, Yiping

2017-01-01

In this study, length-weight relationships and relative condition factors were analyzed for Yellow Croaker (Larimichthys polyactis) along the north coast of China. Data covered six regions from north to south: Yellow River Estuary, Coastal Waters of Northern Shandong, Jiaozhou Bay, Coastal Waters of Qingdao, Haizhou Bay, and South Yellow Sea. In total 3,275 individuals were collected during six years (2008, 2011-2015). One generalized linear model, two simply linear models and nine linear mixed effect models that applied the effects from regions and/or years to coefficient a and/or the exponent b were studied and compared. Among these twelve models, the linear mixed effect model with random effects from both regions and years fit the data best, with lowest Akaike information criterion value and mean absolute error. In this model, the estimated a was 0.0192, with 95% confidence interval 0.0178~0.0308, and the estimated exponent b was 2.917 with 95% confidence interval 2.731~2.945. Estimates for a and b with the random effects in intercept and coefficient from Region and Year, ranged from 0.013 to 0.023 and from 2.835 to 3.017, respectively. Both regions and years had effects on parameters a and b, while the effects from years were shown to be much larger than those from regions. Except for Coastal Waters of Northern Shandong, a decreased from north to south. Condition factors relative to reference years of 1960, 1986, 2005, 2007, 2008~2009 and 2010 revealed that the body shape of Yellow Croaker became thinner in recent years. Furthermore relative condition factors varied among months, years, regions and length. The values of a and relative condition factors decreased, when the environmental pollution became worse, therefore, length-weight relationships could be an indicator for the environment quality. Results from this study provided basic description of current condition of Yellow Croaker along the north coast of China.

Tree-Structured Infinite Sparse Factor Model

PubMed Central

Zhang, XianXing; Dunson, David B.; Carin, Lawrence

2013-01-01

A tree-structured multiplicative gamma process (TMGP) is developed, for inferring the depth of a tree-based factor-analysis model. This new model is coupled with the nested Chinese restaurant process, to nonparametrically infer the depth and width (structure) of the tree. In addition to developing the model, theoretical properties of the TMGP are addressed, and a novel MCMC sampler is developed. The structure of the inferred tree is used to learn relationships between high-dimensional data, and the model is also applied to compressive sensing and interpolation of incomplete images. PMID:25279389

An Integrated Modeling Approach for Describing Fate and Transport of Perfluorinated Compounds (PFCs) in Estuarine Reservoir

NASA Astrophysics Data System (ADS)

Zhang, J.; Nguyen Viet, T.; Wang, X.; Chen, H.; Gin, K. Y. H.

2014-12-01

The fate and transport processes of emerging contaminants in aquatic ecosystems are complex, which are not only determined by their own properties but also influenced by the environmental setting, physical, chemical and biological processes. A 3D-emerging contaminant model has been developed based on Delft3D water quality model and coupled with a hydrodynamic model and a catchment-scale 1D- hydrological and hydraulic model to study the possible fate and transport mechanisms of perfluorinated compounds (PFCs) in Marina Reservoir in Singapore. The main processes in the contaminant model include partitioning (among detritus, dissolved organic matter and phytoplankton), settling, resuspension and degradation. We used the integrated model to quantify the distribution of the total PFCs and two major components, namely perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) in the water, sediments and organisms in the reservoir. The model yielded good agreement with the field measurements when evaluated based on the datasets in 2009 and 2010 as well as recent observations in 2013 and 2014. Our results elucidate that the model can be a useful tool to characterize the occurrence, sources, sinks and trends of PFCs both in the water column and in the sediments in the reservoir. Thisapproach provides a better understanding of mechanisms that influence the fate and transport of emerging contaminants and lays down a framework for future experiments to further explore how the dominant environmental factors change towards mitigation of emerging contaminants in the reservoirs.

Is the Water Heating Curve as Described?

ERIC Educational Resources Information Center

Riveros, H. G.; Oliva, A. I.

2008-01-01

We analysed the heating curve of water which is described in textbooks. An experiment combined with some simple heat transfer calculations is discussed. The theoretical behaviour can be altered by changing the conditions under which the experiment is modelled. By identifying and controlling the different parameters involved during the heating…

Membrane Capacitive Memory Alters Spiking in Neurons Described by the Fractional-Order Hodgkin-Huxley Model

PubMed Central

Weinberg, Seth H.

2015-01-01

Excitable cells and cell membranes are often modeled by the simple yet elegant parallel resistor-capacitor circuit. However, studies have shown that the passive properties of membranes may be more appropriately modeled with a non-ideal capacitor, in which the current-voltage relationship is given by a fractional-order derivative. Fractional-order membrane potential dynamics introduce capacitive memory effects, i.e., dynamics are influenced by a weighted sum of the membrane potential prior history. However, it is not clear to what extent fractional-order dynamics may alter the properties of active excitable cells. In this study, we investigate the spiking properties of the neuronal membrane patch, nerve axon, and neural networks described by the fractional-order Hodgkin-Huxley neuron model. We find that in the membrane patch model, as fractional-order decreases, i.e., a greater influence of membrane potential memory, peak sodium and potassium currents are altered, and spike frequency and amplitude are generally reduced. In the nerve axon, the velocity of spike propagation increases as fractional-order decreases, while in a neural network, electrical activity is more likely to cease for smaller fractional-order. Importantly, we demonstrate that the modulation of the peak ionic currents that occurs for reduced fractional-order alone fails to reproduce many of the key alterations in spiking properties, suggesting that membrane capacitive memory and fractional-order membrane potential dynamics are important and necessary to reproduce neuronal electrical activity. PMID:25970534

Comparison of three nonlinear models to describe long-term tag shedding by lake trout

USGS Publications Warehouse

Fabrizio, Mary C.; Swanson, Bruce L.; Schram, Stephen T.; Hoff, Michael H.

1996-01-01

We estimated long-term tag-shedding rates for lake trout Salvelinus namaycush using two existing models and a model we developed to account for the observed permanence of some tags. Because tag design changed over the course of the study, we examined tag-shedding rates for three types of numbered anchor tags (Floy tags FD-67, FD-67C, and FD-68BC) and an unprinted anchor tag (FD-67F). Lake trout from the Gull Island Shoal region, Lake Superior, were double-tagged, and subsequent recaptures were monitored in annual surveys conducted from 1974 to 1992. We modeled tag-shedding rates, using time at liberty and probabilities of tag shedding estimated from fish released in 1974 and 1978–1983 and later recaptured. Long-term shedding of numbered anchor tags in lake trout was best described by a nonlinear model with two parameters: an instantaneous tag-shedding rate and a constant representing the proportion of tags that were never shed. Although our estimates of annual shedding rates varied with tag type (0.300 for FD-67, 0.441 for FD-67C, and 0.656 for FD-68BC), differences were not significant. About 36% of tags remained permanently affixed to the fish. Of the numbered tags that were shed (about 64%), two mechanisms contributed to tag loss: disintegration and dislodgment. Tags from about 11% of recaptured fish had disintegrated, but most tags were dislodged. Unprinted tags were shed at a significant but low rate immediately after release, but the long-term, annual shedding rate of these tags was only 0.013. Compared with unprinted tags, numbered tags dislodged at higher annual rates; we hypothesized that this was due to the greater frictional drag associated with the larger cross-sectional area of numbered tags.

Folding superfunnel to describe cooperative folding of interacting proteins.

PubMed

Smeller, László

2016-07-01

This paper proposes a generalization of the well-known folding funnel concept of proteins. In the funnel model the polypeptide chain is treated as an individual object not interacting with other proteins. Since biological systems are considerably crowded, protein-protein interaction is a fundamental feature during the life cycle of proteins. The folding superfunnel proposed here describes the folding process of interacting proteins in various situations. The first example discussed is the folding of the freshly synthesized protein with the aid of chaperones. Another important aspect of protein-protein interactions is the folding of the recently characterized intrinsically disordered proteins, where binding to target proteins plays a crucial role in the completion of the folding process. The third scenario where the folding superfunnel is used is the formation of aggregates from destabilized proteins, which is an important factor in case of several conformational diseases. The folding superfunnel constructed here with the minimal assumption about the interaction potential explains all three cases mentioned above. Proteins 2016; 84:1009-1016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be; Van den Bergh, Laura; Al-Mamgani, Abrahim

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including themore » most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions

Taking the Error Term of the Factor Model into Account: The Factor Score Predictor Interval

ERIC Educational Resources Information Center

Beauducel, Andre

2013-01-01

The problem of factor score indeterminacy implies that the factor and the error scores cannot be completely disentangled in the factor model. It is therefore proposed to compute Harman's factor score predictor that contains an additive combination of factor and error variance. This additive combination is discussed in the framework of classical…

Use of a vision model to quantify the significance of factors effecting target conspicuity

NASA Astrophysics Data System (ADS)

Gilmore, M. A.; Jones, C. K.; Haynes, A. W.; Tolhurst, D. J.; To, M.; Troscianko, T.; Lovell, P. G.; Parraga, C. A.; Pickavance, K.

2006-05-01

When designing camouflage it is important to understand how the human visual system processes the information to discriminate the target from the background scene. A vision model has been developed to compare two images and detect differences in local contrast in each spatial frequency channel. Observer experiments are being undertaken to validate this vision model so that the model can be used to quantify the relative significance of different factors affecting target conspicuity. Synthetic imagery can be used to design improved camouflage systems. The vision model is being used to compare different synthetic images to understand what features in the image are important to reproduce accurately and to identify the optimum way to render synthetic imagery for camouflage effectiveness assessment. This paper will describe the vision model and summarise the results obtained from the initial validation tests. The paper will also show how the model is being used to compare different synthetic images and discuss future work plans.

Model tool to describe chemical structures in XML format utilizing structural fragments and chemical ontology.

PubMed

Sankar, Punnaivanam; Alain, Krief; Aghila, Gnanasekaran

2010-05-24

We have developed a model structure-editing tool, ChemEd, programmed in JAVA, which allows drawing chemical structures on a graphical user interface (GUI) by selecting appropriate structural fragments defined in a fragment library. The terms representing the structural fragments are organized in fragment ontology to provide a conceptual support. ChemEd describes the chemical structure in an XML document (ChemFul) with rich semantics explicitly encoding the details of the chemical bonding, the hybridization status, and the electron environment around each atom. The document can be further processed through suitable algorithms and with the support of external chemical ontologies to generate understandable reports about the functional groups present in the structure and their specific environment.

A Risk Factor Analysis of West Nile Virus: Extraction of Relationships from a Neural-Network Model

NASA Astrophysics Data System (ADS)

Ghosh, Debarchana; Guha, Rajarshi

The West Nile Virus (WNV) is an infectious disease spreading rapidly throughout the United States, causing illness among thousands of birds, animals, and humans. The broad categories of risk factors underlying WNV incidences are: environmental, socioeconomic, built-environment, and existing mosquito abatement policies. Computational neural network (CNN) model was developed to understand the occurrence of WNV infected dead birds because of their ability to capture complex relationships with higher accuracy than linear models. In this paper, we describe a method to interpret a CNN model by considering the final optimized weights. The research was conducted in the Metropolitan area of Minnesota, which had experienced significant outbreaks from 2002 till present.

Model of medicines sales forecasting taking into account factors of influence

NASA Astrophysics Data System (ADS)

Kravets, A. G.; Al-Gunaid, M. A.; Loshmanov, V. I.; Rasulov, S. S.; Lempert, L. B.

2018-05-01

The article describes a method for forecasting sales of medicines in conditions of data sampling, which is insufficient for building a model based on historical data alone. The developed method is applicable mainly to new drugs that are already licensed and released for sale but do not yet have stable sales performance in the market. The purpose of this study is to prove the effectiveness of the suggested method forecasting drug sales, taking into account the selected factors of influence, revealed during the review of existing solutions and analysis of the specificity of the area under study. Three experiments were performed on samples of different volumes, which showed an improvement in the accuracy of forecasting sales in small samples.

Model of a ternary complex between activated factor VII, tissue factor and factor IX.

PubMed

Chen, Shu-wen W; Pellequer, Jean-Luc; Schved, Jean-François; Giansily-Blaizot, Muriel

2002-07-01

Upon binding to tissue factor, FVIIa triggers coagulation by activating vitamin K-dependent zymogens, factor IX (FIX) and factor X (FX). To understand recognition mechanisms in the initiation step of the coagulation cascade, we present a three-dimensional model of the ternary complex between FVIIa:TF:FIX. This model was built using a full-space search algorithm in combination with computational graphics. With the known crystallographic complex FVIIa:TF kept fixed, the FIX docking was performed first with FIX Gla-EGF1 domains, followed by the FIX protease/EGF2 domains. Because the FIXa crystal structure lacks electron density for the Gla domain, we constructed a chimeric FIX molecule that contains the Gla-EGF1 domains of FVIIa and the EGF2-protease domains of FIXa. The FVIIa:TF:FIX complex has been extensively challenged against experimental data including site-directed mutagenesis, inhibitory peptide data, haemophilia B database mutations, inhibitor antibodies and a novel exosite binding inhibitor peptide. This FVIIa:TF:FIX complex provides a powerful tool to study the regulation of FVIIa production and presents new avenues for developing therapeutic inhibitory compounds of FVIIa:TF:substrate complex.

Comparisons of Four Methods for Estimating a Dynamic Factor Model

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.

2008-01-01

Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…

Model of Environmental Development of the Urbanized Areas: Accounting of Ecological and other Factors

NASA Astrophysics Data System (ADS)

Abanina, E. N.; Pandakov, K. G.; Agapov, D. A.; Sorokina, Yu V.; Vasiliev, E. H.

2017-05-01

Modern cities and towns are often characterized by poor administration, which could be the reason of environmental degradation, the poverty growth, decline in economic growth and social isolation. In these circumstances it is really important to conduct fresh researches forming new ways of sustainable development of administrative districts. This development of the urban areas depends on many interdependent factors: ecological, economic, social. In this article we show some theoretical aspects of forming a model of environmental progress of the urbanized areas. We submit some model containing four levels including natural resources capacities of the territory, its social features, economic growth and human impact. The author describes the interrelations of elements of the model. In this article the program of environmental development of a city is offered and it could be used in any urban area.

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

Lessons from the Specific Factors Model of International Trade.

ERIC Educational Resources Information Center

Tohamy, Soumaya M.; Mixon, J. Wilson, Jr.

2003-01-01

Uses the Specific Factors model to illustrate the meaning of economic efficiency, how complex economies simultaneously determine prices and quantities, and how changes in demand conditions or technology can affect income distribution among owners of factors of production. Employs spreadsheets to help students see how the model works. (JEH)

Logistic regression for risk factor modelling in stuttering research.

PubMed

Reed, Phil; Wu, Yaqionq

2013-06-01

To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

Modelling the Interplay between Lifestyle Factors and Genetic Predisposition on Markers of Type 2 Diabetes Mellitus Risk.

PubMed

Walker, Celia G; Solis-Trapala, Ivonne; Holzapfel, Christina; Ambrosini, Gina L; Fuller, Nicholas R; Loos, Ruth J F; Hauner, Hans; Caterson, Ian D; Jebb, Susan A

2015-01-01

The risk of developing type 2 diabetes mellitus (T2DM) is determined by a complex interplay involving lifestyle factors and genetic predisposition. Despite this, many studies do not consider the relative contributions of this complex array of factors to identify relationships which are important in progression or prevention of complex diseases. We aimed to describe the integrated effect of a number of lifestyle changes (weight, diet and physical activity) in the context of genetic susceptibility, on changes in glycaemic traits in overweight or obese participants following 12-months of a weight management programme. A sample of 353 participants from a behavioural weight management intervention were included in this study. A graphical Markov model was used to describe the impact of the intervention, by dividing the effects into various pathways comprising changes in proportion of dietary saturated fat, physical activity and weight loss, and a genetic predisposition score (T2DM-GPS), on changes in insulin sensitivity (HOMA-IR), insulin secretion (HOMA-B) and short and long term glycaemia (glucose and HbA1c). We demonstrated the use of graphical Markov modelling to identify the importance and interrelationships of a number of possible variables changed as a result of a lifestyle intervention, whilst considering fixed factors such as genetic predisposition, on changes in traits. Paths which led to weight loss and change in dietary saturated fat were important factors in the change of all glycaemic traits, whereas the T2DM-GPS only made a significant direct contribution to changes in HOMA-IR and plasma glucose after considering the effects of lifestyle factors. This analysis shows that modifiable factors relating to body weight, diet, and physical activity are more likely to impact on glycaemic traits than genetic predisposition during a behavioural intervention.

Development and Application of a Category System to Describe Pre-Service Science Teachers' Activities in the Process of Scientific Modelling

NASA Astrophysics Data System (ADS)

Krell, Moritz; Walzer, Christine; Hergert, Susann; Krüger, Dirk

2017-09-01

As part of their professional competencies, science teachers need an elaborate meta-modelling knowledge as well as modelling skills in order to guide and monitor modelling practices of their students. However, qualitative studies about (pre-service) science teachers' modelling practices are rare. This study provides a category system which is suitable to analyse and to describe pre-service science teachers' modelling activities and to infer modelling strategies. The category system was developed based on theoretical considerations and was inductively refined within the methodological frame of qualitative content analysis. For the inductive refinement, modelling practices of pre-service teachers (n = 4) have been video-taped and analysed. In this study, one case was selected to demonstrate the application of the category system to infer modelling strategies. The contribution of this study for science education research and science teacher education is discussed.

Determination of effective loss factors in reduced SEA models

NASA Astrophysics Data System (ADS)

Chimeno Manguán, M.; Fernández de las Heras, M. J.; Roibás Millán, E.; Simón Hidalgo, F.

2017-01-01

The definition of Statistical Energy Analysis (SEA) models for large complex structures is highly conditioned by the classification of the structure elements into a set of coupled subsystems and the subsequent determination of the loss factors representing both the internal damping and the coupling between subsystems. The accurate definition of the complete system can lead to excessively large models as the size and complexity increases. This fact can also rise practical issues for the experimental determination of the loss factors. This work presents a formulation of reduced SEA models for incomplete systems defined by a set of effective loss factors. This reduced SEA model provides a feasible number of subsystems for the application of the Power Injection Method (PIM). For structures of high complexity, their components accessibility can be restricted, for instance internal equipments or panels. For these cases the use of PIM to carry out an experimental SEA analysis is not possible. New methods are presented for this case in combination with the reduced SEA models. These methods allow defining some of the model loss factors that could not be obtained through PIM. The methods are validated with a numerical analysis case and they are also applied to an actual spacecraft structure with accessibility restrictions: a solar wing in folded configuration.

Systematics of g factors of 2{sub 1}{sup +} states in even-even nuclei from Gd to Pt: A microscopic description by the projected shell model

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

Bian, Bao-An; Institute of Low Energy Nuclear Physics, Beijing Normal University, Beijing 100875; Di, Yao-Min

2007-01-15

The systematics of g factor of the first excited 2{sup +} state vs neutron number N is studied by the projected shell model. The study covers the even-even nuclei of all isotopic chains from Gd to Pt. g factors are calculated by using the many-body wave functions that well reproduce the energy levels and B(E2)s of the ground-state bands. For Gd to W isotopes the characteristic feature of the g factor data along an isotopic chain is described by the present model. Deficiency of the model in the g factor description for the heavier Os and Pt isotopes is discussed.

Continuum approaches for describing solid-gas and solid-liquid flow

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

Diamond, P.; Harvey, J.; Levine, H.

Two-phase continuum models have been used to describe the multiphase flow properties of solid-gas and solid-liquid mixtures. The approach is limited in that it requires many fitting functions and parameters to be determined empirically, and it does not provide natural explanations for some of the qualitative behavior of solid-fluid flow. In this report, we explore a more recent single-phase continuum model proposed by Jenkins and Savage to describe granular flow. Jenkins and McTigue have proposed a modified model to describe the flow of dense suspensions, and hence, many of our results can be straight-forwardly extended to this flow regime asmore » well. The solid-fluid mixture is treated as a homogeneous, compressible fluid in which the particle fluctuations about the mean flow are described in terms of an effective temperature. The particle collisions are treated as inelastic. After an introduction in which we briefly comment on the present status of the field, we describe the details of the single-phase continuum model and analyze the microscopic and macroscopic flow conditions required for the approach to be valid. We then derive numerous qualitative predictions which can be empirically verified in small-scale experiments: The flow profiles are computed for simple boundary conditions, plane Couette flow and channel flow. Segregaion effects when there are two (or more) particle size are considered. The acoustic dispersion relation is derived and shown to predict that granular flow is supersonic. We point out that the analysis of flow instabilities is complicated by the finite compressibility of the solid-fluid mixture. For example, the large compressibility leads to interchange (Rayleigh-Taylor instabilities) in addition to the usual angular momentum interchange in standard (cylindrical) Couette flow. We conclude by describing some of the advantages and limitations of experimental techniques that might be used to test predictions for solid-fluid flow. 19 refs.« less

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

QSAR models for describing the toxicological effects of ILs against Staphylococcus aureus based on norm indexes.

PubMed

He, Wensi; Yan, Fangyou; Jia, Qingzhu; Xia, Shuqian; Wang, Qiang

2018-03-01

The hazardous potential of ionic liquids (ILs) is becoming an issue of great concern due to their important role in many industrial fields as green agents. The mathematical model for the toxicological effects of ILs is useful for the risk assessment and design of environmentally benign ILs. The objective of this work is to develop QSAR models to describe the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of ILs against Staphylococcus aureus (S. aureus). A total of 169 and 101 ILs with MICs and MBCs, respectively, are used to obtain multiple linear regression models based on matrix norm indexes. The norm indexes used in this work are proposed by our research group and they are first applied to estimate the antibacterial toxicity of these ILs against S. aureus. These two models precisely and reliably calculated the IL toxicities with a square of correlation coefficient (R 2 ) of 0.919 and a standard error of estimate (SE) of 0.341 (in log unit of mM) for pMIC, and an R 2 of 0.913 and SE of 0.282 for pMBC. Copyright © 2017 Elsevier Ltd. All rights reserved.

On Modeling Research Work for Describing and Filtering Scientific Information

NASA Astrophysics Data System (ADS)

Sicilia, Miguel-Ángel

Existing models for Research Information Systems (RIS) properly address the description of people and organizations, projects, facilities and their outcomes, e.g. papers, reports or patents. While this is adequate for the recording and accountability of research investments, helping researchers in finding relevant people, organizations or results requires considering both the content of research work and also its context. The content is not only related to the domain area, but it requires modeling methodological issues as variables, instruments or scientific methods that can then be used as search criteria. The context of research work is determined by the ongoing projects or scientific interests of an individual or a group, and can be expressed using the same methodological concepts. However, modeling methodological issues is notably complex and dependent on the scientific discipline and research area. This paper sketches the main requirements for those models, providing some motivating examples that could serve as a point of departure for future attempts in developing an upper ontology for research methods and tools.

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.

PubMed

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

Can model Hamiltonians describe the electron-electron interaction in π-conjugated systems?: PAH and graphene

NASA Astrophysics Data System (ADS)

Chiappe, G.; Louis, E.; San-Fabián, E.; Vergés, J. A.

2015-11-01

Model Hamiltonians have been, and still are, a valuable tool for investigating the electronic structure of systems for which mean field theories work poorly. This review will concentrate on the application of Pariser-Parr-Pople (PPP) and Hubbard Hamiltonians to investigate some relevant properties of polycyclic aromatic hydrocarbons (PAH) and graphene. When presenting these two Hamiltonians we will resort to second quantisation which, although not the way chosen in its original proposal of the former, is much clearer. We will not attempt to be comprehensive, but rather our objective will be to try to provide the reader with information on what kinds of problems they will encounter and what tools they will need to solve them. One of the key issues concerning model Hamiltonians that will be treated in detail is the choice of model parameters. Although model Hamiltonians reduce the complexity of the original Hamiltonian, they cannot be solved in most cases exactly. So, we shall first consider the Hartree-Fock approximation, still the only tool for handling large systems, besides density functional theory (DFT) approaches. We proceed by discussing to what extent one may exactly solve model Hamiltonians and the Lanczos approach. We shall describe the configuration interaction (CI) method, a common technology in quantum chemistry but one rarely used to solve model Hamiltonians. In particular, we propose a variant of the Lanczos method, inspired by CI, that has the novelty of using as the seed of the Lanczos process a mean field (Hartree-Fock) determinant (the method will be named LCI). Two questions of interest related to model Hamiltonians will be discussed: (i) when including long-range interactions, how crucial is including in the Hamiltonian the electronic charge that compensates ion charges? (ii) Is it possible to reduce a Hamiltonian incorporating Coulomb interactions (PPP) to an ‘effective’ Hamiltonian including only on-site interactions (Hubbard)? The

Factor models for cancer signatures

NASA Astrophysics Data System (ADS)

Kakushadze, Zura; Yu, Willie

2016-11-01

We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an ;overall; mode of somatic mutational noise. We give a prescription for factoring out this noise and source code for fixing the number of signatures. We apply nonnegative matrix factorization (NMF) to genome data aggregated by cancer subtype and filtered using our method. The resultant signatures have substantially lower variability than those from unfiltered data. Also, the computational cost of signature extraction is cut by about a factor of 10. We find 3 novel cancer signatures, including a liver cancer dominant signature (96% contribution) and a renal cell carcinoma signature (70% contribution). Our method accelerates finding new cancer signatures and improves their overall stability. Reciprocally, the methods for extracting cancer signatures could have interesting applications in quantitative finance.

Development of a model describing the inhibitory effect of selected preservatives on the growth of Listeria monocytogenes in a meat model system.

PubMed

Dussault, Dominic; Vu, Khanh Dang; Lacroix, Monique

2016-02-01

The objective of this study was to evaluate the impact of seven independent factors consisting of sodium nitrite, pH, sodium chloride, sodium acetate, sodium lactate syrup, calcium propionate and a blend of nisin and hop alpha acids on the growth rate of Listeria monocytogenes in ham as a model of ready-to-eat (RTE) meat products. A central composite consisted of seven factors mentioned above was designed and the response surface methodology was applied for creating a mathematic model to predict the growth rate of L. monocytogenes in RTE meat products. Six parameters showed a significant (P ≤ 0.1) influence on the growth rate of L. monocytogenes. Only the blend of nisin and hop alpha acids did not show any significant effect (P > 0.1) in the concentrations used in this study. Increasing concentration of sodium chloride, sodium nitrite, sodium acetate, potassium lactate and calcium propionate in meat reduced bacterial growth rate while increasing pH in meat increased the growth rate of L. monocytogenes. The current mathematical equation will be an important tool in order to reduce the required number of challenge studies performed in order to ensure a safe food product. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Five-Factor Model framework for understanding childhood personality disorder antecedents.

PubMed

De Clercq, Barbara; De Fruyt, Filip

2012-12-01

The present contribution reviews evidence that supports the relevance of childhood antecedents of personality disorders, and advocates that the validity of a Five-Factor Model framework for describing general trait differences in childhood can be extended towards the field of developmental personality difficulties. In addition, we suggest that several traditional childhood Axis I conditions include a substantial trait component that may be responsible for the recurring finding that childhood Axis I disorders are predictive for adult Axis II disorders. Given the valuable information provided by a trait assessment, we further propose to integrate dimensional personality and personality pathology measures as standard tools in mental health assessments at a young age. © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.

Tree-based modeling of complex interactions of phosphorus loadings and environmental factors.

PubMed

Grunwald, S; Daroub, S H; Lang, T A; Diaz, O A

2009-06-01

Phosphorus (P) enrichment has been observed in the historic oligotrophic Greater Everglades in Florida mainly due to P influx from upstream, agriculturally dominated, low relief drainage basins of the Everglades Agricultural Area (EAA). Our specific objectives were to: (1) investigate relationships between various environmental factors and P loads in 10 farm basins within the EAA, (2) identify those environmental factors that impart major effects on P loads using three different tree-based modeling approaches, and (3) evaluate predictive models to assess P loads. We assembled thirteen environmental variable sets for all 10 sub-basins characterizing water level management, cropping practices, soils, hydrology, and farm-specific properties. Drainage flow and P concentrations were measured at each sub-basin outlet from 1992-2002 and aggregated to derive monthly P loads. We used three different tree-based models including single regression trees (ST), committee trees in Bagging (CTb) and ARCing (CTa) modes and ten-fold cross-validation to test prediction performances. The monthly P loads (MPL) during the monitoring period showed a maximum of 2528 kg (mean: 103 kg) and maximum monthly unit area P loads (UAL) of 4.88 kg P ha(-1) (mean: 0.16 kg P ha(-1)). Our results suggest that hydrologic/water management properties are the major controlling variables to predict MPL and UAL in the EAA. Tree-based modeling was successful in identifying relationships between P loads and environmental predictor variables on 10 farms in the EAA indicated by high R(2) (>0.80) and low prediction errors. Committee trees in ARCing mode generated the best performing models to predict P loads and P loads per unit area. Tree-based models had the ability to analyze complex, non-linear relationships between P loads and multiple variables describing hydrologic/water management, cropping practices, soil and farm-specific properties within the EAA.

Teacher Burnout: A Comparison of Two Cultures Using Confirmatory Factor and Item Response Models

PubMed Central

Denton, Ellen-ge; Chaplin, William F.; Wall, Melanie

2014-01-01

The present study addresses teacher burnout and in particular cultural differences and similarities in burnout. We used the Maslach Burnout Inventory Education Survey (MBI-ES) as the starting point for developing a latent model of burnout in two cultures; Jamaica W.I. teachers (N= 150) and New York City teachers (N= 150). We confirm a latent 3 factor structure, using a subset of the items from the MBI-ES that adequately fit both samples. We tested different degrees of measurement invariance (model fit statistics, scale reliabilities, residual variances, item thresholds, and total variance) to describe and compare cultural differences. Results indicate some differences between the samples at the structure and item levels. We found that factor variances were slightly higher in the New York City teacher sample. Emotional Exhaustion (EE) was a more informative construct for differentiating among teachers at moderate levels of burnout, as opposed to extreme high or low levels of burnout, in both cultures. In contrast, Depersonalization in the Workplace (DW) was more informative at the more extreme levels of burnout among both teacher samples. By studying the influence of culture on the experience of burnout we can further our understanding of burnout and potentially discover factors that might prevent burnout among primary and secondary school teachers. PMID:25729572

A Twin Factor Mixture Modeling Approach to Childhood Temperament: Differential Heritability

ERIC Educational Resources Information Center

Scott, Brandon G.; Lemery-Chalfant, Kathryn; Clifford, Sierra; Tein, Jenn-Yun; Stoll, Ryan; Goldsmith, H.Hill

2016-01-01

Twin factor mixture modeling was used to identify temperament profiles while simultaneously estimating a latent factor model for each profile with a sample of 787 twin pairs (M[subscript age] = 7.4 years, SD = 0.84; 49% female; 88.3% Caucasian), using mother- and father-reported temperament. A four-profile, one-factor model fit the data well.…

Evaluation and Validation of a TCAT Model to Describe Non-Dilute Flow and Species Transport in Porous Media

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Harrison, E.; Miller, C. T.

2017-12-01

A thermodynamically constrained averaging theory (TCAT) model has been developed to simulate non-dilute flow and species transport in porous media. This model has the advantages of a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; the explicit inclusion of dissipative terms that arise from spatial gradients in pressure and chemical activity; and the ability to describe both high and low concentration displacement. The TCAT model has previously been shown to provide excellent agreement for a set of laboratory data and outperformed existing macroscale models that have been used for non-dilute flow and transport. The examined experimental dataset consisted of stable brine displacements for a large range of fluid properties. This dataset however only examined one type of porous media and had a fixed flow rate for all experiments. In this work, the TCAT model is applied to a dataset that consists of two different porous media types, constant head and flow rate conditions, varying resident fluid concentrations, and internal probes that measured the pressure and salt mass fraction. Parameter estimation is performed on a subset of the experimental data for the TCAT model as well as other existing non-dilute flow and transport models. The optimized parameters are then used for forward simulations and the accuracy of the models is compared.

Using a Model to Describe Students' Inductive Reasoning in Problem Solving

ERIC Educational Resources Information Center

Canadas, Maria C.; Castro, Encarnacion; Castro, Enrique

2009-01-01

Introduction: We present some aspects of a wider investigation (Canadas, 2007), whose main objective is to describe and characterize inductive reasoning used by Spanish students in years 9 and 10 when they work on problems that involved linear and quadratic sequences. Method: We produced a test composed of six problems with different…

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…

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

PubMed Central

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H.; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established. PMID:26924996

Factors of collaborative working: a framework for a collaboration model.

PubMed

Patel, Harshada; Pettitt, Michael; Wilson, John R

2012-01-01

The ability of organisations to support collaborative working environments is of increasing importance as they move towards more distributed ways of working. Despite the attention collaboration has received from a number of disparate fields, there is a lack of a unified understanding of the component factors of collaboration. As part of our work on a European Integrated Project, CoSpaces, collaboration and collaborative working and the factors which define it were examined through the literature and new empirical work with a number of partner user companies in the aerospace, automotive and construction sectors. This was to support development of a descriptive human factors model of collaboration - the CoSpaces Collaborative Working Model (CCWM). We identified seven main categories of factors involved in collaboration: Context, Support, Tasks, Interaction Processes, Teams, Individuals, and Overarching Factors, and summarised these in a framework which forms a basis for the model. We discuss supporting evidence for the factors which emerged from our fieldwork with user partners, and use of the model in activities such as collaboration readiness profiling. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Factors accounting for youth suicide attempt in Hong Kong: a model building.

PubMed

Wan, Gloria W Y; Leung, Patrick W L

2010-10-01

This study aimed at proposing and testing a conceptual model of youth suicide attempt. We proposed a model that began with family factors such as a history of physical abuse and parental divorce/separation. Family relationship, presence of psychopathology, life stressors, and suicide ideation were postulated as mediators, leading to youth suicide attempt. The stepwise entry of the risk factors to a logistic regression model defined their proximity as related to suicide attempt. Path analysis further refined our proposed model of youth suicide attempt. Our originally proposed model was largely confirmed. The main revision was dropping parental divorce/separation as a risk factor in the model due to lack of significant contribution when examined alongside with other risk factors. This model was cross-validated by gender. This study moved research on youth suicide from identification of individual risk factors to model building, integrating separate findings of the past studies.

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

Discussion and revision of the mathematical modeling tool described in the previously published article "Modeling HIV Transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy".

PubMed

Cassels, Susan; Pearson, Cynthia R; Kurth, Ann E; Martin, Diane P; Simoni, Jane M; Matediana, Eduardo; Gloyd, Stephen

2009-07-01

Mathematical models are increasingly used in social and behavioral studies of HIV transmission; however, model structures must be chosen carefully to best answer the question at hand and conclusions must be interpreted cautiously. In Pearson et al. (2007), we presented a simple analytically tractable deterministic model to estimate the number of secondary HIV infections stemming from a population of HIV-positive Mozambicans and to evaluate how the estimate would change under different treatment and behavioral scenarios. In a subsequent application of the model with a different data set, we observed that the model produced an unduly conservative estimate of the number of new HIV-1 infections. In this brief report, our first aim is to describe a revision of the model to correct for this underestimation. Specifically, we recommend adjusting the population-level sexually transmitted infection (STI) parameters to be applicable to the individual-level model specification by accounting for the proportion of individuals uninfected with an STI. In applying the revised model to the original data, we noted an estimated 40 infections/1000 HIV-positive persons per year (versus the original 23 infections/1000 HIV-positive persons per year). In addition, the revised model estimated that highly active antiretroviral therapy (HAART) along with syphilis and herpes simplex virus type 2 (HSV-2) treatments combined could reduce HIV-1 transmission by 72% (versus 86% according to the original model). The second aim of this report is to discuss the advantages and disadvantages of mathematical models in the field and the implications of model interpretation. We caution that simple models should be used for heuristic purposes only. Since these models do not account for heterogeneity in the population and significantly simplify HIV transmission dynamics, they should be used to describe general characteristics of the epidemic and demonstrate the importance or sensitivity of parameters in the

The Lewis Electron-Pair Model, Spectroscopy, and the Role of the Orbital Picture in Describing the Electronic Sructure of Molecules.

ERIC Educational Resources Information Center

Gallup, G. A.

1988-01-01

Describes why specific forms of orbitals used to interpret spectroscopy involving electronic transitions may not say much about the electronic structure of molecules. Discusses several theoretical approaches to explain the anomoly. Determines that the Lewis electron-pair model for molecules is a good predictor of spectroscopic results. (ML)

The Barrett-Crane model: asymptotic measure factor

NASA Astrophysics Data System (ADS)

Kamiński, Wojciech; Steinhaus, Sebastian

2014-04-01

The original spin foam model construction for 4D gravity by Barrett and Crane suffers from a few troubling issues. In the simple examples of the vertex amplitude they can be summarized as the existence of contributions to the asymptotics from non-geometric configurations. Even restricted to geometric contributions the amplitude is not completely worked out. While the phase is known to be the Regge action, the so-called measure factor has remained mysterious for a decade. In the toy model case of the 6j symbol this measure factor has a nice geometric interpretation of V-1/2 leading to speculations that a similar interpretation should be possible also in the 4D case. In this paper we provide the first geometric interpretation of the geometric part of the asymptotic for the spin foam consisting of two glued 4-simplices (decomposition of the 4-sphere) in the Barrett-Crane model in the large internal spin regime.

Interculture: Some Concepts for Describing the Situation of Immigrants.

ERIC Educational Resources Information Center

Ekstrand, Lars Henric; And Others

1981-01-01

Attempts to find new ways of describing and analyzing dynamic interactions in country of origin, host country, and immigrant community caused by migration. Analyzes linguistic models, concept of culture, emigration psychology, and identity formation. (Author/BK)

Consumer's Online Shopping Influence Factors and Decision-Making Model

NASA Astrophysics Data System (ADS)

Yan, Xiangbin; Dai, Shiliang

Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

Use of nonlinear models for describing scrotal circumference growth in Guzerat bulls raised under grazing conditions.

PubMed

Loaiza-Echeverri, A M; Bergmann, J A G; Toral, F L B; Osorio, J P; Carmo, A S; Mendonça, L F; Moustacas, V S; Henry, M

2013-03-15

The objective was to use various nonlinear models to describe scrotal circumference (SC) growth in Guzerat bulls on three farms in the state of Minas Gerais, Brazil. The nonlinear models were: Brody, Logistic, Gompertz, Richards, Von Bertalanffy, and Tanaka, where parameter A is the estimated testis size at maturity, B is the integration constant, k is a maturating index and, for the Richards and Tanaka models, m determines the inflection point. In Tanaka, A is an indefinite size of the testis, and B and k adjust the shape and inclination of the curve. A total of 7410 SC records were obtained every 3 months from 1034 bulls with ages varying between 2 and 69 months (<240 days of age = 159; 241-365 days = 451; 366-550 days = 1443; 551-730 days = 1705; and >731 days = 3652 SC measurements). Goodness of fit was evaluated by coefficients of determination (R(2)), error sum of squares, average prediction error (APE), and mean absolute deviation. The Richards model did not reach the convergence criterion. The R(2) were similar for all models (0.68-0.69). The error sum of squares was lowest for the Tanaka model. All models fit the SC data poorly in the early and late periods. Logistic was the model which best estimated SC in the early phase (based on APE and mean absolute deviation). The Tanaka and Logistic models had the lowest APE between 300 and 1600 days of age. The Logistic model was chosen for analysis of the environmental influence on parameters A and k. Based on absolute growth rate, SC increased from 0.019 cm/d, peaking at 0.025 cm/d between 318 and 435 days of age. Farm, year, and season of birth significantly affected size of adult SC and SC growth rate. An increase in SC adult size (parameter A) was accompanied by decreased SC growth rate (parameter k). In conclusion, SC growth in Guzerat bulls was characterized by an accelerated growth phase, followed by decreased growth; this was best represented by the Logistic model. The inflection point occurred at

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

Scale-model charge-transfer technique for measuring enhancement factors

NASA Technical Reports Server (NTRS)

Kositsky, J.; Nanevicz, J. E.

1991-01-01

Determination of aircraft electric field enhancement factors is crucial when using airborne field mill (ABFM) systems to accurately measure electric fields aloft. SRI used the scale model charge transfer technique to determine enhancement factors of several canonical shapes and a scale model Learjet 36A. The measured values for the canonical shapes agreed with known analytic solutions within about 6 percent. The laboratory determined enhancement factors for the aircraft were compared with those derived from in-flight data gathered by a Learjet 36A outfitted with eight field mills. The values agreed to within experimental error (approx. 15 percent).

A Multilevel Multiset Time-Series Model for Describing Complex Developmental Processes

PubMed Central

Ma, Xin; Shen, Jianping

2017-01-01

The authors sought to develop an analytical platform where multiple sets of time series can be examined simultaneously. This multivariate platform capable of testing interaction effects among multiple sets of time series can be very useful in empirical research. The authors demonstrated that the multilevel framework can readily accommodate this analytical capacity. Given their intention to use the multilevel multiset time-series model to pursue complicated research purposes, their resulting model is relatively simple to specify, to run, and to interpret. These advantages make the adoption of their model relatively effortless as long as researchers have the basic knowledge and skills in working with multilevel growth modeling. With multiple potential extensions of their model, the establishment of this analytical platform for analysis of multiple sets of time series can inspire researchers to pursue far more advanced research designs to address complex developmental processes in reality. PMID:29881094

An analytical mechanical model to describe the response of NiTi rotary endodontic files in a curved root canal.

PubMed

Leroy, Agnès Marie Françoise; Bahia, Maria Guiomar de Azevedo; Ehrlacher, Alain; Buono, Vicente Tadeu Lopes

2012-08-01

To build a mathematical model describing the mechanical behavior of NiTi rotary files while they are rotating in a root canal. The file was seen as a beam undergoing large transformations. The instrument was assumed to be rotating steadily in the root canal, and the geometry of the canal was considered as a known parameter of the problem. The formulae of large transformations mechanics then allowed the calculation of the Green-Lagrange strain field in the file. The non-linear mechanical behavior of NiTi was modeled as a continuous piecewise linear function, assuming that the material did not reach plastic deformation. Criteria locating the changes of behavior of NiTi were established and the tension field in the file, and the external efforts applied on it were calculated. The unknown variable of torsion was deduced from the equilibrium equation system using a Coulomb contact law which solved the problem on a cycle of rotation. In order to verify that the model described well reality, three-point bending experiments were managed on superelastic NiTi wires, whose results were compared to the theoretical ones. It appeared that the model gave a good mentoring of the empirical results in the range of bending angles that interested us. Knowing the geometry of the root canal, one is now able to write the equations of the strain and stress fields in the endodontic instrument, and to quantify the impact of each macroscopic parameter of the problem on its response. This should be useful to predict failure of the files under rotating bending fatigue, and to optimize the geometry of the files. Copyright © 2012 Elsevier B.V. All rights reserved.

Computational Thermochemistry: Scale Factor Databases and Scale Factors for Vibrational Frequencies Obtained from Electronic Model Chemistries.

PubMed

Alecu, I M; Zheng, Jingjing; Zhao, Yan; Truhlar, Donald G

2010-09-14

Optimized scale factors for calculating vibrational harmonic and fundamental frequencies and zero-point energies have been determined for 145 electronic model chemistries, including 119 based on approximate functionals depending on occupied orbitals, 19 based on single-level wave function theory, three based on the neglect-of-diatomic-differential-overlap, two based on doubly hybrid density functional theory, and two based on multicoefficient correlation methods. Forty of the scale factors are obtained from large databases, which are also used to derive two universal scale factor ratios that can be used to interconvert between scale factors optimized for various properties, enabling the derivation of three key scale factors at the effort of optimizing only one of them. A reduced scale factor optimization model is formulated in order to further reduce the cost of optimizing scale factors, and the reduced model is illustrated by using it to obtain 105 additional scale factors. Using root-mean-square errors from the values in the large databases, we find that scaling reduces errors in zero-point energies by a factor of 2.3 and errors in fundamental vibrational frequencies by a factor of 3.0, but it reduces errors in harmonic vibrational frequencies by only a factor of 1.3. It is shown that, upon scaling, the balanced multicoefficient correlation method based on coupled cluster theory with single and double excitations (BMC-CCSD) can lead to very accurate predictions of vibrational frequencies. With a polarized, minimally augmented basis set, the density functionals with zero-point energy scale factors closest to unity are MPWLYP1M (1.009), τHCTHhyb (0.989), BB95 (1.012), BLYP (1.013), BP86 (1.014), B3LYP (0.986), MPW3LYP (0.986), and VSXC (0.986).

An Introduction to Human Factors and Combat Models

DTIC Science & Technology

1989-03-01

Combat Models by Timothy F. Schroth Captain, United States Army B . A., Temple University, 1982 Submitted in partial fulfillment of the requirements for...INTRODUCTION .......... ................. 4 B . DEFINING HUMAN FACTORS - AN HISTORICAL APPROACH 4 C. BEFORE/AFTER THE BATTLE ...... ........... 8 1. Culture...16 III. COMBAT MODELS ....... .................. 18 A. INTRODUCTION ....... ................. 18 B . PURPOSE OF COMBAT MODELS ... ........... 20 1

A Biophysical Neural Model To Describe Spatial Visual Attention

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

Hugues, Etienne; Jose, Jorge V.

2008-02-14

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We firstmore » constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.« less

A Biophysical Neural Model To Describe Spatial Visual Attention

NASA Astrophysics Data System (ADS)

Hugues, Etienne; José, Jorge V.

2008-02-01

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.

Calibration of the computer model describing flows in the water supply system; example of the application of a genetic algorithm

NASA Astrophysics Data System (ADS)

Orłowska-Szostak, Maria; Orłowski, Ryszard

2017-11-01

The paper discusses some relevant aspects of the calibration of a computer model describing flows in the water supply system. The authors described an exemplary water supply system and used it as a practical illustration of calibration. A range of measures was discussed and applied, which improve the convergence and effective use of calculations in the calibration process and also the effect of such calibration which is the validity of the results obtained. Drawing up results of performed measurements, i.e. estimating pipe roughnesses, the authors performed using the genetic algorithm implementation of which is a software developed by Resan Labs company from Brazil.

On the Relation between the Linear Factor Model and the Latent Profile Model

ERIC Educational Resources Information Center

Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul

2011-01-01

The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…

A Lagging Model for Describing Drawdown Induced by a Constant-Rate Pumping in a Leaky Confined Aquifer

NASA Astrophysics Data System (ADS)

Lin, Ye-Chen; Yeh, Hund-Der

2017-10-01

This study proposes a generalized Darcy's law with considering phase lags in both the water flux and drawdown gradient to develop a lagging flow model for describing drawdown induced by constant-rate pumping (CRP) in a leaky confined aquifer. The present model has a mathematical formulation similar to the dual-porosity model. The Laplace-domain solution of the model with the effect of wellbore storage is derived by the Laplace transform method. The time-domain solution for the case of neglecting the wellbore storage and well radius is developed by the use of Laplace transform and Weber transform. The results of sensitivity analysis based on the solution indicate that the drawdown is very sensitive to the change in each of the transmissivity and storativity. Also, a study for the lagging effect on the drawdown indicates that its influence is significant associated with the lag times. The present solution is also employed to analyze a data set taken from a CRP test conducted in a fractured aquifer in South Dakota, USA. The results show the prediction of this new solution with considering the phase lags has very good fit to the field data, especially at early pumping time. In addition, the phase lags seem to have a scale effect as indicated in the results. In other words, the lagging behavior is positively correlated with the observed distance in the Madison aquifer.

Fractal attractors and singular invariant measures in two-sector growth models with random factor shares

NASA Astrophysics Data System (ADS)

La Torre, Davide; Marsiglio, Simone; Mendivil, Franklin; Privileggi, Fabio

2018-05-01

We analyze a multi-sector growth model subject to random shocks affecting the two sector-specific production functions twofold: the evolution of both productivity and factor shares is the result of such exogenous shocks. We determine the optimal dynamics via Euler-Lagrange equations, and show how these dynamics can be described in terms of an iterated function system with probability. We also provide conditions that imply the singularity of the invariant measure associated with the fractal attractor. Numerical examples show how specific parameter configurations might generate distorted copies of the Barnsley's fern attractor.

Spatial Distribution and Secular Variation of Geomagnetic Filed in China Described by the CHAOS-6 Model and its Error Analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Gu, Z.; Chen, B.; Yuan, J.; Wang, C.

2016-12-01

The CHAOS-6 geomagnetic field model, presented in 2016 by the Denmark's national space institute (DTU Space), is a model of the near-Earth magnetic field. According the CHAOS-6 model, seven component data of geomagnetic filed at 30 observatories in China in 2015 and at 3 observatories in China spanning the time interval 2008.0-2016.5 were calculated. Also seven component data of geomagnetic filed from the geomagnetic data of practical observations in China was obtained. Based on the model calculated data and the practical data, we have compared and analyzed the spatial distribution and the secular variation of the geomagnetic field in China. There is obvious difference between the two type data. The CHAOS-6 model cannot describe the spatial distribution and the secular variation of the geomagnetic field in China with comparative precision because of the regional and local magnetic anomalies in China.

A method for testing whether model predictions fall within a prescribed factor of true values, with an application to pesticide leaching

USGS Publications Warehouse

Parrish, Rudolph S.; Smith, Charles N.

1990-01-01

A quantitative method is described for testing whether model predictions fall within a specified factor of true values. The technique is based on classical theory for confidence regions on unknown population parameters and can be related to hypothesis testing in both univariate and multivariate situations. A capability index is defined that can be used as a measure of predictive capability of a model, and its properties are discussed. The testing approach and the capability index should facilitate model validation efforts and permit comparisons among competing models. An example is given for a pesticide leaching model that predicts chemical concentrations in the soil profile.

Detecting Social Desirability Bias Using Factor Mixture Models

ERIC Educational Resources Information Center

Leite, Walter L.; Cooper, Lou Ann

2010-01-01

Based on the conceptualization that social desirable bias (SDB) is a discrete event resulting from an interaction between a scale's items, the testing situation, and the respondent's latent trait on a social desirability factor, we present a method that makes use of factor mixture models to identify which examinees are most likely to provide…

Moving in Parallel Toward a Modern Modeling Epistemology: Bayes Factors and Frequentist Modeling Methods.

PubMed

Rodgers, Joseph Lee

2016-01-01

The Bayesian-frequentist debate typically portrays these statistical perspectives as opposing views. However, both Bayesian and frequentist statisticians have expanded their epistemological basis away from a singular focus on the null hypothesis, to a broader perspective involving the development and comparison of competing statistical/mathematical models. For frequentists, statistical developments such as structural equation modeling and multilevel modeling have facilitated this transition. For Bayesians, the Bayes factor has facilitated this transition. The Bayes factor is treated in articles within this issue of Multivariate Behavioral Research. The current presentation provides brief commentary on those articles and more extended discussion of the transition toward a modern modeling epistemology. In certain respects, Bayesians and frequentists share common goals.

Describing the environmental fate of diuron in a tropical river catchment.

PubMed

Camenzuli, Louise; Scheringer, Martin; Gaus, Caroline; Ng, Carla A; Hungerbühler, Konrad

2012-12-01

The use of the herbicide diuron on sugarcane fields along the river catchments of the Great Barrier Reef (GBR) in Australia is an issue of concern due to high levels of diuron reported in the GBR lagoon, and has recently led to a restriction on the use of diuron during the 2011/12 wet season. An important question in this context is how much diuron is mobilised from the agricultural area by strong rainfall and floods in the wet season and transferred to the GBR lagoon. We have set up a multimedia chemical fate model for a tropical catchment to describe the fate of diuron within the Tully River catchment, Queensland, Australia. The model includes highly variable rainfall based on meteorological data from the Tully River catchment and a flood water compartment on top of the agricultural soil that is present during times for which floods were reported. The model is driven by diuron application data estimated for the Tully River catchment and is solved for time-dependent diuron concentrations in agricultural soil and seawater. Model results show that on average 25% of the diuron applied every year is transferred to the GBR lagoon with rainwater and flood water runoff. Diuron concentrations estimated for the seawater range from 0.1 ng/L to 12 ng/L and are in good agreement with concentrations measured in the GBR lagoon. The uncertainty of the diuron concentrations estimated for seawater is approximately a factor of two and mainly derives from uncertainty in the diuron degradation half-life in soil, properties of the soil compartment such as organic matter content, and the speed of the seawater current removing diuron dissolved in seawater from the seawater compartment of the model. Copyright © 2012 Elsevier B.V. All rights reserved.

Low-Dimensional Models of "Neuro-Glio-Vascular Unit" for Describing Neural Dynamics under Normal and Energy-Starved Conditions.

PubMed

Chhabria, Karishma; Chakravarthy, V Srinivasa

2016-01-01

The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low--dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an "energy" variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising KATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛp, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛp could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed "neuron-energy" unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as

The "zing factor"-how do faculty describe the best pediatrics residents?

PubMed

Rosenbluth, Glenn; O'Brien, Bridget; Asher, Emily M; Cho, Christine S

2014-03-01

Faculty in graduate medical education programs may not have uniform approaches to differentiating the quality of residents, and reviews of evaluations suggest that faculty use different standards when assessing residents. Standards for assessing residents also do not consistently map to items on evaluation forms. One way to improve assessment is to reach consensus on the traits and behaviors that are (or should be) present in the best residents. A trained interviewer conducted semistructured interviews with faculty affiliated with 2 pediatrics residency programs until content saturation was achieved. Interviewees were asked to describe specific traits present in residents they identify as the best. Interviews were recorded and transcribed. We used an iterative, inductive approach to generate a coding scheme and identify common themes. From 23 interviews, we identified 7 thematic categories of traits and behaviors: personality, energy, professionalism, team behaviors, self-improvement behaviors, patient-interaction behaviors, and medical knowledge and clinical skills (including a subcategory, knowledge integration). Most faculty interviewees focused on traits like passion, enthusiasm, maturity, and reliability. Examination score or intelligence was mentioned less frequently than traits and behaviors categorized under personality and professionalism. Faculty identified many traits and behaviors in the residents they define as the best. The thematic categories had incomplete overlap with Accreditation Council for Graduate Medical Education (ACGME) and CanMEDS competencies. This research highlights the ongoing need to review our assessment strategies, and may have implications for the ACGME Milestone Project.

Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

PubMed

Maldonado, G; Greenland, S

1998-07-01

A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

Identification of major factors in Australian primary care pharmacists' practice environment that have a bearing on the implementation of professional models of practice.

PubMed

Jackson, John K; Hussainy, Safeera Y; Kirkpatrick, Carl M J

2017-08-01

Objective The aim of the present study was to describe an environmental framework for pharmacists in primary care in Australia and determine the major factors within that environment that have the greatest bearing on their capacity to implement patient-focused models of professional practice. Methods A draft framework for pharmacists' practice was developed by allocating structures, systems and related factors known to the researchers or identified from the literature as existing within pharmacists' internal, operational and external environments to one of five domains: Social, Technological, Economic, Environmental or Political [STEEP]. Focus groups of pharmacists used an adapted nominal group technique to assess the draft and add factors where necessary. Where applicable, factors were consolidated into groups to establish a revised framework. The three major factors or groups in each domain were identified. The results were compared with the enabling factors described in the profession's vision statement. Results Seventy-eight individual factors were ultimately identified, with 86% able to be grouped. The three dominant groups in each of the five domains that had a bearing on the implementation of professional models of practice were as follows: (1) Social: the education of pharmacists, their beliefs and the capacity of the pharmacist workforce; (2) Technological: current and future practice models, technology and workplace structures; (3) Economic: funding of services, the viability of practice and operation of the Pharmaceutical Benefits Scheme; (4) Environmental: attitudes and expectations of stakeholders, including consumers, health system reform and external competition; and (5) Political: regulation of practice, representation of the profession and policies affecting practice. Conclusions The three dominant groups of factors in each of the five STEEP environmental domains, which have a bearing on pharmacists' capacity to implement patient-focused models of

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

Human factors systems approach to healthcare quality and patient safety

PubMed Central

Carayon, Pascale; Wetterneck, Tosha B.; Rivera-Rodriguez, A. Joy; Hundt, Ann Schoofs; Hoonakker, Peter; Holden, Richard; Gurses, Ayse P.

2013-01-01

Human factors systems approaches are critical for improving healthcare quality and patient safety. The SEIPS (Systems Engineering Initiative for Patient Safety) model of work system and patient safety is a human factors systems approach that has been successfully applied in healthcare research and practice. Several research and practical applications of the SEIPS model are described. Important implications of the SEIPS model for healthcare system and process redesign are highlighted. Principles for redesigning healthcare systems using the SEIPS model are described. Balancing the work system and encouraging the active and adaptive role of workers are key principles for improving healthcare quality and patient safety. PMID:23845724

Reaction norm model to describe environmental sensitivity across first lactation in dairy cattle under tropical conditions.

PubMed

Bignardi, Annaiza Braga; El Faro, Lenira; Pereira, Rodrigo Junqueira; Ayres, Denise Rocha; Machado, Paulo Fernando; de Albuquerque, Lucia Galvão; Santana, Mário Luiz

2015-10-01

Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

QCD dipole model and k T factorization

NASA Astrophysics Data System (ADS)

Bialas, A.; Navelet, H.; Peschanski, R.

2001-01-01

It is shown that the colour dipole approach to hard scattering at high energy is fully compatible with k T factorization at the leading logarithm approximation (in - logx Bj). The relations between the dipole amplitudes and unintegrated diagonal and non-diagonal gluon distributions are given. It is also shown that including the exact gluon kinematics in the k T factorization formula destroys the conservation of transverse position vectors and thus is incompatible with the dipole model for both elastic and diffractive amplitudes.

Dependence of spectral characteristics on parameters describing CO2 exchange between crop species and the atmosphere

NASA Astrophysics Data System (ADS)

Uździcka, Bogna; Stróżecki, Marcin; Urbaniak, Marek; Juszczak, Radosław

2017-07-01

The aim of this paper is to demonstrate that spectral vegetation indices are good indicators of parameters describing the intensity of CO2 exchange between crops and the atmosphere. Measurements were conducted over 2011-2013 on plots of an experimental arable station on winter wheat, winter rye, spring barley, and potatoes. CO2 fluxes were measured using the dynamic closed chamber system, while spectral vegetation indices were determined using SKYE multispectral sensors. Based on spectral data collected in 2011 and 2013, various models to estimate net ecosystem productivity and gross ecosystem productivity were developed. These models were then verified based on data collected in 2012. The R2 for the best model based on spectral data ranged from 0.71 to 0.83 and from 0.78 to 0.92, for net ecosystem productivity and gross ecosystem productivity, respectively. Such high R2 values indicate the utility of spectral vegetation indices in estimating CO2 fluxes of crops. The effects of the soil background turned out to be an important factor decreasing the accuracy of the tested models.

Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study.

PubMed

Cottrell, Gilles; Kouwaye, Bienvenue; Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André

2012-01-01

Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission--even at a very local scale--is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.

Use of a probabilistic PBPK/PD model to calculate Data Derived Extrapolation Factors for chlorpyrifos.

PubMed

Poet, Torka S; Timchalk, Charles; Bartels, Michael J; Smith, Jordan N; McDougal, Robin; Juberg, Daland R; Price, Paul S

2017-06-01

A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model combined with Monte Carlo analysis of inter-individual variation was used to assess the effects of the insecticide, chlorpyrifos and its active metabolite, chlorpyrifos oxon in humans. The PBPK/PD model has previously been validated and used to describe physiological changes in typical individuals as they grow from birth to adulthood. This model was updated to include physiological and metabolic changes that occur with pregnancy. The model was then used to assess the impact of inter-individual variability in physiology and biochemistry on predictions of internal dose metrics and quantitatively assess the impact of major sources of parameter uncertainty and biological diversity on the pharmacodynamics of red blood cell acetylcholinesterase inhibition. These metrics were determined in potentially sensitive populations of infants, adult women, pregnant women, and a combined population of adult men and women. The parameters primarily responsible for inter-individual variation in RBC acetylcholinesterase inhibition were related to metabolic clearance of CPF and CPF-oxon. Data Derived Extrapolation Factors that address intra-species physiology and biochemistry to replace uncertainty factors with quantitative differences in metrics were developed in these same populations. The DDEFs were less than 4 for all populations. These data and modeling approach will be useful in ongoing and future human health risk assessments for CPF and could be used for other chemicals with potential human exposure. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

Stability margin of linear systems with parameters described by fuzzy numbers.

PubMed

Husek, Petr

2011-10-01

This paper deals with the linear systems with uncertain parameters described by fuzzy numbers. The problem of determining the stability margin of those systems with linear affine dependence of the coefficients of a characteristic polynomial on system parameters is studied. Fuzzy numbers describing the system parameters are allowed to be characterized by arbitrary nonsymmetric membership functions. An elegant solution, graphical in nature, based on generalization of the Tsypkin-Polyak plot is presented. The advantage of the presented approach over the classical robust concept is demonstrated on a control of the Fiat Dedra engine model and a control of the quarter car suspension model.

A mathematical model describing the glycemic response of diabetic patients to meal and i.v. infusion of insulin.

PubMed

Fabietti, P G; Calabrese, G; Iorio, M; Bistoni, S; Brunetti, P; Sarti, E; Benedetti, M M

2001-10-01

Nine type 1 diabetic patients were studied for 24 hours. During this period they were given three calibrated meals. The glycemia was feedback-controlled by means of an artificial pancreas. The blood concentration of glucose and the infusion speed of the insulin were measured every minute. The experimental data referring to each of the three meals were used to estimate the parameters of a mathematical model suitable for describing the glycemic response of diabetic patients at meals and at the i.v. infusion of exogenous insulin. From the estimate a marked dispersion of the parameters was found, both interindividual and intraindividual. Nevertheless the models thus obtained seem to be usable for the synthesis of a feedback controller, especially in view of creating a portable artificial pancreas that now seems possible owing to the realization (so far experimental) of sufficiently reliable glucose concentration sensors.

The Meaning of Higher-Order Factors in Reflective-Measurement Models

ERIC Educational Resources Information Center

Eid, Michael; Koch, Tobias

2014-01-01

Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…

[Risk factors on the recurrence of ischemic stroke and the establishment of a Cox's regression model].

PubMed

An, Ya-chen; Chen, Yun-xia; Wang, Yu-xun; Zhao, Xiao-jing; Wang, Yan; Zhang, Jiang; Li, Chun-ling; Peng, Yan-bo; Gao, Su-ling; Chang, Li-sha; Zhang, Li; Xue, Xin-hong; Chen, Rui-ying; Wang, Da-li

2011-08-01

To investigate the risk factors and establish the Cox's regression model on the recurrence of ischemic stroke. We retrospectively reviewed consecutive patients with ischemic stroke admitted to the Neurology Department of the Hebei United University Affiliated Hospital between January 1, 2008 and December 31, 2009. Cases had been followed since the onset of ischemic stroke. The follow-up program was finished in June 30, 2010. Kaplan-Meier methods were used to describe the recurrence rate. Monovariant and multivariate Cox's proportional hazard regression model were used to analyze the risk factors associated to the episodes of recurrence. And then, a recurrence model was set up. During the period of follow-up program, 79 cases were relapsed, with the recurrence rates as 12.75% in one year and 18.87% in two years. Monovariant and multivariate Cox's proportional hazard regression model showed that the independent risk factors that were associated with the recurrence appeared to be age (X₁) (RR = 1.025, 95%CI: 1.003 - 1.048), history of hypertension (X₂) (RR = 1.976, 95%CI: 1.014 - 3.851), history of family strokes (X₃) (RR = 2.647, 95%CI: 1.175 - 5.961), total cholesterol amount (X₄) (RR = 1.485, 95%CI: 1.214 - 1.817), ESRS total scores (X₅) (RR = 1.327, 95%CI: 1.057 - 1.666) and progression of the disease (X₆) (RR = 1.889, 95%CI: 1.123 - 3.178). Personal prognosis index (PI) of the recurrence model was as follows: PI = 0.025X₁ + 0.681X₂ + 0.973X₃ + 0.395X₄ + 0.283X₅ + 0.636X₆. The smaller the personal prognosis index was, the lower the recurrence risk appeared, while the bigger the personal prognosis index was, the higher the recurrence risk appeared. Age, history of hypertension, total cholesterol amount, total scores of ESRS, together with the disease progression were the independent risk factors associated with the recurrence episodes of ischemic stroke. Both recurrence model and the personal prognosis index equation were successful

Models describing metronidazole pharmacokinetics in relation to hemodynamics in turkeys.

PubMed

Grabowski, Tomasz; Pasławska, Urszula; Poźniak, Błażej; Świtała, Marcin

2017-06-01

Linking haemodynamic (HD) and pharmacokinetic (PK) parameters provides much insight into interrelations between circulatory system and drug disposition. This effect is particularly pronounced in rapidly growing animals. Heart rate (HR), cardiac output (CO) and stroke volume (SV) are tightly linked with the animal's age and correlate with the increasing body weight (BW). The aim of this study was to establish and validate the relations between BW, HD and chosen PK parameters of metronidazole (MTZ) and its metabolite - hydroxymetronidazole (MTZ-OH) in growing turkeys. The study was carried out on broiler turkeys (BUT-9, n=26). All individuals were subjected to single dose PK studies four times, that is when the mean BW in the group reached: 1.4 (group A); 2.7 (group B); 5.5 (group C); 10.7kg (group D). Some PK parameters normalized with regard to HR were found to take constant values in all the age groups under investigation. CO↔1/MRT, SV↔1/MRT and SV↔MRT model was validated with regard to both metabolite and drug PK. This study proposed a model for the analysis of the relations HD↔BW and HD↔PK. Models developed in this study provide empirical evidence that HD affect the PK of MTZ and MTZ-OH in a different fashion. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dimensional models of personality: the five-factor model and the DSM-5

PubMed Central

Trull, Timothy J.; Widiger, Thomas A.

2013-01-01

It is evident that the classification of personality disorder is shifting toward a dimensional trait model and, more specifically, the five-factor model (FFM). The purpose of this paper is to provide an overview of the FFM of personality disorder. It will begin with a description of this dimensional model of normal and abnormal personality functioning, followed by a comparison with a proposal for future revisions to DSM-5 and a discussion of its potential advantages as an integrative hierarchical model of normal and abnormal personality structure. PMID:24174888

A drift-diffusion checkpoint model predicts a highly variable and growth-factor-sensitive portion of the cell cycle G1 phase.

PubMed

Jones, Zack W; Leander, Rachel; Quaranta, Vito; Harris, Leonard A; Tyson, Darren R

2018-01-01

Even among isogenic cells, the time to progress through the cell cycle, or the intermitotic time (IMT), is highly variable. This variability has been a topic of research for several decades and numerous mathematical models have been proposed to explain it. Previously, we developed a top-down, stochastic drift-diffusion+threshold (DDT) model of a cell cycle checkpoint and showed that it can accurately describe experimentally-derived IMT distributions [Leander R, Allen EJ, Garbett SP, Tyson DR, Quaranta V. Derivation and experimental comparison of cell-division probability densities. J. Theor. Biol. 2014;358:129-135]. Here, we use the DDT modeling approach for both descriptive and predictive data analysis. We develop a custom numerical method for the reliable maximum likelihood estimation of model parameters in the absence of a priori knowledge about the number of detectable checkpoints. We employ this method to fit different variants of the DDT model (with one, two, and three checkpoints) to IMT data from multiple cell lines under different growth conditions and drug treatments. We find that a two-checkpoint model best describes the data, consistent with the notion that the cell cycle can be broadly separated into two steps: the commitment to divide and the process of cell division. The model predicts one part of the cell cycle to be highly variable and growth factor sensitive while the other is less variable and relatively refractory to growth factor signaling. Using experimental data that separates IMT into G1 vs. S, G2, and M phases, we show that the model-predicted growth-factor-sensitive part of the cell cycle corresponds to a portion of G1, consistent with previous studies suggesting that the commitment step is the primary source of IMT variability. These results demonstrate that a simple stochastic model, with just a handful of parameters, can provide fundamental insights into the biological underpinnings of cell cycle progression.

Using Neural Networks to Describe Tracer Correlations

NASA Technical Reports Server (NTRS)

Lary, D. J.; Mueller, M. D.; Mussa, H. Y.

2003-01-01

Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). In this study a neural network using Quickprop learning and one hidden layer with eight nodes was able to reproduce the CH4-N2O correlation with a correlation co- efficient of 0.9995. Such an accurate representation of tracer-tracer correlations allows more use to be made of long-term datasets to constrain chemical models. Such as the dataset from the Halogen Occultation Experiment (HALOE) which has continuously observed CH4, (but not N2O) from 1991 till the present. The neural network Fortran code used is available for download.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790

Four- and five-factor models of the WAIS-IV in a clinical sample: Variations in indicator configuration and factor correlational structure.

PubMed

Staffaroni, Adam M; Eng, Megan E; Moses, James A; Zeiner, Harriet Katz; Wickham, Robert E

2018-05-01

A growing body of research supports the validity of 5-factor models for interpreting the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). The majority of these studies have utilized the WAIS-IV normative or clinical sample, the latter of which differs in its diagnostic composition from the referrals seen at outpatient neuropsychology clinics. To address this concern, 2 related studies were conducted on a sample of 322 American military Veterans who were referred for outpatient neuropsychological assessment. In Study 1, 4 hierarchical models with varying indicator configurations were evaluated: 3 extant 5-factor models from the literature and the traditional 4-factor model. In Study 2, we evaluated 3 variations in correlation structure in the models from Study 1: indirect hierarchical (i.e., higher-order g), bifactor (direct hierarchical), and oblique models. The results from Study 1 suggested that both 4- and 5-factor models showed acceptable fit. The results from Study 2 showed that bifactor and oblique models offer improved fit over the typically specified indirect hierarchical model, and the oblique models outperformed the orthogonal bifactor models. An exploratory analysis found improved fit when bifactor models were specified with oblique rather than orthogonal latent factors. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach

PubMed Central

Sproesser, Gudrun; Schupp, Harald T; Renner, Britta

2018-01-01

and fitness apps, ranging from having “decided to” but not yet begun to act (stage 2; nutrition: 6.88%, 70/1017; fitness: 9.23%, 95/1029) to being “disengaged” following previous adoption (stage 5; nutrition: 13.77%, 140/1017; fitness: 15.06%, 155/1029). Conclusions Using a behavior stage model approach to describe the process of adopting nutrition and fitness apps revealed motivational stage differences between nonusers (being “unengaged,” having “decided not to act,” having “decided to act,” and being “disengaged”), which might contribute to a better understanding of the process of adopting mHealth apps and thus inform the future development of digital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive decision-making style. PMID:29535078

The forgotten cue: Daphnia bears a not yet described gravireceptive organ system

NASA Astrophysics Data System (ADS)

Laforsch, Christian; Fischer, Jessica; Wolfschoon Ribeiro, Bernard; Schoppmann, Kathrin; Trotter, Benjamin

Gravity has been the only constant environmental factor in evolution of life. For plenty of pelagic organisms it is the only reliable cue for orientation in a three dimensional space especially in turbid or completely dark waters. However, there is a considerable lack of knowledge about gravisensing mechanisms in a huge variety of plankton organisms. Here we introduce a novel mechanoreceptive organ system in the model organism Daphnia functioning as a sinking receptor for the detection of the gravitational field. This organ is connected to two prominent appendages known as the postabdominal setae with so far unknown functioning. Our morphological and behavioural studies show, that the organ system is involved in gravisensing by a passive deflection mechanism not yet described in the animal kingdom. The description of this bifunctional mechanoreceptor will help to elucidate general gravity-related mechanisms valid for other organisms as well and may therefore increase our knowledge on the evolution of graviperception in aquatic ecosystems.

Cognitive Factors Affecting Student Understanding of Geologic Time.

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

Presents a model that describes how students reconstruct geological transformations over time. Defines the critical factors influencing reconstructive thinking: (1) the transformation scheme, which influences the other diachronic schemes; (2) knowledge of geological processes; and (3) extracognitive factors. (Author/KHR)

A Twin Factor Mixture Modeling Approach to Childhood Temperament: Differential Heritability

PubMed Central

Scott, Brandon G.; Lemery-Chalfant, Kathryn; Clifford, Sierra; Tein, Jenn-Yun; Stoll, Ryan; Goldsmith, H. Hill

2016-01-01

Twin factor mixture modeling was used to identify temperament profiles, while simultaneously estimating a latent factor model for each profile with a sample of 787 twin pairs (Mage =7.4 years; SD = .84; 49% female; 88.3% Caucasian), using mother- and father-reported temperament. A 4-profile, 1-factor model fit the data well. Profiles included ‘Regulated, Typical Reactive’, ‘Well-regulated, Positive Reactive’, ‘Regulated, Surgent’, and ‘Dysregulated, Negative Reactive.’ All profiles were heritable, with heritability lower and shared environment also contributing to membership in the ‘Regulated, Typical Reactive’ and ‘Dysregulated, Negative Reactive’ profiles. PMID:27291568

Representing and organizing information to describe the lived experience of health from a personal factors perspective in the light of the International Classification of Functioning, Disability and Health (ICF): a discussion paper.

PubMed

Geyh, Szilvia; Schwegler, Urban; Peter, Claudio; Müller, Rachel

2018-03-06

To discuss the representation and organization of information describing persons' lived experience of health from a personal factors perspective in the light of the International Classification of Functioning, Disability and Health, using spinal cord injury as a case in point for disability. The scientific literature was reviewed, discussion rounds conducted, and qualitative secondary analyses of data carried out using an iterative inductive-deductive approach. Conceptual considerations are explicated that distinguish the personal factors perspective from other components of the International Classification of Functioning, Disability and Health. A representation structure is developed that organizes health-related concepts describing the internal context of functioning. Concepts are organized as individual facts, subjective experiences, and recurrent patterns of experience and behavior specifying 7 areas and 211 concept groups. The article calls for further scientific debate on the perspective of personal factors in the light of the International Classification of Functioning, Disability and Health. A structure that organizes concepts in relation to a personal factors perspective can enhance the comprehensiveness, transparency and standardization of health information, and contribute to the empowerment of persons with disabilities. Implications for rehabilitation The present study collected data from scientific literature reviews, discussion rounds and qualitative secondary analyses in order to develop a representation and organization of information describing persons' lived experience of health from a personal factors perspective in the light of the International Classification of Functioning, Disability and Health. The following representation structure for health-related information from a personal factors perspective was developed: (i) Individuals facts (i.e., socio-demographical factors, position in the immediate social and physical context, personal history

Factors influencing sorption of ciprofloxacin onto activated sludge: experimental assessment and modelling implications.

PubMed

Polesel, Fabio; Lehnberg, Kai; Dott, Wolfgang; Trapp, Stefan; Thomas, Kevin V; Plósz, Benedek Gy

2015-01-01

Many of the pharmaceuticals and personal care products occurring in municipal sewage are ionizing substances, and their partitioning behaviour is affected by ionic interactions with solid matrices. In activated sludge systems, such interactions have currently not been adequately understood and described, particularly for zwitterionic chemicals. Here we present an assessment of the effects of pH and iron salt dosing on the sorption of ciprofloxacin onto activated sludge using laboratory experiments and full-scale fate modelling. Experimental results were described with Freundlich isotherms and showed that non-linear sorption occurred under all the conditions tested. The greatest sorption potential was measured at pH=7.4, at which ciprofloxacin is speciated mostly as zwitterion. Iron salt dosing increased sorption under aerobic and, to a lesser extent, anoxic conditions, whereas no effect was registered under anaerobic conditions. The activated sludge model for xenobiotics (ASM-X) was extended with Freundlich-based sorption kinetics and used to predict the fate of ciprofloxacin in a wastewater treatment plant (WWTP). Scenario simulations, using experimental Freundlich parameters, were used to identify whether the assessed factors caused a significant increase of aqueous ciprofloxacin concentration in full-scale bioreactors. Simulation results suggest that a pH increase, rather than a reduction in iron salt dosing, could be responsible for a systematic deterioration of sorption of ciprofloxacin in the WWTP. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling impulsive factors for electronics and restaurant coupons’ e-store display

NASA Astrophysics Data System (ADS)

Ariningsih, P. K.; Nainggolan, M.; Sandy, I. A.

2018-04-01

In many times, the increment of e-store visitors does not followed by sales increment. Most purchases through e-commerce are impulsive buying, however only small amount of study is available to understand impulsive factors of e-store display. This paper suggests a preliminary concept on understanding the impulsive factors in Electronics and Restaurant Coupons e-store display, which are two among few popular group products sold through e-commerce. By conducting literature study and survey, 31 attributes were identified as impulsive factors in electronics e-store display and 20 attributes were identified as impulsive factors for restaurant coupon e-store. The attributes were then grouped into comprehensive impulsive factors by factor analysis. Each group of impulsive attributes were generated into 3 factors. Accessibility Factors and Trust Factors appeared for each group products. The other factors are Internal Factors for electronics e-store and Marketing factors for restaurant coupons e-store. Structural Equation Model of the impulsive factors was developed for each type of e-store, which stated the covariance between Trust Factors and Accessibility Factors. Based on preliminary model, Internal Factor and Trust Factor are influencing impulsive buying in electronics store. Special factor for electronics e-store is Internal Factor, while for restaurant coupons e-store is Marketing Factor.

Enhanced dopamine release by dopamine transport inhibitors described by a restricted diffusion model and fast scan cyclic voltammetry

PubMed Central

Hoffman, Alexander F.; Spivak, Charles E.; Lupica, Carl R.

2016-01-01

Fast-scan cyclic voltammetry (FSCV) using carbon fiber electrodes is widely used to rapidly monitor changes in dopamine (DA) levels in vitro and in vivo. Current analytical approaches utilize parameters such as peak oxidation current amplitude and decay times to estimate release and uptake processes, respectively. However, peak amplitude changes are often observed with uptake inhibitors, thereby confounding the interpretation of these parameters. To overcome this limitation, we demonstrate that a simple, 5 parameter, two compartment model mathematically describes DA signals as a balance of release (r/ke) and uptake (ku), summed with adsorption (kads and kdes) of DA to the carbon electrode surface. Using non-linear regression, we demonstrate that our model precisely describes measured DA signals obtained in brain slice recordings. The parameters extracted from these curves were then validated using pharmacological manipulations that selectively alter vesicular release or DA transporter (DAT)-mediated uptake. Manipulation of DA release through altered Ca2+/Mg2+ ratio or tetrodotoxin (TTX), reduced the release parameter with no effect on the uptake parameter. The DAT inhibitors methylenedioxypyrovalerone (MDPV), cocaine, and nomifensine significantly reduced uptake and increased vesicular DA release. In contrast, a low concentration of amphetamine reduced uptake but had no effect on DA release. Finally, the kappa-opioid receptor (KOR) agonist U50,488 significantly reduced vesicular DA release but had no effect on uptake. Together, these data demonstrate a novel analytical approach to distinguish the effects of manipulations on DA release or uptake that can be used to interpret FSCV data. PMID:27018734

Enhanced Dopamine Release by Dopamine Transport Inhibitors Described by a Restricted Diffusion Model and Fast-Scan Cyclic Voltammetry.

PubMed

Hoffman, Alexander F; Spivak, Charles E; Lupica, Carl R

2016-06-15

Fast-scan cyclic voltammetry (FSCV) using carbon fiber electrodes is widely used to rapidly monitor changes in dopamine (DA) levels in vitro and in vivo. Current analytical approaches utilize parameters such as peak oxidation current amplitude and decay times to estimate release and uptake processes, respectively. However, peak amplitude changes are often observed with uptake inhibitors, thereby confounding the interpretation of these parameters. To overcome this limitation, we demonstrate that a simple five-parameter, two-compartment model mathematically describes DA signals as a balance of release (r/ke) and uptake (ku), summed with adsorption (kads and kdes) of DA to the carbon electrode surface. Using nonlinear regression, we demonstrate that our model precisely describes measured DA signals obtained in brain slice recordings. The parameters extracted from these curves were then validated using pharmacological manipulations that selectively alter vesicular release or DA transporter (DAT)-mediated uptake. Manipulation of DA release through altering the Ca(2+)/Mg(2+) ratio or adding tetrodotoxin reduced the release parameter with no effect on the uptake parameter. DAT inhibitors methylenedioxypyrovalerone, cocaine, and nomifensine significantly reduced uptake and increased vesicular DA release. In contrast, a low concentration of amphetamine reduced uptake but had no effect on DA release. Finally, the kappa opioid receptor agonist U50,488 significantly reduced vesicular DA release but had no effect on uptake. Together, these data demonstrate a novel analytical approach to distinguish the effects of manipulations on DA release or uptake that can be used to interpret FSCV data.

A model of memory impairment in schizophrenia: cognitive and clinical factors associated with memory efficiency and memory errors.

PubMed

Brébion, Gildas; Bressan, Rodrigo A; Ohlsen, Ruth I; David, Anthony S

2013-12-01

Memory impairments in patients with schizophrenia have been associated with various cognitive and clinical factors. Hallucinations have been more specifically associated with errors stemming from source monitoring failure. We conducted a broad investigation of verbal memory and visual memory as well as source memory functioning in a sample of patients with schizophrenia. Various memory measures were tallied, and we studied their associations with processing speed, working memory span, and positive, negative, and depressive symptoms. Superficial and deep memory processes were differentially associated with processing speed, working memory span, avolition, depression, and attention disorders. Auditory/verbal and visual hallucinations were differentially associated with specific types of source memory error. We integrated all the results into a revised version of a previously published model of memory functioning in schizophrenia. The model describes the factors that affect memory efficiency, as well as the cognitive underpinnings of hallucinations within the source monitoring framework. © 2013.

Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

Treesearch

Patricia L. Andrews

2012-01-01

Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

Applying a physical continuum model to describe the broadband X-ray spectra of accreting pulsars at high luminosity

NASA Astrophysics Data System (ADS)

Pottschmidt, Katja; Hemphill, Paul B.; Wolff, Michael T.; Cheatham, Diana M.; Iwakiri, Wataru; Gottlieb, Amy M.; Falkner, Sebastian; Ballhausen, Ralf; Fuerst, Felix; Kuehnel, Matthias; Ferrigno, Carlo; Becker, Peter A.; Wood, Kent S.; Wilms, Joern

2018-01-01

A new window for better understanding the accretion onto strongly magnetized neutron stars in X-ray binaries is opening. In these systems the accreted material follows the magnetic field lines as it approaches the neutron star, forming accretion columns above the magnetic poles. The plasma falls toward the neutron star surface at near-relativistic speeds, losing energy by emitting X-rays. The X-ray spectral continua are commonly described using phenomenological models, i.e., power laws with different types of curved cut-offs at higher energies. Here we consider high luminosity pulsars. In these systems the mass transfer rate is high enough that the accreting plasma is thought to be decelerated in a radiation-dominated radiative shock in the accretion columns. While the theory of the emission from such shocks had already been developed by 2007, a model for direct comparison with X-ray continuum spectra in xspec or isis has only recently become available. Characteristic parameters of this model are the accretion column radius and the plasma temperature, among others. Here we analyze the broadband X-ray spectra of the accreting pulsars Centaurus X-3 and 4U 1626-67 obtained with NuSTAR. We present results from traditional empirical modeling as well as successfully apply the radiation-dominated radiative shock model. We also take the opportunity to compare to similar recent analyses of both sources using these and other observations.

Photon migration through a turbid slab described by a model based on diffusion approximation. I. Theory.

PubMed

Contini, D; Martelli, F; Zaccanti, G

1997-07-01

The diffusion approximation of the radiative transfer equation is a model used widely to describe photon migration in highly diffusing media and is an important matter in biological tissue optics. An analysis of the time-dependent diffusion equation together with its solutions for the slab geometry and for a semi-infinite diffusing medium are reported. These solutions, presented for both the time-dependent and the continuous wave source, account for the refractive index mismatch between the turbid medium and the surrounding medium. The results have been compared with those obtained when different boundary conditions were assumed. The comparison has shown that the effect of the refractive index mismatch cannot be disregarded. This effect is particularly important for the transmittance. The discussion of results also provides an analysis of the role of the absorption coefficient in the expression of the diffusion coefficient.

A new approach for describing glass transition kinetics.

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

Vasin, N. M.; Shchelkachev, M. G.; Vinokur, V. M.

2010-04-01

We use a functional integral technique generalizing the Keldysh diagram technique to describe glass transition kinetics. We show that the Keldysh functional approach takes the dynamical determinant arising in the glass dynamics into account exactly and generalizes the traditional approach based on using the supersymmetric dynamic generating functional method. In contrast to the supersymmetric method, this approach allows avoiding additional Grassmannian fields and tracking the violation of the fluctuation-dissipation theorem explicitly. We use this method to describe the dynamics of an Edwards-Anderson soft spin-glass-type model near the paramagnet-glass transition. We show that a Vogel-Fulcher-type dynamics arises in the fluctuation regionmore » only if the fluctuation-dissipation theorem is violated in the process of dynamical renormalization of the Keldysh action in the replica space.« less

An ensemble model of competitive multi-factor binding of the genome

PubMed Central

Wasson, Todd; Hartemink, Alexander J.

2009-01-01

Hundreds of different factors adorn the eukaryotic genome, binding to it in large number. These DNA binding factors (DBFs) include nucleosomes, transcription factors (TFs), and other proteins and protein complexes, such as the origin recognition complex (ORC). DBFs compete with one another for binding along the genome, yet many current models of genome binding do not consider different types of DBFs together simultaneously. Additionally, binding is a stochastic process that results in a continuum of binding probabilities at any position along the genome, but many current models tend to consider positions as being either binding sites or not. Here, we present a model that allows a multitude of DBFs, each at different concentrations, to compete with one another for binding sites along the genome. The result is an “occupancy profile,” a probabilistic description of the DNA occupancy of each factor at each position. We implement our model efficiently as the software package COMPETE. We demonstrate genome-wide and at specific loci how modeling nucleosome binding alters TF binding, and vice versa, and illustrate how factor concentration influences binding occupancy. Binding cooperativity between nearby TFs arises implicitly via mutual competition with nucleosomes. Our method applies not only to TFs, but also recapitulates known occupancy profiles of a well-studied replication origin with and without ORC binding. Importantly, the sequence preferences our model takes as input are derived from in vitro experiments. This ensures that the calculated occupancy profiles are the result of the forces of competition represented explicitly in our model and the inherent sequence affinities of the constituent DBFs. PMID:19720867

Public Libraries and Internet Public Access Models: Describing Possible Approaches.

ERIC Educational Resources Information Center

Tomasello, Tami K.; McClure, Charles R.

2002-01-01

Discusses ways of providing Internet access to the general public and analyzes eight models currently in use: public schools, public libraries, cybermobiles, public housing, community technology centers, community networks, kiosks, and cyber cafes. Concludes that public libraries may wish to develop collaborative strategies with other…

Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure

PubMed Central

Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J.; Barrada, Juan R.

2017-01-01

Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content. PMID:29085313

Describing a Strongly Correlated Model System with Density Functional Theory.

PubMed

Kong, Jing; Proynov, Emil; Yu, Jianguo; Pachter, Ruth

2017-07-06

The linear chain of hydrogen atoms, a basic prototype for the transition from a metal to Mott insulator, is studied with a recent density functional theory model functional for nondynamic and strong correlation. The computed cohesive energy curve for the transition agrees well with accurate literature results. The variation of the electronic structure in this transition is characterized with a density functional descriptor that yields the atomic population of effectively localized electrons. These new methods are also applied to the study of the Peierls dimerization of the stretched even-spaced Mott insulator to a chain of H 2 molecules, a different insulator. The transitions among the two insulating states and the metallic state of the hydrogen chain system are depicted in a semiquantitative phase diagram. Overall, we demonstrate the capability of studying strongly correlated materials with a mean-field model at the fundamental level, in contrast to the general pessimistic view on such a feasibility.

An Investigation of the Factor Structure and Convergent and Discriminant Validity of the Five-Factor Model Rating Form

ERIC Educational Resources Information Center

Samuel, Douglas B.; Mullins-Sweatt, Stephanie N.; Widiger, Thomas A.

2013-01-01

The Five-Factor Model Rating Form (FFMRF) is a one-page measure designed to provide an efficient assessment of the higher order domains of the Five Factor Model (FFM) as well as the more specific, lower order facets proposed by McCrae and Costa. Although previous research has suggested that the FFMRF's assessment of the lower order facets converge…

Modeling the Influence of Local Environmental Factors on Malaria Transmission in Benin and Its Implications for Cohort Study

PubMed Central

Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André

2012-01-01

Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission—even at a very local scale—is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors. As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages. This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics. PMID:22238582

Celecoxib restores angiogenic factor expression at the maternal-fetal interface in the BPH/5 mouse model of preeclampsia.

PubMed

Reijnders, Dorien; Liu, Chin-Chi; Xu, Xinjing; Zhao, Anna M; Olson, Kelsey N; Butler, Scott D; Douglas, Nataki C; Sones, Jenny L

2018-05-01

Preeclampsia (PE), a hypertensive disease of pregnancy, is a leading cause of fetal and maternal morbidity/mortality. Early angiogenic and inflammatory disturbances within the placenta are thought to underlie the development of the maternal PE syndrome and poor pregnancy outcomes. However, the exact etiology remains largely unknown. Here, we use the BPH/5 mouse model of PE to elucidate the way in which inflammation early in pregnancy contributes to abnormal expression of angiogenic factors at the maternal-fetal interface. We have previously described improvement in maternal hypertension and fetal growth restriction in this model after treatment with the anti-inflammatory cyclooxygenase-2 (Cox2) specific inhibitor celecoxib. To further characterize the mechanisms by which celecoxib improves poor pregnancy outcomes in BPH/5 mice, we determined expression of angiogenic factors and complement pathway components after celecoxib. In BPH/5 implantation sites there was increased hypoxia inducible factor-1α ( Hif1α), heme oxygenase-1 ( Ho-1), and stem cell factor ( Scf) mRNA concomitant with elevated prostaglandin synthase 2 ( Ptgs2), encoding Cox2, and elevated VEGF protein. Angiopoietin 1 ( Ang1), tunica interna endothelial cell kinase-2 receptor ( Tie2), complement factor 3 ( C3), and complement factor B ( CfB) were increased in midgestation BPH/5 placentae. Whereas BPH/5 expression levels of VEGF, Ang1, and Tie2 normalized after celecoxib, placental C3 and CfB mRNA remained unchanged. However, celecoxib did reduce the pregnancy-specific circulating soluble fms-like tyrosine kinase-1 (sFlt-1) rise in BPH/5 mice at midgestation. These data show that elevated Cox2 during implantation contributes to placental angiogenic factor imbalances in the BPH/5 mouse model of PE.

Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model

ERIC Educational Resources Information Center

Greenspan, Stephen

2006-01-01

Diana Baumrind's typology of parenting is based on a two-factor model of "control" and "warmth". Her recommended discipline style, labeled "authoritative parenting", was constructed by taking high scores on these two factors. A problem with authoritative parenting is that it does not allow for flexible and differentiated responses to discipline…

Human Modeling for Ground Processing Human Factors Engineering Analysis

NASA Technical Reports Server (NTRS)

Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

2011-01-01

There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

Multiparameter models in the management of the development of territories, taking into account the influence of hydrometeorological factors

NASA Astrophysics Data System (ADS)

Istomin, E. P.; Popov, N. N.; Sokolov, A. G.; Fokicheva, A. A.

2018-01-01

The article considers the geoinformation management of the territory as a way to manage the organizational and technical systems and territories distributed in space. The article describes the main factors for the development and implementation of management decisions, requirements for the territorial management system and the structure of knowledge and data. Mathematical one-parameter and multiparameter models of risk assessment of management decisions applied to the natural and climatic potential of the development of the territory were considered.

Indigenous Chinese Personality Constructs: Is the Five-Factor Model Complete?

ERIC Educational Resources Information Center

Cheung, Fanny M.; Leung, Kwok; Zhang, Jian-Xin; Sun, Hai-Fa; Gan, Yi-Qun; Song, Wei-Zhen; Xie, Dong

2001-01-01

Three studies involving Chinese respondents from China and Hong Kong and diverse respondents from Hawaii compared the Chinese Personality Assessment Inventory factor structure with the Revised NEO Personality Inventory (NEO-PI-R) and NEO-Five Factor Inventory. Results supported the universality of the five-factor model, the validity of NEO-PI-R,…

Multistate modeling of habitat dynamics: Factors affecting Florida scrub transition probabilities

USGS Publications Warehouse

Breininger, D.R.; Nichols, J.D.; Duncan, B.W.; Stolen, Eric D.; Carter, G.M.; Hunt, D.K.; Drese, J.H.

2010-01-01

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used 1.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, and can be used to assess

A MATHEMATICAL MODEL OF ELECTROSTATIC PRECIPITATION. (REVISION 1): VOLUME I. MODELING AND PROGRAMMING

EPA Science Inventory

The report briefly describes the fundamental mechanisms and limiting factors involved in the electrostatic precipitation process. It discusses theories and procedures used in the computer model to describe the physical mechanisms, and generally describes the major operations perf...

Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach.

PubMed

König, Laura M; Sproesser, Gudrun; Schupp, Harald T; Renner, Britta

2018-03-13

to" but not yet begun to act (stage 2; nutrition: 6.88%, 70/1017; fitness: 9.23%, 95/1029) to being "disengaged" following previous adoption (stage 5; nutrition: 13.77%, 140/1017; fitness: 15.06%, 155/1029). Using a behavior stage model approach to describe the process of adopting nutrition and fitness apps revealed motivational stage differences between nonusers (being "unengaged," having "decided not to act," having "decided to act," and being "disengaged"), which might contribute to a better understanding of the process of adopting mHealth apps and thus inform the future development of digital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive decision-making style. ©Laura M König, Gudrun Sproesser, Harald T Schupp, Britta Renner. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.03.2018.

Four Factors of Clinical Decision Making: A Teaching Model.

ERIC Educational Resources Information Center

Leist, James C.; Konen, Joseph C.

1996-01-01

Four factors of clinical decision making identified by medical students include quality of care, cost, ethics, and legal concerns. This paper argues that physicians have two responsibilities in the clinical decision-making model: to be the primary advocate for quality health care and to ensure balance among the four factors, working in partnership…

The cognitive-interpersonal maintenance model of anorexia nervosa revisited: a summary of the evidence for cognitive, socio-emotional and interpersonal predisposing and perpetuating factors

PubMed Central

2013-01-01

Aim To describe the evidence base relating to the Cognitive-Interpersonal Maintenance Model for anorexia nervosa (AN). Background A Cognitive-Interpersonal Maintenance Model maintenance model for anorexia nervosa was described in 2006. This model proposed that cognitive, socio-emotional and interpersonal elements acted together to both cause and maintain eating disorders. Method A review of the empirical literature relating to the key constructs of the model (cognitive, socio-emotional, interpersonal) risk and maintaining factors for anorexia nervosa was conducted. Results Set shifting and weak central coherence (associated with obsessive compulsive traits) have been widely studied. There is some evidence to suggest that a strong eye for detail and weak set shifting are inherited vulnerabilities to AN. Set shifting and global integration are impaired in the ill state and contribute to weak central coherence. In addition, there are wide-ranging impairments in socio-emotional processing including: an automatic bias in attention towards critical and domineering faces and away from compassionate faces; impaired signalling of, interpretation and regulation of emotions. Difficulties in social cognition may in part be a consequence of starvation but inherited vulnerabilities may also contribute to these traits. The shared familial traits may accentuate family members’ tendency to react to the frustrating and frightening symptoms of AN with high expressed emotion (criticism, hostility, overprotection), and inadvertently perpetuate the problem. Conclusion The cognitive interpersonal model is supported by accumulating evidence. The model is complex in that cognitive and socio-emotional factors both predispose to the illness and are exaggerated in the ill state. Furthermore, some of the traits are inherited vulnerabilities and are present in family members. The clinical formulations from the model are described as are new possibilities for targeted treatment. PMID:24999394

Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM

ERIC Educational Resources Information Center

Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman

2012-01-01

This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…

On non-exponential cosmological solutions with two factor spaces of dimensions m and 1 in the Einstein-Gauss-Bonnet model with a Λ-term

NASA Astrophysics Data System (ADS)

Ernazarov, K. K.

2017-12-01

We consider a (m + 2)-dimensional Einstein-Gauss-Bonnet (EGB) model with the cosmological Λ-term. We restrict the metrics to be diagonal ones and find for certain Λ = Λ(m) class of cosmological solutions with non-exponential time dependence of two scale factors of dimensions m > 2 and 1. Any solution from this class describes an accelerated expansion of m-dimensional subspace and tends asymptotically to isotropic solution with exponential dependence of scale factors.

Numerical Modeling Describing the Effects of Heterogeneous Distributions of Asperities on the Quasi-static Evolution of Frictional Slip

NASA Astrophysics Data System (ADS)

Selvadurai, P. A.; Parker, J. M.; Glaser, S. D.

2017-12-01

A better understanding of how slip accumulates along faults and its relation to the breakdown of shear stress is beneficial to many engineering disciplines, such as, hydraulic fracture and understanding induced seismicity (among others). Asperities forming along a preexisting fault resist the relative motion of the two sides of the interface and occur due to the interaction of the surface topographies. Here, we employ a finite element model to simulate circular partial slip asperities along a nominally flat frictional interface. Shear behavior of our partial slip asperity model closely matched the theory described by Cattaneo. The asperity model was employed to simulate a small section of an experimental fault formed between two bodies of polymethyl methacrylate, which consisted of multiple asperities whose location and sizes were directly measured using a pressure sensitive film. The quasi-static shear behavior of the interface was modeled for cyclical loading conditions, and the frictional dissipation (hysteresis) was normal stress dependent. We further our understanding by synthetically modeling lognormal size distributions of asperities that were randomly distributed in space. Synthetic distributions conserved the real contact area and aspects of the size distributions from the experimental case, allowing us to compare the constitutive behaviors based solely on spacing effects. Traction-slip behavior of the experimental interface appears to be considerably affected by spatial clustering of asperities that was not present in the randomly spaced, synthetic asperity distributions. Estimates of bulk interfacial shear stiffness were determined from the constitutive traction-slip behavior and were comparable to the theoretical estimates of multi-contact interfaces with non-interacting asperities.

Describing and Modeling Workflow and Information Flow in Chronic Disease Care

PubMed Central

Unertl, Kim M.; Weinger, Matthew B.; Johnson, Kevin B.; Lorenzi, Nancy M.

2009-01-01

Objectives The goal of the study was to develop an in-depth understanding of work practices, workflow, and information flow in chronic disease care, to facilitate development of context-appropriate informatics tools. Design The study was conducted over a 10-month period in three ambulatory clinics providing chronic disease care. The authors iteratively collected data using direct observation and semi-structured interviews. Measurements The authors observed all aspects of care in three different chronic disease clinics for over 150 hours, including 157 patient-provider interactions. Observation focused on interactions among people, processes, and technology. Observation data were analyzed through an open coding approach. The authors then developed models of workflow and information flow using Hierarchical Task Analysis and Soft Systems Methodology. The authors also conducted nine semi-structured interviews to confirm and refine the models. Results The study had three primary outcomes: models of workflow for each clinic, models of information flow for each clinic, and an in-depth description of work practices and the role of health information technology (HIT) in the clinics. The authors identified gaps between the existing HIT functionality and the needs of chronic disease providers. Conclusions In response to the analysis of workflow and information flow, the authors developed ten guidelines for design of HIT to support chronic disease care, including recommendations to pursue modular approaches to design that would support disease-specific needs. The study demonstrates the importance of evaluating workflow and information flow in HIT design and implementation. PMID:19717802

Personality Correlates of Midlife Cardiometabolic Risk: The Explanatory Role of Higher-Order Factors of the Five Factor Model

PubMed Central

Dermody, Sarah S.; Wright, Aidan G.C.; Cheong, JeeWon; Miller, Karissa G.; Muldoon, Matthew F.; Flory, Janine D.; Gianaros, Peter J.; Marsland, Anna L.; Manuck, Stephen B.

2015-01-01

Objective Varying associations are reported between Five Factor Model (FFM) personality traits and cardiovascular diseaabolic risk within a hierarchical model of personality that posits higherse risk. Here, we further examine dispositional correlates of cardiomet -order traits of Stability (shared variance of Agreeableness, Conscientiousness, inverse Neuroticism) and Plasticity (Extraversion, Openness), and test hypothesized mediation via biological and behavioral factors. Method In an observational study of 856 community volunteers aged 30–54 years (46% male, 86% Caucasian), latent variable FFM traits (using multiple-informant reports) and aggregated cardiometabolic risk (indicators: insulin resistance, dyslipidemia, blood pressure, adiposity) were estimated using confirmatory factor analysis (CFA). The cardiometabolic factor was regressed on each personality factor or higher-order trait. Cross-sectional indirect effects via systemic inflammation, cardiac autonomic control, and physical activity were tested. Results CFA models confirmed the Stability “meta-trait,” but not Plasticity. Lower Stability was associated with heightened cardiometabolic risk. This association was accounted for by inflammation, autonomic function, and physical activity. Among FFM traits, only Openness was associated with risk over and above Stability and, unlike Stablity, this relationship was unexplained by the intervening variables. Conclusions A Stability meta-trait covaries with midlife cardiometabolic risk, and this association is accounted for by three candidate biological and behavioral factors. PMID:26249259

Clinical application of the five-factor model.

PubMed

Widiger, Thomas A; Presnall, Jennifer Ruth

2013-12-01

The Five-Factor Model (FFM) has become the predominant dimensional model of general personality structure. The purpose of this paper is to suggest a clinical application. A substantial body of research indicates that the personality disorders included within the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders (DSM) can be understood as extreme and/or maladaptive variants of the FFM (the acronym "DSM" refers to any particular edition of the APA DSM). In addition, the current proposal for the forthcoming fifth edition of the DSM (i.e., DSM-5) is shifting closely toward an FFM dimensional trait model of personality disorder. Advantages of this shifting conceptualization are discussed, including treatment planning. © 2012 Wiley Periodicals, Inc.

A three-pathway pore model describes extensive transport data from Mammalian microvascular beds and frog microvessels.

PubMed

Wolf, Matthew B

2002-12-01

To show that a three-pathway pore model can describe extensive transport data in cat and rat skeletal muscle microvascular beds and in frog mesenteric microvessels. A three-pathway pore model was used to predict transport data measured in various microcirculatory preparations. The pathways consist of 4- and 24-nm radii pore systems with a 2.5:1 ratio of hydraulic conductivities and a water-only pathway of variable conductivity. The pore sizes and relative hydraulic conductivities of the small- and large-pore systems were derived from a model fit to reflection coefficient (sigma) data in the cat hindlimb. The fraction (alpha(w)) of total hydraulic conductivity (L(p)) or hydraulic capacity (L(p)S) contributed by the water-only pathway was uniquely determined for each preparation by a fit of the three-pathway model (parameters fixed as above) to sigma data measured in that preparation. These parameter values were unchanged when the model was used to predict diffusion capacity (permeability-surface area product, P(d)S) data in the cat or rat preparations or diffusional permeability (P(d)) data in frog microvessels. The values for L(p) or L(p)S used to predict diffusional data in each preparation were taken from the literature. Predictions of P(d) ratios for solute pairs were also compared with experimental data. The three-pathway model closely predicted the trend of P(d)S or P(d) experimental data in all three preparations; in general, predicted P(d) ratios for paired solutes were quite similar to experimental data. For these comparisons, the only parameter varied between these preparations was alpha(w). It varied considerably, from 7 to 16 to 41% of total in frog, rat, and cat preparations. Individual P(d)S or P(d) experimental data were closely predicted in the cat but somewhat overestimated in the frog and rat. This result could be due the use of L(p) or L(p)S values in the model that were affected by methodological problems. Calculated hydraulic conductivities of

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Positive Matrix Factorization Model for environmental data analyses

EPA Pesticide Factsheets

Positive Matrix Factorization is a receptor model developed by EPA to provide scientific support for current ambient air quality standards and implement those standards by identifying and quantifying the relative contributions of air pollution sources.

Photon migration through a turbid slab described by a model based on diffusion approximation. II. Comparison with Monte Carlo results.

PubMed

Martelli, F; Contini, D; Taddeucci, A; Zaccanti, G

1997-07-01

In our companion paper we presented a model to describe photon migration through a diffusing slab. The model, developed for a homogeneous slab, is based on the diffusion approximation and is able to take into account reflection at the boundaries resulting from the refractive index mismatch. In this paper the predictions of the model are compared with solutions of the radiative transfer equation obtained by Monte Carlo simulations in order to determine the applicability limits of the approximated theory in different physical conditions. A fitting procedure, carried out with the optical properties as fitting parameters, is used to check the application of the model to the inverse problem. The results show that significant errors can be made if the effect of the refractive index mismatch is not properly taken into account. Errors are more important when measurements of transmittance are used. The effects of using a receiver with a limited angular field of view and the angular distribution of the radiation that emerges from the slab have also been investigated.

Secondary Science Teachers Making Sense of Model-Based Classroom Instruction: Understanding the Learning and Learning Pathways Teachers Describe as Supporting Changes in Teaching Practice

NASA Astrophysics Data System (ADS)

Hvidsten, Connie J.

Connie J. Hvidsten September 2016 Education Secondary Science Teachers Making Sense of Model-Based Classroom Instruction: Understanding the Learning and Learning Pathways Teachers Describe as Supporting Changes in Teaching Practice This dissertation consists of three papers analyzing writings and interviews of experienced secondary science teachers during and after a two-year professional development (PD) program focused on model-based reasoning (MBR). MBR is an approach to science instruction that provides opportunities for students to use conceptual models to make sense of natural phenomena in ways that are similar to the use of models within the scientific community. The aim of this research is to better understand the learning and learning pathways teachers identified as valuable in supporting changes in their teaching practice. To accomplish this aim, the papers analyze the ways teachers 1) ascribe their learning to various aspects of the program, 2) describe what they learned, and 3) reflect on the impact the PD had on their teaching practice. Twenty-one secondary science teachers completed the Innovations in Science Instruction through Modeling (ISIM) program from 2007 through 2009. Commonalities in the written reflections and interview responses led to a set of generalizable findings related to the impacts and outcomes of the PD. The first of the three papers describes elements of the ISIM program that teachers associated with their own learning. One of the most frequently mentioned PD feature was being in the position of an adult learner. Embedding learning in instructional practice by collaboratively developing and revising lessons, and observing the lessons in one-another's classrooms provided a sense of professional community, accountability, and support teachers reported were necessary to overcome the challenges of implementing new pedagogical practices. Additionally, teachers described that opportunities to reflect on their learning and connect their

Collective philanthropy: describing and modeling the ecology of giving.

PubMed

Gottesman, William L; Reagan, Andrew James; Dodds, Peter Sheridan

2014-01-01

Reflective of income and wealth distributions, philanthropic gifting appears to follow an approximate power-law size distribution as measured by the size of gifts received by individual institutions. We explore the ecology of gifting by analysing data sets of individual gifts for a diverse group of institutions dedicated to education, medicine, art, public support, and religion. We find that the detailed forms of gift-size distributions differ across but are relatively constant within charity categories. We construct a model for how a donor's income affects their giving preferences in different charity categories, offering a mechanistic explanation for variations in institutional gift-size distributions. We discuss how knowledge of gift-sized distributions may be used to assess an institution's gift-giving profile, to help set fundraising goals, and to design an institution-specific giving pyramid.

An Illumination Modeling System for Human Factors Analyses

NASA Technical Reports Server (NTRS)

Huynh, Thong; Maida, James C.; Bond, Robert L. (Technical Monitor)

2002-01-01

Seeing is critical to human performance. Lighting is critical for seeing. Therefore, lighting is critical to human performance. This is common sense, and here on earth, it is easily taken for granted. However, on orbit, because the sun will rise or set every 45 minutes on average, humans working in space must cope with extremely dynamic lighting conditions. Contrast conditions of harsh shadowing and glare is also severe. The prediction of lighting conditions for critical operations is essential. Crew training can factor lighting into the lesson plans when necessary. Mission planners can determine whether low-light video cameras are required or whether additional luminaires need to be flown. The optimization of the quantity and quality of light is needed because of the effects on crew safety, on electrical power and on equipment maintainability. To address all of these issues, an illumination modeling system has been developed by the Graphics Research and Analyses Facility (GRAF) and Lighting Environment Test Facility (LETF) in the Space Human Factors Laboratory at NASA Johnson Space Center. The system uses physically based ray tracing software (Radiance) developed at Lawrence Berkeley Laboratories, a human factors oriented geometric modeling system (PLAID) and an extensive database of humans and environments. Material reflectivity properties of major surfaces and critical surfaces are measured using a gonio-reflectometer. Luminaires (lights) are measured for beam spread distribution, color and intensity. Video camera performances are measured for color and light sensitivity. 3D geometric models of humans and the environment are combined with the material and light models to form a system capable of predicting lighting conditions and visibility conditions in space.

Space station crew safety: Human factors interaction model

NASA Technical Reports Server (NTRS)

Cohen, M. M.; Junge, M. K.

1985-01-01

A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this space station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.

[Reevaluation of the time course of the effect of propofol described with the Schnider pharmacokinetic model].

PubMed

Sepúlveda, P O; Mora, X

2012-12-01

.34), the BIS at LOC was 77.48 (SD±9.6) and 74.65(SD±6.3) at ROC (P=.027). The calculated Ce in the original model at LOC and ROC were 5.9 (SD±1.35)/1.08 μg/ml (SD±0.32) (P<.001), respectively, and 2.3 (SD±0.63)/2.0 μg/ml (SD±0.65) (NS) for the new model. The values between LOC/ROC were significantly different between the 2 models (P<.001). No differences in k(e0) value were found between males and females, but in the new model the k(e0) was affected by age as a covariable (0.26-[age×0.0022]) (P<.05). The dynamic relationship between propofol plasma concentrations predicted by Schnider's pharmacokinetic model and its hypnotic effect measured with BIS was better characterized with a smaller k(e0) value (slower t½k(e0)) than that present in the original model, with an age effect also not described before. Copyright © 2011 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Published by Elsevier España. All rights reserved.

A dynamic factor model of the evaluation of the financial crisis in Turkey.

PubMed

Sezgin, F; Kinay, B

2010-01-01

Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

Rigorous derivation of the effective model describing a non-isothermal fluid flow in a vertical pipe filled with porous medium

NASA Astrophysics Data System (ADS)

Beneš, Michal; Pažanin, Igor

2018-03-01

This paper reports an analytical investigation of non-isothermal fluid flow in a thin (or long) vertical pipe filled with porous medium via asymptotic analysis. We assume that the fluid inside the pipe is cooled (or heated) by the surrounding medium and that the flow is governed by the prescribed pressure drop between pipe's ends. Starting from the dimensionless Darcy-Brinkman-Boussinesq system, we formally derive a macroscopic model describing the effective flow at small Brinkman-Darcy number. The asymptotic approximation is given by the explicit formulae for the velocity, pressure and temperature clearly acknowledging the effects of the cooling (heating) and porous structure. The theoretical error analysis is carried out to indicate the order of accuracy and to provide a rigorous justification of the effective model.

[Psychosocial factors at work and cardiovascular diseases: contribution of the Effort-Reward Imbalance model].

PubMed

Niedhammer, I; Siegrist, J

1998-11-01

The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

PubMed

van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

2018-06-01

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

Collective Philanthropy: Describing and Modeling the Ecology of Giving

PubMed Central

Gottesman, William L.; Reagan, Andrew James; Dodds, Peter Sheridan

2014-01-01

Reflective of income and wealth distributions, philanthropic gifting appears to follow an approximate power-law size distribution as measured by the size of gifts received by individual institutions. We explore the ecology of gifting by analysing data sets of individual gifts for a diverse group of institutions dedicated to education, medicine, art, public support, and religion. We find that the detailed forms of gift-size distributions differ across but are relatively constant within charity categories. We construct a model for how a donor's income affects their giving preferences in different charity categories, offering a mechanistic explanation for variations in institutional gift-size distributions. We discuss how knowledge of gift-sized distributions may be used to assess an institution's gift-giving profile, to help set fundraising goals, and to design an institution-specific giving pyramid. PMID:24983864

Describing Temperature-Dependent Self-Diffusion Coefficients and Fluidity of 1- and 3-Alcohols with the Compensated Arrhenius Formalism.

PubMed

Fleshman, Allison M; Forsythe, Grant E; Petrowsky, Matt; Frech, Roger

2016-09-22

The location of the hydroxyl group in monohydroxy alcohols greatly affects the temperature dependence of the liquid structure due to hydrogen bonding. Temperature-dependent self-diffusion coefficients, fluidity (the inverse of viscosity), dielectric constant, and density have been measured for several 1-alcohols and 3-alcohols with varying alkyl chain lengths. The data are modeled using the compensated Arrhenius formalism (CAF). The CAF follows a modified transition state theory using an Arrhenius-like expression to describe the transport property, which consists of a Boltzmann factor containing an energy of activation, Ea, and an exponential prefactor containing the temperature-dependent solution dielectric constant, εs(T). Both 1- and 3-alcohols show the Ea of diffusion coefficients (approximately 43 kJ mol(-1)) is higher than the Ea of fluidity (approximately 35 kJ mol(-1)). The temperature dependence of the exponential prefactor in these associated liquids is explained using the dielectric constant and the Kirkwood-Frölich correlation factor, gk. It is argued that the dielectric constant must be used to account for the additional temperature dependence due to variations in the liquid structure (e.g., hydrogen bonding) for the CAF to accurately model the transport property.

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

PubMed

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

THE 1985 NAPAP EMISSIONS INVENTORY: DEVELOPMENT OF SPECIES ALLOCATION FACTORS

EPA Science Inventory

The report describes the methodologies and data bases used to develop species allocation factors and data processing software used to develop the 1985 National Acid Precipitation Assessment Program (NAPAP) Modelers' Emissions Inventory (Version 2). Species allocation factors were...

A one-dimensional model to describe flow localization in viscoplastic slender bars subjected to super critical impact velocities

NASA Astrophysics Data System (ADS)

Vaz-Romero, A.; Rodríguez-Martínez, J. A.

2018-01-01

In this paper we investigate flow localization in viscoplastic slender bars subjected to dynamic tension. We explore loading rates above the critical impact velocity: the wave initiated in the impacted end by the applied velocity is the trigger for the localization of plastic deformation. The problem has been addressed using two kinds of numerical simulations: (1) one-dimensional finite difference calculations and (2) axisymmetric finite element computations. The latter calculations have been used to validate the capacity of the finite difference model to describe plastic flow localization at high impact velocities. The finite difference model, which highlights due to its simplicity, allows to obtain insights into the role played by the strain rate and temperature sensitivities of the material in the process of dynamic flow localization. Specifically, we have shown that viscosity can stabilize the material behavior to the point of preventing the appearance of the critical impact velocity. This is a key outcome of our investigation, which, to the best of the authors' knowledge, has not been previously reported in the literature.

Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

ERIC Educational Resources Information Center

Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

2012-01-01

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

HealthPartners adopts community business model to deepen focus on nonclinical factors of health outcomes.

PubMed

Isham, George J; Zimmerman, Donna J; Kindig, David A; Hornseth, Gary W

2013-08-01

Clinical care contributes only 20 percent to overall health outcomes, according to a population health model developed at the University of Wisconsin. Factors contributing to the remainder include lifestyle behaviors, the physical environment, and social and economic forces--all generally considered outside the realm of care. In 2010 Minnesota-based HealthPartners decided to target nonclinical community health factors as a formal part of its strategic business plan to improve public health in the Twin Cities area. The strategy included creating partnerships with businesses and institutions that are generally unaccustomed to working together or considering how their actions could help improve community health. This article describes efforts to promote healthy eating in schools, reduce the stigma of mental illness, improve end-of-life decision making, and strengthen an inner-city neighborhood. Although still in their early stages, the partnerships can serve as encouragement for organizations inside and outside health care that are considering undertaking similar efforts in their markets.

Describing temperament in an ungulate: a multidimensional approach.

PubMed

Graunke, Katharina L; Nürnberg, Gerd; Repsilber, Dirk; Puppe, Birger; Langbein, Jan

2013-01-01

Studies on animal temperament have often described temperament using a one-dimensional scale, whereas theoretical framework has recently suggested two or more dimensions using terms like "valence" or "arousal" to describe these dimensions. Yet, the valence or assessment of a situation is highly individual. The aim of this study was to provide support for the multidimensional framework with experimental data originating from an economically important species (Bos taurus). We tested 361 calves at 90 days post natum (dpn) in a novel-object test. Using a principal component analysis (PCA), we condensed numerous behaviours into fewer variables to describe temperament and correlated these variables with simultaneously measured heart rate variability (HRV) data. The PCA resulted in two behavioural dimensions (principal components, PC): novel-object-related (PC 1) and exploration-activity-related (PC 2). These PCs explained 58% of the variability in our data. The animals were distributed evenly within the two behavioural dimensions independent of their sex. Calves with different scores in these PCs differed significantly in HRV, and thus in the autonomous nervous system's activity. Based on these combined behavioural and physiological data we described four distinct temperament types resulting from two behavioural dimensions: "neophobic/fearful--alert", "interested--stressed", "subdued/uninterested--calm", and "neoophilic/outgoing--alert". Additionally, 38 calves were tested at 90 and 197 dpn. Using the same PCA-model, they correlated significantly in PC 1 and tended to correlate in PC 2 between the two test ages. Of these calves, 42% expressed a similar behaviour pattern in both dimensions and 47% in one. No differences in temperament scores were found between sexes or breeds. In conclusion, we described distinct temperament types in calves based on behavioural and physiological measures emphasising the benefits of a multidimensional approach.

Probabilistic simulation of the human factor in structural reliability

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Chamis, Christos C.

1991-01-01

Many structural failures have occasionally been attributed to human factors in engineering design, analyses maintenance, and fabrication processes. Every facet of the engineering process is heavily governed by human factors and the degree of uncertainty associated with them. Factors such as societal, physical, professional, psychological, and many others introduce uncertainties that significantly influence the reliability of human performance. Quantifying human factors and associated uncertainties in structural reliability require: (1) identification of the fundamental factors that influence human performance, and (2) models to describe the interaction of these factors. An approach is being developed to quantify the uncertainties associated with the human performance. This approach consists of a multi factor model in conjunction with direct Monte-Carlo simulation.

Predictive model to describe water migration in cellular solid foods during storage.

PubMed

Voogt, Juliën A; Hirte, Anita; Meinders, Marcel B J

2011-11-01

Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Water migration in cellular solid foods involves migration through both the air cells and the solid matrix. For systems in which the water migration distance is large compared with the cell wall thickness of the solid matrix, the overall water flux through the system is dominated by the flux through the air. For these systems, water migration can be approximated well by a Fickian diffusion model. The effective diffusion coefficient can be expressed in terms of the material properties of the solid matrix (i.e. the density, sorption isotherm and diffusion coefficient of water in the solid matrix) and the morphological properties of the cellular structure (i.e. water vapour permeability and volume fraction of the solid matrix). The water vapour permeability is estimated from finite element method modelling using a simplified model for the cellular structure. It is shown that experimentally observed dynamical water profiles of bread rolls that differ in crust permeability are predicted well by the Fickian diffusion model. Copyright © 2011 Society of Chemical Industry.

Probabilistic Usage of the Multi-Factor Interaction Model

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A Multi-Factor Interaction Model (MFIM) is used to predict the insulating foam mass expulsion during the ascending of a space vehicle. The exponents in the MFIM are evaluated by an available approach which consists of least squares and an optimization algorithm. These results were subsequently used to probabilistically evaluate the effects of the uncertainties in each participating factor in the mass expulsion. The probabilistic results show that the surface temperature dominates at high probabilities and the pressure which causes the mass expulsion at low probabil

The Kroll-Lee-Zumino Model and Pion Form Factors

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

Dominguez, C. A.; Loewe, M.

2010-08-04

At the one loop level, we make use of the renormalizable Abelian quantum field theory model of Kroll, Lee, and Zumino (KLZ) in order to compute the vertex corrections to the tree-level, Vector Meson Dominance (VMD) electromagnetic pion form factor. This result, together with the one-loop vacuum polarization contribution, implies an electromagnetic pion form factor which is in outstanding agreement with data in the whole range of accessible momentum transfers in the space-like region. The time-like form factor, which reproduces the Gounaris-Sakurai formula at and near the rho-meson peak, remains unaffected by the vertex correction at order O(g{sup 2}). Wemore » also use the KLZ model to compute the pion scalar radius at the one loop level, finding S = 0.40 fm{sup 2}. From this value we find for the low energy constant of chiral perturbation theory l{sub 4} = 3.4.« less

Correlation of causal factors that influence construction safety performance: A model.

PubMed

Rodrigues, F; Coutinho, A; Cardoso, C

2015-01-01

The construction sector has presented positive development regarding the decrease in occupational accident rates in recent years. Regardless, the construction sector stands out systematically from other industries due to its high number of fatalities. The aim of this paper is to deeply understand the causality of construction accidents from the early design phase through a model. This study reviewed several research papers presenting various analytical models that correlate the contributing factors to occupational accidents in this sector. This study also analysed different construction projects and conducted a survey of design and site supervision teams. This paper proposes a model developed from the analysis of existing ones, which correlates the causal factors through all the construction phases. It was concluded that effective risk prevention can only be achieved by a global correlation of causal factors including not only production ones but also client requirements, financial climate, design team competence, project and risk management, financial capacity, health and safety policy and early planning. Accordingly, a model is proposed.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Two Empirical Models for Land-falling Hurricane Gust Factors

NASA Technical Reports Server (NTRS)

Merceret, Franics J.

2008-01-01

Gaussian and lognormal models for gust factors as a function of height and mean windspeed in land-falling hurricanes are presented. The models were empirically derived using data from 2004 hurricanes Frances and Jeanne and independently verified using data from 2005 hurricane Wilma. The data were collected from three wind towers at Kennedy Space Center and Cape Canaveral Air Force Station with instrumentation at multiple levels from 12 to 500 feet above ground level. An additional 200-foot tower was available for the verification. Mean wind speeds from 15 to 60 knots were included in the data. The models provide formulas for the mean and standard deviation of the gust factor given the mean windspeed and height above ground. These statistics may then be used to assess the probability of exceeding a specified peak wind threshold of operational significance given a specified mean wind speed.

Multi-factor energy price models and exotic derivatives pricing

NASA Astrophysics Data System (ADS)

Hikspoors, Samuel

The high pace at which many of the world's energy markets have gradually been opened to competition have generated a significant amount of new financial activity. Both academicians and practitioners alike recently started to develop the tools of energy derivatives pricing/hedging as a quantitative topic of its own. The energy contract structures as well as their underlying asset properties set the energy risk management industry apart from its more standard equity and fixed income counterparts. This thesis naturally contributes to these broad market developments in participating to the advances of the mathematical tools aiming at a better theory of energy contingent claim pricing/hedging. We propose many realistic two-factor and three-factor models for spot and forward price processes that generalize some well known and standard modeling assumptions. We develop the associated pricing methodologies and propose stable calibration algorithms that motivate the application of the relevant modeling schemes.

NASA: Model development for human factors interfacing

NASA Technical Reports Server (NTRS)

Smith, L. L.

1984-01-01

The results of an intensive literature review in the general topics of human error analysis, stress and job performance, and accident and safety analysis revealed no usable techniques or approaches for analyzing human error in ground or space operations tasks. A task review model is described and proposed to be developed in order to reduce the degree of labor intensiveness in ground and space operations tasks. An extensive number of annotated references are provided.

On the existence of a stationary measure for the stochastic system of the Lorenz model describing a baroclinic atmosphere

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

Klevtsova, Yu Yu

2013-09-30

The paper is concerned with a nonlinear system of partial differential equations with parameters. This system describes the two-layer quasi-solenoidal Lorenz model for a baroclinic atmosphere on a rotating two-dimensional sphere. The right-hand side of the system is perturbed by white noise. Sufficient conditions on the parameters and the right-hand side are obtained for the existence of a stationary measure. Bibliography: 25 titles.

Transcription factors in pancreatic development. Animal models.

PubMed

Martin, Merce; Hauer, Viviane; Messmer, Mélanie; Orvain, Christophe; Gradwohl, Gérard

2007-01-01

Through the analysis of genetically modified mice a hierarchy of transcription factors regulating pancreas specification, endocrine destiny as well as endocrine subtype specification and differentiation has been established. In addition to conventional approaches such as transgenic technologies and gene targeting, recombinase fate mapping in mice has been key in establishing the lineage relationship between progenitor cells and their progeny in understanding pancreas formation. Moreover, the design of specific mouse models to conditionally express transcription factors in different populations of progenitor cells has revealed to what extent transcription factors required for islet cell development are also sufficient to induce endocrine differentiation and the importance of the competence of progenitor cells to respond to the genetic program implemented by these factors. Taking advantage of this basic science knowledge acquired in rodents, immature insulin-producing cells have recently been differentiated in vitro from human embryonic stem cells. Taken together these major advances emphasize the need to gain further in-depth knowledge of the molecular and cellular mechanisms controlling beta-cell differentiation in mice to generate functional beta-cells in the future that could be used for cell therapy in diabetes.

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

NASA Astrophysics Data System (ADS)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Describing the Labor Sectors in Jordan--The Factors That Attract Employees from Graduated Students' Perspectives

ERIC Educational Resources Information Center

AL-Zou'bi, Dalal Mohamad

2014-01-01

This study aimed at exploring perceptions of Jordanian graduating students for the factors that attract them in the work environment based on porter's theory in motivation. A Questionnaire was distributed to a sample of 807 graduating students at three universities. Means, Frequencies, Percentage, Variance analysis and chi-square test were used to…

Alternative Factor Models and Heritability of the Short Leyton Obsessional Inventory--Children's Version

ERIC Educational Resources Information Center

Moore, Janette; Smith, Gillian W.; Shevlin, Mark; O'Neill, Francis A.

2010-01-01

An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD),…

Describing Intravenous Extravasation in Children (DIVE Study).

PubMed

Paquette, Vanessa; McGloin, Rumi; Northway, Tracie; Dezorzi, Pia; Singh, Avash; Carr, Roxane

2011-09-01

Extravasation, the inadvertent leakage of intravenous (IV) medication from the vein into the surrounding tissue, is a iatrogenic cause of patient injury. Extravasation has been reported to occur in 0.1% to 6.5% of hospital inpatients. The incidence may be higher among children because they have multiple risk factors, including small and fragile veins, decreased peripheral circulation, capillary leakage, and flexible subcutaneous tissue. To describe the incidence of extravasation at a pediatric tertiary care hospital, to identify the agents causing extravasation, and to describe the use of antidotes to manage identified cases. A secondary objective was to describe adverse drug effects associated with the antidotes administered. The medical records of pediatric patients with documented extravasation of an IV medication between January 1, 2006, and August 31, 2008, were analyzed retrospectively. The appropriateness of antidote use was determined in terms of adherence to the institution's protocol for treatment of extravasation. A total of 42 patients had documented extravasation, for an overall incidence of 0.04% per patient-day. Of the 40 cases in which location was documented, 12 (30%) occurred on the general pediatric wards, 10 (25%) on the surgical ward, 9 (22%) in the neonatal intensive care unit, 5 (12%) in the pediatric intensive care unit, 3 (8%) in day care, and 1 (2%) in the emergency department. The most common medications involved were fluids for IV administration (18 [43%]), potassium chloride (11 [26%]), antibiotics (8 [19%]), total parenteral nutrition (8 [19%]), calcium chloride (2 [5%]), and epinephrine (2 [5%]). Multiple drugs were involved in some cases of extravasation. The decision to administer an antidote and the choice of antidote (if required) were appropriate in 50% of the cases. No adverse drug effects were reported with use of antidotes. The incidence of extravasation was low. The medications most commonly involved were similar to those

Assessing risk factors for dental caries: a statistical modeling approach.

PubMed

Trottini, Mario; Bossù, Maurizio; Corridore, Denise; Ierardo, Gaetano; Luzzi, Valeria; Saccucci, Matteo; Polimeni, Antonella

2015-01-01

The problem of identifying potential determinants and predictors of dental caries is of key importance in caries research and it has received considerable attention in the scientific literature. From the methodological side, a broad range of statistical models is currently available to analyze dental caries indices (DMFT, dmfs, etc.). These models have been applied in several studies to investigate the impact of different risk factors on the cumulative severity of dental caries experience. However, in most of the cases (i) these studies focus on a very specific subset of risk factors; and (ii) in the statistical modeling only few candidate models are considered and model selection is at best only marginally addressed. As a result, our understanding of the robustness of the statistical inferences with respect to the choice of the model is very limited; the richness of the set of statistical models available for analysis in only marginally exploited; and inferences could be biased due the omission of potentially important confounding variables in the model's specification. In this paper we argue that these limitations can be overcome considering a general class of candidate models and carefully exploring the model space using standard model selection criteria and measures of global fit and predictive performance of the candidate models. Strengths and limitations of the proposed approach are illustrated with a real data set. In our illustration the model space contains more than 2.6 million models, which require inferences to be adjusted for 'optimism'.

Approach of describing dynamic production of volatile fatty acids from sludge alkaline fermentation.

PubMed

Wang, Dongbo; Liu, Yiwen; Ngo, Huu Hao; Zhang, Chang; Yang, Qi; Peng, Lai; He, Dandan; Zeng, Guangming; Li, Xiaoming; Ni, Bing-Jie

2017-08-01

In this work, a mathematical model was developed to describe the dynamics of fermentation products in sludge alkaline fermentation systems for the first time. In this model, the impacts of alkaline fermentation on sludge disintegration, hydrolysis, acidogenesis, acetogenesis, and methanogenesis processes are specifically considered for describing the high-level formation of fermentation products. The model proposed successfully reproduced the experimental data obtained from five independent sludge alkaline fermentation studies. The modeling results showed that alkaline fermentation largely facilitated the disintegration, acidogenesis, and acetogenesis processes and severely inhibited methanogenesis process. With the pH increase from 7.0 to 10.0, the disintegration, acidogenesis, and acetogenesis processes respectively increased by 53%, 1030%, and 30% while methane production decreased by 3800%. However, no substantial effect on hydrolysis process was found. The model also indicated that the pathway of acetoclastic methanogenesis was more severely inhibited by alkaline condition than that of hydrogentrophic methanogenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Saturation behavior: a general relationship described by a simple second-order differential equation.

PubMed

Kepner, Gordon R

2010-04-13

The numerous natural phenomena that exhibit saturation behavior, e.g., ligand binding and enzyme kinetics, have been approached, to date, via empirical and particular analyses. This paper presents a mechanism-free, and assumption-free, second-order differential equation, designed only to describe a typical relationship between the variables governing these phenomena. It develops a mathematical model for this relation, based solely on the analysis of the typical experimental data plot and its saturation characteristics. Its utility complements the traditional empirical approaches. For the general saturation curve, described in terms of its independent (x) and dependent (y) variables, a second-order differential equation is obtained that applies to any saturation phenomena. It shows that the driving factor for the basic saturation behavior is the probability of the interactive site being free, which is described quantitatively. Solving the equation relates the variables in terms of the two empirical constants common to all these phenomena, the initial slope of the data plot and the limiting value at saturation. A first-order differential equation for the slope emerged that led to the concept of the effective binding rate at the active site and its dependence on the calculable probability the interactive site is free. These results are illustrated using specific cases, including ligand binding and enzyme kinetics. This leads to a revised understanding of how to interpret the empirical constants, in terms of the variables pertinent to the phenomenon under study. The second-order differential equation revealed the basic underlying relations that describe these saturation phenomena, and the basic mathematical properties of the standard experimental data plot. It was shown how to integrate this differential equation, and define the common basic properties of these phenomena. The results regarding the importance of the slope and the new perspectives on the empirical

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

The Common Factors Discrimination Model: An Integrated Approach to Counselor Supervision

ERIC Educational Resources Information Center

Crunk, A. Elizabeth; Barden, Sejal M.

2017-01-01

Numerous models of clinical supervision have been developed; however, there is little empirical support indicating that any one model is superior. Therefore, common factors approaches to supervision integrate essential components that are shared among counseling and supervision models. The purpose of this paper is to present an innovative model of…

Describing Myxococcus xanthus Aggregation Using Ostwald Ripening Equations for Thin Liquid Films

PubMed Central

Bahar, Fatmagül; Pratt-Szeliga, Philip C.; Angus, Stuart; Guo, Jiaye; Welch, Roy D.

2014-01-01

When starved, a swarm of millions of Myxococcus xanthus cells coordinate their movement from outward swarming to inward coalescence. The cells then execute a synchronous program of multicellular development, arranging themselves into dome shaped aggregates. Over the course of development, about half of the initial aggregates disappear, while others persist and mature into fruiting bodies. This work seeks to develop a quantitative model for aggregation that accurately simulates which will disappear and which will persist. We analyzed time-lapse movies of M. xanthus development, modeled aggregation using the equations that describe Ostwald ripening of droplets in thin liquid films, and predicted the disappearance and persistence of aggregates with an average accuracy of 85%. We then experimentally validated a prediction that is fundamental to this model by tracking individual fluorescent cells as they moved between aggregates and demonstrating that cell movement towards and away from aggregates correlates with aggregate disappearance. Describing development through this model may limit the number and type of molecular genetic signals needed to complete M. xanthus development, and it provides numerous additional testable predictions. PMID:25231319

The Spiral-Interactive Program Evaluation Model.

ERIC Educational Resources Information Center

Khaleel, Ibrahim Adamu

1988-01-01

Describes the spiral interactive program evaluation model, which is designed to evaluate vocational-technical education programs in secondary schools in Nigeria. Program evaluation is defined; utility oriented and process oriented models for evaluation are described; and internal and external evaluative factors and variables that define each…

Confirmatory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Kende, D; Rener-Sitar, K; Reissmann, D R

2014-09-01

Previous exploratory analyses suggest that the Oral Health Impact Profile (OHIP) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher-order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health-Related Quality of Life (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample (n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four-factor model and a bifactor model that included one general factor and four group factors. Using model-fit criteria and factor interpretability as guides, the four-factor model was deemed best in terms of strong item loadings, model fit (RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors - which we have named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact - can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four-factor solution suggest that OHRQoL can also be sufficiently described with one score. © 2014 John Wiley & Sons Ltd.

Application of variational principles and adjoint integrating factors for constructing numerical GFD models

NASA Astrophysics Data System (ADS)

Penenko, Vladimir; Tsvetova, Elena; Penenko, Alexey

2015-04-01

direction on a time step. In each direction, they have tridiagonal structure. They are solved by the sweep method. An important advantage of the discrete-analytical schemes is that the values of derivatives at the boundaries of finite volume are calculated together with the values of the unknown functions. This technique is particularly attractive for problems with dominant convection, as it does not require artificial monotonization and limiters. The same idea of integrating factors is applied in temporal dimension to the stiff systems of equations describing chemical transformation models [2]. The proposed method is applicable for the problems involving convection-diffusion-reaction operators. The work has been partially supported by the Presidium of RAS under Program 43, and by the RFBR grants 14-01-00125 and 14-01-31482. References: 1. V.V. Penenko, E.A. Tsvetova, A.V. Penenko. Variational approach and Euler's integrating factors for environmental studies// Computers and Mathematics with Applications, (2014) V.67, Issue 12, P. 2240-2256. 2. V.V.Penenko, E.A.Tsvetova. Variational methods of constructing monotone approximations for atmospheric chemistry models // Numerical analysis and applications, 2013, V. 6, Issue 3, pp 210-220.

Digital controller design: Continuous and discrete describing function analysis of the IPS system

NASA Technical Reports Server (NTRS)

1977-01-01

The dynamic equations and the mathematical model of the continuous-data IPS control system are developed. The IPS model considered included one flexible body mode and was hardmounted to the Orbiter/Pallet. The model contains equations describing a torque feed-forward loop (using accelerometers as inputs) which will aid in reducing the pointing errors caused by Orbiter disturbances.

On the Performance Characteristics of Latent-Factor and Knowledge Tracing Models

ERIC Educational Resources Information Center

Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus

2015-01-01

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

Qualitative models of seat discomfort including static and dynamic factors.

PubMed

Ebe, K; Griffin, M J

2000-06-01

Judgements of overall seating comfort in dynamic conditions sometimes correlate better with the static characteristics of a seat than with measures of the dynamic environment. This study developed qualitative models of overall seat discomfort to include both static and dynamic seat characteristics. A dynamic factor that reflected how vibration discomfort increased as vibration magnitude increased was combined with a static seat factor which reflected seating comfort without vibration. The ability of the model to predict the relative and overall importance of dynamic and static seat characteristics on comfort was tested in two experiments. A paired comparison experiment, using four polyurethane foam cushions (50, 70, 100, 120 mm thick), provided different static and dynamic comfort when 12 subjects were exposed to one-third octave band random vertical vibration with centre frequencies of 2.5 and 5.5 Hz, at magnitudes of 0.00, 0.25 and 0.50 m x s(-2) rms measured beneath the foam samples. Subject judgements of the relative discomfort of the different conditions depended on both static and dynamic characteristics in a manner consistent with the model. The effect of static and dynamic seat factors on overall seat discomfort was investigated by magnitude estimation using three foam cushions (of different hardness) and a rigid wooden seat at six vibration magnitudes with 20 subjects. Static seat factors (i.e. cushion stiffness) affected the manner in which vibration influenced the overall discomfort: cushions with lower stiffness were more comfortable and more sensitive to changes in vibration magnitude than those with higher stiffness. The experiments confirm that judgements of overall seat discomfort can be affected by both the static and dynamic characteristics of a seat, with the effect depending on vibration magnitude: when vibration magnitude was low, discomfort was dominated by static seat factors; as the vibration magnitude increased, discomfort became dominated

Adolescent Personality: A Five-Factor Model Construct Validation

ERIC Educational Resources Information Center

Baker, Spencer T.; Victor, James B.; Chambers, Anthony L.; Halverson, Jr., Charles F.

2004-01-01

The purpose of this study was to investigate convergent and discriminant validity of the five-factor model of adolescent personality in a school setting using three different raters (methods): self-ratings, peer ratings, and teacher ratings. The authors investigated validity through a multitrait-multimethod matrix and a confirmatory factor…

Systematically describing gross lesions in corals

USGS Publications Warehouse

Work, Thierry M.; Aeby, Greta S.

2006-01-01

Many coral diseases are characterized based on gross descriptions and, given the lack or difficulty of applying existing laboratory tools to understanding causes of coral diseases, most new diseases will continued to be described based on appearance in the field. Unfortunately, many existing descriptions of coral disease are ambiguous or open to subjective interpretation, making comparisons between oceans problematic. One reason for this is that the process of describing lesions is often confused with that of assigning causality for the lesion. However, causality is usually something not obtained in the field and requires additional laboratory tests. Because a concise and objective morphologic description provides the foundation for a case definition of any disease, there is a need for a consistent and standardized process to describe lesions of corals that focuses on morphology. We provide a framework to systematically describe and name diseases in corals involving 4 steps: (1) naming the disease, (2) describing the lesion, (3) formulating a morphologic diagnosis and (4) formulating an etiologic diagnosis. This process focuses field investigators on describing what they see and separates the process of describing a lesion from that of inferring causality, the latter being more appropriately done using laboratory techniques.

Technosocial Modeling of IED Threat Scenarios and Attacks

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

Whitney, Paul D.; Brothers, Alan J.; Coles, Garill A.

2009-03-23

This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiationmore » of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.« less

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

Five-Factor Model of Personality and Career Exploration

ERIC Educational Resources Information Center

Reed, Mary Beth; Bruch, Monroe A.; Haase, Richard F.

2004-01-01

This study investigates whether the dimensions of the five-factor model (FFM) of personality are related to specific career exploration variables. Based on the FFM, predictions were made about the relevance of particular traits to career exploration variables. Results from a canonical correlation analysis showed that variable loadings on three…

Transport in semiconductor nanowire superlattices described by coupled quantum mechanical and kinetic models.

PubMed

Alvaro, M; Bonilla, L L; Carretero, M; Melnik, R V N; Prabhakar, S

2013-08-21

In this paper we develop a kinetic model for the analysis of semiconductor superlattices, accounting for quantum effects. The model consists of a Boltzmann-Poisson type system of equations with simplified Bhatnagar-Gross-Krook collisions, obtained from the general time-dependent Schrödinger-Poisson model using Wigner functions. This system for superlattice transport is supplemented by the quantum mechanical part of the model based on the Ben-Daniel-Duke form of the Schrödinger equation for a cylindrical superlattice of finite radius. The resulting energy spectrum is used to characterize the Fermi-Dirac distribution that appears in the Bhatnagar-Gross-Krook collision, thereby coupling the quantum mechanical and kinetic parts of the model. The kinetic model uses the dispersion relation obtained by the generalized Kronig-Penney method, and allows us to estimate radii of quantum wire superlattices that have the same miniband widths as in experiments. It also allows us to determine more accurately the time-dependent characteristics of superlattices, in particular their current density. Results, for several experimentally grown superlattices, are discussed in the context of self-sustained coherent oscillations of the current density which are important in an increasing range of current and potential applications.

A UML-based ontology for describing hospital information system architectures.

PubMed

Winter, A; Brigl, B; Wendt, T

2001-01-01

To control the heterogeneity inherent to hospital information systems the information management needs appropriate hospital information systems modeling methods or techniques. This paper shows that, for several reasons, available modeling approaches are not able to answer relevant questions of information management. To overcome this major deficiency we offer an UML-based ontology for describing hospital information systems architectures. This ontology views at three layers: the domain layer, the logical tool layer, and the physical tool layer, and defines the relevant components. The relations between these components, especially between components of different layers make the answering of our information management questions possible.

Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

USGS Publications Warehouse

Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.

2011-01-01

Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American

Describing the strongly interacting quark-gluon plasma through the Friedberg-Lee model

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

Shu Song; Li Jiarong; Institute of Particle Physics, Hua-Zhong Normal University, Wuhan 430079

2010-10-15

The Friedberg-Lee (FL) model is studied at finite temperature and density. The soliton solutions of the FL model in the deconfinement phase transition are solved and thoroughly discussed for certain boundary conditions. We indicate that the solitons before and after the deconfinement have different physical meanings: the soliton before deconfinement represents hadrons, while the soliton after the deconfinement represents the bound state of quarks which leads to a strongly interacting quark-gluon plasma phase. The corresponding phase diagram is given.

Describing the Climate of Student Organizations: The Student Organization Environment Scales.

ERIC Educational Resources Information Center

Winston, Roger B., Jr.; Bledsoe, Tyrone; Goldstein, Adam R.; Wisbey, Martha E.; Street, James L.; Brown, Steven R.; Goyen, Kenneth D.; Rounds, Linda E.

1997-01-01

Using M. R. Weisbord's model of organizational diagnosis, researchers developed the Student Organization Environment Scales to measure students' perceptions of the psychosocial environment or climate of college student organizations. Development of the instrument is described and estimates of its reliability and validity are reported. Describes…

Dietary Factors Modulate Helicobacter-Associated Gastric Cancer in Rodent Models

PubMed Central

Fox, James G.; Wang, Timothy C.

2014-01-01

Since its discovery in 1982, the global importance of H. pylori-induced disease, particularly in developing countries, remains high. The use of rodent models particularly mice, and the unanticipated usefulness of the gerbil to study H. pylori pathogenesis have been used extensively to study the interactions of the host, the pathogen and the environmental conditions influencing the outcome of persistent H. pylori infection. Dietary factors in humans are increasingly recognized as being important factors in modulating progression and severity of H. pylori-induced gastric cancer. Studies using rodent models to verify and help explain mechanisms whereby various dietary ingredients impact disease outcome should continue to be extremely productive. PMID:24301796

A simple geometrical model describing shapes of soap films suspended on two rings

NASA Astrophysics Data System (ADS)

Herrmann, Felix J.; Kilvington, Charles D.; Wildenberg, Rebekah L.; Camacho, Franco E.; Walecki, Wojciech J.; Walecki, Peter S.; Walecki, Eve S.

2016-09-01

We measured and analysed the stability of two types of soap films suspended on two rings using the simple conical frusta-based model, where we use common definition of conical frustum as a portion of a cone that lies between two parallel planes cutting it. Using frusta-based we reproduced very well-known results for catenoid surfaces with and without a central disk. We present for the first time a simple conical frusta based spreadsheet model of the soap surface. This very simple, elementary, geometrical model produces results surprisingly well matching the experimental data and known exact analytical solutions. The experiment and the spreadsheet model can be used as a powerful teaching tool for pre-calculus and geometry students.

Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

PubMed Central

Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel

2014-01-01

The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903

A quasi-likelihood approach to non-negative matrix factorization

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

A unified approach to non-negative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proven using the Expectation-Maximization algorithm. In addition, a measure to evaluate the goodness-of-fit of the resulting factorization is described. The proposed methods allow modeling of non-linear effects via appropriate link functions and are illustrated using an application in biomedical signal processing. PMID:27348511

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

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

2011-01-01

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

The Manifest Association Structure of the Single-Factor Model: Insights from Partial Correlations

ERIC Educational Resources Information Center

Salgueiro, Maria de Fatima; Smith, Peter W. F.; McDonald, John W.

2008-01-01

The association structure between manifest variables arising from the single-factor model is investigated using partial correlations. The additional insights to the practitioner provided by partial correlations for detecting a single-factor model are discussed. The parameter space for the partial correlations is presented, as are the patterns of…

Numerical approach to describe complementary drying of banana slices osmotically dehydrated

NASA Astrophysics Data System (ADS)

da Silva Júnior, Aluízio Freire; da Silva, Wilton Pereira; de Farias Aires, Juarez Everton; Farias Aires, Kalina Lígia C. A.

2018-02-01

In this work, diffusion model was used to describe the water loss in the complementary drying process of cylindrical slices of banana pretreated by osmotic dehydration. A numerical solution has been proposed for the diffusion equation in cylindrical coordinates, which was obtained through the Finite Volume Method. The diffusion equation was discretized assuming that the effective water diffusivity and the dimensions of a finite cylinder may vary; also considering the boundary condition of the third kind. The banana slices were cut in length of about 1.00 cm and average radius 1.70 cm before osmotic pretreatment, and completed the pretreatment with length of about 0.74 cm and average radius 1.40 cm. The complementary drying was carried out in a kiln with circulation and air exchange. Drying temperatures were the same as used in the osmotic pretreatment (40 to 70 °C). The proposed model described well the water loss, with good statistical indicators for all fits.

Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.

Modeling the factors affecting unsafe behavior in the construction industry from safety supervisors' perspective.

PubMed

Khosravi, Yahya; Asilian-Mahabadi, Hassan; Hajizadeh, Ebrahim; Hassanzadeh-Rangi, Narmin; Bastani, Hamid; Khavanin, Ali; Mortazavi, Seyed Bagher

2014-01-01

There can be little doubt that the construction is the most hazardous industry in the worldwide. This study was designed to modeling the factors affecting unsafe behavior from the perspective of safety supervisors. The qualitative research was conducted to extract a conceptual model. A structural model was then developed based on a questionnaire survey (n=266) by two stage Structural Equation Model (SEM) approach. An excellent confirmed 12-factors structure explained about 62% of variances unsafe behavior in the construction industry. A good fit structural model indicated that safety climate factors were positively correlated with safety individual factors (P<0.001) and workplace safety condition (P<0.001). The workplace safety condition was found to play a strong mediating role in linking the safety climate and construction workers' engagement in safe or unsafe behavior. In order to improve construction safety performance, more focus on the workplace condition is required.